Type-2 Fuzzy Control for Driving State and Behavioral Decisions of Unmanned Vehicle

In this paper, interval type-2 fuzzy sets, fuzzy comprehensive evaluation and the fuzzy control rules are synthesized to realize the control of unmanned vehicle in driving state and behavioral decisions. Compared to the type-1 fuzzy set, type-2 fuzzy sets have more advantages in handling the model based on uncertainties, linguistic information because the membership functions are fuzzy sets. Different membership functions are established for each factor when the unmanned vehicle is driving at different speed intervals. In addition, a new evaluation method is developed to analyze unmanned vehicle’s driving state. Finally, a set of dynamic fuzzy rules are sorted out, which can be applied to the unmanned vehicle’s behavioral decision-making and provide a new idea to related research.

Mechanical suppression of breast cancer cell invasion and paracrine signaling to osteoclasts requires nucleo-cytoskeletal connectivity

Exercise benefits the musculoskeletal system and reduces the effects of cancer.The effects of exercise are multifactorial,where metabolic changes and tissue adaptation influence outcomes.Mechanical signals,a principal component of exercise,are anabolic to the musculoskeletal system and restrict cancer progression.We examined the mechanisms through which cancer cells sense and respond to low-magnitude mechanical signals introduced in the form of vibration.Low-magnitude,high-frequency vibration was applied to human breast cancer cells in the form of low-intensity vibration(LIV).LIV decreased matrix invasion and impaired secretion of osteolytic factors PTHLH,IL-11,and RANKL.Furthermore,paracrine signals from mechanically stimulated cancer cells,reduced osteoclast differentiation and resorptive capacity.Disconnecting the nucleus by knockdown of SUN1 and SUN2 impaired LIV-mediated suppression of invasion and osteolytic factor secretion.LIV increased cell stiffness;an effect dependent on the LINC complex.These data show that mechanical vibration reduces the metastatic potential of human breast cancer cells,where the nucleus serves as a mechanosensory apparatus to alter cell structure and intercellular signaling.

Standardized Evaluation of Camera-based Driver State Monitoring Systems

Driver state sensing technologies, such as vehicular systems, start to be widely considered by automotive manufacturers. To reduce the cost and minimize the intrusiveness towards driving, the majority of these systems rely on the in-cabin camera(s) and other optical sensors. With their great capabilities in detecting and intervening of driver distraction and inattention,these technologies may become key components in future vehicle safety and control systems. However, to the best of our knowledge,currently, there is no common standard available to objectively compare the performance of these technologies. Thus, it is imperative to develop one standardized process for evaluation purposes.In this paper, we propose one systematic and standardized evaluation process after successfully addressing three difficulties:1) defining and selecting the important influential individual and environmental factors, 2) countering the effects of individual differences and randomness in driver behaviors, and 3) building a reliable in-vehicle driver head motion tracking tool to collect ground-truth motion data. We have collected data on a large scale on a commercial driver state-sensing platform. For each subject, 30 to 40 minutes of head motion data was collected and included variables, such as lighting conditions, head/face features,and camera locations. The collected data was analyzed based on a proposed performance measure. The results show that the developed process can efficiently evaluate an individual camerabased driver state sensing product, which builds a common base for comparing the performance of different systems.

Preparation and evaluation of a novel antibacterial glass-ionomer cement

A novel antibacterial glass-ionomer cement has been developed. Compressive strength (CS) and S. mutans viability were used to evaluate the mechanical strength and antibacterial activity of the formed cement. Compressive yield strength (YS), modulus (M), diametral tensile strength (DTS) and flexural strength (FS) were also determined. All the formulated antibacterial cements showed a significant antibacterial activity, accompanying with an initial CS reduction. The effect of the synthesized antibacterial polymer loading was significant. Increasing loading from 1% to 20% significantly decreased the S. mutans viability from 3% to 50% and also reduced the initial CS (325 MPa) of the formed cements from 19% to 75%. The cement with 5% antibacterial polymer loading showed 142 MPa, 6.9 GPa, 224 MPa, 52 MPa, and 62 MPa in YS, M, CS, DTS and FS, respectively, as compared to 170, 7.1, 325, 60 and 87 for the experimental cement without antibacterial polymer addition and 141, 6.9, 236, 42 and 53 for Fuji II LC. It was also found that the chlorine-containing antibacterial cement showed better CS values than the bromine-containing cement, with no significant difference in antibacterial activity. The antibacterial cement also showed a similar antibacterial activity to Streptococcus mutans, lactobacillus, Staphylococcus aureus and Staphylococcus epidermidis. The human saliva did not affect the antibacterial activity of the cement. The thirty-day aging study indicates that the cements may have a long-lasting antibacterial function.

Automation 5.0: The Key to Systems Intelligence and Industry 5.0

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with machinery.The rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:L.Vlacic,H.Huang,M.Dotoli,Y.Wang,P.Ioanno,L.Fan,X.Wang,R.Carli,C.Lv,L.Li,X.Na,Q.-L.Han,and F.-Y.Wang,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA J.Autom.Sinica,vol.11,no.8,pp.1723-1727,Aug.2024.

A Survey of Model Predictive Control Methods for Traffic Signal Control

Enhancing traffic efficiency and alleviating(even circumventing) traffic congestion with advanced traffic signal control(TSC) strategies are always the main issues to be addressed in urban transportation systems. Since model predictive control(MPC) has a lot of advantages in modeling complex dynamic systems, it has been widely studied in traffic signal control over the past 20 years. There is a need for an in-depth understanding of MPC-based TSC methods for traffic networks. Therefore, this paper presents the motivation of using MPC for TSC and how MPC-based TSC approaches are implemented to manage and control the dynamics of traffic flows both in urban road networks and freeway networks. Meanwhile, typical performance evaluation metrics, solution methods, examples of simulations,and applications related to MPC-based TSC approaches are reported. More importantly, this paper summarizes the recent developments and the research trends in coordination and control of traffic networks with MPC-based TSC approaches. Remaining challenges and open issues are discussed towards the end of this paper to discover potential future research directions.

Enhanced Ionic Accessibility of Flexible MXene Electrodes Produced by Natural Sedimentation

MXene nanosheets have been used for preparing highly flexible integrated electrodes due to their two-dimensional(2D)morphology,flexibility,high conductivity,and abundant functional groups.However,restacking of 2D nanosheets inhibits the ion transport in MXene electrodes,limiting their thickness,rate performance,and energy storage capacity.Here,we employed a natural sedimentation method instead of the conventional vacuum-assisted filtration to prepare flexible Ti3C2TxMXene films with enlarged interlayer spacing,which facilitates the access of the lithium ions to the interlayers and thus leads to a greatly enhanced electrochemical performance.The naturally sedimented flexible film shows a double lithium storage capacity compared to the conventional vacuum-filtered MXene film,along with improved rate performance and excellent cycle stability.

ACP-based social computing and parallel intelligence： Societies 5.0 and beyond

Social computing, as the technical foundation of future computational smart societies, has the potential to improve the effectiveness of opensource big data usage, systematically integrate a variety of elements including time, human, resources, scenarios, and organizations in the current cyber-physical-social world, and establish a novel social structure with fair information, equal rights, and a flat configuration. Meanwhile, considering the big modeling gap between the model world and the physical world, the concept of parallel intelligence is introduced. With the help of software-defined everything, parallel intelligence bridges the big modeling gap by means of constructing artificial systems where computational experiments can be implemented to verify social policies, economic strategies, and even military operations. Artificial systems play the role of ＂social laboratories＂ in which decisions are computed before they are executed in our physical society. Afterwards, decisions with the expected outputs are executed in parallel in both the artificial and physical systems to interactively sense, compute, evaluate and adjust system behaviors in real-time, leading system behaviors in the physical system converging to those proven to be optimal in the artificial ones. Thus, the smart guidance and management for our society can be achieved.

Poly(ethylene glycol) and poly(N-vinlypyrrolidone) for improved porcine islet cryopreservation

Water-soluble polymers poly(ethylene glycol) (PEG) and poly(N-vinylpyrrolidone) (PVP) were used to study cryopreservation of porcine islets. DMSO was used as control. The effects of polymer purity, molecular weight (MW) and concentration on islet viability were investigated. The results show that both PVP and PEG are good cyroprotectant candidates for islet cryopreservation. The effects of polymer purity and concentration were significant. Increasing concentration significantly increased the islet viability. However, after the concentration reached a certain level, there was no significant difference in viability probably due to increased viscosity of the polymer solution. The effect of polymer MW was not significant. It is concluded that polymers can be a suitable cryoprotectant for porcine islet cryopreservation. The islet viability is polymer concentration-dependent. It seems that PVP is a better cryoprotectant candidate as compared to PEG because the former showed a fast dissolution rate in culture medium and lower viscosity. The polymer concentration at 30% appears to be the optimal for cryopreservation from the viewpoint of islet viability and medium viscosity.

Smartphone Based Fall Detection and Logic Testing Application Using Android SDK

Smart systems aimed at detecting the fall of a person have increased significantly due to recent technological advances and availability of modular electronics. This work presents the use of embedded accelerometer and gyroscope in mobile phones to accurately detect and classify the type of fall a person is experiencing before suffering an impact. Early classification of fall type helps in optimizing the algorithm of the fall detection. User acceptance, feasibility and the limitations in the accuracy of the existing devices have also been considered in this study. High efficiency and low power approaches were emphasized with wireless capability that enhanced the system performance for variety of applications. There is a need of reducing the time for analyzing the smart algorithms designed. It is also emphasized that this application will be a good platform that can be used to test various algorithms and multiple sensors at a time with ease and obtain data analysis in a short period.

Point Cloud Classification Using Content-Based Transformer via Clustering in Feature Space

Recently, there have been some attempts of Transformer in 3D point cloud classification. In order to reduce computations, most existing methods focus on local spatial attention,but ignore their content and fail to establish relationships between distant but relevant points. To overcome the limitation of local spatial attention, we propose a point content-based Transformer architecture, called PointConT for short. It exploits the locality of points in the feature space(content-based), which clusters the sampled points with similar features into the same class and computes the self-attention within each class, thus enabling an effective trade-off between capturing long-range dependencies and computational complexity. We further introduce an inception feature aggregator for point cloud classification, which uses parallel structures to aggregate high-frequency and low-frequency information in each branch separately. Extensive experiments show that our PointConT model achieves a remarkable performance on point cloud shape classification. Especially, our method exhibits 90.3% Top-1 accuracy on the hardest setting of ScanObjectN N. Source code of this paper is available at https://github.com/yahuiliu99/PointC onT.

粒子群优化方法在动态优化中的研究现状

作为一种基于群智能的并行随机优化方法,粒子群优化算法(PSO)在优化求解问题中体现出了良好的性能.从提出至今引起了广泛的关注,研究成果也不断涌现.从2000年开始,PSO被用于动态优化问题中.这对PSO的研究提出了新的挑战,对于动态问题的优化不再是在解空间中找到一个最优点,而是要尽可能地在解空间中跟踪运动变化的最优点.对目前为止对于PSO在动态环境优化问题的研究内容进行了分析和总结,介绍了针对动态环境优化问题PSO的改进方法、对环境变化的检测和应对策略、优化性能评价的一系列方法以及各种试验及应用案例.

The ChatGPT After: Building Knowledge Factories for Knowledge Workers with Knowledge Automation

Briefing: This perspective introduces the concept and framework of knowledge factories with knowledge machines for knowledge workers to achieve knowledge automation for Industry 5.0 and intelligent industries.Introduction The big hit of Chat GPT makes it imperative to contemplate the practical applications of big or foundation models [1]-[5]. However, as compared to conventional models, there is now an increasingly urgent need for foundation intelligence of foundation models for real-world industrial applications.

Steps toward Parallel Intelligence

The origin of artificial intelligence is investigated, based on which the concepts of hybrid intelligence and parallel intelligence are presented. The paradigm shift in Intelligence indicates the ''new normal'' of cyber-social-physical systems (CPSS), in which the system behaviors are guided by Merton's Laws. Thus, the ACP-based parallel intelligence consisting of Artificial societies, Computational experiments and Parallel execution are introduced to bridge the big modeling gap in CPSS. © 2014 Chinese Association of Automation.

A Situation-Aware Collision Avoidance Strategy for Car-Following

Abstract--In this paper, we discuss how to develop an appropriate collision avoidance strategy for car-following. This strategy aims to keep a good balance between traffic safety and efficiency while also taking into consideration the unavoidable uncertainty of position/speed perception/measurement of vehicles and other drivers. Both theoretical analysis and numerical testing results are provided to show the effectiveness of the proposed strategy. Index Terms--Collision avoidance, safety, traffic efficiency, uncertainty.

Hybrid Nanoelectronics： Future of Computer Technology

Nanotechnology may well prove to be the 21st century＇s new wave of scientific knowledge that transforms people＇s lives. Nanotechnology research activities are booming around the globe. This article reviews the recent progresses made on nanoelectronic research in US and China, and introduces several novel hybrid solutions specifically useful for future computer technology. These exciting new directions will lead to many future inventions, and have a huge impact to research communities and industries.

Guidance Control for Parallel Parking Tasks

Parking into small berths remains difficult for unskilled drivers. Researchers had proposed different automatic parking systems to solve this problem. The first kind of strategies(called parking trajectory planning) designs a detailed reference trajectory that links the start and ending points of a special parking task and let the vehicle track this reference trajectory so as to park into the berth. The second kind of strategies(called guidance control) just characterizes several regimes of driving actions as well as the important switching points in certain rule style and let the vehicle follows the pre-selected series of actions so as to park into the berth. Parking guidance control is simpler than parking trajectory planning. However, no studies thoroughly validated parking guidance control before. In this paper, a new automatic parking method is presented, which could characterize the desired control actions directly. Then the feasibility is examined carefully. Tests show that a simple parking guidance control strategy can work in most parallel parking tasks, if the available parking berth is not too small. This finding helps to build more concise automatic parking systems that can efficiently guide human drivers.

Nonlinear energy harvesting from vibratory disc-shaped piezoelectric laminates

Implementing resonators with geometrical nonlinearities in vibrational energy harvesting systems leads to considerable enhancement of their operational bandwidths. This advantage of nonlinear devices in comparison to their linear counterparts is much more obvious especially at small-scale where transition to nonlinear regime of vibration occurs at moderately small amplitudes of the base excitation. In this paper the nonlinear behavior of a disc-shaped piezoelectric laminated harvester considering midplane-stretching effect is investigated. Extended Hamilton’s principle is exploited to extract electromechanically coupled governing partial differential equations of the system. The equations are firstly order-reduced and then analytically solved implementing perturbation method of multiple scales. A nonlinear finite element method(FEM) simulation of the system is performed additionally for the purpose of verification which shows agreement with the analytical solution to a large extent. The frequency response of the output power at primary resonance of the harvester is calculated to investigate the effect of nonlinearity on the system performance. Effect of various parameters including mechanical quality factor, external load impedance and base excitation amplitude on the behavior of the system are studied. Findings indicate that in the nonlinear regime both output power and operational bandwidth of the harvester will be enhanced by increasing the mechanical quality factor which can be considered as a significant advantage in comparison to linear harvesters in which these two factors vary in opposite ways as quality factor is changed.

Computer Simulation/Practical Models for Human Thyroid Thermographic Imaging

We have demonstrated a successful computer model utilizing ANSIS software that is verified with a practical model using Infrared (IR) sensors. The simulation model incorporates the three heat transfer coefficients: conduction, convection, and radiation. While the conduction component was a major contributor to the simulation model, the other two coefficients have added to the accuracy and precision of the model. Convection heat allows for the influence of blood flow within the study, while the radiation aspect, sensed through IR sensors, links the practical model of the study. This study also compares simulation data with the applied model generated from IR probe sensors. These sensors formed an IR scanner that moved via servo mechanical system, tracking the temperature distribution within and around the thyroid gland. These data were analyzed and processed to produce a thermal image of the thyroid gland. The acquired data were then compared with an Iodine uptake scan for the same patients.

Hardware Design for Low Power Integrated Sensor System

An integrated sensor system is implemented using inter-integrated circuit mode (I2C) software, utilizing the PIC182585 MPLAB embedded control system utilizing hardware. The hardware implementation features high level of integration, reliability, high precision, and high speed communications. The system was demonstrated by temperature and CO2 sensors. An extension for Zigbee system is proposed to enhance the security of the integrated system. A bi-directional air/liquid flow sensor is also added to detect the flow magnitude and direction that can be applied to heating, ventilating, and air-conditioning (HVAC), local and national security within subway systems, and medical equipment. The hardware design of the flow sensor included one heating element and two sensing elements to detect the bi-directional flow. Platinum sensors were found to be of high sensitivity and linear characteristics within 0℃ to 100℃ range, and their high temperature coefficient (0.00385 Ω/Ω/℃). Polyimide thin film heater was used as the heating element due to its high throughput and good thermal efficiency. Two bridge circuits were also designed to sense the temperature distribution in the vicinity of the sensing elements. Three high precision instrumentation low power amplifiers with offset voltage ~2.5 μV (50 μV max) were used for the overall design. The system security is also enhanced with the detection of poison gas using Carbon Nanotube devices (CNT). An antenna system was designed, and a frequency shift was detected to designate the type of poison gas used for a general threat.