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Spectral period doubling and encoding of dissipative optical solitons via gain control

PhotoniX 2024年第1期5卷 290-305页

作者： Kangwen Yang Yi Zhou Yuqing Ling Kevin K.Tsia Heping Zeng Kenneth K.Y.Wong Shanghai Key Laboratory of Modern Optical System and Engineering Research Center of Optical Instrument and SystemMinistry of EducationSchool of Optical Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina Advanced Biomedical Instrumentation Centre Hong Kong Science ParkHong KongChina State Key Laboratory of Precision Spectroscopy East China Normal UniversityShanghai 200062China

Period-doubling bifurcation,as an intermediate state between order and chaos,is ubiquitous in all disciplines of nonlinear ***,previous experimental observations of period doubling in ultrafast fiber lasers are mainly restricted to self-sustained steady state,controllable manipulation and dynamic switching between period doubling and other intriguing dynamical states are still largely ***,we propose to expand the vision of dissipative soliton periodic doubling,which we illustrate experimentally by reporting original spontaneous,collisional,and controllable spectral period doubling in a polarization-maintaining ultrafast fiber ***,the spontaneous period doubling can be observed in both single-and *** mechanism of the switchable state and periodic doubling was revealed by numerical ***,state transformation of individual solitons can be resolved during the collision of triple solitons involving stationary,oscillating,and period ***,controllable deterministic switching between period doubling and other dynamical states,as well as exemplifying the application of period-doubling-based digital encoding,is achieved under programmable pump *** results open a new window for unveiling complex Hopf bifurcation in dissipative systems and bring useful insights into nonlinear science and applications.

关键词： Period doubling Mode locking Ultrafast fiber lasers

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Machine Learning Safety System for Treadmill Users

Machine Learning Safety System for Treadmill Users

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Natarajan, Ravishankar Yu, Xinrui Saniie, Jafar Department of Electrical and Computer Engineering Research Laboratory ChicagoIL United States

ISBN: (纸本)9781665480093

In this paper, we present an AI-based treadmill assistant that employs computer vision and Deep learning algorithms to offer a comprehensive safety net for treadmill users. The system is designed and implemented with minimal components including an off-the-shelf camera, speaker, an IoT smart plug, and Jetson Nano (a single board GPU-based embedded computing device). To provide an extensive set of safety features such as face recognition, facial stress detection, object detection, and distance and aspect measurement to the treadmill user, the system uses CNN architectures based on ResNet, MobileNet SSD, and customized fully connected neural networks. This set of features monitored in real-time will play a crucial role in mitigating treadmill user falls and injuries. © 2022 IEEE.

关键词： computer vision

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Feature Model Configuration Reuse Scheme for Self-Adaptive Systems

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computers, Materials & Continua 2022年第4期71卷 1249-1262页

作者： Sumaya Alkubaisi Said Ghoul Oguz Ata Electrical and Computer Engineering Department Altinbas UniversityIstanbul34218Turkey Faculty of Information Technology Research Laboratory on Bio-Inspired Software EngineeringPhiladelphia UniversityAmman26160Jordan

Most large-scale systems including self-adaptive systems utilize feature models(FMs)to represent their complex architectures and benefit from the reuse of commonalities and variability ***-adaptive systems(SASs)are capable of reconfiguring themselves during the run time to satisfy the scenarios of the requisite ***,reconfiguration of SASs corresponding to each adaptation of the system requires significant computational time and *** process of configuration reuse can be a better alternative to some contexts to reduce computational time,effort and ***,systems’complexity can be reduced while the development process of systems by reusing elements or *** are considered one of the new ways of reuse process that are able to introduce new opportunities for the reuse process beyond the conventional system *** current FM-based modelling techniques represent,manage,and reuse elementary features to model SASs concepts,modeling and reusing configurations have not yet been *** this context,this study presents an extension to FMs by introducing and managing configuration features and their reuse *** results demonstrate that reusing configuration features reduces the effort and time required by a reconfiguration process during the run time to meet the required scenario according to the current context.

关键词： Self-adaptive system feature model system reuse configuration management variability modeling

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Design Flow of Blowfish Symmetric-Key Block Cipher on FPGA

Design Flow of Blowfish Symmetric-Key Block Cipher on FPGA

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Palka, Piotr Perez, Rafael A. Fang, Tianyang Saniie, Jafar Department of Electrical and Computer Engineering Research Laboratory ChicagoIL United States

ISBN: (纸本)9781665480093

Cryptography is an essential topic for modern digital systems. In the past two decades, FPGA-based encryptions has proved to be effective. Through this project, we explore a cryptographic application of FPGAs by implementing the Blowfish symmetric-key block cipher on a Xilinx ZedBoard. The motivation behind this is to explore how FPGAs can be used to accelerate the performance of a symmetric-key block cipher. Our goal is to compare the performance of a hardware implementation of Blowfish to a software implementation. Our Blowfish block cipher is implemented in VHDL and is functionally verified against a Python reference model. The design as a whole supports user input of various keys for key initialization along with full encryption and decryption functionality. Furthermore, the design was successfully synthesized and implemented on the ZedBoard FPGA. A performance evaluation was conducted between the hardware implementation and a Blowfish library running in Python by comparing the time it takes to perform the key initialization and encrypt/decrypt operation. © 2022 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Autonomous Robotic Arm for Object Sorting and Motion Compensation using Kalman Filter

Autonomous Robotic Arm for Object Sorting and Motion Compens...

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Ndambani, Melanie Acelor Fang, Tianyang Saniie, Jafar Department of Electrical and Computer Engineering Research Laboratory ChicagoIL United States

ISBN: (纸本)9781665480093

Robotic arm has played a key role in the industry for more than a half-century. Although robotic arms have superior accuracy and efficiency, they are not always cost-effective, especially for small-scale applications. This paper proposes an autonomous robotic arm system that can identify, sort, and interact with different objects, using IoT devices. For precision robotic arm movement, we have developed a Kalman filter-based motion compensation system. The embedded computing system is used for real-time object recognition and motion compensation. Experimental results show that the proposed high precision autonomous robotic arm system can recognize objects with 95% accuracy, and locate and sort the moving objects with a mean error of 1.1mm. © 2022 IEEE.

关键词： Kalman filters

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Long-term radiofrequency electromagnetic fields exposure attenuates cognitive dysfunction in 5×FAD mice by regulating microglial function

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Neural Regeneration research 2023年第11期18卷 2497-2503页

作者： Yeonghoon Son Hye-Jin Park Ye Ji Jeong Hyung-Do Choi Nam Kim Hae-June Lee Division of Radiation Biomedical Research Korea Institute of Radiological&Medical SciencesSeoulKorea Department of EMF Research Team Radio and Broadcasting Technology LaboratoryElectronics and Telecommunications Research InstituteDaejonKorea School of Electrical and Computer Engineering Chungbuk National UniversityCheongjuKorea

We have previously found that long-term effects of exposure to radiofrequency electromagnetic fields in 5xFAD mice with severe late-stage Alzheimer’s disease reduced both amyloid-βdeposition and glial activation,including *** examine whether this therapeutic effect is due to the regulation of activated microglia,we analyzed mic roglial gene expression profiles and the existence of microglia in the brain in this study.5xFAD mice at the age of 1.5 months were assigned to sham-and radiofrequency electromagnetic fields-exposed groups and then animals were exposed to 1950 MHz radiofrequency electromagnetic fields at a specific absorption rate of 5 W/kg for 2 hours/day and 5 days/week for 6 *** conducted behavioral tests including the object recognition and Y-maze tests and molecular and histopathological analysis of amyloid precursor protein/a myloid-beta metabolism in brain *** confirmed that radiofrequency electromagnetic field exposure for 6 months ameliorated cognitive impairment and amyloid-β*** expression levels of Iba1(pan-microglial marker)and colony-stimulating factor 1 receptor(CSF1R;regulates microglial prolife ration)in the hippocampus in 5xFAD mice treated with radiofrequency electromagnetic fields were significantly reduced compared with those of the sham-exposed ***,we analyzed the expression levels of genes related to mic rogliosis and microglial function in the radiofrequency electromagnetic fields-exposed group compared to those of a CSF1R inhibitor(PLX3397)-treated *** radiofrequency electromagnetic fields and PLX3397 suppressed the levels of genes related to microgliosis(Csf1r,CD68,and Ccl6)and pro-inflammatory cytokine interleukin-1β.N otably,the expression levels of genes related to mic roglial function,including Trem2,Fcgr1α,Ctss,and Spi1,were decreased after long-term radiofrequency electromagnetic field exposure,which was also observed in response to microglial suppression by *** res

关键词： 5×FAD Alzheimer’s disease CSF1R long term exposure microglial function neuroinflammation radiofrequency electromagnetic fields therapeutic effect

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Image Processing for Detecting Botnet Attacks: A Novel Approach for Flexibility and Scalability

Image Processing for Detecting Botnet Attacks: A Novel Appro...

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2022 IEEE International Conference and Expo on Real Time Communications at IIT, RTC 2022

作者： Agniel, Aurelien Arnold, David Saniie, Jafar Research Laboratory Department of Electrical and Computer Engineering ChicagoIL United States

ISBN: (数字)9781665475037

ISBN: (纸本)9781665475037

Continued adoption of the Internet of Things (IoT) redefines the paradigm of network architectures. Historically, network architectures relied on centralized resources and data centers. The introduction of the IoT challenges this notion by placing computing resources and observation at the edge of the network. As a result, decentralized approaches for information processing and gathering can be adopted and explored. However, this shift greatly expands the network footprint and shifts traffic away from the center of the network, where observation and cybersecurity monitoring tools are frequently located. Further, IoT devices are often computationally constrained, limiting their readiness to deal with cyber-threats. These security vulnerabilities make the IoT an easy target for hacking groups and lead to the proliferation of zombie networks of compromised devices. Frequently, zombie networks, otherwise known as botnets, are coordinated to attack targets and overload network resources through a Distributed Denial of Service (DDoS) attack. In order to crack down on these botnets, it is essential to develop new methods for quickly and efficiently detecting botnet activity. This study proposes a novel botnet detection technique that first pre-processes network data through computer vision and image processing. The processed dataset is then sent to a neural network for final classification. Two neural networks will be explored, a sequential model and an auto-encoder model. The application of image processing has two advantages over current methods. First, the image processing is simple enough to be completed at the edge of the network by the IoT devices. Second, preprocessing the data allows us to use a shallower network, decreasing detection time further. We will utilize the N-BaIoT dataset and compare our findings to their results. © 2022 IEEE.

关键词： Cybersecurity

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PowerShell Malware Analysis Using a Novel Malware Rating System

PowerShell Malware Analysis Using a Novel Malware Rating Sys...

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Arnold, David David, Charlotte Saniie, Jafar Department of Electrical and Computer Engineering Research Laboratory ChicagoIL United States

ISBN: (纸本)9781665480093

Recent high-profile cyberattacks highlight an increased use of social engineering attacks and ransomware by hackers worldwide. These attacks target human operators directly, bypassing many of the cyber-safeguards developed through years of malware analysis. In response to these challenges, many organizations have turned to white-hat hackers and penetration testing to identify potential weaknesses and reinforce cyber-safety protocols. To assist in the threat evaluation process, malware rating systems are often used to highlight the danger and potential damage malware may cause. Current malware rating systems focus on assigning a danger score for malware based on its ability to move throughout the network, damage system resources, and evade detection. Due to the increased reliance on social engineering, a new malware rating system is proposed that incorporates malware deceitfulness as a means to trick human operators. The novel rating system will score malware based on its Stealth, Ease of Creation, Deceitfulness, Versatility, Instantaneousness, and Persistence. This system provides operators with insight into each key characteristics as opposed to a single value. To showcase the malware evaluation process, different PowerShell Reverse Bind Shell malwares are rated based on the proposed criteria. © 2022 IEEE.

关键词： Malware

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Distributed Gesture Controlled Systems for Human-Machine Interface

Distributed Gesture Controlled Systems for Human-Machine Int...

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Johnson, Hans Saniie, Jafar Department of Electrical and Computer Engineering Research Laboratory ChicagoIL United States

ISBN: (纸本)9781665480093

This paper presents the design flow of an IoT human-machine touchless interface. The device uses embedded computing in conjunction with the Leap Motion Controller to provide an accurate and intuitive touchless interface. Its main function is to augment current touchscreen devices in public spaces through a combination of computer vision technology, event-driven programming, and machine learning. Especially following the COVID-19 pandemic, this technology is important for hygiene and sanitation purposes for public devices such as airport, food, and ATM kiosks where hundreds or even thousands of people may touch these devices in a single day. A prototype of the touchless interface was designed with a Leap Motion Controller housed on a Windows PC exchanging information with a Raspberry Pi microcontroller via internet connection. © 2022 IEEE.

关键词： Internet of things

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Design Flow of mmWave Radar and Machine Vision Fusion for Pedestrian Collision Warning

Design Flow of mmWave Radar and Machine Vision Fusion for Pe...

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2022 IEEE International Conference on Electro Information Technology, eIT 2022

作者： Graves, Kaitlyn Kanwal, Madiha Yu, Xinrui Saniie, Jafar Department of Electrical and Computer Engineering Research Laboratory ChicagoIL United States

ISBN: (纸本)9781665480093

This paper presents a millimeter wave (mmWave) radar and Machine Vision fusion system to alert drivers of potential pedestrian collisions. The system is composed of two subsystems, the mmWave Pedestrian Localization subsystem and the Machine Vision Pedestrian Classification subsystem. The mmWave Pedestrian Localization subsystem obtains the relative location of the pedestrians using a mmWave radar sensor while the Machine Vision Pedestrian Classification subsystem uses Histogram of Oriented Gradients and Support Vector Machine algorithms to classify pedestrians in a camera's field-of-view. The two-layer pedestrian detection design protects the system from any miss detections within a single subsystem. By utilizing mmWave technology with Machine Vision, the safety operation of cars and pedestrian safety can be increased. The proposed system utilizes Texas Instrument's AWR1642BOOST mmWave Radar with the high computing power of NVIDIA's Jetson Nano © 2022 IEEE.

关键词： computer vision

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