this paper presents the results of analyzing the statics and dynamics models of the industrial welding robot with6 degrees of freedom (DOF) before and after optimizing the geometric structure based on the generative ...
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ISBN:
(纸本)9798350345650
this paper presents the results of analyzing the statics and dynamics models of the industrial welding robot with6 degrees of freedom (DOF) before and after optimizing the geometric structure based on the generative Design (GD) module on the INVENTOR software. the second link (2nd link) on the robot was selected for the optimized design of the structure withthe criteria of mass, stress and displacement. the static model of the robot is established in the general case. the position of the maximum load at joints 2 and joint 3 is directly related to the optimal link considered. the force and moment values acting on these joints are calculated as the basis for determining the static stress and displacement. Similarly, the dynamics model of the robot is considered in the state of motion withthe maximum velocity of joint 2. the post-optimized part reduces the mass by 39% compared to the original. the results of the post-optimized dynamics analysis showed that the maximum stress and displacement on link 2 decreased by 53.95% and 46.06%, respectively. the results of this study can be used as a basis to investigate the kinematics and dynamics of the robot during motion such as velocity, acceleration, driving torque and trajectory programming. Moreover, the problem of reducing energy consumption costs as well as reducing fabricating costs based on additive manufacturing technology can also be interested and developed in the near future.
Steganography is one of most important techniques for covert communication. In recent years, generative steganography, which transforms a secret information into a generated picture, is a prospective steganography-res...
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the authors raise the problem of providing research work of students, postgraduates, and university teachers with up-To-date information on the functioning of national and international market structures, prove the ne...
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Novice programmers face various errors during the learning of a programming language. Most of them need help from instructors since they lack error resolution skills. On the other side, instructors spend a lot of time...
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ISBN:
(纸本)9783031630279;9783031630286
Novice programmers face various errors during the learning of a programming language. Most of them need help from instructors since they lack error resolution skills. On the other side, instructors spend a lot of time figuring out students' error causes. Long error detection times result in delayed and failed feedback, leading to a loss of student motivation. To support instructor's fast feedback, a detection method of error cause is needed. Existing detection methods, which are code-based, detect common and specific errors that can be identified by analyzing source code. these methods do not cover the diverse error patterns of novice programmers sufficiently, such as logical defects. To resolve this issue, it may be beneficial to detect rough and correct error causes of diverse error patterns. In this paper, a prediction method of rough error cause is proposed by considering not only source code, but also problem information, execution results, and the cognitive level indicating programming skills. We assume that different programming skills lead to different error patterns, which can help roughly but precisely predict error causes of runtime and logic errors in novice programmers. For performance evaluation, data from two introductory programming courses are used to validate the effectiveness of the cognitive level. Additionally, the usability for fast feedback is validated by comparing the error causes detection times of the instructors in each case.
We present a no-reference image-quality - assessment algorithm based on active reasoning module. this algorithm has three modules: the feature extraction module, the active reasoning module, and the quality assessment...
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Artificial intelligence (AI) has become a transformative force in various industries, including software development and innovation. this paper focuses on measuring the impact of two branches of AI, generative AI and ...
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ISBN:
(纸本)9789819716814
Artificial intelligence (AI) has become a transformative force in various industries, including software development and innovation. this paper focuses on measuring the impact of two branches of AI, generative AI and knowledge-based systems, in the context of software development and innovation. generative AI involves machines generating content without explicit human programming, while knowledge-based systems leverage explicit knowledge representation and reasoning techniques. the technology has the potential to enhance software development processes, drive innovation, and improve overall efficiency. this paper explores the applications of generative AI systems in software development and innovation through case studies, real-world examples, and empirical research. Metrics such as development speed, code quality, innovation rate, and developer satisfaction are used to assess the tangible benefits of these technologies. Additionally, potential challenges and ethical considerations are discussed, along with future directions for integrating these technologies into software development practices. In this paper, we will delve into the specific applications of generative AI systems in software development and innovation. We will explore case studies, real-world examples, and empirical research to measure the impact of these technologies. We will examine metrics such as development speed, code quality, innovation rate, and developer satisfaction to assess the tangible benefits of generative AI and knowledge-based systems. Additionally, we will discuss potential challenges, ethical considerations, and future directions in leveraging these technologies for software development and innovation. By understanding and measuring the impact of generative AI systems in software development and innovation, we aim to provide insights into the potential benefits, limitations, and implications of adopting these technologies. through this research, we hope to contribute to the ongoing
Turbofan engine is a key component in aerospace. Its health condition determines whether an aircraft can operate reliably. However, it is difficult to predict the remaining useful life (RUL) precisely because of the c...
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In healthcare, Big Data analytics has attracted great attention among the research community. Health care records is enormous challenging not only by its volume but also the nature of diversification of data sets and ...
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'What are we learning this for?' is a common refrain heard in education. Showing how engineering practices are relevant to everyday needs like building science models in K-12 classes may lead to greater motiva...
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ISBN:
(纸本)9798350336429
'What are we learning this for?' is a common refrain heard in education. Showing how engineering practices are relevant to everyday needs like building science models in K-12 classes may lead to greater motivation for students in STEM learning. this paper investigates how horizontal integration of different streams of learning may enable students to see why and how each element of knowledge is relevant to the whole. By combining microcontroller-based electronics, programming, and 3D design and fabrication to build science models, students may develop a stronger appreciation of how the component technologies interrelate (internal contextualization) and how these integrated computational models contribute to the enterprise of science (external contextualization). Furthermore, students in science classrooms see how computation can make physical models dynamic to represent changes and relationships more effectively. the implicit representational science models and the incorporation of technology and computation into a regular science curriculum make the knowledge transferable beyond an individual lesson. Students learn the component technologies cumulatively through a sustained process of engagement across multiple science modeling projects. the major challenges of this approach are how the science modeling projects may be designed and what factors have to be considered in the designs to realize this learning progression. To answer these questions, this paper describes a rigorous design process for the Physical Computational Models (PCMs) that incorporates science model correctness, progression of learning across all streams, pedagogical efficacy, classroom dynamics and manufacturability. In addition, we implemented a year-long project using our Horizontal Learning (HL) approach at two local public schools. this paper reports in detail two PCMs we developed for authentic 5th and 6th grade classrooms to illustrate the integration of the learning streams in science, compu
this paper presents the development of a universal system designed for creating web applications that function as components of an automated equipment control system. the user interface development component of the sy...
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