bluuebunny/crossref_metadata_2025_split huggingface dataset:
Outlier Prediction and Training Set Modification to Reduce Catastrophic Outlier Redshift Estimates in Large-scale Surveys
Authors: Wyatt M. , Singal J. 
Published: April 2021

Abstract
We present results of using individual galaxies’ probability distribution over redshift as a method of identifying potential catastrophic outliers in empirical photometric redshift estimation. In the course of developing this approach we develop a method of modification of the redshift distribution of training sets to improve both the baseline accuracy of high redshift (z > 1.5) estimation as well as catastrophic outlier mitigation. We demonstrate these using two real test data sets and one simulated test data set spanning a wide redshift range (0 < z < 4). Results presented here inform an example “prescription” that can be applied as a realistic photometric redshift estimation scenario for a hypothetical large-scale survey. We find that with appropriate optimization, we can identify a significant percentage (>30%) of catastrophic outlier galaxies while simultaneously incorrectly flagging only a small percentage (<7% and in many cases <3%) of non-outlier galaxies as catastrophic outliers. We find also that our training set redshift distribution modification results in a significant (>10) percentage point decrease of outlier galaxies for z > 1.5 with only a small (<3) percentage point increase of outlier galaxies for z < 1.5 compared to the unmodified training set. In addition, we find that this modification can in some cases cause a significant (∼20) percentage point decrease of galaxies which are non-outliers but which have been incorrectly identified as outliers, while in other cases cause only a small (<1) increase in this metric.
Biases from Non-simultaneous Regression with Correlated Covariates: A Case Study from Supernova Cosmology
Authors: Dixon Samantha 
Published: April 2021

Abstract
Several Type Ia supernova analyses make use of non-simultaneous regressions between observed supernova and host galaxy properties and supernova luminosity: first the supernova magnitudes are corrected for their light curve shape and color, and then they are separately corrected for their host galaxy masses. This two-step regression methodology does not introduce any biases when there are no correlations between the variables regressed in each correction step. However, correlations between these covariates will bias estimates of the size of the corrections, as well as estimates of the variance of the final residuals. In this work, we analyze the general case of non-simultaneous regression with correlated covariates to derive the functional forms of these biases. We also simulate this effect on data from the literature to provide corrections to remove these biases from the data sets studied. The biases examined here can be entirely avoided by using simultaneous regression techniques.
The Properties of Semi-Simple Splicing System Over Alternating Group, A3
Authors: Selvarajoo Mathuri , Heng Fong Wan , Sarmin Nor Haniza , Turaev Sherzod 
Published: April 2021

Abstract
Splicing system was introduced by Head in 1987 in order to explore the recombinant behaviour of deoxyribonucleic acid (DNA) strands in the presence of restriction enzymes and ligases. Restriction enzymes cut the DNA strands into a left - pattern and right-pattern while the ligases recombine the left-pattern of the first string with the right-pattern of the second string and vice-versa. Semi-simple splicing system is a variant of splicing system where the splicing of DNA strands will be at two distinct sites. Splicing languages generated from the splicing system are classified based on their computational power, according to the Chomsky Hierarchy. Previous researchers found that the splicing system of finite set of strings and rules generates only regular languages which has the lowest computational power. Hence, some restriction has been introduced to increase the computational power of splicing languages generated. In this research, an element of alternating group of order three is associated with the initial strings of semi-simple splicing system to generate non-regular languages which has higher computational power. Some lemmas and theorems are proven to show that associating the alternating group to the initial strings could increase the computational power of the splicing languages.
A Study On Virtual Intelligence
Authors: Krishna R. Sathya Bama , Praveena D. Anto , Nazhath Nafizza N , Naveena Ramesh Vardhini J 
Published: April 2021

Abstract
Virtual Intelligence can be otherwise known as digital intellect. VI is one of the developing technologies of this decade. It is the result of union of two technologies that are swiftly shooting up. They are Virtual Reality and Artificial Intelligence. While Artificial Intelligence will make machines react like an individual, VR will create an imaginary computer universe. This tech intends in transforming machines more like people. Using this VI technology, one can feel virtual world of their desire. This technology is utilized in many fields. Virtual Intelligence will integrate the mode of teaching. This will boost the gaming sector and will play a role in automation.
Automatic Motion Triggered Street Light Using IoT
Authors: Roobini M.S. , Suji Helen L. , Viji Amutha Mary A. , Selvan Mercy Paul , Jancy S. 
Published: April 2021

Abstract
Smart Street light is a computerized methodology that mechanizes the road path. The aim of Smart Street light is decreasing force utilization when are vehicles are not there. The Smart road light will gleam with high power when there are vehicles are moving and the power will stay diminish. With this progression of innovation, things become less difficult and it becomes simple for all people on the planet today. Robotization is a method of controlling human work in the creation of products.
Steady Marangoni instabilities in variable-viscosity liquid layer in the presence of insoluble surfactant
Authors: Kechil Seripah Awang , Allias Razihan 
Published: April 2021

Abstract
The ability to control the complex convective flow patterns is important and one of the factors that alter the dynamics of the surface tension is surface-active agents or surfactants. Surfactants affect the surface tension at the free upper surface by producing tangential stress. This study theoretically examines the onset of steady instabilities in a thin nondeformable and deformable variable-viscosity liquid layer in the presence of insoluble surfactant. The surface tension at the free surface is assumed to be linearly dependent on temperature and concentration gradients. The dynamic viscosity is assumed to be exponentially dependent on temperature. The stability problems are governed by the systems of nonlinear partial differential equations consisting of continuity, momentum and energy equations. Linear stability analysis consisting of scaling, perturbation of infinitesimal disturbances and superposition in normal modes are used to transform the system of partial differential equations into system of ordinary differential equations. The exact analytical solutions are derived and the marginal curves are illustrated to show effects of some controlling parameters particularly the variable viscosity and elasticity parameter. Viscosity variation and elasticity parameter of surfactant act as destabilizer while the Biot number and Lewis number stabilize. For deformable surface, convection sets in at long wavelength for liquid with variable viscosity but convection occurs at short wavelength for constant viscosity liquid.
Dusty Fluid Flow - Unsteady MHD with Two Parallel Plates with Heat and Mass Source
Authors: Ashraf Ali M. , Mohamed Ismail A. , Vaithyasubramanian S. 
Published: April 2021

Abstract
In dusty fluid flow, this paper analyses the composition of an unstable MHD with two parallel plates with heat and mass source transfer. By using the transformation of similarity, the differential equations of momentum and energy which will be of more than one variable is simplified into equations of single variable. Flow characteristics and characteristics of heat transfer for various control parameter values; viz. Analysis involves fluid velocity, dust phase velocity with corresponding heat and mass source parameters.
Heat and mass transfer effect between vertical plates through porous medium and chemical reaction effect on free convective MHD flow with soret effect
Authors: Niranjana N. , Vidhya M. , Govindarajan A. , Priyadarshini E. 
Published: April 2021

Abstract
This Problem deals with an oscillatory progression of an electrically conducting liquid with viscosity in the two dimensional field. MHD, mass and heat transfer are all consider here. The fluid passes through a permeable moving wet porous plate in the presences of transverse magnetic field. Vertical infinite porous plate is considered here.. Thermal diffusion effect is added into the governing equation. By using the perturbation technique, the analytical solution of the problem was obtained for the velocity, temperature and concentration profiles, Various non-dimensional parameters like Soret number, Schmidt number, Modified Grashof number, Prandtl number for heat and mass transfer are all discussed and he results depicted through graphs1.
A Novel Way of Detecting and Correcting Transmitted Errors using Fuzzy Logic
Authors: Neeraja A. , Amudhambigai B. 
Published: April 2021

AbstractTransmission and receival of messages always play an important role on various channels. Besides the transmission it is also necessary to be sure that only the exactly transmitted is transferred and the original message is not trampled due to the presence of some disturbance sources in the channel. Inspite of precautions if there is an error in transmission it is mandatory to recover the original message with the aid of several decoding measures. One among the decoding measures is the method of implementing the notion of fuzzy logic, which has its wide applications in several fields. Thus in this paper with the help of the concept of relative weights, the codes are studied in the sense of fuzzy logic to decode the transmitted message, detect errors in transmission and to correct them. Hence the technique of detecting and correcting errors presented in this paper provides a better outcome in comparison with several existing such methods. The prime aim of studying these concepts in fuzzy logic, is it’s precision and accuracy in terms of membership values which avoids the disparities that arises in other methods.
One Modulo Three Mean Labeling Of Graphs
Authors: Sudarvizhi G. , Balasangu K. 
Published: April 2021

AbstractThe concept of one modulo three mean labeling graph is, if there is an injective functionφfrom the vertex set of G to the set {a/0 ≤a≤ 3q− 2and either a≡ 0(mod3)or a≡ 1 (mod3)} where q is the number of edges of G andφinduces a bijectionφ* from the edge set of G to {a/1≤a≤ 3q− 2,a≡ 1 (mod3) } given byφ*(uυ)=[φ(u)+φ(υ)2]and the functionφis called one modulo three mean labeling of G. In this paper, we obtain the results of one modulo three mean labeling of some several graphs.
Dominator Coloring of Hajós and Trampoline graph
Authors: Manjula T , Rajeswari R 
Published: April 2021

Abstract
A proper node coloring of a graph where every node of the graph dominates all nodes of some color class is called the dominator coloring of the graph. The least number of colors used in the dominator coloring of a graph is called the dominator coloring number denoted by χd
(G). The dominator coloring number and domination number of generalized Hajós graph, partial generalized Hajós graph and trampoline are derived and the relation between them are expressed in this paper.
On the Secure Domination of Benes Networks
Authors: Angel D , Mary Jeya Jothi R , Revathi R , Raja A. 
Published: April 2021

Abstract
This paper focuses on the fascinating and highly active area of research on domination in graphs. In this article, the secure domination problem in graph theory is solved for Benes networks. The results obtained can be used in finding minimum secure dominating sets for an interconnection network whose vertices are the routing servers while it becomes necessary to obtain an optimal solution for designing the network defence strategy.
Implementation of hybrid model Converter for Photovoltaic Applications
Authors: Amala Rani V. , Marshiana D. , Jamunarani D. , Rajalakshmi G. , Bestley Joe S. 
Published: April 2021

Abstract
The increase in the use of non-conventional energy sources in our day to day life is to save our earth. The hybrid wind and photovoltaic power generation system allow supplying the load either individually or at the same time. This technique includes the Cuk and Sepic converters together and this eliminates the accessibility for extra input filters having high-frequency harmonics. The rapid changes in the atmospheric conditions can be control by using the Maximum Power Point Tracking technique because of its high tracking accuracy. To increase the output power and efficiency the Buck Boost and Sepic converters are used. Converters output ripple voltage can be reduced by the photovoltaic array voltage which can vary from 0 to 600V. The thin-film PV panels and the MPPT methodology is produced with the help of converters by reducing the stress occurred in voltage due to inverters and to work at 230V DC-bus voltage reducing Simulation is carried out MATLAB Simulink.
Ionic liquid-assisted nanocellulose preparation from microcrystalline cellulose
Authors: Haron Gamal Abdalla Suliman , Noh Hilmi Bin , Moniruzzaman Muhammad 
Published: April 2021

Abstract
Nanocellulose (NC) has generated interest from the scientific community because of their biodegradability, and unique physiochemical characteristics. In this study, ionic liquid 1-butyl-3-methylimidazolium hydrogen sulfate [Bmim][HSO4] combined with high ultrasonication is used to prepare NC from microcrystalline cellulose (MCC). The investigation by atomic force microscopy (AFM) revealed that the obtained NC had a rod-like shape with average particle diameter and length of 0.77±0.28μm, 2.11±0.65mμ respectively. Fourier transform infrared spectroscopy (FTIR) characterization exhibited that the prepared NC maintained the cellulose type I structure and the recovered IL (97%) composition remained intact as the pure IL. Therefore, it is expected to develop a green approach to produce nanocellulose with high quality using ILs.
Collaborative filtering recommendation algorithm based on user behavior and drug semantics
Authors: Wang Ruiyang , Li Tao 
Published: April 2021

Abstract
When the traditional collaborative filtering algori- thm is applied to drug recommendation, the recommendation effect is not good due to the sparsity of data. In view of the above problems, this paper proposes a collaborative filtering recommendation algorithm based on user behavior and drug semantics (UBDS-CF). Firstly, we construct the purchasing behavior matrix of users and drugs, and use the weighted cosine similarity to calculate the basic similarity between drugs; then construct the category label matrix of drugs, calculate the category similarity, and extract the feature vector of drug function text using the word vector model; category and main function together constitute the drug semantic information; finally, the above two similarities are integrated in a linear weighted manner to obtain the final similarity of drugs. Experimental results show that the average absolute error and root mean square error of the algorithm are significantly reduced, which proves the effectiveness of the proposed algorithm.
Defect Recognition in Radioscopic Image Sequences based on Bag-of-Words
Authors: Chang Fan , Chen Fumin , Tang KaiXuan 
Published: April 2021

Abstract
Digital X-ray real-time imaging is a new technology in non-destructive detection using image sequences. At present, manual identification of defects is mainly used in practice, which is expertise-dependent and prone to errors. The existing automatic recognition method based on radiographic images mainly recognizes a single defect type for a single radiographic image, which is easy to produce a large number of false detections in non-defect areas, and cannot correctly identify images containing multiple types of defects. A defect recognition method based on Bag-of-Words is proposed, which uses the inter-frame difference method to obtain the moving target area, namely the defect area, and uses the SIFT operator based on the Bag-of-Words model to extract the defect features, and then the trained support vector machine (SVM) performs recognition. Experimental results show that the proposed method can effectively reduce false detections in non-defective areas. The defect recognition method correctly recognizes the defect category with a probability of 85.3%.
Research and implementation of yield recognition of Citrus reticulata based on target detection
Authors: Qin Xiaoyue , Huang Ruwei , Hua Bei 
Published: April 2021

Abstract
In order to effectively assess the yield of Citrus. This paper proposed a scheme to identify and calculate the size of the Citrus objects on the tree in order to achieve yield prediction which is based on the target detection technology and the principle of insinuation geometry. The results of the experiments show that, this scheme has good detection effect on the whole Citrustree or local multiple fruit on the tree in the field orchard whose correct rate of identification can reach 90% and recognition rate is as low as 1.006 frame per second. After manual measurement verification, the conFiguration achieved the accuracy of 80%. This paper is of great significance in the practicality of fast fruit counting, and the difficult problem of selecting Citrus, which consumes a supply of manpower, is solved preliminary.
Characteristic Analysis and Investigation Strategy of Computer Network Crime
Authors: Tang Liangyan 
Published: April 2021

Abstract
This article analyzes the basic characteristics of computer network crime, including diversity, concealment, severity. The research content of this article combines the key points of application of electronic forensics technology, network investigation technology, and network tracking investigation technology. The author studied how to determine the investigative strategy, implement temptation investigation, and do a good job of monitoring and tracking coping strategies. The purpose of this article is to speed up the investigation of computer network crimes and improve the efficiency of solving cases.
Web Page Design of Automobile Energy Saving and Emission Reduction System Based on Neural Network
Authors: Zu Lin-Mei , Quan Kai-Li , Qi Guang-Lei , Hou Xiao-Gang 
Published: April 2021

Abstract
With the continuous development of economy and society, the demand and use of automobiles are increasing all over the world. China’s automobile industry has gradually grown into one of the important industries. Automobile exhaust has become one of the main sources of air pollutants in many cities, and automobile exhaust in some cities has a great impact on many air pollution indicators. If we can provide a more energy-saving route for the driver before the driver leaves, combining with the traffic situation forecast, we can better realize the energy-saving and emission-reduction of automobile travel. This paper mainly introduces the web page design of an automobile energy saving and emission reduction system based on neural network, which is implemented by Python, Html, JavaScript, CSS, Java and other programming languages, and meets the basic needs of users.
Multi-UAVs cooperative task assignment and path planning scheme
Authors: Du Xiaoyu , Guo Qicheng , Li Hui , Zhang Yanyu 
Published: April 2021

Abstract
The task assignment and path planning problems of multiple unmanned aerial vehicles (multi-UAVs) cooperative assistance roadside units (RSUs) for data collection are optimization problems with the goal of minimizing time and energy consumption. This paper proposes a hierarchical optimization scheme for multi-UAVs collaborative assistance RSUs data collection. This solution solves the problems that the number of UAVs needs to be set in advance, the convergence speed is slow when the number of tasks increases, and it is easy to fall into a local optimal solution, and the convergence accuracy is poor. First, the solution uses the K-means algorithm to allocate tasks and group RSUs to find the right number of UAVs to perform the task. Then, this paper proposes a hybrid optimization algorithm based on bionic learning for path planning. Finally, we set up a reasonable evaluation mechanism and conducted simulation experiments. The algorithm in this paper is compared with genetic algorithm, gray wolf algorithm and whale algorithm, the results show that the total cost of the task obtained by the proposed algorithm is the lowest, the algorithm stability is better, and the convergence accuracy is the highest.
Airborne Multi-channel Video Synchronization Playback Technology Based on C/S Mode
Authors: Hao Zhao , An Ying , Zhang Guo Wang 
Published: April 2021

Abstract
In the flight test, the airborne video data is an important part of the flight test data. At present, the airborne recorded video data is an independent M2T file, and the existing video playback software can only play back a single video file. In order to solve the problem of synchronous playback of airborne multi-channel video data, a multi-channel video synchronous playback technology based on C/S mode is proposed. The server performs video file reading control, and the client performs video decoding and display. Firstly, the basic concept of FFMPEG is introduced. Then the overall design of the system is discussed. The design and implementation of the server and the client are emphasized. The system is designed with C++ language, and the TCP/IP protocol is used in the server to interact with the client. Software design uses modularity and multi-threaded to improve processing efficiency and ensure functional scalability. At present, the software has been successfully applied to the simultaneous playback of multiple types of missions and multiple channels of video. The actual application results show that the system is stable and can effectively improve the efficiency of model flight tests.
Research and design of distributed key-value storage system based on Raft consensus algorithm
Authors: Wang Lin , Chen Xiaobing , Li Weifeng 
Published: April 2021

Abstract
With the rapid development of the Internet, data storage technology has gradually become a major research field in the industry. But stand-alone storage has poor performance in terms of consistency or fault tolerance. Therefore, a new type of key-value storage system for unstructured data storage is widely used. This article mainly researches and designs a distributed key-value storage system based on the Raft consensus algorithm.
AN OPTIMIZED ADABOOST ALGORITHM BASED ON K-MEANS CLUSTERING
Authors: Zhang Peng 
Published: April 2021

Abstract
Classification plays an important role on data mining techniques. AdaBoost is a classic upgrade algorithm on data classification. The Optimization algorithm on AdaBoost emerged is endless. In this paper we make some improvement on the base of a nonlinear AdaBoost algorithm based on statistics for K-nearest neighbors. In the basic algorithm, the prediction accuracies were improved more or less while it took plenty of time to calculate the Euclidean distance between the instance and all the samples. So we raise an improved method to shorten the computing time with K-means Clustering algorithm, and the classification accuracies will be as accurate as the original. Experiment results show that improvement is an effective method while the number of samples is large. And the bigger the number of the samples is, the more time can be saving in the stage of classification for the instance.