Gavriloski, Viktor

Preferred name

Gavriloski, Viktor

Official Name

Gavriloski, Viktor

Main Affiliation

viktor.gavriloski@mf.edu.mk

Now showing 1 - 10 of 12

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Modular Origami Robot Inspired by a Scorpion Tail
(American Society of Mechanical Engineers, 2018-09-10)
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Anachkova, Maja
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Petrevski, Dimitar
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Grazhdani, Franka
<jats:p>Arthropod animals like scorpions with modular body parts can be an inspiration for a robot’s structure. The design presented here relays on inter-connected origami towers, but could also be easily disassembled. Each origami tower is fully autonomous and at the same time is part of the robot as a whole. The towers are positioned between two platforms that enable modularity. The scorpion’s tale shape is achieved by the varying platform diameter resulting in cone-like form. Each tower is actuated independently to enable multiple degrees of freedom. Maneuvering with separated units, assists in easier reparation as well as replacement. Detaching the towers into separate parts makes this structure develop more precise movements, since every unit will move autonomously. Therefore, having a higher number of separated movements combined leads to a smooth bionic movement. So, the overall hierarchy will be modular contributing to a greater curvature bending of the whole structure. Actuating and maneuvering the robot in the main concept is done by separated electro motors, built in the platform. The basic structure will be built from thick paper with plastic coatings. The thick paper itself is lightweight, but at the same time flexible. To protect the paper towers, double plastic foil is placed as an outer coating which acts as an origami cover. This transparent layer is elastic hence it can follow and support the individual units’ movements.</jats:p> <jats:p>This work is focused on understanding origami towers kinematics and different combinations of inter-connected towers to achieve multiple degrees of freedom. A conceptual model is developed, supported by CAD and mathematical models. At the end a prototype is presented.</jats:p>
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Glass - steel hybrid elements under four point bending test
(Centre for Evaluation in Education and Science (CEON/CEES), 2015)
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Problems evolving from the brittleness of structural glass result in need of innovative solutions which will improve the post-breakage behavior of the elements in the structure. As the need of the glass performance gets higher, the fully tempered glass gets in the focus and its usage becomes greater. But although this type of glass gives great performance with its tensile strength and deflection capacity, it has no residual strength. Due to its breakage pattern into small pieces the collapse of the element may be instant even in laminated glass elements. Thus, increasing the post breakage behavior is crucial in order to keep the integrity of the tempered glass element. This can be done either by changing the inter layer properties, or including kind of reinforcement in the element structure. This paper presents experimental testing of the performances of steel plate reinforced hybrid glass element under four point bending test. As a result, it shows the improvement in mechanical behavior of the described hybrid structure concept compared to a monolithic glass element with same dimensions, by means of stress distribution and reinforcement capacity.
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Design of low-cost wireless noise monitoring sensor unit based on IoT concept
(JVE International Ltd., 2021-01-22)
Anachkova, Maja
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Domazetovska, Simona
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Experimental analysis of mechanical characteristics of FRP materials
(MASE - Macedonian Association of Structural Engineers, 2015-10)
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AI Supported Noise Analyses for Structure Design Requirements Definition
(American Society of Mechanical Engineers, 2021-09-14)
Domazetovska, Simona
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<jats:title>Abstract</jats:title> <jats:p>The artificial intelligence (AI) field has encountered a turning point mainly due to advancements in machine learning, which allows systems to learn, improve, and perform a specific task through data without being explicitly programmed. Machine learning can be utilized with machining processes to improve product quality levels and productivity rates and to optimize design and process parameters. The systems for acoustic event detection and classification (AED/C) of noise events is a process consisted of feature extraction of the signals, meaning processing acoustic signals and converting them into symbolic descriptions that correspond to the various sound events present in the signals and their sources. The main objective of the AED/C systems is to develop algorithms able to recognize and classify sound events that occur in the chosen environment, giving an appropriate response to users.</jats:p> <jats:p>By utilizing the acoustic events detection and classification systems, a clear set of design requirements can be extracted based on the noise to be attenuated. A smart structure design for noise attenuation needs clear noise input for proper smart material choice, placement and active control. This paper shows a method for detection of noise events based on machine-learning algorithm that can be further used for definition of design requirements.</jats:p>
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The impact of COVID-19 lockdown on the noise pollution: case study in the city of Skopje
(Institute of Noise Control Engineering (INCE), 2021-08-01)
Domazetovska, Simona
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Anachkova, Maja
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Sokolikj, Ankica
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Stojkovska, Sandra
<jats:p>The lockdown that the city of Skopje has suffered during the months of April to June 2020 in order to control the spread of COVID-19 has significantly changed the acoustic environment in the urban parts of the city. The absence of vehicles, people on the streets and closed restaurants has led to a noise reduction captured by the low-cost wireless sensor network in the City of Skopje. The analysis carried out in this paper show reduction in noise pollution strongly correlated with the population's activity and behavior to the new circumstances. Overall, the sound pressure levels vary around 65 dB; however, some extreme decrease can be noticed, especially during the quarantine weekends. Also, the noise levels were compared between the same time periods during the year of 2019 and 2020, where it can be perceived reduction in the sound level for 36,5% for the day-evening-night noise level indicator (L). Significant variations occur for the indicators L, L, and L, especially during the lockdown weekends.</jats:p>
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Design and development of a planar MEMS microphone array
(Institute of Noise Control Engineering (INCE), 2025-10-22)
Pecioski, Damjan
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Domazetovska Markovska, Simona
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Anachkova, Maja
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Shishkovski, Dejan
<jats:p>In the last few years viewing an audio source has become a widely used tool in many fields such as speech recognition and enhancement and especially in noise localization in different environments. Acoustic cameras are widely used as a tool for noise source investigation, however an acoustic image is difficult to achieve in environments with a large amount of noise and reverberation. An effective approach to overcome this is the use of beamforming theory coupled with a microphone array in order to obtain a recording of the desired acoustic signal. The aim of this work is to design and develop a low cost microphone array which can be upgraded with a camera, i.e. acoustic camera, based on digital MEMS microphones and a raspberry pi. Different formations of the microphone array are developed, tested and compared. The details on hardware integration as well as the development environment are discussed in this paper.</jats:p>
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Urban Sound Classification for IoT Devices in Smart City Infrastructures
(MDPI AG, 2025-12-05)
Domazetovska Markovska, Simona
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Pecioski, Damjan
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Anachkova, Maja
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Shishkovski, Dejan
<jats:p>Urban noise is a major environmental concern that affects public health and quality of life, demanding new approaches beyond conventional noise level monitoring. This study investigates the development of an AI-driven Acoustic Event Detection and Classification (AED/C) system designed for urban sound recognition and its integration into smart city application. Using the UrbanSound8K dataset, five acoustic parameters—Mel Frequency Cepstral Coefficients (MFCC), Mel Spectrogram (MS), Spectral Contrast (SC), Tonal Centroid (TC), and Chromagram (Ch)—were mathematically modeled and applied to feature extraction. Their combinations were tested with three classical machine learning algorithms: Support Vector Machines (SVM), Random Forest (RF), Naive Bayes (NB) and a deep learning approach, i.e., Convolutional Neural Networks (CNN). A total of 52 models with the three ML algorithms were analyzed along with 4 models with CNN. The MFCC-based CNN models showed the highest accuracy, achieving up to 92.68% on test data. This achieved accuracy represents approximately +2% improvement compared to prior CNN-based approaches reported in similar studies. Additionally, the number of trained models, 56 in total, exceeds those presented in comparable research, ensuring more robust performance validation and statistical reliability. Real-time validation confirmed the applicability for IoT devices, and a low-cost wireless sensor unit (WSU) was developed with fog and cloud computing for scalable data processing. The constructed WSU demonstrates a cost reduction of at least four times compared to previously developed units, while maintaining good performance, enabling broader deployment potential in smart city applications. The findings demonstrate the potential of AI-based AED/C systems for continuous, source-specific noise classification, supporting sustainable urban planning and improved environmental management in smart cities.</jats:p>
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Modeling and Simulation of an Electromagnetic Energy Harvesting System
(IEEE, 2024-06-11)
Pecioski, Damjan
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Shishkovski, Dejan
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Ignajatovska, Anastasija Angjusheva
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Markovska, Simona Domazetovska
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Low-power electronic devices can be powered using the concepts of micro-scale energy harvesting techniques to ensure a near-infinite lifetime work cycle. Nonetheless, this conversion of energy is not ideal and as a result, there is always a certain percentage of wasted energy. One must strive that the modeling and simulation of these systems is as close as possible to the real systems and conditions. Within this paper, an electromagnetic energy harvesting system that is attached to an elastic mechanical structure in the form of a cantilever beam has been developed. A mathematical model for the structure and the linear electromagnetic generator has been derived. The simulations concerning the obtained model have been conducted using the Matlab/Simulink software package. Finally, an experimental model has been created to validate the prior acquired results from the simulation.
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Statistical Analysis of Urban Noise Measurements Data: Case Study for the City of Skopje
(EuroRegio, 2022)
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Nikolovski, Filip
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Gavriloski, Viktor

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