bluuebunny/crossref_metadata_2025 huggingface dataset:
Energy Scavenging from Triaxial Tactile Sensing and Peltier Effect Sensing System
Authors: B Muthuraj , S Sundramoorthi , V Vasudevan , J Jessica Angelyn , R Raveena
Published: November 2020

In the recent past there has been a significant increase in the research on vibration-based energy harvesting. Wherever mechanical movement exists, a lot of heat and vibration energy is wasted which could be used and converted as a supplement to the energy requirements. Towards this objective this project aims to provide a general theory that can be used for generating electricity from vibrating as well as heat body and store the acquired energy using advanced component called the super capacitor. A combination of Cantilever beam and MMA sensor is used for the sensing vibratory motion and the Peltier sensor is used for sensing the temperature of the source. The output obtained from the former source is converted into voltage using MMA technology and the latter is converted directly into the same. Boosted voltage is stored effectively with the help of super capacitor in primary storage device. The acquired voltage from the battery is 12V with respect to this project. For the AC load, the current produced are 300mA. The output would change with respect to the vibrating and the temperature sources like generators or automotive engines
Modeling and Design of a Controller for a Dehumidifier
Authors: R J Vijaya Saraswathi , S Sukambika , F Wilcy Theresa , M Ishwarya , T Srinithi
Published: November 2020

Many industries like pharmaceutics, plastics, food and confectionery, tobacco and cold storage, maintaining the humidity at the desired level is very important. The aim of this paper is to process the model and to design a controller for a dehumidifier to control the humidity at the desired set point. The air is humidified using a humidity chamber. This humid air which is the primary air is mixed with secondary air from the compressor and sent to the dehumidifier. The dehumidifier used here is a centrifugal separator. The humidity of the dehumidified air is measured using a sensor. The output signal of the sensor is compared to the set point. If the output measured exceeds the set point, accordingly the flow rate of the secondary air to the dehumidifier is varied until it reaches the desired set point .The model of the process is identified from the response of the process to the input signals. The controller is designed for the model obtained and the performance of the controller based on the time domain specification is compared.
Segmentation and Detection of Brain Tumor Using 2D and 3D Image Processing
Authors: S Aathithya , S Kavya , J Malavika , L R Aishwarya , M Jeevika
Published: November 2020

Brain tumor is a growth of abnormal cells in the brain that can be either benign or malignant. It tends to affect people irrespective of age group. Thus earlier detection and treatment of brain tumor is needed for quick recovery. Doctors use Magnetic Resonance Imaging (MRI) to identify the intensity of tumor. The MRI images are pre-processed and then Deep learning neural network and spearman algorithms are used to provide segmentation of images. The segmented images are grouped using Fuzzy clustering technique. The CNN and SVM Classifiers are used to classify and detect the size of tumor cell. On comparison, it was found that CNN classifiers are more accurate, sensitive and yields high performance as compared to SVM classifiers for both 2D and 3D images.
Investigation on the Sensing Properties of Organic Field Effect Transistors Using P3HT
Authors: Prasad Silpa S. , G Divya , S Sindhu , K Shreekrishna Kumar
Published: November 2020

The humidity sensing behavior and the properties of P3HT based thin film organic field effect transistor (OFET) has been reported. Layers with (Au)/P3HT/SiO2/(Au) are coated and OFET is fabricated. The XRD pattern of thin films are plotted which shows an orientation of (100) indicating its crystalline nature. The morphological studies report the presence of dreg like structures that can absorb water molecules from a humid environment which can be used in humidity sensing applications.
Automatic Threading and Metal Cutting in Smart Industries Using IoT
Authors: J Brindha , H Dharshan , P Maheshwar , SB Mugilan
Published: November 2020

The key objective of the project is to automate an industrial process of threading and metal cutting. The main objective of the project is that it uses IOT in industries with Artificial Intelligence to monitor and control the industrial processes thus increasing productivity and to reduce cost and man power. The system uses a microcontroller for processing all user commands and EEPROM chip to save data. Digital voltmeter, ammeter, wattmeter and IR cam etc., can be linked to the same IOT device without any additional circuits.
Analyzing Fake News Based on Machine Learning Algorithms
Authors: A B Pawar , M A Jawale , D N Kyatanavar
Published: November 2020

Usages of Natural Language Processing techniques in the field of detection of fake news is analyzed in this research paper. Fake news are misleading concepts spread by invalid resources can provide damages to human-life, society. To carry out this analysis work, dataset obtained from web resource OpenSources.co is used which is mainly part of Signal Media. The document frequency terms as TF-IDF of bi-grams used in correlation with PCFG (Probabilistic Context Free Grammar) on a set of 11,000 documents extracted as news articles. This set tested on classification algorithms namely SVM (Support Vector Machines), Stochastic Gradient Descent, Bounded Decision Trees, Gradient Boosting algorithm with Random Forests. In experimental analysis, found that combination of Stochastic Gradient Descent with TF-IDF of bi-grams gives an accuracy of 77.2% in detecting fake contents, which observes with PCFGs having slight recalling defects
A Novel Technique to Regenerate Sculpture Using Generative Adversarial Network
Authors: Jainulabudeen S.A.K. , Shalma H. , Shankar S. Gowri , Anuradha D. , Soniya K.
Published: November 2020

Dancing, music or any format of art has been a prominent thing from the past centuries. The many dynasties ruled the nation for centuries but every king encouraged the art one way or the other. The present day is just a minute part of the finest part of that era of art; the art of any form had been lost in the shadows to redeem the lost art we are going to use the latest technology like machine learning and artificial intelligence. The art lovers of the present age can seek the knowledge of lost art through this modern day technology. The retrieval of this art can only be done if there is a possibility to learn their language which helps in reading the old sculptures or the paintings on the walls of the ancient architecture. Now using the present day technology we are going to recoup that lost art through reading the walls of those structures where the art has been hidden for centuries. So at present we do not allow the art to continue to fall into shadow and extinguish later on, thus in this paper we present a DC-GAN model which has been created to inherit all the artistic skills of our ancestors by training from the key images of art designed as sculptures by our forefathers.
Intelligent Systems to Predict and Diagnose Benign and Malignant Skin Lesions
Authors: C Geetha , Darapaneni Aparna , Manaswini Lakkamaneni Chandana
Published: November 2020

The main purpose of Intelligent systems is to reason, calculate and perceive relationships and analogies. These Intelligent systems learn from experience and retrieve information from memory and provide the same to the users based onss their requirement. Currently, there is a trend for the use of intelligent systems in health informatics. The main objective of this is to improve quality, efficiency and availability of health services to people round the clock at a lower cost. Intelligent systems aim to predict and diagnose the skin cancer and abrasions based on their images. It understands the cause and thereby analyses the image based on some of the image processing techniques like patterns, anisotropic diffusion, image editing, independent component analysis and image restoration. We make use of image processing software which captures the image and then converts it to digital form and perform the required manipulations.
WSN Based on Bio-Inspired Algorithm in Cluster Head Formation
Authors: M S Vinmathi , M S Josephine , V Jeyabalaraja
Published: November 2020

A sort of inclusion improvement technique dependent on bio-inspired algorithm was implemented so as to fathom the irrationality and low system inclusion of sensor hub in WSN at the irregular dispersion. Right off the bat, the ebb and flow investigate status of WSN inclusion was broke down, the hub inclusion and territorial inclusion in WSN on the premise were examined, the comparing scientific model was set up, the bio-enlivened calculation was taken to tackle the built up numerical model, and the WSN inclusion advancement program dependent on the bio-roused was gotten. At last, MATLAB was utilized for the recreation analyses, and the reproduction results demonstrated that the presentation of bio-motivated calculation improved the hub inclusion in WSN viably; the inclusion territory was huger at a similar measure of hubs. In addition, the calculation can get the ideal arrangement in the worldwide extension, and arrive at the better system inclusion advancement impact with less sensor hubs, and the quantity of cycles was diminished altogether.
HCI Based Input Device for Differently Abled
Authors: J Brammi , R Dhivya , T Padmavathy , R Anitha
Published: November 2020

Tremendous advancements in the technology has lead to the monumental growth of various branches of computing such as Computer Vision and Human-Computer Interaction (HCI). Computer’s input has data about different properties of users, objects or places. For instance, mouse and keyboard works by the movement performed by the end user’s hands. These approaches are not appropriate for differently abled people. Away to create an application which replaces the input devices such as mouse and keyboard by using face of the user is proposed. This paper introduces how head motion of the user can be used to control the mouse cursor and how gaze tracking can be used to control the keyboard. A face detecting system precisely records the motion parameters from video at real-time using a typical webcam. While the pace reduces while using the virtual mouse and keyboard, the performance of the system is intact for differently abled people whose only means of communication are the head movements and gaze.
Investigation on Mechanical Properties of Graphene Reinforced Jute Fibre Reinforced Polymer Composites
Authors: G Rathinasabapathi , A Krishnamoorthy
Published: November 2020

In this study, the impact of adding Graphene Nano Platelets on the mechanical properties of Jute Fiber reinforced Polymer (JFRP) composites has been investigated. JFRP composite specimens were fabricated with varying number of layers (3 Layers, 4 Layers, and 5 Layers) and different orientations (30 degree, 45 degree, 60 degree) reinforced with 2% weight graphene nano platelet. Ultrasonicator is used for dispersion of graphene nano platelets into the epoxy matrix. Mechanical Tests namely Tensile test, flexural test and impact test is carried out to study the behavior of JFRP with different layers and orientations. The results proved that the use of 2% weight of Graphene Nano platelets led an enhancement in fatigue strength and impact strength. Also it is found that 3 layered with 30 degree orientation composite specimens had better mechanical properties compared to 4 layered and 5 layered composite specimens.
ANFIS Controller Based Speed Control of High-Speed BLDC Motor Drive
Authors: Muthamizhan T. , Silas Stephen D. , Sivakumar A.
Published: November 2020

The paper aims to define the speed control of Brushless DC Motor (BLDC) drive using an Adaptive Neuro Fuzzy Interface System (ANFIS) controller. ANFIS controller-based switching scheme reduces the power quality issues present in the system by minimizing the Total Harmonic Distortion (THD). Incremental conductance algorithm-based control technique for the Maximum Power Point Tracking (MPPT) in variable solar irradiation conditions for photovoltaic (PV) system is proposed. INC algorithm are used to operate the photovoltaic panels at maximum power, by generating PWM pulse to control the flyback converters in differential power processing mode. BLDC motor drive is electronically commutated by means of switching logical pulses from the rotor position sensor using PI controllers. The simulation shows the significance and robustness of BLDC drive and the results offered illustrates the intended control is effective, with fast responseandminimum settling times.
Design of Compact BranchlineBalun
Authors: J Indhumathi , S Maheswari
Published: November 2020

This paper present the compact branch line balun to operate at the frequency range of 2.4GHz. The compact branchlinebalun is designed using the substrate material with the dielectric constant of FR4 material. The proposed balun is designed using different transmission lines. Thus the balun should achieves -3dB power division and 1800 phase differences between the outputs. The main objective of this design focuses on size reduction. To reduce the size, A balun is realized using the equivalent T-shape structure. After the reduction techniques the implemented size of the balun is 29.41x44.32 mm2 achieves 35% of size reduction. Thus the measured S11 are -23 dB and the S21,S31 remains -3dB and provide 1790 phase difference between the outputs at the frequency of 2.4GHz.
Investigation of Meandered Antenna for WLAN Application
Authors: S B Nivetha , B Bhuvaneswari
Published: November 2020

In this paper patch antenna using coplanar waveguide structure is designed. The dimension of the antenna is 12x22mm. The substrate material used is FR4 with thickness of 1.6mm. The dual band frequency is obtained by creating slot in the patch. Four slot is created in the patch. The frequency obtained for proposeddesign is 2.5 and 5.00GHz. The gain obtained for proposed antenna is 2.8dBi. The return loss obtained for proposed design is -35db at 5GHz and -34dB at 2.5GHz frequency. The meander antenna with two arm is designed using normal ground structure. Single band resonance is obtained for meander antenna with two arm at the frequency of 5.7GHz. The coplanar waveguide structure is chosen for dual band resonance and reduction in size. The designed antenna is used for WLAN application.
Probability Detection for Heterogeneous Networks Using FODPSO with ACO Optimization in Tunnel Based High Speed Trains
Authors: S Priyanka , S Leones Sherwin Vimalraj , J Lydia
Published: November 2020

Wireless communication on train is said to efficient when it has a good throughput and low latency. But the efficiency is reduced during underground tunnels and high speed trains. Heterogeneous network is said to be a network which is used to connect different kinds of network and hence it is said to be a efficient network. At times, it is found to be difficult to access the network. This problem can be overcome by using the optimization techniques such as FODPSO and ACO algorithm. It is proposed for optimizing the heterogeneous network by comparing different networks such as LTE, WiFi and WiMax. For efficient communication, the quality of services is important which should be maintained entire transmission.
A Review on Video Tracking for Multiple Objects in Neural Network
Authors: S Uma , S Umamaheswari
Published: November 2020

Video Multiple Object Detection and Tracking (VMODT) is the current area of research in computer vision which has increased due to the attention of commercial and academic potential it has offered. Multiple Object Tracking (MOT) shares all challenges to be handled such that long time occluded, fully occluded in small object, frequent occlusion in crowd and severely blurred in fast motion in video etc., In this paper, a review on VMODT with various models,approaches and tracking algorithms is carried out. Neural Networks are developed to provide optimal solution in monitoring the regularity, re-identification, predicting the activity and control action of objects in surveillance application. This review work will be helpful for understanding the start-of-art in VMODT, finding the limitation in current algorithm. However, hybriding the different tracking methods will improve the performance and facilitate new approaches in deep learning.
A Study on Massive Mimo 5G Challenges
Authors: A Kanchana Devi , B Bhuvaneswari
Published: November 2020

Massive MIMO is a advance of MIMO technology. M-MIMO use hundreds of Base station (BS) to simultaneously serve multiple users. It combines with millimeter wave (mmWave) to provide huge spectral efficient, high reliability and high energy efficiency. Massive MIMO gives huge antennas, high signal strength, less noise reduction and also using better channel model. This paper discusses the detail description of fifth generation (5G) network architecture and to improve massive MIMO in existing technology.
Design of Compact High Gain Multilayer Stacked Patch Antenna
Authors: NithyaDorairajan  , Perumal Chitra M. , PT Padmavathi , R Ranjanadevi , VJ BhagavathShruthi
Published: November 2020

In this paper a compact multilayer stacked patch antenna with high gain is proposed. The structure is composed of stacked patches with U slots and shorting pins. The proposed antenna is capable for resonating at the center frequency of 2.25 GHz. The performance of the antenna is characterized by the simulated result of bandwidth, gain and reflection coefficient. The antenna has reflection coefficient of less than -10 dB with a maximum gain of 7.07 dBi. The proposed antenna has bandwidth of nearly 400MHz and has less size with an overall height of 10.3 mm. The designed frequency range occupies S band which is used for various applications like weather radar, surface ship radar, Bluetooth and ZigBee.
Survey on TYDER Based Algorithm for Radio Resource Allocation in 5G Heterogeneous Scenarios
Authors: A Premi , S Rajakumar
Published: November 2020

The rapid growth of machine-to-machine communications in cellular networks poses the challenge of meeting the various Quality-of-Service requirements of massive number of machine to machine communications devices with limited radio resources. In this study, we discuss the minimum resource allocation problem for M2M communications through 5G and beyond the cellular networks. Then, in 5G mobile networks we propose a TYDER based algorithm for allocation the radio resource. The next-generation network environment, associated with heterogeneous performance, is expected to include the networks of diverse types. This paper introduces the network Traffic Type-based Differentiated Reputation (TYDER) solution, which differentiates the data delivery process according to its type.This approach however requires creativity in the reduction of hardware and cost decrease in the plan of little cell base station.
Optical Wireless Communication: A Survey of Recent Advances, Applications and Challenges
Authors: R Nandhini Devi , S Leones Sherwin Vimalraj , J Lydia
Published: November 2020

This paper proposes the Optical Wireless Communication (OWC) for different Application, Advances and Challenges as high data rate multimedia services are evolving continuously and exponentially increasing the demand for wireless capacity 5G generation and upgrading Technologies. These are used to bypass the RF transmission band, which is inadequate to meet the demand for future high data rate 5G services. It offers services for both indoor and outdoor application as well as in the submerged area with contact distances ranging from nm to more than 10,000 km. This paper provides an overview and performance analysis of technical communication involving Visible light, Line of sight underwater, free space, optical communication, optical camera communication and light detection for all surveys of keys understanding technologies (OWCs) and presents them as aspects of criteria such as spectrum use, application, design, classification advances and challenges.
Survey on Mobile Edge Computing for Internet of Things System
Authors: K Keerthivasan , S Shibu
Published: November 2020

IOT is the latest advanced technology. To help the customer value, it is the backbone of both service sector and product area businesses. In 5G technology, internet of things is a main role to play in future. It is used to support the intelligent, big data analytics and lots of application such as health care, smart cities and industrial. Advancement of 5G technology will recognize MECfor future of cloud computing. MEC is used to provide multiple application such as service providers, mobile subscribers, enterprises and other vertical segments. MEC technology provides low latency and quality of services [QOS].It distributes the network uniformly with strong mobility supports. In this paper a detailed review of MEC technology for IoT application is discussed.
Parallelizing Bidirectional A* Algorithm
Authors: Sharma Sumit , Srijan Shashwat , J V Vidhya
Published: November 2020

Dijkstra’s algorithm is one of the simplest shortest path finding algorithm. A star(A*) algorithm is a variation of the shortest path first Dijkstra’s algorithm and is very commonly used in games using heuristics. The idea behind A* is to assign weight to each open node and then use a heuristic to calculate the cost from start to finish. A* uses heuristics and cost functions to find the most appropriate path in games and robotics. Games are needed to be fast and so we can have tradeoffs between speed and accuracy. So instead of accuracy we focus more on speed which is not needed in some of the situations like autonomous vehicles and simulation games. So, the A* algorithm may underestimate the costs but will never overestimate it. Bidirectional A*reduces the computation by calculating the shortest path from the source as well as the destination. A solution may be the General-Purpose Graphics Processing Units. It can be used to enhance the processing and execution speed of Bidirectional A* algorithm by using parallel processing and multiple threads. GPU based path finding may be approximately 45 times as fast as CPU pathfinding mechanism.
Smart Forest Fire Identification and Notification System Using Iot Based Wireless Sensor Networks
Authors: M Santhiya , M Siva Rathnam , T Radha Krishnan , S Nishanth
Published: November 2020

Wildlife and wildlife authorities face the problem of animal migration from woodland to residential areas in the present environment. Natural calamities triggered by nature, wind and dry undergrowth will destroy acres of land and consume everything in their way that causes significant harm to both natural and human capital. The proposed system to design an IoT-based system that will be able to detect the fire as soon as possible before the fire spreads over the wide area and prevent poaching. Raspberry interfacing with a temperature sensor, a smoke sensor, webcam and a buzzer. GSM gateway is used to conduct this project to provide the user with the final SMS via given number in simulation program. The temperature sensor used to indicate high and low temperatures, the PIR sensor designed to track human activity on the LCD display, the flame sensor used to signify the intensity of flames and the forest fire observed on the LCD display. Once large, image processing is used to determine the accuracy of the fire rate. Wireless Sensor Network (WSN) for data processing to be used as input data in our control system. WSN comprising of temperature sensor system and GPS module to sense forest fire by measuring the level and sending its position to the server utilizing GSM communication contact and GPS functionality. Raspberry Pi cluster, a complicated computation is broken into multiple parts using MPI, and each component runs on separate raspberry pi device. Such sections will be analysed in sequence and then MPI must merge the output and turn it over to the user, essentially they operate as individual units (but in tandem and together) to produce very quick results.
Early Detection of Breast Cancer Using Ensemble Machine Learning Algorithm
Authors: P S Sainikhileaswar , G Parthasarathy
Published: November 2020

As showed by World Health Organization (WHO), Breast cancer growth is the most incessant disease among ladies, 627,000 ladies died due to breast cancer in the year 2018, which implies about 15 present of all cancer deaths among ladies. In order to improve breast cancer results and endurance, early recognition is significant. For detecting breast cancer growth early for the most part AI techniques are used. Right now proposed flexible outfit utilizing ensemble procedure for examining breast cancer using Wisconsin Breast Cancer (WBC) dataset. The purpose of the introduced paper is to consider and explain how different classification algorithms works on our dataset and to identify best algorithm for outfit models, for example, Random Forest Voting Ensemble and XGBoost work and how ensemble systems make the performance of the predictive models better by improving their precision and accuracy.
Two-scale homogenization of abstract linear time-dependent PDEs
Authors: Neukamm Stefan , Varga Mario , Waurick Marcus
Published: November 2020

Many time-dependent linear partial differential equations of mathematical physics and continuum mechanics can be phrased in the form of an abstract evolutionary system defined on a Hilbert space. In this paper we discuss a general framework for homogenization (periodic and stochastic) of such systems. The method combines a unified Hilbert space approach to evolutionary systems with an operator theoretic reformulation of the well-established periodic unfolding method in homogenization. Regarding the latter, we introduce a well-structured family of unitary operators on a Hilbert space that allows to describe and analyze differential operators with rapidly oscillating (possibly random) coefficients. We illustrate the approach by establishing periodic and stochastic homogenization results for elliptic partial differential equations, Maxwell’s equations, and the wave equation.
Expression analysis of CD24 and CD44 transcripts in Iranian breast cancer patients
Authors: Liaghati Pegah , Momeni Parto , Esfandi Farbod , Kholghi Oskooei Vahid , Sattari Ali , Ghafouri-Fard Soudeh , Taheri Mohammad
Published: November 2020

BACKGROUND: The importance of cancer stem cells (CSCs) in initiation and progression of breast cancer has been well established. This population of cells is characterized by high expression of CD44 and low expression of CD24. OBJECTIVE: However, the relative abundance of CD24 and CD44 transcripts in breast cancer tissues and adjacent non-cancerous tissues (ANCTs) has not been quantified yet. METHODS: In the present investigation, we assessed expression of CD24 and CD44 at transcript level in breast cancer tissues and ANCTs in association with clinical determinants of patients’ outcome and parameters that predict response to therapeutic options. RESULTS: There was no significant difference in expression of CD24 and CD44 in breast cancer tissues compared with ANCTs (Expression ratios: 1.03 and 0.84, P values: 0.92 and 0.61, respectively). However, CD44 expression was associated with tumor size in a way this gene was up-regulated in all of small sized (≤2 cm) tumors compared with the corresponding ANCTs (P value = 0.04). Besides, CD44 expression was significantly higher in tumors with extracapsular nodal extension compared with those without extension (P = 0.04). Expression of CD24 was higher in grade 3 tumors compared with grade 2 tumors (P = 0.04). CONCLUSION: Expression levels of CD24 and CD44 were correlated with each other in ANCTs but not in tumoral tissues. The current study shows another aspect of CSC markers in the development of breast cancer.
Structure Optimization of Magnetic Levitation Motor Rotor
Authors: Yao Shuyan , Wu Bo , Liu Qiang , Xu Kang
Published: November 2020

With the development of science and technology, magnetic suspension products are gradually favored by people for the characteristics of no friction and wear, no lubrication and long life. With the increasing consumption of fossil energy, magnetic levitation green energy-saving equipment is gradually studied by researchers. Taking magnetic suspension flywheel (MSMFW) as typical representative, magnetic suspension products in aerospace field have been greatly developed. As the core component of magnetic suspension flywheel, magnetic levitation motor has been widely studied. To obtain the better performance of magnetic levitation motor when it was used in magnetic suspended momentum flywheel, the motor rotor system structure was optimized in this paper. Firstly, the rotor system moment of inertia was calculated and analyzed, and the optimum ratio of polar moment of inertia to equatorial moment of inertia was obtained. Then the basic structure of motor rotor was designed on the basis of the rotor system dynamic analysis. Thirdly, based on the flywheel motor system model, the ANSYS Parametric Design Language (APDL) file was established, and it was applied to optimization software ISIGHT to complete the optimization. In the optimization process, the design variables boundary conditions were given, and the Sequence Quadratic Programming method was used for maintaining the optimization process and the optimization convergence results was obtained. The magnetic flux density as the optimization objective is increased from 0.393 T to 0.53 T through the optimization, which is 34.9% larger than before. It is of great significance for the magnetic levitation motor design, and the engineering application of magnetic levitation motor based on optimization results will be done in the future.
Investigation of a Method for EEG Signal De-Noising Based on the DIVA Model
Authors: Zhang Shaobai , Jiao Lihong , Zhou Ningning
Published: November 2020

The DIVA (Directions Into Velocities of Articulators) model is an adaptive neural network model that is used to control the movement of the analog vocal tract to generate words, syllables, or phonemes. The input signal to the DIVA model is the EEG (electroencephalogram) signal acquired from the human brain. However, due to the influence of power frequency interference and other forms of noise, the input signal can be non-stationary and can also contain a variety of multi-form waveforms in its instantaneous structure. Input of such a signal into the DIVA model affects normal speech processing. Therefore, based on the concept of sparse decomposition, this paper applies and improves an adaptive sparse decomposition model for feature extraction of the general EEG signal structure and then uses the Matching Pursuit algorithm to compute the optimal atom. The original EEG signal can then be represented by atoms in a complete atomic library. This model removes noise from the EEG signal resulting in a better signal than the wavelet transform method. Finally, applies the EEG signal de-noised by this model to DIAV model. Simulation results show that the method improves phonetic pronunciation greatly.
A Statistical Analysis of the Social Status of Chinese Women: Data Mining Method Based on MapReduce
Authors: Liu Xiangdong , Yang Mingzhu , Luo Chengshuai
Published: November 2020

By studying the influencing indicators of women’s social status, we perform an ordered Logit regression analysis on the data of the China Comprehensive Social Survey in 2012, 2013 and 2015, and then select the assessment of self-social status in the female sample as the dependent variable. Using the impact indicators as independent variables to explore the impact of each variable on women’s social status. At the same time, applying k-means clustering analysis based on MapReduce to mine the relationship between employment and education level between different genders. We find out the fact that women have a high level of education does not necessarily result in good employment treatment. Gender discrimination in the Chinese labor market is also persistent.
News-Based Research on Forecast of International Natural Gas Price Trend
Authors: Li Tianxiang , Han Xiaosong , Wang Aoqing , Li Hui , Liu Guosheng , Pei Ying
Published: November 2020

In this paper, we build a deep learning network to predict the trends of natural gas prices. Given a time series, for each day, the gas price trend is classified as “up” and “down” according to the price compared to the last day. Meanwhile, we collect news articles as experimental materials from some natural gas related websites. Every article was then embedded into vectors by word2vec, weighted with its sentiment score, and labeled with corresponding day’s price trend. A CNN and LSTM fused network was then trained to predict price trend by these news vectors. Finally, the model’s predictive accuracy reached 62.3%, which outperformed most of other traditional classifiers.
Neighborhood Based Multi-Granularity Attribute Reduction: An Acceleration Approach
Authors: Song Jingjing , Dou Huili , Rao Xiansheng , Luo Xiaojing , Yan Xuan
Published: November 2020

As a feature selection technique in rough set theory, attribute reduction has been extensively explored from various viewpoints especially the aspect of granularity, and multi-granularity attribute reduction has attracted much attention. Nevertheless, it should be pointed out that multiple granularities require to be considered simultaneously to evaluate the significance of candidate attribute in the corresponding process of computing reduct, which may result in high elapsed time of searching reduct. To alleviate such a problem, an acceleration strategy for neighborhood based multi-granularity attribute reduction is proposed in this paper, which aims to improve the computational efficiency of searching reduct. Our proposed approach is actually realized through the positive approximation mechanism, and the processes of searching qualified attributes are executed through evaluating candidate attributes over the gradually reduced sample space rather than all samples. The experimental results over 12 UCI data sets demonstrate that the acceleration strategy can provide superior performance to the naive approach of deriving multi-granularity reduct in the elapsed time of computing reduct without generating different reducts.
The Overview of Genetic Algorithm with Tree Chromosome Structure to Identify Functions
Authors: Matayoshi Mitsukuni
Published: November 2020

This paper is a collection of previous studies for function identification by simple genetic algorithm (GA) [1] with tree chromosome structure which has been proposed in [2]-[7], and gives the details more than survey paper. This paper also aims to introduce the studies which were written in Japanese. In this paper, there are five main points. First, a tree chromosome structure, which is the core idea of the studies, is introduced. The tree chromosome structure makes GA succeed in function identification called symbolic regression. Second, the proposed GA with tree chromosome structure succeeded in identifying the target functions from the observed data are shown indeed. The target functions are algebraic functions, primary transcendental functions, time series functions including chaos function, and user-defined one-variable functions. Third, to find function represented with some parentheses, a hierarchical tree chromosome structure is introduced. Forth, some local search methods to aim at the improvement for identification success rate and shortening identification time are introduced. In the end of this paper, the proposed tree and hierarchical tree chromosome structure can be adapted for identifying Boolean functions are laid out.
The Design of ERP Intelligent Sales Management System
Authors: Liu Jianghui , Chen Qiuyi , Qiu Yuexing
Published: November 2020

With the popularization of informatization, most companies have their own information management systems. However, faced with massive amounts of data, most companies cannot integrate and utilize its potential value. When traditional companies make sales forecasts, they usually purchase data completion, connect multiple data source channels, and then judge the future sales situation perceptually. This lack of data accumulation and analysis, and it is impossible to display the intrinsic value of the massive data in the system. Some companies will also build professional data analysis teams or seek help from third-party companies. But this will cause high expenses and greatly reduce sales expenses. This study combines artificial intelligence technology with ERP sales management system. We apply artificial intelligence, machine learning, cloud computing to the design and construction of intelligent ERP sales management system. It solves the core problems of enterprise product sales through the deep learning function of the sales system. It may predict enterprise sales and rationally allocate enterprise resources, increase product sales effectively, and help enterprises build effective modern management systems.
The Efficiency of Employment Relationship: Through Data Envelopment Analysis
Authors: Wang Kunyi , Liu Ping , Liu Yujiang
Published: November 2020

Employment relationship (ER) is a social exchange relationship in nature with uncertainty and incongruence during the exchange process. Previous studies has been stuck on regression-based methods, examining and exploring related issue by studying the exchanges of both parties and even more stakeholders, but the nature of the exchange process itself is ignored. This study jumps out of the causality study represented by the regression analysis method, and uses the FCE that reflects the essence of object better and the Data Envelopment Analysis (DEA) to measure the efficiency of the exchange process, which can help enterprises to improve the evaluation of ER. DEA is used to evaluate the technical effectiveness of decision units (DMUs) with the same type of inputs and outputs. The result suggests that the phenomenon of inefficient exchange is still widespread. We make the importance ranking of selected inducement and find that labors in China attach importance to the correctness of management process rather than the additional benefits. For the first time, the quantitative efficiency value replaces the simple description “uncertainty” in research of the exchange process. Meanwhile, the framework independently measures the input of enterprises and the output of employees which has high adaptability. It can adjust, modify and accurately evaluate the exchange efficiency of two parties according to the actual exchange situation.
Reward-Free Reinforcement Learning Algorithm Using Prediction Network
Authors: Yu Zhen , Feng Yimin , Liu Lijun
Published: November 2020

In general reinforcement learning tasks, the formulation of reward functions is a very important step in reinforcement learning. The reward function is not easy to formulate in a large number of systems. The network training effect is sensitive to the reward function, and different reward value functions will get different results. For a class of systems that meet specific conditions, the traditional reinforcement learning method is improved. A state quantity function is designed to replace the reward function, which is more efficient than the traditional reward function. At the same time, the predictive network link is designed so that the network can learn the value of the general state by using the special state. The overall structure of the network will be improved based on the Deep Deterministic Policy Gradient (DDPG) algorithm. Finally, the algorithm was successfully applied in the environment of FrozenLake, and achieved good performance. The experiment proves the effectiveness of the algorithm and realizes rewardless reinforcement learning in a class of systems.
Visualization of the Artist Relations Using Twitter User Profiles
Authors: Yoshida Minoru , Kohno Shogo , Matsumoto Kazuyuki , Kita Kenji
Published: November 2020

We propose a new music artist recommendation algorithm using Twitter profile texts. Today, music recommendation is provided in many music streaming services. In this paper, we propose a new recommendation algorithm for this music recommendation task. Our idea is to use Twitter profile texts to find appropriate artist names to recommend. We obtained word embedding vectors for each artist name by applying word2vec algorithm to the corpus obtained by collecting such user profile texts, resulting in vectors that reflect artist co-occurrence in the profile texts.
Hardware Detection Method of Transmission Line Patrol Inspection Image Based on Improved YOLOV4 Model
Authors: Wang Ning , Zhao Hanghang , Zheng Wulue , Wang Chaoshuo
Published: November 2020

In order to solve the problem of intelligent hardware detection in aerial images, a hardware target detection method based on improved YOLOV4 model is proposed. In order to solve the problems of dense hardware and occlusion in aerial images, the improved network based on channel and spatial hybrid attention mechanism can further improve the detection effect of dense occlusion hardware and reduce image false detection and missed detection. In order to solve the problem that there is a great error in the position of the detection frame caused by the interference between the hardware and the hardware and between the hardware and the background, the prior frame is optimized by K-means++, and it is determined that the anchors generated by K=12 is the best, and the detection boxes are more suitable for the target. The experimental results show that the proposed method solves the problems of missing detection, misdetection and inaccurate detection frame to some extent, in which the mAP (mean Average Precision) value of the performance index is increased from 65.03% to 70.72%. The research can lay a good foundation for further state detection and fault diagnosis of typical hardware.
The Relation of Career Adaptability to Values Realization Degree and Organizational Citizenship Behavior
Authors: Zhu Qingsong , Tan Ruiting , Wang Ping
Published: November 2020

The sudden outbreak of the pandemic COVID-19 inevitably has a great impact on economic and social development. Therefore, the innovation-driven value becomes more and more prominent. Through literature review, it is not difficult to find that values have gradually become an important reference standard for organizations to select talents for their teams, as well as an important reference factor for studying organizational citizenship behavior. In order to explore the relationship between values realization degree and organizational citizenship behavior, this investigation based on the social interaction theory was conducting using a sample of enterprise staff (N=358). In this paper, LISRELV9.2 and SPSS21.0 were used to analyze the sample data, including descriptive statistical analysis, common variance deviation test, reliability and validity test, one-way ANOVA, correlation analysis, regression analysis, and validation of mediating effects. The results showed that values realization degree positively predicted organizational citizenship behavior, and job satisfaction played an intermediary role in the relationship between values realization degree and organizational citizenship behavior. Besides, there were some differences between the relation that work values realization degree and organizational citizenship behavior acted on organizational citizenship behavior.
Monitoring the Development Quality of College Students Based on Knowledge Graph
Authors: Wu Aiyan , Zhang Yongmei
Published: November 2020

With the rapid development of higher education, how to innovate management means and ensure the quality of education is an urgent problem faced by higher education management. The paper focuses on a large number of data that include students’ enrollment performance, family status, lessons performance, volunteer service, competition, rewards and punishments, social practice, etc. And it puts forward an education quality monitoring means that uses knowledge graph to reveal students’ development and can guide the development of students according to the needs of local talents. The means includes three parts: the current situation of students’ development, the early warning of development and the guidance of development. Finally, taking the postgraduate education in School of Information Science and Technology, North China University of Technology as an example, it demonstrates the feasibility and effectiveness of the means.
All About Animals
Authors: Franklin Cindy , Revels Trisha , Summerall Debra , Glauer Deborah J.
Published: November 2020

Produced by the Department of Family, Youth and Community Sciences in cooperation with the Florida 4-H Youth Development Program, University of Florida Cooperative Extension, Institute of Food and Agricultural Sciences, June, 1997; Reviewed June 2002.
The World of Animals
Authors: Harrelson Joanna , Glauer Deborah J.
Published: November 2020

Produced by the Florida 4-H Youth Developmemt Program, University of Florida Cooperative Extension, Institute of Food and Agricultural Sciences, June, 1996; reviewed June 2002.
Fun with Clothes Leaders Guide
Authors: Jordan Joy Cantrell , Hackler R. Nadine , Pourciau Johannah
Published: November 2020

4-H FUN with CLOTHES is the first level of the 4-H Clothing and Textiles Curricula that is designed to help 5-8 yearold children understand the basics of Clothing and Textiles.
Clothing Capers Leaders Guide
Authors: Jordan Joy Cantrell , Hackler R. Nadine , Pourciau Johannah
Published: November 2020

Produced by the Department of 4-H and Other Youth Programs and Department of Home Economics, University of Florida Cooperative Extension, Institute of Food and Agricultural Sciences, June, 1996; reviewed June 2002.
Fun with Clothes Project Book
Authors: Armstrong Shona , Pourciau Johannah , Jordan Joy Cantrell , Hackler R. Nadine
Published: November 2020

This document is 4HCCM10 of the Florida 4-H Youth Development Program, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Published in 1994; Reviewed June 2002.
Clothing Capers Workbook
Authors: Jordan Joy Cantrell , Hackler R. Nadine
Published: November 2020

This information was published May 1996, by the Florida Cooperative Extension Service. Reprinted March1998; reviewed June 2002.
4-H Energy Encounters Leader's Guide
Authors: Barber Linda , Simmons Marilyn , Miller Craig R.
Published: November 2020

4-H ENERGY ENCOUNTERS was developed through a team effort of the Department of 4-H and Other YouthPrograms, Institute of Food and Agricultural Sciences, University of Florida. Printed on April, 1993 and May, 1996; reviewed in 2002.
Soil, Water, and Land Use: I. Understanding Pesticide Interaction
Authors: Schipper Angela , Edgell Alison , Hornsby Art , Jessup Ron
Published: November 2020

Produced jointly by the Soil and Water Science Department and the 4-H Youth Development Program, Florida Cooperative Extension Service, Institute of Food and AgriculturalSciences. University of Florida, Revised March 1997; reviewed June 2002.

https://edis.ifas.ufl.edu/4h134
Food, Fun and Fitness Leader's Guide
Authors: Cook Linda , Jordan Joy C. , Leath Henry
Published: November 2020

Produced by the Department of Family, Youth and Community Sciences and the Florida 4-H Youth Development Program, Institute of Food and Agricultural Sciences, University of Florida Cooperative Extension, May 1996. Revised March 1997; reviewed June, 2002.

https://edis.ifas.ufl.edu/4h149
Food Fundamentals Workbook
Authors: Jordan Joy C. , Cook Linda D.
Published: November 2020

4-H FOOD FUNdamentals will introduce you to the fundamentals of health, nutrition and fitness. There are nine fundamental topics to help you score with PYRAMID POWER! This information was published October 1994, as 4HFNM12, Florida Cooperative Extension Service. Revised March 1999. Reviewed June 2002. Printed October 2002.

https://edis.ifas.ufl.edu/4h154
Making Posters
Authors: Hermance Gary , Johnson Nancy
Published: November 2020

This document is 4HGCM60 of the Florida 4-H Youth Development Program, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Printed, October 1989; Reviewed June 2002.