Naumoski, Andreja

Preferred name

Naumoski, Andreja

Official Name

Naumoski, Andreja

Translated Name

Naumoski, A.

Main Affiliation

andreja.naumoski@finki.ukim.mk

Now showing 1 - 10 of 81

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Feature Selection for Improved Classification of Protein Structures
(IEEE, 2019-05)
Mirceva, Georgina
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Classifying Protein Structures by Using Protein Ray Based Descriptor, KNN and FuzzyKNN Classification Methods
(IEEE, 2020-09-28)
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Evaluation of Yager Families of Aggregation Operators in Discovering the Diatoms Indicating Properties
(IEEE, 2018-10)
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Mirceva, Georgina
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Fuzzy aggregation operators perform operations between two fuzzy sets that satisfy certain axioms. They play an important role in fuzzy data mining process. As an integral part of many algorithms, the aggregation operators influence on the outcome of model and thus on the experimental evaluation of the models. Both pattern tree (PT) and the weighted pattern tree (WPT) algorithms use the aggregation operators to increase the accuracy of the model by making different operations between the descriptive and target attributes. Selecting the right operator is very important, especially considering generalized families of aggregation operators. Therefore, this paper aims to investigate the influence of the generalized Yager families of aggregation operators and their influence on both (PT and WPT) algorithms accuracy. This is done by modifying the λ parameter. This parameter is not the only parameter that influences the model performance, other factors are also in play, like the shape and the number of the membership functions (MFs), as well as the similarity metric. Our experimental evaluation will evaluate the descriptive and predictive performance of the models as well as the statistical significance of the results. The evaluation results show that the best descriptive and predictive models with both PT and WPT algorithms are obtained when λ is set to 1. For future work, we plan to investigate the influence of this family of aggregation operators with different similarity metrics, as well as other datasets.
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Population Analysis of Children's Clothing/Toys Stores in the City of Skopje
(IEEE, 2024-11-04)
Lekoska, Mila
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Sedmakova, Ivana
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Children growth and development can be supported by children stores that specialize in toys and clothing. Not only do these stores stock a wide variety of goods, but they also have a huge influence on the way children think, express themselves, and dress. The presence of such stores allows for a convenient and pleasant shopping experience for children and their parents, so their accessibility is crucial. This accessibility can lead to a child having a greater variety of clothing options, having more fun while playing, and having positive interactions with peers that help with their social development. The spatial dynamics of children clothing/toy stores in the city of Skopje is the subject of this research paper. This study collects and analyzes geographic data on store distribution and customer satisfaction ratings. To visualize and analyze user satisfaction scores, we use ArcGIS as well as Inverse Distance Measurement and Kriging techniques. We also use optimized hot spot analysis to find spatial patterns and clusters within the data. With this analysis, retail players gain important insights that help them optimize store locations and offers.
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Noise Pollution Measurement System - Implementation and Perspectives
(IEEE, 2021-05-26)
Meshkov, Oncho
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The noise pollution poses a high environmental risk to human health, both direct and indirect, and it can be defined as unwanted or harmful outdoor sound. The purpose of this paper is hardware and software implementation of a noise measurement and monitoring system. The system contains sound sensor (microphone), computer for processing and sampling the sound, calculating frequency and power of the sound and for communication with a server, server for storing the data computed from the measurement. This system is using Raspberry Pi 3 model B+ as a computer, because it is easy to set-up, easy to use and it is low-priced. Heroku, cloud platform, is used as a server for this system, which has a free plan for hosting. All the data calculated from the system, are stored in the server. The current system lacks the ability to be installed anywhere, because of the internet connection and the power supply and only a web application is available. For future work, we plan to solve the power supply problem using batteries and the internet connection problem using SIM cards. Furthermore, we plan to introduce a notification/alert system, to send and alert the authorities.
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Ski Slopes Digitalization and Rating Analysis of Ski Resorts in Mavrovo and Popova Shapka
(IEEE, 2019)
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Winter months are about snow, and there is no greater benefit for people that live in polluted cities to spend some time on high mountains in fresh air and sun. Therefore, the economical developing of location that offers such winter recreational activities is very important. In this direction, this paper aims to use Geographic Information Systems (GIS) to improve the understanding of the relationship between the ski resorts and a user rating of satisfactory opinion through data analysis and digitalization. GIS is a powerful digitalization and analytical tool and most importantly, the users can access the platform from anywhere and anytime. As a case study, we have considered two major ski resorts in our country, as well as rating data for customer satisfaction scores. Furthermore, as a showcase, we have digitalized one ski resorts slope. The results of this research will provide a framework for future analysis and the development of ski tourism. In the future, we plan to advance this further improve the data analysis with other data and advance the decision-making process.
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Evaluation of diatoms biodiversity models by applying different discretization on the class attribute
(IEEE, 2020-09-28)
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One of the main goals of knowledge discovery from environmental data is through data analysis to find the relationship between the living organisms, represented with the diversity of the diatoms community members, and the characteristics of the environment. This is very important information for both ecologists and decision makers. Therefore, in this paper we apply various machine learning algorithms for revealing this relationship by using different number of discretization levels for the target attribute. The target attribute represents the biodiversity index of the community and it is calculated based on the abundances of the diatoms. For building models, different types of machine learning algorithms are considered including decision trees, rule induction algorithms, neural networks and Naïve Bayes. The obtained models are also examined regarding resistance to over-fitting, as well as statistical significance.
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Modelling the Impact of the Hotel Facilities on Online Hotel Review Score for City of Skopje
(IEEE, 2018-10)
Stojchevska, Marija
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Having a reliable and objective opinion regarding their hotel facilities is very important for hotel managers. In today's internet-connected world where each year millions of travelers book, stay in, and review hotel accommodations, it is very easy to obtain desired information with the right tools. This study utilizes online data generated from thousands of guests' hotel reviews to provide comparative and benchmarking insights about the customer satisfaction through hotel review scores. Skopje, an emerging tourist destination in the Republic of Macedonia, was selected for this study. The data for this study consisted of over a thousand user-generated reviews for 80 hotels that were posted on Booking.com and Tripadviser.com. Twenty hotel facilities influencing the hotel review score were identified, such as Sauna, Spa, Fitness Center, Soundproof, Free Parking and others. Relating the review score with hotel facilities was done through visual display and graphic analysis using the ArcGIS software. This enabled us to compare the hotel review score between 3, 4 and 5-star hotels and the hotel facilities. Depending on the hotel manager's needs, the users can browse hotels through ArcGIS map hotels according to popularity, number of stars, or distance to the city center. Many of the generated graph results revealed interesting patterns that can deliver powerful feedback relationships for researchers as well as hotel managers. In the future we plan to expand our analysis on other cities to provide comprehensives data statistics for the tourist sector in Republic of Macedonia.
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Ski Slopes Digitalization and Rating Analysis of Ski Resorts in Mavrovo and Popova Shapka
(IEEE, 2019-10)
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Bodybuilding Gyms and Sports Goods Centers in Skopje
(IEEE, 2019)
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The purpose of this work is to bring bodybuilding closer to our everyday lives. Most of the time, we might feel unmotivated to go to a gym, giving ourselves unreasonable excuses, such as, there is no gym near our homes, or that its open hours do not fit our busy schedule. This project makes a contribution in three ways: 1) by collecting data for gyms in the capital city of our country, we try to undermine the excuses, 2) once the excuses are eliminated, by visual representation on the map, and by interpolation of the ratings given to each gym, we try to recommend a gym to everyone in Skopje, 3) we analyze the spatial correlation of gym ratings with the variety of sport equipment offered in the sport stores near-by.

Naumoski, Andreja

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