A multi-step standard-cell placement algorithm of optimizing timing and congestion behavior

The timing behavior and congestion behavior are two important goals in the performance-driven standard-cell placement. In this paper, we analyze the relationship between the timing and congestion behavior. We bring up a multi-step placement algorithm to reach the two goals. First, the timing-driven placement algorithm is used to find the global optimal solution. In the second step, the algorithm tries to decrease the maximum congestion while not deteriorating the timing behavior. We have implemented our algorithm and tested it with real circuits. The results show that the maximum delay can decrease by 30% in our timing-driven placement and in the second step the maximum congestion will decrease by 10% while the timing behavior is unchanged.     

Simultaneous monitoring of oxygen consumption and acidification rates of a single zebrafish embryo during embryonic development within a microfluidic device

A microfluidic device with a light modulation system was developed to simultaneously measure the oxygen consumption rate (OCR) and acid extrusion rate (AER) of a single zebrafish embryo during embryonic development. The device combines two components: an array of acrylic microwells containing two sensing layers as the dual luminescent sensor for oxygen (O₂) and acid (pH) detection, and a microfluidic module with pneumatically actuated glass lids to controllably seal the microwells. The continuous blue LED and modulated UV LED lights were simultaneously used to excite the dual luminescent sensor, with the emission detected by a single photodetector. The detection signals were then split into DC and AC components to measure the time variations in fluorescence intensity and phosphorescence lifetime for pH and O₂ detection, respectively. We have successfully measured the OCR and AER of a single developing zebrafish embryo inside a sealed microwell from the blastula stage (3 h post-fertilization, 3 hpf) through the hatching stage of 48 hpf. We also demonstrated the measurement of the OCR and AER of a single 48 hpf zebrafish that experienced acute hypoxia by using our device to monitor the transition between aerobic and anaerobic metabolism. We observed that the AER began to significantly increase, while the OCR rapidly decreased after 20 min of hypoxia, indicating the time point of transition where the non-mitochondrial metabolism subsequently dominated the energy production. Our proposed methodology provides the potential for studying the bioenergetic metabolism in a developing organism that relates mitochondrial physiology and disease.     

硅基高通量单细胞阵列芯片制备与研究

采用微机电系统(MEMS)技术结合金属辅助化学腐蚀工艺制作出关键结构为纳米氧化硅的阵列芯片,细胞可以定点黏附在纳米氧化硅上.通过实验计算和分析得知,在0.7~23μm内,纳米线长度约为3μm时深宽比适宜,有利于黏附蛋白充分铺展,黏附效率达到最高85%.改变培养时间(5~480 min)和细胞浓度(0.5~4.0),发现培养时间在不低于4 h,细胞浓度在1.5时,由于伪足充分缠绕于纳米线上,阵列饱和度达到最高83%.实验结果表明:制作出的单细胞阵列芯片具有较高的黏附效率和阵列饱和度,达到了高通量的标准.     

单幅图像去雨算法研究现状及展望

图像去雨算法通过对有雨图像进行分析和处理从而去除雨水条纹,恢复干净的背景场景,有助于提升计算机视觉任务识别精度,因此成为当下的研究热点。为系统地了解该领域的研究现状和发展趋势,首先介绍了典型的雨水合成模型,其次从基于模型驱动和基于数据驱动两个方面重点分析了典型图像去雨算法模型和方法;之后比较了去雨图像质量评价指标及雨水数据集;最后,对单幅图像去雨算法未来发展趋势进行了展望。     

Automatic estimation and removal of noise from a single image

Image denoising algorithms often assume an additive white Gaussian noise (AWGN) process that is independent of the actual RGB values. Such approaches are not fully automatic and cannot effectively remove color noise produced by todays CCD digital camera. In this paper, we propose a unified framework for two tasks: automatic estimation and removal of color noise from a single image using piecewise smooth image models. We introduce the noise level function (NLF), which is a continuous function describing the noise level as a function of image brightness. We then estimate an upper bound of the real noise level function by fitting a lower envelope to the standard deviations of per-segment image variances. For denoising, the chrominance of color noise is significantly removed by projecting pixel values onto a line fit to the RGB values in each segment. Then, a Gaussian conditional random field (GCRF) is constructed to obtain the underlying clean image from the noisy input. Extensive experiments are conducted to test the proposed algorithm, which is shown to outperform state-of-the-art denoising algorithms.     

Automated synthesis of resilient and tamper-evident analog circuits without a single point of failure

This study focuses on the use of genetic programming to automate the design of robust analog circuits. We define two complementary types of failure modes: partial short-circuit and partial disconnect, and demonstrated novel circuits that are resilient across a spectrum of fault levels. In particular, we focus on designs that are uniformly robust, and unlike designs based on redundancy, do not have any single point of failure. We also explore the complementary problem of designing tamper-proof circuits that are highly sensitive to any change or variation in their operating conditions. We find that the number of components remains similar both for robust and standard circuits, suggesting that the robustness does not necessarily come at significant increased circuit complexity. A number of fitness criteria, including surrogate models and co-evolution were used to accelerate the evolutionary process. A variety of circuit types were tested, and the practicality of the generated solutions was verified by physically constructing the circuits and testing their physical robustness.     

The optimisation of the single surface mount device placement machine in printed circuit board assembly: a survey

This article surveys research on the single surface mount device (SMD) placement machine optimisation problem. We classify the optimisation problem into five sub-problems: feeder setup, component placement sequencing, nozzle optimisation, component retrieval plan and motion control; and analyse issues relevant to each of these. One of the aims of this article is to provide guidance to other researchers and gain a deeper understanding of the various optimisation issues that arise in this domain. This could lead to the design of improved heuristics, which are more appropriate to the real-world scheduling problem of the SMD placement machine.     

Automated classification and analysis of the calcium response of single T lymphocytes using a neural network approach

The gene activities in T lymphocytes that regulate immune responses are influenced by Ca/sup 2+/ ([Ca/sup 2+/]/sub i/). The intracellular calcium signals are highly heterogeneous and vitally important in determining the immune outcome. The signals in individual cells can be measured using fluorescence microscopy but to group the cells into classes with similar signal kinetics is currently laborious. Here, we demonstrate a method for the automated classification of the responses into four categories formerly identified by an expert's inspection. This method comprises characterising the response by a second-order model, performing frequency analysis, and using derived features as inputs to two multilayer perceptron neural networks (NNs). We compare the algorithm's performance on an example data set against the human classification: it was found to classify identically more than 70% of the data, despite small sample sizes in two categories and significant overlap between the other two classes. The group characterized by an oscillating signal showed the presence of a number of frequencies, which may be important in determining gene activation. A classification threshold enables the automatic identification of patterns with a low-classification certainty. Future refinement of the algorithm may allow the identification of more classes, which may be important in different immune responses associated with disease.     

单幅图像去雨数据集和深度学习算法的联合评估与展望

雨天会影响室外图像捕捉的质量,进而引起户外视觉任务性能下降。基于深度学习的单幅图像去雨研究因算法性能优越而引起了大家的关注,并且聚焦点集中在数据集的质量、图像去雨方法、单幅图像去雨后续高层任务的研究和性能评价指标等方面。为了方便研究者快速全面了解该领域,本文从上述4个方面综述了基于深度学习的单幅图像去雨的主流文献。依据数据集的构建方式将雨图数据集分为4类：基于背景雨层简单加和、背景雨层复杂融合、生成对抗网络 (generative adversarial network,GAN)数据驱动合成的数据集,以及半自动化采集的真实数据集。依据任务场景、采取的学习机制以及网络设计对主流算法分类总结。综述了面向单任务和联合任务的去雨算法,单任务即雨滴、雨纹、雨雾和暴雨的去除;联合任务即雨滴和雨纹、所有噪声去除。综述了学习机制和网络构建方式(比如:卷积神经网络 (convolutional neural network,CNN)结构多分支组合,GAN的生成结构,循环和多阶段结构,多尺度结构,编解码结构,基于注意力,基于Transformer)以及数据模型双驱动的构建方式。综述了单幅图像去雨后续高层任务的研究文献和图像去雨算法性能的评价指标。通过合成数据集和真实数据集上的综合实验对比,证实了领域知识隐式引导网络构建可以有效提升算法性能,领域知识显式引导正则化网络的学习有潜力进一步提升算法的泛化性。最后,指出单幅图像去雨工作目前面临的挑战和未来的研究方向。     

Automated sleep stage identification system based on time-frequency analysis of a single EEG channel and random forest classifier

In this work, an efficient automated new approach for sleep stage identification based on the new standard of the American academy of sleep medicine (AASM) is presented. The propose approach employs time-frequency analysis and entropy measures for feature extraction from a single electroencephalograph (EEG) channel. Three time-frequency techniques were deployed for the analysis of the EEG signal: Choi-Williams distribution (CWD), continuous wavelet transform (CWT), and Hilbert-Huang Transform (HHT). Polysomnographic recordings from sixteen subjects were used in this study and features were extracted from the time-frequency representation of the EEG signal using Renyi's entropy. The classification of the extracted features was done using random forest classifier. The performance of the new approach was tested by evaluating the accuracy and the kappa coefficient for the three time-frequency distributions: CWD, CWT, and HHT. The CWT time-frequency distribution outperformed the other two distributions and showed excellent performance with an accuracy of 0.83 and a kappa coefficient of 0.76.     

Pole placement: Stability and sensitivity of dynamic compensators

Recent results for arbitrary closed-loop pole placement are discussed with regard to the stability of the corresponding dynamic feedback compensators, as well as the sensitivity of closed-loop pole locations to imperfections in such compensators.     

Effective display of medical laboratory report results on small screens: Evaluation of linear and hierarchical displays

Two studies evaluated linear and hierarchy+elision small‐screen display formats for clinical reasoning tasks. A controlled, quantitative study with 28 medically naive participants using a task abstracted from clinical use of laboratory results found that both display formats supported rapid and accurate decision making. Distribution of the search targets significantly affected speed, with decisions in linear format made 13% faster (4.7 sec) when all targets could be viewed on a single screen than when targets required scrolling between several screens and in hierarchical format 15% faster (5.1 sec) when all the targets were confined within one category. Performance was equivalent regardless of the relative order of the target results and data in the laboratory report. In a qualitative study, 7 physicians used the displays to perform a realistic diagnosis. Physicians were comfortable with both display formats, but preference varied with clinical experience. The 5 less experienced clinicians favored hierarchy+elision, whereas the 2 highly experienced clinicians tended to prefer the linear display.     

Automated planning and optimization of machining processes: A systems approach

A system is presented that combines the automated planning and optimization functions in machining processes. The planning function is performed by a systematic analysis of the stated requirements of the finished part in the light of information on available machining facilities and raw materials. The optimization phase utilizes a mathematical programming model to take into account various costs and constraints under alternative machining conditions. A gradient or “hill-climbing” algorithm is shown to be a convenient optimization technique for this class of problems. Implementation of the system is illustrated in some detail for the case of the face milling process.     

Metaform: updatable form screens and their application to the use of office metaphors in query language instruction

Abstract

A database interface language and system, called Metaform, which automatically generates multi-relational form screen interfaces for use by non-computer professionals has been developed. A form screen is a subset of the relational database, with a particular relation or combination of relations being represented. Through form screens, users can simultaneously query and update several relations in the database without having to know about its underlying structure. An overview of the Metaform system is presented and several examples of the use of the Metaform query language and update operators are described.

A series of ‘usability’ studies were conducted on a prototype of the Metaform system to examine the claims that the form concept aids computer-naive users in building complex database queries. These studies adopted the form screen concept to present six office paper work analogies to users to help them to understand the database retrieval concepts. The analogies of a file cabinet, a file folder, a stack of forms, a single form, a table of information on a form and a field of information were used in a two-staged training module.

At the end of each training sequence, users answered questions with the prototype and with paper and pencil which tapped their understanding of the database retrievals they were learning to perform. The results from these questionnaires were mixed. Users performed successful relational queries for simple retrievals and for those using existential quantifiers. They had difficulty with queries involving multiple steps and intermediate stages. Although users understood and used the analogies, they ran into difficulties with the ambiguities in the English statements of the queries, thus suggesting a need for another level of metaphors and/or problem representation tools not associated with the machine but with the user's comprehension of database retrieval problems.     

Mobile link prediction: Automated creation and crowdsourced validation of knowledge graphs

Building trustworthy knowledge graphs for cyber–physical social systems (CPSS) is a challenge. In particular, current approaches relying on human experts have limited scalability, while automated approaches are often not validated by users resulting in knowledge graphs of questionable quality. This paper introduces a novel pervasive knowledge graph builder for mobile devices that brings together automation, experts’ and crowdsourced citizens’ knowledge. The knowledge graph grows via automated link predictions using genetic programming that are validated by humans for improving transparency and calibrating accuracy. The knowledge graph builder is designed for pervasive devices such as smartphones and preserves privacy by localizing all computations. The accuracy, practicality, and usability of the knowledge graph builder is evaluated in a real-world social experiment that involves a smartphone implementation and a Smart City application scenario. The proposed methodology of knowledge graph building outperforms a baseline method in terms of accuracy while demonstrating its efficient calculations on smartphones and the feasibility of the pervasive human supervision process in terms of high interactions throughput. These findings promise new opportunities to crowdsource and operate pervasive reasoning systems for cyber–physical social systems in Smart Cities.     

Metaform: updatable form screens and their application to the use of office metaphors in query language instruction

A database interface language and system, called Metaform, which automatically generates multi-relational form screen interfaces for use by non-computer professionals has been developed. A form screen is a subset of the relational database, with a particular relation or combination of relations being represented. Through form screens, users can simultaneously query and update several relations in the database without having to know about its underlying structure. An overview of the Metaform system is presented and several examples of the use of the Metaform query language and update operators are described.

A series of 'usability' studies were conducted on a prototype of the Metaform system to examine the claims that the form concept aids computer-naive users in building complex database queries. These studies adopted the form screen concept to present six office paper work analogies to users to help them to understand the database retrieval concepts. The analogies of a file cabinet, a file folder, a stack of forms, a single form, a table of information on a form and a field of information were used in a two-staged training module.

At the end of each training sequence, users answered questions with the prototype and with paper and pencil which tapped their understanding of the database retrievals they were learning to perform. The results from these questionnaires were mixed. Users performed successful relational queries for simple retrievals and for those using existential quantifiers. They had difficulty with queries involving multiple steps and intermediate stages. Although users understood and used the analogies, they ran into difficulties with the ambiguities in the English statements of the queries, thus suggesting a need for another level of metaphors and/or problem representation tools not associated with the machine but with the user's comprehension of database retrieval problems.     

A new approach for optimizing automotive crashworthiness: concurrent usage of ANFIS and Taguchi method

Design optimization is presented for the crashworthiness improvement of an automotive body structure. The optimization objective was to improve automotive crashworthiness conditions according to the defined criterion (occupant chest deceleration) during a full frontal impact. The controllable factors used in this study consisted of six internal parts of the vehicle’s frontal structure in a condition that their thickness was the “design parameter”. First using the Taguchi method, this study analyzed the optimum conditions in discontinuous design area and impact factors and their optimal levels of design objectives were obtained by analyzing the experimental results. Next to model a precise understanding of the explicit mathematical input–output relationship, fuzzy logic is utilized which make use of full factorial design set of experimental test cases resulted from Taguchi predicting formulations. Interestingly, the optimum conditions for automotive crashworthiness occurred with 2.72 % improvement in the defined crashworthiness criterion in comparison with the baseline design while selected structural parts experienced mass reduction by 8.23 %.     

RETRACTED ARTICLE: Prediction model of port throughput based on game theory and multimedia Bayesian regression

In order to simulate the situation of freight flow in overlapping hinterland, we forecast the throughput of port and introduce the game theory to improve it. On the basis of this, a multimedia Bayesian regression model is established. On the basis of the existing port throughput prediction theory and actual situation of ports in China, through the analysis of China’s coastal port cargo and impact, a coastal port cluster cargo throughput prediction model, improve China’s coastal port throughput prediction precision and accuracy, which provides more reliable reference for China’s coastal areas port investment planning. The main features of this model are as follows. For the first time, we analyze and predict the throughput of coastal ports from the point of view of the composition of port throughput. Considering the coordination relationship between major coastal port cargo throughput under, we use game theory, to deal with the port cargo throughput index, the maximum information is retained to ensure the accuracy of prediction model. The model is convenient and flexible, and can be extended to the throughput prediction of a single port or port group. It can be extended to the prediction problem with more time series indexes under multimedia environment.

     

一种自适应调整种群子代数量 与步长的优化算法——爆米花算法

提出了一种新的群体智能优化算法——爆米花算法。借鉴了烟花算法爆炸机制的优点,利用个体在寻优过程中适应度值的优劣来动态调整子代的数量,个体的适应度值越好,产生的子代数量越多,并且在该个体附近搜索的子代数量越多,以此控制局部搜索与全局搜索之间的平衡。还借鉴了粒子群优化算法的记忆机制,引入个体最优和全局最优来构造新的爆炸半径,使算法能够在寻优过程中动态地调整步长,并对全局最优进行高斯扰动,增加种群的多样性。实验结果表明:与其他优化算法(如蝙蝠算法、标准粒子群算法、烟花算法)相比,本文提出的爆米花算法总体性能更优。