search
Include:
The following results are related to Rural Digital Europe. Are you interested to view more results? Visit OpenAIRE - Explore.
41,326 Research products, page 1 of 4,133

  • Rural Digital Europe
  • Publications
  • Research data
  • 2018-2022
  • Conference object

10
arrow_drop_down
Relevance
arrow_drop_down
  • Publication . Conference object . Article . 2018
    Open Access English
    Authors: 
    Kees Van Teeffelen; Douwe Dresscher; Wietse van Dijk; Stefano Stramigioli;
    Publisher: IEEE Computer Society
    Country: Netherlands

    Humans have multiple ways to adapt their arm dynamics to the task they have to perform. One way of doing this is through co-contraction of antagonist muscles. In telemanipulation this ability is easily lost due to time delays, quantization effects, bandwidth or hardware limitations. In this work a new concept for telemanipulation is presented. The end-point stiffness of a (simulated) telerobot is controlled via a variable impedance controller. The end effector stiffness scales with an estimate of the co-contraction around the elbow of the teleoperator. The telemanipulation concept was evaluated with ten subjects that performed two telemanipulation tasks in six different conditions. Three impedance levels: Low, high, and variable, and two delay settings. The first task was on positioning accuracy, the second task on impact minimization. We have shown that low and variable impedance performed significantly better on the force task than high impedance. We have also shown that high and variable impedance performed significantly better on the position task than low impedance. This shows that the human ability to control arm stiffness can effectively be transferred to a telemanipulated robot.

  • Authors: 
    Prabha Sundaravadivel; Kavya Kesavan; Lokeshwar Kesavan; Saraju P. Mohanty; Elias Kougianos; Madhavi K. Ganapathiraju;
    Publisher: IEEE

    Malnutrition is a condition where the body is deprived of important nutrients required to maintain healthy tissues and organ function. Maintaining the right balance in food intake is very important, especially in infants where tremendous growth occurs. Unlike adults, infants require someone's assistance in their food intake. In the modern world, where most of the infants are being sent to daycare, an automated food monitoring system helps in keeping track of their food intake. In this paper an automated food monitoring system with predictions to help a balanced meal is proposed. This sensor system consists of a piezo-based sensor board which can help in analyzing the weight of each meal and a smart phone camera to obtain nutrition facts of the ingredients.

  • Open Access English
    Authors: 
    Savaglio, C. (Claudio); Leppänen, T. (Teemu); Russo, W. (Wilma); Riekki, J. (Jukka); Fortino, G. (Giancarlo);
    Publisher: RWTH Aachen University
    Country: Finland

    Abstract The Agent-based Cooperating Smart Objects methodology (ACOSO-Meth) fully supports the systematic development of Internet of Things (IoT) systems from analysis to implementation by tackling their manifold requirements (e.g., self-management, distributed smartness, interoperability). At the same time, ACOSO-Meth allows the re-engineering of existing IoT systems, thus enhancing their maintainability, reusability and extensibility. In such direction, this paper (i) first presents the integration of the resource-oriented agent framework complying with the IETF Constrained RESTful Environment (CoRE) framework into ACOSO-Meth; then (ii) reports a case study to exemplify the re-engineering of a resource-constrained agent application through the ACOSO-Meth metamodel-driven approach.

  • Publication . Conference object . Part of book or chapter of book . 2020
    Authors: 
    C.D. Martin; R.S. Read; P.A. Lang;
    Publisher: CRC Press
  • Publication . Conference object . 2019
    Closed Access
    Authors: 
    Zhenling Ma; Xiao Xu; Yannan Chen; Weijie Wang;
    Publisher: IEEE

    This paper further explores bathymetric extraction techniques using overlapping orthoimages in shallow water areas through two-medium ray refraction and multispectral information inversion. In texture-rich areas, a ray refraction method using overlapping orthoimages is developed to calculate the depth information of the underwater features. In texture-less areas, the commonly-used multispectral inversion techniques are applied. The depth information from the ray refraction method acts as the references for the multispectral inversion techniques, therefore, an integrated approach of extracting the shallow bathymetry based on overlapping orthoimages is formed. The results from an aerial overlapping orthoimages experiment show that 0.5 m accuracy can be achieved in the study area. The proposed approach is the combination of two simple methods, and is easy to be implemented and flexible to use, giving that there are a large amount of existing overlapping multispectral orthoimages in water related areas, the proposed approach has the great potentials for the practical use.

  • Authors: 
    Fodio Longman;
    Publisher: Royal Microscopical Society
  • Authors: 
    Hamadi Larthani; Amira Zrelli; Tahar Ezzedine;
    Publisher: IEEE

    In this paper, we discuss the detection of disasters such as floods, earthquake, landslides and fire using optical fiber sensors and IoT technologies especially wireless sensors networks (WSNs). We address the problem of disasters detection systems. then we nodes deployment in this system. Therefore, we treat the case of RPL routing protocols (IPv6 Routing Protocol for Low-Power and Lossy Networks for IoT application used to predict disasters. Indeed, we discuss the significance of node deployment to cover the whole of region where eventual disaster may be established. Moreover, we evaluate temperature and humidity variation on real time through optical sensors.

  • Closed Access
    Authors: 
    Yiqi Yang; Tao Sun; Zhuangzhuang Zhang; Kaiyi Xie; Xiaoxiao Zhu; Qixin Cao;
    Publisher: IEEE

    The paper proposed dual-arm robot for avionics systems testing according to the limited space in cabinet. The robot included two commercial collaborative robots KUKA LBRIIWA7, a robotic torso with one prismatic joint in each side and a control unit. Based on modified D-H method, the paper established kinematic model of the two arms. Meanwhile, the workspace of dual-arm robot was obtained by both geometric method and Monte Carlo method. The common part in two results matched well. Through taking end effector into consideration, several criterions for avionics system testing robot was raised and the parameters of the robot was optimized. By using the Robotics Toolbox in matlab, the inverse kinematics of all goal points was solved as required. The result proved that our proposed dual-arm robot had at least one feasible solution for all the avionics system testing targets, which laid a foundation for later motion planning of robot.

  • Authors: 
    S Ruchi; Pravin Srinath;
    Publisher: IEEE

    In recent years, enterprise related data is becoming increasingly digitized. Due to the exponential volume of enterprise data being generated, there is an increased demand in managing this data for efficient decision making. Data Mining and machine learning aids in achieving valuable insight of a business and its growth through the exploration of data by recognizing business project relationships and dependencies. Enterprise project data is a subset of enterprise data being created online or offline. This paper presents the proposed architectural design and related concept explanation for efficient enterprise project management in current data scenario. Also, an analysis of the current enterprise project techniques has been presented along with challenges that need to be addressed.

  • Authors: 
    Sunit Fulari;
    Publisher: IEEE

    Object detection in videos is widely used in entertainment, robotics, surveillance etc. A major challenge in effective object detection is observed when there is occlusion, bad illumination or cluttered background. Besides, cameras do not provide any mechanism for detecting moving objects after capture. Researchers have proposed different methods for object detection in video frames, ranging from traditional to deep learning approaches. However, using the right method in the right situation for efficient and accurate detection is a concern. Even though deep learning has shown high accuracy in detection, the training and testing time and cost is a concern. In our research, we explore the best motion models for tracking objects in a video sequence. The characteristics of each model was analyzed and the results were compared using different types of videos. Our observations determine that depending on the quality of input video, traditional approaches show high accuracy in detection, comparable to state-of-the art methods.

search
Include:
The following results are related to Rural Digital Europe. Are you interested to view more results? Visit OpenAIRE - Explore.
41,326 Research products, page 1 of 4,133
  • Publication . Conference object . Article . 2018
    Open Access English
    Authors: 
    Kees Van Teeffelen; Douwe Dresscher; Wietse van Dijk; Stefano Stramigioli;
    Publisher: IEEE Computer Society
    Country: Netherlands

    Humans have multiple ways to adapt their arm dynamics to the task they have to perform. One way of doing this is through co-contraction of antagonist muscles. In telemanipulation this ability is easily lost due to time delays, quantization effects, bandwidth or hardware limitations. In this work a new concept for telemanipulation is presented. The end-point stiffness of a (simulated) telerobot is controlled via a variable impedance controller. The end effector stiffness scales with an estimate of the co-contraction around the elbow of the teleoperator. The telemanipulation concept was evaluated with ten subjects that performed two telemanipulation tasks in six different conditions. Three impedance levels: Low, high, and variable, and two delay settings. The first task was on positioning accuracy, the second task on impact minimization. We have shown that low and variable impedance performed significantly better on the force task than high impedance. We have also shown that high and variable impedance performed significantly better on the position task than low impedance. This shows that the human ability to control arm stiffness can effectively be transferred to a telemanipulated robot.

  • Authors: 
    Prabha Sundaravadivel; Kavya Kesavan; Lokeshwar Kesavan; Saraju P. Mohanty; Elias Kougianos; Madhavi K. Ganapathiraju;
    Publisher: IEEE

    Malnutrition is a condition where the body is deprived of important nutrients required to maintain healthy tissues and organ function. Maintaining the right balance in food intake is very important, especially in infants where tremendous growth occurs. Unlike adults, infants require someone's assistance in their food intake. In the modern world, where most of the infants are being sent to daycare, an automated food monitoring system helps in keeping track of their food intake. In this paper an automated food monitoring system with predictions to help a balanced meal is proposed. This sensor system consists of a piezo-based sensor board which can help in analyzing the weight of each meal and a smart phone camera to obtain nutrition facts of the ingredients.

  • Open Access English
    Authors: 
    Savaglio, C. (Claudio); Leppänen, T. (Teemu); Russo, W. (Wilma); Riekki, J. (Jukka); Fortino, G. (Giancarlo);
    Publisher: RWTH Aachen University
    Country: Finland

    Abstract The Agent-based Cooperating Smart Objects methodology (ACOSO-Meth) fully supports the systematic development of Internet of Things (IoT) systems from analysis to implementation by tackling their manifold requirements (e.g., self-management, distributed smartness, interoperability). At the same time, ACOSO-Meth allows the re-engineering of existing IoT systems, thus enhancing their maintainability, reusability and extensibility. In such direction, this paper (i) first presents the integration of the resource-oriented agent framework complying with the IETF Constrained RESTful Environment (CoRE) framework into ACOSO-Meth; then (ii) reports a case study to exemplify the re-engineering of a resource-constrained agent application through the ACOSO-Meth metamodel-driven approach.

  • Publication . Conference object . Part of book or chapter of book . 2020
    Authors: 
    C.D. Martin; R.S. Read; P.A. Lang;
    Publisher: CRC Press
  • Publication . Conference object . 2019
    Closed Access
    Authors: 
    Zhenling Ma; Xiao Xu; Yannan Chen; Weijie Wang;
    Publisher: IEEE

    This paper further explores bathymetric extraction techniques using overlapping orthoimages in shallow water areas through two-medium ray refraction and multispectral information inversion. In texture-rich areas, a ray refraction method using overlapping orthoimages is developed to calculate the depth information of the underwater features. In texture-less areas, the commonly-used multispectral inversion techniques are applied. The depth information from the ray refraction method acts as the references for the multispectral inversion techniques, therefore, an integrated approach of extracting the shallow bathymetry based on overlapping orthoimages is formed. The results from an aerial overlapping orthoimages experiment show that 0.5 m accuracy can be achieved in the study area. The proposed approach is the combination of two simple methods, and is easy to be implemented and flexible to use, giving that there are a large amount of existing overlapping multispectral orthoimages in water related areas, the proposed approach has the great potentials for the practical use.

  • Authors: 
    Fodio Longman;
    Publisher: Royal Microscopical Society
  • Authors: 
    Hamadi Larthani; Amira Zrelli; Tahar Ezzedine;
    Publisher: IEEE

    In this paper, we discuss the detection of disasters such as floods, earthquake, landslides and fire using optical fiber sensors and IoT technologies especially wireless sensors networks (WSNs). We address the problem of disasters detection systems. then we nodes deployment in this system. Therefore, we treat the case of RPL routing protocols (IPv6 Routing Protocol for Low-Power and Lossy Networks for IoT application used to predict disasters. Indeed, we discuss the significance of node deployment to cover the whole of region where eventual disaster may be established. Moreover, we evaluate temperature and humidity variation on real time through optical sensors.

  • Closed Access
    Authors: 
    Yiqi Yang; Tao Sun; Zhuangzhuang Zhang; Kaiyi Xie; Xiaoxiao Zhu; Qixin Cao;
    Publisher: IEEE

    The paper proposed dual-arm robot for avionics systems testing according to the limited space in cabinet. The robot included two commercial collaborative robots KUKA LBRIIWA7, a robotic torso with one prismatic joint in each side and a control unit. Based on modified D-H method, the paper established kinematic model of the two arms. Meanwhile, the workspace of dual-arm robot was obtained by both geometric method and Monte Carlo method. The common part in two results matched well. Through taking end effector into consideration, several criterions for avionics system testing robot was raised and the parameters of the robot was optimized. By using the Robotics Toolbox in matlab, the inverse kinematics of all goal points was solved as required. The result proved that our proposed dual-arm robot had at least one feasible solution for all the avionics system testing targets, which laid a foundation for later motion planning of robot.

  • Authors: 
    S Ruchi; Pravin Srinath;
    Publisher: IEEE

    In recent years, enterprise related data is becoming increasingly digitized. Due to the exponential volume of enterprise data being generated, there is an increased demand in managing this data for efficient decision making. Data Mining and machine learning aids in achieving valuable insight of a business and its growth through the exploration of data by recognizing business project relationships and dependencies. Enterprise project data is a subset of enterprise data being created online or offline. This paper presents the proposed architectural design and related concept explanation for efficient enterprise project management in current data scenario. Also, an analysis of the current enterprise project techniques has been presented along with challenges that need to be addressed.

  • Authors: 
    Sunit Fulari;
    Publisher: IEEE

    Object detection in videos is widely used in entertainment, robotics, surveillance etc. A major challenge in effective object detection is observed when there is occlusion, bad illumination or cluttered background. Besides, cameras do not provide any mechanism for detecting moving objects after capture. Researchers have proposed different methods for object detection in video frames, ranging from traditional to deep learning approaches. However, using the right method in the right situation for efficient and accurate detection is a concern. Even though deep learning has shown high accuracy in detection, the training and testing time and cost is a concern. In our research, we explore the best motion models for tracking objects in a video sequence. The characteristics of each model was analyzed and the results were compared using different types of videos. Our observations determine that depending on the quality of input video, traditional approaches show high accuracy in detection, comparable to state-of-the art methods.