Applied and Computational Engineering

- The Open Access Proceedings Series for Conferences

Volume Info.

  • Title

    Proceedings of the 2023 International Conference on Machine Learning and Automation

    Conference Date






    978-1-83558-293-0 (Print)

    978-1-83558-294-7 (Online)

    Published Date



    Mustafa İSTANBULLU, Cukurova University


  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230284

    Enhancing a star algorithm for robot path planning

    This paper describes the importance of robot path planning in artificial intelligence and control theory, and proposes three improvements to the A-algorithm: bi-directional A-search, improved heuristic functions and pruning strategies. The performance of the different algorithms in terms of computation time, path length and number of nodes is compared through experiments. Moreover, it is emphasised in the article that in practical applications suitable algorithms and their improvements are selected according to the characteristics of the specific problem and reasonable evaluation criteria are used to measure the performance of the algorithms.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230286

    Improving machine translation and post-editing for Chinese tourism texts using transformer-based models

    As the digital age and globalization continue to evolve, the demand for accurate machine translation of tourism texts has increased substantially. This paper investigates how to improve the quality of machine translation (MT) and machine translation post-editing (MTPE) of Chinese tourism texts for non-native speakers. A review of the machine translation literature reveals a significant progression in translation methods from rule-based to corpus-based, statistical, and finally to the current neural machine translation (NMT) models. Despite its advanced capabilities, NMT requires large amounts of parallel data for training, which often presents challenges. This study proposes the use of Transformer-based models for MT and MTPE to improve translation quality. A dataset was curated from online sources, mainly Chinese tourism websites. The methodology involved pre-processing the data, performing machine translation using the Transformer model, and post-editing the results. The experiment demonstrated an increase in the BLEU score, suggesting an improvement in translation quality. However, challenges such as the handling of synonyms and geographical nouns were encountered, indicating the need for further research and model optimization.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230288

    Comparative study of the execution efficiency of Python and C++——Based on topological sorting

    C++, a compiled language, and Python, an interpreted language, are among those essential coding languages that function in diverse areas of the current computer industry. However, different languages have disparate benefits and fit in various circumstances. When large amounts of data are involved or fast execution speed is required, one should consider which language performs better. This research mainly aims to find out whether C++ or Python is more efficient through Topological Sorting, which is utilized to linearize the vertices of a Directed Acyclic Graph (DAG). In the approach of coding the Topological Sorting algorithm in C++ and Python and comparing their execution times on each matrix representing a DAG randomly generated by a Python program, it is concluded that C++ generally has a higher efficiency than Python.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230289

    Research on the application of computer in drug design

    Virtual screening by computer is of great scientific significance for drug research and development. In recent years, a large number of computer simulation methods have been developed and applied to drug development for a variety of diseases. This paper summarized and prospected the application progress of computer aided drug design (CADD) in the research and development of new drugs, focusing on the working principle of CADD, related algorithms, and the advantages and disadvantages of existing methods. Although CADD has been successfully applied to a number of drug development projects, the accuracy of auxiliary drug structure optimization is still not high. Therefore, it is urgent to develop more accurate and efficient CADD models and algorithms to promote the process of new drug discovery.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230290

    Exploring the coexisting relationship between Artificial Intelligence-Generated Content (AIGC) and designer

    This paper focuses on how designers can find the right balance and new foundation between themselves and Artificial Intelligence Generated Content (AIGC) at a time when the current artificial intelligence trend is invading the design industry like a wave. This study uses two methods of text analysis and semi-structured interviews to explore the coexistence between AIGC and designers. The results show that, for now, AIGC can help solve some of the fundamental problems in the design process but not all of them. Almost all designers dare not underestimate the possibility of AIGC in the future, and the arrival of AIGC is already an irreversible fact. This study explores the future impact of AIGC on the creative design industry through the perspective of designers and critical theory. It provides practical inspiration and some valuable thinking for the design industry.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230293

    AIGC (Artificial Intelligence Generated Content) infringes the copyright of human artists

    With the rapid development of artificial intelligence technology, content generated by artificial intelligence has been rapidly applied to people's lives. At the same time, it is also accompanied by many infringement lawsuits, whether AIGC has really caused different degrees of infringement to human artists. Through the analysis of the existing literature on copyright issues and the walkthrough of Stable Diffusion, an AI-generated image platform, this article digs into the main factors that the AI-generated platform causes infringements on human artists. Provide references for using AI by enterprises and related media, and let more scholars pay attention to this issue. The study found that in the workflow of the AI generation platform, taking Stable Diffusion as an example, the two processes of model training and image generation may cause copyright infringement to a certain extent. Based on this, the AI generation platform has unauthorized use of copyright works, excessive plagiarism and adaptation of copyright works, and the generated images are not marked with watermarks or sources, which damages the copyright owner's rights.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230294

    Snapchat's disappearing messages: Balancing entertainment and privacy in digital communication

    Modern instant messaging platforms often default to permanent data retention, raising concerns about data privacy and users' ability to manage their digital artifacts. In contrast, emerging applications like Snapchat introduce ephemeral communication, where messages automatically vanish after being viewed. This paper investigates the motivations and experiences of users utilizing Snapchat's disappearing message feature. The study employs semi-structured interviews with young adults aged 18-24, who are active Snapchat users. Findings reveal that Snapchat's primary appeal lies in entertainment, creative expression, and maintaining casual relationships. While the disappearing feature contributes to privacy perceptions, users' trust in the feature's privacy protection is not absolute. The paper highlights the challenge of conducting task-oriented or deep conversations due to the ephemerality, emphasizing Snapchat's utility for informal and lighthearted interactions. Ultimately, the study underscores the importance of aligning user experiences with application design, providing insights for practitioners seeking to enhance user-centered product development in the evolving landscape of digital communication.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230295

    From a new product: Apple Vision Pro ̶ ̶ Impact of VR technology development on VR gaming

    Apple vision pro renewed interest in VR technology. Whether academia and communities all have many discussions. In this article, three main questions could be discussed after the selecting of some data. The first is how it is being applied in the future. The second is what experience does this current application provide to the user. The last question is what direction could be taken in the future. This research may answer some of the doubts and bring some thoughts to the table

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230296

    A literature review on snow simulation with MPM in computer graphics

    Snow simulation is always a challenge in the computer graphics community due to its combined nature of solids and fluids. In the past, researchers usually applied different solvers to computationally simulate the behavior of snow at different phases, which made the simulation both slow and complicated. In 2013, the material point method, abbreviated as MPM, was first introduced for snow simulation, eliminating the need for multiple solvers. This paper investigates the history of the application of MPM to snow simulation in computer graphics specifically, and offers an overview of its evolution since the pioneering work by Stomakhin. It aims at showing the current state-of-art as well as any limitations. Nowadays, the development of MPM and snow simulation focuses on improvements of the stability and physical accuracy of the method itself, and the generalization of the application scope from snow to arbitrary granular materials. The trade-off between efficiency and accuracy remains a problem, thus it introduces more potential research directions, ranging from developing simpler mathematical models for better physical accuracy to incorporating machine learning techniques to accelerate the simulation process.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230297

    FPGA accelerator for wireless AR/VR display

    Nowadays, Virtual reality(VR) and Aug- mented reality(AR) have become one of the most popular format in many fields, for example video gaming, medical training and even aviation. VR and AR technique simulates images in an edge device, it gives an immersive experience to the users. AR/VR requires high resolution and high FPS for good experience. However, most of the AR/VR devices are made of embedded device due to the limitation of the size and weight of the headset. It is hard to render high quality frames in headset. Many popular VR/AR applications utilize the desktop and server to render the frames and transmit the frames to VR/AR for display. Data transmission from a more powerful device to the VR/AR device requires high transmission speed (1.6GB/s for Oculus quest 2), it is hard to provide the bandwidth with wireless protocol (WIFI/5G). HDMI or DP cable can be applied, but they limit the use case of the VR/AR devices. In this paper, we proposed a latency sensitive super sampling hardware accelerator for VR/AR devices based on machine learning which can significantly reduce the bandwidth requires to transmit frames to VR/AR. In our experiment, the super sampling can deliver high-resolution frames with 25% bandwidth which enable the wireless protocal for VR/AR devices. We implemented the accelerators in RTL and synthesis it with 130 nm skywater pkd. The power consumption of our accelerator at normal data rate for VR/AR devices is 20.97 w and the area is 299.602 mm2.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230299

    Exploration of special children education based on AR technology

    Augmented Reality (AR) is a nascent technical advancement that enables the seamless amalgamation of real-world and virtual-world data. The notion of materializing virtual information to enable its perception by human senses is a subject of significant scholarly interest, resulting in a perceptual experience that transcends the confines of conventional reality. Because of the popularity of augmented reality, artificial intelligence, and Internet support, distance learning systems with contextualized learning, gamified learning, and collaborative learning will empower all traditional classrooms or home education, rapidly adding massive learning resources. This research evaluates the current literatures related to AR as well as the influence and efficacy of AR on the education of special needs children, such as hearing impairment, intellectual disability, autism, emotional-behavioral disorders, etc. The purpose of this research is to uncover the benefits and challenges of AR, as well as recommendations and future directions, by studying pertinent situations.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230301

    Research on real-time fire detection and locating for automotive firefighting robot in factories based on Convolutional Neural Network

    Automotive fire robots that are used in factories can carry out diverse operations in regard to patrolling, fire detection, and programmed fire rescue. An accurate detection of fire sources in factories is significantly crucial for unmanned firefighting robot in terms of building a reliable sensor system. An approach proposed by this paper to recognize the color and dynamic shape of varying flames based on HSV color algorithms and Convolutional Neural Network. As a comparison to traditional RGB image processing, this approach is more efficient in isolating colors in environment and more adaptive to a fire site that includes multiple noise factors. The research in this paper uses image processing algorithms that is trained by CNN to detect flames in simulated factory environments, followed by a HSV color locating algorithm to compute the coordinates of target fire to perform inverse kinematic analysis on an unmanned firefighting robot.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230303

    Research on path planning technology of mobile robot in the restaurant scene based on A* and D* algorithm

    Intelligent robots have found widespread applications in various fields including medical treatment, industrial production, and social services. These robots are specifically designed to fulfill diverse tasks in different environments, the design and control of these robots play a crucial role in ensuring their efficiency and security. In response to the high demand for fast and convenient service, the catering field is a crucial and promising application field for intelligent robots. This article is primarily focused on the robot in the restaurant scene where the robot could automatically deliver food to the customers, thus reducing the burden on human service providers. In this special environment, the delivery robot must possess the capability to identify its surroundings within the restaurant and autonomously calculate an obstacle-free path from the starting point to the desired destination without colliding with either obstacles or individuals. In this article, the restaurant scene is built in the Gazebo, and map scanning and conversion methods are utilized to enable the robots to recognize the environment effectively. Furthermore, A* and D* algorithms are employed in Python to achieve global and local path planning, respectively, thus validating the feasibility of the methods. The combination of these two algorithms demonstrates a successful path-planning application within the context of a restaurant scene.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230304

    A design of intelligent AGV system combined with a robotic arm for flexible production lines

    Unmanned mobile robots have broad application prospects in industrial production. With the continuous deepening of Industry 4.0, the complexity of manufacturing workflows has skyrocketed, and researching robots suitable for flexible production is becoming a focus of development. With the rapid development of computer technology and sensor technology, the ability of robots to obtain their own state and environmental information has also been greatly expanded. Studying the work, path planning, and obstacle avoidance of robots has important practical significance. This article designs a flexible production robot that integrates Automated Guided Vehicle (AGV) with industrial robots. It has the ability to perceive the environment, make optimal decisions, and operate independently. It can achieve functions such as mobile transportation, flexible operation, and human-machine interaction and cooperation in the production line. This article uses Gazebo to construct a production environment and simulate robot movement. In addition, MATLAB is used to conduct simulation experiments on the operation of the UR10 robot. The results and planning path map validate the feasibility and effectiveness of this method. The mobile robot designed in this article combines a robotic arm with an AGV, which has certain application value in future flexible manufacturing factories and provides a certain reference value for flexible production.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230307

    Development and analysis of autonomous driving technology for wheeled robots

    A The remarkable progress achieved in the evolution and utilization of autonomous driving technology in wheeled robots is thoroughly analysed in this extensive review article. It begins by stressing the significance of autonomous driving technology in the functioning of wheeled robots. The article proceeds to explore the advancement and application of the core components of autonomous driving technology, namely perception, decision-making, and control, in wheeled robots. Moreover, the comprehensive examination sheds light on the main stumbling blocks and restrictions faced in the current implementation of self-driving technology in wheeled robots, including the need for advanced perception systems and decision-making abilities. Touching on future directions in this domain and offering suggestions for further investigation, the review ultimately emphasizes the capacity of self-driving technology to augment the efficiency and security of wheeled robots, while stressing the inevitable requirement for continuous research and innovation to surmount existing hurdles and actualize this potential in its entirety.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230308

    An design of robotic arm control algorithm for explosive disposal robots

    Automatic explosive disposal robot have great potential to replace manual Explosive ordnance disposal(EOD) robots. In order to face the practical application scenarios of complex transformations, it is of great practical significance to study a fully automatic and autonomous EOD robot that can transfer dangerous goods to a safe area. In this paper, a mechanical arm algorithm based on the inverse kinematics of robot is presented. The relative position of the bomb is input by the electromagnetic induction device to guide the mechanical arm to the corresponding position. After obtaining the bomb, the deviation angle of the mechanical arm is input in real time by the gyroscope to achieve the relative stability of the object transportation. The experimental results indicate that the explosive disposal robot has certain practical significance.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230309

    Application development analysis and prospect of express sorting system based on mechanical arm

    At present, with the improvement of people’s living standards and the rapid development of e-commerce, the volume of express delivery is increasing. The existing manual express sorting method is high-cost and low-efficiency, and an efficient domestic waste sorting method is urgently needed by the society. At present, the field of robotics is developing rapidly, and mechanical arms have various types and functions. Using mechanical arms to replace manual work to complete express sorting tasks has advantages such as high efficiency and labor saving. This paper analyses the application and development of different types of mechanical arms in express sorting system. First, the research status of express sorting and the development of mechanical arm are introduced in detail. Second, based on the structural characteristics, mechanical arms are divided into articulated robot and parallel manipulator. At the same time, the characteristics of the two kinds of mechanical arms and their application in express sorting system are analysed. Finally, by comparing the advantages and limitations of different mechanical arms in express sorting field, the application prospects of different types of mechanical arms in logistics sorting field are discussed.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230310

    Design and analysis of an autonomous warehouse robot system with 6-DOF manipulator

    With the increasing need for efficiency and accuracy in warehouse operations, the functions and market demands of automated warehouse robots are constantly increasing. This study presents the design, simulation, and implementation of a warehouse robot, showcasing effective automation solution. Leveraging the Robot Operating System (ROS) and Gazebo, a robot with a six-degree-of-freedom robotic arm for diverse manipulation tasks and a differential drive base for broad-spectrum navigation was designed. The simulation environment in Gazebo faithfully replicates real-world warehouse conditions, enabling comprehensive path planning and real-time modifications, powered by move_base. A camera sensor serves as the robot's safety system, designed to detect moving obstacles and initiate appropriate responses, contributing to the enhancement of warehouse safety standards. Simulation results demonstrate the robot's effectiveness in performing pick-and-place tasks while successfully navigating through the environment, indicating the significant potential for real-world warehouse automation applications. Therefore, this work provides a foundation reference for future research aimed at optimizing and expanding the capabilities of autonomous warehouse robots.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230311

    Verification of using radar vital sign monitors in deception tests (2023)

    This study examines the validity and accuracy of a typical radar-based vital signal monitoring system during spoken responses, a common and necessary scenario in deception tests. Traditional deception tests, such as polygraph tests, often involve testees wearing numerous electrodes, which can induce nervousness and affect their physiological measurements. Additionally, testers may be hindered by the potential Hawthorne effect caused by such varied measurements, while the movement and behavior of testees are typically restricted to ensure data validity. Based on the conclusive findings of this paper, practitioners can employ radar technology to non-invasively extract crucial vital signs during deception tests, ensuring validation. This approach enhances efficiency and affords greater flexibility to testers.

  • Open Access | Article 2024-02-04 Doi: 10.54254/2755-2721/34/20230312

    Adaptive simulation of digital signal transmission

    High-order modulated signals have lower anti-interference ability than low-order modulated signals with the same modulation method and conditions. In situations with low signal-to-noise ratios, the quality of high-order signals can degrade significantly. An algorithm capable of intelligently switching the modulation order based on the current signal-to-noise ratio can effectively address this issue. This paper presents an adaptive signal transmission algorithm that intelligently selects different orders of Phase shift keying (PSK) modulation depending on varying signal noise ratio (SNR) conditions, while ensuring the user-specified upper limit of bit error rate (BER). This approach guarantees signal transmission quality. The algorithm is implemented in Python and involves simulating the relationship curve between SNR and BER for different PSK orders. This simulation is combined with theoretical transmission rate analysis, resulting in an adaptive algorithm that intelligently switches modulation methods under complex conditions to meet transmission requirements. The proposed algorithm dynamically adapts to diverse user requirements for signal-to-noise ratios in various environments. It achieves this by adjusting the modulation order, calculating theoretical transmission times based on the given signal frequency, and ultimately verifying the actual bit error rate through transmission and testing. Upon testing, this design successfully achieved its intended goals.

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