Learning is a process of acquisition, depending on experience, thanks to which certain activities... more Learning is a process of acquisition, depending on experience, thanks to which certain activities/behaviours are formed or modified under the influence of repetitive and variable world conditions. Learning is a human-specific evolutionary process, consisting in acquiring the experience of life. Schools have an important role in promoting learning, introducing us to the secrets of knowledge. Questions like 'Why does learning take place?' or 'How does learning take place?', led to theories and models of instruction (learning). 'The theory explains the process, and the model describes it', says . The first question is answered by explaining the deep mechanisms of the learning process and its causal determinations. As regards the second question, , for example, finds that learning is associated with several knowledge paradigms, one of which, relevant here, advances the idea that school learning is a process of O. Geman (B)
This editorial summarises the special issue entitled "Deep Learning Blockchain-enabled Technology... more This editorial summarises the special issue entitled "Deep Learning Blockchain-enabled Technology for Improved Healthcare Industrial Systems", which deals with the intersection and use of deep learning and blockchain technologies in the healthcare industry. This special issue consists of eleven scientific articles.
Computational Intelligence and Neuroscience, Sep 15, 2022
e development of unusual cells in the cerebrum causes brain cancer. It is classi ed primarily int... more e development of unusual cells in the cerebrum causes brain cancer. It is classi ed primarily into two classes: a noncarcinogenic (benign) type of growth and cancerous (malignant) growth. Early detection of this disease is a quintessential task for all medical practice professionals. For traditional approaches of tumor detections, certain limitations exist. ey include less e ectiveness, inability to detect due to low-quality processing of images, less dataset for training and testing, less predictive nature to models, and skipping of quintessential stages. All these lead to inaccurate results of tumor detections. To overcome this issue, this paper brings an e ective deep learning technique for brain tumor detection with the following stages: (a) data collection from REMBRANDT dataset containing multisequence MRI of 130 patients; (b) preprocessing using conversion to greyscale, skull stripping, and histogram equalization; (c) segmentation uses genetic algorithm; (d) feature extraction using discrete wavelet transform (DWT); (e) particle swarm optimization technique for feature selection; (f) classi cation using U-Net. Experiment evaluation states that the proposed model (GA-UNET) outperforms (accuracy: 0.97, sensitivity: 0.98, speci city: 0.98) compared to other advanced models.
The IoT concept plays an important role in healthcare systems. This paper presents a sensors netw... more The IoT concept plays an important role in healthcare systems. This paper presents a sensors network based on interdigital capacitive sensor that is incorporated in clothes in order to build a device for screening and management of patients with Diabetic Neuropathy. The use of interdigital capacitive sensors embedded in clothes is a viable manner for monitoring the tremor of various parts of the body, including legs, neck and head. This method of monitoring, using capacitive sensors inserted in clothes is proper for the analysis of the subject's daily activity and in order to determine the patient's evolution and early detection of the modifications produced by Diabetic Neuropathy. Future work would supplement the system with wearable photovoltaic modules, or other solutions to guarantee energetic independence of the system.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Wireless network devices can attain the required level of quality of service (QoS) and maintain c... more Wireless network devices can attain the required level of quality of service (QoS) and maintain connectivity even after detaching from a current point of access. This detachment (mobility) requires various mobility management (MM) mechanisms, which present numerous challenges due to the exponential growth of wireless devices and the demands of users. The network must be heterogeneous and dense to manage such a heightened escalation of network traffic, increased number of devices, and different types of user demands. Such factors will seriously challenge MM solutions, eventually making the networks non-feasible from the dependability, adaptability, extensibility, and power consumption points of view. Therefore, novel perspectives on MM mechanisms are desired for 5G networks and beyond. This paper introduces an innovative discussion of the functional requirements of MM mechanisms for advanced wireless networks. We present comprehensive arguments on whether the prevailing mechanisms perceived by standard bodies attempt to fulfill the stated requirements. We complete this discussion through innovative qualitative evaluation. We assess each of the discussed mechanisms in terms of their capability to fulfill the dependability, adaptability, extensibility, and power consumption benchmarks for upcoming MM schemes. Hereafter, we demonstrate the outcome and the identified gaps/challenges for the planning and deployment of 5G MM frameworks and beyond. Next, we present the capabilities and possible MM solutions to tackle the gaps/difficulties. We complete our discussion by proposing a 6G MM architecture based on defined parameters.
In this paper we propose an innovative method and an innovative system dedicated to analyze the h... more In this paper we propose an innovative method and an innovative system dedicated to analyze the head tremor of people with neurological disorders. The method envisages the acquisition of the tremor data using intelligent clothes. A set of capacitive sensors are inserted in the collar and detect the head position and movement. The tremor parameters resulted after FFT analysis (amplitudes and frequencies) reveals the presence of essential tremor which is difficult to be identified by visual investigation.
COVID-19 is a fatal disease caused by the SARS-CoV-2 virus that has caused around 5.3 Million dea... more COVID-19 is a fatal disease caused by the SARS-CoV-2 virus that has caused around 5.3 Million deaths globally as of December 2021. The detection of this disease is a time taking process that have worsen the situation around the globe, and the disease has been identified as a world pandemic by the WHO. Deep learning-based approaches are being widely used to diagnose the COVID-19 cases, but the limitation of immensity in the publicly available dataset causes the problem of model over-fitting. Modern artificial intelligence-based techniques can be used to increase the dataset to avoid from the over-fitting problem. This research work presents the use of various deep learning models along with the state-of-the-art augmentation methods, namely, classical and generative adversarial network-(GAN-) based data augmentation. Furthermore, four existing deep convolutional networks, namely, DenseNet-121, InceptionV3, Xception, and ResNet101 have been used for the detection of the virus in Xray images after training on augmented dataset. Additionally, we have also proposed a novel convolutional neural network (QuNet) to improve the COVID-19 detection. The comparative analysis of achieved results reflects that both QuNet and Xception achieved high accuracy with classical augmented dataset, whereas QuNet has also outperformed and delivered 90% detection accuracy with GAN-based augmented dataset.
Telemedicine is the delivery of general and specialty e-clinical services to remote area, using I... more Telemedicine is the delivery of general and specialty e-clinical services to remote area, using Information and Communication Technologies (ICT) and network of sensors. Successful health management of a patient who has visual impairment and also obesity problems includes multiple treatment strategies, focusing on changing the patient's diet, modifying eating and physical activity habits, and also monitoring the health parameters such as heart rate, systolic and diastolic blood pressure, blood sugar and body mass index. Because people with visual impairment and also with obesity problems represent a special group of patients, we intend to improve their quality of life by creating a low-cost health care self-monitoring system using a network of sensors that transmits the biomedical information played by voice to the patient and help him to move and to know the exact location of obstacles, using a sound signal received in headphones or speakers.
The market for wearable technology has been slowly growing and has recently exploded with the pop... more The market for wearable technology has been slowly growing and has recently exploded with the popularity of fitness trackers and smart watches. Recent technologic advancements in Information and Communication Technologies have enabled the design of a wearable, low-cost, system that can be embedded in smart clothing. This article reviews the development of smart clothing and shows the potential impact on clinical rehabilitation. A wearable recovery pants architecture for monitoring the movement activity is proposed in this article. Also, the main types and components of a smart Internet of Things wearable clothing are presented.
2019 International Conference on Sensing and Instrumentation in IoT Era (ISSI)
This paper present some considerations on the development of IoT systems. Among these application... more This paper present some considerations on the development of IoT systems. Among these applications we mention: intelligent house, automatic plant care system, automatic system for creating graphic elements, etc.
Learning is a process of acquisition, depending on experience, thanks to which certain activities... more Learning is a process of acquisition, depending on experience, thanks to which certain activities/behaviours are formed or modified under the influence of repetitive and variable world conditions. Learning is a human-specific evolutionary process, consisting in acquiring the experience of life. Schools have an important role in promoting learning, introducing us to the secrets of knowledge. Questions like 'Why does learning take place?' or 'How does learning take place?', led to theories and models of instruction (learning). 'The theory explains the process, and the model describes it', says . The first question is answered by explaining the deep mechanisms of the learning process and its causal determinations. As regards the second question, , for example, finds that learning is associated with several knowledge paradigms, one of which, relevant here, advances the idea that school learning is a process of O. Geman (B)
This editorial summarises the special issue entitled "Deep Learning Blockchain-enabled Technology... more This editorial summarises the special issue entitled "Deep Learning Blockchain-enabled Technology for Improved Healthcare Industrial Systems", which deals with the intersection and use of deep learning and blockchain technologies in the healthcare industry. This special issue consists of eleven scientific articles.
Computational Intelligence and Neuroscience, Sep 15, 2022
e development of unusual cells in the cerebrum causes brain cancer. It is classi ed primarily int... more e development of unusual cells in the cerebrum causes brain cancer. It is classi ed primarily into two classes: a noncarcinogenic (benign) type of growth and cancerous (malignant) growth. Early detection of this disease is a quintessential task for all medical practice professionals. For traditional approaches of tumor detections, certain limitations exist. ey include less e ectiveness, inability to detect due to low-quality processing of images, less dataset for training and testing, less predictive nature to models, and skipping of quintessential stages. All these lead to inaccurate results of tumor detections. To overcome this issue, this paper brings an e ective deep learning technique for brain tumor detection with the following stages: (a) data collection from REMBRANDT dataset containing multisequence MRI of 130 patients; (b) preprocessing using conversion to greyscale, skull stripping, and histogram equalization; (c) segmentation uses genetic algorithm; (d) feature extraction using discrete wavelet transform (DWT); (e) particle swarm optimization technique for feature selection; (f) classi cation using U-Net. Experiment evaluation states that the proposed model (GA-UNET) outperforms (accuracy: 0.97, sensitivity: 0.98, speci city: 0.98) compared to other advanced models.
The IoT concept plays an important role in healthcare systems. This paper presents a sensors netw... more The IoT concept plays an important role in healthcare systems. This paper presents a sensors network based on interdigital capacitive sensor that is incorporated in clothes in order to build a device for screening and management of patients with Diabetic Neuropathy. The use of interdigital capacitive sensors embedded in clothes is a viable manner for monitoring the tremor of various parts of the body, including legs, neck and head. This method of monitoring, using capacitive sensors inserted in clothes is proper for the analysis of the subject's daily activity and in order to determine the patient's evolution and early detection of the modifications produced by Diabetic Neuropathy. Future work would supplement the system with wearable photovoltaic modules, or other solutions to guarantee energetic independence of the system.
This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY
Wireless network devices can attain the required level of quality of service (QoS) and maintain c... more Wireless network devices can attain the required level of quality of service (QoS) and maintain connectivity even after detaching from a current point of access. This detachment (mobility) requires various mobility management (MM) mechanisms, which present numerous challenges due to the exponential growth of wireless devices and the demands of users. The network must be heterogeneous and dense to manage such a heightened escalation of network traffic, increased number of devices, and different types of user demands. Such factors will seriously challenge MM solutions, eventually making the networks non-feasible from the dependability, adaptability, extensibility, and power consumption points of view. Therefore, novel perspectives on MM mechanisms are desired for 5G networks and beyond. This paper introduces an innovative discussion of the functional requirements of MM mechanisms for advanced wireless networks. We present comprehensive arguments on whether the prevailing mechanisms perceived by standard bodies attempt to fulfill the stated requirements. We complete this discussion through innovative qualitative evaluation. We assess each of the discussed mechanisms in terms of their capability to fulfill the dependability, adaptability, extensibility, and power consumption benchmarks for upcoming MM schemes. Hereafter, we demonstrate the outcome and the identified gaps/challenges for the planning and deployment of 5G MM frameworks and beyond. Next, we present the capabilities and possible MM solutions to tackle the gaps/difficulties. We complete our discussion by proposing a 6G MM architecture based on defined parameters.
In this paper we propose an innovative method and an innovative system dedicated to analyze the h... more In this paper we propose an innovative method and an innovative system dedicated to analyze the head tremor of people with neurological disorders. The method envisages the acquisition of the tremor data using intelligent clothes. A set of capacitive sensors are inserted in the collar and detect the head position and movement. The tremor parameters resulted after FFT analysis (amplitudes and frequencies) reveals the presence of essential tremor which is difficult to be identified by visual investigation.
COVID-19 is a fatal disease caused by the SARS-CoV-2 virus that has caused around 5.3 Million dea... more COVID-19 is a fatal disease caused by the SARS-CoV-2 virus that has caused around 5.3 Million deaths globally as of December 2021. The detection of this disease is a time taking process that have worsen the situation around the globe, and the disease has been identified as a world pandemic by the WHO. Deep learning-based approaches are being widely used to diagnose the COVID-19 cases, but the limitation of immensity in the publicly available dataset causes the problem of model over-fitting. Modern artificial intelligence-based techniques can be used to increase the dataset to avoid from the over-fitting problem. This research work presents the use of various deep learning models along with the state-of-the-art augmentation methods, namely, classical and generative adversarial network-(GAN-) based data augmentation. Furthermore, four existing deep convolutional networks, namely, DenseNet-121, InceptionV3, Xception, and ResNet101 have been used for the detection of the virus in Xray images after training on augmented dataset. Additionally, we have also proposed a novel convolutional neural network (QuNet) to improve the COVID-19 detection. The comparative analysis of achieved results reflects that both QuNet and Xception achieved high accuracy with classical augmented dataset, whereas QuNet has also outperformed and delivered 90% detection accuracy with GAN-based augmented dataset.
Telemedicine is the delivery of general and specialty e-clinical services to remote area, using I... more Telemedicine is the delivery of general and specialty e-clinical services to remote area, using Information and Communication Technologies (ICT) and network of sensors. Successful health management of a patient who has visual impairment and also obesity problems includes multiple treatment strategies, focusing on changing the patient's diet, modifying eating and physical activity habits, and also monitoring the health parameters such as heart rate, systolic and diastolic blood pressure, blood sugar and body mass index. Because people with visual impairment and also with obesity problems represent a special group of patients, we intend to improve their quality of life by creating a low-cost health care self-monitoring system using a network of sensors that transmits the biomedical information played by voice to the patient and help him to move and to know the exact location of obstacles, using a sound signal received in headphones or speakers.
The market for wearable technology has been slowly growing and has recently exploded with the pop... more The market for wearable technology has been slowly growing and has recently exploded with the popularity of fitness trackers and smart watches. Recent technologic advancements in Information and Communication Technologies have enabled the design of a wearable, low-cost, system that can be embedded in smart clothing. This article reviews the development of smart clothing and shows the potential impact on clinical rehabilitation. A wearable recovery pants architecture for monitoring the movement activity is proposed in this article. Also, the main types and components of a smart Internet of Things wearable clothing are presented.
2019 International Conference on Sensing and Instrumentation in IoT Era (ISSI)
This paper present some considerations on the development of IoT systems. Among these application... more This paper present some considerations on the development of IoT systems. Among these applications we mention: intelligent house, automatic plant care system, automatic system for creating graphic elements, etc.
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