• Title/Summary/Keyword: python language

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Design and Implementation of the ChamCham and WordChain Play Robot for Reduction of Symptoms of Depressive Disorder Patient (우울증 진단 환자의 증상 완화를 위한 참참참, 끝말잇기 놀이 로봇 설계 및 구현)

  • Eom, Hyun-Young;Seo, Dong-Yoon;Lee, Gyeong-Min;Lee, Seong-Ung;Choi, Ji-Hwan;Lee, Kang-Hee
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.2
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    • pp.561-566
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    • 2020
  • We propose to design and to implement a recreational and end - of - play robot for symptom relief in patients with depression. The main symptom of depression is the loss of interest and interest in life. The depression diagnosis patient confirms the emotional analysis revealed by his / her robot through the robot, and performs the greeting or ending play. After analyzing the emotions in the expressions after the play, the function of the embodying robot is confirmed by receiving the report. A simple play can not completely cure a patient with a diagnosis of depression, but it can contribute to symptom relief through gradual use. The design of the play-by-play robot is using Q.bo One, an open-source robot that can interact with Thecorpora. Q.bo One's system captures a user's face, takes a picture, passes the value to the Azure server, and checks the emotional analysis before and after the play with the accumulated data.Play is implemented in Rasubian, the OS of Q.bo One, using the programming language Python and interacting with external sensors. The purpose of this paper is to help the symptom relief of depressive patients in a relatively short time with a play robot.

A Convergence Study of the Research Trends on Stress Urinary Incontinence using Word Embedding (워드임베딩을 활용한 복압성 요실금 관련 연구 동향에 관한 융합 연구)

  • Kim, Jun-Hee;Ahn, Sun-Hee;Gwak, Gyeong-Tae;Weon, Young-Soo;Yoo, Hwa-Ik
    • Journal of the Korea Convergence Society
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    • v.12 no.8
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    • pp.1-11
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    • 2021
  • The purpose of this study was to analyze the trends and characteristics of 'stress urinary incontinence' research through word frequency analysis, and their relationships were modeled using word embedding. Abstract data of 9,868 papers containing abstracts in PubMed's MEDLINE were extracted using a Python program. Then, through frequency analysis, 10 keywords were selected according to the high frequency. The similarity of words related to keywords was analyzed by Word2Vec machine learning algorithm. The locations and distances of words were visualized using the t-SNE technique, and the groups were classified and analyzed. The number of studies related to stress urinary incontinence has increased rapidly since the 1980s. The keywords used most frequently in the abstract of the paper were 'woman', 'urethra', and 'surgery'. Through Word2Vec modeling, words such as 'female', 'urge', and 'symptom' were among the words that showed the highest relevance to the keywords in the study on stress urinary incontinence. In addition, through the t-SNE technique, keywords and related words could be classified into three groups focusing on symptoms, anatomical characteristics, and surgical interventions of stress urinary incontinence. This study is the first to examine trends in stress urinary incontinence-related studies using the keyword frequency analysis and word embedding of the abstract. The results of this study can be used as a basis for future researchers to select the subject and direction of the research field related to stress urinary incontinence.

A Study on the Development of a Program for Predicting Successful Welding of Electric Vehicle Batteries Using Laser Welding (레이저 용접을 이용한 전기차 배터리 이종접합 성공 확률 예측 프로그램 개발에 관한 연구)

  • Cheol-Hwan Kim;Chan-Su Moon;Kwan-Su Lee;Jin-Su Kim;Ae-Ryeong Jo;Bo-Sung Shin
    • Journal of the Microelectronics and Packaging Society
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    • v.30 no.4
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    • pp.44-49
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    • 2023
  • In the global pursuit of carbon neutrality, the rapid increase in the adoption of electric vehicles (EVs) has led to a corresponding surge in the demand for batteries. To achieve high efficiency in electric vehicles, considerations of weight reduction and battery safety have become crucial factors. Copper and aluminum, both recognized as lightweight materials, can be effectively joined through laser welding. However, due to the distinct physical characteristics of these two materials, the process of joining them poses technical challenges. This study focuses on conducting simulations to identify the optimal laser parameters for welding copper and aluminum, with the aim of streamlining the welding process. Additionally, a Graphic User Interface (GUI) program has been developed using the Python language to visually present the results. Using machine learning image data, this program is anticipated to predict joint success and serve as a guide for safe and efficient laser welding. It is expected to contribute to the safety and efficiency of the electric vehicle battery assembly process.

Development and application of automation algorithm for optimal parameter combination in two-dimensional flow analysis model (2차원 흐름해석모형의 매개변수 최적조합결정 자동화 알고리즘의 개발과 적용)

  • An, Sehyuck;Shin, Eun-taek;Song, Chang Geun;Park, Sungwon
    • Journal of Korea Water Resources Association
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    • v.56 no.spc1
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    • pp.1007-1014
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    • 2023
  • Two-dimensional flow analysis, a fundamental component of hydrodynamics, plays a pivotal role in numerically simulating fluid behavior in rivers and waterways. This modeling approach heavily relies on parameters such as eddy viscosity and roughness coefficient to accurately represent flow characteristics. Therefore, combination of appropriate parameters is very important to accurately simulate flow characteristics. In this study, an automation algorithm was developed and applied to find the optimal combination of parameters. Previously, when applying a two-dimensional flow analysis model, former researchers usually depend on the empirical approach, which causes many difficulties in finding optimal variable values. Using the experimental data, we tracked errors according to the combination of various parameters and applied the algorithm that can determine the optimal combination of parameters with the Python language. The automation algorithm can easily determine the most accurate combination by comparing the flow velocity error values among the two-dimensional flow analysis results among the combinations of 121 (11×11) parameters. In the perspective of utilizing automation algorithm, there is an expected high utility in promptly and straightforwardly determining the optimal combination of parameters with the smallest error.

Design and Implementation of IoT based Low cost, Effective Learning Mechanism for Empowering STEM Education in India

  • Simmi Chawla;Parul Tomar;Sapna Gambhir
    • International Journal of Computer Science & Network Security
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    • v.24 no.4
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    • pp.163-169
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    • 2024
  • India is a developing nation and has come with comprehensive way in modernizing its reducing poverty, economy and rising living standards for an outsized fragment of its residents. The STEM (Science, Technology, Engineering, and Mathematics) education plays an important role in it. STEM is an educational curriculum that emphasis on the subjects of "science, technology, engineering, and mathematics". In traditional education scenario, these subjects are taught independently, but according to the educational philosophy of STEM that teaches these subjects together in project-based lessons. STEM helps the students in his holistic development. Youth unemployment is the biggest concern due to lack of adequate skills. There is a huge skill gap behind jobless engineers and the question arises how we can prepare engineers for a better tomorrow? Now a day's Industry 4.0 is a new fourth industrial revolution which is an intelligent networking of machines and processes for industry through ICT. It is based upon the usage of cyber-physical systems and Internet of Things (IoT). Industrial revolution does not influence only production but also educational system as well. IoT in academics is a new revolution to the Internet technology, which introduced "Smartness" in the entire IT infrastructure. To improve socio-economic status of the India students must equipped with 21st century digital skills and Universities, colleges must provide individual learning kits to their students which can help them in enhancing their productivity and learning outcomes. The major goal of this paper is to present a low cost, effective learning mechanism for STEM implementation using Raspberry Pi 3+ model (Single board computer) and Node Red open source visual programming tool which is developed by IBM for wiring hardware devices together. These tools are broadly used to provide hands on experience on IoT fundamentals during teaching and learning. This paper elaborates the appropriateness and the practicality of these concepts via an example by implementing a user interface (UI) and Dashboard in Node-RED where dashboard palette is used for demonstration with switch, slider, gauge and Raspberry pi palette is used to connect with GPIO pins present on Raspberry pi board. An LED light is connected with a GPIO pin as an output pin. In this experiment, it is shown that the Node-Red dashboard is accessing on Raspberry pi and via Smartphone as well. In the final step results are shown in an elaborate manner. Conversely, inadequate Programming skills in students are the biggest challenge because without good programming skills there would be no pioneers in engineering, robotics and other areas. Coding plays an important role to increase the level of knowledge on a wide scale and to encourage the interest of students in coding. Today Python language which is Open source and most demanding languages in the industry in order to know data science and algorithms, understanding computer science would not be possible without science, technology, engineering and math. In this paper a small experiment is also done with an LED light via writing source code in python. These tiny experiments are really helpful to encourage the students and give play way to learn these advance technologies. The cost estimation is presented in tabular form for per learning kit provided to the students for Hands on experiments. Some Popular In addition, some Open source tools for experimenting with IoT Technology are described. Students can enrich their knowledge by doing lots of experiments with these freely available software's and this low cost hardware in labs or learning kits provided to them.

Control Technology Based on the Finger Recognition of Robot Cleaners (손가락 인식을 기반으로 한 로봇청소기 제어기술)

  • Yoo, Hyang-Joon;Mok, Seung-Su;Kim, Jun-Seo;Baek, Ji-A;Ko, Yun-Seok
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.1
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    • pp.139-146
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    • 2020
  • The disadvantage of the general robot cleaner is that it works only on the designated route, so it is impossible to clean the place outside the designated route. Therefore, in this study, the direction control methodology for searching the place other than the designated route based on the finger recognition technology was studied to compensate for the shortcomings of the existing cleaner. Raspberry Pi was used as the main controller and Open CV program was used to recognize the number of fingers. To verify the validity of the proposed methodology, a finger recognition algorithm was implemented using Python language, and as a result of adopting the Logitech C922, the success rate was 100% at 90cm and 70% at 110cm, respectively.

The Study on LCS Embedded Design of Traffic Signal Evaluation System HILS (교통신호 평가시스템 HILS에서의 LCS 임베디드 설계 연구)

  • Kim, Bong seob;Lee, Jeong jun;Koo, Seung Hoe
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.18 no.6
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    • pp.1-10
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    • 2019
  • Traffic Signal Evaluation HILS is a system designed to evaluate a traffic signal system, and has a function of driving that simulates a real environment using a simulator that simulates a real traffic signal environment and an LCS that simulates a traffic signal controller. This study simulates the function of the traffic signal controller and is designed for design the LCS which is connected to the center system and the traffic simulator (VISSIM). The design of the LCS program uses a portable python language, and the code is designed in two versions running on Windows in the PC environment and unning on embedded environment, with a slight modification of the code. In this study, we analyzed the limitations of using LCS on Windows in PC environment and confirmed the ease of simulation Linux in embedded environment at large capacity.

Development of a Navigation Control Algorithm for Mobile Robots Using D* Search and Fuzzy Algorithm (D* 서치와 퍼지 알고리즘을 이용한 모바일 로봇의 충돌회피 주행제어 알고리즘 설계)

  • Jung, Yun-Ha;Park, Hyo-Woon;Lee, Sang-Jin;Won, Moon-Cheol
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.34 no.8
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    • pp.971-980
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    • 2010
  • In this paper, we present a navigation control algorithm for mobile robots that move in environments having static and moving obstacles. The algorithm includes a global and a local path-planning algorithm that uses $D^*$ search algorithm, a fuzzy logic for determining the immediate level of danger due to collision, and a fuzzy logic for evaluating the required wheel velocities of the mobile robot. To apply the $D^*$ search algorithm, the two-dimensional space that the robot moves in is decomposed into small rectangular cells. The algorithm is verified by performing simulations using the Python programming language as well as by using the dynamic equations for a two-wheeled mobile robot. The simulation results show that the algorithm can be used to move the robot successfully to reach the goal position, while avoiding moving and unknown static obstacles.

Scenic Image Research Based on Big Data Analysis - Take China's Four Ancient Cities as an Example

  • Liang, Rui;Guo, Hanwen;Liu, Jiayu;Liu, Ziyang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.7
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    • pp.2769-2784
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    • 2020
  • This paper aims to compare the scenic images of four ancient Chinese cities including Lijiang, Pingyao, Huizhou and Langzhong, so as to provide specific development strategies for the ancient cities. In this paper, the ancient cities' scenic images are divided into three sub-indexes and eight evaluation dimensions. Based on this, the study first uses Python software to collect tourists' online comments on the four ancient cities. Then, the social network analysis method is used to build a high-frequency keywords matrix of tourist comments and the R language is used to generate a visual network graph. After this, the entropy weight method is used to determine the weights and values of eight evaluation dimensions. Finally, the tourists' overall satisfaction indexes of the four ancient cities are calculated accordingly. The results show that (1) the overall satisfaction of Lijiang is the highest, while that of Huizhou is the lowest; (2) from the weight of each evaluation dimension, it can be seen that tourists care more about the national culture and historical culture; (3) from tourists' satisfaction index on each evaluation dimension of the four ancient cities, we can find that the four ancient cities has their own advantages and disadvantages in tourism development. (4) local tourism-related institutions should strengthen their advantages and improve their deficiencies so as to enhance tourists' overall image of the ancient city.

Study of Image Production using Steadicam Effects for 3D Camera (3D 카메라 기반 스테디캠 효과를 적용한 영상제작에 관한연구)

  • Lee, Junsang;Park, Sungdae;Lee, Imgeun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.12
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    • pp.3035-3041
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    • 2014
  • The steadicam effects is widely used in production of the 3D animation for natural camera movement. Conventional method for steadicam effects is using keyframe animation technique, which is annoying and time consuming process. Furthermore it is difficult and unnatural to simulate camera movement in real world. In this paper we propose a novel method for representing steadicam effects on virtual camera of 3D animation. We modeled a camera of real world into Maya production tools, considering gravity, mass and elasticity. The model is implemented with Python language, which is directly applied to Maya platform as a filter module. The proposed method reduces production time and improves production environment. It also makes more natural and realistic footage to maximize visual effects.