Search Results

Neural Networks derives intelligent systems and modern autonomous applications. With the complexity introduced in today’s systems, designing architectures remains open research problem in all fields. Despite many efforts to generalize, the resources required by neural architectures remain challenge. Robots design, Smart cities, IoTs …etc. become the leading industry and driving the fourth industrial revolutions. All…

Deep neural networks (DNNs) have demonstrated remarkable success across a wide range of machine learning tasks. However, determining an effective network architecture, particularly the sizes of the hidden layers, remains a significant challenge and often relies on inefficient trial-and-error experimentation. In this paper, we propose an automated architecture design approach based on structurally adaptive DNNs,…

Providing timely and meaningful feedback in photography education is challenging, particularly in large classes where manual assessment can delay skill development. This paper presents M-Stock, an AI-based automated photo evaluation system that uses Convolutional Neural Networks (CNNs) to assess student photography assignments on web browser. M-Stock evaluates both technical aspects (such as lighting, composition, and…

Deep Neural Networks (DNNs) prove to be susceptible to synthetically generated samples, so-called adversarial examples. Such adversarial examples aim at generating misclassifications by specifically optimizing input data for a matching perturbation. With the increasing use of deep learning on embedded devices and the resulting use of quantization techniques to compress deep neural networks, it is…

RetePAIoT of Emilia-Romagna region is an IoT Public Network, financed by Emilia-Romagna Region and developed by Lepida Scpa, where citizens, private companies and Public Administrations can integrate free of charge their own sensors of any type and anywhere in the region. The main objective of the project is to provide a facility to implement the…

Machine learning-based predictive models often face challenges, particularly biases and a lack of trust in their predictions when deployed by individual agents. Establishing a robust deployment methodology that supports validating the accuracy and fairness of these models is a critical endeavor. In this paper, we introduce a novel approach to deploying predictive models, such as…

The solar photovoltaic (PV) power generation industry has experienced substantial, ongoing growth over the past decades as a clean, cost-effective energy source. As electric grids use ever-larger proportions of solar PV, the technology’s inherent variability—primarily due to clouds—poses a challenge to maintaining grid stability. This is especially true for geographically dense, electrically isolated grids common…

Being known as an irreversible neurodegenerative disease which has no cure to date, detection and classification of Alzheimer’s disease (AD) in its early stages is significant so that the deterioration process can be slowed down. Generally, AD can be classified into three major stages, ranging from the “normal control” stage with no symptoms shown, the…

The cybercriminal utilized the skills and freely available tools to breach the networks of internet-connected devices by exploiting confidentiality, integrity, and availability. Network anomaly detection is crucial for ensuring the security of information resources. Detecting abnormal network behavior poses challenges because of the extensive data, imbalanced attack class nature, and the abundance of features in…

Cybercriminal exploits integrity, confidentiality, and availability of information resources. Cyberattacks are typically invisible to the naked eye, even though they target a wide range of our digital assets, such as internet-connected smart devices, computers, and networking devices. Implementing network anomaly detection proves to be an effective method for identifying these malicious activities. The traditional anomaly…

Designing efficient control strategies for opinion dynamics is a challenging task. Understanding how individuals change their opinions in social networks is essential to countering malicious actors and fake news and mitigating their effect on the network. In many applications such as marketing design, product launches, etc., corporations often post curated news or feeds on social…

The increase electricity production based on renewable energies sources responds to the requirements of sustainable development. In recent years, the investment in the wind energy sector has increased to satisfy green electricity generation and environment protection. Wind energy is currently the most competitive energy resource that is part of the world’s countries views on the…

Determining the best candidates for a certain job rapidly has been one of the most interesting subjects for recruiters and companies due to high costs and times that takes the process. The accuracy of the models, particularly, is heavily influenced by the discriminant variables that are chosen for predicting the candidates scores. This study aims…

Bird watchers and people obsessed with raising and taming birds make a kind of motivation about our subject. It consists of the creation of an Android application called ”Birds Images Predictor” which helps users to recognize nearly 210 endemic bird species in the world. The proposed solution compares the performance of the python script, which…

The use of a battery to power an electrical or electronic system is accompanied by battery management, i.e. a set of measures intended to preserve it for preventative maintenance, thus the cost reduction. This management is generally based on two key parameters, the (remaining useful life) RUL and the (State-of-health) SOH, which relate respectively to…

We present in this contribution the distribution of a global multi-input-multi-output system in a sensor and actuator network. Based on controllability and observability, the global system is decentralized and the system properties are preserved as a result. This results in multiple decentralized local single-input-single-output systems with the same system order as the global system. As…

In the time past, virtually all the contemporary communication systems depend on distinct source and channel encoding schemes for data transmission. Irrespective of the recorded success of the distinct schemes, the new developed scheme known as joint source channel coding technique has proven to have technically outperformed the conventional schemes. The aim of the study…

Traffic road management is becoming more complex due to limited resources and an increasing number of hybrid vehicles. Currently, a number of global classical computing tools are used to manage the traffic road network. This kind of classical computing is resource intensive and expensive, and in the best case, optimizing a traffic network takes a…

The main purpose in this work is to explore the fact that chaos, as a biological characteristic in the brain, should be used in an Artificial Neural Network (ANN) system. In fact, as long as chaos is present in brain functionalities, its properties need empirical investigations to show their potential to enhance accuracies in artificial…

Blockchain technology is seeing a trend of popularity and adoption in many different application areas. One such area is healthcare, as there is a need to develop a system that can reliably store and share electronic health records (EHRs) among hospital-based health facilities. In this paper, we present a cloud-based hierarchical consortium blockchain framework for…

The Nodes equipped with wireless technology cooperate in an autonomous and instantaneous way to form a mobile ad hoc network. It turns out that several factors make this type of network vulnerable to various security threats. Considering the sensitivity of user data routed through nodes, routing security should be a priority in mobile ad hoc…

Various applications have helped make vehicular Ad-hoc network communication a reality. Real-time applications, for example, need broadcasting in high video quality with minimal latency. The new High-Efficiency Video Coding (HEVC) has shown great promise for real-time video transmission through Vehicle Ad-hoc Networks due to its high compression level. These networks, on the other hand, have…

Researchers have associated agriculture and food processing with adverse environmental impacts like; falls in the underground freshwater table, energy consumption, and high carbon emission. These factors have the worst effect on developing countries. Therefore, there is a need for on-demand food production techniques that require minimum resource utilization. For these reasons, scientists are now focusing…

The paper describes the control and monitoring systems installed in medium voltage networks by Polish distribution network operators. It also outlines the expected directions of development of these systems, specifies the functions of the individual system components and describes the requirements applicable to them. In particular, attention is paid to the implementation of functions to…

Navigation of a moving object (drone, vehicle, robot, and so on) and related localization in unknown scenes is nowadays a challenging subject to be addressed. Typically, different source devices, such as image sensor, Inertial Measurement Unit (IMU), Time of Flight (TOF), or a combination of them can be used to reach this goal. Recently, due…