In this paper, a simulation model and practical testbed for green Internet of Things (IoT) edge devices are proposed based on solar harvester with constant voltage-maximum power point tracking (CV-MPPT) technique. Billions of connected edge devices represent the essential part of the IoT through the IP-enabled sensor networks based on IPv6 over Low power Wireless Personal Area Network (6LoWPAN). In traditional IoT edge devices, the stored energy in the non-rechargeable battery determines the node lifetime while it is being depleted with time. Therefore, purchasing billions of such batteries is costly and must be disposed of efficiently. This paper is aimed at simulating and implementing a new class of green IoT edge devices that can report data wirelessly and powered perpetually using clean energy. The developed edge device utilizes solar energy harvesting mechanism through photovoltaic (PV) module, this approach will avoid periodical battery replacement and hence, the energy supplied to the sensor mode is not limited anymore. The implemented testbed is based on open-source hardware and software platforms while the simulation environment is based on MATLAB/SIMULINK 2019a. The effects of temperature and solar irradiance on the performance of the developed approach are examined in order to confirm the leverage of the proposed methodology scheme. The lifetime of the developed green IoT device is predicted based on the device's activities, current consumption, and energy storage capacity. The obtained results showed that the battery lifetime is extended by 38-49% when the edge device runs on an independent power source. © Published under licence by IOP Publishing Ltd.
The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats. This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat
... Show MoreThe Present research aimed at identifying:
1- The level of environmental stress among preparatory students
2- The level of self-rebellion among preparatory students
3- The correlation between the two variables of research (environmental stress and self-rebellion) and the extent to which the independent variable contributes to the variable of the middle school students.
The current research has determined the students of the fifth stage of the preparatory stage and all the branches in the departments of education in Baghdad province the morning study for the academic
... Show MoreHuman beings have an innate and natural aim to achieve their self-interests and to show their ability to overcome challenges in a better way, therefore the move towards self determination is expressed by intrinsic motivation. The desire of absorbing in this task is to enjoy the task in it self and benefitting from it such a motivation is the desire rooted in human nature to judge and choose in which individual is conscious in his self, abilities and adequacy that help him in control the different situations of life passed by him. His choices and actions are voluntary and non-restricted to intervention or external control because control is inner and subjective, while his behavior is self-regulated with the feeling of
... Show MoreThe current research aims to identify the Vocational Self of the educational counselors as well as to identify the significant difference in the professional self according to the gender variable (male-female). The researcher adopted the scale of al-hasani (2015), which consisted of (34) items. It was applied to a sample of (300) school counselors (male-female) who were randomly selected from the six directorates in the Baghdad governorate for the academic year 2020/2021. The results showed that the research sample of educational counselors has a vocational self-concept. There are no statistically significant differences in the vocational self-concept between males and females among the educational counselors.
Slow learning becomes a problem in the present , where it comprises ratio musnt ignore in every school . So , its one of education problems facing by parents and teachers .
Slow learning subject regard of new subject attract the attention in the last years of the 20th century where the attention was focusing on the other disabilities but the existence of number of healthy children suffering from Learning problems attract the attention of the researchers .
So , this study aims at recognizing the degree of self , concept among slow learner students and the differences significance of self concept according to sex and academic degree of parents variables.
Because there is not tool , the researcher build a
... Show MoreThe limitations of wireless sensor nodes are power, computational capabilities, and memory. This paper suggests a method to reduce the power consumption by a sensor node. This work is based on the analogy of the routing problem to distribute an electrical field in a physical media with a given density of charges. From this analogy a set of partial differential equations (Poisson's equation) is obtained. A finite difference method is utilized to solve this set numerically. Then a parallel implementation is presented. The parallel implementation is based on domain decomposition, where the original calculation domain is decomposed into several blocks, each of which given to a processing element. All nodes then execute computations in parall
... Show MoreThe purpose of this work is to concurrently estimate the UVvisible spectra of binary combinations of piroxicam and mefenamic acid using the chemometric approach. To create the model, spectral data from 73 samples (with wavelengths between 200 and 400 nm) were employed. A two-layer artificial neural network model was created, with two neurons in the output layer and fourteen neurons in the hidden layer. The model was trained to simulate the concentrations and spectra of piroxicam and mefenamic acid. For piroxicam and mefenamic acid, respectively, the Levenberg-Marquardt algorithm with feed-forward back-propagation learning produced root mean square errors of prediction of 0.1679 μg/mL and 0.1154 μg/mL, with coefficients of determination of
... Show MoreMen with castration-resistant prostate cancer (CRPC) face poor prognosis and increased risk of treatment-incurred adverse effects resulting in one of the highest mortalities among patient population globally. Immune cells act as double-edged sword depending on the tumor microenvironment, which leads to increased infiltration of pro-tumor (M2) macrophages. Development of new immunomodulatory therapeutic agents capable of targeting the tumor microenvironment, and hence orchestrating the differentiation of pro-tumor M2 macrophages to anti-tumor M1, would substantially improve treatment outcomes of CRPC patients. We report, herein, Mangiferin functionalized gold nanoparticles (MGF-AuNPs) and its
Density functional theory (DFT) calculations were used to evaluate the capability of Glutamine (Gln) and its derivative chemicals as inhibitors for the anti-corrosive behavior of iron. The current work is devoted to scrutinizing reactivity descriptors (both local and global) of Gln, two states of neutral and protonated. Also, the change of Gln upon the incorporation into dipeptides was investigated. Since the number of reaction centers has increased, an enhancement in dipeptides’ inhibitory effect was observed. Thus, the adsorption of small-scale peptides and glutamine amino acids on Fe surfaces (1 1 1) was performed, and characteristics such as adsorption energies and the configuration with the highest stability and lowest energy were ca
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