ABSTRACT. Global trend in the maritime industry is achieving carbon-zero and green shipping technology. The demand to design more efficient and low-emission ships has increased the variety of hybrid propulsion and control architectures. Intelligent control strategies are required to improve performance with these architectures. This paper aims to analyze different power and control configurations that can be designed for driving a winch system that will set and furl the sail of a modern ship with hybrid propulsion. All the physical limitations imposed by the position of the winches, maritime rules and regulations, and the goal to achieve an energy-efficient system are considered.

ABSTRACT. The failures in the operational state of an electric power system and their effects are taken in consideration with the reference to the modern protection types, which need to include the data uncertainties in their risk modelling. The paper presents the possible failures and their effects on the electric installation for the power stations. The protections of the electric power system need a special attention because of their subsystems, waiting for the failure. The risk of not answering to the failures, for a power protection system, must be minimized. The fuzzy logic including uncertainties helps to find a qualitative model for each one of the protections associated with different failure types for an electric power equipment. It gives the operational risk overview of the protections related to the failures associated to the protected electric power equipment.

ABSTRACT. The reduction of electricity consumption in the field of lighting requires the use of lamps with LED technology in order to replace incandescent bulbs and neon tubes. Their power sources, which contain controlled semiconductor elements, allow precise adjustment of the light intensity, which enables the integration of these systems in areas related to the comfort parameters of a living space. On the other hand, the switching of the semiconductor elements included in such systems called dimmers produces a change in the waveform of the voltage applied to the lamps, by introducing unwanted frequency harmonics, which can disturb other electrical or electronic elements placed nearby. This paper aims to compare the harmonics produced by 2 commercial dimmer systems, based on TRIAC-type elements, with those produced by a dimmer made in the laboratory, based on IGBT-type elements. The analysis was performed via a digital oscilloscope starting from the waveform of the electric current and using Fast Fourier Transformation.

ABSTRACT. This paper presents an application that determines and processes the temperature increase and the heat dissipation inside an insulated copper conductor of a given section as function depending on the applied conduction current from a SIEMENS WL I 800 N automatic circuit breaker. The application was made with a programmable automation CPU 1215 PLC, analog extension module SM1245 and operator interface TP 700 Comfort (Siemens). The current output is transmitted from the circuit breaker to the PLC using an analog module interface. The determination of the temperature is done indirectly by measuring the conduction current by a current loop 4-20mA generated by the CB interface. The processing of the instantaneous values of the conduction current is carried out by connecting the output module to the analog input port of the extension module having a 10 bits resolution of the analog-digital conversion.

ABSTRACT. Power profiling is important for upper-level analysis models used in low voltage (LV) applications. Characteristic profiles that use energy-related information coming from the metering infrastructure with low reporting rates (e.g., 1h, 30 min, 15 min) are usually assumed, depending on the application type for which they serve as input. The advancement of smart metering using higher reporting rates (e.g., 1 frame/s or 1 frame/min) may enhance the assessment of details in power profiling for LV distribution grids. An analytical-based framework to conduct a quality assessment in power profiling, making use of state-of-the-art infrastructure is proposed in this study. The framework is useful to quantify the accuracy of an assumed power profile model, especially for applications dealing with the operation and planning of microgrids or energy communities.

ABSTRACT. In recent years, the integration of advanced technologies in industrial control processes has gained significant attention, particularly in the domain of wastewater systems. One emerging technology with promising potential is Distributed Ledger Technology (DLT), which offers secure and transparent data management through blockchain-based solutions. This paper presents an in-depth analysis of the performance impact that arises when incorporating DLT-based sensor authentication in industrial control processes of wastewater systems. The study aims to evaluate the benefits and challenges associated with this integration, providing insights into the effectiveness and efficiency of DLT-based sensor authentication in ensuring data integrity and enhancing the overall control process performance.

ABSTRACT. Maritime domain agencies play a critical role in generating situational awareness to detect maritime anomalies and prevent illegal fishing, illegal migration, or even hostile naval activities. Traditionally, these tasks rely especially on human cognitive load, but the use of Artificial Intelligence (AI) can potentially enhance these processes. This paper proposes and analyses several AI-based approaches for vessel type classification based on their trajectory analysis. These approaches draw inspiration from various handwriting signature verification techniques such as deep learning, K-nearest neighbours, support vector machines and convolutional neural networks. Thus, different models were trained using AIS processed data collected from the Black Sea region (Romanian Exclusive Economic Zone). The goal was to obtain a model that classifies non-cooperative vessels when detected only by radar sensors. The trained models aim to identify situations such as illegal fishing, search and rescue operations, or law enforcement activities where vessels may have turned off their AIS transponders. These approaches could have significant implications for enhancing maritime surveillance, particularly in situations where conventional methods are ineffective. Overall, this paper represents a promising step towards improving the safety and security of oceans through advanced vessel type classification techniques.

ABSTRACT. Diabetic Retinopathy (DR) is a condition caused by diabetes that affects the blood vessels in the retina. Detecting the disease early and providing appropriate treatment are crucial in slowing its progression. Therefore, there is great potential in utilizing Machine Learning (ML) to improve the identification and monitoring of DR development in patients. Our study aims to explore the performance of six ML algorithms, namely Random Forest (RF), Adaptive Boosting (AB), K-Nearest Neighbor (K-NN), Gaussian Naive Bayes (GNB), Support Vector Machine (SVM), and Quadratic Discriminant Analysis (QDA), in two binary classifications involving three classes: non-diabetic retinopathy (NoDR), moderate retinopathy (MR), and severe retinopathy (SV). These ML algorithms were applied to ten features extracted using local binary patterns (LBP). The first classification task involved distinguishing between NoDR and MR, while the second task involved differentiating between NoDR and SV. The RF technique achieved the highest classification accuracy, with 0.912 for the first task and 0.94 for the second task.

ABSTRACT. Due to the common limitation of the human visual system, internal features of thermal images cannot be fully discovered. To overcome these drawbacks, a lot of studies analyzed the facial expressions corroborating the features extracted from thermal images with machine learning tools. This paper proposed the first-order features extracted from the image histogram and a binary classification performed by the k-nearest neighbor algorithm (K-NN). The proposed method tests separately the performance of different input data, firstly, the features were extracted from raw images and the robustness of the K-NN algorithm led to an accuracy of 92.6%. Secondly, the features were extracted sequentially from corrupted images with noise. The novelty of the proposed method consists of verifying of quality classification when the images have bad quality, in this case, the accuracy decreased to 70.7%, as a result, the classification of facial expressions is sensitive to the quality of images.

ABSTRACT. Tensor-based signal processing methods can lead to efficient solutions for system identification problems that involve a large parameter space, e.g., a long length impulse response to be identified. Recently, an iterative Wiener filter based on a third-order tensor decomposition has been developed, in the framework of low-rank system identification scenarios. It exploits the nearest Kronecker product decomposition of the (long length) impulse response and obtains its estimate based on a combination of three (much) shorter filters. In order to improve the computational efficiency of this algorithm, we design in this paper a new version using the coordinate descent method, thus avoiding matrix inversion operations. Simulations are performed in an echo cancellation scenario and the results indicate the good performance of the proposed solution.

ABSTRACT. The present work aims at modeling, experimentally simulating and then implementing a computationally-efficient algorithm for jump-type Lévy processes. Within the paper, a pseudocode version for discretizing the continuous Brownian motion component of the Lévy processes is presented. The study also analyzes, through simulation experiments, the effect of each of the three process components upon the overall motion variance, slope and volatility of the result. Further model experiments are performed by tuning the jump size of the internal Poisson component, using four different types of distributions – namely: exponential, hyperexponential, normal and Pareto, in order to study the behavior of the Lévy processes. Finally, first-passage probabilities are estimated upon all these four distributions, which have many applications in financial and economics fields, as well as in the fields of mathematics, physics and engineering.

ABSTRACT. A significant role in electronics and not only is represented by the vibrations variable. The paper aims to present an electronic solution for measuring and recording vibrations on a SD card. The data collected on the SD card can be used to analyze the condition of the vehicle engine by performing a vibration analysis. The hardware solution is based on an ESP8266 microcontroller, an accelerometer sensor, display and SD memory card. With the proper software the hardware can be turned into an IoT solution for future research. This paper covers the hardware solution implemented, real time data reading and processing, data storing using a SD memory card and testing on different car engines. After testing, differences were observed in the vibrations generated by an engine operating in normal parameters compared to a used engine or one with technical problems. Based on vibration analysis a preventive maintenance program can be made for different engines and not only.

ABSTRACT. Low Noise Block (LNB) circuits are an essential component of satellite receiving systems in televisions. LNB converts high-frequency satellite signals into a lower frequency range for transmission to the receiver. Also, LNB ensures lownoise signal reception, enables polarization control, supports multiple frequency bands, and amplifies signals. The LNB power circuits provide power to the LNB. Voltage-controlled boost converters are commonly used in these circuits; the current limiting feature used in these circuits can be insufficient to handle sudden current spikes, leading to feedback from end users. They are not immune to short circuits because of installation problems with satellite cables, which are a common failure mode that potentially damages the LNB power or other components in the television, resulting in a loss of satellite signal. Hence, leading to a poor user experience and harming the manufacturer’s reputation. Replacing a damaged LNB power circuit is also difficult because it is often integrated into the TV’s design and is not easily replaceable. To mitigate this problem, a parallel resonant converter approach is introduced that limits the output current up to a pre-defined level by frequency control, which provides an alternative to voltage-controlled boost converters. Parallel resonant converter circuits operate as current sources so maximum current cannot exceed this defined operation frequency point under any circumstances. In this study, the mathematical equations of the proposed circuit were obtained, and then the operating conditions were determined. The operation frequency ranges were interpreted graphically using Matlab, and the parallel resonant converter design was evaluated using simulation model by using MATLAB’s Simulink Toolbox. These results show that the parallel resonant converter approach maintaining a stable current and reducing the risk of short circuit damage. The proposed design is expected to reduce repair costs due to LNB power circuits for TV manufacturers.

ABSTRACT. Increasing energy demand requires the application of smart Direct current [DC] grids. To empower the creation of these DC systems the need of a smart converter is required. This paper proposes a smart and configurable educational code using a half-bridge topology as a converter. The Universal One Leg and Universal Four Leg are used as the configurable hardware, the universal code will be implemented on an Arduino Internet of Things [IoT] and can be configurable Over-The-Air [OTA]. This combination of flexible hardware and software allows bidirectional energy flow to control and manage appliances. In code, a selection of the functionality can be made. Such as basic buck or boost mode to have a stable voltage or current flowing through the converter. But also smarter functions such as Battery Management Systems [BMS] and Maximum Power Point Trackers [MPPT] systems can be selected. The converter can behave as such a converter and adding more of these converters in a system parts a system response can be measured. All data through this converter will be collected on the server side and can be analyzed through a simple dashboard. Main goal for this converter is to use it as a way to implement a DC micro-grid, although it can also be used to teach students about micro-grids in practical lessons. This document will discuss the architecture and functionality of the code and show results measured in a lab environment.

ABSTRACT. To be able to power all appliances into a camper van room, an efficient power supply system must be designed. It must be able to collect energy from both energy networks, when the camper is parked into a camping spot, but the energy is also needed when the camper is stopped into the wild. Moreover, the battery can be charged from the car alternator, while the camper van is moving from one place to another. This paper aims to provide necessary information about constructing a charging system for a battery which supplies the electronics into the camper van room, focusing on comparing different approaches. It is demonstrated that using only three solar panels with a cumulative power of 250W, enough energy for powering all appliances of high necessity for a camper van is obtained.

ABSTRACT. This paper presents an assay of dynamic of state of charge characteristics of a Li-ion battery. It is proposed an approach of forecasting battery’s state of charge that can be utilized by battery management system to predict the remained quantity of charge in the battery at a certain time, based on real time data acquisition and using a simplified electrical circuit model that simulates, with small errors, the battery signal, the results being experimentally validated.

ABSTRACT. Building-integrated/applied photovoltaic (PV) systems have recently become popular in terms of electrical energy generation in buildings. These systems are applications with much lower power than land type large-scale systems, addressing the area/building where they are installed rather than centralized production. In this framework, maximum power point tracking (MPPT) approaches at module level and sub-module level, balcony railing, Carport or solar tile etc. will be investigated in terms of building integrated PV systems (BIPV). Solar panels act as a building material, insulation material and energy generator in BIPV applications. In building-applied (BAPV) examples, the solar panel is mounted on the building. However, there is no difference between BIPV and BAPV in terms of electrical model. A unique method will be developed for MPPT at module level and sub-module level for such applications. Depending on the power processing strategy in the optimizer power stage, amplifier, synchronous reducer or bidirectional differential power processing topologies will be examined and the most suitable DC-DC converter for the module and sub-module level will be determined. Technically, comparisons of the performances of maximum power point strategies were made in the MATLAB/Simulink program at the central, module level or sub-module level, and it was shown that the power that can be obtained from the solar panel or sub-module increases with the MPPT at the module and sub-module level.