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Wyświetlanie 1-10 z 10
Tytuł:
Analysis of The Effectiveness of Online Electronic Learning System Using Data Traffic Network Performance Management to Succeed Merdeka Learning : Merdeka Campus During the Covid-19 Pandemic
Autorzy:
Budiyanto, Setiyo
Silalahi, Lukman Medriavin
Silaban, Freddy Artadima
Sitorus, Henry Binsar Hamonangan
Rochendi, Agus Dendi
Ismail, Mochamad Furqon
Powiązania:
https://bibliotekanauki.pl/articles/2055225.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
delay
throughput
packet loss
education
Opis:
The problems in the Covid-19 pandemic have a major influence on the field of education with the use of technology to support the teaching and learning process to facilitate students who do home learning activities. The proposed concept of freedom of learning is a more comprehensive concept such as portfolio and assignments such as group assignments, writings, and so on that are done in full online by adding additional features such as Teaching and Learning Activities and Assessment through information technology media. (E-Learning / Learning Management System). The method proposed in this research is the Peer Connection Queue (PCQ) method on mikrotik operating systems. PCQ method is a program to manage network traffic in Quality of Services (QoS). Bandwidth management methods. The hypothesis formulated is to create bandwidth management with PCQ so that bandwidth sharing is automatically and evenly distributed to multi clients. Therefore, in this research finally formulated into the goal of E-Learning effectiveness analysis using bandwidth management analysis method, which will be measured and analyzed in this research is throughput, delay, jitter, and packet loss. So that the final result of this research obtained the feasibility of the teaching and learning process that is carried out effectively.
Źródło:
International Journal of Electronics and Telecommunications; 2021, 67, 4; 595--601
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Light Weight Clustered Trust Sensing Mechanism for Internet of Things Network
Autorzy:
Rajendra Prasad, M.
Krishna Reddy, D.
Powiązania:
https://bibliotekanauki.pl/articles/2055236.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
internet of things
trust sensing
clustering
mobility
packet forwarding factor
malicious detection rate
packet delivery ratio
Opis:
Internet of Things (IoT) is the new research paradigm which has gained a great significance due to its widespread applicability in diverse fields. Due to the open nature of communication and control, the IoT network is more susceptible to several security threats. Hence the IoT network requires a trust aware mechanism which can identify and isolate the malicious nodes. Trust Sensing has been playing a significant role in dealing with security issue in IoT. A novel a Light Weight Clustered Trust Sensing (LWCTS) model is developed which ensures a secured and qualitative data transmission in the IoT network. Simulation experiments are conducted over the proposed model and the performance is compared with existing models. The obtained results prove the effectiveness when compared with existing approaches.
Źródło:
International Journal of Electronics and Telecommunications; 2022, 68, 1; 5--12
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Effect of Voice over IP Transmission Degradations on MAP-EM-GMM Speaker Verification Performance
Autorzy:
Maciejko, W.
Powiązania:
https://bibliotekanauki.pl/articles/177874.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
automatic speaker verification
packet loss
speech compression
voice over IP
Opis:
Despite the growing importance of packet switching systems, there is still a shortage of thorough analyses of VoIP transmission effect on speech and speaker recognition performance. Voice over IP transmission systems use packet switching. There is no guarantee of delivery. The main disadvantage of VoIP is a packet loss which has a major impact on the performance experienced by the users of the network. There are several techniques to mask the effects of a packet loss, referred to as packet loss concealment. In this study, the effect of voice transmission over IP on automatic speaker verification system performance was investigated. The analyzed system was based on MAP-EM-GMM modelling methods. Four various speech codecs of H.323 standard were investigated with special emphasis placed on the packet loss phenomenon and various packet loss concealment techniques.
Źródło:
Archives of Acoustics; 2015, 40, 3; 407-417
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Study on Packet Scheduling Algorithms for Healthcare Contents over Fifth Generation (5G) Mobile Cellular Network
Autorzy:
Ramli, Huda Adibah Mohd
Powiązania:
https://bibliotekanauki.pl/articles/1844466.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
packet scheduling
5G
flexible frame structure
transmission reliability
scalable TTI
Opis:
This paper models the downlink Fifth Generation (5G) network that supports a flexible frame structure and a shorter Round-Trip Time (RTT) for Hybrid Automatic Repeat Request (HARQ). Moreover, the design of the renowned Time Division Multiple Access (TDMA) packet scheduling algorithms is revised to allow these algorithms to support packet scheduling in the downlink 5G. Simulation results demonstrate that the Proportional Fair provides a comparable performance to the delay–aware Maximum-Largest Weighted Delay First for simultaneously providing the desired transmission reliability of the Guaranteed Bit Rate (GBR) and Non-Guaranteed Bit Rate (Non - GBR) healthcare contents whilst maximizing the downlink 5G performance.
Źródło:
International Journal of Electronics and Telecommunications; 2020, 66, 4; 729-735
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Wavelet Packet Transform based Speech Enhancement via Two-Dimensional SPP Estimator with Generalized Gamma Priors
Autorzy:
Sun, P.
Qin, J.
Powiązania:
https://bibliotekanauki.pl/articles/177782.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
speech enhancement
speech presence probability
wavelet packet transform
two-dimensional Teager energy operator
Opis:
Despite various speech enhancement techniques have been developed for different applications, existing methods are limited in noisy environments with high ambient noise levels. Speech presence probability (SPP) estimation is a speech enhancement technique to reduce speech distortions, especially in low signalto-noise ratios (SNRs) scenario. In this paper, we propose a new two-dimensional (2D) Teager-energyoperators (TEOs) improved SPP estimator for speech enhancement in time-frequency (T-F) domain. Wavelet packet transform (WPT) as a multiband decomposition technique is used to concentrate the energy distribution of speech components. A minimum mean-square error (MMSE) estimator is obtained based on the generalized gamma distribution speech model in WPT domain. In addition, the speech samples corrupted by environment and occupational noises (i.e., machine shop, factory and station) at different input SNRs are used to validate the proposed algorithm. Results suggest that the proposed method achieves a significant enhancement on perceptual quality, compared with four conventional speech enhancement algorithms (i.e., MMSE-84, MMSE-04, Wiener-96, and BTW).
Źródło:
Archives of Acoustics; 2016, 41, 3; 579-590
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Rattle Signal Denoising and Enhancing Method Based on Wavelet Packet Decomposition and Mathematical Morphology Filter for Vehicle
Autorzy:
Liang, Linyuan
Chen, Shuming
Li, Peiran
Powiązania:
https://bibliotekanauki.pl/articles/2141688.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
rattle signals
wavelet packet decomposition
mathematical morphology filter
critical frequency band
information entropy
Opis:
Buzz, squeak and rattle (BSR) noise has become apparent in vehicles due to the significant reductions in engine noise and road noise. The BSR often occurs in driving condition with many interference signals. Thus, the automatic BSR detection remains a challenge for vehicle engineers. In this paper, a rattle signal denoising and enhancing method is proposed to extract the rattle components from in-vehicle background noise. The proposed method combines the advantages of wavelet packet decomposition and mathematical morphology filter. The critical frequency band and the information entropy are introduced to improve the wavelet packet threshold denoising method. A rattle component enhancing method based on multi-scale compound morphological filter is proposed, and the kurtosis values are introduced to determine the best parameters of the filter. To examine the feasibility of the proposed algorithm, synthetic brake caliper rattle signals with various SNR ratios are prepared to verify the algorithm. In the validation analysis, the proposed method can well remove the disturbance background noise in the signal and extract the rattle components with well SNR ratios. It is believed that the algorithm discussed in this paper can be further applied to facilitate the detection of the vehicle rattle noise in industry.
Źródło:
Archives of Acoustics; 2022, 47, 1; 43-55
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Noise Detection for Biosignals Using an Orthogonal Wavelet Packet Tree Denoising Algorithm
Autorzy:
Schimmack, M.
Mercorelli, P.
Powiązania:
https://bibliotekanauki.pl/articles/226940.pdf
Data publikacji:
2016
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
noise detection
wavelet packet transform
wavelet analysis
Daubechies wavelet
linux-based embedded system
ARM processor platform
Opis:
This article deals with the noise detection of discrete biosignals using an orthogonal wavelet packet. In specific, it compares the usefulness of Daubechies wavelets with different vanishing moments for the denoising and compression of the digitalised biosignals in case of surface electromyography (sEMG) signals. The work is based upon the discrete wavelet transform (DWT) version of wavelet package transform (WPT). A noise reducing algorithm is proposed to detect unavoidable noise in the acquired data in a model independent way. The noise of a signal sequence will be defined by a seminorm. This method was developed for a possible observation during a fracture healing period. The proposed method is general for signal processing and its design was based upon the wavelet packet.
Źródło:
International Journal of Electronics and Telecommunications; 2016, 62, 1; 15-21
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
City Backbone Network Traffic Forecasting
Autorzy:
Serikov, Tansaule
Zhetpisbayeva, Ainur
Аkhmediyarova, Аinur
Mirzakulova, Sharafat
Aigerim, Kismanova
Tolegenova, Aray
Wójcik, Waldemar
Powiązania:
https://bibliotekanauki.pl/articles/1844529.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
time series
packet intensity
Dickey-Fuller test
Kwiatkowski-Phillips-Perron-Shin-Schmitt test
forecasting
integrated moving average autoregression model
Opis:
The work considers a one-dimensional time series protocol packet intensity, measured on the city backbone network. The intensity of the series is uneven. Scattering diagrams are constructed. The Dickie Fuller test and Kwiatkowski-Phillips Perron-Shin-Schmitt test were applied to determine the initial series to the class of stationary or non-stationary series. Both tests confirmed the involvement of the original series in the class of differential stationary. Based on the Dickie Fuller test and Private autocorrelation function graphs, the Integrated Moving Average Autoregression Model model is created. The results of forecasting network traffic showed the adequacy of the selected model.
Źródło:
International Journal of Electronics and Telecommunications; 2021, 67, 3; 319-324
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Speech emotion recognition using wavelet packet reconstruction with attention-based deep recurrent neutral networks
Autorzy:
Meng, Hao
Yan, Tianhao
Wei, Hongwei
Ji, Xun
Powiązania:
https://bibliotekanauki.pl/articles/2173587.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
speech emotion recognition
voice activity detection
wavelet packet reconstruction
feature extraction
LSTM networks
attention mechanism
rozpoznawanie emocji mowy
wykrywanie aktywności głosowej
rekonstrukcja pakietu falkowego
wyodrębnianie cech
mechanizm uwagi
sieć LSTM
Opis:
Speech emotion recognition (SER) is a complicated and challenging task in the human-computer interaction because it is difficult to find the best feature set to discriminate the emotional state entirely. We always used the FFT to handle the raw signal in the process of extracting the low-level description features, such as short-time energy, fundamental frequency, formant, MFCC (mel frequency cepstral coefficient) and so on. However, these features are built on the domain of frequency and ignore the information from temporal domain. In this paper, we propose a novel framework that utilizes multi-layers wavelet sequence set from wavelet packet reconstruction (WPR) and conventional feature set to constitute mixed feature set for achieving the emotional recognition with recurrent neural networks (RNN) based on the attention mechanism. In addition, the silent frames have a disadvantageous effect on SER, so we adopt voice activity detection of autocorrelation function to eliminate the emotional irrelevant frames. We show that the application of proposed algorithm significantly outperforms traditional features set in the prediction of spontaneous emotional states on the IEMOCAP corpus and EMODB database respectively, and we achieve better classification for both speaker-independent and speaker-dependent experiment. It is noteworthy that we acquire 62.52% and 77.57% accuracy results with speaker-independent (SI) performance, 66.90% and 82.26% accuracy results with speaker-dependent (SD) experiment in final.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 1; art. no. e136300
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Speech emotion recognition using wavelet packet reconstruction with attention-based deep recurrent neutral networks
Autorzy:
Meng, Hao
Yan, Tianhao
Wei, Hongwei
Ji, Xun
Powiązania:
https://bibliotekanauki.pl/articles/2090711.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
speech emotion recognition
voice activity detection
wavelet packet reconstruction
feature extraction
LSTM networks
attention mechanism
rozpoznawanie emocji mowy
wykrywanie aktywności głosowej
rekonstrukcja pakietu falkowego
wyodrębnianie cech
mechanizm uwagi
sieć LSTM
Opis:
Speech emotion recognition (SER) is a complicated and challenging task in the human-computer interaction because it is difficult to find the best feature set to discriminate the emotional state entirely. We always used the FFT to handle the raw signal in the process of extracting the low-level description features, such as short-time energy, fundamental frequency, formant, MFCC (mel frequency cepstral coefficient) and so on. However, these features are built on the domain of frequency and ignore the information from temporal domain. In this paper, we propose a novel framework that utilizes multi-layers wavelet sequence set from wavelet packet reconstruction (WPR) and conventional feature set to constitute mixed feature set for achieving the emotional recognition with recurrent neural networks (RNN) based on the attention mechanism. In addition, the silent frames have a disadvantageous effect on SER, so we adopt voice activity detection of autocorrelation function to eliminate the emotional irrelevant frames. We show that the application of proposed algorithm significantly outperforms traditional features set in the prediction of spontaneous emotional states on the IEMOCAP corpus and EMODB database respectively, and we achieve better classification for both speaker-independent and speaker-dependent experiment. It is noteworthy that we acquire 62.52% and 77.57% accuracy results with speaker-independent (SI) performance, 66.90% and 82.26% accuracy results with speaker-dependent (SD) experiment in final.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 1; e136300, 1--12
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-10 z 10

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