bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis on Sports Data Match Result Prediction Using Machine Learning Libraries
Authors: Kevin Andrews S , Lakshmi Narayanan K , Balasubadra K , Josephine M S 
Published: July 2021

Abstract
Sports research and betting have been powered by quick exposure to the Internet and machine learning popularity. Football is considered the most popular game in 200 countries and contrasts to other sports. It is considered much more diverse and complicated, making soccer an enticing area to do research. A variety of methodologies and methods are used for the production of prediction systems. We expect the outcome of a match between the Premier League and a home side. The projections are based on numerous significant evidences from the Premier League’s previous seasons. These essential characteristics would possibly decide the result of a match. We use three different algorithms to predict the machine learning techniques and then choose from those three the best algorithm for predicting the label.
Enhancement and Development of Next Generation Data Mining Photolithographic Mechanism
Authors: Geetha D , Kavitha V , Manikandan G , Karunkuzhali D 
Published: July 2021

Abstract
The analytical data of project management was established. In a stereolithography method, the APC system was already implemented in essential dimensions and overlays. Productivity and system efficiency have been enhanced. The new APC, however, is created on the inspection information where the method anomalies are blended with the fluctuation of the system and which have to evaluate very small quantities, and it has the impact cap. The inspection data for the CD, overlay and log information of the acquaintance tool in ainteractive data base have been compiled and processed. We have also investigated how the earlier in this thread problem can be paid and resolved. First of all, in the enormous tool log data we have extracted ties between inspection informationbesides several parameters, particularly factor loadings. We then discussed problems with big relationships and have, thus, gathered valuable knowledge which did not come out of the traditional system. In order to show the stabilising machine fluctuation effect, we developed, along with APC, a second-generationinformation mining system.
RETRACTED: Security Protection of Information Utilizing Halfway Speculation
Authors: Ishwarya M V , Suganya J , Nalini M , Kumaresan A , Suresh Anand M 
Published: July 2021

Abstract
Securing privacy in information-digging (data mining) has become indispensable for buying and selling labelled statistics in statistical evaluation, validation, and guide. In such cases, records are either released in published form for re(use) through others for research functions. Here, privacy takes an extensive role to secure the records from ever-escalating net phishing and different probable attackers. Significant upgrades for strong privateness upkeep and protection have emerged as mandatory. In this paper, we endorse the approach of partial speculation. This technique is essential to mask the information in this sort of manner that different facts mining strategies can be without difficulty applied to it. On the alternative hand, it makes the information okay-nameless for this reason, information cannot be re-identified at the same time as records remain almost useful. In partial speculation, simplest identifiers that are vital are speculated first. If this step, safeguards the records from external information linkage, then the technique no longer speculates besides, preventing extra speculation than important with minimal facts loss.
A Transparent Immutable and More Secured Voting System Using Blockchain
Authors: Nagajothi S , Shamrutha S S , Sreeja D , Tejeswini S J 
Published: July 2021

Abstract
Blockchain is a cryptocurrency system with a transaction record of several computers in a peer-to-peer network. Blockchain In this paper, we propose a transparent, immutable, and more secured voting system using blockchain that collectively approaches security and cost issues. In Ballot voting, there is no security, immutability between the voter and the system. The proposed system uses blockchain technology to increase the efficiency of the voting system. Here the algorithm used is blockchain which includes a private key and public key encryption, SHA-256, Merkle hashing tree, and for security, one-time password (OTP) authentication can be done. It permits the voter to vote from any place, which increases the overall attendance percentage. The proposed system gives improved security and manages several data in the blockchain. In this system, we proposed security voting by using blockchain technology. In the existing system easy to vote for the ones who have not voted? I, vote fraudulent is happening on every century, some securities have been implemented but in parallel fraudulent is also increasing.
An Innovative Algorithm for Cluster-Based Decision Support System Using the Fuzzy Soft Set Approach
Authors: Jayagowri P , Arockiaraj S , Karthik R 
Published: July 2021

Abstract
Hard sets and soft sets must be adopted for several unknown logistical problems. This paper seeks to solve the cluster-based decision-making dilemma effectively based on fumigated soft environments. First of all, we are introducing an adjustable approach to resolution of decisions focused on fuzzy soft solutions. Then, the information and the degree of divergence dependent on a-similarity are introduced to determine the weights of the experts. In addition, with uncertain expert weights, we can create an effective cluster-based decision-making strategy. Finally, sensitivity analysis and comparative analysis was conducted with other established approaches.
Design of IoT Based Smart Energy Meter for Home Appliances
Authors: Rupesh M , Anbu Selvan N 
Published: July 2021

AbstractCommunication technology development is increased day by day. Due to the development of communication technology, every product is manufactured with smart activities. From the past decade, most electric devices are executed automatically using the remote control. Internet of Things (IoT) is used to connect various devices easily with the help of sensors. All the connected devices are working automatically without any human interventions. The roles of human beings are only to manage and control the connected devices from a remote location. Electric meters also using the concept of IoT. This paper describes smart meter devices. This system’s main purpose is to au tomatically read the number of current consumption units with LED light, calculate the amount, and display the messages to the user’s website and user’s smartphone. This system also issues the user’s alert message when the current consumption unit crosses the limited level.
Microcontroller Based Automatic Irrigation and Fertilisation System Using Soil Moisture Sensor and Ph Sensor
Authors: Sruthi R , Swytha S , Varsha K , Kavitha P 
Published: July 2021

Abstract
Farmers are reportedly facing a lack of rain and water. The main aim of the paper is the automatic irrigation solution for farmers. This helps to save them precious time and resources. Conventional irrigation technology requires more human action. Human interference can be reduced to a degree with the proposed automatic irrigation and fertilisation technologies. There is still a chance to reduce risks and make work more meekly thanks to the development of technology. The devices focused on integrated and micro controllers have enormous resolutions to voluminous challenges. By using a sensor micro controller system, the proposed programme accurately controls irrigation systems for agriculture. In the field, sensors are mounted to measure PH of a field and relative humidity that transports the signal to the computer for the calculation of crop water requirements. The population of India exceeds 1.2 billion and the pace of population rises daily, so there will be a significant food issue after 2530 years, so it is important to improve agriculture that can be accomplished by introducing these devices in the region.
Improved Prediction of Wind Speed Using Machine Learning
Authors: Giftson Samuel G , Salimath Gangadharayya F , Porselvi T , Karthikeyan V 
Published: July 2021

Abstract
In wind energy systems, wind speed estimation plays an important role. For wind energy systems, accurate forecasting of wind direction is essential, but it is challenging because of its variability. In this paper, wind speed prediction is accomplished using a machine learning-based random forest (RF) method. For the production of wind energy, short-term wind speed prediction is a significant activity. However, it is difficult only to obtain deterministic estimation since wind supplies are erratic and unpredictable. It increases learning that helps to project future values. Average wind speed is a major feature that affects the atmosphere. This paper explains the estimation of wind speed with ML algorithm. It is valuable for assessing the prospects for abnormal climate events and wind energy in the future.
Machine Learning-Based Predictive the Forecasting of Short Term Wind Speed
Authors: Selvaraj Yoganand , Sathyanathan P , Ilango V. , Santhosha D. 
Published: July 2021

Abstract
As a possible emerging technology for electricity generation, wind power is rapidly evolving world’s mainstream influence. However, the inherent spontaneous wind instability poses great obstacles to stable grid usage and power supply stability. One way of efficiently addressing the wind instability problem is to enhance accurate wind velocity forecasts. However, the intrinsic regularity of wind speed data cannot be for the bulk of the wind speed estimation method. Therefore, this paper introduces machine learning (ML) based genetic algorithm (GA) and the Short-term Wind Speed Prediction Model, which can effectively improve wind speed prediction accuracy. The work of study will help evaluate the power grid risks adequately. The appropriate electricity system divisions are expected to create a realistic generation schedule, minimize cost effectively, and significantly encourage green-energy growth.
Dual-input DC/DC Converter for Solar Energy Harvesting Applications
Authors: Jenifer A , Sukhi Y , Nivethitha B P , Jagadeeswari  , Pavithra S 
Published: July 2021

Abstract
In this article, a high-level DC / DC converter is introduced with an external CVS circuit.Theory and experimental results indicate that the control mechanism has a double input design that in particular decreases the cost of the PV generation system;The ZVS auxiliary circuit suggested effectively increases the performance of the converter. The power and control system is straightforward, much like the traditional two-phase booster conversion system.
Grid Connected Bidirectional Converter Based Ems System with Model Predictive Control
Authors: Karthikeyan V , Porselvi T , Salimath Gangadharayya F , Giftson Samuel G 
Published: July 2021

Abstract
In this paper, the bidirectional converter that performs DC-DC power conversion is integrated with the variable speed wind energy conversion system’s grid system. Generally, the voltage quality is reduced, and fluctuation in outputs is performed in renewable energy sources. The stable operation and power generation with fluctuation and power demand in the variable are ensured by developing the energy management system (EMS). In this proposed method, the bidirectional converter’s control is accomplished using the proportional-integral-derivative (PID) controller, which controls the power fluctuation from the WECS to maintain constant. The DC-AC voltage conversion is achieved using the model predictive controller (MPC), which controls both power and voltage. This proposed power and voltage controller enhances the stable AC voltage supply and improves the proper power flow. The proposed method, which is validated in simulation is simple, and the results are obtained using MATLAB/Simulink.
Design of Digital Clock Manager Using Tunable BFD–True Random Number Generator
Authors: Chaitanya Krishna A , Priyanka Ch , Gampala Divya 
Published: July 2021

Abstract
By demanding authentication exercises for example communications, electronic cash frameworks, plate encryption, the cryptographic frameworks have become a core aspect in our daily lives. Random numbers are an significant factor in strengthening and anchoring the protection of e-mail messages used in multiple encryption applications, including key ages, encryption, convention coverage, web wagering. Random flight numbers for basic mystery keys are basic to the protection of criphotographical calculations. In a variety of cryptographic systems, actual random number generators (TRNGs), The part has been incorporated, including PIN / secret word age, validation agreements, key age, random cushions and age of nunce. The circuit uses an undetermined random mechanism as a fundamental source, largely as electric commotion. Programmable field door arrays (FPGAs) are the optimal stage for the success of equipment that offers substantial safety conditions. The TRNG suggested is subject to the Xilinx-FPGA Bit Recurrence Recognition Guideline.
Design and Optimization of CPW-Fed Bow-Tie Slot Patch Antenna
Authors: Malarvizhi C , Brenda M , Bas kar S , Joselin Jeya Sheela J 
Published: July 2021

Abstract
In this article, a mirror edged bow tie slot antenna is modelled and fed by a CPW fed with a finite ground plane. This design is calculated and its material properties such as its substrate FR4 is utilized which is easily available and less cost of fabrication. The height of the substrate is 2.96mm, with sr=2.The operating frequency is set at 2.45GHz which is ISM frequency band of operation. The antenna was simulated using CST Microwave suite and its results are inferred. The resonating frequency is at 2.581 GHz. This antenna is used for Wi-Fi applications.
Classification of FPGA Based Network Traffic Using Machine Learning
Authors: Gunasekaran K , Baskar Radhika , Dhanagopal R , Elangovan K 
Published: July 2021

Abstract
To successfully control infrastructure, the actual identification of internet activity is important. Including faster response times, classifiers automated segmentation strategies have demonstrated favourable performance. Throughout this document, utilizing regression analysis and decision tree features collection, the box and hydraulic model’s appropriateness is checked. Besides, the appropriate number of shipments found in a flow when obtaining flow-level characteristics is calculated by the tests conducted, showing that 46% of movement packages are a reasonable balance that guarantees high efficiency in the minimum time consumed. The tests’ findings show that randomized forests outperform other architectures with a peak precision of 35%. However, since software-driven classification algorithms do not fulfil the expected real-time specifications, we propose a statistical learning device based on the Field-Programmable Gate Array (FPGA) that uses an incredibly parallel architecture simplify the mechanism in this way. The proposed architecture achieves better performance, exceeding the recorded hardware-based classifier outputs using equivalent methods, which guarantees realistic driving management consistency in cluttered computer servers.
A Robust Jitter Noise Power Reduction in Ultra-Speed Optical OFDM Systems
Authors: Lakshmi Devi N , Anusha K , Mahesh AllamVenkata Naga 
Published: July 2021

Abstract
Recently, there is a tremendous growth in wireless communication networks for achieving ultra-high-speed data transmission to enhance the performance of optical communication system. In such systems, jitter is a serious drawback and will leads to impairments in transceivers that causes overall mitigation on the system performance. We used a robust noise reduction technique to minimise the jittering effect under various fading conditions of the channel such as white gaussian additives (AWGN), Rayleigh and Rician distribution to solve this problem. Extensive simulation analysis shown that the proposed approach mitigates the average jitter noise under considered channel circumstances. We also compared the channel performances in terms of sub carrier index versus power.
Design and Development of a Crop Quality Monitoring and Classification System using IoT and Blockchain
Authors: Sangeetha M , Thejaswini Goriparthi , Shoba A , Santoshi Gaikwad S , Amretasre R T , Nivedita S 
Published: July 2021

Abstract
In this paper, an Internet of Things (IoT) based Crop Monitoring and Classification system is proposed for automated sensing, storing, and monitoring real-time parameters that play an important role in determining a crop’s quality and yield. Sensors are placed in-situ in the field and the warehouse to monitor the crop. The long-Range wide area network (LoRa) module is used for communication between the sensing unit placed at the field, warehouse, and data processing unit. The yield is classified based on qualitative analysis posed by the imperative sensor data. Further, to enable an equitable gateway of resource sharing between the distributor and the farmer, a Blockchain-based transaction is taught to enhance trust and security. This proposed method aims to eliminate intermediaries in the trade, thereby helping farmers get the price for their product details stored in an immutable database, which also displays the farmer’s quality of the crop reaped.
Modelling of Multigate MOSFET Short Channel Structure for Low Power Application
Authors: Bantupalli Siva Surya Jaya Praveen , ArunaPriya P , Sharma Tanisha , Hariprasad R 
Published: July 2021

Abstract
The paper proposes a multi-gate structure for MOSFET and focuses on studying the structure with variations in parameters such as channel length, dielectric material, source material, and gate work function. By ensuring small device dimensions, the proposed structure has been simulated using the Silvaco-TCAD tool along with analysis of short-channel effects. The proposed structure can find its usage in low power and high-frequency applications due to high switching rates. The structure also possesses high transconductance at low gate voltages, increasing intrinsic gain and proving useful in RF devices. As the device is nano-scaled, it can prove worthy for fast switching applications with low losses.
Design and Analysis of Frequency Selective Surface for Ism and Lower Ultra-Wideband Antenna
Authors: Janakiram P , Ajith Srighakollapu , Bashyam S , Kamal Nikhil G , Akhil Teja R 
Published: July 2021

Abstract
A Compact, dual-layer Frequency Selective Surface (FSS) is presented for electromagnetic shielding applications. The square loop FSS is modified to provide band rejection characteristics for ISM band and lower Ultra-Wide Band (UWB) covering from 2.2 GHz to 7.1 GHz with the bandwidth of (S21 < -20dB) 4.9 GHz. The novel design exhibits symmetric property due to which it achieves polarization-insensitive stable band rejection of the desired frequency band for various angles of incidences up to 60°. The proposed FSS structure has compact dimensions of 0.170λ x 0.170λ x 0.0117λ. The design was fabricated on either side of the substrate made of FR-4 with a dielectric constant of 4.4 and loss tangent of 0.02. The measured results are well per the simulation results. The proposed FSS in this paper has various applications, including the aerospace industry, hospitals, random, and in the scope of electromagnetic filters, etc.
An Upgraded Design of High-Performance Dual-Band Metal Strip Antenna
Authors: Alwani Abduljalil , Mokaied Mohammad Sadek , Ahmad Ahmad Zakaria , Kassab Mohamed , Nithya V 
Published: July 2021

Abstract
This paper presents an analytical study and an upgrade of reference metal-strip antenna for laptop applications. In recent years, the laptop industry has seen a trend towards more compact designs. This orientation posed new limitations to both designers and manufacturers. Thus, the volume allocated to the internal antenna must be reduced. The results demonstrated in this proposal were obtained through a comprehensive study of the reference design dimensions.
Performance Analysis of UWOC using SISO and SIMO Techniques
Authors: Aravind Jinka Venkata , Kumar Sanjay , Prince Shanthi 
Published: July 2021

Abstract
Underwater communication technology is challenging and so far, there is no alternate to sonar technology for wireless communication. Recently, optical wireless communication is proposed to establish reliable communication link underwater. In this paper, underwater wireless optical communication link is simulated under SISO, SIMO communication model techniques using OptiSystem tool. Link distance is enhanced by increasing the number of receivers in the communication model technique for UWOC system. The performance parameters such as bit error rate, quality factor are analyzed under different UWOC model technique for different link lengths. It is observed that as the number of receivers is increased in the communication model technique, the UWOC efficiency improves in terms of Q factor and BER.
Pedestrian Detection System using Image Processing for Driver Assistance
Authors: Harshavardhan Reddy B , Gayathri N 
Published: July 2021

Abstract
Human beings are the main important reason of road accidents. In high way roads the vehicles are going very fast. Because of such reasons while crossing the roads animals and also humans falls as a prey to the accidents. To avoid such kind of accidents new system is proposed using image processing concepts. In this the system is embedded with the vehicle. Camera is the main part of the proposed system. Whenever the animal or human being tries to cross the road while driving, the camera captures the image. In this proposed system, object detection concept is used. If the people or animals are detected by the camera this system provides an alarm to the user and automatically controls the speed of the vehicle. The type of the images and position of an image are also displayed on the LCD. The entire system is controlled by Arduino controller.
An Effective Segmentation of Tissues from MR Brain Images
Authors: Papachary B , Amru M , Rama Kishore Reddy S 
Published: July 2021

Abstract
Segmentation of MR brain image is quite useful in detection of tissues and further diagnosis. However, precise segmentation of tissues plays a significant role in diagnosing the patient more effectively. Previously, there are plenty of approaches was implemented and however they were failed to detect the exact tissue which led to the failure diagnosis. Therefore, an accurate detection of tissue is required for effective diagnosis. Here, this article presented an efficient segmentation of MR brain image tissues. Our approach includes a hybrid clustering mechanism with pre-processed by median filter. In addition, tissue area also estimated for better diagnosis of patient. In terms of computational complexity and segmentation accuracy the superiority of proposed hybrid approach over conventional segmentation algorithms of simulation results was disclosed.