1,019 research outputs found
A soft jellyfish robot driven by a dielectric elastomer actuator
No full textAlthough dielectric elastomers have been extensively studied recently, to date there has been little research into application of dielectric elastomer actuators to undersea robots. This letter focuses on development of a jellyfish robot using a dielectric elastomer actuator, which exhibits muscle-like properties including large deformation and high energy density. We carry out experiments to test the actuator’s deformation and force. Theoretical simulations are conducted to analyze the performance of the actuator, which are qualitatively consistent with the experiments. The preliminary studies show that this jellyfish robot based on dielectric elastomer technology can move effectively in water. The robot also exhibits fast response and high capacity of payload (compared to its self-weight)
Soft robots based on dielectric elastomer actuators: a review
No full textConventional robots are mainly made of rigid materials, such as steel and aluminum. Recently there has been a surge in the popularity of soft robots owing to their inherent compliance, strong adaptability and capability to work effectively in unstructured environments. Of the multitude of soft actuation technologies, dielectric elastomer actuators (DEAs), also nicknamed 'artificial muscles', exhibit fast response, large deformation and high energy density, and can simply be actuated with electric voltage. In this paper, we will discuss applications of DEAs to soft robots, including robotic grippers, terrestrial robots, underwater robots, aerial robots and humanoid robots. We will survey the state of the art regarding these interesting applications and outline the challenges and perspectives. As we know, there have been extensive studies on dielectric elastomer technology in the aspects of materials, mechanics, design, fabrication and controls. To enable practical applications, efforts are underway to decrease operational voltages, improve reliability, and impart new functionalities. Key challenges include the development of freestanding actuators, untethered operation, smart/electronics free actuators, solid and stretchable electrodes, miniaturization, combination of synergistic actuation technologies to impart novel functionalities, development of effective control strategies, etc. We hope that this review can facilitate and enhance applications of dielectric elastomer technology to soft robots
Optimal auditing and insurance in a dynamic model of tax compliance
Get PDFWe study the optimal auditing of a taxpayer's income in a dynamic principal-agent model of hidden income. Taxpayers in our model initially have low income and stochastically transit to high income that is an absorbing state. A low-income taxpayer who transits to high income can under-report his true income and evade his taxes. With a constant absolute risk-aversion utility function and a costly auditing technology, we show that the optimal auditing mechanism in our model consists of cycles. Within each cycle, a low-income taxpayer is initially unaudited, but if the duration of low-income report exceeds a threshold, then the auditing probability becomes positive. That is, the tax authority guarantees that the taxpayer will not be audited until the threshold duration is reached. We also find that auditing becomes less frequent if the auditing cost is higher or if the variance of income is lower.Tax compliance, tax auditing, stochastic costly state verification
Collective land system in China: Congenital flaw or acquired irrational weakness?
No full textWith the level of urbanization in China now exceeding 50%, its collective rural land system is under increasing pressure, creating conditions in which there is increasing conflict between the efficient use of land for agricultural purposes and its retention as security for the rural population. This paper first examines the fundamental nature of China's collective land system by analyzing the collectivization history of China, then provides a comprehensive appraisal of the strengths and weaknesses of the collective land system's role in history and the challenges it faces in modern times. The main changes needed for the current collective system are identified as (1) the establishment of a new transfer mechanism for potential collective construction land, (2) the completion of land rights verification and consolidation work, and (3) the endowment of villagers with more rights to enjoy the distribution of land incremental value. The paper's main contribution is to question the relevance of collective rural land system in contemporary China, where a shift is now taking place from one of pure economic development to one involving more social concerns, and propose potential viable amendments to integrate the need for both perspectives
Visual Interpretation of Recurrent Neural Network on Multi-dimensional Time-series Forecast
No full textRecent attempts at utilizing visual analytics to interpret Recurrent Neural Networks (RNNs) mainly focus on natural language processing (NLP) tasks that take symbolic sequences as input. However, many real-world problems like environment pollution forecasting apply RNNs on sequences of multi-dimensional data where each dimension represents an individual feature with semantic meaning such as PM2.5 and SO2. RNN interpretation on multi-dimensional sequences is challenging as users need to analyze what features are important at different time steps to better understand model behavior and gain trust in prediction. This requires effective and scalable visualization methods to reveal the complex many-to-many relations between hidden units and features. In this work, we propose a visual analytics system to interpret RNNs on multi-dimensional time-series forecasts. Specifically, to provide an overview to reveal the model mechanism, we propose a technique to estimate the hidden unit response by measuring how different feature selections affect the hidden unit output distribution. We then cluster the hidden units and features based on the response embedding vectors. Finally, we propose a visual analytics system which allows users to visually explore the model behavior from the global and individual levels. We demonstrate the effectiveness of our approach with case studies using air pollutant forecast applications.Accepted author manuscriptComputer Graphics and Visualisatio
Multiple ancestral haplotypes harboring regulatory mutations cumulatively contribute to a QTL affecting chicken growth traits
No full textIn depth studies of quantitative trait loci (QTL) can provide insights to the genetic architectures of complex traits. A major effect QTL at the distal end of chicken chromosome 1 has been associated with growth traits in multiple populations. This locus was fine-mapped in a fifteen-generation chicken advanced intercross population including 1119 birds and explored in further detail using 222 sequenced genomes from 10 high/low body weight chicken stocks. We detected this QTL that, in total, contributed 14.4% of the genetic variance for growth. Further, nine mosaic precise intervals (Kb level) which contain ancestral regulatory variants were fine-mapped and we chose one of them to demonstrate the key regulatory role in the duodenum. This is the first study to break down the detail genetic architectures for the well-known QTL in chicken and provides a good example of the fine-mapping of various of quantitative traits in any species. Yuzhe Wang, Xuemin Cao et al. report the fine-mapping of a major growth trait QTL in chicken using genome-wide association and haplotype association analyses. They discover multiple mutations cumulatively contribute to the previously-reported QTL and identify one of a regulatory mutation that contributes to the variation in the measured traits
A Classical Cipher-Playfair Cipher and Its Improved Versions
No full textIn today's communications world, protecting data security cannot be ignored. Cryptography, which plays a pivotal role in information security, has become an indispensable and important part of information security. Cryptography is to study secret communication for adopting a kind of secret protection for the information to be transmitted. It is a technical science that studies the preparation and deciphering of codes. Classical encryption can be divided into two categories: transposition ciphers and substitution ciphers. This paper will mainly study a kind of substitution ciphers-Playfair cipher and review three improved versions of the 3D Playfair cipher. Then, a conclusion was drawn for these three improved versions of Playfair cipher. Finally looks forward to the future development of Playfair cipher and cryptography
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Learning Generalizable Dexterous Manipulation
Get PDFDexterous manipulation using multi-fingered robotic hands is a crucial area in robotics, aimed at performing intricate tasks with various objects in everyday environments. However, this field presents significant challenges. Modeling the complex contact patterns between a dexterous hand and manipulated objects is difficult, hindering the effectiveness of model-based control methods. Furthermore, the high number of Degrees of Freedom (DoF) in the hand's joints, dramatically increases the complexity of training data-driven policies for dexterous manipulation.This dissertation addresses the challenging task of learning highly generalizable dexterous manipulation skills applicable across diverse scenarios. We investigate two principal directions to enhance the learning capabilities of dexterous manipulation. First, we leverage the inherent structural similarities between human and robotic hands, employing human data to guide robot manipulation skills. This approach is motivated by the bio-inspired design of dexterous hands, which offers a unique opportunity to learn from human demonstrations. To facilitate efficient data collection, we develop AnyTeleop, a general vision-based teleoperation system for dexterous robot arm-hand systems. AnyTeleop utilizes readily available devices like web cameras to provide a versatile interface for teleoperating various arm-hand systems. Furthermore, we introduce CyberDemo, a data augmentation technique that expands the original human demonstrations, generating a dataset hundreds of times larger than the initial set. This approach allows for training policies capable of handling a wider range of scenarios without requiring additional human effort.Second, we explore the potential of using vast amounts of simulated data to learn dexterous manipulation policies. The primary challenge in this direction lies in bridging the domain gap between simulation and the real world, encompassing both dynamics and visual discrepancies. This sim2real gap is particularly pronounced for high DoF dexterous hands. To address this, we propose a sim-to-real reinforcement learning framework, DexPoint, that leverages point cloud and proprioceptive data. This framework integrates multi-modal sensory information into a unified 3D space, preserving the spatial relationships between robot components, sensors, and manipulated objects. This unified representation enables faster policy learning in simulation and smoother transfer to real-world applications
Two Essays on Patent System
No full textThe effectiveness of patent system design has been studied for decades from both microeconomic and macroeconomic perspectives. The existing literature demonstrates that innovations provide product diversity, supporting the view that specialization leads to increasing returns. Moreover, innovators are often rewarded patent rights to recover the cost of innovation. The monopolistic power provided by patents, on the other hand, can result in deadweight loss, hurting social welfare. Traditional studies on designing effective paten systems have investigated the effect of human capital on growth-assuming infinite patents. This thesis, however, investigates two issues: how various factors influence the optimization of patent policy, under which the mechanism designer controls the expected length of patent to guarantee maximization of social welfare; and how the incumbent patentee reacts to the new entrant in the market according to existing patent policies.
In this thesis, we first analyze the environment in which innovators can engage in research that produces technological improvements. Each invention represents a new type of intermediate input. The social planner faces a tradeoff between the needs of encouraging the innovators, and the fact that the monopolistically competitive equilibrium provides less intermediate inputs. In this study, we find that the optimal patent policy is a two-stage arrangement. To counteract the slower technological growth resulting from monopolistic power, the social planner first grants no monopolistic power to the innovators. Then, after the critical time point when the resource in the economy becomes rich, the social planner grants the innovators infinite protection.
From the view of market participants, we evaluate a patent-holding incumbent���s incentives to litigate, settle with, and accommodate a new market entrant. Patent protection is uncertain and is characterized by patentability standards and patent breadth determined during litigation. While litigation has the benefit of blocking an infringing product, it carries a risk of patent invalidation. As a result, the incumbent accommodates large improvements. Improving the incumbent���s market position strengthens his litigation incentives, but it can also benefit the entrant since a stronger incumbent mitigates market competition from non-patented product
Application of fast laser deprocessing techniques in the field of semiconductor manufacturing
No full textWith technology scaling of semiconductor devices and further growth of the integrated circuit (IC) design and function complexity, it is necessary to increase the number of transistors in IC chip, layer stack, and process steps. The last few metal layers of Back End Of Line (BEOL) are usually very thick metal lines (>4µm thickness) and protected with hard Silicon Dioxide (SiO2) material that is formed from (Tetra Ethyl Ortho Silicate) TEOS as Inter-Metal Dielectric (IMD). In order to perform physical failure analysis (PFA) on the logic or memory, the top thick metal layers must be removed. It is time consuming to deprocess those thick metal layers and thick IMD layers. In this project, Fast Laser Deprocessing Technique (FLDT) is proposed to remove the BEOL thick and stubborn metal layers for memory PFA. The proposed FLDT is a cost-effective and quick way to deprocess a sample for defect identification in PFA.
Besides application on top down layer deprocessing, this project also further explores on cross sectional sample preparation. Cross-sectional analysis is one of the important areas for physical failure analysis. Focus Ion Beam (FIB) and mechanical polish sample preparation are commonly used and necessary techniques in the semiconductor industry and FA company. However, each technique has its own limitation. Mechanical polishing technique easily induces artifact by mechanical force, especially on advance technology node. FIB can eliminate mechanically damaged artifact, but have the limitation on cross-sectional view area. Another potential technique will be plasma FIB, it used very high milling current and fast milling speed. However, it comes with a very high cost and having the contamination issue. The contamination issue greatly affects the low kV Scanning Electron Microscopy (SEM) imaging quality. In recent semiconductor industry FA, low kV SEM imaging is preferable, because high kV imaging will be introduced delamination artifact especially on organic material from packaged sample. In third part of this project, Fast Laser Deprocessing Techniques (FLDT) application is further enhanced on large area cross-sectional FA with fast cycle time and low-cost equipment. This is to prevent on mechanical damaged. In short, the proposed FLDT is a cost-effective and quick way to deprocess a sample for defect identification in cross-sectional FA.Bachelor of Engineerin
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