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Experimental observation of coherent-perfect-absorber and laser points in anti-PT symmetry

Physical Review A 2024年第3期110卷 033504页

作者： Minye Yang Qi Zhong Zhilu Ye Şahin K. Özdemir Mohamed Farhat Ramy El-Ganainy Pai-Yen Chen State Key Laboratory for Manufacturing Systems Engineering School of Electronic Science and Engineering Department of Electrical and Computer Engineering Department of Engineering Science and Mechanics The Materials Research Institute Computer Electrical and Mathematical Science and Engineering Division Department of Physics Henes Center for Quantum Phenomena

The coexistence of coherent perfect absorber and laser or amplifier (CPAL) point is a peculiar spectral singularity associated with the scattering matrices of non-Hermitian systems. While the potential of CPAL systems for sensing application has been highlighted recently, the extreme sensitivity of parity-time (PT)-symmetric CPAL devices to the input signal deviations has so far impeded their practical utilization. Here we explore a strategy for implementing CPAL circuits by exploiting another type of non-Hermitian symmetry, namely anti-PT (APT) symmetry. We demonstrate that the condition for building CPAL in our proposed APT-symmetric electronic circuits additionally requires parity symmetry, which simplifies the circuit design and implementation. Additionally, we show that this newly proposed structure is 1.85 times more robust compared to previous CPAL devices studied in the literature.

关键词： Noise Quantum sensing Non-Hermitian systems PT-symmetry

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A High Gain GaAs pHEMT Low Noise Amplifier for Ka-Band Active Phase Shifters

A High Gain GaAs pHEMT Low Noise Amplifier for Ka-Band Activ...

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2024 IEEE Microwaves, Antennas, and Propagation Conference, MAPCON 2024

作者： Karmakar, Nemai C. Lin, Chia-Han Trinh, Kim Tuyen Chiu, Hsien-Chin Kao, Hsuan-Ling Department of Electrical & Computer Systems Engineering Monash University Clayton MelbourneVIC3800 Australia Department of Electronic Engineering Chang Gung University Tao-Yuan Taiwan

ISBN: (纸本)9798350379693

A two-stage common source topology, 36 to 38 GHz GaAs pHEMT Low Noise Amplifier (LNA) was designed, fabricated, and tested. This LNA is an essential part of the proposed active phase shifter for soil moisture radiometer phased array antenna. The LNA provides 23 dB gain. A typical noise figure (NF) of 5 dB was measured at 37 GHz. DC power consumption is about 154 mW. The MMIC chip was fabricated by using 0.15 µm GaAs pHEMT process. The total chip area including all the pads and scribe lines is about 1.5 mm x 0.9 mm. Measured gain flatness is about ±1 dB within 36-38 GHz bandwidth. The high gain, small gain flatness makes this device well suited for the phase shifters in the soil moisture radiometer phased array antenna. © 2024 IEEE.

关键词： III-V semiconductors

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Accelerating CNNs for Pneumonia Disease Diagnosis via Heterogeneous FPGA systems 9

Accelerating CNNs for Pneumonia Disease Diagnosis via Hetero...

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9th South-East Europe Design Automation, computer engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2024

作者： Sanida, Theodora Sideris, Argyrios Sanida, Maria Vasiliki Dossis, Michael Dasygenis, Minas University of Western Macedonia Department of Electrical and Computer Engineering Kozani50131 Greece University of Piraeus Department of Digital Systems Piraeus18534 Greece

ISBN: (纸本)9798350342482

Early and accurate diagnosis of pneumonia is critical for effective treatment and improved patient outcomes. This paper introduces a cutting-edge framework for accelerating the diagnosis of pneumonia using Convolutional Neural Networks (CNNs) on heterogeneous Field-Programmable Gate Array (FPGA) systems. The framework is designed to leverage FPGAs' parallel processing capabilities and reconfigurability, enabling significant enhancements in speed and efficiency for processing medical images. Our approach involves the development of an optimized CNN model tailored to the features and characteristics typical of pneumonia in radiographic images. This model is then mapped onto an FPGA, utilizing high-level synthesis and custom hardware descriptions to maximize data throughput and minimize latency. We conducted testing using a diverse chest X-ray dataset, comparing our FPGA-based system's performance against traditional computing platforms such as GPUs and CPUs. Results indicate that our system accelerates the diagnostic process over 5 times and achieves a 97.58% accuracy rate comparable to state-of-the-art methods. The proposed framework enhances medical imaging devices' capabilities, leading to quicker diagnoses, thus reducing hospitalization time and improving patient care. © 2024 IEEE.

关键词： Digital storage

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Enhancing Early Detection of Lung Cancer through Advanced Image Processing Techniques and Deep Learning Architectures for CT Scans

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computers, Materials & Continua 2024年第10期81卷 271-307页

作者： Nahed Tawfik Heba M.Emara Walid El-Shafai Naglaa F.Soliman Abeer D.Algarni Fathi EAbd El-Samie Computers and Systems Department Electronics Research InstituteEl NozhaHuckstep Cairo12622Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Lung cancer remains a major concern in modern oncology due to its high mortality rates and multifaceted origins,including hereditary factors and various clinical *** stands as the deadliest type of cancer and a significant cause of cancer-related deaths *** diagnosis enables healthcare providers to administer appropriate treatment measures promptly and accurately,leading to improved prognosis and higher survival *** significant increase in both the incidence and mortality rates of lung cancer,particularly its ranking as the second most prevalent cancer among women worldwide,underscores the need for comprehensive research into efficient screening *** in diagnostic techniques,particularly the use of computed tomography(CT)scans,have revolutionized the identification of lung *** scans are renowned for their ability to provide high-resolution images and are particularly effective in detecting small,calcified areas,crucial for identifying earlystage lung ***,there is growing interest in enhancing computer-aided detection(CAD)*** algorithms assist radiologists by reducing false-positive interpretations and improving the accuracy of early cancer *** study aims to enhance the effectiveness of CAD systems through various ***,the Contrast Limited Adaptive Histogram Equalization(CLAHE)algorithm is employed to preprocess CT scan images,thereby improving their visual *** refinement is achieved by integrating different optimization strategies with the CLAHE *** CutMix data augmentation technique is applied to boost the performance of the proposed model.A comparative analysis is conducted using deep learning architectures such as InceptionV3,ResNet101,Xception,and *** study evaluates the performance of these architectures in image classification tasks,both with and without the implementation of the CLAHE *** empirical findings of the study demonst

关键词： Lung cancer detection CLAHE algorithm optimization deep learning classification feature extraction healthcare applications

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Logarithmic-depth quantum circuits for Hamming weight projections

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Physical Review A 2024年第5期110卷 052401页

作者： Soorya Rethinasamy Margarite L. LaBorde Mark M. Wilde School of Applied and Engineering Physics Hearne Institute for Theoretical Physics and Department of Physics and Astronomy School of Electrical and Computer Engineering

A pure state of fixed Hamming weight is a superposition of computational basis states such that each bitstring in the superposition has the same number of ones. Given a Hilbert space of the form H=(C2)⊗n, or an n-qubit system, the identity operator can be decomposed as a sum of projectors onto subspaces of fixed Hamming weight. In this work, we propose several quantum algorithms that realize a coherent Hamming weight projective measurement on an input pure state, meaning that the post-measurement state of the algorithm is the projection of the input state onto the corresponding subspace of fixed Hamming weight. We analyze a depth-width tradeoff for the corresponding quantum circuits, allowing for a depth reduction of the circuits at the cost of more control qubits. For an n-qubit input, the depth-optimal algorithm uses O(n) control qubits and the corresponding circuit has depth O(log(n)), assuming that we have the ability to perform qubit resets. Furthermore, the proposed algorithm construction uses only one- and two-qubit gates.

关键词： Quantum algorithms & computation

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Compact deep-groove-assisted bends on SiN platform for monolithic integrated laser

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Optics Express 2025年第3期33卷 4383-4395页

作者： Zhang, Ziyao Skandalos, Ilias Ma, Rui Chen, Minjia Sun, Bohao Zhong, Chuan Gardes, Frederic Cheng, Qixiang Penty, Richard Centre for Photonic Systems Electrical Engineering Division Department of Engineering University of Cambridge CambridgeCB3 0FA United Kingdom Optoelectronics Research Centre University of Southampton SouthamptonSO17 1BJ United Kingdom Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States

To build a photonic integration platform that incorporates monolithically integrated light sources which require minimized loss and reflection, a micro-meter scale passive layer is needed in addition to the III-V layer. Low temperature plasma-enhanced chemical vapor deposition (PECVD) silicon nitride (SiN) is a promising candidate, owing to its back-end-of-line (BEOL) integration capabilities, along with its amorphous structure that allows the growth of defect-free thick layers. In view of the III-V layer stack, the optimized SiN waveguides are thick and in a rib formation. However, bends on this thick SiN platform suffer from high radiation losses, resulting in the need for a bending radius as large as 800 µm that poses challenges for compact photonic integrated circuits (PICs). This paper describes and demonstrates a novel SiN bending structure with a deep etched groove along the outer side. This structure significantly reduces the bending radii to 37 µm with a bending loss of 0.1 dB/90°. A compact micro-ring resonator (MRR) with deep etched grooves is also investigated, exhibiting a substantial enhancement in the free spectral range (FSR) compared with the rib waveguide MRRs, while offering a passband of 39.1 GHz. These notable performance improvements pave the way for compact integrated emitters on a single substrate. © 2025 Optica Publishing Group (formerly OSA). All rights reserved.

关键词： Silicon nitride

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Arabic text sentiment analysis and emotion classification using transformers 11

Arabic text sentiment analysis and emotion classification us...

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11th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2023

作者： Mossad, Nada Mohamed, Youssef Fares, A. Zaky, Ahmed B. Alexandria21934 Egypt Benha University The Computer Systems Engineering Program Faculty of Engineering at Shoubra The Department of Electrical Engineering Egypt

ISBN: (纸本)9798350369328

Sentiment analysis and emotion classification are two crucial components of natural language processing (NLP), which have been widely explored in recent years due to their broad applications. Sentiment analysis aims to identify the polarity of written texts, ranging from positive to negative. Meanwhile, emotion classification is focused on recognizing and categorizing the emotional states expressed in the text. To achieve a deeper understanding of sentiments and emotions, it's essential to utilize models like BERT transformers that can effectively interpret the context. The process begins with data preprocessing, including tokenization and noise removal, followed by fine-tuning techniques to adapt the BERT model to the proposed tasks. We employed the BERT model on four datasets obtained from various sources, including Twitter, news websites, and restaurant reviews, where each dataset represents a distinct Arabic dialect. Our proposed model outperforms commonly used techniques like LSTM and CNN, yielding superior results. Despite the progress made, there are still challenges to overcome, such as dealing with Arabic diacritics, the new Arabic Arabizi, which uses Latin characters, and handling Arabic idioms. Further research is required to address these challenges adequately. © 2023 IEEE.

关键词： Sentiment analysis

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Implantable UWB Microstrip Patch Antenna for Biomedical Applications 5

Implantable UWB Microstrip Patch Antenna for Biomedical Appl...

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5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Ishraq, Sadman Imran, Md Al Alam, Khorshed Khan, Mohammad Monirujjaman North South University Department of Electrical and Computer Engineering Dhaka Bangladesh Lamar University Phillip M. Drayer Department of Electrical Engineering TX United States Lamar University Industrial and Systems Engineering Department TX United States

ISBN: (纸本)9798331530013

To satisfy the requirements of UWB (3.1-10.6 GHz), a novel implanted ultra-wideband (UWB) antenna with a frequency range of 3.07-13.7 GHz has been developed, targeting biomedical applications. The antenna's performance was analyzed at 4 GHz, 6 GHz, 8 GHz, and 10 GHz in both in-body and free-space environments to ensure optimal functionality. The primary focus of the design is to create a compact, cost-effective, and high-performance antenna tailored for medical and healthcare applications. The radiating element consists of a rectangular patch fabricated on an FR-4 substrate, with total dimensions of 30\times 27\times 1.6\ \textmm^3. A partial ground plane is incorporated to achieve ultra-wideband characteristics, enabling a 10.63 GHz bandwidth that spans frequencies from 3.07 GHz to 13.7 GHz in open space. To evaluate the antenna's performance under implantation conditions, three human tissue layers are incorporated into the design. Key features such as radiation characteristics, gain, and directivity validate its suitability for use within the human body. The entire design process, including simulations and performance evaluations, was carried out using the CST Studio Suite software. © 2024 IEEE.

关键词： Ultra-wideband (UWB)

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An Optimized Algorithm for Resource Allocation for D2D in Heterogeneous Networks

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computers, Materials & Continua 2022年第2期70卷 2923-2936页

作者： Abdul Kadir Hamid Fahd N.Al-Wesabi Nadhem Nemri Ammar Zahary Imran Khan Department of Electrical&Computer Engineering University of SharjahSharjahUnited Arab Emirates Department of Computer Science King Khalid UniversityMuhayel AseerKSA Faculty of Computer and IT Sana’a UniversitySanaaYemen Department of Information Systems King Khalid UniversityMayahel AseerKSA Department of Electrical Engineering University of Engineering and TechnologyPeshawarPaki

With the emergence of 5G mobile multimedia services,end users’demand for high-speed,low-latency mobile communication network access is *** them,the device-to-device(D2D)communication is one of the considerable *** D2D communication,the data does not need to be relayed and forwarded by the base station,but under the control of the base station,a direct local link is allowed between two adjacent mobile *** flexible communicationmode reduces the processing bottlenecks and coverage blind spots of the base station,and can be widely used in dense user communication scenarios such as heterogeneous ultra-dense wireless *** of the important factors which affects the quality-of-service(QoS)of D2D communications is co-channel *** order to solve this problem of co-channel interference,this paper proposes a graph coloring based *** main idea is to utilize the weighted priority of spectrum resources and enables multiple D2D users to reuse the single cellular user *** proposed algorithm also provides simpler power *** heterogeneous pattern of interference is determined using different types of interferences and UE and the priority of color is *** results show that the proposed algorithm effectively reduced the co-channel interference,power consumption and improved the system throughput as compared with existing algorithms.

关键词： 5G device-to-device communication wireless networks spectrum

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Monitoring of Individual Household electrical Appliances and Prediction of Energy Consumption Using Machine Learning 5

Monitoring of Individual Household Electrical Appliances and...

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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Selvam, N. Seenivasan, D. Naveen, G. Sudahar, R. Janagan, P. Dhanushmathi, S. M.Kumarasamy College of Engineering Department of Electrical and Electronics Engineering Karur India M.Kumarasamy College of Engineering Department of Computer Science and Business Systems Karur India

ISBN: (纸本)9798350385649

The study suggests a scalable method for estimating residential power usage. To increase the forecasting accuracy, an SVM (support vector machine) based technique combines many machine learning models, such as random forests, decision trees, and linear regression. Real-world data from Dutch families were used in the study, and the findings demonstrate that the suggested strategy performs better than conventional single-model techniques and attains higher accuracy in predicting energy use. The method is suited for usage in real-world applications since it is scalable and applies to huge datasets. An approach for machine learning used in load forecasting is called SVM (Support Vector Machine). Applications for long-term individual household forecasting include calculating advance payments to customers. However, there is a dearth of research on this type of forecasting;most techniques either concentrate on long-term predictions at the aggregate level or on individual family-level short-term projections. In order to close this distance, we provide a technique that uses only a few months' worth of current year's consumption data to anticipate each monthly consumption throughout the next year. Even with little data, utility suppliers may use this technique to predict any customer's consumption for the upcoming year. Data power use in the future may be predicted using linear regression. The linear regression process is used to forecast data in the future. © 2024 IEEE.

关键词： Forecasting

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