Showing papers by "Nicolae Goga published in 2022"

Challenges of modeling nanostructured materials for photocatalytic water splitting.

Abstract: Understanding the water splitting mechanism in photocatalysis is a rewarding goal as it will allow producing clean fuel for a sustainable life in the future. However, identifying the photocatalytic mechanisms by modeling photoactive nanoparticles requires sophisticated computational techniques based on multiscale modeling. In this review, we will survey the strengths and drawbacks of currently available theoretical methods at different length and accuracy scales. Understanding the surface-active site through Density Functional Theory (DFT) using new, more accurate exchange-correlation functionals plays a key role for surface engineering. Larger scale dynamics of the catalyst/electrolyte interface can be treated with Molecular Dynamics albeit there is a need for more generalizations of force fields. Monte Carlo and Continuum Modeling techniques are so far not the prominent path for modeling water splitting but interest is growing due to the lower computational cost and the feasibility to compare the modeling outcome directly to experimental data. The future challenges in modeling complex nano-photocatalysts involve combining different methods in a hierarchical way so that resources are spent wisely at each length scale, as well as accounting for excited states chemistry that is important for photocatalysis, a path that will bring devices closer to the theoretical limit of photocatalytic efficiency.

Architecture of an Innovative Route Planning System for Sustainable Commercial Vehicle Fleets

Abstract: Nowadays the main challenges for transportation industry are to reduce labor costs, planning time and carbon footprint. Most of the conventional vehicles release considerable volumes of pollutants which accentuate global warming. In this paper we will write about the system architecture of iRoute, an innovative route planning solution specialized for commercial vehicle fleets, considering also electrical vehicles with specific constraints about their drive autonomy and charging stations along the optimized route. We will also describe use cases of such a solution and then detail the main components: Vehicle Data Module, Integration Module, Database, Processing services, User Profile, Optimization Engine, Route monitor services, Driver feedback, Web Application and Mobile Application. This paper is based on the work on Eureka project PN-III-P3-3.5-EUK-2019-0210.

Prediction of COVID-19 Patients Recovery using Ensemble Machine Learning and Vital Signs Data Collected by Novel Wearable Device

Abstract: During the spread of a pandemic such as COVID-19, the effort required of health institutions increases dramatically. Generally, Health systems’ response and efficiency depend on monitoring vital signs such as blood oxygen level, heartbeat, and body temperature. At the same time, remote health monitoring and wearable health technologies have revolutionized the concept of effective healthcare provision from a distance. However, analyzing such a large amount of medical data in time to provide the decision-makers with necessary health procedures is still a challenge. In this research, a wearable device and monitoring system are developed to collect real data from more than 400 COVID-19 patients. Based on this data, three classifiers are implemented using two ensemble classification techniques (Adaptive Boosting and Adaptive Random Forest). The analysis of collected data showed a remarkable relationship between the patient’s age and chronic disease on the one hand and the speed of recovery on the other. The experimental results indicate a highly accurate performance for Adaptive Boosting classifiers, reaching 99%, while the Adaptive Random Forest got a 91% accuracy metric © 2022. International Journal of Advanced Computer Science and Applications.All Rights Reserved.

Blockchain-Enabled Economic Transactions: Recurring Financial Accruals and Payments

Abstract: Economic transactions are based upon implicit or explicit contracts that set out the rights and obligations of the parties to the transactions. Blockchain technology can address fundamental financial, economic, and accounting challenges. We propose a blockchain-based prototype capable of capturing the essence of recurring economic transactions. For this purpose, we have devised an asset rental contract to show how economic transactions are recorded and tracked more effectively, efficiently, and in quasi-real-time, thus changing the traditional way of account keeping and auditing. We use the Ethereum blockchain as the most evolved and widely used smart contract platform. We showcase a significant discovery related to current blockchain technology limitations to making automatic non-custodial recurring payments. We show how the prototype can be extended to a range of recurring transactions.

Determining the User's Requirements for an Intelligent Mind-Controlled Prosthetic Lower Limb System

Abstract: Brain-Computer Interface technology (BCI) evolved since 70’, from a project made for studying brain affection to an approach of giving the ability to people with massive muscular affection. The basis of BCI is the electroencephalography technique (EEG) which captures brain signals from neuronal activity using electrodes placed on the scalp. These signals are interpreted as commands that can be used to control applications or external devices. EEG non-invasive approach is widely preferred due to non-critical procedures, and it doesn't need or require surgery which can be expensive and dangerous. The current prosthetic leg could be expensive, heavy, and hard to control by disabled people. To determine the functional and non-functional requirements of the user, and learn how users wish to engage with the prosthetic lower limb intelligent system, a quantitative questionnaire is offered in this study. The participant's responses will be considered the basis of the system design. The goal of this quantitative questionnaire is to build a low-cost, lightweight, and intelligent functional bionic prosthetic leg that meets the functional and non-functional requirements of the user. This system will be controlled by mind commands using a dedicated neuro headset.

Recurring Payments on EVM-based Platforms

Abstract: This article proposes a concept of building a payment system for subscription-based services in cases of fixed prices and with recurring frequency. The proposed solution offers the user the opportunity for ease-of-use and transaction fee cost savings. The proposed method of calculating balances for crypto-wallets can be applied to other financial services that provide traditional banking products based on decentralized public platforms. The concept is deployed in the form of a smart contract for issuing tokens on Ethereum, which is backward compatible with ERC-20 and ERC-777, and can form the basis for a new EVM-based decentralized network standard.

The behavior of some soybean genotypes from scda turda on the stagnogleized preluvosol from scda livada

Abstract: Increasing the areas cultivated with soybeans in order to develop vegetable protein resources requires the research and knowledge of new genotypes in different pedoclimatic conditions.The type of soil at Livada on which the "preluvosol stagnogley" was experimented is representative of the north-west of Romania and is characterized by a very low potential fertility due to unfavorable physical, hydrophysical and chemical properties as well as a poor supply of nutrients and a reduced microbiological activities (Ștefan 2000).

Adaptive Route Planning Algorithm based on Historical Executions for Commercial Vehicle Fleets

Abstract: This paper describes an algorithm that is supposed to reduce the differences between the theoretical planned routes of commercial vehicles and the practical execution of routes based on historical validated data. The resulted routes will not be as optimized as the they can be, but they should reflect more accurately the reality, keeping in mind local specific conditions, driver habits or other business factors that can not be used in a route planning algorithm. The first prototype of the algorithm use input parameters received from the historical execution of real-life vehicle routes. The reason for developing such an adaptive algorithm is to get smaller differences between planned and executed routes, a very important business indicator for commercial vehicle fleets. This paper is based on the work on Eureka project PN-III-P3-3.S-EUK-2019-0210.

An overview of blockchain technology in STAMINA project

Abstract: The future of the healthcare sector and its systems are beginning to take shape by combining technological innovations with traditional techniques to generate new and efficient solutions for patient care and data storage. Most conventional medical information management and storage systems are centralized, which means there is a risk of data loss in the event of malicious attacks or even natural disasters because of the single point of failure that centralized systems have. Blockchain technology is decentralized and emerging, offering the potential to significantly revolutionize how data is stored and managed in the healthcare industry. This paper presents the advantages of using blockchain in the healthcare sector, as this technology has a strategic role in both the management of stored data and the creation of predictive systems that could prevent a pandemic like the one generated by the SARS-Cov-2 virus. We present different existing studies and the method addressed in the ongoing STAMINA project.

Improving Security and Scalability in Smart Grids using Blockchain Technologies

Abstract: In the current industrial century, smart grid is one of the technologies that has been proposed for efficient and quality distribution of electricity. However, this technology is exposed to many security threats and vulnerabilities. These challenges have led to the development of advanced technologies and sustainable solutions to make smart grids more secure and reliable. Blockchain is one of the recent technologies that has attracted a lot of attention in various applications, including smart grids. SealedGRID is a project designed, analyzed and implemented with the aim of providing a scalable and reliable Smart Grid security platform based on blockchain. In this paper, we present a scalable and secure solution for smart grids using Hyperledger Fabric and MQTT.

Virtual Reality Application for Pain Management: User Requirements

Abstract: —The usage of fully immersive Virtual Reality applications for pain relief is still in an exploratory stage. In consequence there is a need to understand the user perspective and wishes regarding this kind of product. To address this issue, this paper presents quantitative research in order to establish the functional and non-functional requirements of our application. Voluntary response sampling was used for the research (N = 55). The inquiry form contained questions regarding serious game content, eagerness for testing, performance, resource consumption optimization, portability, accessibility. The questionnaire was shared via Google Forms. The answers were collected and interpreted. The study revealed that a significant part of the participants was willing to test the application and that they would use an immersive Virtual Reality application during a normal treatment session if the opportunity is available. As functional requirements, the following were considered important: the presence of animals in game, a bright environment and nature-based background sounds. The following non-functional requirements were considered important: game optimization, portability, data security, accessibility, graphics quality and a short learning curve.

Design and Development of a Bracelet to Monitor Vital signs of COVID-19 Patients

Abstract: COVID-19, which stands for Coronavirus disease 2019, is an infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), first reported in December 2019 in Wuhan, China. The new coronavirus has spread rapidly around the world, causing extensive deaths, and turning into a new global public health crisis. This paper proposes a prototype system to assist medical staff in identifying and monitoring COVID-19 symptoms by measuring vital signs. This study aims to help prevent hospitalization of patients in the ICU by continuously monitoring the patient’s vital signs, which allows medical staff to diagnose the patient’s health at the appropriate time. The use of sensors has grown in many areas over the past decade, especially in wearable healthcare devices. In this paper, the hardware components, and the design structure of the bracelet have been presented. The bracelet is responsible for measuring and transferring vital signs like body temperature, oxygen saturation, and heart rate to the Base Control Unit. The Max 30100 and DS18B20 sensors are used to read the vital signs of the patient and transmit them to the microcontroller inside the bracelet. The microcontroller will send vital signs data to the Raspberry Pi to analyse, process, save, and display. The design and implementation of this bracelet have been done by developing a 3D printed model after examining several models on people of different ages.

Detection and Analysis of Oil Spill using Image Processing

Abstract: —Thousands of oil spills occur every year on offshore oil production platforms. Moreover, ships that crosses rivers to reach the harbor cause spills each year. The current study focuses on IRAQI marine and rivers, especially Al-Bakr, Khor al-Amaya, ABOT oil terminal and SHAT AL-Arab river inside Al Başrah oil terminal. In order to mitigate and manage oil spill impacts, an unmanned aerial vehicle has proven to be a valuable tool in mitigating and managing incidents. To achieve high accuracy, the objective of the current research is to analyze captured images for rivers, identify oil pollution and determine its location. The images were taken from the Iraqi Regional Organization for the Protection, General Company for Ports of Iraq, Iraqi Ministry of Environment and online websites. In the current paper is presented a software framework for detecting oil spills, pollution in rivers and other kinds of garbage. The framework based on artificial intelligence is divided into two parts: a training model and an operational model. In the training model part, a machine learning model is applied, which is one of the fastest and most accurate methods, integrated inside PipelineMLML. Thus, the object detection technique used can identify one or more categories of objects in a picture or video. Furthermore, the locations of objects can be identified with the help of neural networks. In the operational mode, models can identify oil spills in images.

English and Romanian Brain-to-Text Brain-Computer Interface Word Prediction System

Abstract: —Brain-Computer Interface (BCI) can recognise the thoughts of a human through various electrophysiological signals. Electrodes (sensors) placed on the scalp are used to detect these signals, or by using electrodes implanted inside the brain. Usually, BCI can detect brain activity through different neuroimage methods, but the most preferred is Electroencephalography (EEG) because it is a non-invasive and non-critical method. BCI systems applications are very helpful in restoring functionalities to people suffering from disabilities due to different reasons. In this study, a novel brain-to-text BCI system is presented to predict the word that the subject is thinking. This brain-to-text can assist mute people or those who cannot communicate with others due to different diseases to restore some of their abilities to interact with the surrounding environment and express themselves. In addition, brain-to-text may be used in different control or entertainment applications. EMOTIV™ Insight headset has been used to collect EEG signals from the subject’s brain. Feature extraction of EEG signals for BCI systems is very important to classification performance. Statistical-based feature extraction has been used in this system to extract valuable features to be used for classification. The datasets are sentences involving some commonly used words in English and Romanian languages. The results of the English language elucidated that K-Nearest neighbour (KNN) has a prediction accuracy of 86.7%, 86.1% for Support Vector Machine (SVM), and 79.2% for Linear discriminant analysis (LDA), while the Romanian language has a prediction accuracy of 96.1%, 97.1%, and 94.8% for SVM, LDA, and KNN respectively. This system is a step forward in developing advanced brain-to-text BCI prediction systems.

Virtual Reality Application for Acute Pain Therapy - User Experience

Abstract: The use of Virtual Reality applications under the form of serious games is gaining traction in the medical domain. The development is pushed by new technological advancements in immersive Virtual Reality technology, improved game-engines and improved hardware capabilities. The user experience is an important aspect that needs to be taken into consideration while developing serious games for medical purpose. In this article we show the methods we have applied in our custom-made serious game application for pain therapy, in order to obtain and to analyse relevant user experience data. The two main tools that we have used were the System Usability Scale and the Short User Experience Questionnaire. We have used the mentioned tools to get information regarding the complexity of our system, integrity, usability, ease of use and most importantly the effects on pain. Other information that we took in consideration were game performance, user friendliness, user motivation, and user enjoyment. The results show that our initial prototype has a consistent and sustainable development as well as a noticeable effect on reducing the pain felt by the users.

Software Implementation of a Smart Bracelet Prototype to Monitor Vital Signs, Locate, and Track COVID-19 Patients in Quarantine Zone

Abstract: This paper describes the design and software implementation of a wearable prototype that allows users to monitor the vital signs of COVID-19 patients in quarantine areas. This prototype consists of two parts, the bracelet, andthe Base control unit (BCU). The bracelet is built with ESP8266 and sensors as main components, as well as the battery and other parts needed to fulfill the system's purpose (monitoring the vital signs of COVID-19 patients). At the same time, the Raspberry Pi (SCB) single board computer and GSM/GPRS/HAT are the main components of the Basic Control Unit (BCU). The current work describes the main parts of the pseudocode, as well as the activity diagram for the microcontroller and Raspberry Pi. This paper describes the mechanism of sending alert messages, whereby the system's ability to configure two types of alert messages; (1) physician Messages (these Messages will be sent to the physicianassociated with the patient if one or more vital signs reach a critical value; these messages contain all measurements of a patient's vital signs); (2) Authorize messages (these messages will be sent if the quarantine rules are violated; the patient's location will be sent to the authorized person as a Google Mapslink). Also, this paper describes the graphical user interface for communication, management,. and interaction between the users of the system.

An Innovative Blockchain System for Smart Grids

Abstract: Smart grids are one of the most advanced technologies that can intelligently integrate generators, consumers and energy storage. TESTBED2 is a large interdisciplinary European research project that focuses on developing new techniques to improve the scalability of smart grid services using new technologies such as blockchain. In the current paper we explained a general architecture of Testbed2 system that includes blockchain as a certification authority. Next to the description of the system in the current paper we present the blockchain implementation together with policies for smart grid authorization.

Human individuals' localization monitoring (using open source technologies)

Abstract: Remote human beings location monitoring through methods that are provided remotely managed open source services, becomes a required component in many public and private systems that work with human beings and for theirs benefits (in this category can also be included citizens with a certain degree of disability, or having limited movement areas).

Medical System for Tests Analysis and Symptom Checker

Abstract: The covid-19 pandemic brought the need to reduce human interaction so in order to facilitate the interaction with the doctors but reduce unnecessary trips to a medical specialty, and have a better understanding of the investigation result, we present our approach of a medical test interpreter, integrated with a symptom checker. Our system aims to provide a temporary solution for diagnostic a condition until the patient reaches a doctor, so a proper diagnose can be made. This system can also be used in low-income countries were access to healthcare is limited and people discover diseases too late.

Computer Kinesiotherapy Movement Simulator

Abstract: Serious games are an integral part of our modern life. They are mainly used as tools for training individuals in different fields such as industrial, automotive, or in medical domain. The current research presents an interesting approach on the use of serious games. The main concept is based on the use of serious games to showcase multiple series of kinesiotherapy movements meant to prevent medical problems like arthritis, posture disorders, acute or chronic pain, muscle strength conditions or work-related injuries. The application presented in this paper offers the users the possibility to execute specific kinesiotherapy movements from home, after an initial session with the therapist for a in depth explanation of the application and the purpose of the exercises. This application would improve the quality of life of individuals as it would provide an alternative solution to normal sessions of kinesiotherapy and prevent usual problems caused by sedentarism or muscle injuries.