bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of divertor heat flux width for ITER pre-fusion power operation using BOUT++ transport code
Authors: He X.X. , Xu X.Q. , Li Z.Y. , Zhu B. , Liu Y.
Published: December 2021

Prediction of divertor heat flux width is performed for the first and the second pre-fusion power operation (PFPO) phases specified in the new ITER research plan using BOUT++ transport code (Li et al 2018 Comput. Phys. Commun.
228 69–82). The initial plasma profiles inside the separatrix are taken from CORSICA scenario studies. Transport coefficients in transport code are calculated by inverting the plasma profiles inside the separatrix and are assumed to be constants in the scrape-off-layer. An anomalous thermal diffusivity scan is performed with E × B and magnetic drifts. The results in two scenarios identifying two distinct regimes: a drift-dominant regime when diffusivity is smaller than the respective critical thermal diffusivity χ
c and a turbulence-dominant regime when diffusivity is larger than it. The Goldston heuristic drift model and the ITPA multi-machine experimental scaling yield a lower limit of the width λ

q
. From transport simulations, we obtain the critical thermal diffusivity χ
c = 0.5 m2 s−1 for the PFPO-1 scenario with toroidal magnetic field B = 1.77 T and plasma current I
p = 5 MA, and χ
c = 0.3 m2 s−1 for the PFPO-2 scenario with toroidal magnetic field B = 2.65 T and plasma current I
p = 7.5 MA. Separatrix temperature and collisionality also have a significant impact on the heat flux width in the drift-dominant regime. The investigation clearly yields a scaling for critical thermal diffusivity

χ

c

∝

A

1
/
2

/

(

Z

1
+
Z

1

2

B

p

2

)

using ITER scenarios with fixed safety factor q
95, major radius R, aspect ratio R/a, and the separatrix temperature T
sep, and establishes the connection with CFETR and C-Mod discharges. This scaling implies that for a given tokamak device with q
95, R, R/a, and T
sep fixed, a reduction of poloidal magnetic field by a factor of 3 leads to a 9 times higher critical value of thermal diffusivity χ
c, possibly yielding a transition from turbulence- to drift-dominant regime.
Orbit tomography of energetic particle distribution functions
Authors: Stagner L. , Heidbrink W.W. , Salewski M. , Jacobsen A.S. , Geiger B. , the DIII-D  , ASDEX Upgrade Teams
Published: December 2021

Both fast ions and runaway electrons are described by distribution functions, the understanding of which are of critical importance for the success of future fusion devices such as ITER. Typically, energetic particle diagnostics are only sensitive to a limited subsection of the energetic particle phase-space which is often insufficient for model validation. However, previous publications show that multiple measurements of a single spatially localized volume can be used to reconstruct a distribution function of the energetic particle velocity-space by using the diagnostics’ velocity-space weight functions, i.e. velocity-space Tomography. In this work we use the recently formulated orbit weight functions to remove the restriction of spatially localized measurements and present orbit tomography, which is used to reconstruct the 3D phase-space distribution of all energetic particle orbits in the plasma. Through a transformation of the orbit distribution, the full energetic particle distribution function can be determined in the standard {energy, pitch, r, z}-space. We benchmark the technique by reconstructing the fast-ion distribution function of an MHD-quiescent DIII-D discharge using synthetic and experimental FIDA measurements. We also use the method to study the redistribution of fast ions during a sawtooth crash at ASDEX upgrade using FIDA measurements. Finally, a comparison between the orbit tomography and velocity-space tomography is shown.
Modelling of sawtooth-induced fast ion transport in positive and negative triangularity in TCV
Authors: Vallar Matteo , Podesta Mario , Baquero-Ruiz Marcelo , Bonofiglo Phillip , Duval Basil P , Karpushov Alexander N , Merle Antoine , Mykytchuk Dmytry , Sauter Olivier , Stipani Lorenzo , Testa Duccio S
Published: December 2021

Internal kinks are a common magneto hydro-dynamic (MHD) instability observed in tokamak operation when the q profile in the plasma core is close to unity. This MHD instability impacts both the transport of the bulk plasma (current, particle and energy transport) and minority species, such as fast ions. In TCV (R 0 /a = 0.88 m/0.25 m) the fast ion population is generated in the plasma by neutral beam tangential injection of energies up to 28 keV. TCV features 16 active shaping coils permitting a great flexibility in plasma shape, including negative triangularity (δ) configurations that show surprisingly high confinement. This study focuses on the transport of fast ions induced by sawteeth, by comparing two triangularity cases and simulation results with experimental data. Comparison of two equilibria with opposite δ shows that the fast ion drifts are larger for δ < 0. Furthermore, the sawtooth-induced transport in this case is larger than δ > 0 in similar conditions. Comparison with experimental data confirms the dominance of the modification of thermal kinetic profiles following the sawtooth crash in explaining drops in the neutron rates and FIDA signals. Additional fast ion diffusion, however, improves the interpretation of the experimental data. For δ < 0, the amplitude of the perturbation better representing the experimental data is larger. Finaly, an exploratory study for 50 keV particles (soon available in TCV) shows that the situation does not worsen for such particles.
Experimental validation of universal plasma blob formation mechanism
Authors: Bisai N. , Banerjee Santanu , Zweben S.J. , Sen A.
Published: December 2021

Anomalous plasma transport in the boundary region of a tokamak plasma is commonly associated with the formation and evolution of coherent density structures known as blobs. Recently, a theory for a universal mechanism of plasma blob formation has been put forward. It is based on a breaking process of a radially elongated streamer due to poloidal and radial velocity shears. The theory is well supported by two-dimensional and three-dimensional numerical simulation results but lacks experimental validation. In this work, we report the first ever experimental validation of this universal criterion by testing it against NSTX data on blobs obtained using the gas-puff imaging diagnostic. It is found that the criterion is widely satisfied in most L-mode discharges and may explain the significantly larger number of blob events. We also validate the theoretical criterion against ADITYA Langmuir probe data taken in the scrape-off layer region.
Progress on neutronic analysis for CFETR
Authors: Lu Peng , Wu Qiuran , Du Hua , Zheng Yu , Zhang Xiaokang , Zhu Qingjun , Ma Xuebin , Liu Songlin
Published: December 2021

The neutron-induced irradiation field is a key problem in a fusion reactor related to nuclear responses, shielding design, nuclear safety and thermo-hydraulic analysis. To support the system design of the China Fusion Engineering Test Reactor (CFETR), a comprehensive analysis of the irradiation field has been conducted in support of many newly developed advanced tools. This paper first summarizes recent progress on the related effort to develop neutronics code including the geometry conversion tool cosVMPT, Monte Carlo variance reduction technology and ‘on-the-fly’ global variance reduction. Such developed tools have been fully validated and applied to the CFETR nuclear analysis. The neutron irradiation has been evaluated on the CFETR water-cooled ceramic breeder blanket, divertor, vacuum vessel (VV), superconductive coils and four kinds of heating systems: electron cyclotron resonance heating, ion cyclotron resonance heating, low hybrid wave and neutral beam injection. The nuclear responses of tritium breeding ratio, heating, irradiation damage and the hydrogen/helium production rate of material have been analyzed. In the case of neutron damage and overheating, deposition on the superconductive coils and VV, the interface and the shielding design among heating systems, and the blanket and other systems, has been initialized. The results show the shielding design can meet the requirement of coil and VV after several iterated neutronics calculations.
Quasipotentials in the nonequilibrium stationary states or a method to get explicit solutions of Hamilton–Jacobi equations
Authors: Garrido P L
Published: December 2021

We assume that a system at a mesoscopic scale is described by a field ϕ(x, t) that evolves by a Langevin equation with a white noise whose intensity is controlled by a parameter

1
/

Ω

. The system stationary state distribution in the small noise limit (Ω → ∞) is of the form P

st
[ϕ] ≃ exp(−ΩV
0[ϕ]), where V
0[ϕ] is called the quasipotential. V
0 is the unknown of a Hamilton–Jacobi equation. Therefore, V
0 can be written as an action computed along a path that is the solution from Hamilton’s equation that typically cannot be solved explicitly. This paper presents a theoretical scheme that builds a suitable canonical transformation that permits us to do such integration by deforming the original path into a straight line and including some weights along with it. We get the functional form of such weights through conditions on the existence and structure of the canonical transformation. We apply the scheme to get the quasipotential algebraically for several one-dimensional nonequilibrium models as the diffusive and reaction–diffusion systems.
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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.
Offline Signature Verification System Using SVM Classifier with Image Pre-processing Steps and SURF Algorithm
Authors: Goon Li Wen , Kheng Eng Swee
Published: December 2021

A signature is a mark or name that represents the identity of the people and the Signature Verification System (SVS) is used to validate the identity of people. The signature verification system is mostly used for bank cheques, vouchers, intelligence agencies and others. There are two types of SVS which are online and offline signature verification systems. The paper deals with an offline signature verification system. The proposed system consists of four main stages, (i) image acquisition, (ii) image pre-processing, (iii) feature extraction and (iv) classification. The image pre-processing steps involved binarization, noise removal using Gaussian filter and image resizing and thinning. In the feature extraction stage, Bag-of-Features with the Speeded Up Robust Features (SURF) extractor was utilized. In the third stage, the Support Vector Machine (SVM) classifier is used. Lastly, the confusion matrix and the verification rate were used to evaluate the performance of the classifier. In this paper, we implement and compare the performance of the signature verification system without entering the user ID and the signature verification system entering the user ID. For the ratio of 75% and 25% of the training and testing, respectively, the average accuracy for the signature verification system without entering the user ID is 71.36%, whereas the average accuracy for the signature verification system entering the user ID is 79.55%.
Effect of Temperature on Phase Transformation of NiTi-based Shape Memory Alloy
Authors: Ma Xingxing , Zhou Yun , Chen Xia , Lu Gailing , Ji Jingjing , Zhao Shilei
Published: December 2021

For NiTi-based alloys, the phase transition temperature directly affects and limits their application fields. In order to apply the NiTi-based shape memory alloy in the wider field, it is necessary to control the phase transformation temperature. Studies have shown that the content of Ni element in the NiTi-based alloy and the precipitates of the alloy, such as NiTi2, Ni3Ti2 and Ni4Ti3, will affect the phase transition temperature of the alloy. At the same time, adding a third or even a fourth element to the NiTi binary alloy can also effectively regulate the phase transition temperature of NiTi-based alloy. We then pay attention to the problems confronting the current state of the NiTi-based shape memory alloy. We have confidence that the NiTi-based shape memory alloy have a bright future in the development and innovation of excellent properties.
Sodium-ion battery technology: Advanced anodes, cathodes and electrolytes
Authors: Lu Wanyu , Wang Zijie , Zhong Shuhang
Published: December 2021

The development of electric vehicles has made massive progress in recent years, and the battery part has been receiving constant attention. Although lithium-ion battery is a powerful energy storage technology contemporarily with great convenience in the field of electric vehicles and portable/stationary storage, the scantiness and increasing price of lithium have raised significant concerns about the battery’s developments; an alternative technology is needed to replace the expensive lithium-ion batteries at use. Therefore, the sodium-ion batteries (SIBs) were brought back to life. Sharing a similar mechanism as the lithium-ion batteries makes SIBs easier to understand and more effective in the research. In recent years, the developed materials for anode and cathode in the SIB have extensively promoted its advancements in increasing the energy density, power rate, and cyclability; multiple types of electrolytes, either in the form of aqueous, solid, or ions, offers safety and stability. Still, to rival the lithium-ion batteries, the SIB needs much more work to improve its performance, further expanding its application. Overall, the SIB has tremendous potential to be the future leading battery technology because of its abundance.
Slow Light Tuning in Annular Slotted Photonic Crystal Waveguide with Incoming Polymer
Authors: Zhu Kongtao , Yang Hongxue , Du Hui
Published: December 2021

An advanced post-processing scheme of reconfigurable dielectric infiltration into an annular slotted photonic crystal waveguide (ASPhCW) is proposed in this paper. Ionic liquids have had prominent effects in enhancing the optical properties of photonic crystals, especially in the aspect of tuning the transmission rate and velocity through optical materials. Using the two-dimensional plane wave expansion method, the flat band dispersion of the slow light is obtained and the tuning of the operating wavelength of the crystal could be realized by incoming polymer technology. The operating wavelength tuning range could be as large as 459.27nm and the group index could be tuned as high as 44.8 with a near zero group velocity dispersion. Using this method, a high group index equaling 45 with the bandwidth equaling 11.3nm and the normalized delay bandwidth product (NDBP) equaling 0.25 is realized. This incoming polymer technology provides an effective method of getting flat band of slow light flexibly and makes it possible to offer longer delay and low group velocity after fabrication.
Analysis of Infrared Radiation Intensity by Water-Mist Spraying in Ship Exhaust System
Authors: Sun Zhongke , Wang Zhen , Chen Zhongwei , Liu Zhihua , Liu Mo , Zhang Shuai
Published: December 2021

The infrared radiation intensity in 3~5μm of conventional ship exhaust system are so severe [1] that can be easily captured by detector. Therefore, it’s necessary to take measure like spraying water mist to decrease temperature of exhaust system in order to decrease infrared radiation intensity. In this paper, the calculation of infrared radiation intensity of conventional ship exhaust system with water-mist spraying will be given. The results show that the average and maximum infrared radiation intensity of the exhaust system can be reduced by 90.3% and 95.7% after water mist cooling.
1550nm Infrared Laser Heating NaYF4:Er3+ Nanoparticle In Isolated Pig Liver and Up-conversion Fluorescence Intensity Ratio Temperature Measurement
Authors: He Xinyu , Liao Songsong , Feng Zhuohong , Huang Wenqi , Huang Yantang
Published: December 2021

Hyperthermia is an important means of cancer treatment which is called “tumor green therapy”. The clinical heat therapy heating sources include ultrasound, microwave, alternating magnetic field, infrared laser. However, it is still difficult to accurately measure the temperature of tumor hyperthermia and the dose of hyperthermia. Here, NaYF4:Er3+ nanoparticles were injected into a small part of isolated pig liver, and heated it with 1550nm infrared laser. At the same time, the laser excited the NaYF4:Er3+ nanoparticles to generate up-conversion green fluorescence. The fluorescence intensity ratio was used to measure the temperature of the heating part in real time.
Human-posture-tracking sensor selection for motion recognition
Authors: Tan Chongwei
Published: December 2021

Very recently special attention has been paid to soft sensors for motion tracking. It is known from the work by Chen et al [2021, Comp Anim Virtual Worlds. 2021; e1993.] that a wearable motion tracking system was developed, in which five sensors were placed around the region of arm and shoulder. In this study, we explore the effect of different sensors on motion recognition and select the sensors with excellent differentiation for different movements.
Decentralized Path Planning for Multi-Objective Robot Swarm System
Authors: Wu Zhuokai
Published: December 2021

The multi-robot path planning aims to explore a set of non-colliding paths with the shortest sum of lengths for multiple robots. The most popular approach is to artificially decompose the map into discrete small grids before applying heuristic algorithms. To solve the path planning in continuous environments, we propose a decentralized two-stage algorithm to solve the path-planning problem, where the obstacle and inter-robot collisions are both considered. In the first stage, an obstacle- avoidance path-planning problem is mathematically developed by minimizing the travel length of each robot. Specifically, the obstacle-avoidance trajectories are generated by approximating the obstacles as convex-concave constraints. In the second stage, with the given trajectories, we formulate a quadratic programming (QP) problem for velocity control using the control barrier and Lyapunov function (CBF-CLF). In this way, the multi-robot collision avoidance as well as time efficiency are satisfied by adapting the velocities of robots. In sharp contrast to the conventional heuristic methods, path length, smoothness and safety are fully considered by mathematically formulating the optimization problems in continuous environments. Extensive experiments as well as computer simulations are conducted to validate the effectiveness of the proposed path-planning algorithm.
Research on Optical Fiber Sensor Signal Processing Technology Based on Variational Mode Decomposition and Singular Spectrum Analysis
Authors: Dong ZheHao , Ding YanHong , Zhang ZhiLi , Zhu HaiQiang
Published: December 2021

To better apply the phase-sensitive optical time-domain reflectometer (Φ-OTDR) in projects with complex environments, given the problem of the low signal-to-noise ratio of the Φ-OTDR signal, a variational modal decomposition (VMD) is proposed. Signal processing algorithm combined with singular spectrum analysis. First, the equalization optimizer (EO) optimizes the VMD. The VMD decomposes the preprocessed signal into a multi-layer eigenmode function (IMF), selects the IMF component according to the correlation coefficient, and after the SSA noise reduction process, the signal Reconstruction to realize the noise reduction processing of the Φ-OTDR signal. Through experiments, it is proved that the relative mean square error (RMSE) of the method in this paper is lower than that of EO-VMD, and the noise reduction performance is better.
Waterway control assembly for rope core drilling rig and its application method
Authors: Fan Dong , Lu Feifei
Published: December 2021

In the process of conventional rope core drilling, the connection and disassembly of waterway occupy a lot of auxiliary time, which seriously affects the drilling efficiency, and even causes drilling or safety accidents. The waterway control assembly and application method for the rope coring rig developed by the author’s team can control the waterway flow direction. It does not need to disassemble the water pipe frequently to control the raising speed of the inner pipe and avoid damaging the drilling tool too fast.Introduction.
Design and Experimental Study of Array Eddy Current Sensor for Internal Inspection of Natural Gas Pipeline
Authors: Zhou Qingxiang , Li Gangqing , Hou Kai , Cao Feng , Song Kai
Published: December 2021

Array eddy current detection (ECAT) technology has the advantages of fast scanning speed and high detection efficiency, and has a wide range of application prospects. However, the traditional array eddy current sensor has a poor coupling effect with the inner wall of the pipeline and is not suitable for in-pipe inspection. Based on the basic principles of ECAT, a flexible array eddy current sensor made by flexible printed circuit board (FPCB) technology is designed and developed, which can realize 360° detection of defects on the inner wall of natural gas pipelines. The paper uses ANSYS finite element software to establish a simulation model of multi-parameter effects, study the influence of sensor size parameters and detection parameters on eddy current signals, carry out detection experiments on blind hole defects in the inner wall of steel pipes, analyze the response characteristics of defect signals, and verify the feasibility of using the FPCB array eddy current sensor for internal inspection of natural gas pipeline.
Different improvement designs of conventional comparator
Authors: Fu Xinmiao , He Miao , Zhang Yuan
Published: December 2021

Comparators play a significant role in the semiconductor industry and have become indispensable in the design of ADC. The delay and energy consumption are two important indicators of the comparator. Many designs have been made to reduce the delay and energy consumption, such as separated gata-biasing cross-coupled transistors for a new latching stage, and pMOS is used to replace nMOS in comparators. This paper analyzes the working principle of the proposed comparators designed for different needs reported on different papers. It compares their simulation results about key data such as delay and energy consumption.
SELNN: Effective Crossover Features by Attention Mechanism and Logarithmic Conversion for CTR
Authors: Meng Lu , Wang Li
Published: December 2021

With the continuous increase of web resources, information overload is becoming more and more serious. Getting the information that meets the needs of a large amount of data has become an urgent problem. One of the popular studies in click-through rate prediction is to construct feature interactions to improve prediction accuracy. Traditional models with low-order interactions cannot adequately represent the intersection information, and deep models with undifferentiated feature intersections lack relevance. In this paper, we propose a model called SELNN, which improves the accuracy of click-through rate prediction through attention mechanism and logarithmic conversion. On the one hand, improving attention mechanisms learns the importance of each feature itself. On the other hand, combining logarithmic conversion structure with feedforward neural networks to learn different orders of feature interactions. The experimental results indicated that the AUC values of SELNN on the Criteo and Movielens-1M datasets were 81.46% and 87.36%, respectively. SELNN effectively improves the prediction accuracy and reduces the number of parameters and computational effort.
Feature extraction and recognition of rotating machinery fault noise based on convolutional neural networks
Authors: Xu Yongshao , Liu Bingzheng , Shang Haotian , Ge Yueqi
Published: December 2021

Rotating machines are common equipment in industrial production, which may cause failure for a long time. Because of its convenient use and non-destructive to itself, acoustic detection method is suitable for fault diagnosis of rotating machinery. The convolution neural network model is used to identify several typical rotating machine faults. The repeatability experiments and different training sets show that the method has good universality. A visual fault identification system is built, and the effect of the system is verified by experiments.