148 research outputs found
Electromagnetic Waves Scattering Characteristics of Metasurfaces
No full textAlmost extreme control of electromagnetic fields is achievable using metamaterial and metasurfaces. This chapter details design techniques, challenges, and possible solutions of diffraction type, transmitted, specular, and absorptive type of metasurfaces in an attempt to achieve extraordinary device performance for a particular application. In metasurfaces, the transmission can also involve scattering using the phenomenon of diffraction, which is directly defined by the properties of the metasurface. Electromagnetic wave scattering patterns dependent on the incident polarization can be tailored by the encoded metasurfaces with regular sequences. On contrast, polarization-insensitive diffusion-like scattering can also be successfully achieved by digital metasurface encoded with randomly distributed coding sequences leading to substantial suppression of backward scattering in a broadband microwave frequency. It is believed that controlling the electromagnetic waves reflected from and transmitted through intelligently designed metasurfaces can shape the future of the communication industry.<br/
Beamformer development challenges for 5G and beyond
No full textIn this chapter, we first discussed the definitions that are vital to understand the working of a beamformer. We then classified the beamformer based on the architecture, frequency of operation and a use case. These clarifications are done keeping in mind the future technological advancements in the communication industry. Beamformer architectures are further divided into purely analog, digital and hybrid types, when each one of them has a specific need in specialized communication standards. Frequency bands of operations are divided into the well-known 5G sub bands that are sub-6-GHz and mmWave bands. We further discussed the ways in which a beamformer function differs when they are operating at different frequency bands. Lastly, we classified beamformers in terms of their utility as a fixed or mobile radio in a communication system. State-of-the-art beamformer examples are comparatively analyzed to better predict the most suitable choice for a given classification of beamformers in the 5G and beyond applications
Standardization of three dimensional Brain SPECT images. Application of Automated ImageRegistration in Research and Clinics
No full textapplication/pdf博士学位論文の要旨及び審査結果の要旨 (Summary of Thesis(DR))253290 bytesothe
Medicine supply chain model for an integrated healthcare system with uncertain product complaints
No full textHybrid Intrusion Detection System Based on Optimal Feature Selection and Evolutionary Algorithm for Wired Networks
No full textThe field of cybersecurity encounters ongoing difficulties in identifying and preventing attacks in networks, and the pervasive threat of cyberattacks demands continual advancements in intrusion detection systems (IDS) to safeguard network integrity. Traditional intrusion detection systems face the challenge of class imbalance. Addressing the formidable challenges posed by class imbalance and high-dimensional data, this research proposes a novel hybrid IDS approach. Leveraging (ACO), the algorithm navigates complex datasets to identify salient features, effectively mitigating the complexities associated with high-dimensional data. Subsequently, a Weighted Stacking Classifier amalgamates the strengths of Random Forest, AdaBoost, and Gradient Boosting classifiers, fortifying the system’s ability to handle class imbalance robustly. By strategically enhancing the importance of base classifiers with favourable training outcomes and diminishing the influence of those yielding inferior results, the hybrid IDS endeavors to optimize classification efficacy. The experimentation, conducted exclusively on the dataset named NSL-KDD, demonstrates the efficacy of the proposed model, yielding remarkable results. With a 90.13% Accuracy, 88.87% precision, 91.23% Recall, and 87.33% F1-score, the hybrid IDS exhibits superior performance in detecting malicious activity. The findings underscore the viability of the proposed hybrid IDS as a potent tool in the ongoing battle against cyber threats, positioning it for real-world deployment across diverse networks
Hybrid Intrusion Detection System Based on Optimal Feature Selection and Evolutionary Algorithm for Wired Networks
No full textThe field of cybersecurity encounters ongoing difficulties in identifying and preventing attacks in networks, and the pervasive threat of cyberattacks demands continual advancements in intrusion detection systems (IDS) to safeguard network integrity. Traditional intrusion detection systems face the challenge of class imbalance. Addressing the formidable challenges posed by class imbalance and high-dimensional data, this research proposes a novel hybrid IDS approach. Leveraging (ACO), the algorithm navigates complex datasets to identify salient features, effectively mitigating the complexities associated with high-dimensional data. Subsequently, a Weighted Stacking Classifier amalgamates the strengths of Random Forest, AdaBoost, and Gradient Boosting classifiers, fortifying the system’s ability to handle class imbalance robustly. By strategically enhancing the importance of base classifiers with favourable training outcomes and diminishing the influence of those yielding inferior results, the hybrid IDS endeavors to optimize classification efficacy. The experimentation, conducted exclusively on the dataset named NSL-KDD, demonstrates the efficacy of the proposed model, yielding remarkable results. With a 90.13% Accuracy, 88.87% precision, 91.23% Recall, and 87.33% F1-score, the hybrid IDS exhibits superior performance in detecting malicious activity. The findings underscore the viability of the proposed hybrid IDS as a potent tool in the ongoing battle against cyber threats, positioning it for real-world deployment across diverse networks
Cloudlet computing : recent advances, taxonomy, and challenges
No full textA cloudlet is an emerging computing paradigm that is designed to meet the requirements and expectations of the Internet of things (IoT) and tackle the conventional limitations of a cloud (e.g., high latency). The idea is to bring computing resources (i.e., storage and processing) to the edge of a network. This article presents a taxonomy of cloudlet applications, outlines cloudlet utilities, and describes recent advances, challenges, and future research directions. Based on the literature, a unique taxonomy of cloudlet applications is designed. Moreover, a cloudlet computation offloading application for augmenting resource-constrained IoT devices, handling compute-intensive tasks, and minimizing the energy consumption of related devices is explored. This study also highlights the viability of cloudlets to support smart systems and applications, such as augmented reality, virtual reality, and applications that require high-quality service. Finally, the role of cloudlets in emergency situations, hostile conditions, and in the technological integration of future applications and services is elaborated in detail. © 2013 IEEE
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