bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simplified ciphertext-policy attribute-based encryption scheme with attribute level collusion resistance for cloud storage
Authors: Vurukonda Naresh , Velde Venkateshwarlu , TrinathBasu M. , Tejasri P. 
Published: December 2021

Abstract
The core objective of our paper is that to overcome the challenges of secure data sharing problem in cloud where users can access data if they acquire a certain set of attributes or credentials. At present, there is only one way for implementing such procedures is by employing a reliable server to mediate access control, store the data. The service providers have whole control over cloud applications, client’s data and hardware. However, if the data stored in the cloud server is conceded, then the data confidentiality will be compromised. With simplified CP-ABE data is confidential even though storage server is un trusted. Hence privacy of cloud data is enhanced by proposing a methodology that uses a privacy policy, encrypts the data based upon various group of attributes related to the user. The decryption of the data can be done only when his/her attributes match with the privacy policy. Simplified CP-ABE makes it easier to secure, broadcast and control the access of sensitive information, specifically across the cloud’s server and decrease collision resistance.
Experimental Validation for A Nine-Switched 3-phase Multilevel Inverter (MLI) With a Photovoltaic (PV) Source of Array
Authors: Nalli Praveen Kumar , Kadali Kalyan Sagar , Bhukya Ramu , Rajeswari V. , Garapati Durga Prasad 
Published: December 2021

Abstract
Now-a-days Usage of Multilevel Inverters application is very wide in the industrial applications. Keeping in view of industrial applications, a multi-level inverter with a solar PV array is designed in this paper to deliver power to the Alternating Current based load. A step-up converter is used at the input side of the three-phase multilevel inverter, which delivers the energy for the three-phase load, to regulate the output voltage of the solar Photovoltaic panel. The multilevel inverter utilizes 9 switching devices with five level sources in accordance to the usage of the level of sources in recent topologies. However, the advantage of this topology is that it uses fewer semiconductor switches than current topologies. Eventually, the paper includes the results of the modelling in the MATLAB and the experimental implementation of the proposed topology.
Noise-residue learning convolutional network model for magnetic resonance image enhancement
Authors: Singh Ram , Kaur Lakhwinder 
Published: December 2021

Abstract
Magnetic Resonance Image (MRI) is an important medical image acquisition technique used to acquire high contrast images of human body anatomical structures and soft tissue organs. MRI system does not use any harmful radioactive ionized material like x-rays and computerized tomography (CT) imaging techniques. High-resolution MRI is desirable in many clinical applications such as tumor segmentation, image registration, edges & boundary detection, and image classification. During MRI acquisition, many practical constraints limit the MRI quality by introducing random Gaussian noise and some other artifacts by the thermal energy of the patient body, random scanner voltage fluctuations, body motion artifacts, electronics circuits impulse noise, etc. High-resolution MRI can be acquired by increasing scan time, but considering patient comfort, it is not preferred in practice. Hence, postacquisition image processing techniques are used to filter noise contents and enhance the MRI quality to make it fit for further image analysis tasks. The main motive of MRI enhancement is to reconstruct a high-quality MRI while improving and retaining its important features. The new deep learning image denoising and artifacts removal methods have shown tremendous potential for high-quality image reconstruction from noise degraded MRI while preserving useful image information. This paper presents a noise-residue learning convolution neural network (CNN) model to denoise and enhance the quality of noise-corrupted low-resolution MR images. The proposed technique shows better performance in comparison with other conventional MRI enhancement methods. The reconstructed image quality is evaluated by the peak-signal-to-noise ratio (PSNR) and structural similarity index (SSIM) metrics by optimizing information loss in reconstructed MRI measured in mean squared error (MSE) metric.
IoT based health monitoring and record management using distributed ledger
Authors: Makka Shanthi , Arora Gagandeep , Mopuru Bhargavi 
Published: December 2021

Abstract
Frequent visit of doctors during pandemicis not recommended due to COVID-19 scenario. Internet of Things (IoT) based sensors can be used to measure andto do certain tests at home. The blockchain-based strategy promises to aid in the delivery of health-care services while maintaining data privacy. To maintain transparency in the health record, medications, claim history, etc., up-to-dated distributed ledger is required. Doctors have sometimes necessitate patients to undergo lab tests or buy drugs from those organisations merely in order to generate personal profit, even if the medical shop or pathology labs have a bad reputation. Therefore, blockchain technology provides trust among multiple parties so that any party could not be misguided. At times, the patient visits the hospital in critical condition and they may not be in situation to explain about medical history. In such scenario, the information stored in distributed leger may be helpful to the doctors for further treatment. The medical emergencies such as cardiac arrest and breathing issues, the patient requires immediate treatment or medicine at his/her location, the intelligent drone is useful for faster delivery of medicines and needed medical accessories.
A Survey on Security of the Hadoop Framework in the Environment of Bigdata
Authors: Gattoju Saritha , Vadlamani NagaLakshmi 
Published: December 2021

Abstract
The world is becoming increasingly digital at the moment. Every day, a significant amount of data is generated by everyone who uses the internet nowadays. The data are critical for carrying out day-to-day operations, as well as assisting corporate management in achieving their objectives and making the best judgments possible based on the information gathered. BigData is the process of merging many hardware and software solutions to deal with extremely huge amounts of data that surpass storage capability. It’s possible that large amounts of data will be generated. Hadoop systems are used in a variety of areas, including healthcare, finance, and government. insurance, and social media, in order to provide a quick and cost-effective big data solution. The Apache Hadoop is a framework for storing and processing data, managing, and distributing large amounts of information over a large number of server nodes. Here are some solutions that work on top of the Apache Hadoop stack to guarantee data security. To get a complete picture of the problem, we decided to conduct an investigation into existing security solutions for Apache Hadoop security in sensitive data which is stored on a huge data platform employing distributed computing on a cluster of commodity devices. The goal of this paper is to provide knowledge of security and Big Data issues.
Hardware Implementation of Automatic Power Factor Correction Unit For Industry
Authors: Shende Amit G. , Khubalkar Swapnil W. , Vaidya Prajakta 
Published: December 2021

Abstract
Power factor correction has always been challenging task. Most of electrical energy is wasted due to leading and lagging power factor. Thyristor switch modules are widely used in the rolling mills where more fluctuating load is available. The thyristor switch module with the reactor and capacitor is usedfor the compensating the reactive power in electrical power system. Automatic power factor correctionunit is required to keep unity power factor and optimize current consumption. Harmonics is reduced by connecting detuned reactor/inductor in series with capacitor and thyristor switched module. This paper shows design and hardware implementation of thyristorised automatic power factor correction unit for three phase circuit in an industry. The unit is flexible to maintain nearly unity power factor. The outcome is confirmed and acquired that the recommended circuit is perfect to produce improved output.
Six Maps with a Common Fixed Point in b-Metric Space
Authors: Surjeet Singh Chauhan Gonder , Sharma Ria 
Published: December 2021

Abstract
By using some generalized contractive self-mappings, we proved newfixed point results for six maps in b-MS. Results proved in this paper expand and improve some similar theorems got already. We additionally introduced an example and application to stake the appropriateness and applicability of the theorem proved.
L-Diversity for Data Analysis: Data Swapping with Customized Clustering
Authors: Lingala Thirupathi , Kishor Kumar Reddy C , Ramana Murthy B V , Shastry Rajashekar , Pragathi YVSS 
Published: December 2021

Abstract
Data anonymization should support the analysts who intend to use the anonymized data. Releasing datasets that contain personal information requires anonymization that balances privacy concerns while preserving the utility of the data. This work shows how choosing anonymization techniques with the data analyst requirements in mind improves effectiveness quantitatively, by minimizing the discrepancy between querying the original data versus the anonymized result, and qualitatively, by simplifying the workflow for querying the data.
Designing Performance Improvement Strategy in Automotive Companies Using SCOR Model and Importance Performance Analysis
Authors: Fauzia Dianawati , Zamzamy Kemas Zaky 
Published: December 2021

Abstract
This research begins by determining and validating indicators (KPIs) that will be used to measure performance in the company’s supply chain, and making questionnaires to compare priorities between indicators and also each attribute and process at each SCOR level. This study has five general processes of supply chain. Each process is further divided into several attributes that are included at level two within the SCOR framework, namely reliability, responsiveness, flexibility, cost, and assets. Furthermore, each of these attributes has a total of 49 performance indicator indicators. The next step is to validate and ensure each indicator can be measured in research by holding discussions with the company. This paper aims to obtain the value of the company's supply chain performance to determine the supply chain performance improvement strategy of PT. X so that the performance of the company's supply chain can improve.
Machine Learning Based Hybrid Intrusion Detection ForVirtualized Infrastructures In Cloud Computing Environments
Authors: Sarosh Ayesha 
Published: December 2021

Abstract
Nowadays technology steady shift have seen from the models of conventional software to the cloud technologies. Cloud computing is rapidly becoming the standard by fulfilling the computer infrastructure demands of all sizes of enterprises. One of the essential tools forbuilding trustworthy& secure environment of Cloud computing is the Intrusion detection, given the ubiquitous cyber attacks which can proliferate morph dynamically & rapidly. Machine learning (ML) based hybrid intrusion detection for virtualized infrastructures in cloud computing environments is presented in this paper. This infrastructure uses Hybrid algorithm: SVM (support vector machine) & K – means clustering classification algorithm, for improving the anomaly detection system accuracy. For evaluating this approach, UNSW-NB15 study is utilized from dataset & results compared with earlier techniques. For evaluating theperformance of suggested technique utilizes performance measures like average detection time. This approach has better accuracy compared to earlier approaches.
Design and Implementation of Efficient MOSFET’s Utilization Based Proposed Voltage Controlled Oscillator
Authors: Priyanka Kumari B S , Saxena Sobhit 
Published: December 2021

Abstract
Ring oscillator is a device which consists of NOT gates connected in the form of ring. This ring oscillator’s output oscillates between the true and false stages controlled by applied voltage. Now days this voltage controlled oscillator (VCO) becomes the heart of modern electronic devices and communication systems. Earlier five-stage complementary metal oxide semiconductor (CMOS) based VCO for the Phase Locked Loop (PLL) was implemented. High frequency oscillations are required for many applications and further it is observed that a very general technique is normally adopted by researchers to achieve high frequency that if number of transistors is increased then the frequency can be increased. But the consequences of increase in number of transistors are the increase in delay and more number of MOSFET occupies more area and more power dissipation. So, in this paper VCO is designed with efficient utilization of MOSFETs. There is a balance between frequency and number of transistors, so that the area and power dissipation can be reduced. From the obtained results it can observed that the number of MOSFET’s, Independent Nodes, boundary nodes total nodes and power are reduced compared to five stage VCO and VCO based Ring oscillator.
Attendance Management System Using Face Recognition Method
Authors: Mansoora Syed , Sadineni Giribabu , Kauser Shaik Heena 
Published: December 2021

Abstract
When it comes to classroom management, the attendance check is a critical component. Time-consuming, particularly when it comes to open meetings, is checking attendance by calling names or by handing around a sign-in sheet to make it easier to commit fraud. An implementation of a real-time attendance check is described in this article in great detail facial recognition system and its outcomes. The system must be able to identify a student’s face in order for it to work first snap a photograph of the pupil and save it in a database as a reference for future use. During the event, there were students may be identified by using the webcam, which captures photos of their faces auto-detects faces and selects students with names that are most likely to match, and lastly, depending on the facial recognition findings, an excel file will be updated to reflect attendance. To identify faces in webcam footage, the system uses a pre-trained Haar Cascade model. As a result, a 128-bit FaceNet has been generated by training it to minimise the triplet loss. The dimensions of the facial picture. When two facial pictures have similar encodings If the two facial pictures are from the same student or different. Use of the system as part of a class, and the outcomes have been extremely positive. There has been a poll done to find out more about There are both advantages and disadvantages to using a college attendance system.
Analysis On Power Gating Circuits Based Low Power VLSI Circuits (BCD Adder)
Authors: Srinivas M. , Daya Sagar K.V. 
Published: December 2021

Abstract
Currently, energy consumption in the digital circuit is a key design parameter for emerging mobile products. The principal cause of the power dissipation during idle mode is leakage currents, which are rising dramatically. Sub-threshold leakage is increased by the scaling of threshold voltage when gate current leakage increases because oxide thickness is scaled. With rising demands for mobile devices, leakage energy consumption has received even greater attention. Since a mobile device spends most of its time in standby mode, leakage power savings need to prolong the battery life. That is why low power has become a significant factor in CMOS circuit design. The required design and simulation of an AND gate with the BSIM4 MOS parameter model at 27 0C, supply voltage of 0,70V with CMOS technology of 65nm are the validation of the suitability of the proposed circuit technology. AND simulation. The performance parameters for the two AND input gate are compared with the current MTCMOS and SCCMOS techniques, such as sub-threshold leakage power dissipations in active and standby modes, the dynamic dissipation, and propagation period. The proposed hybrid super cutoff complete stack technique compared to the current MTCMOS technology shows a reduction in sub-threshold dissipation power dissipation by 3. 50x and 1.15x in standby modes and active modes respectively. The hybrid surface-cutting technique also shows savings of 2,50 and 1,04 in power dissipation at the sub-threshold in standby modes and active modes compared with the existing SCCMOS Technique.
Development of a Mobile Platform with IoT for LIDAR
Authors: Keong Tew Chin , Shukor S.A.A. , Rahim N.A. 
Published: December 2021

Abstract
Nowadays, interior scanning is very significant in mobile robot applications because it helps humans to monitor, study and investigate the environments, especially the challenging ones with clutter, hazardous, unexplored, dynamic, and others. A LIDAR can be utilised to perform the task; however, suitable mobile platform should be accompanying it to allow mobility while collecting data representing the environment. This paper shows the process of developing a suitable mobile platform for a low-cost laser rangefinder, RP LIDAR from SLAMTEC with its scanning performance. The mobile platform used in this project is an Arduino Uno R3 4WD mobile robot. L298 H-Bridge IC and HC-05 Bluetooth module is implemented on the robot to make the user able to control its movement through a mobile application. MIT app inventor is used to develop the mobile application. Through the application, user can control the mobile robot with the LIDAR to move around the selected indoor area to scan its environment. To show the scanning results, MATLAB will be used to plot the map. Analysis from the plotting show good mapping results and similar to the real environment, thus presenting its potential to be used in the above-mentioned situations.
IoT-based Carbon Monoxide (CO) Real-Time Warning System Application in Vehicles
Authors: Kamarudin A.A.A. , Khalid N.S , Ibrahim I.I. , Bakar M.A.A , Mahadi M.Z , Shukor S.A.A , Hasan M.Z , Mansor H 
Published: December 2021

Abstract
The project is about develop a system and application for detect the presence of Carbon Monoxide(CO) in car, since recently there are many cases of drowning while sleeping in car due to inhaling CO. The build system are able to detect the presence of CO and provide warning about level of CO to the users. It uses Blynk application to monitors level of CO inside the vehicle, MQ-9 gas sensor as the input sensor, ESP 8266 as medium to send data to the application via IoT-based and the level concentration of CO is displayed on the LCD in real-time displayed. For the output, it has 3 different condition based on the level concentration of CO. This project has been testing in six different situation. Based on the result, ambience air and in car with open window situation have lowest of CO level. Meanwhile, the highest of CO level is detect in smoke that are produced from fuel combustion of the car exhaust at distance 5 cm. Additionally, Principal Component Analysis (PCA) is used to analysed the ability of this system in clustering for each situation. As a result, PCA have clearly clustering data for every situation with the value of PC1 is 71.82% and PC2 is 28.18%, hence it is verified that the build system is able to applied in detecting the presence of CO. This project is believed able in helping to reduce the numbers of cases people drowning while sleeping due to inhaling CO in the car.
Motion Simulation for Triangular-Shaped Autonomous Underwater Vehicle (TAUV) with Controllable Rudder
Authors: Amran I Y , Isa K 
Published: December 2021

Abstract
The dynamic model and motion simulation for a Triangular-Shaped Autonomous Underwater Vehicle (TAUV) with independently controlled rudders are described in this paper. The TAUV is designed for biofouling cleaning in aquaculture cage fishnet. It is buoyant underwater and moves by controlling two thrusters. Hence, in this research work, the authors designed a TAUV that is propelled by two thrusters and maneuvered by using an independently controllable rudder. This paper discussed the development of a mathematical model for the TAUV and its dynamic characteristics. The mathematical model was simulated by using Matlab and Simulink to analyze the TAUV’s motion based on open-loop control of different rudder angles. The position, linear and angular velocities, angle of attack, and underwater vehicle speed are all demonstrated in the findings.
Cycling performance prediction based on cadence analysis by using multiple regression
Authors: Sudin Sukhairi , Aziz Azizi Naim Abdul , Saad Fathinul Syahir Ahmad , Khalid Nurul Syahirah , Ibrahim Ismail Ishaq 
Published: December 2021

Abstract
This project examined the influence of the cadence, speed, heart rate and power towards the cycling performance by using Garmin Edge 1000. Any change in cadence will affect the speed, heart rate and power of the novice cyclist and the changes pattern will be observed through mobile devices installed with Garmin Connect application. Every results will be recorded for the next task which analysis the collected data by using machine learning algorithm which is Regression analysis. Regression analysis is a statistical method for modelling the connection between one or more independent variables and a dependent (target) variable. Regression analysis is required to answer these types of prediction problems in machine learning. Regression is a supervised learning technique that aids in the discovery of variable correlations and allows for the prediction of a continuous output variable based on one or more predictor variables. A total of forty days’ worth of events were captured in the dataset. Cadence act as dependent variable, (y) while speed, heart rate and power act as independent variable, (x) in prediction of the cycling performance. Simple linear regression is defined as linear regression with only one input variable (x). When there are several input variables, the linear regression is referred to as multiple linear regression. The research uses a linear regression technique to predict cycling performance based on cadence analysis. The linear regression algorithm reveals a linear relationship between a dependent (y) variable and one or more independent (y) variables, thus the name. Because linear regression reveals a linear relationship, it determines how the value of the dependent variable changes as the value of the independent variable changes. This analysis use the Mean Squared Error (MSE) expense function for Linear Regression, which is the average of squared errors between expected and real values. Value of R squared had been recorded in this project. A low R-squared value means that the independent variable is not describing any of the difference in the dependent variable-regardless of variable importance, this is letting know that the defined independent variable, although meaningful, is not responsible for much of the variance in the dependent variable’s mean. By using multiple regression, the value of R-squared in this project is acceptable because over than 0.7 and as known this project based on human behaviour and usually the R-squared value hardly to have more than 0.3 if involve human factor but in this project the R-squared is acceptable.