A novel handover scheme using torch nodes and adaptive measurement aggregation mechanism to improve QoS in high-speed railway communication

Technological advancement in the field of trans- portation and communication has been happening at a faster pace in the past few decades. As the demand for high-speed transportation increases, the need for an improved seamless communication system to handle higher data traffic in a highly mobile environment becomes imperative. This paper proposes a novel scheme to enhance the quality of service in high-speed railway （HSR） communication environment using the concept of torch nodes （TNs） and adaptive measurement aggregation （AMA）. The system was modeled using an object-oriented discrete event sim- ulator, and the performance was analyzed against the existing single-antenna scheme. The simulation results show that the proposed scheme with its minimal imple- mentation overhead can efficiently perform seamless han- dover with reduced handover failure and communication interruption probability.

Robust Deep Learning Model for Black Fungus Detection Based on Gabor Filter and Transfer Learning

Black fungus is a rare and dangerous mycology that usually affects the brain and lungs and could be life-threatening in diabetic cases.Recently,some COVID-19 survivors,especially those with co-morbid diseases,have been susceptible to black fungus.Therefore,recovered COVID-19 patients should seek medical support when they notice mucormycosis symptoms.This paper proposes a novel ensemble deep-learning model that includes three pre-trained models:reset(50),VGG(19),and Inception.Our approach is medically intuitive and efficient compared to the traditional deep learning models.An image dataset was aggregated from various resources and divided into two classes:a black fungus class and a skin infection class.To the best of our knowledge,our study is the first that is concerned with building black fungus detection models based on deep learning algorithms.The proposed approach can significantly improve the performance of the classification task and increase the generalization ability of such a binary classification task.According to the reported results,it has empirically achieved a sensitivity value of 0.9907,a specificity value of 0.9938,a precision value of 0.9938,and a negative predictive value of 0.9907.

Optimization Techniques in University Timetabling Problem:Constraints,Methodologies,Benchmarks,and Open Issues

University timetabling problems are a yearly challenging task and are faced repeatedly each semester.The problems are considered nonpolynomial time(NP)and combinatorial optimization problems(COP),which means that they can be solved through optimization algorithms to produce the aspired optimal timetable.Several techniques have been used to solve university timetabling problems,and most of them use optimization techniques.This paper provides a comprehensive review of the most recent studies dealing with concepts,methodologies,optimization,benchmarks,and open issues of university timetabling problems.The comprehensive review starts by presenting the essence of university timetabling as NP-COP,defining and clarifying the two formed classes of university timetabling:University Course Timetabling and University Examination Timetabling,illustrating the adopted algorithms for solving such a problem,elaborating the university timetabling constraints to be considered achieving the optimal timetable,and explaining how to analyze and measure the performance of the optimization algorithms by demonstrating the commonly used benchmark datasets for the evaluation.It is noted that meta-heuristic methodologies are widely used in the literature.Additionally,recently,multi-objective optimization has been increasingly used in solving such a problem that can identify robust university timetabling solutions.Finally,trends and future directions in university timetabling problems are provided.This paper provides good information for students,researchers,and specialists interested in this area of research.The challenges and possibilities for future research prospects are also explored.

CFOA Based Low Pass and High Pass Ladder Filter—A New Configuration

A new technique using signal flow graph for conversion of ladder based filter into CFOA based filter has been proposed. The proposed technique converts the existing LC ladder based filter into CFOA in low pass and high pass configuration. The design of low pass filter and high pass filter has been realized using the proposed technique. The proposed configuration is implemented using CFOA as an active device and all the capacitors are grounded. Simulation has been carried out using simulation software I-cap. The simulation results have been demonstrated and discussed.

A Configuration for Realizing Voltage Controlled Floating Inductance and Its Application

A configuration using current feedback amplifiers AD844 and multiplier AD534 has been presented, which is capable of realizing Voltage Controlled Floating Inductance (proportional and in-verse proportional). The application of band pass filter in Figure 4(a), notch filter in Figure 5(a) and Hartley oscillator in Figure 6(a) and simulation result in Figures 4(b)-(d), Figures 5(b)-(d), Figures 6(b)-(d) shows the workability of proposed configuration.

Deep insights into the advancements and applications of perovskite based photovoltaic cells

The organometal halide perovskite materials have a blend of surprising optoelectronic properties, for example high value of absorption coefficient and abrupt optical retention edge, lifetime, long charge carrier diffusion length and many more. Brought in conjunction with the capacity for manufacturing at low temperature, likewise from the solution, devices based on perovskite, particularly solar cells have been contemplated seriously with striking advancements in performance, in the course of recent years. The amalgamation of minimal effort, high efficiency and extra applications gives incredible potential to commercialization of these cells. The applications and performance of perovskite cells frequently relate with the structures of the device. Numerous creative structures of the devices were produced, targeting for vast scale manufacture, diminishing creation cost, upgrading the PCE and subsequently expanding the prospective for future applications. This paper outlines the various advanced structures of PSC, challenges confronted by these PSCs and their future perspectives. The commercial applications of PSC are additionally talked about in this paper.

An Analysis of Cybersecurity Attacks against Internet of Things and Security Solutions

Internet of Things (IoT) has become a prevalent topic in the world of technology. It helps billion of devices to connect to the internet so that they can exchange data with each other. Nowadays, the IoT can be applied in anything, from cellphones, coffee makers, cars, body sensors to smart surveillance, water distribution, energy management system, and environmental monitoring. However, the rapid growth of IoT has brought new and critical threats to the security and privacy of the users. Due to the millions of insecure IoT devices, an adversary can easily break into an application to make it unstable and steal sensitive user information and data. This paper provides an overview of different kinds of cybersecurity attacks against IoT devices as well as an analysis of IoT architecture. It then discusses the security solutions we can take to protect IoT devices against different kinds of security attacks. The main goal of this research is to enhance the development of IoT research by highlighting the different kinds of security challenges that IoT is facing nowadays, and the existing security solutions we can implement to make IoT devices more secure. In this study, we analyze the security solutions of IoT in three forms: secure authentication, secure communications, and application security to find suitable security solutions for protecting IoT devices.

Wideband Cognitive Radio Networks Based Compressed Spectrum Sensing: A Survey

Spectrum sensing is a core function at cognitive radio systems to have spectrum awareness. This could be achieved by collecting samples from the frequency band under observation to make a conclusion whether the band is occupied, or it is a spectrum hole. The task of sensing is becoming more challenging especially at wideband spectrum scenario. The difficulty is due to conventional sampling rate theory which makes it infeasible to sample such very wide range of frequencies and the technical requirements are very costly. Recently, compressive sensing introduced itself as a pioneer solution that relaxed the wideband sampling rate requirements. It showed the ability to sample a signal below the Nyquist sampling rate and reconstructed it using very few measurements. In this paper, we discuss the approaches used for solving compressed spectrum sensing problem for wideband cognitive radio networks and how the problem is formulated and rendered to improve the detection performance.

Process Tolerant and Power Efficient SRAM Cell for Internet of Things Applications

The use of Internet of Things(IoT)applications become dominant in many systems.Its on-chip data processing and computations are also increasing consistently.The battery enabled and low leakage memory system at subthreshold regime is a critical requirement for these IoT applications.The cache memory designed on Static Random-Access Memory(SRAM)cell with features such as low power,high speed,and process tolerance are highly important for the IoT memory system.Therefore,a process tolerant SRAM cell with low power,improved delay and better stability is presented in this research paper.The proposed cell comprises 11 transistors designed with symmetric approach for write operations and single ended circuit for read operations that exhibits an average dynamic power saving of 43.55%and 47.75%for write and 35.59%and 36.56%for read operations compared to 6 T and 8 T SRAM cells.The cell shows an improved write delay of 26.46%and 37.16%over 6 T and 8T and read delay is lowered by 50.64%and 72.90%against 6 T and 10 T cells.The symmetric design used in core latch to improve the write noise margin(WNM)by 17.78%and 6.67%whereas the single ended separate read circuit improves the Read Static Noise Margin(RSNM)by 1.88x and 0.33x compared to 6 T and 8T cells.The read power delay product and write power delay product are lower by 1.94x,1.39x and 0.17x,2.02x than 6 T and 8 T cells respectively.The lower variability from 5000 samples validates the robustness of the proposed cell.The simulations are carried out in Cadence virtuoso simulator tool with Generic Process Design Kit(GPDK)45 nm technology file in this work.

Design and validation of a handheld capnography device for cardiopulmonary assessment based on the Arduino platform

The design of a handheld capnography device is in great demand because of its effective and practical uses in all cardiac arrest resuscitations,according to the recommendation of the American Heart Association.Herein,a handheld capnography device that can be used in clinical settings and the home environment is reported.The proposed device was developed by using an infrared CO_(2)sensor,Arduino Mega2560,and a high-resolution display(2.8").Furthermore,two rechargeable batteries(7.6 V,0.99 A)and a secure digital card with a capacity of 16 GB were incorporated to increase the portability and usability of the device.Algorithms were implemented to measure standard features,namely,inspired CO_(2)(ICO_(2)),end-tidal CO_(2)(EtCO_(2)),and re-spiratory rate(RR).The features of 15 healthy subjects were recorded by using the developed prototype and the standard capnography device(Capnostream^(TM)20 Model CS08798).Validation was performed with Bland-Altman plots.Findings revealed that mean differences±standard deviations for the set limits of ICO_(2),EtCO_(2)and RR were 0.29±1.30 millimeters of mercury(mmHg),0.15±1.77 mmHg and 0.40±0.97 breaths per minute(bpm),respectively.Most of the differences among device measurements across all features fell within the 95%limits of agreement.Thus,the developed device may help manage respiratory distress conditions in and outside of a hospital setting.

Performance of WSNs under the Effect of Collisions and Interference

This paper proposes a methodology for calculating the energy consumed by a Wireless Sensor Network as well as its throughput under the effect of a jamming node modelling interference to account for collisions and retransmissions. Accordingly, the proposed methodology takes into consideration retransmissions and data dropped due to interference and collisions simultaneously. Simulations are conducted using OPNET to model various scenarios utilizing off-the-shelf wireless communication standards, namely ZigBee, Wi-Fi and Low Power Wi-Fi. A figure of merit is developed to offer more representative results for applications with different requirements. In achieving different requirements for a given application, there is a clear trade-off between energy consumption and throughput.

Performance Issues and Behavioral Analysis of Routing Protocols in MANETs

Mobile ad hoc network (MANET) is an autonomous system of mobile nodes connected by wireless links. Infrastructure-less environment and frequently changing topology due to mobility of nodes makes routing a difficult task. There is no centralized control such as base station and can be set up according to demand wherever required. Effective routing protocol is required for finding the optimum path as per the application requirement. In this paper, analysis has been carried out about various basic routing protocols techniques, issues related to them especially in MANETs routing and performance comparison of different proposed approaches in terms of different network performance parameters.

CFOA Based Band Pass and Band Stop Ladder Filter—A New Configuration

A new technique for the conversion of ladder based filter into CFOA based filter has been proposed. The technique uses signal flow graph and converts the existing LC ladder based filter into band pass & band stop configurations. The design of band pass and band stop filter has been realized using the proposed technique. The proposed configuration is implemented using CFOA as an active device and all the capacitors are grounded. CFOA based circuits have greater linearity, high dynamic rate, high slew rate and high signal bandwidth. Simulation has been carried out using simulation software P Spice (v10.1). The simulation results have been demonstrated and discussed.

4-Port Octagonal Shaped MIMO Antenna with Low Mutual Coupling for UWB Applications

A4-port multiple-input multiple-output(MIMO)antenna exhibiting lowmutual coupling andUWBperformance is developed.The octagonal-shaped four-antenna elements are connected with a 50microstrip feed line that is arranged rotationally to achieve the orthogonal polarization for improving the MIMO system performance.The antenna has a wideband impedance bandwidth of 7.5GHz with S11<−10 dB from(103.44%)3.5–11GHz and inter-element isolation higher than 20 dB.Antenna validation is carried out by verifying the simulated and measured results after fabricating the antenna.The results in the form of omnidirectional radiation patterns,peak gain(≥4 dBi),and Envelope Correlation Coefficient(ECC)(≤0.01)are extracted to validate the suggested antenna performance.Aswell,time-domain analysis was investigated to demonstrate the operation of the suggested antenna in wideband applications.Finally,the simulated and experimental outcomes have almost similar tendenciesmaking the antenna suitable for its use in UWBMIMOapplications.

2 kHz High Power Smart Transducer for Acoustic Sub-bottom Profiling Applications

在这研究， 2 kHz Tonpilz 投影机用 Terfenol-D 被设计并且在 ATILA 当模特儿。为为研究建模的目的，一个放射的头团更好展出，这被决定了在 136 公里直径播送当前的反应(TCR ) ，在回声发生在 2.4 kHz 和 118 dB re 的山峰价值的地方在 1 m 的 1 Pa/A 发生在 12 kHz。另外，在从头团的中心的 46 公里距离的门栓在 2.4 kHz，和 115.3 dB re 的山峰价值提供回声在 1m 的 1 Pa/A 发生在 11.5 kHz。这个优化图案与 3 公里厚度的聚氨酯被制作并且塑造。原型在海洋技术(NIOT ) 的国家研究所的声学的测试设备(ATF ) 被测试为它的在水下表演。基于结果，基本回声决心是 2.18 kHz 和 182 dB re 的 TCR 的山峰价值在 1m 的 1 Pa/A 发生在 14 kHz。RS 的最大的价值被发现是在在 2.1 kHz 的频率的 1m 的 190 dB re 1V/Pa。

Novel Optimized Cross-Layer Design with Maximum Weighted Capacity Based Resource Allocation for AMC/HARQ Wireless Networks

To provide quality-of service (QoS) guarantees for heterogeneous applications, most recent wireless communications technologies and standards combine the error-correcting capability of hybrid automatic repeat request (HARQ) schemes at the data link layer (DLL) with the adaptation ability of the adaptive modulation and coding (AMC) modes at the physical layer (PHY) layer. This paper aims to investigate the aggregated system capacity as well as the breakdown of this capacity for different ACM modes in each HARQ scheme. This investigation was done by using maximum weighted capacity (MWC) resource allocation at the PHY layer in conjunction with a novel packet error rate (PER)-based scheduling at the medium access control (MAC) layer. As a result, the dominant AMC mode corresponding to channel SNR was available.

SCHS: Smart Cluster Head Selection Scheme for Clustering Algorithms in Wireless Sensor Networks

Wireless sensor networks are energy constraint networks. Energy efficiency, to prolong the network for a longer time is critical issue for wireless sensor network protocols. Clustering protocols are energy efficient approaches to extend the lifetime of network. Intra-cluster communication is the main driving factor for energy efficiency of clustering protocols. Intra-cluster energy consumption depends upon the position of cluster head in the cluster. Wrongly positioned clusters head make cluster more energy consuming. In this paper, a simple and efficient cluster head selection scheme is proposed, named Smart Cluster Head Selection (SCHS). It can be implemented with any distributed clustering approach. In SCHS, the area is divided into two parts: border area and inner area. Only inner area nodes are eligible for cluster head role. SCHS reduces the intra-cluster communication distance hence improves the energy efficiency of cluster. The simulation results show that SCHS has significant improvement over LEACH in terms of lifetime of network and data units gathered at base station.

Stator Fault Diagnosis of Induction Motor Based on Discrete Wavelet Analysis and Neural Network Technique

A novel approach by introducing a statistical parameter to estimate the severity of incipient stator inter-turn short circuit(ITSC)faults in induction motors(IMs)is proposed.Determining the incipient ITSC fault and its severity is challenging for several reasons.The stator currents in the healthy and faulty cases are highly similar during the primary stage of the fault.Moreover,the conventional statistical parameters resulting from the analysis of fault signals do not consistently show a systematic variation with respect to the increase in fault intensity.The objective of this study is the early detection of incipient ITSC faults.Furthermore,it aims to determine the percentage of shorted turns in the faulty phase,which acts as an indicator for severe damage to the stator winding.Modeling of the motor in healthy and defective cases is performed using the Clarke Concordia transform.A discrete wavelet transform is applied to the motor currents using a Daubechies-8 wavelet.The statistical parameters L1 and L2 norms are computed for the detailed coefficients.These parameters are obtained under a variety of loads and defects to acquire the most accurate and generalized features related to the fault.Combining L1 and L2 norms creates a novel statistical parameter with notable characteristics to achieve the research aim.An artificial neural network-based back propagation algorithm is employed as a classifier to implement the classification process.The classifier output defines the percentage of defective turns with a high level of accuracy.The competency of the adopted methodology is validated via simulations and experiments.The results confirm the merits of the proposed method,with a classification test correctness of 95.29%.