This paper examines urban parking prediction using advanced AI-based technologies like machine and deep learning, automated ML (AutoML), and Federated Learning (FL). ML and DL can provide models with high predictive p...
详细信息
ISBN:
(数字)9798350364316
ISBN:
(纸本)9798350364323
This paper examines urban parking prediction using advanced AI-based technologies like machine and deep learning, automated ML (AutoML), and Federated Learning (FL). ML and DL can provide models with high predictive performance if appropriate data processing has been applied to the raw data collected by the parking sensors. The achieved performance is also determined by the selection and fine-tuning of the proper model. AutoML tools automate this time-consuming process, delivering equivalent or better accuracy. The methodology covers data collection and preprocessing, as well as model development, and highlights the integration of FL for improved data privacy and security. The implementation utilizes open-source tools, making our work applicable to real-world scenarios.
Increasing bus frequency to fulfill the performance requirements of dependable applications may increase the susceptibility of the system to transient faults. This paper describes an integration of protection against ...
Increasing bus frequency to fulfill the performance requirements of dependable applications may increase the susceptibility of the system to transient faults. This paper describes an integration of protection against transient bus faults into the interface of the Hardisc RISC-V core. The protection is based on information redundancy with spatial redundancy features. It enables uninterrupted execution in the presence of transient faults and provides a hardware-software interface for its reporting. The benchmarking results indicate that most of the applications will be impacted minimally. The protection has a negligible impact on the maximal frequency and 8% area and power consumption overhead.
With the emergence of the COVID-19 pandemic,the World Health Organization(WHO)has urged scientists and industrialists to exploremodern information and communication technology(ICT)as a means to reduce or even eliminat...
详细信息
With the emergence of the COVID-19 pandemic,the World Health Organization(WHO)has urged scientists and industrialists to exploremodern information and communication technology(ICT)as a means to reduce or even eliminate *** World Health Organization recently reported that the virus may infect the organism through any organ in the living body,such as the respiratory,the immunity,the nervous,the digestive,or the cardiovascular *** the abovementioned goal,we envision an implanted nanosystem embedded in the intra living-body *** main function of the nanosystem is either to perform diagnosis and mitigation of infectious diseases or to implement a targeted drug delivery system(i.e.,delivery of the therapeutic drug to the diseased tissue or targeted cell).The communication among the nanomachines is accomplished via communication-based molecular *** control/interconnection of the nanosystem is accomplished through the utilization of Internet of bio-nano things(IoBNT).The proposed nanosystem is designed to employ a coded relay nanomachine disciplined by the decode and forward(DF)principle to ensure reliable drug delivery to the targeted ***,both the sensitivity of the drug dose and the phenomenon of drug molecules loss before delivery to the target cell site in long-distance due to the molecules diffusion process are taken into *** this paper,a coded relay NM with conventional coding techniques such as RS and Turbo codes is selected to achieve minimum bit error rate(BER)performance and high signal-to-noise ratio(SNR),while the detection process is based on maximum likelihood(ML)probability and minimum error probability(MEP).The performance analysis of the proposed scheme is evaluated in terms of channel capacity and bit error rate by varying system parameters such as relay position,number of released molecules,relay and receiver *** results are validated through simulation and demonstrate that the proposed scheme can
In the physical propagation environment, the channel matrices of neighboring users exhibit a joint sparsity structure due to the shared scatterers at the Base Station (BS) side. Based on this observation, we consider ...
详细信息
Software development companies commonly use Global Software Development (GSD) in their industry. A competent Scrum team supports the success of the GSD project. This research aims to identify the game components in th...
详细信息
In the dynamic landscape of online social networks, recognizing sensitive content is essential for safeguarding user privacy, fostering inclusivity, and enhancing diversity awareness. Building on prior research, this ...
详细信息
ISBN:
(数字)9798350394191
ISBN:
(纸本)9798350394207
In the dynamic landscape of online social networks, recognizing sensitive content is essential for safeguarding user privacy, fostering inclusivity, and enhancing diversity awareness. Building on prior research, this study explores new dimensions and methodologies for detecting sensitive content. We examine the temporal evolution of sensitive content, revealing how patterns shift over time, and address cross-linguistic challenges, emphasizing cultural and contextual nuances in detection. We employ advanced machine learning techniques, including deep learning models and BERT that improve the accuracy and robustness of the detection procedure. In the experimental study, BERT transformer reported the best performance in detecting sensitive content in text. Additionally, we incorporate explainability techniques such as LIME and SHAP to provide deeper insights into the model's decision-making processes, ensuring predictions are interpretable and reliable. Our work enhances the theoretical framework of sensitive content detection in social networks and provide methods that are accurate and scalable and can facilitate the creation of user-centric interaction that prioritize privacy and user experience.
This paper examines urban parking prediction using advanced AI-based technologies like machine and deep learning, automated ML (AutoML), and Federated Learning (FL). ML and DL can provide models with high predictive p...
详细信息
Mission/safety-critical applications rely on the dependability of their semiconductor control systems. The lockstepping is state-of-the-art when it comes to their protection. This paper compares the dual/triple lockst...
详细信息
ISBN:
(数字)9798350380385
ISBN:
(纸本)9798350380392
Mission/safety-critical applications rely on the dependability of their semiconductor control systems. The lockstepping is state-of-the-art when it comes to their protection. This paper compares the dual/triple lockstep systems with the Hardisc, which features microarchitecture-level protection. For a fair comparison, each system is based on the same architecture and integrates protection against bit-flips in memory and transient faults in the bus. We analyse how individual structures of the system affect the vulnerability of a system to faults. Our fault injection methodology combines pre-synthesis simulation with synthesis data to scale the fault rate of the structures according to their size. The results show that the Hardisc can withstand fault rates orders of magnitude higher than the dual-core lockstep system while preserving the same area and power consumption. It comes with a 5% frequency penalty. The pipeline logic has the most significant impact on the vulnerability of the lockstep system. On the other hand, the ECC-protected register file constraints the maximum failure rate the Hardisc can withstand due to fault accumulation during specific program sections.
Modified Walsh-Hadamard code division multiplexing (MWHCDM) is effective for helicopter satellite communications, where the rotor blades block the transmission channel pe-riodically. This paper addresses reducing peak...
详细信息
ISBN:
(数字)9798350353983
ISBN:
(纸本)9798350353990
Modified Walsh-Hadamard code division multiplexing (MWHCDM) is effective for helicopter satellite communications, where the rotor blades block the transmission channel pe-riodically. This paper addresses reducing peak-to-average power ratio (PAPR) for MWHCDM, applying a selected mapping (SLM) method without side information, proposed for orthogonal frequecy division multiplexing (OFDM) previously, to MWHCDM. The SLM method is especially suitable for the primary modu-lation of quaternary phase-shift keying (QPSK), although the primary modulation of MWHCDM is binary phase-shift keying (BPSK). A novel multiplexing processing based on the structure of MWHCDM signals resolves this mismatch. In addition, introducing amplitude information to the evaluation function employed for blind estimation of phase sequence enhances the estimation performance. computer simulation shows that the proposed SLM method achieves excellent PAPR reduction and phase sequence estimation performance, causing no degradation in bit error rate (BER) performance.
Smart grids (SGs) rely on home area networks (HANs) and neighborhood area networks (NANs) to ensure efficient power distribution, real-time monitoring, and seamless communication between smart devices. Despite these a...
详细信息
暂无评论