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A new model to correlate solubility of drug compounds in supercritical carbon dioxide

Chemical Thermodynamics and Thermal Analysis 2025年 18卷

作者： Raghavan, Amrithaa Alwi, Ratna Surya M, Geetha Devi Garlapati, Chandrasekhar Centre for Pollution Control and Environmental Engineering Pondicherry University Puducherry 605014 India Research Center for Computing National Research and Innovation Agency (BRIN) Jl. Raya Jakarta-Bogor KM 46 Cibinong Indonesia Department of Mechanical & Industrial Engineering College of Engineering National University of Science & Technology Oman Department of Chemical Engineering Puducherry Technological University Puducherry 605014 India

A new solubility model based on enhancement factor concept is proposed to correlate solubility of drug compounds in supercritical carbon dioxide (SCCO2). The correlating ability of the new model is compared with exist... 详细信息

A new solubility model based on enhancement factor concept is proposed to correlate solubility of drug compounds in supercritical carbon dioxide (SCCO₂). The correlating ability of the new model is compared with existing solubility model. The proposed model and existing models were tested with twenty nine drug-supercritical carbon dioxide systems reported in the literature. The proposed model correlating performance is indicated in terms of absolute relative deviation percentage. Additionally, Akaike's Information Criterion (AIC) was used to assess the model's performance compared with existing solubility model. The results show the compared to existing solubility model, the proposed model accurately correlates the *** global absolute average relative deviation percentage for the existing model and proposed new model are 22.17 % and 16.11 % respectively. © 2025

关键词： Akaike's information criterion Enhancement factor Solubility Supercritical carbon dioxide

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An approach towards Model-To-Model Mapping between AUTOSAR and Android systems

An approach towards Model-To-Model Mapping between AUTOSAR a...

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Proceedings of the International Convention MIPRO

作者： Radomir Zlatković Vuk Č abrilo Marija Antić Branimir Kovač ević Department of Computing and Control Engineering Faculty of Technical Sciences University of Novi Sad RT-RK Institute for Computer Based Systems Novi Sad Serbia

ISBN: (数字)9789532331035

ISBN: (纸本)9781665484343

Every new generation of modern vehicles aims to provide the customers with a higher level of comfort and entertainment services. Consequently, the burden is placed upon the manufacturers to incorporate ever more complex electronic systems in their products and introduce service-based technologies. To meet these demands, service-oriented architecture (SOA) has become an integral part of the Adaptive AUTOSAR as the industry standard. Also, mobile services and applications are natively supported in the new in-vehicle infotainment systems (IVI) which usually run on the Android operating system. As these fundamentally different technologies are incorporated in the vehicles, the developers are facing the challenge of connecting them and exchanging information between the services running in different domains. Service-oriented architectures usually rely on a model-driven engineering approach to facilitate the development of the applications. However, as the complexity of the system grows, the mapping of various metamodels becomes a challenge, as no single standard is used across all domains in the vehicle. This paper provides a possible solution for mapping the already existing AUTOSAR metamodel to an Android Interface Definition Language (AIDL) metamodel. By applying the proposed mapping, it is possible to build applications that require the cooperation of various domains within the vehicle.

关键词： Operating systems Merging Entertainment industry Model driven engineering Generators Service-oriented architecture Complexity theory

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Bitroute SOME/IP: Implementation of a Scalable and Service Oriented Communication Middleware

Bitroute SOME/IP: Implementation of a Scalable and Service O...

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Proceedings of the International Convention MIPRO

作者： M. Vujanić N. Trifunović I. Kaš telan B. Kovač ević Department of Computing and Control Engineering Faculty of Technical Sciences University of Novi Sad RT-RK Institute for Computer Based Systems Novi Sad Serbia

ISBN: (数字)9789532331035

ISBN: (纸本)9781665484343

SOME/IP is a communication protocol introduced in automotive industry to enable Service Oriented Architecture which is not possible using traditional automotive protocols such as CAN or FlexRay. A trend emerging in the last years in the Advanced Driver Assistance Systems (ADAS) is that SOME/IP became one of main communication protocols used for communication between safety and performance ECU devices. Currently in the market, including the open-source solutions, there is a set of different SOME/IP implementations that have different audience and combination of characteristics like high royalty costs, available feature set and software solution maturity. This paper presents the Bitroute SOME/IP, a new implementation of the SOME/IP communication protocol with focus on performance and deployment platform independency and compares it with the open-source solution from The Connected Vehicle Systems Alliance (COVESA).

关键词： Performance evaluation Protocols Costs Market research Libraries Safety Service-oriented architecture

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A Dispatching Method for Integrated Energy System Based on Dynamic Time-interval of Model Predictive control

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Journal of Modern Power Systems and Clean Energy 2020年第5期8卷 841-852页

作者： Xun Dou Jun Wang Zhen Wang Lijuan Li Linquan Bai Shuhui Ren Min Gao IEEE College of Electrical Engineering and Control Science Nanjing Tech UniversityNanjingChina Department of Systems Engineering and Engineering Management University of North Carolina at CharlotteCharlotteUSA Falcon Computing Solutions 10880 Wilshire Blvd Suite 1132Los AngelesCA 90024USA

In integrated energy systems(IESs),traditional fixed time-interval dispatching scheme is unable to adapt to the need of dynamic properties of the transient network,demand response characteristics,dispatching time scales in energy subsystems and renewable power *** scheme may easily result in uneconomic source-grid-load-storage operations in *** this paper,we propose a dispatching method for IES based on dynamic time-interval of model predictive control(MPC).We firstly build models for energy sub-systems and multi-energy loads in the power-gas-heat ***,we develop an innovative optimization method leveraging trajectory deviation control,energy control,and cost control frameworks in MPC to handle the requirements and constraints over the timeinterval of ***,a dynamic programming algorithm is introduced to efficiently solve the proposed *** and simulation results prove the effectiveness of the method.

关键词： Dispatching scheme dynamic time-interval integrated energy system model predictive control

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Synthetic-to-Real Video Person Re-ID

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IEEE Transactions on Information Forensics and Security 2025年 20卷 5438-5450页

作者： Xiangqun Zhang Ruize Han Likai Wang Linqi Song Junhui Hou Wei Feng School of Computer Science and Technology College of Intelligence and Computing Tianjin University Tianjin China Shenzhen University of Advanced Technology Shenzhen China Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen China Department of Computer Science City University of Hong Kong Hong Kong Department of Computer Science City University of Hong Kong Kowloon Tong SAR Hong Kong

Person re-identification (Re-ID) is an important task and has significant applications for public security and information forensics, which has progressed rapidly with the development of deep learning. In this work, we investigate a novel and challenging setting of Re-ID, i.e., cross-domain video-based person Re-ID. Specifically, we utilize synthetic video datasets as the source domain for training and real-world videos for testing, notably reducing the reliance on expensive real data acquisition and annotation. To harness the potential of synthetic data, we first propose a self-supervised domain-invariant feature learning strategy for both static and dynamic (temporal) features. Additionally, to enhance person identification accuracy in the target domain, we propose a mean-teacher scheme incorporating a self-supervised ID consistency loss. Experimental results across five real datasets validate the rationale behind cross-synthetic-real domain adaptation and demonstrate the efficacy of our method. Notably, the discovery that synthetic data outperforms real data in the cross-domain scenario is a surprising outcome. The code and data are publicly available at https://***/XiangqunZhang/UDA_Video_ReID

关键词： Synthetic data Training Representation learning Identification of persons Data models Feature extraction Data mining Artificial intelligence Adaptation models Accuracy

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Data-Driven Predictive control for Robust Exoskeleton Locomotion

arXiv

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arXiv 2024年

作者： Li, Kejun Kim, Jeeseop Xiong, Xiaobin Hamed, Kaveh Akbari Yue, Yisong Ames, Aaron D. Department of Computation and Neural Systems Caltech PasadenaCA91125 United States Department of Mechanical and Civil Engineering Caltech PasadenaCA91125 United States Department of Mechanical Engineering University of Wisconsin-Madison MadisonWI53706 United States Department of Mechanical Engineering Virginia Tech VA24061 United States Department of Computing and Mathematical Sciences Caltech PasadenaCA91125 United States Department of Control and Dynamical Systems Caltech PasadenaCA91125 United States

Exoskeleton locomotion must be robust while being adaptive to different users with and without payloads. To address these challenges, this work introduces a data-driven predictive control (DDPC) framework to synthesize walking gaits for lower-body exoskeletons, employing Hankel matrices and a state transition matrix for its data-driven model. The proposed approach leverages DDPC through a multi-layer architecture. At the top layer, DDPC serves as a planner employing Hankel matrices and a state transition matrix to generate a data-driven model that can learn and adapt to varying users and payloads. At the lower layer, our method incorporates inverse kinematics and passivity-based control to map the planned trajectory from DDPC into the full-order states of the lower-body exoskeleton. We validate the effectiveness of this approach through numerical simulations and hardware experiments conducted on the Atalante lower-body exoskeleton with different payloads. Moreover, we conducted a comparative analysis against the model predictive control (MPC) framework based on the reduced-order linear inverted pendulum (LIP) model. Through this comparison, the paper demonstrates that DDPC enables robust bipedal walking at various velocities while accounting for model uncertainties and unknown perturbations. © 2024, CC BY.

关键词： Inverse kinematics

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Autonomous navigation of a tracked unmanned ground vehicle*

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IFAC-PapersOnLine 2022年第14期55卷 120-125页

作者： Marija Seder Anđela Jurić Ana Šelek Filip Marić Marija Lovrić Ivan Petrović University of Zagreb Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Laboratory for Autonomous Systems and Mobile Robotics (LAMOR) Zagreb Croatia University of Zagreb Croatian Military Academy Dr. Franjo Tuđman Zagreb Croatia

This work proposes a complete autonomous navigation system for a tracked vehicle. The system enables a complete autonomous execution of waypoint and patrolling tasks selected by the user. It also enables user-vehicle shared autonomy, switching between the user teleoperation and the vehicle autonomous operation. Our navigation system uses the model predictive control scheme based on a navigation function. We propose the navigation function which takes into account changing environments, any-shape footprint, and non-holonomic motion of the tracked vehicle. Besides the waypoint and patrolling tasks, we implemented a fail-safe scenario in case of the user-vehicle communication loss, in which the vehicle returns autonomously to the previously visited goal where the communication was stable. The efficiency of the proposed system is validated by experimental results on the Komodo tracked vehicle.

关键词： Robot navigation path planning obstacle detection avoidance motion control map building

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PCE-GAN: A Generative Adversarial Network for Point Cloud Attribute Quality Enhancement based on Optimal Transport

arXiv

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arXiv 2025年

作者： Guo, Tian Yuan, Hui Liu, Qi Su, Honglei Hamzaoui, Raouf Kwong, Sam School of Control Science and Engineering Shandong University Jinan250061 China Key Laboratory of Machine Intelligence and System Control Ministry of Education Ji’nan250061 China School of Electronic Information Qingdao University Qingdao266071 China School of Engineering and Sustainable Development De Montfort University LeicesterLE1 9BH United Kingdom Department of Computing and Decision Science Lingnan University Hong Kong

Point cloud compression significantly reduces data volume but sacrifices reconstruction quality, highlighting the need for advanced quality enhancement techniques. Most existing approaches focus primarily on point-to-point fidelity, often neglecting the importance of perceptual quality as interpreted by the human visual system. To address this issue, we propose a generative adversarial network for point cloud quality enhancement (PCE-GAN), grounded in optimal transport theory, with the goal of simultaneously optimizing both data fidelity and perceptual quality. The generator consists of a local feature extraction (LFE) unit, a global spatial correlation (GSC) unit and a feature squeeze unit. The LFE unit uses dynamic graph construction and a graph attention mechanism to efficiently extract local features, placing greater emphasis on points with severe distortion. The GSC unit uses the geometry information of neighboring patches to construct an extended local neighborhood and introduces a transformer-style structure to capture long-range global correlations. The discriminator computes the deviation between the probability distributions of the enhanced point cloud and the original point cloud, guiding the generator to achieve high quality reconstruction. Experimental results show that the proposed method achieves state-of-the-art performance. Specifically, when applying PCE-GAN to the latest geometry-based point cloud compression (G-PCC) test model, it achieves an average BD-rate of -19.2% compared with the PredLift coding configuration and -18.3% compared with the RAHT coding configuration. Subjective comparisons show a significant improvement in texture clarity and color transitions, revealing finer details and more natural color gradients. Copyright © 2025, The Authors. All rights reserved.

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Autonomous On-ramp Merge Strategy Using Deep Reinforcement Learning in Uncertain Highway Environment

Autonomous On-ramp Merge Strategy Using Deep Reinforcement L...

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2022 IEEE International Conference on Unmanned Systems, ICUS 2022

作者： Wu, Sifan Tian, Daxin Zhou, Jianshan Duan, Xuting Sheng, Zhengguo Zhao, Dezong Beijing Key Laboratory For Cooperative Vehicle Infrastructure Systems&Safety Cooperative Control Beijing China Beijing Advanced Innovation Center For Big Data and Brain Computing Beijing China Department of Engineering and Design Richmond United Kingdom University of Sussex Richmond United Kingdom James Watt School of Engineering Glasgow United Kingdom University of Glasgow Glasgow United Kingdom

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

On-ramp merge is a complex traffic scenario in autonomous driving. Because of the uncertainty of the driving environment, most rule-based models cannot solve such a problem. In this study, we design a Deep Reinforcement Learning (DRL) method to solve the issue of ramp merges in uncertain scenarios and modify the structure of the Twin Delayed Deep Deterministic policy gradient algorithm (TD3), using Long Short-Term Memory (LSTM) to select an action based on temporal information. The proposed method is applied in the on-ramp merge and verified in the Simulation of Urban Mobility (SUMO). Results show that the proposed method performs significantly better generalization in uncertain traffic scenarios. © 2022 IEEE.

关键词： Long short-term memory

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Adjusted and controllability Properties of Memristor Rucklidge System

Adjusted and Controllability Properties of Memristor Rucklid...

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2023 IEEE International Conference on Memristive computing and Applications, ICMCA 2023

作者： Zang, Hongyan Huang, Lili Zhang, Shourong Joseph, Annie Anak Fu, Haiyan Lei, Tengfei Qilu Institute of Technology Collaborative Innovation Center of Memristive Computing Application Jinan250200 China Universiti Malaysia Sarawak Faculty of Engineering Kota Samarahan Sarawak Malaysia College of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan250200 China Shandong Vanform High Energy Physics Technology Co. Ltd. Jinan250100 China Universiti Malaysia Sarawak Department of Electrical and Electronics Kota Samarahan Sarawak Malaysia College of Computer and Information Engineering Qilu Institute of Technology Jinan250200 China Jinan250200 China

ISBN: (纸本)9798350316230

There are many models of memristors, but there are no reports on exponential memristors. In this paper, a three- dimension memristor Rucklidge system with exponential memristor is proposed by introducing exponential function and constructing exponential memristor. The dynamic behavior of the system is analyzed by means of Lyapunov exponent and bifurcation diagram. The complex attractor coexistence and amplitude modulation characteristics of the system are found. The internal variable of memristor is introduced into the second two-dimensional equation as a feedback term, and a conditional symmetric system is constructed for the three-dimensional memristor system, which can realize the polarity control of output signal. By discussing the dynamic characteristics of exponential memristor chaotic system and the control mechanism of amplitude modulation, bias and conditional symmetry, the complex dynamic characteristics of exponential function memristor are revealed, which lays a foundation for its application in the field of secure communication. © 2023 IEEE.

关键词： Memristors

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