Deep Learning Based Gesture Classification for Hand Physical Therapy Interactive Program

Rungruanganukul, Maleewan; Siriborvornratanakul, Thitirat

doi:10.1007/978-3-030-49904-4_26

Cited by 17 publications

(18 citation statements)

References 5 publications

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“…For example, a deep learning framework trains convolutional neural networks as a part of an artificial intelligent characteristic of a cooperative game intending to inspire the white-collar workers to exercise their hands and wrists regularly by playing a game. This network aims to classify a still image into one of the six predefined classes of gestures, and it looks to cope well with small variations in size, skin tone, position, and orientation of the hand [31]. An architecture focuses on finding the overall sentiments and feelings of related topics with reference to a given topic was developed [32].…”

Section: Recent Studies In Social Networking Recommendationmentioning

confidence: 99%

Cosine similarity-based algorithm for social networking recommendation

Al-Otaibi

Altwoijry

Alqahtani

et al. 2022

IJECE

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Social media have become a discussion platform for individuals and groups. Hence, users belonging to different groups can communicate together. Positive and negative messages as well as media are circulated between those users. Users can form special groups with people who they already know in real life or meet through social networking after being suggested by the system. In this article, we propose a framework for recommending communities to users based on their preferences; for example, a community for people who are interested in certain sports, art, hobbies, diseases, age, case, and so on. The framework is based on a feature extraction algorithm that utilizes user profiling and combines the cosine similarity measure with term frequency to recommend groups or communities. Once the data is received from the user, the system tracks their behavior, the relationships are identified, and then the system recommends one or more communities based on their preferences. Finally, experimental studies are conducted using a prototype developed to test the proposed framework, and results show the importance of our framework in recommending people to communities.

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Section: Recent Studies In Social Networking Recommendationmentioning

confidence: 99%

Cosine similarity-based algorithm for social networking recommendation

Al-Otaibi

Altwoijry

Alqahtani

et al. 2022

IJECE

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“…However, active power filters have a very high cost for high rating of power so a hybrid power filters are presented [7]- [10]. Vision-based technology such as using deep learning for useful insights into issues [11], the artificial intelligence and augmented reality developed during the COVID-19 outbreak [12]. According to the researches, a filter or compensator is the best solution to remove the liability of the utilities in light of the existence of specific and wide-ranging impacts on the client or the existence of legislation that requires limited levels of harmonics.…”

Section: Introductionmentioning

confidence: 99%

Power quality improvement of distribution systems asymmetry caused by power disturbances based on particle swarm optimization-artificial neural network

Saeed

Sheikhyounis

2022

IJEECS

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With an increase of non-linear load in today’s electrical power systems, the rate of power quality drops and the voltage source and frequency deteriorate if not properly compensated with an appropriate device. Filters are most common techniques that employed to overcome this problem and improving power quality. In this paper an improved optimization technique of filter applies to the power system is based on a particle swarm optimization with using artificial neural network technique applied to the unified power flow quality conditioner (PSO-ANN UPQC). Design particle swarm optimization and artificial neural network together result in a very high performance of flexible AC transmission lines (FACTs) controller and it implements to the system to compensate all types of power quality disturbances. This technique is very powerful for minimization of total harmonic distortion of source voltages and currents as a limit permitted by IEEE-519. The work creates a power system model in MATLAB/Simulink program to investigate our proposed optimization technique for improving control circuit of filters. The work also has measured all power quality disturbances of the electrical arc furnace of steel factory and suggests this technique of filter to improve the power quality.

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“…The numerous advantages of wireless network communication have been achieved by using IoT. Researchers in [20]- [24] and [25]- [29] have focused on the security system from different perspectives, such as utilizing [25], so the image is classified by the trained network into six classes of gestures to monitor and encourage the worker to exercise hands and wrists frequently through playing the game. This paper has not focused on vision-based technology only because sensing the movement in this paper is enough to protect the dedicated area and it can be adapted with any other systems such as vision technology.…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of an adaptive multilevel wireless security system using IoT

Sultan

Saeed

Sana

2021

IJEECS

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Securing property plays a crucial role in human life. Therefore, an adaptive multilevel wireless security system (ML-WSS) based on the internet of things (IoT) has been proposed to observe and secure a certain place. ML-WSS consists of hardware and software components, such as a set of sensors, Wi-Fi module, and operation and monitoring mobile application (OMM). The OMM application is designed to remotely monitor and control the proposed system through the Internet and by using ThingSpeak cloud as a data store. The proposed scheme is based on dividing the required zone of the place into three regions (levels), low-risk region (LRR) as level-1, moderate-risk region (MRR) level-2, and high-risk region (HRR) as level-3. Each level may contain one or set of sensors, so the number of sensors, their placement, and under which level is labelled is specified according to the security requirements. Several processes are done based on these levels when a breach occurs in the system. Mathematical model and pseudocode were created to illustrate the mechanism of the proposed system. The results show that the proposed system has been implemented successfully and the number of breaches that occurs in level-3 area was reduced by 50% as compared to level-1.

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Deep Learning Based Gesture Classification for Hand Physical Therapy Interactive Program

Cited by 17 publications

References 5 publications

Cosine similarity-based algorithm for social networking recommendation

Cosine similarity-based algorithm for social networking recommendation

Power quality improvement of distribution systems asymmetry caused by power disturbances based on particle swarm optimization-artificial neural network

Design and implementation of an adaptive multilevel wireless security system using IoT

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