Medi-Block Record Secure Data Sharing in Healthcare System:Issues,Solutions and Challenges

With the advancements in the era of artificial intelligence,blockchain,cloud computing,and big data,there is a need for secure,decentralized medical record storage and retrieval systems.While cloud storage solves storage issues,it is challenging to realize secure sharing of records over the network.Medi-block record in the healthcare system has brought a new digitalization method for patients’medical records.This centralized technology provides a symmetrical process between the hospital and doctors when patients urgently need to go to a different or nearby hospital.It enables electronic medical records to be available with the correct authentication and restricts access to medical data retrieval.Medi-block record is the consumer-centered healthcare data system that brings reliable and transparent datasets for the medical record.This study presents an extensive review of proposed solutions aiming to protect the privacy and integrity of medical data by securing data sharing for Medi-block records.It also aims to propose a comprehensive investigation of the recent advances in different methods of securing data sharing,such as using Blockchain technology,Access Control,Privacy-Preserving,Proxy Re-Encryption,and Service-On-Chain approach.Finally,we highlight the open issues and identify the challenges regarding secure data sharing for Medi-block records in the healthcare systems.

Polariton lasing in Mie-resonant perovskite nanocavity

Deeply subwavelength lasers(or nanolasers)are highly demanded for compact on-chip bioimaging and sensing at the nanoscale.One of the main obstacles for the development of single-particle nanolasers with all three dimensions shorter than the emitting wavelength in the visible range is the high lasing thresholds and the resulting overheating.Here we ex-ploit exciton-polariton condensation and mirror-image Mie modes in a cuboid CsPbBr3 nanoparticle to achieve coherent emission at the visible wavelength of around 0.53μm from its ultra-small(≈0.007μm3 or≈λ3/20)semiconductor nanocav-ity.The polaritonic nature of the emission from the nanocavity localized in all three dimensions is proven by direct com-parison with corresponding one-dimensional and two-dimensional waveguiding systems with similar material parameters.Such a deeply subwavelength nanolaser is enabled not only by the high values for exciton binding energy(≈35 meV),re-fractive index(>2.5 at low temperature),and luminescence quantum yield of CsPbBr3,but also by the optimization of po-laritons condensation on the Mie resonances with quality factors improved by the metallic substrate.Moreover,the key parameters for optimal lasing conditions are intermode free spectral range and phonons spectrum in CsPbBr3,which govern polaritons condensation path.Such chemically synthesized colloidal CsPbBr3 nanolasers can be potentially de-posited on arbitrary surfaces,which makes them a versatile tool for integration with various on-chip systems.

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.

Cost and Efficiency Analysis of Steganography in the IEEE 802.11ah IoT Protocol

The widespread use of the Internet of Things(IoT)applications has enormously increased the danger level of data leakage and theft in IoT as data transmission occurs through a public channel.As a result,the security of the IoT has become a serious challenge in the field of information security.Steganography on the network is a critical tool for preventing the leakage of private information and enabling secure and encrypted communication.The primary purpose of steganography is to conceal sensitive information in any form of media such as audio,video,text,or photos,and securely transfer it through wireless networks.In this paper,we analyse the performance characteristics of one of the steganography techniques called Hidden Communication System for Corrupted Networks(HCCNETs)for hiding sensitive data.This performance analysis includes the efficiency and the cost of the system in Wireless Local Area Networks(WLANs),specifically in the IEEE 802.11ah IoT protocol.The analysis is mainly based on a two-dimensional Markov chain model in the presence of an error channel.Additionally,the model considers packet arrival rate,back-off timer freezing,back-off stages,and short retry limit to ensure compliance with IEEE 802.11ah requirements.It stresses the importance of taking these elements into consideration while modeling the efficiency and cost of the steganographic channel system.These parameters often result in a high precise channel access estimation,a more accurate and efficient accuracy measurements system,efficient channel utilisation,avoidance of throughput saturation overestimation,and ensuring that no packet is served endlessly.Evaluated results demonstrate that HCCNETs is an effective approach at low cost.

Compression of ECG Signals Based on DWT and Exploiting the Correlation between ECG Signal Samples

This paper presents a hybrid technique for the compression of ECG signals based on DWT and exploiting the correlation between signal samples. It incorporates Discrete Wavelet Transform (DWT), Differential Pulse Code Modulation (DPCM), and run-length coding techniques for the compression of different parts of the signal;where lossless compression is adopted in clinically relevant parts and lossy compression is used in those parts that are not clinically relevant. The proposed compression algorithm begins by segmenting the ECG signal into its main components (P-waves, QRS-complexes, T-waves, U-waves and the isoelectric waves). The resulting waves are grouped into Region of Interest (RoI) and Non Region of Interest (NonRoI) parts. Consequently, lossless and lossy compression schemes are applied to the RoI and NonRoI parts respectively. Ideally we would like to compress the signal losslessly, but in many applications this is not an option. Thus, given a fixed bit budget, it makes sense to spend more bits to represent those parts of the signal that belong to a specific RoI and, thus, reconstruct them with higher fidelity, while allowing other parts to suffer larger distortion. For this purpose, the correlation between the successive samples of the RoI part is utilized by adopting DPCM approach. However the NonRoI part is compressed using DWT, thresholding and coding techniques. The wavelet transformation is used for concentrating the signal energy into a small number of transform coefficients. Compression is then achieved by selecting a subset of the most relevant coefficients which afterwards are efficiently coded. Illustrative examples are given to demonstrate thresholding based on energy packing efficiency strategy, coding of DWT coefficients and data packetizing. The performance of the proposed algorithm is tested in terms of the compression ratio and the PRD distortion metrics for the compression of 10 seconds of data extracted from records 100 and 117 of MIT-BIH database. The obtained results revealed that the proposed technique possesses higher compression ratios and lower PRD compared to the other wavelet transformation techniques. The principal advantages of the proposed approach are: 1) the deployment of different compression schemes to compress different ECG parts to reduce the correlation between consecutive signal samples;and 2) getting high compression ratios with acceptable reconstruction signal quality compared to the recently published results.

Hybrid Uplink-Time Difference of Arrival and Assisted-GPS Positioning Technique

A hybrid positioning system is merely one in which multiple systems are used for positioning purposes. This virtually always, though not necessarily, includes Global Positioning System (GPS) as it is the only global positioning network currently. Combination of mobile network and GPS positioning techniques provide a higher accuracy of mobile location than positions based on a standalone GPS or mobile network based positions. High accuracy of mobile position is mainly essential for emergency, military and many other location based services such as productivity enhancement, entertainment, position-based advertising, navigation, asset management and geographic information access. Assisted GPS, also known as A-GPS or AGPS, enhances the performance of the standard GPS in devices connected to the cellular network. This paper introduces a new hybrid technique for mobile location determination utilizing Universal Mobile Telecommunication System (UMTS) network, Mobile Station (MS) and GPS positioning characteristics. Different positioning techniques are chosen according to positioning parameters. The minimum required number of UMTS base stations, location measurement units and GPS satellites are calculated in this paper. The required number of GPS satellites is reduced from four satellites to three ones while using three dimension positioning and from three satellites to two ones at two dimension positioning. Moreover, MS receiver main functions including both network and GPS received paths to achieve output assisted data are discussed. In this paper many drawbacks such as indoor positioning, receiver high power consumption, delay in first time to fix position, low position accuracy as well as large number of required satellites and base stations are improved.

Application of LED Type Lamps in Domestic and Public Utilities and Gain Capability to Run New Small Investments in Rwanda

The Rwandan State-run Energy Water and Sanitation Authority Company (EWSA) is rapidly increasing the number of population having access to electrical power energy. 30% of electrical energy is used in lighting. The incandescent bulbs, compact fluorescent lamp bulbs as well as fluorescent tubes are mostly used to convert electrical energy into light. The said light sources have many disadvantages such as excessive power consumption leading to giant bills of electricity, short life span leading to continuous replacement of lamps, and emission of CO2. Application of light-emitting diode (LED) lamps in lighting in long term suppresses the aforementioned problems resulting into saving of money that will be used for running new small investments.

Distributional Relations on Impulse Radiating Surface and Point Type Sources

The electromagnetic field relations are demonstrated on impulse radiating surface and point type sources, which are characterized by first and second order singularities at rest in a Schwartz-Sobolev space setting. The investigation starts with a general introduction to Schwartz-Sobolev distributions, the electromagnetic field equations and various modes of impulsive radiation. This is followed by an outline of temporal distributional relations in arbitrary media and distributional derivative operations on an arbitrary regular surface, all of which are employed in an investigation of impulse radiation mechanism on single and double layer sources. Similar steps are followed in a description of point distributions and investigation of impulse radiation mechanism on electric and magnetic point dipoles.

Comparison of Solar Trackers and Application of a Sensor Less Dual Axis Solar Tracker

In the 21th century, one of the biggest problems that the world faces is energy provision. Today, the way that most countries use for energy production is not clean and continuous. The most obvious proof for that is the change in the climate. The amount of CO2 （carbon dioxide） that is caused by fossil fuel burning increases day by day and this situation creates the greenhouse effect and change in the climate. The sun is one of the best solutions to this problem. It is not only clean and continuous, but also available anywhere, anytime. However, the efficiency of a photovoltaic system is directly related to the amount of solar energy acquired by the system which means that, it is necessary to follow the sun to have a high efficient system. There are two types of trackers that follow the sun and there are several ways to build them. In this paper, solar tracker designs are examined and a new dual axis solar tracker design is given.

A novel anti-slip control approach for railway vehicles with traction based on adhesion estimation with swarm intelligence

Anti-slip control systems are essential for railway vehicle systems with traction.In order to propose an effective anti-slip control system,adhesion information between wheel and rail can be useful.However,direct measurement or observation of adhesion condition for a railway vehicle in operation is quite demanding.Therefore,a proportional–integral controller,which operates simultaneously with a recently proposed swarm intelligencebased adhesion estimation algorithm,is proposed in this study.This approach provides determination of the adhesion optimum on the adhesion-slip curve so that a reference slip value for the controller can be determined according to the adhesion conditions between wheel and rail.To validate the methodology,a tram wheel test stand with an independently rotating wheel,which is a model of some low floor trams produced in Czechia,is considered.Results reveal that this new approach is more effective than a conventional controller without adhesion condition estimation.

Performance Analysis of Modulation Techniques in 5G Communication System

In the 5^(th) generation mobile communication(5G)system,better bitrate,better power consumption,and better Bit Error Rate are needed.To meet all these requirements in 5G,the waveform is important.Although the Orthogonal Frequency Division Multiplexing(OFDM)modulation scheme has been commonly used in 4G,it is difficult to meet the requirements of 5G.A lot of candidate waveforms are discussed in the 5G system included Filter Bank Multicarrier(FBMC),Universal Filtered Multicarrier(UFMC),Filtered OFDM(F-OFDM),and Generalized Frequency Division Multiplexing(GFDM),etc.However,since GFDM is no longer widely used,in this paper,FBMC,UFMC,and F-OFDM modulation schemes are discussed and compared with OFDM.Power Spectral Density(PSD),Bit Error Rate(BER),Transmitted Signal Power,Peak Average Power Ratio(PAPR)and Bit Rate parameters of the modulation schemes are studied and compared with OFDM.FBMC demonstrates to be the most promising modulation scheme for 5G systems.

Voltage Unbalance Mitigation in Low Voltage Distribution Networks with Photovoltaic Systems

This paper proposes a technique to mitigate the voltage unbalance issue caused by the high penetration of photovoltaic （PV） systems into the low voltage distribution networks （LVDN） using a single phase energy storage system （ESS）. The ESS comprises a hi-directional power flow inverter and a battery bank. The system is capable of absorbing the excess power and delivering power to the network in order to keep the voltage unbalance factor （VUF） below the statutory limit of 1%. Investigations are carried out in the experimental small-scale energy zone （SSEZ）. The experimental results demonstrate that the ESS is capable of mitigating the VUF of the network.

A New Method for Fastening the Convergence of Immune Algorithms Using an Adaptive Mutation Approach

This paper presents a new adaptive mutation approach for fastening the convergence of immune algorithms (IAs). This method is adopted to realize the twin goals of maintaining diversity in the population and sustaining the convergence capacity of the IA. In this method, the mutation rate (pm) is adaptively varied depending on the fitness values of the solutions. Solutions of high fitness are protected, while solutions with sub-average fitness are totally disrupted. A solution to the problem of deciding the optimal value of pm is obtained. Experiments are carried out to compare the proposed approach to traditional one on a set of optimization problems. These are namely: 1) an exponential multi-variable function;2) a rapidly varying multimodal function and 3) design of a second order 2-D narrow band recursive LPF. Simulation results show that the proposed method efficiently improves IA’s performance and prevents it from getting stuck at a local optimum.

The Prediction of Propagation Loss of FM Radio Station Using Artificial Neural Network

In order to calculate the propagation loss of electromagnetic waves produced by a transmitter, a variety of models based on empirical and deterministic formulas are used. In this study, one of the artificial neural networks models, Levenberg-Marquardt algorithm, which is quite effective for predicting the propagation is used and the results obtained by this algorithm are compared with the simulation results based on ITU-R 1546 and Epstein-Peterson models. In this paper, the propagation loss of FM radio station using artificial neural networks models is studied depending on the Levenberg-Marquardt algorithm. For training the artificial neural network, as the input data;range (r), effective antenna height (h) and terrain irregularity (△H) parameters are involved and measured values are treated as the output data. The good results obtained in the city area reveal that the artificial neural network is a very efficient method to compute models which integrate theoretical and experimental data. Meanwhile, the results show that an ANN model performs very well compared with theoretical and empiric propagation models with regard to prediction accuracy, complexity, and prediction time. By comparing the results, the RMSE for Neural Network Model using Levenberg-Marquardt is 9.57, and it is lower than that of classical propagation model using Epstein-Peterson for which RMSE is 10.26.

Delta-doped quantum wire tunnel junction for highly concentrated solar cells

We propose a novel structure for tunnel junction based on delta-doped AlGaAs/GaAs quantum wires. Higher spatial confinement of quantum wires alongside the increased effective doping concentration in the delta-doped regions extremely increase the peak tunneling current and enhance the performance of tunnel junction. The proposed structure can be used as tunnel junction in the multijunction solar cells under the highest possible thermodynamically limited solar concentration.The combination of the quantum wire with the delta-doped structure can be of benefit to the solar cells' advantages including higher number of sub-bands and high degeneracy. Simulation results show a voltage drop of 40 mV due to the proposed tunnel junction used in a multijunction solar cell which presents an extremely low resistance to the achieved peak tunneling current.

Compensating the effects of DC bias lines on terahertz photomixer antennas using resistively loaded lines

This paper proposed a method,namely resistively loaded lines(RLL),to compensate the effects of the DC bias lines after investigating its effects on several types of antennas for terahertz photomixers.The RLL is formed by placing lumped resistances periodically on the DC bias line in order to cease the leakage current virtually,w hich cause a significant amount of distortion on the antenna performance.The simulation results of the dipole,folded dipole,log-periodic,and spiral antennas show that RLL almost removes the effects of the bias lines and improves the antenna radiation resistance and radiation pattern notably compared w ith that of the commonly used bias line types,such as coplanar stripline and photonic bandgap type bias lines.

Distributed Air-Conditioning Energy Management System within the Smart Grid Context

-Air-conditioning （AC） systems are the major energy consumption units in residential and commercial buildings. In the context of smart grid, optimizing AC operations leads to substantial saving in energy consumption, reducing the consumer＇s bill and contributing to the environment by minimizing carbon emissions from generating stations. This paper presents a distributed AC energy management system for buildings by using networked master-slaves controller architecture. The proposed system was designed, simulated, and experimentally tested by using real AC units in a students＇ residence hall. Based on the students＇ class schedules, several operational scenarios were implemented and tested. The proposed system implementation leads to a 40% to 60% saving of the consumed energy by the tested units. The same energy management scheme can be applied and implemented in other commercial and residential buildings.

A Novel PoW Scheme Implemented by Probabilistic Signature for Blockchain

PoW(Proof of Work)plays a significant role in most blockchain systems to grant an accounting right over decentralized participants and ensure tamper resistance.Though hash functions are generally exploited for PoW due to their merits on summering,anti-collision,and irreversibility,they cannot certify that the bookkeeper is exactly the worker.Thereafter,such insistence may lead to abuse or even embezzlement of computing power for the benefit of malicious miners.To preserve the functionality of PoW but also bind the miners’signing keys with their works,we build a post-quantum PoW scheme by changing the approximate closest vector norm for probabilistic NTRUSign.Different from the schemes based on hash functions,our scheme takes signing as the proof of work where signature verification is just the evidence of block reward.We also presented a method to adjust the difficulty of signing by modifying the probability of generating a correct signature.The performance of our scheme is also analyzed theoretically and experimentally,which implies its practicability and advantages.

A New Type of Capacitive Machine

The paper proposes a new type of the synchronous capacitive machine operated on a principle of the electric field effect. The proposed machine has smaller size and lighter weight than the standard electromagnetic synchronous machines with the same rated parameters. Another important advantage is a simple structure of the machine, which simplifies the production process and reduces the costs of the motor. The paper also presents extensive simulation results of the proposed capacitive machine. The simulation results show that the proposed machine is able to reach the same power output as the electromagnetic machines.

Compact Two Shorting Pin Loaded ETMA

In this study ETMA （Equilateral Triangular Microstrip Antennas） are designed to form dual frequency by inserting two shorting pins. Microstrip patch antennas＇ resonant frequencies with two shorting pins are represented in this study by not only considering the theoretical results but also considering the both simulated and experimental results. For each geometry, positions of shorting pins are varied and effects of these variations are analyzed. The presented patch antennas in literature which have the same shape with shorting pin and without shorting pin are compared and results are presented. The methods in literature presented for estimating the resonant frequency depends on analytical methods which are originated from curve fitting. The results of this study will be the basement of the latter studies that predict the resonant frequencies of mentioned antennas before producing the antenna so that the engineers handle the problem by saving the time and estimating the frequency before production.