Real-time audio/video transmission through Internet media is an important part of communication. Due to bandwidth limitations and a noisy environment, delivery of multimedia content to a remote location is not 100% guaranteed. These limitations are the basic cause of missing packets which affect the Quality of Service (QoS). A protocol for the recovery of lost packets is described in [Maxemchuk, Nicholas F., K. Padmanabhan, and S. Lo. “A cooperative packet recovery protocol for multicast video.” Network Protocols, 1997. Proc. of 1997 International Conference on. IEEE]. This protocol claims significant improvement in QoS. We formally specify the protocol in a network of timed automata. By model-checking (A mathematical technique), we find that packet recovery is not always there. In this article, We report such scenarios of malfunctioning in the protocol when the size of multimedia contents is known (e.g., live video/audio broadcasting) and middle-level servers have different rates of data sending and receiving. We formulate the effect of inter-packet delay and transmission speed difference on a buffer.
In the 5G and beyond networks, low-latency digital signatures are essential to ensure the security, integrity, and non-repudiation of massive data in communication processes. The binary finite field-based elliptic curve digital signature algorithm (ECDSA) is particularly suitable for achieving low-latency digital signatures due to its carry-free characteristics. This paper proposes a low-latency and universal architecture for point multiplication (PM) and double point multiplication (DPM) based on the differential addition chain (DAC) designed for signing and verification in ECDSA. By employing the DAC, the area-time product of DPM can be decreased, and throughput efficiency can be increased. Besides, the execution pattern of the proposed architecture is uniform to resist simple power analysis and high-order power analysis. Based on the data dependency, two Karatsuba–Ofman multipliers and four non-pipeline squarers are utilized in the architecture to achieve a compact timing schedule without idle cycles for multipliers during the computation process. Consequently, the calculation latency of DPM is minimized to five clock cycles in each loop. The proposed architecture is implemented on Xilinx Virtex-7, performing DPM in 3.584, 5.656, and <inline-formula> <tex-math notation="LaTeX">$7.453~\mu s$ </tex-math></inline-formula> with 8135, 13372, and 17898 slices over GF(2<sup>163</sup>), GF(2<sup>233</sup>), GF(2<sup>283</sup>), respectively. In the existing designs that are resistant to high-order analysis, our architecture demonstrates throughput efficiency improvements of 36.7% over GF(2<sup>233</sup>) and 9.8% over GF(2<sup>283</sup>), respectively.
Jamiu O. Oladigbolu, Asad Mujeeb, Yusuf A. Al-Turki
et al.
In Saudi Arabia, the energy sector is presently the most significant contributor to carbon emissions, followed by the transportation sector, which contributes about 26% of the gross greenhouse gas emissions. The adoption of electric vehicles (EVs) in the transportation sector worldwide is one way to bring about a global green solution that can support the decarbonization of the environment, which now constitutes a new electric power demand for the utility grid network. To preserve the environment, and reduce the pressure on the existing grid network, we propose the utilization of EV charging stations (EVCSs) in off-grid locations. It is essential to have an alternative stand-alone renewables-based electrification framework to secure the charging demand needed for the electric vehicles. The present study performs a techno-economic investigation of a novel off-grid scheme that combines renewable energy resources to provide clean electricity for EV charging stations. The optimized system for the EVCS is compared with the alternative option of grid extension using economic criteria evaluation metrics and distance limitations. The optimization and comparative analysis results reveal that the option of an optimum stand-alone hybrid charging station is an economical, sustainable, and eco-friendly alternative to the option of grid expansion.
Nanomachines are submicrometer-scale devices led by nanotechnology that can perform simple sensing, local actuation, limited data processing, storage, and communication tasks in the terahertz (THz) band, that is, from <inline-formula> <tex-math notation="LaTeX">$\mathrm {0.1~}$ </tex-math></inline-formula>- <inline-formula> <tex-math notation="LaTeX">$\mathrm {10~ \text {T} \text {Hz} }$ </tex-math></inline-formula>. Electromagnetic nanocommunication among nanomachines results in a nanonetwork which could breakthrough promising applications in multiple domains such as software-defined metamaterials, in-body communication, and on-chip communication. This study adopts a modulation scheme for nanomachine communication based on <italic>multilevel</italic> pulse position modulation (ML-PPM). The multilevel scheme uses several orthogonal codes and is combined with PPM to generate the final transmit signal consisting of several multilevels. In this paper, we propose a more advanced scheme called <italic>level trimming</italic> to further boost the data rates of the ML-PPM scheme. Employing level-trimming, we transmit a fewer number of levels than required in ML-PPM, which will result in an spectral efficiency gain at the nanoreceiver. The simulation results reveal that the link capacity of the proposed scheme can be increased more than twofold using the level-trimming approach while the error rate performance remains better than the conventional ML-PPM. For instance, ML-PPM with level trimming achieves a data rate of approximately 4.5 terabits per second (Tbps) when trimming the levels from seven to one compared to ML-PPM that achieves around <inline-formula> <tex-math notation="LaTeX">$\mathrm {1~Tbps}$ </tex-math></inline-formula> under the same network conditions. At the same time, a <inline-formula> <tex-math notation="LaTeX">$\mathrm {2~dB}$ </tex-math></inline-formula> gain in BER performance is achieved with level trimming. Moreover, the computational complexity of nanotransceivers is reduced with the transmission of fewer levels. Furthermore, although level-trimming causes artificial errors, it improves the decoding performance by reducing the number of levels. We believe that the potential impact of this study will open doors for further investigations on various possible modulation formats for THz nanocommunication.
Jinyin CHEN, Wenchang SHANGGUAN, Jingjing ZHANG
et al.
For the problem of poor performance of exciting membership inference attack (MIA) when facing the transfer learning model that is generalized, the MIA for the transfer learning model that is generalized was first systematically studied, the anomaly detection was designed to obtain vulnerable data samples, and MIA was carried out against individual samples.Finally, the proposed method was tested on four image data sets, which shows that the proposed MIA has great attack performance.For example, on the Flowers102 classifier migrated from VGG16 (pretraining with Caltech101), the proposed MIA achieves 83.15% precision, which reveals that in the environment of transfer learning, even without access to the teacher model, the MIA for the teacher model can be achieved by visiting the student model.
Shafiqur Rehman, N. Natrajan, Mohamed Mohandes
et al.
Hybrid power systems are technically suitable for providing continuous and quality power to remotely located dwellings and have the potential of reducing the greenhouse gases emissions. The present study aims at finding an optimal hybrid power system based on wind, solar, diesel, and battery backup, which can address the load requirements of a village (Muhavoor, India). The present study utilizes the HOMER software for sizing the major power components, performing economic analysis and estimating greenhouse gas emission. It uses the minimum cost of energy as the basis for optimum system selection. Local load, wind speed, and solar radiation data along with technical and financial input of wind turbines, solar photovoltaic panels, diesel generators, inverters, and fuel are considered in the simulation. Several options have been considered in the study including: diesel, PV/diesel/battery, wind/diesel, and PV/wind/diesel/battery hybrid power systems. Based on the simulation results and analysis, the PV/diesel/battery system with 53MW capacity of PV, 16.55MW diesel generator capacity, 3,520MWh of battery backup, and 15.5MW of converter is recommended as the best option for the concerned village. This system is capable of meeting the entire load of the village with annual energy yield of 92,549MWh with an excess energy of 7,262MWh. Of the total electricity produced, PV panels generate 92.71% with a renewable fraction of 89.2% at an energy cost of 0.117US$/kWh. The total cost of the proposed hybrid power system can be recovered in 11 or 8 years with positive cash flows at the end of year 12 or 9 based on sale of electricity alone or with additional income from fuel savings and greenhouse gases credit incentive.
Vegetation pattern is one of the most important self-organized patterns in ecological systems. The formation mechanism of vegetation patterns has been attributed to dynamic bifurcations, while from the external perspective, the regularity of patterns could also be influenced by some statistical indicators. Shannon entropy and contagion index are the most commonly used indicators of landscape diversity and connectivity in landscape ecology. These two indicators can explain the self-organization of vegetation patterns. In this research, vegetation patterns are neither randomly generated nor captured from vegetation map. Based on a discrete vegetation-sand model, formation process of vegetation patterns are simulated in different situations of bifurcations. Given different situations of bifurcations (Turing bifurcation, Neimark-Sacker bifurcation and Turing-Neimark-Sacker bifurcation), several formation processes are studied. Along the process, the corresponding Shannon entropy and contagion index of simulated vegetation patterns are calculated based on slightly modified calculation formulas. Comparing different variation curves of Shannon entropy and contagion index, we can see that variation trends of both Shannon entropy and contagion index are closely related to the formation stages of vegetation patterns. The different final values of Shannon entropy and contagion index in different patterns can be used to determine which bifurcation is in dominant when both bifurcations occur.
In electronic warfare, the conflict relationship between the radar and the jammer can be modeled using game theory. In this paper, the strategies design problem for the monostatic radar and the jammer is investigated within the framework of Stackelberg game and egalitarian game. The radar waveform and the jammer power spectrum density are regarded as their strategies respectively and mutual information criterion is used to formulate the utility function. In the Stackelberg game, Stackelberg Equilibrium (SE) strategies of the radar and the jammer are derived based on a two-stage optimization method. In the egalitarian game, the existence condition of Nash equilibrium (NE) is investigated and the corresponding NE strategies are also given. If the existence condition is not satisfied, it is pointed out that the SE strategies are still acceptable as safe strategies from the perspective of game theory. The simulation results are presented and the performances of the SE strategies are compared with other strategies.
Automated model generation (AMG) is an automated artificial neural network (ANN) modeling algorithm, which integrates all the subtasks (including adaptive sampling/data generation, model structure adaptation, training, and testing) in neural model development into one unified framework. In existing AMG, most of the time is spent on data sampling and model structure adaptation due to the iterative neural network training and the sequential computation mechanism. In this paper, we propose an advanced AMG algorithm using parallel computation and interpolation approaches to speed up the neural modeling of microwave devices. Efficient interpolation approaches are incorporated to avoid repetitive training of the intermediate neural networks during adaptive sampling process in AMG. Parallel computation formulation based on a multi-processor environment is proposed to further save time during interpolation calculation, data generation, and model structure adaptation process. Examples of automated modeling of two microwave filters are presented to show the advantage of this paper.
In order to effectively improve the resource utilization of information transmission network in reality,the spectrum allocation problem in flexible optical network in smart grid environment was analyzed,and a spectrum allocation method was proposed.Combining the advantages of genetic algorithm and ant colony algorithm,the genetic algorithm was used to generate the initial solution.Finally,the optimal solution of the spectrum allocation problem was obtained by the characteristics of positive feedback of ant colony algorithm and efficient convergence.The performance of the optimization algorithm mentioned was verified by software simulation.The proposed algorithm can optimize the use of idle spectrum resources to meet the needs of mass data transmission in distribution network,and improve the reliability of distribution network communication system,which is of great significance to the safe and reliable operation of smart grid.
By considering the exclusion characteristics of foreign objects in a new intake system with a bypass duct for turboprop engines, two kinds of common rigid foreign objects, the grains, and metal pieces, are modeled based on airworthiness standards and reference reports. On the assumption that only a perfect elastic collision occurs without any structural damage to the objects or intake walls, a numerical method based on single high-fidelity computational fluid dynamics (CFD) and dynamic unstructured mesh techniques to simulate the 6DOF motion and impacts of the rigid foreign objects is presented. A practical used intake system with a bypass duct is employed to validate the method. According to the tolerance size of the intake, two spherical grains with the radius of 0.037 m and 0.0555 m and a regular hexahedron aluminum metal piece with the dimension of 0.20 m×0.11 m×0.01 m are built to test the exclusion ability of the intake and analyze their effects on the intake performance. The simulation results indicate that, in the cases of a symmetrical flow field, geometry, and initial states, all the rigid foreign objects will move in the intake without lateral motions. The spherical grains without an initial angular velocity only translate in the intake, and the small one finally enters into the bypass duct after four impacts, while the larger one flies into the inner part of the engine after six impacts. The larger grain can lead to a more apparent loss on the intake performance due to the greater shielding effect on the flow field, and the maximum decrements of the total pressure recovery coefficient and mass flow can reach to 2% and 4.1%, respectively; the total pressure distortion rate increases 116%. A coupled motion of translation and rotation occurs for the regular hexahedron aluminum piece, and after four impacts on the intake, it finally excludes to the outer space of the nacelles from the bypass duct. Compared to the spherical grains, the aluminum piece has more significant actions on the intake performance. The maximum losses of the total pressure recovery coefficient and mass flow can be 2.3% and 1.54%, respectively, while the distortion rate increases 518%. Although the numerical method in this study is simple and ideal, it can help researchers to obtain quick and effective evaluation results in the initial design stage of the new intake system with a bypass duct for the turboprop engine to improve the design efficiency and level.
Андрей Сергеевич Рубель, Владимир Васильевич Лукин
Efficiency of filtering based on tetrolet transform for test image database with different properties distorted by additive white Gaussian noise with different intensity is investigated. As the performance criteria, both standard metrics, for instance, PSNR and visual quality metrics (PSNR-HVS-M, MSSIM, and FSIM) are used. Effect of test image features on optimal threshold is analyzed. A comparative analysis of the tetrolet transform-based filter with DCT-filter with respect toobject edge preservation and effective denoising is shown
Giovanny M. Tarazona B., Juan S. Chávez L., Roberto Ferro E.
Este artículo desarrolla y describe un modelo para un sistema recomendador de productos en empresas de alquiler de películas. Al aplicarlo sistemáticamente, caracteriza los clientes y permite conocer sus tendencias de manera oportuna, veraz y fiable. Para ello se utiliza la metodología de redes neuronales artificiales y la teoría de la resonancia adaptativa, ya que la flexibilidad implícita de adaptarse a las necesidades corporativas incrementa la eficiencia de las transacciones en el ámbito de las aplicaciones web. Se usa la base de datos de contenidos de alquiler electrónico de películas vía web The Netflix Prize. La validación y simulación del modelo se codifica en MatLab®.
With the ever evolving mobile communication technology, achieving a high quality seamless mobility
access across mobile networks is the present challenge to research and development engineers.
Existing algorithms are used to make handover while a mobile station is roaming between cells.
Such algorithms have some handover instability due to method of making handover decision.
This paper proposes an enhanced handover algorithm that substantially reduces the handover
redundancy in vertical and horizontal handovers. Also, it enables users to select the most
appropriate target network technology based on their preferences even in the worst case where
the mobile station roams between cell boundaries, and has high ability to have efficient
performance in the critical area full of interferences. The proposed algorithm uses
additional quality of service criteria, such as cost, delay, available bandwidth
and network condition with two handover thresholds to achieve a better seamless
handover process. After developing and testing this algorithm, the simulation results
show a major reduction in the redundant handover, so high accuracy of horizontal and
vertical handovers obtained. Moreover, the signal strength is kept at a level higher than
the threshold during the whole simulation period, while maintaining low delay and connection
cost compared to other two algorithms in both scenarios.