Reviewerly/exHarmony huggingface dataset:
The Impact of Different Backbone Architecture on Autonomous Vehicle Dataset

Abstract Object detection is a crucial component of autonomous driving, and many detection applications have been developed to address this task. These applications often rely on backbone architectures, which extract representation features from inputs to perform the object detection task. The quality of the features extracted by the backbone architecture can have a significant impact on the overall detection performance. Many researchers have focused on developing new and improved backbone architectures to enhance the efficiency and accuracy of object detection applications. While these backbone architectures have shown state-of-the-art performance on generic object detection datasets like MS-COCO and PASCAL-VOC, evaluating their performance under an autonomous driving environment has not been previously explored. To address this, our study evaluates three well-known autonomous vehicle datasets, namely KITTI, NuScenes, and BDD, to compare the performance of different backbone architectures on object detection tasks.
Solar Trackers Using Spherical Mechanisms

Abstract The power harvesting from a solar panel is maximized when its face is perpendicular to the solar ray. In order for a solar panel to face the sun during the daytime, its orientation has to be adjusted by a solar tracker. There are two relative motions between earth and sun. Compared with its daily east to west rotation, sun’s south-north movement is much smaller. If only sun’s east-west relative motion is considered for developing solar trackers, mechanisms with single degree of freedom can be adopted. If the orientation of a solar tracker with single degree of freedom is adjusted seasonally or monthly to cover sun’s small south-north relative movement, the solar tracker can effectively fulfill its solar tracking function. Single-axis solar trackers commonly consume less power to operate than their two-axis counterparts and cost less to fabricate and maintain, which brings their solar tracking merits. This research is on single-axis solar tracking mechanisms that are based on four-bar mechanisms. Because of their simple structure, high reliability, and easy maintenance, four-bar mechanisms have been extensively employed for various applications that include solar tracking. Four-bar solar tracking mechanisms currently have room for further improvement. The difficulties facing them include limited solar tracking motion, high solar tracking power consumption, and lacking self-locking function. Surmounting these difficulties makes designing four-bar solar tracking mechanisms challenging. Four-bar solar tracking mechanisms can be planar 4R, planar 3R1P, spherical four-bar mechanisms. Each of the three types has its unique solar tracking features. In this research, the performances of these four-bar solar tracking mechanisms are analyzed, simulated and compared with the motivation of improving them. The research results are tried to provide some guidelines for developing and promoting four-bar solar trackers.
Implementation of an Artificial Intelligence (AI) Instructional Support System in a Virtual Reality (VR) Thermal-Fluids Laboratory

Abstract Physical laboratory experiments have long been the cornerstone of higher education, providing future engineers practical real-life experience invaluable to their careers. However, demand for laboratory time has exceeded physical capabilities. Virtual reality (VR) labs have proven to retain many benefits of attending physical labs while also providing significant advantages only available in a VR environment. Previously, our group had developed a pilot VR lab that replicated six (6) unique thermal-fluids lab experiments developed using the Unity game engine. One of the VR labs was tested in a thermal-fluid mechanics laboratory class with favorable results, but students highlighted the need for additional assistance within the VR simulation. In response to this testing, we have incorporated an artificial intelligence (AI) assistant to aid students within the VR environment by developing an interaction model. Utilizing the Generative Pre-trained Transformer 4 (GPT-4) large language model (LLM) and augmented context retrieval, the AI assistant can provide reliable instruction and troubleshoot errors while students conduct the lab procedure to provide an experience similar to a real-life lab assistant. The updated VR lab was tested in two laboratory classes and while the overall tone of student response to an AI-powered assistant was excitement and enthusiasm, observations and other recorded data show that students are currently unsure of how to utilize this new technology, which will help guide future refinement of AI components within the VR environment.
Basic Research on Music Prescriptions - Second Experiment With Classical Music

Abstract The authors assume that the stress state can be expressed by a value, SMB, and are trying to develop a method to change the value in an appropriate direction by music. This paper compares the results of the music therapy experiment conducted in 2022 with those in 2020. Subjects are recruited and classified into four groups according to whether they know the pieces played and whether they like the music. Some subjects wear the pulse oximeter throughout the concert. Other methods are employed to measure the stress states of all subjects at the beginning, the intermission, and the end of the concert. Based on the experiment, the possibility of prescribing classical music to patients is recognized. The same music has different effects on the subjects, depending on the type of music and the subject’s characteristics such as gender and whether he/she likes the music. The effects also differ depending on the piano player. In other words, prescribing music would not be simply selecting songs according to the symptoms. In the future, the music database will be grown up and the experimental methods using public concerts will be improved. Some of the stress measurement methods employed in this experiment may be combined to determine SMD.
Model-Based Visual Control for Robotic Manipulators Using Udwadia Kalaba Formulation

Abstract This work presents the development of a model-based visual control strategy for robotic manipulators performing target tracking. The proposed approach leverages fiducial-based techniques for target identification with the Udwadia-Kalaba (UK) formulation for constrained robotic motion control. Using Baumgarte’s approach leads to a model-based visual control strategy capable of stable behavior when discontinuities are present in the desired trajectory that the robot has to follow, as well as when there are uncertainties in the dynamic model of the system. The control strategy is tested in simulation with a 4-DOF Reach Alpha 5 manipulator using real-world visual target tracking. The qualitative and quantitative evaluation of the strategy shows its capabilities in accurately tracking the desired trajectories.
On-Machine Positioning Method for Integral Impellers Based on Three-Dimensional Point Cloud

Abstract The integral impellers are crucial components of aerospace engines. In recent years, pre-formed blanks made through 3D (three-dimensional) printing and powder metallurgy have been increasingly used to improve material removal rate and processing efficiency. However, advanced blank manufacturing processes require higher precision in clamping alignment. The 3D camera system is poised to replace on-machine probes in achieving precise pose of blanks as they provide measurements with high accuracy and density. In this paper, we propose a methodology for precisely determining the positioning and pose of integral impeller blanks based on 3D point clouds. We first calibrated the 3D camera on the CNC machine. The homogeneous transformation matrix of the 3D camera coordinate system relative to the CNC machine coordinate system was calculated. Then, our proposed method enables a rapid alignment of the point clouds obtained from the blank with the corresponding CAD model. Finally, the machining allowance at the blades on the blank is calculated and optimized. Our on-machine 3D camera system has been successfully implemented on a CNC machine, and our proposed method has been validated. The system reduces measurement time by 5/6 compared to contact probes, making it highly efficient. The average machining allowance distribution was adjusted from 2.55 ∼ 3.56 mm before optimization to 2.92 ∼ 3.22 mm after optimization. On-machine measurement experiments with the contact probe have also verified that compensation is effective. The system is expected to be extended to other complex-shaped parts such as inlets for clamping processes.
Development of an Articulating Robot Arm Kit As an Educational Tool for Middle School Students

Abstract This paper describes the design and build of a working prototype of an industrial robot arm kit. The kit is intended to be used by middle school students as an educational tool or an inspiration for them to pursue engineering fields, specifically robotics, and automation. With the end users in mind, the robot arm is designed to be highly modular, engaging, easy to assemble and control, and inexpensive. The robot arm itself is classified or designed as an articulating arm robot. It consists of seven modules with five degrees of freedom. The seven modules are a base assembly, a lower arm, an upper arm, a controller, and three interchangeable end effectors. Three interchangeable end effectors are a pen holder, a circular two-jaw gripper, and a camera, which enable the robot arm to draw on paper with a pen, move an object from one location to another, and capture images of an object. Realizing that most children are more willing to learn about a subject or object if they interact with it, the robot arm has been set up with several coded presets to illustrate its performance capabilities, interactions with users, and manual control buttons on the controller.
Modelling of a Drone to Analyze Dynamic Instabilities With its Delivery System

Abstract In the study herein, an alternative mathematical model was developed with the intention of understanding the dynamics associated with the instabilities generated by an UAV and its delivery system, particularly the coupled nonlinearities of the system, and thus provide feedback to optimize drone design. In this regard, a Newton-Euler methodology was adopted to establish the parameters of the equations of motion of the target UAV system, which consisted of a combination of a platform and delivery system operating simultaneously. Specifically, the UAV platform was modelled as a rigid body which accounted for a total of six-degrees-of-freedom, three corresponding to the linear (position) directions of the system, and three correlative with the rotational (attitude) directions, thus elucidating drone maneuverability during operation. In this context, the delivery system, attached to the center of the UAV platform, was simultaneously modelled to account for oscillation patterns relative to a single coordinate of the platform, as well as the payload of the package unit. The response of the UAV and its delivery system was captured by imposing various initial conditions, while a power spectral density function was approximated to elucidate the dynamic characteristics of the drone.
Primary and Secondary Datum Planes Using Constrained Least Squares As An Efficient, Robust Solution for Standardization

Abstract Datum planes based on a constrained least-squares fit are being adopted in US and ISO standards. Some reasons for the adoption are presented here. In particular, the advantages of this definition over the current definition in ISO 5459 is highlighted. Further, the contrast between the constrained least-squares and the so-called “shifted least squares” is brought out as there is widespread confusion between the two. The handling of secondary datum planes is not a settled matter, and this document explains three candidates for ways to define the secondary datum. The authors show why that of the three, the method that reduces the secondary planar datum problem into a two-dimensional problem is preferred. But up until now, a unsolved issue for that method was the question of how to handle cases when the secondary planar datum feature is not orthogonal to the primary. One of the significant contributions of this paper is solving that thorny case in a straightforward manner, thus removing any technical limitation to its possible adoption.
Preliminary Dynamical Model of the LISA/LISA-Pathfinder Release Mechanism

Abstract LISA Pathfinder (LPF) is a space mission launched in 2015 aimed at testing key technologies for LISA, the first gravitational wave observatory in space. The LPF payload includes two gravitational reference sensors (GRSs), each one hosting a floating test mass (TM). The grabbing, positioning and release mechanism (GPRM) injects the TM into the scientific free-fall state, satisfying strict position and velocity requirements at release. In LPF, the TMs acquired non-compliant velocity at the release, compatible with spurious impacts with the GPRM. The impacts could be caused by oscillations of the mechanism due to the impulsive retraction of a piezo-driven release tip. Ground-based measurements of the GPRM dynamic response show vibrations triggered by the quick tip retraction together with a static deformation at steady state, so far unnoticed. In this work, we build a lumped parameters model, validate it by matching the experimental data, and use it to understand the mechanism dynamics. Moreover, we reshape an existing GPRM finite element model to the analysis of vibrations, in order to provide a physics-based tool to explore different designs and conditions. We present here the preliminary results of these activities.
Fully Homomorphic Encryption Scheme Over Integers Based on DGHV Scheme

Homomorphic encryption was introduced to enable untrusted parties to apply computation over encrypted data, without decrypting the message. It makes a promising future to solve security challenges with Cloud Computing. Still, because of complex problems, HE is not yet usable in real-world applications. However homomorphic encryption suffers from many complex issues like large-time computation, which is difficult to implement, and huge ciphertext size. In this paper, we take into account many vital homomorphic encryption schemes, all of them is depend on computing over integers, by converting the message to a binary format, then the ciphertext is calculated to every single bit of plaintext. So, we suggested another symmetric Fully Homomorphic encryption that depends on an integer number without converting it to binary format, it encrypts the message using a prime secret key. The proposed system is considered a great improvement to the DGHV system. Where it reduced the ciphertext size and the execution time significantly. The present proposed system shows an improvement of DGHV where it is faster about 23.8 times from DGHV, and we gain one ciphertext for the whole message instead of ciphertext for every bit of the message. The scheme's hardness depends on the greatest common divisor (GCD) problem. We present a detailed explanation of these schemes showing their efficient techniques and compare it with the proposed algorithm in terms of ciphertext size of algorithm, and execution time and analyze their security them finally draw several conclusions.
TO THE QUESTION OF DEFINITION ETYMOLOGY CYBERCRIME AND CYBERSPACE

The article discusses the actual concepts of "cybercrime" and "cybercrime", the basic component of which is cyberspace as a special area of activity in the information space. The emergence of these concepts is due to the global computerization of society, which determines the ongoing modernization of information technology and the emergence of new types of crimes committed through cyberspace. However, at present, both within the framework of international acts and in domestic legislation, there are no generally accepted definitions of these concepts, along with the lack of a unified approach to determining their content aspect. In addition, there is no consensus on the list of cybercrimes. In this connection, there is a need for a detailed study of national legislation and international acts that provide for liability for committing cybercrimes.
PID Control Tuning Based on Wind Speed Sensor in Flying Robot

The problem that is often faced by flying robots when carrying out the Vertical Take Off Landing (VTOL) process is the lack of stability of the vehicle due to differences in wind speed at any time. This is because the PID that has been pre-tuned is the PID at a certain wind speed and it is possible that during the race the wind speed suddenly changes, causing the vehicle to be less stable in carrying out the mission. Therefore, this study proposes a PID Control Tuning Control system based on the Wind Speed Sensor. In experiments that have been carried out with anemometer readings of 1-5 m/s, the ideal tuning results are obtained with each parameter P_roll = 0.1453, I_roll = 0.0892, D_roll = 0.004, P_pitch = 0.144, I_pitch = 0.09, D_pitch = 0.004, P_yaw = 0.184, I_yaw = 0.0184, D_yaw = 0.00309. In experiments with anemometer readings of 6-10 m/s, the ideal tuning results were obtained with each parameter P_roll = 0.148, I_roll = 0.0905, D_roll = 0.004, P_pitch = 0.1444, I_pitch = 0.09, D_pitch = 0.004, P_yaw = 0.1867, I_yaw = 0.0181, D_yaw = 0.0037. In an experiment with an anemometer reading of 11-15 m/s, the ideal tuning results were obtained with each parameter P_roll = 0.1494, I_roll = 0.09, D_roll = 0.004, P_pitch = 0.1457, I_pitch = 0.0902, D_pitch = 0.004, P_yaw = 0.1894, I_yaw = 0.018, D_yaw = 0.0037. PID adjustment based on this anemometer sensor utilizes the latest real-time wind speed data to support the robot in order to overcome instability in certain wind conditions by tuning PID so that the vehicle can maintain stability when carrying out certain missions.
Analysis of the Influence of Number of Segments on Similarity Level in Wound Image Segmentation Using K-Means Clustering Algorithm

This study underscores the importance of wound image segmentation in the medical world to speed up first aid for victims and increase the efficiency of medical personnel in providing appropriate treatment. Although the body has a protective function from external threats, the skin can be easily damaged and cause injuries that require rapid detection and treatment. This study used the K-Means clustering algorithm to segment the external wound image dataset consisting of three types of wounds, namely abrasion, puncture, and laceration. The results showed that K-Means clustering is an effective method for segmenting wound images. The greater the number of segments used, the better the quality of the resulting segmentation. However, it is necessary to take into account the specific characteristics of each type of wound and the number of segments used in order to choose the most suitable segmentation method. Evaluation using various metrics, such as VOI, GCE, MSE, and PSNR, provides an objective assessment of the quality of segmentation. The results showed that abrasion wounds were easier to segment compared to puncture wounds and lacerations. In addition, the size of the image file also affects the speed of program execution, although it is not always absolute depending on the characteristics of the image.
Simulating Virtual Environment and Experience for Training, Exergaming, and Edutainment in eXtended Reality (XR): A Survey

In recent years, eXtended Reality (XR) technologies, including Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), have emerged as transformative technologies in various domains and have revolutionized the fields of training, exergaming, and edutainment. These immersive XR technologies offer unique opportunities to simulate virtual environments and experiences that facilitate interactive learning and engaging physical activities. The simulation of virtual environments and experiences plays a crucial role in delivering high-quality and effective XR programs. This survey explores existing research and advancements in simulating virtual environments and experiences for training, exergaming, and edutainment in XR. This survey aims at providing an overview of the current state of research and development, discusses the challenges and opportunities in virtual environment and experience simulation, and highlights their future directions. By clarifying the advancements in virtual environment and experience simulation, this survey helps researchers discover the potential of XR in enhancing training, promoting physical activity, and revolutionizing education.
A Software and Application of Aviation Speech Recognition System Based on Artificial Intelligence

With the rapid development of the civil aviation industry and the increase in air traffic flow, the demand for control personnel has also sharply increased. The land air communication is the most important communication tool between controllers and pilots, and its accuracy directly affects air traffic safety. With the rapid development of information technologies such as big data and cloud computing, this article adopts an artificial intelligence deep learning engine as the core to implement an aviation speech recognition system software, it can not only display the actual situation of seats, allowing control personnel to quickly understand current information, but also recognize Chinese and English air traffic control speech and convert it into text for display, thus achieving various applications in the field of air traffic control. The system software interface is simple and easy to operate, with complete functions, making control work intelligent, reducing the workload of controllers, reducing the understanding deviation and operational errors of air traffic control commands, and safeguarding the flight safety of the aircraft.
Research on the Construction of Accurate Evaluation System of Classroom Teaching Supported by Big Data Technology

As a representative of the new generation of information technology, big data is the key support to promote the innovation, development and change in the field of education. The school classroom evaluation system also achieves innovative development due to the power of big data ,and to promote the improvement of classroom teaching quality. This study first expounds the basic principles of precision evaluation of classroom teaching supported by big data, Collect students' learning data before, during, and after class through online learning platforms such as cloud classes, constructs an accurate evaluation system, then carries out practical exploration, in order to improve the efficiency of classroom teaching evaluation.
Research on the Mechanism of Usage Continuance Intention in Green Gamification System

To explore the mechanism of usage continuance intention in the green gamification system, this study takes the four types of gamification affordance (autonomy support, visibility of achievement, competition, and Interactivity) as independent variables, and identity (self-identity and social identity) as mediating variables, thus constructs a theoretical model of the influence of gamification affordance on usage continuance intention. Based on this, the questionnaire was designed and the theoretical model was validated using a structural equation modeling approach. The results of the study show that gamification affordance demonstrates the ability to positively influence identity, which in turn has a positive impact on usage continuance intention. It is a reference for the rational design of the green gamification system and the improvement of user loyalty and user stickiness of the green gamification system.