Analysis of Evolutionary Social Media Activities: Pre-Vaccine and Post-Vaccine Emergency Use

Dear Editor,In this letter,we analyze the public discourse sentiments over time and seek to understand the salient patterns around COVID-19 vaccines and vaccination from social media data.Globally,more than 373 million people have been diagnosed with COVID-19 and 5.66 million have died from this disease by 2022.It continues to have a negative impact on human daily life and the global economic development till now,due to the lack of effective treatment of COVID-19 induced issues and prevention of transmission methods.

LSTM Based Spectrum Prediction for Real-Time Spectrum Access for IoT Applications

In the Internet of Things(IoT)scenario,many devices will communi-cate in the presence of the cellular network;the chances of availability of spec-trum will be very scary given the presence of large numbers of mobile users and large amounts of applications.Spectrum prediction is very encouraging for high traffic next-generation wireless networks,where devices/machines which are part of the Cognitive Radio Network(CRN)can predict the spectrum state prior to transmission to save their limited energy by avoiding unnecessarily sen-sing radio spectrum.Long short-term memory(LSTM)is employed to simulta-neously predict the Radio Spectrum State(RSS)for two-time slots,thereby allowing the secondary node to use the prediction result to transmit its information to achieve lower waiting time hence,enhanced performance capacity.A frame-work of spectral transmission based on the LSTM prediction is formulated,named as positive prediction and sensing-based spectrum access.The proposed scheme provides an average maximum waiting time gain of 2.88 ms.The proposed scheme provides 0.096 bps more capacity than a conventional energy detector.

Multivariate Aggregated NOMA for Resource Aware Wireless Network Communication Security

NonorthogonalMultiple Access(NOMA)is incorporated into the wireless network systems to achieve better connectivity,spectral and energy effectiveness,higher data transfer rate,and also obtain the high quality of services(QoS).In order to improve throughput and minimum latency,aMultivariate Renkonen Regressive Weighted Preference Bootstrap Aggregation based Nonorthogonal Multiple Access(MRRWPBA-NOMA)technique is introduced for network communication.In the downlink transmission,each mobile device’s resources and their characteristics like energy,bandwidth,and trust are measured.Followed by,the Weighted Preference Bootstrap Aggregation is applied to recognize the resource-efficient mobile devices for aware data transmission by constructing the different weak hypotheses i.e.,Multivariate Renkonen Regression functions.Based on the classification,resource and trust-aware devices are selected for transmission.Simulation of the proposed MRRWPBA-NOMA technique and existing methods are carried out with different metrics such as data delivery ratio,throughput,latency,packet loss rate,and energy efficiency,signaling overhead.The simulation results assessment indicates that the proposed MRRWPBA-NOMA outperforms well than the conventional methods.

Stressed Coral Reef Identification Using Deep Learning CNN Techniques

Deep learning is a machine learning technique that allows the computer to process things that occur naturally to humans.Today,deep learning techniques are commonly used in computer vision to classify images and videos.As a result,for challenging computer vision problems,deep learning provides state of the art solutions to it.Coral reefs are an essential resource of the earth.A new study finds the planet has lost half of its coral reefs since 1950.It is necessary to restore and prevent damage to coral reefs as they play an important role in maintaining a balance in the marine ecosystem.This proposed work helps to prevent the corals from bleaching and restore them to a healthy condition by identifying the root cause of the threats.In the proposed work,using deep learning CNN techniques,the images are classified into Healthy and Stressed coral reefs.Stressed coral reefs are an intermediate state of coral reef between healthy and bleached coral reefs.The pre-trained models Resnet50 and Inception V3 are used in this study to classify the images.Also,a proposed CNN model is built and tested for the same.The results of Inception V3 and Resnet50 are improved to 70%and 55%by tuning the hypermeters such as dropouts and batch normalisation.Similarly,the proposed model is tuned as required and obtains a maximum of up to 90%accuracy.With large datasets,the optimum amount of neural networks and tuning it as required brings higher accuracy than other methods.

基于对比敏感度的DASH客户端码率选择算法研究

基于带宽估算的码率选择算法具有带宽利用率高的优点,但是同时也存在容易受网络波动影响造成计算出的目标码率出现瞬时峰值而造成带宽浪费的问题。针对于此,该文提出一种基于人眼对比敏感度特征的码率选择算法,在客户端利用人眼对比敏感度模型计算当前观看条件下人眼截止空间频率,选择服务器中和截止空间频率差的绝对值最小视频分片对应的码率作为目标码率。和基于带宽估算选择目标码率的方法进行对比实验,测试二者在不同视角内计算的目标码率,得到两者的码率计算结果阶梯图。实验结果表明,在视角为5o到15o情况下,所提方法较带宽估计方法在确保视频效果前提下能够有效节约带宽。

一种采用无源软开关吸收电路技术的新型高效DC/DC变换器

主要从4个方面叙述了采用无源软开关吸收电路技术70kW的DC/DC变换器,即(1)无源吸收电路的工作原理;(2)PWM控制方式的选择和比较;(3)大功率高频变压器的设计步骤;(4)一次侧整流电路二极管过冲电压限制以及吸收电阻的选型分析。最后给出了试验波形和效率曲线。

GA and PSO culled hybrid technique for economic dispatch problem with prohibited operating zones

This paper presents an efficient and reliable genetic algorithm (GA) based particle swarm optimization (PSO) tech- nique (hybrid GAPSO) for solving the economic dispatch (ED) problem in power systems. The non-linear characteristics of the generators, such as prohibited operating zones, ramp rate limits and non-smooth cost functions of the practical generator operation are considered. The proposed hybrid algorithm is demonstrated for three different systems and the performance is compared with the GA and PSO in terms of solution quality and computation efficiency. Comparison of results proved that the proposed algo- rithm can obtain higher quality solutions efficiently in ED problems. A comprehensive software package is developed using MATLAB.

Cognitive Radios： A Survey On Spectrum Sensing, Security and Spectrum Handoff

Pervasive wireless computing and communication have created an ever-increasing demand for more radio spectrum. Since, most of the spectrum is underutilized, it motivated the introduction of the concept of cognitive radios, a dynamic spectrum access enabling technology. The first stage of cognitive radio is to sense the environment and determine which parts of the spectrum are available. This is achieved through spectrum sensing. However, spectrum sensing poses the most fundamental challenge in cognitive radios. Moreover, cognitive radios suffer from many vulnerabilities and the security attacks can severely degrade the performance of cognitive radios. This paper surveys state-of-theart research on spectrum sensing and security threats in cognitive radios. Lastly, we also consider the analysis of issues related to spectrum handoffs in cognitive radios.

Advances in Digital Control for High-frequency Switched-mode Power Converters

Over the last decade,practical digital control of high-frequency switched-mode power converters has moved from proof-of-concept demonstrations to controller chips commercially available from multiple vendors,with applica-tions to point-of-load and isolated DC/DC converters,microprocessor power supplies,power-factor-correction rectifiers,and others.This paper summarizes some of the advances in the area,including approaches to realizations of high-per-formance,high-frequency digital pulse-width modulated(DPWM) controllers,related analysis,modeling and design techniques,as well as performance gains enabled by digital control such as dynamic response and efficiency improve-ments.Examples of experimentally demonstrated results are presented,together with pointers to areas of current and future research and development.

Analysis of EMD Algorithm for Identification and Extraction of An Acoustic Signal in Underwater Channel Against Wind Driven Ambient Noise

Sonar generated acoustic signals transmitted in underwater channel for distant communications are affected by numerous factors like ambient noise, making them nonlinear and non-stationary in nature. In recent years, the application of Empirical Mode Decomposition(EMD) technique to analyze nonlinear and non-stationary signals has gained much attention. It is an empirical approach to decompose a signal into a set of oscillatory modes known as intrinsic mode functions(IMFs). In general, Hilbert transform is used in EMD for the identification of oscillatory signals. In this paper a new EMD algorithm is proposed using FFT to identify and extract the acoustic signals available in the underwater channel that are corrupted due to various ambient noises over a range of 100 Hz to 10 kHz in a shallow water region. Data for analysis are collected at a depth of 5 m and 10 m offshore Chennai at the Bay of Bengal. The algorithm is validated for different sets of known and unknown reference signals. It is observed that the proposed EMD algorithm identifies and extracts the reference signals against various ambient noises. Significant SNR improvement is also achieved for underwater acoustic signals.

Feasibility analysis of WDM links for radar applications

Active phased array antennas enhances the performance of modern radars by using multiple low power transmit/receive modules in place of a high power transmitter in conventional radars. Fully distributed phased array radars demand the distribution of various signals in radio frequency(RF) and digital domain for real time operation. This is normally achieved through complex and bulky coaxial distribution networks. In this work, we intend to tap the inherent advantages of fiber links with wavelength division multiplexed(WDM) technology and a feasibility study to adapt these links for radar applications is carried out. This is done by analysing various parameters like amplitude, delay, frequency and phase variation response of various radar waveforms over WDM links. This also includes performance evaluation of non-linear frequency modulation(NLFM) signals, known for better signal to noise ratio(SNR) to specific side lobe levels. NLFM waveforms are further analysed using pulse compression(PC) technique. Link evaluation is also carried out using a standard simulation environment and is then experimentally verified with other waveforms like RF continuous wave(CW), pulsed RF and digital signals. Synchronization signals are generated from this variable duty cycle digital signals during real time radar operation. During evaluation of digital signals, variable transient effects for different duty cycles are observed from an amplifier configuration. A suppression method is proposed to eliminate this transient effects. Further, the link delay response is investigated using different lengths of fiber spools. It can be inferred from the experimental results that WDM links are capable of handling various signals significant to radar applications.

Human blood plasma-based electronic integrated circuit amplifier configuration

Dear Editor:There is accumulating evidence that human blood electronic circuit components and their application circuits become more and more important to cyborg implant/engineering,man-machine interface,human disease detection and healing,and artificial brain evolution[1-5].Here,we report the first development of human plasma-based amplifier circuit in the discrete as well as integrated circuit(IC)configuration mode.Electrolytes in the human blood contain an enormous number of charge carriers such as positive and negative molecule/atom ions,which are electri-

On the construction of cryptographically strong Boolean functions with desirable trade-off

This paper proposes a practical algorithm for systematically generating strong Boolean functions (f:GF(2)n→GF(2)) with cryptographic meaning. This algorithm takes bent function as input and directly outputs the resulted Boolean function in terms of truth table sequence. This algorithm was used to develop two classes of balanced Boolean functions, one of which has very good cryptographic properties: nl(f)=22k?1?2k+2k?2 (n=2k), with the sum-of-squares avalanche characteristic of f satisfying σf=24k+23k+2+23k+23k?2 and the absolute avalanche characteristic of ?f satisfying ?f=2k+1. This is the best result up to now compared to existing ones. Instead of bent sequences, starting from random Boolean functions was also tested in the algorithm. Experimental results showed that starting from bent sequences is highly superior to starting from random Boolean functions.

ESTIMATION OF 2-D DOA USING NON-CIRCULAR MUSIC METHOD FOR UNIFORM CIRCULAR AND RECTANGULAR ARRAYS

This paper extends the Non-Circular MUltiple SIgnal Classification(MUSIC)(NC-MUSIC) method for the common array geometries including Uniform Circular Arrays(UCAs) and Uniform Rectangular Arrays(URAs),which enables the algorithm to estimate 2-D Direction Of Arrival(DOA).A comparison between UCAs and URAs of NC-MUSIC is made in this paper.The simulations show that the NC-MUSIC method doubles the maximum estimation number of standard MUSIC.Using non-circular signals,the performance of URAs is improved remarkably while the improvement of UCAs is not so significantly.Moreover,the influence of arrays structures on the NC-MUSIC method is discussed.

Detection of Subsurface Cavities in a Power Plant Through Artificial Neural Network from Micro-Gravity Data

Subsurface cavities are very susceptible subsurface locations for down-lifting of a dam construction.In order to detect the low-density zones of a power plant a micro-gravity survey was conducted in a site considered for construction of a power plant site in Iran.First we gain the residual anomalies through bouger anomalies and then we design an Artificial Neural Network(ANN)which is trained by a set of training data.The ANN was tested for both synthetic and real data.For real data some suitable features are derivate from residual anomalies and applied to

Improved Eigenstructure-Based 2D DOA Estimation Approaches Based on Nystrom Approximation

In this paper,we propose improved approaches for two-dimensional(2 D) direction-of-arrival(DOA) estimation for a uniform rectangular array(URA).Unlike the conventional eigenstructure-based estimation approaches such as Multiple Signals Classification(MUSIC) and Estimation of Signal Parameters via Rotational Invariance Technique(ESPRIT),the proposed approaches estimate signal and noise subspaces with Nystr?m approximation,which only need to calculate two sub-matrices of the whole sample covariance matrix and avoid the need to directly calculate the eigenvalue decomposition(EVD) of the sample covariance matrix.Hence,the proposed approaches can improve the computational efficiency greatly for large-scale URAs.Numerical results verify the reliability and efficiency of the proposed approaches.

Enhanced removal of benzene in nonthermal plasma with ozonation, flow recycling, and flow recirculation

A double stage AC/DC sequential high voltage reactor has been developed to study the decomposition of benzene in the air stream at atmospheric pressure. The removal efficiency was measured as a function of ozonation, flow recycling, and flow recirculation. Ozonation in the inlet, and recycling of the exhaust stream increased the removal of benzene, also with increasing of specific input energy(J l^-1) the effect of inlet flow ozonation on benzene decomposition was enhanced. The highest removal efficiency was obtained up to >99% in recirculation six times,while CO2 selectivity reached 99.9% and energy efficiency was 0.59 g kWh^-1. O3 production/decomposition > production of OH radicals > electronic and ionic collisions were indicated as the main mechanisms influencing benzene abatement in this research.

RETINAL SPECTRAL IMAGING AND BLOOD FLOW MEASUREMENT

Measurement of both oxygen saturation and blood flow in the retinal vessels has proved to give important information about the eye health and the onset of eye pathologies such as diabetic retinopathy.In this study,we present the implementation,on a commercially available fundus camera,of a retinal imager and a retina blood flow velocimeter.The retinal imager uses division of aperture to acquire nine wavelength-dependent sub-images of the retina.Careful consideration is taken to improve image transfer by measuring the optical properties of the fundus camera and modeling the optical train in Zemax.This part of the setup is calibrated with optical phantoms of known optical properties that are also used to build a lookup table(LUT)linking phantom optical properties to measured reflectance.The retina blood flow velocimeter relies on tracking clusters of erythrocytes and uses a fast acquisition camera attached to a zoom lens,with a green illumination LED-engine.Calibration is provided using a calibrated quartz capillary tube and human blood at a known flow rate.Optical properties of liquid phantoms are retrieved from measured reflectance using the LUT,and blood flow measurements in the retina are presented.

Effective Size Reduction Technique for Microstrip Filters

In this paper an effective size reduction technique using fractal structure is suggested. The proposed technique has been applied on a band stop and a low pass filter separately. This technique provides 42% reduction of size for the band stop filter and about 26% for the low pass counterpart. Both the designed structures are fabricated and the measured results are compared with the simulated results. The proposed technique does not require any recalculation or optimization of dimensions of the filter, and is straightforward to implement. The band stop filter is designed for the center frequency of 3 GHz where as the cut-off frequency for low pass filter is 2.5 GHz. A good agreement between the simulated and measured results is observed. A comprehensible explanation of the proposed technique is also provided.

Ultra-Low Power Designing for CMOS Sequential Circuits

Power consumption is the bottleneck of system performance. Power reduction has become an important issue in digital circuit design, especially for high performance portable devices (such as cell phones, PDAs, etc.). Many power reduction techniques have also been proposed from the system level down to the circuit level. High-speed computation has thus become the expected norm from the average user, instead of being the province of the few with access to a powerful mainframe. Power must be added to the portable unit, even when power is available in non-portable applications, the issue of low-power design is becoming critical. Thus, it is evident that methodologies for the design of high-throughput, low-power digital systems are needed. Techniques for low-power operation are shown in this paper, which use the lowest possible supply voltage coupled with architectural, logic style, circuit, and technology optimizations. The threshold vol-tages of the MTCMOS devices for both low and high Vth are constructed as the low threshold Vth is approximately 150 - 200 mv whereas the high threshold Vth is managed by varying the thickness of the oxide Tox. Hence we are using different threshold voltages with minimum voltages and hence considered this project as ultra-low power designing.