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Automated desktop wiring of micromodular electronic systems with submicron electrohydrodynamic jet printed interconnects

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Additive Manufacturing 2025年 109卷

作者： Kaifan Yue Rebecca K. Banner Siddharth Kurup Hubert N. Elly Eric M. Vogel Michael A. Filler Kira Barton Robotics Department University of Michigan Ann Arbor 48105 MI United States School of Materials Science and Engineering Georgia Institute of Technology Atlanta 30332 GA United States School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta 30332 GA United States School of Chemical and Biomolecular Engineering Georgia Institute of Technology Atlanta 30332 GA United States

Wiring microscale modular electrical components into functional circuits presents significant challenges in fabricating high-resolution interconnects through contactless, maskless processes and aligning them reliably with imprecisely placed components. This work introduces an integrated, desktop-scale process flow for assembling high-performance micromodular electronic systems, by synergistically combining: (1) modularized components for seamless electrical interconnection under ambient conditions, (2) vision-assisted adaptive routing to compensate for irregular placement and orientation, and (3) electrohydrodynamic jet printing for submicron-resolution interconnect fabrication. Physical interface requirements (e.g., approach angle, overlay count, continuation length, and deviation tolerance) and process constraints (e.g., nozzle idle time, crosstalk spacing, and stage acceleration limits) are embedded directly into routing algorithms to ensure reliable, high-quality interconnect formation. Statistical evaluation demonstrates high routing feasibility and runtime efficiency across varying circuit complexities and layout conditions. Experimental validation using micromodular n-MOSFETs as building blocks successfully assembled transistor test structures and depletion-load nMOS inverters, achieving 650 nm interconnect resolution, 82% device-level yield, and excellent transistor characteristics including sub-1 V threshold voltages and electron mobilities exceeding 600 cm 2 /(V ⋅ s). This adaptive, process-aware routing framework advances the integration of additive manufacturing and modular microelectronics, paving the way for scalable, robust, and highly customizable electronic systems.

关键词： Adaptive circuit routing Modular electronic system E-jet printing High-resolution interconnect Process automation

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Asymmetric Transfer Hashing with Adaptive Bipartite Graph Learning

arXiv

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arXiv 2022年

作者： Lu, Jianglin Zhou, Jie Chen, Yudong Pedrycz, Witold Hung, Kwok-Wai The College of Computer Science and Software Engineering Shenzhen University Guangdong Shenzhen518060 China Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States The College of Computer Science and Software Engineering Shenzhen University SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Guangdong Shenzhen518060 China The School of Information Technology and Electrical Engineering University of Queensland BrisbaneQLD4072 Australia The Department of Electrical & Computer Engineering University of Alberta Edmonton Canada The Systems Research Institute Polish Academy of Sciences Warsaw Poland Tencent Music Entertainment Guangdong Shenzhen518060 China

Thanks to the efficient retrieval speed and low storage consumption, learning to hash has been widely used in visual retrieval tasks. However, the known hashing methods assume that the query and retrieval samples lie in homogeneous feature space within the same domain. As a result, they cannot be directly applied to heterogeneous cross-domain retrieval. In this paper, we propose a Generalized Image Transfer Retrieval (GITR) problem, which encounters two crucial bottlenecks: 1) the query and retrieval samples may come from different domains, leading to an inevitable domain distribution gap;2) the features of the two domains may be heterogeneous or misaligned, bringing up an additional feature gap. To address the GITR problem, we propose an Asymmetric Transfer Hashing (ATH) framework with its unsupervised/semi-supervised/supervised realizations. Specifically, ATH characterizes the domain distribution gap by the discrepancy between two asymmetric hash functions, and minimizes the feature gap with the help of a novel adaptive bipartite graph constructed on cross-domain data. By jointly optimizing asymmetric hash functions and the bipartite graph, not only can knowledge transfer be achieved but information loss caused by feature alignment can also be avoided. Meanwhile, to alleviate negative transfer, the intrinsic geometrical structure of single-domain data is preserved by involving a domain affinity graph. Extensive experiments on both single-domain and cross-domain benchmarks under different GITR subtasks indicate the superiority of our ATH method in comparison with the state-of-the-art hashing methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Hash functions

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DIMENSION-FREE INEQUALITIES FOR LOW AND HIGH DEGREE FUNCTIONS ON THE HAMMING CUBE

arXiv

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arXiv 2024年

作者： Domelevo, Komla Durcik, Polona Fragkiadaki, Valentia Klein, Ohad Oliveira E Silva, Diogo Slavíková, Lenka Wróbel, Blażej Faculty of Mathematics and Computer Science Institute of Mathematics Emil-Fischer-Str. 41 Würzburg97074 Germany Schmid College of Science and Technology Chapman University One University Drive OrangeCA92866 United States Department of Mathematics Texas A&M University College station TX77843 United States School of Computer Science and Engineering Hebrew University of Jerusalem Jerusalem Israel Center for Mathematical Analysis Geometry and Dynamical Systems Departamento de Matemática Instituto Superior Técnico Av. Rovisco Pais Lisboa1049-001 Portugal Department of Mathematical Analysis Faculty of Mathematics and Physics Charles University Sokolovská 83 Praha 8186 75 Czech Republic Institute of Mathematics of the Polish Academy of Sciences Śniadeckich 8 Warsaw00-656 Poland Institute of Mathematics University of Wroclaw Plac Grunwaldzki 2 Wroclaw50-384 Poland

We prove two types of optimal dimension-free Lp inequalities, 1 0 and k ∈ N, and any function f with spectrum bounded from below by d satisfies the upper bound on the decay of the heat semigroup (Equation presented), for any t, Ε > 0. Here, Q(f) denotes the quotient between the largest and smallest non-zero values of f, and the constants c(p, Ε) and C(p, Ε) depend only on p and Ε;crucially, they are independent of the dimension n. In particular, if f is Boolean-valued or f: {−1, 1}n → {−1, 0, 1}, then the bounds we obtain are independent of Q(f). We also provide counterexamples at the endpoint p = ∞, for which a linear growth in d does not suffice when k = *** Codes Primary 42C10, Secondary 41A17, 41A63, 47A60 © 2024, CC BY.

关键词： geometry

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Probabilistic mixture-of-experts for efficient deep reinforcement learning

arXiv

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arXiv 2021年

作者： Ren, Jie Li, Yewen Ding, Zihan Pan, Wei Dong, Hao CFCS Computer Science Department Peking University Beijing China School of Electronic Engineering Xidian University Xián China Princeton University Princeton United States Department of Cognitive Robotics Delft University of Technology Delft Netherlands

Deep reinforcement learning (DRL) has successfully solved various problems recently, typically with a unimodal policy representation. However, grasping distinguishable skills for some tasks with non-unique optima can be essential for further improving its learning efficiency and performance, which may lead to a multimodal policy represented as a mixture-of-experts (MOE). To our best knowledge, present DRL algorithms for general utility do not deploy this method as policy function approximators due to the potential challenge in its differentiability for policy learning. In this work, we propose a probabilistic mixture-of-experts (PMOE) implemented with a Gaussian mixture model (GMM) for multimodal policy, together with a novel gradient estimator for the indifferentiability problem, which can be applied in generic off-policy and on-policy DRL algorithms using stochastic policies, e.g., Soft Actor-Critic (SAC) and Proximal Policy Optimisation (PPO). Experimental results testify the advantage of our method over unimodal polices and two different MOE methods, as well as a method of option frameworks, based on the above two types of DRL algorithms, on six MuJoCo tasks. Different gradient estimations for GMM like the reparameterisation trick (Gumbel-Softmax) and the score-ratio trick are also compared with our method. We further empirically demonstrate the distinguishable primitives learned with PMOE and show the benefits of our method in terms of exploration. © 2021, CC BY.

关键词： Deep learning

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Continuous-time fitted value iteration for robust policies

arXiv

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arXiv 2021年

作者： Lutter, Michael Belousov, Boris Mannor, Shie Fox, Dieter Garg, Animesh Peters, Jan Intelligent Autonomous Systems group Computer Science Department Technical University of Darmstadt Darmstadt Germany Andrew and Erna Viterbi Faculty of Electrical & Computer Engineering Technion – Israel Institute of Technology and a Distinguished Scientist at NVIDIA Tel Aviv Israel Allen School of Computer Science & Engineering University of Washington and Senior Director of Robotics Research NVIDIA Washington Seattle United States Computer Science Department University of Toronto NVIDIA Toronto Canada

Solving the Hamilton-Jacobi-Bellman equation is important in many domains including control, robotics and economics. Especially for continuous control, solving this differential equation and its extension the Hamilton-Jacobi-Isaacs equation, is important as it yields the optimal policy that achieves the maximum reward on a give task. In the case of the Hamilton-Jacobi-Isaacs equation, which includes an adversary controlling the environment and minimizing the reward, the obtained policy is also robust to perturbations of the dynamics. In this paper we propose continuous fitted value iteration (cFVI) and robust fitted value iteration (rFVI). These algorithms leverage the non-linear control-affine dynamics and separable state and action reward of many continuous control problems to derive the optimal policy and optimal adversary in closed form. This analytic expression simplifies the differential equations and enables us to solve for the optimal value function using value iteration for continuous actions and states as well as the adversarial case. Notably, the resulting algorithms do not require discretization of states or actions. We apply the resulting algorithms to the Furuta pendulum and cartpole. We show that both algorithms obtain the optimal policy. The robustness Sim2Real experiments on the physical systems show that the policies successfully achieve the task in the real-world. When changing the masses of the pendulum, we observe that robust value iteration is more robust compared to deep reinforcement learning algorithm and the non-robust version of the algorithm. Videos of the experiments are shown at https://***/view/rfvi Copyright © 2021, The Authors. All rights reserved.

关键词： Dynamic programming

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An efficient and adaptable multimedia system for converting PAL to VGA in real-time video processing

An efficient and adaptable multimedia system for converting ...

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作者： Jain, Deepak Kumar Jacob, Sunil Alzubi, Jafar Menon, Varun Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing College of Automation Chongqing University of Posts and Telecommunications Chongqing400065 China Center for Robotics SCMS School of Engineering and Technology Kerala683576 India School of Engineering Al-Balqa Applied University Salt19117 Jordan Department of Computer Science and Engineering SCMS School of Engineering and Technology Kerala683576 India

Real-time video processing has found its range of applications from defense to consumer electronics for surveillance, video conferencing, etc. With the advent of Field Programmable Gate Arrays (FPGAs), flexible real-time video processing systems which can meet hard real-time constraints are easily realized with short development time. Most of the existing solutions have high utilization of system resources and are not quite flexible with many applications. Here we propose a hardware–software co-design for an FPGA-based real-time video processing system to convert video in standard Phase Alternating Line (PAL) 576i format to standard video of Video Graphics Array (VGA)/Super Video Graphics Array (SVGA) format with little utilization of resources. Switching between multiple video streams, character/text overlaying, and skin color detection are also incorporated with the system. The system is also adaptable for rugged applications. VHSIC Hardware Description Language (VHDL) codes for the architecture were synthesized using Altera Quartus II and targeted for Altera Stratix I FPGA. Results achieved confirm that the proposed system performs efficient conversion with very less resource utilization compared to the existing solutions. Since the proposed system is also flexible, many other applications can be incorporated in the future. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Field programmable gate arrays (FPGA)

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An efficient artificial intelligence approach for early detection of cross-site scripting attacks

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Decision Analytics Journal 2024年 11卷

作者： Younas, Faizan Raza, Ali Thalji, Nisrean Abualigah, Laith Zitar, Raed Abu Jia, Heming Department of Computer Science & Information Technology The University Of Lahore Lahore 54000 Pakistan Department of Software Engineering The University Of Lahore Lahore 54000 Pakistan Department of Robotics and Artificial Intelligence Jadara University Irbid Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan Computer Science Department Al al-Bayt University Mafraq 25113 Jordan Artificial Intelligence and Sensing Technologies (AIST) Research Center University of Tabuk Tabuk 71491 Saudi Arabia MEU Research Unit Middle East University Amman 11831 Jordan Applied science research center Applied science private university Amman 11931 Jordan School of Engineering and Technology Sunway University Malaysia Petaling Jaya 27500 Malaysia Sorbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi Abu Dhabi 38044 United Arab Emirates School of Information Engineering Sanming University Sanming 365004 China

Cross-Site Scripting (XSS) attacks continue to pose a significant threat to web applications, compromising the security and integrity of user data. XSS is a web application vulnerability where malicious scripts are injected into websites, allowing attackers to execute arbitrary code in the victim's browser. The consequences of XSS attacks can be severe, ranging from financial losses to compromising sensitive user information. XSS attacks enable attackers to deface websites, distribute malware, or launch phishing campaigns, compromising the trust and reputation of affected organizations. This study proposes an efficient artificial intelligence approach for the early detection of XSS attacks, utilizing machine learning and deep learning approaches, including Long Short-Term Memory (LSTM). Additionally, advanced feature engineering techniques, such as the Term Frequency-Inverse Document Frequency (TFIDF), are applied and compared to evaluate results. We introduce a novel approach named LSTM-TFIDF (LSTF) for feature extraction, which combines temporal and TFIDF features from the cross-site scripting dataset, resulting in a new feature set. Extensive research experiments demonstrate that the random forest method achieved a high performance of 0.99, outperforming state-of-the-art approaches using the proposed features. A k-fold cross-validation mechanism is utilized to validate the performance of applied methods, and hyperparameter tuning further enhances the performance of XSS attack detection. We have applied Explainable Artificial Intelligence (XAI) to understand the interpretability and transparency of the proposed model in detecting XSS attacks. This study makes a valuable contribution to the growing body of knowledge on XSS attacks and provides an efficient model for developers and security practitioners to enhance the security of web applications. © 2024 The Author(s)

关键词： Artificial intelligence Cross-site scripting attacks Deep learning Feature engineering Feature fusion Machine learning

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通用最优轨迹规划——基于最小作用量原理实现自动驾驶（英文）

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Engineering 2024年第2期 63-76页

作者： Heye Huang Yicong Liu Jinxin Liu Qisong Yang Jianqiang Wang David Abbink Arkady Zgonnikov School of Vehicle and Mobility Tsinghua University Department of Cognitive Robotics Faculty of Mechanical Maritime and Materials Engineering (3mE) Delft University of Technology Department of Software Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Xi'an Institute of High-Technology

This study presents a general optimal trajectory planning(GOTP) framework for autonomous vehicles(AVs) that can effectively avoid obstacles and guide AVs to complete driving tasks safely and ***,we employ the fifth-order Bezier curve to generate and smooth the reference path along the road *** coordinates are then transformed to achieve the curvature continuity of the generated *** the road constraints and vehicle dynamics,limited polynomial candidate trajectories are generated and smoothed in a curvilinear coordinate ***,in selecting the optimal trajectory,we develop a unified and auto-tune objective function based on the principle of least action by employing AVs to simulate drivers' behavior and summarizing their manipulation characteristics of "seeking benefits and avoiding losses." Finally,by integrating the idea of receding-horizon optimization,the proposed framework is achieved by considering dynamic multi-performance objectives and selecting trajectories that satisfy feasibility,optimality,and *** simulations and experiments are performed,and the results demonstrate the framework's feasibility and effectiveness,which avoids both dynamic and static obstacles and applies to various scenarios with multisource interactive traffic ***,we prove that the proposed method can guarantee real-time planning and safety requirements compared to drivers' manipulation.

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Sparse decomposition of pressure pulse wave signal based on time frequency analysis

Sparse decomposition of pressure pulse wave signal based on ...

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International Conference on Intelligent Informatics and Biomedical sciences (ICIIBMS)

作者： Zhixing Jiang Guangming Lu David Zhang School of Computer Science and Technology Harbin Institute of Technology Shenzhen Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China

ISBN: (数字)9781728180229

ISBN: (纸本)9781728180236

In traditional Chinese medicine (TCM), wrist pulse is of great significance to help doctors in diagnosis. With the development of sensing technology, the computerized wrist pulse analysis has been attracting more attention in modern medicine for its non-invasive and convenient. Considering the TCM pulse diagnosis theory, it is necessary to develop effective feature extraction methods for computerized diagnosis. In this paper, we decompose the pressure pulse waveform of the radial artery to several components by sparse decomposition with Gabor function. In order to better represent the pulse waveform signal, we use an Gabor function based on the characteristics of the pulse waveform to generate a time-frequency dictionary. Compared with the conventional representation methods, the shape of the Gabor function is more variable, which can better represent both the contour and specific peaks. In addition, due to the limitation of the windowing, the Gabor function can reduce the influence on other positions when representing specific position. The feature vector composed of the decomposed components can be used for the computerized pulse signal analysis and disease diagnosis. The experimental results show that the proposed method can exhibit superior performance in distinguishing between the signals collected from patients and healthy individuals.

关键词： Wrist Time-frequency analysis Dictionaries Shape Physiology Sensors Signal analysis

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On Session Continuation among Slices for Inter-Slice Mobility Support in 3GPP Service-based Architecture

arXiv

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arXiv 2020年

作者： Sajjad, Muhammad Mohtasim Jayalath, Dhammika Tian, Yu-Chu Bernardos, Carlos J. School of Electrical Engineering and Robotics School of Computer Science Queensland University of Technology Brisbane Australia Universidad Carlos III de Madrid Spain

The 3GPP has provided its first standard specifications for network slicing in the recent Release 15. The fundamental principles are specified which constitute the standard network slicing framework. These specifications, however, lack the session continuation mechanisms among slices, which is a fundamental requirement to achieve inter-slice mobility. In this paper, we propose three solutions which enable session continuation among slices in the current 3GPP network slicing framework. These solutions are based on existing, well-established standard mechanisms. The first solution is based on the Return Routability/Binding Update (RR/BU) procedure of the popular Internet standard, Mobile IPv6 (MIPv6). The second solution is based on the 3GPP standard GPRS Tunnelling Protocol User Plane (GTPv1-U), which establishes a GTP tunnel between previous and new slice for session continuation. The third solution is a hybrid solution of both MIPv6-RR/BU and GTPv1-U protocols. We compare the performance of all these solutions through analytical modelling. Results show that the GTPv1-U based and the hybrid MIPv6/GTPv1-U solutions promise lower service disruption latency, however, incur higher resource utilization overhead compared to MIPv6-RR/BU and 3GPP standard PDU Session Establishment process. Copyright © 2020, The Authors. All rights reserved.

关键词： Standardization

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