scholarly journals Statistical Time-Frequency Multiplexing of HD Video Traffic in DVB-T2

2009 ◽  
Vol 2009 ◽  
pp. 1-12 ◽  
Author(s):  
Mehdi Rezaei ◽  
Imed Bouazizi ◽  
Moncef Gabbouj
Keyword(s):  
High Performance ◽  
Transmission Scheme ◽  
High Definition ◽  
Time Frequency ◽  
Proposed Model ◽  
Frequency Domains ◽  
Video Broadcast ◽  
Statistical Time ◽  
Digital Video Broadcast

Digital video broadcast-terrestrial 2 (DVB-T2) is the successor of DVB-T standard that allows a two-dimensional multiplexing of broadcast services in time and frequency domains. It introduces an optional time-frequency slicing (TFS) transmission scheme to increase the flexibility of service multiplexing. Utilizing statistical multiplexing (StatMux) in conjunction with TFS is expected to provide a high performance for the broadcast system in terms of resource utilization and quality of service. In this paper, a model for high-definition video (HDV) traffic is proposed. Then, utilizing the proposed model, the performance of StatMux of HDV broadcast services over DVB-T2 is evaluated. Results of the study show that implementation of StatMux in conjunction with the newly available features in DVB-T2 provides a high performance for the broadcast system.

scholarly journals Dual Protectıon for Data usıng Steganographıc Technıques with Embedded Framework

2019 ◽  
Vol 8 (5S3) ◽  
pp. 155-159
Keyword(s):  
High Performance ◽  
Data Communication ◽  
Original Data ◽  
Cover Image ◽  
Original Text ◽  
Dual Protection ◽  
Proposed Model ◽  
Encryption And Decryption ◽  
Secured Data

As the world is getting digitalized, the rush for need of secured data communication is overtop. Provoked by the vulnerability of human visual system to understand the progressive changes in the scenes, a new steganography method is proposed. The paper represents a double protection methodology for secured transmission of data. The original data is hidden inside a cover image using LSB substitution algorithm. The image obtained is inserted inside a frame of the video producing a stego-video. Stego-video attained is less vulnerable to attacks. After decryption phase, the original text is obtained which is error-free and the output image obtained is similar as the cover image. The quality of stego-video is high and there is no need for additional bandwidth for transmission. The hardware implement is required in order to calculate the corresponding analytical results. The proposed algorithm is examined and realized for various encryption standards using Raspberry Pi3 embedded hardware. The results obtained focuses on the attributes of the proposed model. On comparing with other conventional algorithms, the proposed scheme exhibits high performance in both encryption and decryption process with increase in efficiency of secured data communication.

scholarly journals Discriminative sparse coding in the analysis of electrocardiogram during ventricular arrhythmias

2021 ◽  
Author(s):  
Iman Kalaji
Keyword(s):  
Ventricular Fibrillation ◽  
Sparse Coding ◽  
Ventricular Arrhythmias ◽  
Treatment Options ◽  
Survival Rates ◽  
Learning Approach ◽  
Time Frequency ◽  
Frequency Domains ◽  
Optimized Treatment

Abnormalities in the rhythmic electromechanical contractions of the heart results in cardiac arrhythmias. When these abnormalities rise from the ventricles of the heart, they are classified as ventricular arrhythmias. The two major types of ventricular arrhythmias are ventricular tachycardia (VT) and ventricular fibrillation (VF). Ventricular fibrillation is the most dangerous among the two arrhythmias, that usually leads to sudden cardiac death if not treated immediately. Annually about 40,000 sudden cardiac deaths are reported in Canada. Due to high mortality rate and serious impact on quality of life, researchers have been focusing on characterizing ventricular arrhythmias that may lead to delivering optimized treatment options in improving the survival rates. In this thesis two major types of ventricular arrhythmias were analyzed and quantified by performing discriminative sparse coding analysis called label consistent K-SVD using time frequency dictionaries that are well localized in time and frequency domains. The analyzed signals were 670 ECG ventricular arrhythmia segments from 33 patients extracted from the Malignant Ventricular Ectopy and Creighton University Tachy-Arrhythmia databases. Using the LCKSVD dictionary learning approach, an overall maximum classification accuracy of 73.3% was achieved with a hybrid optimized wavelet dictionary. Based on the comparative analysis, the trained (learned) dictionaries yielded better performance than the untrained dictionaries. The results indicate that discriminative sparse coding approach has greater potential in extracting signal adaptive and morphologically discriminative time-frequency structures in studying ventricular arrhythmias.

scholarly journals Discriminative sparse coding in the analysis of electrocardiogram during ventricular arrhythmias

2021 ◽  
Author(s):  
Iman Kalaji
Keyword(s):  
Ventricular Fibrillation ◽  
Sparse Coding ◽  
Ventricular Arrhythmias ◽  
Treatment Options ◽  
Survival Rates ◽  
Learning Approach ◽  
Time Frequency ◽  
Frequency Domains ◽  
Optimized Treatment

Abnormalities in the rhythmic electromechanical contractions of the heart results in cardiac arrhythmias. When these abnormalities rise from the ventricles of the heart, they are classified as ventricular arrhythmias. The two major types of ventricular arrhythmias are ventricular tachycardia (VT) and ventricular fibrillation (VF). Ventricular fibrillation is the most dangerous among the two arrhythmias, that usually leads to sudden cardiac death if not treated immediately. Annually about 40,000 sudden cardiac deaths are reported in Canada. Due to high mortality rate and serious impact on quality of life, researchers have been focusing on characterizing ventricular arrhythmias that may lead to delivering optimized treatment options in improving the survival rates. In this thesis two major types of ventricular arrhythmias were analyzed and quantified by performing discriminative sparse coding analysis called label consistent K-SVD using time frequency dictionaries that are well localized in time and frequency domains. The analyzed signals were 670 ECG ventricular arrhythmia segments from 33 patients extracted from the Malignant Ventricular Ectopy and Creighton University Tachy-Arrhythmia databases. Using the LCKSVD dictionary learning approach, an overall maximum classification accuracy of 73.3% was achieved with a hybrid optimized wavelet dictionary. Based on the comparative analysis, the trained (learned) dictionaries yielded better performance than the untrained dictionaries. The results indicate that discriminative sparse coding approach has greater potential in extracting signal adaptive and morphologically discriminative time-frequency structures in studying ventricular arrhythmias.

Evaluation of potential auras in generalized epilepsy from EEG signals using deep convolutional neural networks and time-frequency representation

2020 ◽  
Vol 65 (4) ◽  
pp. 379-391 ◽  
Author(s):  
Hasan Polat ◽  
Mehmet Ufuk Aluçlu ◽  
Mehmet Siraç Özerdem
Keyword(s):  
Eeg Signals ◽  
Deep Convolutional Neural Networks ◽  
One Dimensional ◽  
Time Frequency ◽  
Specificity And Sensitivity ◽  
Frequency Representation ◽  
Proposed Model ◽  
Generalized Epilepsy ◽  
Short Time

AbstractThe general uncertainty of epilepsy and its unpredictable seizures often affect badly the quality of life of people exposed to this disease. There are patients who can be considered fortunate in terms of prediction of any seizures. These are patients with epileptic auras. In this study, it was aimed to evaluate pre-seizure warning symptoms of the electroencephalography (EEG) signals by a convolutional neural network (CNN) inspired by the epileptic auras defined in the medical field. In this context, one-dimensional EEG signals were transformed into a spectrogram display form in the frequency-time domain by applying a short-time Fourier transform (STFT). Systemic changes in pre-epileptic seizure have been described by applying the CNN approach to the EEG signals represented in the image form, and the subjective EEG-Aura process has been tried to be determined for each patient. Considering all patients included in the evaluation, it was determined that the 1-min interval covering the time from the second minute to the third minute before the seizure had the highest mean and the lowest variance to determine the systematic changes before the seizure. Thus, the highest performing process is described as EEG-Aura. The average success for the EEG-Aura process was 90.38 ± 6.28%, 89.78 ± 8.34% and 90.47 ± 5.95% for accuracy, specificity and sensitivity, respectively. Through the proposed model, epilepsy patients who do not respond to medical treatment methods are expected to maintain their lives in a more comfortable and integrated way.

scholarly journals A flash-based thermal simulation of scanning paths in LPBF additive manufacturing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kamel Ettaieb ◽  
Sylvain Lavernhe ◽  
Christophe Tournier
Keyword(s):  
High Performance ◽  
Laser Scanning ◽  
Thermal Field ◽  
Computational Cost ◽  
Three Dimensional ◽  
Three Dimensional Model ◽  
Content Type ◽  
Proposed Model ◽  
Scanning Path

Purpose This paper aims to propose an analytical thermal three-dimensional model that allows an efficient evaluation of the thermal effect of the laser-scanning path. During manufacturing by laser powder bed fusion (LPBF), the laser-scanning path influences the thermo-mechanical behavior of parts. Therefore, it is necessary to validate the path generation considering the thermal behavior induced by this process to improve the quality of parts. Design/methodology/approach The proposed model, based on the effect of successive thermal flashes along the scanning path, is calibrated and validated by comparison with thermal results obtained by FEM software and experimental measurements. A numerical investigation is performed to compare different scanning path strategies on the Ti6Al4V material with different stimulation parameters. Findings The simulation results confirm the effectiveness of the approach to simulate the thermal field to validate the scanning strategy. It suggests a change in the scale of simulation thanks to high-performance computing resources. Originality/value The flash-based approach is designed to ensure the quality of the simulated thermal field while minimizing the computational cost.

Interference Alignment-Based Resource Sharing for Device-to-Device Communication Underlaying Cellular Networks

2013 ◽  
Vol 411-414 ◽  
pp. 832-839
Author(s):  
Yu Yang ◽  
Zhang Xiao ◽  
Wang Shuai ◽  
Meng Rui ◽  
Chao Wei Wang
Keyword(s):  
Cellular Networks ◽  
Resource Sharing ◽  
Radio Resource Management ◽  
Interference Alignment ◽  
D2d Communication ◽  
Shared Resources ◽  
Time Frequency ◽  
Frequency Domains ◽  
Device To Device

In this paper, we investigate Device-to-Device (D2D) communication underlaying cellular networks to provide spectrally efficient support of local services. Since in underlay mode, D2D communications share resources in the time and frequency domains with cellular system, it will introduce potentially severe interference to the cellular users and accordingly presents a challenge in radio resource management. In order to avoid generating interference to the high-priority users (cellular users) operating on the same time-frequency resources and to optimize the throughput over the shared resources under the transmit power and the quality of service (QoS) constraints, we propose an interference alignment-based resource sharing scheme for D2D communication underlaying cellular networks. The simulation results demonstrate that by using the proposed scheme, D2D communication can effectively improve the total throughput without generating harmful interference to cellular networks.

scholarly journals Early Detection and Classification of Tomato Leaf Disease Using High-Performance Deep Neural Network

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7987
Author(s):  
Naresh K. Trivedi ◽  
Vinay Gautam ◽  
Abhineet Anand ◽  
Hani Moaiteq Aljahdali ◽  
Santos Gracia Villar ◽  
...  
Keyword(s):  
Neural Network ◽  
Crop Yield ◽  
High Performance ◽  
Early Stage ◽  
Tomato Plants ◽  
Leaf Disease ◽  
Proposed Model ◽  
Tomato Diseases

Tomato is one of the most essential and consumable crops in the world. Tomatoes differ in quantity depending on how they are fertilized. Leaf disease is the primary factor impacting the amount and quality of crop yield. As a result, it is critical to diagnose and classify these disorders appropriately. Different kinds of diseases influence the production of tomatoes. Earlier identification of these diseases would reduce the disease’s effect on tomato plants and enhance good crop yield. Different innovative ways of identifying and classifying certain diseases have been used extensively. The motive of work is to support farmers in identifying early-stage diseases accurately and informing them about these diseases. The Convolutional Neural Network (CNN) is used to effectively define and classify tomato diseases. Google Colab is used to conduct the complete experiment with a dataset containing 3000 images of tomato leaves affected by nine different diseases and a healthy leaf. The complete process is described: Firstly, the input images are preprocessed, and the targeted area of images are segmented from the original images. Secondly, the images are further processed with varying hyper-parameters of the CNN model. Finally, CNN extracts other characteristics from pictures like colors, texture, and edges, etc. The findings demonstrate that the proposed model predictions are 98.49% accurate.

Real-Time Full Motion Stereo Microscopy Over Internet

1999 ◽  
Vol 5 (S2) ◽  
pp. 368-369
Author(s):  
Gary N. Case ◽  
Mladen A. Vouk ◽  
John M. Mackenzie
Keyword(s):  
Quality Of Service ◽  
Real World ◽  
High Performance ◽  
Video Transmission ◽  
Three Dimensional ◽  
High Definition ◽  
The Real ◽  
Remote Imaging ◽  
Full Screen

One of the problems with remote imaging which purports to represent the real world (Tele-presence) is that the images are two-dimensional and the “real” world is three dimensional. When viewing many objects, the lack of depth perceptiorican be a serious deficiency. For example, one would want a micro-surgeon to have a good idea how deep to cut into tissue during a tele-presence operation. There is a wealth of three dimensional information in light, SEM, AFM, confocal, and computer reconstructed or simulated objects. To transfer that information faithfully over the networks using broadcast quality high definition video transmission technologies such as MPEG2 may require as much as 20 Mbps per channel. Furthermore, stereo imaging is particularly sensitive to any phase delays and jitter between the two eye channels. Control of these parameters requires advance quality of service features that current internet does not provide, but that may be available on high-performance intranets. All this may present a problem for routine use of the stereo facility .The next generation of Internet, however, will be able to routinely provision much higher bandwidth and other quality of service, in general through protocols that will allow for not only full screen full resolution television but also the use of two channels (left and right) that can stay in fairly close synchrony.

scholarly journals A novel performance evaluation technique based on integrated weighting approach: A case study in the field of sport management

2021 ◽  
Vol 10 (4) ◽  
pp. 511-524
Author(s):  
Ömer Faruk Görçün ◽  
Hande Küçükönder
Keyword(s):  
Sensitivity Analysis ◽  
High Performance ◽  
Sport Management ◽  
Aggregation Operator ◽  
Soccer Players ◽  
Key Factors ◽  
Proposed Model ◽  
Criteria Weights ◽  
Decision Alternatives

It is a fact accepted by everybody that football is the most popular sport around the world. The result of a derby match may be very important for millions of people. Even the time seems to stop on a match day for so many people. Show and entertainment are the most important aspects of football. If soccer players have a high performance, a match may provide pleasure and excitement to audiences. Briefly, the performance and quality of soccer players are the key factors, which draw audiences. Goalkeepers are also one of the important components of football like other players playing different positions such as strikers, mid-fielders, and defenders. Moreover, a goalkeeper can affect the result of a match positively or negatively. Therefore, with the help of a mathematical approach as the methodological framework, it can be seen that the examination of the performance of goalkeepers can be beneficial for decision-makers performing in the fields of sport and the future studies. The current paper proposes an improved integrated multi-criteria decision-making approach to evaluate the selection of goalkeepers; and this model can be applied for goalkeeper’s performance analysis. The proposed model combines the weights of criteria calculated with the help of both the CRITIC and the PSI techniques by applying the weight aggregation operator. It also ranks the decision alternatives by implementing the WASPAS technique based on the final criteria weights obtained by using the weight aggregation operator. In addition, a comprehensive sensitivity analysis consisting of three stages was performed to verify the validation of the suggested hybrid model. It has been observed that A11 has remained the best option for all scenarios. As a result, the results of the sensitivity analysis prove that the proposed hybrid MCDM technique is a very useful, strong and applicable approach. Also, the results obtained by applying the proposed model are accurate, realistic, and reasonable according to the results of the validation test.

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