69 research outputs found

    Temperature Control System in Closed House for Broilers Based on ANFIS

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     Indonesia is a tropical country with high ambient temperatures for broilers since daily temperature reaches an average daily temperature of 360C (maximum) and 320 C (minimum); whereas the optiml temperature for broilers is in the range of 28-300C. Thefefore, midle or large scale broiler industries have been using a control system to maintain the optimal temperature within a broiler house. Therefore, the role of a control system for regulating environmental parameters, not only temperature but also humidity, light intensity, and amonia content level, is very critical and relevant for better broiler production. This study aims to design an ANFIS control system for controlling the temperature inside a broiler house (closed house) for broiler. Data is collected at three different periods of the starter period (5 days): 29.50C-30.900C, a period of 25 days is a grower-29.0C 34.20C, and the finisher of 30 days is obtained 33.20C. Set point control simulation using the same temperature 290C for starter, grower and finisher period. The simulation results show the output in a closed house temperature fluctuates around set point the 290C-340C

    The Brain Computer Interface: A Review and Some New Concepts

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    Over the past decade, many laboratories have begun to explore brain computer interface (BCI) technology as a new communication option for those with neuromuscular impairments that prevent them from using conventional augmentative communication methods. This work outlines the potential benefits of BCI, summarises a number of developments which have been made in recent years and provides an overview of the fundamental requirements which must be acknowledged for the successful progression of BCI technology. A novel proposal for a unique BCI system is also detailed

    Detecting and Modelling Stress Levels in E-Learning Environment Users

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    A modern Intelligent Tutoring System (ITS) should be sentient of a learner's cognitive and affective states, as a learner’s performance could be affected by motivational and emotional factors. It is important to design a method that supports low-cost, task-independent and unobtrusive sensing of a learner’s cognitive and affective states, to improve a learner's experience in e-learning, as well as to enable personalized learning. Although tremendous related affective computing research were done in this area, there is a lack of empirical research that can automatically measure a learner's stress using objective methods. This research is set to examine how an objective stress measurement model can be developed, to compute a learner’s cognitive and emotional stress automatically using mouse and keystroke dynamics. To ensure the measurement is not affected even if the user switches between tasks, three preliminary research experiments were carried out based on three common tasks during e-learning − search, assessment and typing. A stress measurement model was then built using the datasets collected from the experiments. Three stress classifiers were tested, namely certainty factors, feedforward back-propagation neural network and adaptive neuro-fuzzy inference system. The best classifier was then integrated into the ITS stress inference engine, which is designed to decide necessary adaptation, and to provide analytical information of learners' performances, which include stress levels and learners’ behaviours when answering questions

    Some aspects of human performance in a Human Adaptive Mechatronics (HAM) system

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    An interest in developing the intelligent machine system that works in conjunction with human has been growing rapidly in recent years. A number of studies were conducted to shed light on how to design an interactive, adaptive and assistive machine system to serve a wide range of purposes including commonly seen ones like training, manufacturing and rehabilitation. In the year 2003, Human Adaptive Mechatronics (HAM) was proposed to resolve these issues. According to past research, the focus is predominantly on evaluation of human skill rather than human performance and that is the reason why intensive training and selection of suitable human subjects for those experiments were required. As a result, the pattern and state of control motion are of critical concern for these works. In this research, a focus on human skill is shifted to human performance instead due to its proneness to negligence and lack of reflection on actual work quality. Human performance or Human Performance Index (HPI) is defined to consist of speed and accuracy characteristics according to a well-renowned speed-accuracy trade-off or Fitts’ Law. Speed and accuracy characteristics are collectively referred to as speed and accuracy criteria with corresponding contributors referred to as speed and accuracy variables respectively. This research aims at proving a validity of the HPI concept for the systems with different architecture or the one with and without hardware elements. A direct use of system output logged from the operating field is considered the main method of HPI computation, which is referred to as a non-model approach in this thesis. To ensure the validity of these results, they are compared against a model-based approach based on System Identification theory. Its name is due to being involved with a derivation of mathematical equation for human operator and extraction of performance variables. Certain steps are required to match the processing outlined in that of non-model approach. Some human operators with complicated output patterns are inaccurately derived and explained by the ARX models

    Gaze tracking algorithm using night vision camera

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    Nowadays, the advancement of medical technology has given birth into many innovative machines and devices to improve our health life, especially to those who are disabled or gifted. On some people with severe disabilities such as quadriplegia, the human eye-ball does not only serve as a vision system, but also a means of conveying information and intention to other people. This is because although quadriplegic patients suffer the loss of motor sensory functions from the neck and below, upper neck functions such as the vision system is normally spared. This enables the patient to control the movement of his/her eyeballs to convey desired information. Although many similar researches have been done, this paper proposes the use of image processing on image captured using webcam with its Infra-Red (IR) filter removed (a.k.a night vision) to achieve robustness. This allows the algorithm to properly track the location of the iris despite of its and the pupil color variations. Two image processing algorithms are then used, each with owns tradeoff between speed and accuracy. Analysis on both algorithms shows good tracking performance despite of the mentioned tradeoff

    UFGM - 2006 Annual Report

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    INGV, SEZIONE DI CATANIAPublished2.6. TTC - Laboratorio di gravimetria, magnetismo ed elettromagnetismo in aree attiveope

    A Human−Computer Interface Replacing Mouse and Keyboard for Individuals with Limited Upper Limb Mobility

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    People with physical disabilities in their upper extremities face serious issues in using classical input devices due to lacking movement possibilities and precision. This article suggests an alternative input concept and presents corresponding input devices. The proposed interface combines an inertial measurement unit and force sensing resistors, which can replace mouse and keyboard. Head motions are mapped to mouse pointer positions, while mouse button actions are triggered by contracting mastication muscles. The contact pressures of each fingertip are acquired to replace the conventional keyboard. To allow for complex text entry, the sensory concept is complemented by an ambiguous keyboard layout with ten keys. The related word prediction function provides disambiguation at word level. Haptic feedback is provided to users corresponding to their virtual keystrokes for enhanced closed-loop interactions. This alternative input system enables text input as well as the emulation of a two-button mouse

    Real-time EMG based pattern recognition control for hand prostheses : a review on existing methods, challenges and future implementation

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    Upper limb amputation is a condition that significantly restricts the amputees from performing their daily activities. The myoelectric prosthesis, using signals from residual stump muscles, is aimed at restoring the function of such lost limbs seamlessly. Unfortunately, the acquisition and use of such myosignals are cumbersome and complicated. Furthermore, once acquired, it usually requires heavy computational power to turn it into a user control signal. Its transition to a practical prosthesis solution is still being challenged by various factors particularly those related to the fact that each amputee has different mobility, muscle contraction forces, limb positional variations and electrode placements. Thus, a solution that can adapt or otherwise tailor itself to each individual is required for maximum utility across amputees. Modified machine learning schemes for pattern recognition have the potential to significantly reduce the factors (movement of users and contraction of the muscle) affecting the traditional electromyography (EMG)-pattern recognition methods. Although recent developments of intelligent pattern recognition techniques could discriminate multiple degrees of freedom with high-level accuracy, their efficiency level was less accessible and revealed in real-world (amputee) applications. This review paper examined the suitability of upper limb prosthesis (ULP) inventions in the healthcare sector from their technical control perspective. More focus was given to the review of real-world applications and the use of pattern recognition control on amputees. We first reviewed the overall structure of pattern recognition schemes for myo-control prosthetic systems and then discussed their real-time use on amputee upper limbs. Finally, we concluded the paper with a discussion of the existing challenges and future research recommendations
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