Repositorio Universidad Europea del Atlántico
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IoTTPS: Ensemble RKSVM Model-Based Internet of Things Threat Protection System
No full textAn Internet of Things (IoT) network is prone to many ways of threatening individuals. IoT sensors are lightweight, lack complicated security protocols, and face threats to privacy and confidentiality. Hackers can attack the IoT network and access personal information and confidential data for blackmailing, and negatively manipulate data. This study aims to propose an IoT threat protection system (IoTTPS) to protect the IoT network from threats using an ensemble model RKSVM, comprising a random forest (RF), K nearest neighbor (KNN), and support vector machine (SVM) model. The software-defined networks (SDN)-based IoT network datasets such as KDD cup 99, NSL-KDD, and CICIDS are used for threat detection based on machine learning. The experimental phase is conducted by using a decision tree (DT), logistic regression (LR), Naive Bayes (NB), RF, SVM, gradient boosting machine (GBM), KNN, and the proposed ensemble RKSVM model. Furthermore, performance is optimized by adding a grid search hyperparameter optimization technique with K-Fold cross-validation. As well as the NSL-KDD dataset, two other datasets, KDD and CIC-IDS 2017, are used to validate the performance. Classification accuracies of 99.7%, 99.3%, 99.7%, and 97.8% are obtained for DoS, Probe, U2R, and R2L attacks using the proposed ensemble RKSVM model using grid search and cross-fold validation. Experimental results demonstrate the superior performance of the proposed model for IoT threat detection
Formal modeling and analysis of security schemes of RPL protocol using colored Petri nets
No full textIn the Internet of things (IoT), data packets are accumulated and disseminated across IoT devices without human intervention, therefore the privacy and security of sensitive data during transmission are crucial. For this purpose, multiple routing techniques exist to ensure security and privacy in IoT Systems. One such technique is the routing protocol for low power and lossy networks (RPL) which is an IPv6 protocol commonly used for routing in IoT systems. Formal modeling of an IoT system can validate the reliability, accuracy, and consistency of the system. This paper presents the formal modeling of RPL protocol and the analysis of its security schemes using colored Petri nets that applies formal validation and verification for both the secure and non-secure modes of RPL protocol. The proposed approach can also be useful for formal modeling-based verification of the security of the other communication protocols
Empowering Lower Limb Disorder Identification through PoseNet and Artificial Intelligence
No full textA novel approach is presented in this study for the classification of lower limb disorders, with a specific emphasis on the knee, hip, and ankle. The research employs gait analysis and the extraction of PoseNet features from video data in order to effectively identify and categorize these disorders. The PoseNet algorithm facilitates the extraction of key body joint movements and positions from videos in a non-invasive and user-friendly manner, thereby offering a comprehensive representation of lower limb movements. The features that are extracted are subsequently standardized and employed as inputs for a range of machine learning algorithms, such as Random Forest, Extra Tree Classifier, Multilayer Perceptron, Artificial Neural Networks, and Convolutional Neural Networks. The models undergo training and testing processes using a dataset consisting of 174 real patients and normal individuals collected at the Tehsil Headquarter Hospital Sadiq Abad. The evaluation of their performance is conducted through the utilization of K-fold cross-validation. The findings exhibit a notable level of accuracy and precision in the classification of various lower limb disorders. Notably, the Artificial Neural Networks model achieves the highest accuracy rate of 98.84%. The proposed methodology exhibits potential in enhancing the diagnosis and treatment planning of lower limb disorders. It presents a non-invasive and efficient method of analyzing gait patterns and identifying particular conditions
Insights into the cellular, molecular, and epigenetic targets of gamma-aminobutyric acid against diabetes: a comprehensive review on its mechanisms
No full textDiabetes is a metabolic disease due to impaired or defective insulin secretion and is considered one of the most serious chronic diseases worldwide. Gamma-aminobutyric acid (GABA) is a naturally occurring non-protein amino acid commonly present in a wide range of foods. A number of studies documented that GABA has good anti-diabetic potential. This review summarized the available dietary sources of GABA as well as animal and human studies on the anti-diabetic properties of GABA, while also discussing the underlying mechanisms. GABA may modulate diabetes through various pathways such as inhibiting the activities of α-amylase and α-glucosidase, promoting β-cell proliferation, stimulating insulin secretion from β-cells, inhibiting glucagon secretion from α-cells, improving insulin resistance and glucose tolerance, and increasing antioxidant and anti-inflammatory activities. However, further mechanistic studies on animals and human are needed to confirm the therapeutic effects of GABA against diabetes
Necessidade de políticas públicas para combater a violência de género no Brasil
No full textEl escenario de la opresión femenina ha tomado espacio en todo el mundo, despojando a las mujeres de sus derechos más fundamentales. Este contexto comienza a cambiar de manera más efectiva, recién a partir del siglo XX, cuando las mujeres comienzan a escalar los espacios sociales y reclamar sus derechos de manera más asertiva. En Brasil, este proceso se desarrolló lenta y gradualmente. En el escenario político, fue recién el 24 de febrero de 1932, a través de la promulgación de la Constitución Federal de 1934, que el Código Electoral pasó a garantizar el sufragio femenino, una de las principales conquistas de la mujer brasileña en este siglo. En 1988, un grupo de mujeres abrió espacio para el ingreso y la participación activa de las mujeres en el escenario político nacional, siendo considerada un hito de los derechos civiles en Brasil y garantizando la eficacia de las políticas públicas en la defensa de sus intereses. En este contexto, este artículo cualitativo de revisión bibliográfica realizó una investigación documental a través del método deductivo, buscando comprender la importancia de la participación femenina registrada en la Constitución de 1988, responsable de encadenar un importante proceso de empoderamiento de las mujeres, desencadenando el derecho a la igualdad de género. tan necesaria en vista del contexto de violencia en el país. Esa ocupación en el escenario político vino a garantizar importantes reformas legales, como la Ley Maria da Penha, un hito de la violencia contra la muje
Accuracy of plasma Aβ40, Aβ42, and p-tau181 to detect CSF Alzheimer’s pathological changes in cognitively unimpaired subjects using the Lumipulse automated platform
No full textBackground
The arrival of new disease-modifying treatments for Alzheimer’s disease (AD) requires the identification of subjects at risk in a simple, inexpensive, and non-invasive way. With tools allowing an adequate screening, it would be possible to optimize the use of these treatments. Plasma markers of AD are very promising, but it is necessary to prove that alterations in their levels are related to alterations in gold standard markers such as cerebrospinal fluid or PET imaging. With this research, we want to evaluate the performance of plasma Aβ40, Aβ42, and p-tau181 to detect the pathological changes in CSF using the automated Lumipulse platform.
Methods
Both plasma and CSF Aβ40, Aβ42, and p-tau181 have been evaluated in a group of 208 cognitively unimpaired subjects with a 30.3% of ApoE4 carriers. We have correlated plasma and CSF values of each biomarker. Then, we have also assessed the differences in plasma marker values according to amyloid status (A − / +), AD status (considering AD + subjects to those A + plus Tau +), and ATN group defined by CSF. Finally, ROC curves have been performed, and the area under the curve has been measured using amyloid status and AD status as an outcome and different combinations of plasma markers as predictors.
Results
Aβ42, amyloid ratio, p-tau181, and p-tau181/Aβ42 ratio correlated significantly between plasma and CSF. For these markers, the levels were significantly different in the A + / − , AD + / − , and ATN groups. Amyloid ratio predicts amyloid and AD pathology in CSF with an AUC of 0.89.
Conclusions
Plasma biomarkers of AD using the automated Lumipulse platform show good diagnostic performance in detecting Alzheimer’s pathology in cognitively unimpaired subjects
Valorization of Olea europaea and olive oil processing by-products/wastes
No full textOlive (Olea europaea) is a native species from the Mediterranean region and widely cultivated for its edible fruit, known as olives. Olives are a rich source of monounsaturated fatty acids, vitamin E, and polyphenols, and have been shown to have various health benefits. They are commonly used for cooking and are also employed in cosmetics and the pharmaceutical industry. The extract obtained from olive fruits and several subproducts of the olive industry has demonstrated several biological activities mainly associated with their antioxidant and inflammatory properties. Thus, olives, olive-derived products, and subproducts of the olive industry have gained popularity in recent years due to their potential health benefits and their use in traditional medicine. The present chapter summarizes the main applications of Olea europaea and olive oil processing by-products as therapeutic agents against cancer, cardiovascular diseases, and antimicrobial agents
House cricket (Acheta domesticus): A review based on its nutritional composition, quality, and potential uses in the food industry
No full textBackground
The house cricket (A. domesticus) is one of the edible insects that are gaining attention as a new source of protein and nutrients with potential use in the food industry as a safe and environmentally sustainable option with high biological value.
Scope and approach
Here, we review the published literature on studies of chemical composition, nutritional value, and potential risks that the consumption of house crickets entails. We discuss the benefits of consuming A. domesticus from a nutritional point of view, as well as information concerning the properties of its components for use in the food industry
Deep learning model for detection of brown spot rice leaf disease with smart agriculture
No full textGiven that it provides nourishment for more than half of humanity, rice is regarded as one of the most significant plants in the world in agriculture. The quantity and quality of the product may be impacted by diseases that can damage rice plants which can occasionally cause crop losses ranging from 30 to 60%. This manuscript proposed a Convolutional Neural Network (CNN) and Visual Geometry Group (VGG)19 i.e. CNN-VGG19 model with a transfer learning-based method for the precise identification and classification of rice leaf diseases. This scheme employs a transfer learning technique based on the VGG19 which can identify the brown spot class. The accuracy is 93.0% in the deployment of the dataset of rice leaf disease. The other parameters are sensitivity, specificity, precision and F1-score with 89.9%, 94.7%, 92.4% and 90.5% respectively. The developed technique obtained better results as compared to the existing baseline models