1,170 research outputs found

    Wavelet based joint denoising of depth and luminance images

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    In this paper we present a new method for joint denoising of depth and luminance images produced by time-of-flight camera. Here we assume that the sequence does not contain outlier points which can be present in the depth images. Our method first performs estimation of noise and signal covariance matrices and then performs vector denoising. Two versions of the algorithm are presented, depending on the method used for the classification of the image contexts. Denoising results are compared with the ground truth images obtained by averaging of the multiple frames of the still scene

    Depth video enhancement for 3D displays

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    At the current stage of technology, depth maps acquired using cameras based on a time-of-flight principle have much lower spatial resolution compared to images that are captured by conventional color cameras. The main idea of our work is to use high resolution color images to improve the spatial resolution and image quality of the depth maps

    Wavelet based stereo images reconstruction using depth images

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    It is believed by many that three-dimensional (3D) television will be the next logical development toward a more natural and vivid home entertaiment experience. While classical 3D approach requires the transmission of two video streams, one for each view, 3D TV systems based on depth image rendering (DIBR) require a single stream of monoscopic images and a second stream of associated images usually termed depth images or depth maps, that contain per-pixel depth information. Depth map is a two-dimensional function that contains information about distance from camera to a certain point of the object as a function of the image coordinates. By using this depth information and the original image it is possible to reconstruct a virtual image of a nearby viewpoint by projecting the pixels of available image to their locations in 3D space and finding their position in the desired view plane. One of the most significant advantages of the DIBR is that depth maps can be coded more efficiently than two streams corresponding to left and right view of the scene, thereby reducing the bandwidth required for transmission, which makes it possible to reuse existing transmission channels for the transmission of 3D TV. This technique can also be applied for other 3D technologies such as multimedia systems. In this paper we propose an advanced wavelet domain scheme for the reconstruction of stereoscopic images, which solves some of the shortcommings of the existing methods discussed above. We perform the wavelet transform of both the luminance and depth images in order to obtain significant geometric features, which enable more sensible reconstruction of the virtual view. Motion estimation employed in our approach uses Markov random field smoothness prior for regularization of the estimated motion field. The evaluation of the proposed reconstruction method is done on two video sequences which are typically used for comparison of stereo reconstruction algorithms. The results demonstrate advantages of the proposed approach with respect to the state-of-the-art methods, in terms of both objective and subjective performance measures

    Π£Π»ΠΎΠ³Π°Ρ‚Π° ΠΈ Π·Π½Π°Ρ‡Π΅ΡšΠ΅Ρ‚ΠΎ Π½Π° оркСстарот Π½Π° Π½Π°Ρ€ΠΎΠ΄Π½ΠΈ инструмСнти Π½Π° макСдонската Ρ€Π°Π΄ΠΈΠΎ Ρ‚Π΅Π»Π΅Π²ΠΈΠ·ΠΈΡ˜Π° Π²ΠΎ ΠΎΠ΄Ρ€ΠΆΡƒΠ²Π°ΡšΠ΅Ρ‚ΠΎ Π½Π° сопствСната ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠ° Ρ‚Ρ€Π°Π΄ΠΈΡ†ΠΈΡ˜Π°

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    Π’ΠΎ Π³Π΅Π½Π΅Ρ€Π°Π»Π½Π°Ρ‚Π° ΠΏΡ€Π΅Π·Π΅Π½Ρ‚Π°Ρ†ΠΈΡ˜Π° Π½Π° макСдонската ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠ° ΠΊΡƒΠ»Ρ‚ΡƒΡ€Π°,Π·Π½Π°Ρ‡Π°Π΅Π½ сСгмСнт Π·Π°Π·Π΅ΠΌΠ° Π·Π²ΡƒΡ‡Π½Π°Ρ‚Π° Π½Π°Π΄Π³Ρ€Π°Π΄Π±Π° Π½Π° макСдонската Ρ‚Ρ€Π°Π΄ΠΈΡ†ΠΈΠΎΠ½Π°Π»Π½Π° ΠΌΡƒΠ·ΠΈΠΊΠ°. Π’ΡΡƒΡˆΠ½ΠΎΡΡ‚, ΠΎΠ²Π°Π° ΠΌΡƒΠ·ΠΈΠΊΠ° сС Ρ‚Π΅ΠΌΠ΅Π»ΠΈ Π½Π° ΠΏΠΎΡΡ‚ΠΎΡ˜Π°Π½Π°Ρ‚Π° ΠΈ Π½Π΅ΠΏΡ€Π΅ΡΡƒΡˆΠ½Π° ΠΈΠ½ΡΠΏΠΈΡ€Π°Ρ†ΠΈΡ˜Π° ΠΎΠ΄ Ρ‚Ρ€Π°Π΄ΠΈΡ†ΠΈΠΎΠ½Π°Π»Π½ΠΈΠΎΡ‚ Π½Π°Ρ€ΠΎΠ΄Π΅Π½ мСлос Π²ΠΎ Π³Ρ€Π°Π΄Π΅ΡšΠ΅Ρ‚ΠΎ Π½Π° сопствСниот ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠΈ ΠΈΠ·Ρ€Π°Π·. Π“Π»Π΅Π΄Π°Π½ΠΎ ΠΎΠ΄ историско-ΡΠΎΡ†ΠΈΠΎΠ»ΠΎΡˆΠΊΠΈ ΠΈ ΠΌΡƒΠ·ΠΈΠΊΠΎΠ»ΠΎΡˆΠΊΠΈ аспСкт, ΠΏΠΎΡ‡Π΅Ρ‚ΠΎΠΊΠΎΡ‚ Π½Π° ΠΏΡ€Π΅Π·Π΅Π½Ρ‚ΠΈΡ€Π°ΡšΠ΅Ρ‚ΠΎ ΠΈ ΡˆΠΈΡ€ΠΎΠΊΠΎΡ‚ΠΎ ΠΏΠΎΠΏΡƒΠ»Π°Ρ€ΠΈΠ·ΠΈΡ€Π°ΡšΠ΅ Π½Π° овој ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠΈ ΠΆΠ°Π½Ρ€ Π΅ комплСксна појава тСсно ΠΏΠΎΠ²Ρ€Π·Π°Π½Π° со: – ΠΏΠΎΡ‚Ρ€Π΅Π±Π°Ρ‚Π° ΠΎΠ΄ Π½Π΅Π³ΡƒΠ²Π°ΡšΠ΅ ΠΈ ΠΏΡ€Π΅Ρ‚ΡΡ‚Π°Π²ΡƒΠ²Π°ΡšΠ΅ Π½Π° сопствСната ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠ° ΠΊΡƒΠ»Ρ‚ΡƒΡ€Π°; – ΠΏΠΎΡ‚Π²Ρ€Π΄Π°Ρ‚Π° Π½Π° сопствСниот ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠΈ ΠΈΠ΄Π΅Π½Ρ‚ΠΈΡ‚Π΅Ρ‚; – ΠΏΡ€ΠΈΠ²Π»Π΅ΠΊΡƒΠ²Π°ΡšΠ΅Ρ‚ΠΎ Π½Π° Π΅Π΄Π½Π° ΠΏΠΎΡˆΠΈΡ€ΠΎΠΊΠ° структура Π½Π° ΡΠ»ΡƒΡˆΠ°Ρ‚Π΅Π»ΠΈ ΠΈ – ΠΎΡ‚Π²ΠΎΡ€Π°ΡšΠ΅Ρ‚ΠΎ Π½Π° моТноста Π·Π° Π³ΠΎΠ»Π΅ΠΌ Π±Ρ€ΠΎΡ˜ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡƒΠ°Π»Ρ†ΠΈ Π΄Π° сС ΠΎΠΏΡ€Π΅Π΄Π΅Π»Π°Ρ‚Π·Π° профСсионално ΠΏΠΎΡΠ²Π΅Ρ‚ΡƒΠ²Π°ΡšΠ΅ Π½Π° ΠΎΠ²Π° ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠΎ ΠΏΠΎΠ»Π΅

    Content adaptive wavelet based method for joint denoising of depth and luminance images

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    In this paper we present a new method for joint denoising of depth and luminance images produced by time-of-flight camera. Here we assume that the sequence does not contain outlier points which can be present in the depth images. Our method first performs estimation of noise and signal covariance matrices and then performs vector denoising. Luminance image is segmented into similar contexts usina k-means algorithm, which are used for calculation of covariance matrices. Denoising results are compared with the ground truth images obtained by averaging of the multiple frames of the still scene

    ΠšΠΎΡ€Π΅Π½ΠΈ, ΠŸΠ΅Ρ‡Π°Π»Π±Π°Ρ€ΡΠΊΠΈ ΠΌΠ΅Ρ€Π°ΠΊ

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    Автор Π½Π° ΠΌΡƒΠ·ΠΈΠΊΠ° ΠΈ Π°Ρ€Π°Π½ΠΆΠΌΠ°Π½: Π˜Π»Ρ‡ΠΎ Јованов Π‘ΠΎ исклучок Π½Π° Π±Ρ€.6 ΠΈ10 Π°Ρ€Π°Π½ΠΆΠΌΠ°Π½: Π‘Π»Π°Π³ΠΎΡ˜Π° ДСскоски ΠœΡƒΠ·ΠΈΠΊΠ°Ρ‚Π° Π½Π° овој авторски Π°Π»Π±ΡƒΠΌ Π΅ ΠΈΠ·Π±ΠΎΡ€ ΠΎΠ΄ Π΅Π΄Π½ΠΎ мошнС ΠΎΠ±Π΅ΠΌΠ½ΠΎ Ρ‚Π²ΠΎΡ€Π΅ΡˆΡ‚Π²ΠΎ Π½Π° Π΅Π΄Π΅Π½ нСсСкојднСвСн ΠΌΡƒΠ·ΠΈΡ‡Π°Ρ€. β€žΠšΠΎΡ€Π΅Π½ΠΈβ€œ Π΅ ΠΏΡ€ΠΈΠΊΠ°Π·Π½Π° Π·Π° Π΅Π΄Π΅Π½ Π²Ρ™ΡƒΠ±Π΅Π½ΠΈΠΊ Π²ΠΎ Ρ…Π°Ρ€ΠΌΠΎΠ½ΠΈΠΊΠ°Ρ‚Π° кој сиот свој ΠΆΠΈΠ²ΠΎΡ‚ Π½Π΅ прСстанал Π΄Π° создава ΠΌΡƒΠ·ΠΈΠΊΠ° Π²ΠΎ Π΄ΡƒΡ…ΠΎΡ‚ ΠΈ Ρ‚Ρ€Π°Π΄ΠΈΡ†ΠΈΡ˜Π°Ρ‚Π° Π½Π° ΡΠ²ΠΎΡ˜ΠΎΡ‚ Π½Π°Ρ€ΠΎΠ΄. ПослС ΠΌΠ½ΠΎΠ³Ρƒ напишани ΠΊΠΎΠΌΠΏΠΎΠ·ΠΈΡ†ΠΈΠΈ, оркСстрации ΠΈ солистички ΠΈΠ·Π²Π΅Π΄Π±ΠΈ Π˜Π»Ρ‡ΠΎ Јованов Π½ΠΈ сС прСтставува со овој компилациски осврт, опус кој Π·Π°ΠΏΠΎΡ‡Π½Π°Π» Π΄Π° сС создава ΠΏΡ€Π΅Π΄ Ρ‚Ρ€ΠΈ Π΄Π΅Ρ†Π΅Π½ΠΈΠΈ. Π ΠΎΠ΄Π΅Π½ Π΅ Π²ΠΎ Π¨Ρ‚ΠΈΠΏ Π²ΠΎ 1962 Π³ΠΎΠ΄ΠΈΠ½Π°. УчСствува Π½Π° ΠΌΠ½ΠΎΠ³Ρƒ фСстивали ΠΈ ΠΊΠΎΠ½Ρ†Π΅Ρ€Ρ‚ΠΈΡ€Π° насСкадС ΠΏΠΎ свСтот. Автор Π΅ Π½Π° Π³ΠΎΠ»Π΅ΠΌ Π±Ρ€ΠΎΡ˜ ΠΊΠΎΠΌΠΏΠΎΠ·ΠΈΡ†ΠΈΠΈ, Π°Ρ€Π°Π½ΠΆΠΌΠ°Π½ΠΈ ΠΈ оркСстрации инспирирани ΠΎΠ΄ макСдонскиот Ρ„ΠΎΠ»ΠΊΠ»ΠΎΡ€. Π—Π° Π½Π΅Π³ΠΎΠ²ΠΈΠΎΡ‚ ΡƒΠΌΠ΅Ρ‚Π½ΠΈΡ‡ΠΊΠΈ придонСс Π΄ΠΎΠ΄Π΅Π»Π΅Π½ΠΈ ΠΌΡƒ сС Π±Ρ€ΠΎΡ˜Π½ΠΈ Π²Ρ€Π²Π½ΠΈ Π½Π°Π³Ρ€Π°Π΄ΠΈ ΠΈ ΠΏΡ€ΠΈΠ·Π½Π°Π½ΠΈΡ˜Π° ΠΌΠ΅Ρ“Ρƒ ΠΊΠΎΠΈ особСно мСсто Π·Π°Π·Π΅ΠΌΠ° β€žΠŸΡ€Π²Π° Ρ…Π°Ρ€ΠΌΠΎΠ½ΠΈΠΊΠ° Π½Π° ΠˆΡƒΠ³ΠΎΡΠ»Π°Π²ΠΈΡ˜Π°β€œ освоСна Π½Π° прСстиТниот Π½Π°Ρ‚ΠΏΡ€Π΅Π²Π°Ρ€ Π²ΠΎ Π‘ΠΎΠΊΠΎ Π‘Π°ΡšΠ° (ΠΏΠΎΡ€Π°Π½Π΅ΡˆΠ½Π° ΠˆΡƒΠ³ΠΎΡΠ»Π°Π²ΠΈΡ˜Π°) Π²ΠΎ 1982 Π³ΠΎΠ΄ΠΈΠ½Π°. Π”ΠΈΠΏΠ»ΠΎΠΌΠΈΡ€Π°Π» Π½Π° Π€Π°ΠΊΡƒΠ»Ρ‚Π΅Ρ‚ΠΎΡ‚ Π·Π° ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠ° умСтност Π²ΠΎ БкопјС, магистрирал Π½Π° Π”Ρ€ΠΆΠ°Π²Π½Π°Ρ‚Π° ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠ° акадСмија β€žΠŸΠ°Π½Ρ‡ΠΎ Π’Π»Π°Π΄ΠΈΠ³Π΅Ρ€ΠΎΠ²'' Π²ΠΎ Π‘ΠΎΡ„ΠΈΡ˜Π° Π° ΡΠ²ΠΎΡ˜ΠΎΡ‚ Π΄ΠΎΠΊΡ‚ΠΎΡ€Π°Ρ‚ ΠΎΠ΄ областа Π½Π° ΠœΡƒΠ·ΠΈΡ‡ΠΊΠ°Ρ‚Π° Ρ‚Π΅ΠΎΡ€ΠΈΡ˜Π° ΠΈ пСдагогија Π³ΠΎ стСкнува Π½Π° MΠ΅Ρ“ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½ΠΈΠΎΡ‚ Π£Π½ΠΈΠ²Π΅Ρ€Π·ΠΈΡ‚Π΅Ρ‚ Π²ΠΎ КиСв, Π£ΠΊΡ€Π°ΠΈΠ½Π°. ΠŸΡ€ΠΎΡ„Π΅ΡΠΎΡ€ Π΄-Ρ€ Π˜Π»Ρ‡ΠΎ Јованов ΠΎΠ΄ 2007 Π³ΠΎΠ΄ΠΈΠ½Π° Π΅ Π΄Π΅ΠΊΠ°Π½ Π½Π° Π€Π°ΠΊΡƒΠ»Ρ‚Π΅Ρ‚ΠΎΡ‚ Π·Π° ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠ° умСтност ΠΏΡ€ΠΈ Π£Π½ΠΈΠ²Π΅Ρ€Π·ΠΈΡ‚Π΅Ρ‚ΠΎΡ‚ ,,Π“ΠΎΡ†Π΅ Π”Π΅Π»Ρ‡Π΅Π²'' Π²ΠΎ Π¨Ρ‚ΠΈΠΏ Π Π΅ΠΏΡƒΠ±Π»ΠΈΠΊΠ° МакСдонија

    Analysis of information threats and counteractions in consumer oriented organizations (separating the best from the rest

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    Generation Y, what do they really want? It’s the 21st century and the greatest consumers of information ever are on roll. Consumers are embracing a digital lifestyle and enterprises are interacting in new ways. In times like this, when the information are the companies most valuable resource, the issue about information threats and security should be their top priority. With opportunities come risks and protection is about more than just technology, it’s about people, process and technology. While some companies are struggling to survive, others are rethinking their business strategies and redesigning the marketing practices to build more profitable, enduring relationships with their customers

    ΠšΠΎΡ€Π΅Π½ΠΈ, Π˜Π»Ρ‡ΠΎΠ²ΠΎ ΠΎΡ€ΠΎ

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    Автор Π½Π° ΠΌΡƒΡ‡ΠΈΡ‡ΠΊΠΈ Π°Ρ€Π°ΠΆΠΌΠ°Π½: Π˜Π»Ρ‡ΠΎ Јованов Π‘ΠΎ исклучок Π½Π° Π±Ρ€. 6 ΠΈ 10 Π°Ρ€Π°ΠΆΠΌΠ°Π½: Π‘Π»Π°Π³ΠΎΡ˜Π° ДСскоски ΠœΡƒΠ·ΠΈΠΊΠ°Ρ‚Π° Π½Π° овој авторски Π°Π»Π±ΡƒΠΌ Π΅ ΠΈΠ·Π±ΠΎΡ€ ΠΎΠ΄ Π΅Π΄Π½ΠΎ мошнС ΠΎΠ±Π΅ΠΌΠ½ΠΎ Ρ‚Π²ΠΎΡ€Π΅ΡˆΡ‚Π²ΠΎ Π½Π° Π΅Π΄Π΅Π½ нСсСкојднСвСн ΠΌΡƒΠ·ΠΈΡ‡Π°Ρ€. β€žΠšΠΎΡ€Π΅Π½ΠΈβ€œ Π΅ ΠΏΡ€ΠΈΠΊΠ°Π·Π½Π° Π·Π° Π΅Π΄Π΅Π½ Π²Ρ™ΡƒΠ±Π΅Π½ΠΈΠΊ Π²ΠΎ Ρ…Π°Ρ€ΠΌΠΎΠ½ΠΈΠΊΠ°Ρ‚Π° кој сиот свој ΠΆΠΈΠ²ΠΎΡ‚ Π½Π΅ прСстаналда создава ΠΌΡƒΠ·ΠΈΠΊΠ° Π²ΠΎ Π΄ΡƒΡ…ΠΎΡ‚ ΠΈ Ρ‚Ρ€Π°Π΄ΠΈΡ†ΠΈΡ˜Π°Ρ‚Π° Π½Π° ΡΠ²ΠΎΡ˜ΠΎΡ‚ Π½Π°Ρ€ΠΎΠ΄. ПослС ΠΌΠ½ΠΎΠ³Ρƒ напишани ΠΊΠΎΠΌΠΏΠΎΠ·ΠΈΡ†ΠΈΠΈ, оркСстрации ΠΈ солистички ΠΈΠ·Π²Π΅Π΄Π±ΠΈ Π˜Π»Ρ‡ΠΎ Јованов Π½ΠΈ сС прСтставува со овој компилациски осврт, опус кој Π·Π°ΠΏΠΎΡ‡Π½Π°Π» Π΄Π° сС создава ΠΏΡ€Π΅Π΄ Ρ‚Ρ€ΠΈ Π΄Π΅Ρ†Π΅Π½ΠΈΠΈ. Π ΠΎΠ΄Π΅Π½ Π΅ Π²ΠΎ Π¨Ρ‚ΠΈΠΏ Π²ΠΎ 1962 Π³ΠΎΠ΄ΠΈΠ½Π°. УчСствува Π½Π° ΠΌΠ½ΠΎΠ³Ρƒ фСстивали ΠΈ ΠΊΠΎΠ½Ρ†Π΅Ρ€Ρ‚ΠΈΡ€Π° насСкадС ΠΏΠΎ свСтот. Автор Π΅ Π½Π° Π³ΠΎΠ»Π΅ΠΌ Π±Ρ€ΠΎΡ˜ ΠΊΠΎΠΌΠΏΠΎΠ·ΠΈΡ†ΠΈΠΈ, Π°Ρ€Π°Π½ΠΆΠΌΠ°Π½ΠΈ ΠΈ оркСстрации инспирирани ΠΎΠ΄ макСдонскиот Ρ„ΠΎΠ»ΠΊΠ»ΠΎΡ€. Π—Π° Π½Π΅Π³ΠΎΠ²ΠΈΠΎΡ‚ ΡƒΠΌΠ΅Ρ‚Π½ΠΈΡ‡ΠΊΠΈ придонСс Π΄ΠΎΠ΄Π΅Π»Π΅Π½ΠΈ ΠΌΡƒ сС Π±Ρ€ΠΎΡ˜Π½ΠΈ Π²Ρ€Π²Π½ΠΈ Π½Π°Π³Ρ€Π°Π΄ΠΈ ΠΈ ΠΏΡ€ΠΈΠ·Π½Π°Π½ΠΈΡ˜Π° ΠΌΠ΅Ρ“Ρƒ ΠΊΠΎΠΈ особСно мСсто Π·Π°Π·Π΅ΠΌΠ° β€žΠŸΡ€Π²Π° Ρ…Π°Ρ€ΠΌΠΎΠ½ΠΈΠΊΠ° Π½Π° ΠˆΡƒΠ³ΠΎΡΠ»Π°Π²ΠΈΡ˜Π°β€œ освоСна Π½Π° прСстиТниот Π½Π°Ρ‚ΠΏΡ€Π΅Π²Π°Ρ€ Π²ΠΎ Π‘ΠΎΠΊΠΎ Π‘Π°ΡšΠ° (ΠΏΠΎΡ€Π°Π½Π΅ΡˆΠ½Π° ΠˆΡƒΠ³ΠΎΡΠ»Π°Π²ΠΈΡ˜Π°) Π²ΠΎ 1982 Π³ΠΎΠ΄ΠΈΠ½Π°. Π”ΠΈΠΏΠ»ΠΎΠΌΠΈΡ€Π°Π» Π½Π° Π€Π°ΠΊΡƒΠ»Ρ‚Π΅Ρ‚ΠΎΡ‚ Π·Π° ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠ° умСтност Π²ΠΎ БкопјС, магистрирал Π½Π° Π”Ρ€ΠΆΠ°Π²Π½Π°Ρ‚Π° ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠ° акадСмија β€žΠŸΠ°Π½Ρ‡ΠΎ Π’Π»Π°Π΄ΠΈΠ³Π΅Ρ€ΠΎΠ²'' Π²ΠΎ Π‘ΠΎΡ„ΠΈΡ˜Π° Π° ΡΠ²ΠΎΡ˜ΠΎΡ‚ Π΄ΠΎΠΊΡ‚ΠΎΡ€Π°Ρ‚ ΠΎΠ΄ областа Π½Π° ΠœΡƒΠ·ΠΈΡ‡ΠΊΠ°Ρ‚Π° Ρ‚Π΅ΠΎΡ€ΠΈΡ˜Π° ΠΈ пСдагогија Π³ΠΎ стСкнува Π½Π° MΠ΅Ρ“ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½ΠΈΠΎΡ‚ Π£Π½ΠΈΠ²Π΅Ρ€Π·ΠΈΡ‚Π΅Ρ‚ Π²ΠΎ КиСв, Π£ΠΊΡ€Π°ΠΈΠ½Π°. ΠŸΡ€ΠΎΡ„Π΅ΡΠΎΡ€ Π΄-Ρ€ Π˜Π»Ρ‡ΠΎ Јованов ΠΎΠ΄ 2007 Π³ΠΎΠ΄ΠΈΠ½Π° Π΅ Π΄Π΅ΠΊΠ°Π½ Π½Π° Π€Π°ΠΊΡƒΠ»Ρ‚Π΅Ρ‚ΠΎΡ‚ Π·Π° ΠΌΡƒΠ·ΠΈΡ‡ΠΊΠ° умСтност ΠΏΡ€ΠΈ Π£Π½ΠΈΠ²Π΅Ρ€Π·ΠΈΡ‚Π΅Ρ‚ΠΎΡ‚ ,,Π“ΠΎΡ†Π΅ Π”Π΅Π»Ρ‡Π΅Π²'' Π²ΠΎ Π¨Ρ‚ΠΈΠΏ - Π Π΅ΠΏΡƒΠ±Π»ΠΈΠΊΠ° МакСдонија
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