The rise in popularity of the Internet of Things (IoT) has increased the need to power devices wirelessly, a process called Wireless Power Transfer (WPT), to avoid the usage of batteries, which present limited lifespans. In particular, Microwave Power Transfer (MPT), both Near-field (NF) and Far-field (FF), use Electromagnetic (EM) waves to transfer power between two points. However, these systems still present some downsides, mainly efficiency-wise. This paper explores the usage of Multibeam Antennas (MBAs), specifically Beamforming Network (BFN)-based ones, to improve the capabilities of traditional MPT and Radio Frequency Energy Harvesting (RFEH) systems. The paper starts by introducing the usage of MPT in IoT applications and how MBAs could help solve some of them or at least mitigate them. Afterward, a general explanation of the typical MBAs architectures, including Passive Multibeam Antennas (PMBAs), Multibeam Phased-Array Antennas (MBPAAs), and Digital Multibeam Antennas (DMBAs) is presented, along with their advantages, drawbacks, and some emerging trends. After introducing the typical architectures of MBAs, a comprehensive literature survey is done around rectennas and MPT Transmitters (TXs). This approach allows us to understand better why some architectures are more present than others in both applications, highlighting the exclusive usage of PMBAs in rectennas due to them not using energy. To finalize the paper, using the literature survey done, some challenges associated with integrating MBAs in MPT and RFEH are presented, along with some works presenting ways to mitigate them.
Telecommunication, Electric apparatus and materials. Electric circuits. Electric networks
Dharmesh Dhabliya, Shailesh V. Kulkarni, Netaji Jadhav
et al.
In the field of healthcare, the intersection of Artificial Intelligence (AI) and Public Health has emerged as an essential component, presenting numerous opportunities for innovation that are one of a kind. The purpose of this research paper is to investigate the historical development, current patterns, and global repercussions of incorporating AI into healthcare systems. The paper provides a comprehensive analysis of the application of AI in the field of public health. It
covers the progression of the field, beginning with the initial efforts to automate diagnostic procedures and ending with the most recent developments in predictive modeling and precision medicine. The research investigates the degree to which various nations have adopted AI, highlighting both successful implementations and ongoing challenges in the framework of the global landscape. The intentional incorporation of AI is presented as a driving force for the transformation of healthcare provision. This transformation has the potential to provide potential benefits such as improved precision in diagnosis, effectiveness in treatment, and efficient utilization of treatment resources. In addition, the paper places an emphasis on the proactive role that AI plays in identifying and mitigating emerging health risks.
Providing useful information about the policies, practices, and frameworks that enable the efficient incorporation of AI
into public health is the primary objective of this research. The purpose of this paper is to provide policymakers,
healthcare practitioners, and researchers with suggestions that can be put into practice today by combining historical
perspectives and analyzing patterns that are currently occurring. The purpose of this action is to have an impact on the
conversation that is taking place about the future of healthcare delivery, with the intention of highlighting the
significant impact that AI can have on improving the circumstances of public health.
With the large-scale commercial use of the global 5G network and the rapid growth of mobile Internet traffic, more abundant wireless spectrum resources can be released, and the demand for high-speed optical modules in wireless front-haul networks is increasingly prominent. Focusing on the key technologies of 50 Gbit/s front-haul optical modules, two main networking methods were deeply analyzed, the typical transmission distance and link loss were analyzed, the maximum and minimum dispersion values of coarse wave division multiplexing (CWDM) wavelengths in a 10 km scenario were explored, and the corresponding dispersion compensation strategies were studied. Through experiments, the changes in optical power penalty of different multi-path interference (MPI) were verified, and the potential impact of MPI noise on error performance was analyzed in detail. In addition, deep research on the optoelectronic chip scheme of 50 Gbit/s modules was conducted, the parameters of various types of optical modules were rigorously tested, standardized suggestions for the optoelectronic interface parameters of 50 Gbit/s front-haul modules were proposed, the current standard status of 50 Gbit/s modules at home and abroad was detailed, and the development trend of future applications was prospected.
Modeling the probability distribution of rows in structured electronic health records and generating realistic synthetic data is a non-trivial task.Tabular data usually contains discrete columns, and traditional encoding approaches may suffer from the curse of feature dimensionality.Poincaré Ball model was utilized to model the hierarchical structure of nominal variables and Gaussian copula-based generative adversarial network was employed to provide synthetic structured electronic health records.The generated training data are experimentally tested to achieve only 2% difference in utility from the original data yet ensure privacy.
This work presents a comprehensive theoretical analysis of current-mode power amplifiers as a function of input power for different biasing classes under the common simplifying assumption of constant transconductance and hard current cut-off/saturation. Typically, the theoretical analysis of power amplifier performance and behavior are carried out only at maximum output power. However, to achieve high data-rates, modern telecommunication systems adopt signals characterized by a very high peak-to-average power ratio, thus it is useful to analyze the power amplifier behavior as a function of power back-off. Moreover, in many cases, to enhance the efficiency and/or to apply harmonic shaping techniques, a clipped drain-source current, which approaches a square wave, is required. The classical analysis can be extended to low power levels only under the assumption of power-independent conduction angle, which is true only for class-A and class-B amplifiers, and does not take into account possible waveform clipping at maximum current. This work presents a complete theoretical Fourier analysis of FET-based power amplifiers as a function of quiescent drain-source current at any input power level and accounting for the clipped current case, up to the square-wave limit, reorganizing and completing the material that can be found in classical textbooks in the field.
Paul M Garrett, Joshua P White, Stephan Lewandowsky
et al.
In response to the COVID-19 pandemic, many Governments are instituting mobile tracking technologies to perform rapid contact tracing. However, these technologies are only effective if the public is willing to use them, implying that their perceived public health benefits must outweigh personal concerns over privacy and security. The Australian federal government recently launched the 'COVIDSafe' app, designed to anonymously register nearby contacts. If a contact later identifies as infected with COVID-19, health department officials can rapidly followup with their registered contacts to stop the virus' spread. The current study assessed attitudes towards three tracking technologies (telecommunication network tracking, a government app, and Apple and Google's Bluetooth exposure notification system) in two representative samples of the Australian public prior to the launch of COVIDSafe. We compared these attitudes to usage of the COVIDSafe app after its launch in a further two representative samples of the Australian public. Using Bayesian methods, we find widespread acceptance for all tracking technologies, however, observe a large intention-behaviour gap between people's stated attitudes and actual uptake of the COVIDSafe app. We consider the policy implications of these results for Australia and the world at large.
To solve the problem that in the system wide information management (SWIM) network,the SWIM service provider suffers from SWIM service interruption,service delay increase or service quality degradation due to malicious attack or self-failure.Therefore,a proactive migration model of SWIM service was proposed on the basis of situation awareness,which used the random forest algorithm to timely judge the SWIM service provider security situation.SWIM service authority was actively migrated according to security situation,and the emergencies impact on SWIM services were reduces.Experimental results show that the proposed model can guarantee services continuity in an emergency event,which has higher reliability and stability than SWIM network in which the service migration model is not deployed.
Dhanielly P. R. de Lima, Marco A. Gerosa, Tayana U. Conte
et al.
Abstract Online discussion forums are asynchronous communication tools that are widely used in Learning Management Systems. However, instructors and students face various difficulties, and instructors lack a guide on what strategies they can use to achieve a more participatory forum environment. This work aims to identify benefits and difficulties of using online discussion forums from the instructors’ point of view, and to provide a list of strategies and improvements that can mitigate the challenges and lead to a more participatory forum. We used coding procedures to analyze data collected through semi-structured interviews. The results of our exploratory analysis are relevant to the distance learning community and can inform instructors, developers, and researchers to help them improve the quality of mediation and use of forums.
Sangkil Kim, Amin Rida, Vasileios Lakafosis
et al.
This paper introduces a low‐cost, high‐performance mmWave antenna array module at 77 GHz. Conventional waveguide transitions have been replaced by 3D CPW‐microstrip transitions which are much simpler to realize. They are compatible with low‐cost substrate fabrication processes, allowing easy integration of ICs in 3D multi‐chip modules. An antenna array is designed and implemented using multilayer coupled‐fed patch antenna technology. The proposed 16 × 16 array antenna has a fractional bandwidth of 8.4% (6.5 GHz) and a 23.6‐dBi realized gain at 77 GHz.
Margherita Zito, Federica Emanuel, Monica Molino
et al.
Turnover intentions refer to employees' intent to leave the organization and, within call centers, it can be influenced by factors such as relational variables or the perception of the quality of working life, which can be affected by emotional dissonance. This specific job demand to express emotions not felt is peculiar in call centers, and can influence job satisfaction and turnover intentions, a crucial problem among these working contexts. This study aims to detect, within the theoretical framework of the Job Demands-Resources Model, the role of emotional dissonance (job demand), and two resources, job autonomy and supervisors' support, in the perception of job satisfaction and turnover intentions among an Italian call center.The study involved 318 call center agents of an Italian Telecommunication Company. Data analysis first performed descriptive statistics through SPSS 22. A path analysis was then performed through LISREL 8.72 and tested both direct and indirect effects.Results suggest the role of resources in fostering job satisfaction and in decreasing turnover intentions. Emotional dissonance reveals a negative relation with job satisfaction and a positive relation with turnover. Moreover, job satisfaction is negatively related with turnover and mediates the relationship between job resources and turnover.This study contributes to extend the knowledge about the variables influencing turnover intentions, a crucial problem among call centers. Moreover, the study identifies theoretical considerations and practical implications to promote well-being among call center employees. To foster job satisfaction and reduce turnover intentions, in fact, it is important to make resources available, but also to offer specific training programs to make employees and supervisors aware about the consequences of emotional dissonance.
Moutakki Zakaria, Ouloul Imad Mohamed, Afdel Karim
et al.
Today, Road traffic video surveillance becomes the centre of several concerns. It presents an important way for analysis of road traffic in highways. Road traffic video surveillance can help to resolve many problems which can influence road safety. This paper presents a real-time management and control system which serve to analyze road traffic using a stationary camera. The proposed system can measure the quantity and characteristics of traffic in real time based on three modules, segmentation, classification and vehicle counting. Our contribution consists of developing a feature-based counting system for vehicle detection and recognition under the conditions which present a challenge in recent systems, such as occlusions, and illumination conditions. Our method can perform vehicle detection and classification by eliminating the influence of many factors on system efficiency. The obtained results show that the system proposed in this paper provides a counting rate higher than that of some existing methods.
This paper addresses the problem of efficient searchingfor Nonlinear Feedback Shift Registers (NLFSRs) with a guaranteed full period. The maximum possible period for an n-bit NLFSR is 2n1 (an all-zero state is omitted). A multi-stages hybrid algorithm which utilizes Graphics Processor Units (GPU) power was developed for processing data-parallel throughput computation. Usage of the abovementioned algorithm allows giving an extended list of n-bit NLFSR with maximum period for 7 cryptographically applicable types of feedback functions
Based on the mutual information power analysis attack in time domain of the crypto chip,a method for analyzing the energy of the maximum mutual information coefficient in the frequency domain was proposed.This method combined the principle of password chip information leakage in frequency domain and the principle of mutual information power analysis.The concept of maximum mutual information coefficient was introduced,which avoided the operation of accurate alignment in time domain.Experiments on the algorithm of SMS4 show that the effectiveness of the maximum mutual information coefficient attack in the frequency domain is extended to the method of the side channel energy analysis.
At present, RFID is installed on mobile devices such as mobile phones or PDAs and provides a means to obtain information about objects equipped with an RFID tag over a multi-channeled telecommunication networks. To use mobile RFIDs, reader collision problems should be addressed given that readers are continuously moving. Moreover, in a multichannel environment for mobile RFIDs, interference between adjacent channels should be considered. This work first defines a new concept of a reader collision problem between adjacent channels and then suggests a novel reader anti-collision algorithm for RFID readers that use multiple channels. To avoid interference with adjacent channels, the suggested algorithm separates data channels into odd and even numbered channels and allocates odd-numbered channels first to readers. It also sets an unused channel between the control channel and data channels to ensure that control messages and the signal of the adjacent channel experience no interference. Experimental results show that suggested algorithm shows throughput improvements ranging from 29% to 46% for tag identifications compared to the GENTLE reader anti-collision algorithm for multichannel RFID networks.
The imaging sensors are able to provide intuitive visual information for quick recognition and decision. However, imaging sensors usually generate vast amount of data. Therefore, processing and coding of image data collected in a sensor network for the purpose of energy efficient transmission poses a significant technical challenge. In particular, multiple sensors may be collecting similar visual information simultaneously. We propose in this paper a novel collaborative image coding and transmission scheme to minimize the energy for data transmission. First, we apply a shape matching method to coarsely register images to find out maximal overlap to exploit the spatial correlation between images acquired from neighboring sensors. For a given image sequence, we transmit background image only once. A lightweight and efficient background subtraction method is employed to detect targets. Only the regions of target and their spatial locations are transmitted to the monitoring center. The whole image can then be reconstructed by fusing the background and the target images as well as their spatial locations. Experimental results show that the energy for image transmission can indeed be greatly reduced with collaborative image coding and transmission.