Faculty of Computer Science and Engineering

Permanent URI for this communityhttps://repository.ukim.mk/handle/20.500.12188/5

The Faculty of Computer Science and Engineering (FCSE) within UKIM is the largest and most prestigious faculty in the field of computer science and technologies in Macedonia, and among the largest faculties in that field in the region. The FCSE teaching staff consists of 50 professors and 30 associates. These include many “best in field” personnel, such as the most referenced scientists in Macedonia and the most influential professors in the ICT industry in the Republic of Macedonia.

Browse

Search Results

Now showing 1 - 10 of 10

Some of the metrics are blocked by your
consent settings
Colonoscopy image analysis for polyp detection: A systematic review of existing approaches and opportunities
(Elsevier BV, 2025)
Albuquerque, Carlos
;
Neves, Paulo Alexandre
;
Godinho, António
;
;
Some of the metrics are blocked by your
consent settings
Virtual reality as a learning tool: Evaluating the use and effectiveness of simulation laboratories in educational settings
(Elsevier BV, 2025-01-01)
Dodevska, Mila
;
;
;
Branco, Frederico
;
Virtual Reality Laboratories (VRLs) are essential progress towards educational solutions that would allow students to learn the sometimes complex experimental processes without spending physical resources. The resources used in some experiments often require significant procurement effort, significantly impacting the environment where an experiment would be conducted. The main focus of this research is to review the possibility of using VR solutions as educational tools and innovative approaches to scientific knowledge production. This paper systematically reviews relevant publications in this area while covering several existing virtual lab solutions. The analysis shows that VRL tools can be effectively used for educational purposes, allow access to lab resources for people with disabilities, and could be used to reach the desired learning outcomes. A gap exists between natural laboratories and VRLs, especially in the collaborative aspect of the laboratory exercises. However, there is significant ongoing research on this topic and a high potential for development.
Some of the metrics are blocked by your
consent settings
Feasibility analysis of an electrogastrography sensor for digestion detection
(IEEE, 2023-03-20)
Neves, Paulo Alexandre
;
Gonçalves, Norberto Jorge
;
Varanda, Pedro
;
Simões, João
;
Pires, Filipe
This paper presents a preliminary study on the use of an electrogastrography sensor for digestion detection and monitoring. The chosen architecture is based on the BITalino platform, with a three-lead sensor array and a data acquisition and communication board. Data is gathered through Bluetooth with a computer running OpenSignals software. Although currently a process to evaluate feasibility of other devices for dietary practice is not defined, this study focusses on analysis of detection, social acceptability, comfort, and battery life. The first results seem promising, with clear detection of stomach digestion movements. However, a more refined solution must be faced in order to improve on comfort and acceptability. Future work includes data processing and logging to help detect abnormal digestion patterns and the relation with nutrition quality.
Some of the metrics are blocked by your
consent settings
Advancing methods in big data capture, integration, classification and liberation
(BioMed Central, 2023-04-27)
;
Pires, Ivan Miguel
This special issue focuses on the importance of advancing research techniques for managing and analyzing data in today’s data-rich landscape. In this editorial, we set the context and invite contributions for a BMC Collection of articles titled ‘Advancing methods in data capture, integration, classification and liberation’. The collection emphasizes the need for efficient ways to standardize, cleanse, integrate, enrich, and liberate data, highlighting recent advancements in research methods and industrial technologies that facilitate this. We invite researchers to submit their best work to the collection and to showcase the latest advancements and additions to research techniques.
Some of the metrics are blocked by your
consent settings
Wearable and mobile data analysis methodologies for personalized medicine
(Frontiers, 2023-09-20)
Pires, Ivan Miguel
;
Dobre, Ciprian
;
;
Garcia, Nuno M
The Frontiers in Digital Health Research Topic Wearable and Mobile Data Analysis Methodologies for Personalized Medicine aimed to receive contributions related to the multidisciplinary field of personalized and precision medicine, which encompasses physics, statistics, telemedicine, biomedical engineering, digital signal processing, artificial intelligence, system engineering, and health privacy and security. Information and communication technologies have changed the landscape of many knowledge and societal areas, and medicine included. Bringing technology to the end users (or patients), a larger share of users can engage in personalized and precision therapies. Numerous and diverse pathologies can be monitored remotely, and as a consequence, better monitoring of health-related information may not only empower people but also hold the promise of aiding in the early detection of diseases.
Some of the metrics are blocked by your
consent settings
Smart Objects and Technologies for Social Goods
(Springer Nature, 2023-03-15)
Pires, Ivan Miguel
;
;
Garcia, Nuno Cruz
This book constitutes the refereed post-conference proceedings of the 8th EAI International Conference on Smart Objects and Technologies for social Goods, GOODTECHS 2022, held in Aveiro, Portugal, in November 16-18, 2022 The 7 full papers presented were selected from 18 submissions and issue design, implementation, deployment, operation, and evaluation of smart objects and technologies for social good. Social goods are products and services provided through private enterprises, government, or non-profit institutions and are related to healthcare, safety, sports, environment, democracy, computer science, and human rights.
Some of the metrics are blocked by your
consent settings
Corrigendum to “Extraction of notable points from ECG data: A description of a dataset related to 30-s seated and 30-s stand up”[Data in Brief, volume 46 (2023) 108874]
(Elsevier, 2023-04-01)
Duarte, Rui Pedro
;
Marinho, Francisco Alexandre
;
Bastos, Eduarda Sofia
;
Pinto, Rui João
;
Silva, Pedro Miguel
This work is funded by FCT/MEC through national funds and, when applicable, co-funded by the FEDER-PT2020 partnership agreement under the project UIDB/50008/2020. This work is also funded by FCT/MEC through national funds and, when applicable, co-funded by the FEDER-PT2020 partnership agreement under the project UIDB/00308/2020. Hanna Vitaliyivna Denysyuk is funded by the Portuguese Foundation for Science and Technology under scholarship number 2021.06685. BD
Some of the metrics are blocked by your
consent settings
Mobile and wearable technologies for the analysis of Ten Meter Walk Test: A concise systematic review
(Elsevier, 2023-05-25)
Lopes Gabriel, Cristiana
;
Pires, Ivan Miguel
;
Coelho, Paulo Jorge
;
;
Physical issues started to receive more attention due to the sedentary lifestyle prevalent in modern culture. The Ten Meter Walk Test allows measuring the person’s capacity to walk along 10 m and analyzing the advancement of various medical procedures for ailments, including stroke. This systematic review is related to the use of mobile or wearable devices to measure physical parameters while administering the Ten Meter Walk Test for the analysis of the performance of the test. We applied the PRISMA methodology for searching the papers related to the Ten Meter Walk Test. Natural Language Processing (NLP) algorithms were used to automate the screening process. Various papers published in two decades from multiple scientific databases, including IEEE Xplore, Elsevier, Springer, EMBASE, SCOPUS, Multidisciplinary Digital Publishing Institute (MDPI), and PubMed Central were analyzed, focusing on various diseases, devices, features, and methods. The study reveals that chronometer and accelerometer sensors measuring spatiotemporal features are the most pertinent in the Gait characterization of most diseases. Likewise, all studies emphasized the close relation between the quality of the sensor’s data obtained and the system’s ultimate accuracy. In other words, calibration procedures are needed because of the body part where the sensor is worn and the type of sensor. In addition, using ambient sensors providing kinematic and kinetic features in conjunction with wearable sensors and consistently acquiring walking signals can enhance the system’s performance. The most common weaknesses in the analyzed studies are the sample size and the unavailability of continuous monitoring devices for measuring the Ten Meter Walk Test.
Some of the metrics are blocked by your
consent settings
Algorithms for automated diagnosis of cardiovascular diseases based on ECG data: A comprehensive systematic review
(Elsevier, 2023-02-01)
Vitaliyivna Denysyuk, Hanna
;
Pinto, Rui Joao
;
Silva, Pedro Miguel
;
Duarte, Rui Pedro
;
Marinho, Francisco Alexandre
The prevalence of cardiovascular diseases is increasing around the world. However, the technology is evolving and can be monitored with low-cost sensors anywhere at any time. This subject is being researched, and different methods can automatically identify these diseases, helping patients and healthcare professionals with the treatments. This paper presents a systematic review of disease identification, classification, and recognition with ECG sensors. The review was focused on studies published between 2017 and 2022 in different scientific databases, including PubMed Central, Springer, Elsevier, Multidisciplinary Digital Publishing Institute (MDPI), IEEE Xplore, and Frontiers. It results in the quantitative and qualitative analysis of 103 scientific papers. The study demonstrated that different datasets are available online with data related to various diseases. Several ML/DP-based models were identified in the research, where Convolutional Neural Network and Support Vector Machine were the most applied algorithms. This review can allow us to identify the techniques that can be used in a system that promotes the patient's autonomy.
Some of the metrics are blocked by your
consent settings
Activities of Daily Living and Environment Recognition Using Mobile Devices: A Comparative Study
(MDPI AG, 2020-01-18)
Ferreira, José M.
;
Pires, Ivan Miguel
;
Marques, Gonçalo
;
García, Nuno M.
;
<jats:p>The recognition of Activities of Daily Living (ADL) using the sensors available in off-the-shelf mobile devices with high accuracy is significant for the development of their framework. Previously, a framework that comprehends data acquisition, data processing, data cleaning, feature extraction, data fusion, and data classification was proposed. However, the results may be improved with the implementation of other methods. Similar to the initial proposal of the framework, this paper proposes the recognition of eight ADL, e.g., walking, running, standing, going upstairs, going downstairs, driving, sleeping, and watching television, and nine environments, e.g., bar, hall, kitchen, library, street, bedroom, living room, gym, and classroom, but using the Instance Based k-nearest neighbour (IBk) and AdaBoost methods as well. The primary purpose of this paper is to find the best machine learning method for ADL and environment recognition. The results obtained show that IBk and AdaBoost reported better results, with complex data than the deep neural network methods.</jats:p>

Faculty of Computer Science and Engineering

Browse

Filters

Settings

Sort By

Results per page

Search Results