bluuebunny/crossref_metadata_2025_split huggingface dataset:
Geometric Analysis and YOLO Algorithm for Automatic Face Detection System in a Security Setting
Authors: Ayo Femi Emmanuel , Mustapha Abiodun Muyideen , Braimah Joachim Ayodeji , Aina Daniel Ayodele 
Published: February 2022

Abstract
Face detection is a computer technology that determines the location and size of the human face in an arbitrary digital image employed for authentication. Face recognition technology plays a vital role in network security, video compression, content indexing, and retrieval since "humans" are the focal point of many videos. Face recognition-based network access control makes it almost difficult for hackers to obtain a user’s "password" and improves user-friendliness in human-computer interaction. In this paper, an automatic face detection system that accurately detects human faces and ignores any other object that is not a human face using geometric analysis and the you-only-look-once (YOLO) algorithm is introduced. The system is able to predict the ages and genders of the faces detected. It also detects the facial landmarks of the faces and indicates the emotions of the faces detected. A sample of four faces is considered for testing the system; thus, accurately detecting gender and emotion but not age correctly. In all, the evaluation shows about 80% accuracy. With the results got, the system can support security and analytics. It can be used to get analytics in an event with a lot of attendees and can also be used to get a facial mapping of someone involved in a crime scene for security purposes.
Application of solar energy to fruit and vegetable refrigerator in aiding the impoverished during the Covid-19 pandemic
Authors: Nguyen Thanh Tung , Hoa Dinh Thi , Truc Ho Ngoc Thanh , Phu Huynh Minh 
Published: February 2022

Abstract
Solar energy has now been applied to provide energy in many different fields around the world. In Vietnam, many solar energy projects are being implemented. In this transdisciplinarity research, research team and local stakeholders participate in designing a solar application to power a fruit and vegetable refrigerator located at Cu lao Rua, Thanh Hoi commune, Tan Uyen Town, Binh Duong province, Vietnam for the poor worker living in the disadvantaged localities with difficulties due to the impact of the Covid-19 pandemic. This is considered a community development project with the use of renewable energy, contributing to environmental protection of the new rural commune.
Mechanical and Microstructural Properties of Hybrid Bio-Composites using Microwaved Coconut Fibre and Rice Husk
Authors: Johar M F , Ariff T F 
Published: February 2022

Abstract
The outstanding mechanical and environmental qualities of hybrid bio-composites have made them popular. The drying procedure to remove the moisture before manufacture, on the other hand, can take a long period. By modifying the macromolecular structure considerably faster, hybrid bio-composites with additional physical treatment utilising microwave energy could improve their mechanical capabilities. Fillers of 80:15:5, 90:5:5, and 98:1:1 coconut fibre and rice husk were combined with poly-lactic acid (PLA) utilising melt-mixing and hot press techniques. The fillers were dried in a conventional oven at 60°C for 24 hours and in a microwave oven at 2.45 GHz for 3 minutes. When tensile strength was tested, it was discovered that oven-treated fibres with a 98:1:1 composition had a higher tensile strength (63 MPa) than microwave-treated fibres (58 MPa). Microwave-treated fibres, on the other hand, had a higher flexural strength (69 MPa) than those treated in a normal oven (60 MPa). Furthermore, when compared to plain PLA, microwave energy enhanced the toughness of the bio-composites by at least 4%. For the 80:15:5 composition, microwave-treated fibres had a lower water absorptivity (2%) than conventionally treated fibres, which had a water absorptivity of 5%. SEM images confirmed the presence of agglutination and voids with higher fibre content, resulting in poor adhesion and low tensile and flexural strength.
Implementation of Two-step Hybrid Block Adams Moulton Solution Methods for First Order Delay Differential Equations
Authors: Chibuisi C. , Osu B. O. , Edeki S. O. , Akinlabi G. O. , Olunkwa C. , Ogundile O. P. 
Published: February 2022

Abstract
In this paper, Hybrid Block Adams Moulton Methods for step number k = 2 merged with two and three off-grid points were obtained and implemented in solving first order delay differential equations without the use of interpolation condition in evaluating the delay expression. The discrete schemes of these off-grid hybrid block methods were assessed through the continuous development of the linear multistep collocation method using a matrix conversion formula. The results obtained after the implementation of the proposed method in for numerical experiment of some first-order DDEs, the BHAMM2 schemes performed better and faster in satisfying the axioms for convergence and region of absolute stability than the BHAMM3 schemes at fixed step size z when examined with other existing methods.
Laplace decomposition method for series solutions of systems of linear partial differential models
Authors: Engworo G. P. , Ogunniyi P. O. , Edeki S. O. 
Published: February 2022

Abstract
Most of the real-life problems experienced in the industry these days cannot be expressed as a single differential equation but as a system of differential equations. Such structures of linear partial differential models are considered in this work with the aid of the Laplace Adomian decomposition method (LADM) in terms of solutions. Various examples are taken into consideration. The results are easily obtained, are in good agreement when compared to their exact forms. In addition, the proposed method seems effective and efficient; the solutions are graphically presented.
Solar energy research for the design and manufacturing of oxygen aerator model for shrimp farming
Authors: Phu Huynh Minh , Nguyen Thanh Tung 
Published: February 2022

Abstract
This project refers to the research, design, and manufacturing of an oxygen aerator prototype for shrimp farming using solar energy. An offline solar system is calculated, designed to drive a 24VDC motor that rotates the propellers to generate oxygen in shrimp ponds. This system is researched for shrimp farming areas without electricity in order to expand shrimp farming capacity for coastal areas. The system can connect to the phone via Bluetooth to transmit the model’s parameters to the user interface. An app that connects the phone to the oxygen aerator is also designed to control and monitor data. Solar-powered oxygen aerators for shrimp ponds can help farmers save 2 to 3 times the cost compared to gas and oil-powered oxygen aerators.
Analysis of Seasonal Precipitation Rate in Nigeria Using Dataset from Tropical Rainfall Measuring Mission
Authors: Arijaje T. E. , Omotosho T. V. , Akinwumi S. A. , Ometan O. O. , Fashade O. O. 
Published: February 2022

Abstract
The study aimed to analyze the seasonal precipitation rate using dataset retrieved from TRMM over Nigeria. The Seasons evaluated are December to February (DJF), March to May (MAM), June to August (JJA) and September to October (SON) using ten years (December 2009-November 2019) data acquired from TRMM data base. The result shows that, the precipitation rate differs and these ranges from light precipitation from the northern regions to heavy precipitation in the southern regions. For the DJF season, the northern regions experience little or no precipitation especially during the dry season. Meanwhile, during the MAM, JJA and SON seasons, the northern regions experiences light to moderate (0 ≤ R < 5 mm/h) precipitation rate according to World Meteorological Organization (WMO) while the southern regions experience moderate to heavy (0.1 ≤ R ≥ 0.5 mm/h) precipitation rate with its peak at MAM and SON seasons which correspond to the wet months/season and early dry season. It follows that the result obtained from this work is in agreement with the WMO. The result from this work will provide an insight on precipitation event which in turn, will help in decision making on various ways of adaptation and also, planning of outdoors events such as agricultural activities (food securities), sport activities and also in the telecommunication and aviation as increase in the rate precipitation increases the attenuation on communication link.
Remarks on Analytical Solutions of a Non-Homogeneous Gas Dynamic Model via Successive Approximation Method
Authors: Edeki S.O. , Adeyeye F.J. , Akinlabi G.O. , Udjor V.O. 
Published: February 2022

Abstract
The Successive Approximation Method (SAM) is introduced in this research to solve the non-homogeneous Gas Dynamic Equation (GDE). This GDE’s analytical solution is expressed via the SAM, in series form, with readily computed components. The proposed technique is used directly, without transformation, discretization, linearization, or any restrictive assumptions.
Unsupervised Kernel-Induced Fuzzy Possibilistic C-Means Technique in Investigating Real-World Data
Authors: Devi R 
Published: February 2022

Abstract
The goal of this study is to break down a large dataset into meaningful groupings. Due to the vast dimension and significant resemblance seen among data, exploring divided clusters in real-world datasets is the most difficult assignment. As a result, this work proposes a fuzzy set-based unsupervised effective clustering technique that includes possibilistic memberships, and fuzzy membership degrees into the membership, weighted Cauchy kernel-based similarity measure and center equations. The empirical findings demonstrate the feasibility of the proposed effective clustering technique.
Stability Analysis of an SIR Infectious Disease Model
Authors: Ezekiel D , Iyase S A , Anake T A 
Published: February 2022

Abstract
The paper investigates the stability of the SIR mathematical model of transmission of an infectious disease with delay. First, the study investigates local stability of the positive steady state of an infectious disease model by analyzing the linearised system where more general stability criteria with delay and model parameters are obtained. Secondly, the study shows that the model exhibits Hopf bifurcation on choosing the delay as a bifurcation parameter. Conditions for existence of qualitative behaviour for positive steady state are identified. Finally, numerical simulation of results and biological interpretations were verified using MATLAB software for the delay model. The study supplements theoretical improvement to earlier results obtained in the literature.
A Factor Graph Approach to Simultaneous Robot-World and Hand-Eye Calibration Based on Lie Group
Authors: Lan Bin , Wang Xueqiang , Li Zhiheng 
Published: February 2022

AbstractThe existing robot-world and hand-eye calibration algorithms always treated the robot pose as a deterministic value. Its uncertainty is not taken into account, which affects the calibration accuracy when the robot’s position accuracy is low. In this paper, we proposed a factor graph approach to simultaneous robot-world and hand-eye calibration, which considers the measurement error of the robot joint encoder. And then, the nonlinear optimization of reprojection error minimization based on a product of exponentials (POE)-based model is implemented to solve the calibration problem based on lie groups. Through simulation and experiment, we validated that the proposed algorithm can get more accurate calibration results compared with the state algorithm.
Terrain Estimation with Least Squares and Virtual Model Control for Quadruped Robots
Authors: Qin Haipeng , Zhu Yaguang , Zhang Yaqiang , Wei Qibin 
Published: February 2022

Abstract
In this paper, a method to estimate the terrain based on footholds and least-squares is presented to make quadrupedal locomotion stable on the sloped terrains, with joint encoders, force sensors and inertial measurement unit (IMU) instead of visual sensors. This method which is tested successfully in simulation can predict two types of terrain, one for adjusting the robot pose and the other for adjusting the trajectory of swing phase. And to make full use of these new capabilities, general balance and locomotion controller is presented. The virtual model controller is embedded into architecture and it allows the robot to handle unexpected terrain. The quadrupedal locomotion in terrain with different inclination prove the robustness of this method.
Real-time Wide-depth-range Pose Estimation with Laser Scanning Point Cloud
Authors: Su Yu , Xu Tianlai , Zhang Zexu , Wang Yishi , Yuan Mengmeng 
Published: February 2022

Abstract
In this work, a real-time wide depth pose estimation method with laser scanning point cloud is proposed. Unlike other 6D pose estimation methods, the proposed method can maintain a robust and accurate tracking performance even when the target spacecraft has an obvious transformation in depth. To make full use of the known model, a pose estimation network based on CNNs is established to estimate the position. After the point cloud is translated according to the estimation result, the quaternion of the target is calculated independently. To evaluate the consequent of the network, we simulated the scanning point cloud with a wide depth range. The results show that the proposed method has strong robustness to the depth transformation and higher computational efficiency.
A Minimum Mutual Information Optimized SSD and Application In Bearing Fault Detection
Authors: Wang Zhenya , Liu Tao , Chu Wei 
Published: February 2022

Abstract
For purpose of efficiently extracting the fault detailed characteristics of rolling bearing vibration signals in the midst of heavy noise interference, the author combines the mutual information theory and proposes a singular spectrum decomposition effective component discrimination method based on the minimum mutual information criterion. First, the SSD algorithm is used to decompose the original vibration signal into a number of SSC; then the mutual information value between the original signal and each singular spectrum component is calculated separately, based on the nature of the bearing fault vibration signal and the mutual information theory for derivation and analysis, and the selection is determined the singular spectrum component with the smallest mutual information value among the original signal and each component is taken as the best component; finally, the best component selected based on the minimum mutual information value criterion is analysed by envelope spectrum to extract the fault characteristics of rolling bearing. Through the analysis of bearing fault simulation signal and the comparison with other indicators, it is shown that this set of experiments significantly extracts the characteristics of the vibration signals emitted by rolling bearings due to faults in noisy environments, thus revealing promising applications and development prospects.
Design and Implementation of Temperature Verification System Based on Robotic Arm
Authors: Qiu Shi , Yang Zongbo , Huang Lei , Zhang Xuehan 
Published: February 2022

Abstract
The key issue of meteorological temperature verification is how to operate itself without personnel deployment. This paper presents a meteorological temperature verification system based on robotic arm. Its goal is to realize the automatically operating by integrating robotic arm controller and verification software. The device level provides temperature verification instruments and the robotic arm. The communication function such as cyclic measurement of the resistance of temperature sensor, verification environmental data communication and temperature generator control can be realized by networking level. The interactive level ensures stable operation and fault location. Some key methods such as the system layout, the system workflow and the system integration method are also illustrated for system implementation.
A Configuration Design Method for Reconfigurable Robots Based on Terrain Understanding
Authors: Shang Hua , Xi Yurong , Xie Zhibing , Xiao Xueming , Yao Meibao 
Published: February 2022

Abstract
Reconfigurable robots have excellent reconfigurability and environmental adaptability, but the configuration design method to select appropriate configuration with different environments has not been fully studied. Most of the existing work is based on the known global environment information, or only focus on the structure design. How to effectively obtain rich terrain information for subsequent configuration design is the subject of this paper. In our work, a comprehensive method of obtaining robotic configuration is proposed which considering geometric information and semantic information of unstructured terrain. And it provides new possibilities for reconfigurable robots to perform autonomous tasks in complex scenarios. Results of simulation experiments prove the availability of the mentioned method.
Acceleration of Infrared Target Detection via Efficient Channel Pruning
Authors: Miao Zhuang , Zhang Yong , Li Weihua , Chen Ruimin 
Published: February 2022

Abstract
Deployment of modern detection models is difficult for infrared target detection used in robot vision systems due to their heavy computational burden. To alleviate this situation, a simple but efficient channel pruning method is proposed for model acceleration. Specifically, a soft-gated module combined with batch normalization (SGBN) is designed as a standalone layer to substitute the standard batch normalization (BN) layer during training. The conversion between SGBN and BN is easy, and the training overhead introduced is almost negligible after replacement. By controlling the sparsity of the scaling factor in SGBN, unimportant channels with small output are blocked automatically and globally, which is simultaneous with model training. Removing these redundant channels no longer requires fine-tuning, thus significantly speeding up the pruning process. Experiments of pruning different detection models on the infrared dataset show the effectiveness of our method. For example, the parameters and FLOPs of pruned CetnerNet are reduced by 72.70% and 40.20%, respectively, without accuracy loss. The inference speed on the CPU is 12.01ms faster. Extended studies on the classification task also demonstrate its great potential when transferring to other applications.
Positioning in Urban Scenarios Based on Smartphone Camera/IMU and Digital TV Signal
Authors: Pan Yinghua , Chen Liang , Jiao Zhenhang , Liu Xiaoyan , Chen Ying 
Published: February 2022

Abstract
The built-in sensors of smartphone, such as cameras, accelerometers and gyroscopes, provide abundant environmental information for positioning. VIO (visual-inertial odometry) can be derived from the embedded camera and inertial sensors to provide the estimation of a continuous and smooth trajectory of the pedestrian. However, the trajectory will drift due to the accumulation of system errors. Currently, DTV (digital TV) signal has been verified to be promising for precise ranging in urban scenarios. Therefore, this paper investigates a method of fusing the VIO with the ranging information from DTV signal to improve the positioning accuracy. An Extended Kalman filter is presented to estimate pedestrian mobile state. Field tests have been carried out and the fusion results can effectively reduce trajectory drift errors and improves positioning performance.
An SLAM Algorithm Based on Laser Radar and Vision Fusion with Loop Detection Optimization
Authors: Li Lina , Yuan Jing , Sun Hao , Song Yan 
Published: February 2022

Abstract
SLAM (Simultaneous Localization And Mapping, SLAM) is the key technology for mobile robots to obtain information about their position and surrounding environment, but both laser radar and vision sensors have limitations in solving SLAM problems, for example: a single laser sensor can’t do mapping effectively for hollowed-out obstacles, while a single vision sensor can’t work well in areas without texture. Besides, the existing loop detection technology still has some problems such as large calculation resources and errors. To solve the above problems, an improved SLAM algorithm laser and vision fusion was presented in this paper. In this algorithm, a Gaussian statistical linear interpolation algorithm was used to interpolate the laser point cloud, and then the interpolated laser raster map and visual raster map are fused by the Bayesian method to obtain a denser and more accurate map. Furthermore, the histogram was used to improve the loop detection part to further improve the positioning accuracy. The improved loop detection algorithm was simulated and verified by running the TUM data set. On this basis, a mobile robot experiment system was built to do mapping in the laboratory scene. The experimental results show that the algorithm proposed in this paper can map the hollowed-out area accurately and effectively, it plays a significant role in improving the drawing effect of the robot, and can provide more accurate location information, which has good practicability.
Design of an Improved Impedance Controller for Powered Transtibial Prosthesis
Authors: Xie Changle , Tu Mingyu , Liu Jingjing 
Published: February 2022

Abstract
With the rapid development of powered transtibial prostheses, the control of motorized actuators is a research hotspot. This study designs a double-loop impedance controller to improve the performance of the traditional controller. Including time-varying parameters, the designed controller is implemented on a novel elastic actuator. Under different loads of users’ weights, simulation tests are conducted in a working condition of walking, and the results show that the designed control system has outstanding performances in the control of an entire gait cycle. The error between output and reference of ankle joint position during walking is less than 0.013rad in each sample time. A position disturbance test demonstrates that the control also has a high tolerance of any position disturbance at the ankle joint. The double-loop impedance controller can replace traditional finite-state impedance control in the field of the powered transtibial prosthesis and has the potential to be applied in other relative fields.
The Execution Efficiency of the Response Time Analysis under Different Task Sequencing Strategies
Authors: Ma Li , Zhou Li , Zhou Qiupeng , Wang Qixin 
Published: February 2022

Abstract
Tasks in real-time systems have strict time requirements and need to be completed before their deadlines. Whenever the real-time task set changes, the real-time system reruns the schedulability analysis method to determine whether the tasks in the new task set can be completed before their deadlines. Since new tasks can not be executed until the execution of the schedulability analysis method is completed, the execution efficiency of the schedulability analysis method directly affects the actual performance of the real-time system. Response time analysis (RTA) is a typical method for schedulability analysis. It calculates the response times of tasks and tests the schedulability of tasks by comparing the calculation results and the relative deadlines of tasks. We found that the execution efficiency of existing RTAs can be improved by reasonably sorting the calculation order of the tasks. A task sequencing strategy is proposed to improve the execution efficiency of existing RTAs.