bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing data rate and power in BLE network for health care
Authors: Jayanthy S , Gouthamm G 
Published: July 2021

Abstract
There is a need for low power high bandwidth connected patient monitoring solution for patients in large volumes with easy deployment. The paper proposes data compression algorithms for optimizing data rate and power in Bluetooth Low energy network. The system is implemented using Bluetooth Low Energy (BLE) devices for data collection from a patient and a gateway to transfer the data to remote computer in an Internet Protocol (IP) network. The compression algorithms are optimized for the ARM microprocessor to compress the recorded values along with time stamps into a block. The sensor module is designed to be wearable continuously reads temperature and Electrocardiogram (ECG) and transmits them to a nearby gateway device. The gateway decompresses the data and uploads them to a cloud infrastructure. The system also allows for intensive monitoring of patient vitals. The collected data is processed and displayed in a moving graph in a remote web terminal. Results indicate that data rate and power has reduced by more than 45% and 3% respectively. With these results it is shown that high bandwidth monitoring solution is feasible with no extra expense in power. This system would be very beneficial to society in terms of affordable medical care as it can be used in large hospitals and remote medical camps alike where the patients can be monitored remotely.
A Photonic Based Multiband Signal Generation, Transmission and processing for 5G ROF front-haul
Authors: Kavitha C. , Manimegalai C. T. 
Published: July 2021

Abstract
This work proposes the generation of multi-band K-band, V-band, W-band of millimeter-wave (mm-wave) and its transmission performance through the standard SMF of various lengths. The optical frequency multiplication (OFM) principle is used for multi-band signal generation by the optical modulator’s non-linear characteristic. The frequency doubling, quadrupling, and six-tupling are done for multi-band generation. The generated multi-band is modulated with downlink data at the central station and transmitted through the conventional Radio over Fiber (RoF) network. The received signal is photo-electrically converted by heterodyne mixing with the local oscillator according to the user’s requirement. The transmission performance is analyzed at the receiver end for varying lengths of SMF. The simulation analysis result shows that the RoF system holds good for multi-band transmission of 30, 60, 90 GHz for about 40 km. The power penalty for 30, 60, 90 GHz signal from B-T-B to 40 km is -3.79 dB, -4.847 dB, -6.33 dB.
VLSI Tree-Based Inference Design Applications for Low-Power Learning
Authors: Nagaraju V , Suresh G , Uthayakumar C , Jijina G O 
Published: July 2021

Abstract
For the decision tree ensemble, this paper suggests a hardware architecture utilizing many feature channels. The proposed work uses the complexity of function channels for rapid identification compared to parallel processing in spatial domain scheduling to achieve conflict-free system memory. The results’ analysis demonstrates that only an FPGA implementation of the new architecture with a pedestrian sensor collated channel feature will conduct 229 thousand pulses per second at an operational value of 100 MHz while providing relatively limited resources. Checking estimation systems’ electricity-accuracy trade-offs has become central. This research evaluates the nature of data sets, investigating the outcomes of design difficulty or intensity of accuracy approximation. We improved the simulations’ precision by up to 6.7 percent by quantizing the inputs to small sizes relative to specific scenarios. The gap in model complexity was more important than source distance in terms of capacity, as we achieved reductions of up to 67 percent by reducing tree depth.
Equalization of Finite-Alphabet MMSE for All-Digital Massive MU-MIMO mm-Wave Communication
Authors: Paulchamy B , Chidambaram S , Vairaprakash S , Duraivel A N 
Published: July 2021

Abstract
For more than twenty years, growing the performance and efficiency of wireless communications systems using antenna arrays has been an active field of study. Wireless networks with multiple-input multiple-output are also part of the current norms and are implemented around the world. Access points or BSs with comparatively few antennas are used for standard MIMO systems, and the resulting increase in spectral efficiency was relatively modest. A Multiple-Input Multiple-Output platform’s capacity is researched where the transmitter outputs are processed and quantified by a set of limit quantizes through an analogue linear combining network. The linear mixing weights and cutoff levels are chosen from with a collection of possible combinations as a function of the transmitted signal. Millimetre-wave networking requires optimum data transmission to various computers on same moment network in combination with large multi-user actually massive. In order to guarantee efficient data transmission, the heavy insertion loss of wave propagation at su ch a faster speed needs proper channel estimation. A new channel estimation algorithm called Beam space Channel Estimation is suggested. From a set of possible configurations, the capacity of a massive stream from which antennas signals are handled by an analog channel as a part of the channel matrix, linear mixture weights and frequency modulation levels are selected. Probable implementations of specific analogue receiver designs for the combined network model, such as smart antenna selection, sign antennas output thresholding or linear output processing. To demonstrate the effectiveness of BEACHES in service and have FPGA implementation results, we are developing VLSI architecture. Our results show that for large MU-MIMOs, mm-wave communications with hundreds of antennas, specially made denoising can be done at maximum bandwidth and in an equipment format.
Design and Analysis of Dual Port Super WideBand Antenna Set for MIMO Applications
Authors: Gireesh Parvathy , Sandeep Kumar P , Malathi K , Khanra Ishani , Agarwal Aakansha , Sivakumar Kaushika 
Published: July 2021

Abstract
A planar monopole antenna with a super wideband frequency range covering a wide range of applications and compatible with MIMO applications is duly proposed. Compactness, i.e., reduction of size, is achieved following compatibility with MIMO application and also with SWB (Super Wide Band) applications. The bandwidth achieved is in the band range from 2 GHz to 20 GHz with a ratio of 1:10. Compactness in terms of size of the antenna is achieved, dimensions being 40mm*30mm. FR4 substrate is used in the design of the antenna, having a relative permittivity of 4.4. A hexagonal structure with an ellipse added on top is made as to the radiating element with at a per feed having a width of 3.1mm feeding an input of 50ohm into the antenna. Parasitic elements are introduced on the substrate for the design of the antenna.DGS techniques have been used in the semicircular structure of the partial ground plane of the antenna. A dual-port antenna supporting MIMO applications is therefore achieved by replicating the antenna described above on a horizontal plane with a 90-degree shift and hence accommodating both the vertical and horizontal polarization at the transmitting and receiving side as well.
AI Based Intrusion Detection System using Multi Sensors
Authors: Karthikeyan R , Hema L K , Vineet S , Vivek Prajapati P , Reginald Paul 
Published: July 2021

Abstract
In an intrusion detection system, the existing system uses single sensor that causes false alarms due to lack of accuracy and also leads to misuse of fuels that are stored in nuclear power plants/ reactors. The fuels that are used in the reactors are too expensive and high in price. The fuels use in nuclear power plants/ reactors must be protected under such circumstances that may reduce the detection and inactive secure system of false alarms under given area. In this paper multiple sensors are used to interface with Arduino to overcome false detection using KNN algorithm for the classification of nearest neighboring values that compares with the predefined and predicted values in the given database. Hence the KNN uses to forecast a new point in sample classification, a database where the data points are divided into many groups. This is the point where KNN is located in the Scikit-learning algorithm list. Therefore, the K Nearest Neighbors method stores all available cases and starting lineup cases on the basis of mutual information.
Design and Implementation of Dielectric Resonator Antenna Array for Satellite Applications
Authors: Raghavendra Ch , Neelaveni Ammal M 
Published: July 2021

Abstract
A dielectric resonator antenna with size 100*100*10 operating at 6GHZ is proposed. The proposed antenna is constructed using triangular monopoles on top of the cylinders and fed by using a power divider with four ports. Power is fed through the microstrip line to the power divider. The cylinders are combined with patches of triangular shape. The designed antenna has a bandwidth from 5GHZ to 9GHZwith a peak gain 26dBand for satellite uplink applications.
MR and CT Image Fusion Using Nonlinear Anisotropic Filtering in PCA Domain
Authors: Rama Kishore Reddy S , Swathi V , Anusha K 
Published: July 2021

Abstract
In medical science it has been commonly used for computer-aided brain surgery, Alzheimer’s therapy, tumour identification & other medical assessment. Accurate fusion algorithms can be made to ensure proper detection of diseases. The mechanism of fusion is incredibly insightful, since it transforms information from a single picture from two or more pictures into a single picture. In addition, the most common application is the use of images of the magnet resonance (MR) & the computed tomography image (CT). The objects in the source images must be reduced. A new algorithm is introduced here for image fusion. In the principal component analysis (PCA) domain, the nonlinear anisotropic filtering (NLAF) most efficiently preserves texture features of the segmented image. The source images are broken down into estimation & information layers by NLAF. The PCA support is used to measure the actual detail & approximation layers. Fusioned images are eventually generated by last detail and approximation layers linear combination. The algorithm suggested efficiency & quantitative output is evaluated by image consistency parameters, including the PSNR, entropy (E), square-root root (RMS) & structural similitude (SSIM) indices. Compared with the conventional & recent image fusion algorithms, detailed simulation findings of the suggested hybrid technique. Evaluation of efficiency shows that the proposed fusion solution is beyond the actual fusion approach.
Real Time Traffic Light Controlling System Using Morphological Operators and Fuzzy Logic
Authors: Hari Krishna B , Santosh Kumar Patra P , Kalpana Ganapuram 
Published: July 2021

Abstract
There is a need for development of advanced smart traffic controlling schemes due to the enhancement in urban traffic congestion. Currently, there are some traffic controlling methods based on timers or controlled by human. However, due to these systems there must be wastage of power in the night times and early morning hours. In order to address this issue, this paper introduces a novel and Traffic light management scheme in real-time with digital image recognition using contrast improvement and fluctuating logic systems for morphological operators. The proposed traffic control system provides an upgrade over traditional systems in terms of time of response, automation, stability and overall performance.
Android Application and SMS Alert Based Garbage Monitoring and Navigation System
Authors: Umapathy K , Mangayarkarasi T , Subitha D , Sivagami A 
Published: July 2021

Abstract
The treatment of waste is unsafe in city centres where residents are more involved, leading to germs that can lead to disease. How commonly these litter containers are used in different regions is different. Regular timing checks are not helpful. Often, they will overflow much faster than expected. In this article, a smart waste monitoring method is advised to prevent this and increase cleaning, to figure out where the waste is complete.The architecture of the method collects and transmits information through a wireless network. Under this technique, the dustbin’s waste level is measured by sensors and information is transmitted through the GSM and GPS module to the official mobile station. Wi-Fi Module is used to track waste levels online at the control room. Arduino Processor uses network modules to link sensor systems.
Design and Development of Smart Portable System for Underground Pipeline Leakage Monitoring Based on IoT
Authors: Puviarasi R , Dineshkumar T , Suresh Babu V , Partheeban Pachaivannan 
Published: July 2021

Abstract
Water is arguably the world’s most important resource. Enormous water is lost around the world due to leakages of water pipelines. Wisely wasting water should be stopped in order to exploit this advantage. This article suggests a safer approach in which the pipeline controls water pressure, and the leaking of the pipeline is observed. Observatory package with Raspberry Pi and a water quality sensor pair are connected throughout the pipeline. Continuously uploads the sensor data to the cloud server. If the pressure is below the specified threshold and the processor sends the warning message to the workers concerned amid persistent stress, the water quality disrupts. In order to post to the server, we need Internet access. However, warning messages can also be sent via SMS services that operate with the GPRS in the absence of the internet. This article further clarifies tentative steps to minimize leakage. The flow of water through the valves located at the link between the pipelines is supplied and controlled. The control valve location is controlled to mitigate water loss due to the leakage generators so that water flow is decreased into the same pipeline resulting in lower water loss.
RF Based Lo-Ra Transceiver Patient Health Detection System
Authors: Malarvizhi C , Periyarselvam K , Sendhilkumar N C , Anand M 
Published: July 2021

Abstract
In the last century, remote treatment surveillance grew rapidly, along with the increasing number of internet users with things (IoT). Health management, especially because early disease diagnosis can minimize distress and treatment costs, is very important for prevention. The diagnosis and timely care of multiple conditions will dramatically boost patient treatment alternatives: Wireless Clinical Management and Monitoring Device for Patients. Wireless health surveillance system or patient surveillance system requires remotely tracking the critical patients through computers, which transmit patient data wirelessly to distant locations. Health networks based on IoT seek to increase the quality of healthcare services via data collection and analysis in real-time. Nonetheless, conventional IoT systems have several drawbacks. In areas with a weak or unreliable Internet, for example, they cannot operate effectively. Low power large area network (LPWAN) technologies such as long-range network components like LoRa are a viable solution for showing the issue of Internet services. In diagnostic techniques and therapies, monitoring system plays an essential part.
Industrial Speed Control of IM Based Model Predictive Controller Using Zeta Converter
Authors: Pattanaik Balachandra , Barani Sundaram B , Mishra Manish Kumar , Thirumoorthy Dhanabal , Rastogi Umang 
Published: July 2021

Abstract
For induction, machine-based configuration, the model predictive control scheme, power converter based renewable system is presented in this paper. The PV system is proposed to provide an input source for the model predictive control (MPC) based system. The control method predictive is used based on vector control. According to this, the drive system behaviour of the fault-tolerant capacity is enhanced. The ZETA converter is proposed to improve the system input source, which fed on the PV system. The proposed ZETA converter is used to increase the DC link voltage of the system. The motor’s speed and torque can be controlled by the model predictive control method based on vector control. The results of the proposed system are obtained and verified using the MATLAB/Simulink.
Healthcare Technology with Flexible Smash Crystal Access Management System
Authors: Kalimuthu K , Balarengadurai C , Akilandeswari A , Raja A 
Published: July 2021

Abstract
The Internet of Things (IoT) healthcare has been suggested as a talented way of importantly increasing patient productivity also satisfaction. In IoT, medical instruments calculate the critical symptoms of the patients and add them onto medical databases that are processed and retrieved by healthcare personnel in the cloud. Encryption is usually used to maintain authentication by trusted parties to medical data while avoiding unauthorized access to them to protect patient privacy. The prompt access to patient files in emergency cases is important in healthcare. In this article we suggest a scheme that facilitates the access to protected medical data, attribute-based access and broken glass access, which is a compact blow access control (LiBAC). Under normal cases an attribute-set medical worker can decode and view the data that complies with the access policy of the medical file. The break-glass entry system circumvents the patient file access regulation, allowing emergency medical services or rescue personnel to access the records in good time. As the instruments in the IoT healthcare network conduct very few calculations and storage in addition communication overheads are minimal, LiBAC is light-weight. LiBAC in the standard model has been officially proven stable, and comprehensive studies are carried out to illustrate its efficacy.
VLSI based Implementation of Channel oriented ICA Processor for Biomedical systems
Authors: Mishra Suman , Rajeshkannan S , Mohankumar N , Ganesh Babu T R 
Published: July 2021

Abstract
The remarkable developments in neural engineering in collecting and analyzing big data have made it possible to further recognize the patient’s brain conditions through their neural recovery, reconstruction, identification, and diagnosis. As a recent science field, the convergence of signal processing and neural processing begins to emerge to work with a major amount of neuronal information for easy, long, but powerful purposes. With complex neuroscience uses, mass spectroscopy indications for brain-computer connections have proved very exciting. We concentrated on EEG-based methods in this analysis from Solutions in getting high and power solutions. Specifically, in Ecg signals’ growing field, we discuss the latest practices, scientific prospects, and CS threats. We stressed that big CS imaging techniques summarise the minimum foundation and the calculation function being used CS to interpret electrical signals. The whole researcher noted selecting an efficient recovery method, imperfect base, and measuring matrix; it will increase current Adc Brain imaging assessments’ efficiency. Finally, the possibilities and issues emerging from promoting the implementation of its application domain architecture are discussed. Research article presents 4-channel Ica in Eeg data differentiation for treated patients and studies brain functionality. A modern ICA process is developed using a mixed linear, tube, and concurrent processing elements and using alternating and triangular Systems in the brain to achieve a device design and manufactured with UMC 90nm Strong Conventional technologies.
Implementation of Deep Neural Network Using VLSI by Integral Stochastic Computation
Authors: Khan Vijitha , Parameshwaran R , Arulkumaran G , Gopi B 
Published: July 2021

Abstract
Efficient machine learning techniques that need substantial equipment and power usage in its computation phase are computational models. Stochastic computation has indeed been added and the solution a compromise between this ability of the project and information systems and organisations to introduce computational models. Technical specifications and energy cost are greatly diminished in Stochastic Computing by marginally compromising the precision of inference and calculation pace. However, Sc Neural Network models’ efficiency has also been greatly enhanced with recent advances in SC technologies, making it equivalent to standard relational structures and fewer equipment types. Developers start with both the layout of a rudimentary SC nerve cell throughout this essay and instead study different kinds of SC machine learning, including word embedding, reinforcement learning, convolutionary genetic algorithms, and reinforcement learning.
Consequently, rapid developments in SC architectures that further enhance machine learning’s device speed and reliability are addressed. Both for practice and prediction methods, the generalised statement and simplicity of SC Machine Learning are demonstrated. After this, concerning conditional alternatives, the strengths and drawbacks of SC Machine learning are addressed.
VLSI Architecture of Flexible Macroblock Ordering Manchester Encoding with Sols Method
Authors: Srinivas L , Upender G , Aravinda N L 
Published: July 2021

Abstract
Encoding techniques are getting the essential role of conversation. Strategies like Manchester and FM0 encoding are used as a part of numerous applications.Every strategy has distinctive activities relies upon its requirements. Every single encoding plan is utilized without losing any of its parameters. SOLS, which incorporates architecture and sync, and DSRC framework is often used to preserve the dc balance, and signal reliability is the semi-oriented logic simplification technology (SOLS). We may reduce the number of transistors and change DC by applying both procedures. The present work manages to get an incorporated design of FM0, Manchester encoding to conquer a traditional method. In this provided method, the number of hardware modules is minimized, and the total area used in Dedicated Short Reach Communication (DSRC) is consequently decreased.