xOpat: eXplainable Open Pathology Analysis Tool

Histopathology research quickly evolves thanks to advances in whole slide imaging (WSI) and artificial intelligence (AI). However, existing WSI viewers are tailored either for clinical or research environments, but none suits both. This hinders the adoption of new methods and communication between the researchers and clinicians. The paper presents xOpat, an open-source, browser-based WSI viewer that addresses these problems. xOpat supports various data sources, such as tissue images, pathologists' annotations, or additional data produced by AI models. Furthermore, it provides efficient rendering of multiple data layers, their visual representations, and tools for annotating and presenting findings. Thanks to its modular, protocol-agnostic, and extensible architecture, xOpat can be easily integrated into different environments and thus helps to bridge the gap between research and clinical practice. To demonstrate the utility of xOpat, we present three case studies, one conducted with a developer of AI algorithms for image segmentation and two with a research pathologist.     

A distributed perception infrastructure for robot assisted living

This paper presents an ambient intelligence system designed for assisted living. The system processes the audio and video data acquired from multiple sensors spread in the environment to automatically detect dangerous events and generate automatic warning messages. The paper presents the distributed perception infrastructure that has been implemented by means of an open-source software middleware called NMM. Different processing nodes have been developed which can cooperate to extract high level information about the environment. Examples of implemented nodes running algorithms for people detection or face recognition are presented. Experiments on novel algorithms for people fall detection and sound classification and localization are discussed. Eventually, we present successful experiments in two test bed scenarios.     

面向视频的细粒度多模态实体链接

随着互联网和大数据的飞速发展,数据规模越来越大,种类也越来越多.视频作为其中重要的一种信息方式,随着近期短视频的发展,占比越来越大.如何对这些大规模视频进行理解分析,成为学界关注的热点.实体链接作为一种背景知识补全方式,可以提供丰富的外部知识.视频上的实体链接可以有效地帮助理解视频内容,从而实现对视频内容的分类、检索、推荐等.但是现有的视频链接数据集和方法的粒度过粗,因此提出面向视频的细粒度实体链接,并立足于直播场景,构建了细粒度视频实体链接数据集.此外,依据细粒度视频链接任务的难点,提出利用大模型抽取视频中的实体及其属性,并利用对比学习得到视频和对应实体的更好表示.实验结果表明,该方法能够有效地处理视频上的细粒度实体链接任务.     

Four-legged intelligent mobile autonomous robot

This paper presents the design and development of a four-legged mobile robot with intelligent sensing and decision-making capabilities. Multiple sensors with embedded knowledge bases and learning capabilities are used in a novel approach towards environmental perception and reaction. These sensors continuously monitor the environment as well as their own operating parameters. Priority is given to any one or a group of sensors based on prevailing environmental conditions. Intelligent sensing is shown to be the key towards a high degree of autonomy for a mobile robot. Nicknamed Flimar, this robot has the ability to function at varying degrees of intelligence made possible by an object-oriented architecture with embedded intelligence at various levels. This architecture is shown to be conducive towards incremental learning. Each of the four legs has three degrees of freedom, i.e. Flimar has a total of 12 motors on its four legs. Flimar can walk and turn without dragging or skidding, and also turns about its center of gravity with a zero radius. Flimar responds to light, sound and touch in different ways, based on prevailing environmental conditions. The overall goal of the paper is to present a novel walking principle and control architecture for a walking robot.     

基于MIDI1.0协议的工尺谱乐谱音乐信息数字存储格式

描述了工尺谱记谱法（GCN,Gong-che Notation）的一些基本知识,指出了它和五线谱记谱法之间的异同点,然后利用MIDI1.0协议提出了具有兼容性的工尺谱乐谱的CGCN（Code of GCN）类MIDI文件的文件结构,最后对CGCN类MIDI文件的软件接口设计进行了必要的说明。提出的工尺谱乐谱的类MIDI文件结构具有较强的兼容性、鲁棒性和容错性,能实现音乐作品的音序信息和乐谱信息的同步传播,有效解决了工尺谱乐谱译谱过程中的歧义性问题,使中国传统音乐作品在数字时代得到良好的传播和复用。     

Toward the integration of knowledge for engineering modeling and computation

Recent developments in computer science, especially in the area of artificial intelligence (AI), have made possible the representation of knowledge in symbolic terms. This, in turn, has made it possible to represent and integrate a broader range of engineering knowledge so as to provide new kinds of computer support for both analysis and design. This paper presents a typology of engineering knowledge to provide a conceptual basis for its computational integration. A review of the roles of numerical, geometric, and symbolic representations is also given within the context of the knowledge typology. Illustrations are provided from the domain of structural engineering.     

Context provenance to enhance the dependability of ambient intelligence systems

Ambient intelligence systems would benefit from the possibility of assessing quality and reliability of context information based on its derivation history, named provenance. While various provenance frameworks have been proposed in data management, context data have some peculiar features that claim for a specific support. However, no provenance model specifically targeted to context data has been proposed till the time of writing. In this paper, we report an initial investigation of this challenging research issue by proposing a provenance model for data acquired and processed in ambient intelligence systems. Our model supports representation of complex derivation processes, integrity verification, and a shared ontology to facilitate interoperability. The model also deals with uncertainty and takes into account temporal aspects related to the quality of data. We experimentally show the impact of the provenance model in terms of increased dependability of a sensor-based smart-home infrastructure. We also conducted experiments to evaluate the communication and computational overhead introduced to support our provenance model, using sensors and mobile devices currently available on the market.     

基于多步聚类的汉语命名实体识别和歧义消解

命名实体识别和歧义消解是自然语言理解的重要研究内容。针对提供实体知识库情况下的命名实体识别和歧义消解任务,该文提出了一种基于多步聚类的方法。首先通过两轮聚类将命名实体与知识库实体定义链接,然后通过层次聚合式聚类对知识库中未出现的实体进行聚类,最后进行普通词的识别和基于K-Means聚类的结果调整。在CLP-2012的汉语命名实体识别和歧义消解评测数据上的实验表明,该文的方法表现出良好的性能,在测试集上的F值高出评测参赛队伍最好水平6.46%,达到86.68%。     

An Expedient Wireless Sensor Automaton With System Scalability and Efficiency Benefits

Wireless sensor networks are characterized by energy-constrained nodes that are tasked with collecting and forwarding environmental parameters with a requisite measurement, which is spatial and temporal fidelity. At the system level, fidelity is not the only issue of interest but also the achievement of a low-cost solution and a long life for the deployed network. As such, sensor nodes should be low in complexity and should achieve the requisite fidelity requirements, with minimum communication and coordination. This paper proposes that these nodes can operate as automata and still achieve the overall system performance requirements with minimal control. This paper presents and analyzes an automaton architecture and a control strategy designed to maintain spatial fidelity as the performance objective. In particular, we show the following: 1) that the architecture permits control of the number of nodes actively transmitting information in each epoch (denoted by $Q$ ); 2) that the variance of $Q$ can be controlled and, particularly, can be set to a value significantly less than that of a Bernoulli-process benchmark (i.e., the architecture is expedient with respect to the control of this variance); 3) that the control strategy is scalable over several orders of magnitudes; and 4) that the methodology is efficient in approaching benchmark performance with respect to energy usage. The proposed methodology has the following specific advantages over the benchmark: 1) The total number of sensors deployed in the network need not be known, and 2) the strategy maintains a robust control of $Q$ over changes in the commanded value and changes in the number of deployed sensors.      

Decentralized Delayed-State Information Filter (DDSIF): A new approach for cooperative decentralized tracking

This paper presents a decentralized data fusion approach to perform cooperative perception with data gathered from heterogeneous sensors, which can be static or carried by robots. In particular, a decentralized delayed-state information filter (DDSIF) is described, in which full-state trajectories (that is, delayed states) are considered to fuse the information. This approach allows obtaining an estimation equal to that provided by a centralized system and reduces the impact of communication delays and latency in the estimation. The sparseness of the information matrix maintains the communication overhead at a reasonable level. The method is applied to cooperative tracking, and some results in disaster management scenarios are shown. In this kind of scenario, the target might move in both open-field and indoor areas, so the fusion of data provided by heterogeneous sensors is beneficial. The paper also shows experimental results with real data and integrating several sources of information.     

Semantic ambient media: From ambient advertising to ambient-assisted living

The term ambient media was in its beginning used only for ambient advertising. Nowadays it denotes the media environment and the communication of information in ubiquitous and pervasive environments. With the addition of intelligence, the new field of semantic ambient media was established. In recent years, the field of semantic ambient media has spread its span from only a few sub-areas, such as ambient advertising, to new ones, such as ambient-assisted living (AAL) and health-monitoring media, significantly supported by intelligence. The study presented in this paper provides an advanced introduction to the field of semantic ambient media including the solutions for threat issues and illustration of success stories of the field. It conducts a survey of the related work and presents a thorough discussion of it. The related work is grouped according to the coverage of the principles of semantic ambient media. Based on the state-of-the-art research, the future possibilities of the field are demonstrated, especially for the ambient-assisted living, audio-visual rendering of media objects, user design principles and the society impact of the field. The paper provides ideas for impacting ambient media and directions and questions for further research. It also discusses the potential of the combination of several research studies.     

一种统计和词性相结合的命名实体发现方法

在利用专业文献自动构建知识库的过程中， 需要正确识别专业文献中的命名实体。文章针对命名实体识别问题．提出了一种以统计为主发现命名实体的方法。该方法利用切分标记将原文切分为较短的汉字串，采用自增长统计算法从汉字串中生成原始模式集，并利用统计信息和词性信息筛选出命名实体。     

TSK fuzzy modeling for tool wear condition in turning processes: An experimental study

This paper presents an experimental study for turning process in machining by using Takagi-Sugeno-Kang (TSK) fuzzy modeling to accomplish the integration of multi-sensor information and tool wear information. It generates fuzzy rules directly from the input-output data acquired from sensors, and provides high accuracy and high reliability of the tool wear prediction over a wide range of cutting conditions. The experimental results show its effectiveness and satisfactory comparisons relative to other artificial intelligence methods.     

Fuzzy classification in dynamic environments

The persistence and evolution of systems essentially depend on their adaptivity to new situations. As an expression of intelligence, adaptivity is a distinguishing quality of any system that is able to learn and to adjust itself in a flexible manner to new environmental conditions and such ability ensures self-correction over time as new events happen, new input becomes available, or new operational conditions occur. This requires self-monitoring of the performance in an ever-changing environment. The relevance of adaptivity is established in numerous domains and by versatile real-world applications. The present paper presents an incremental fuzzy rule-based system for classification purposes. Relying on fuzzy min–max neural networks, the paper explains how fuzzy rules can be continuously online generated to meet the requirements of non-stationary dynamic environments, where data arrives over long periods of time. The approach proposed to deal with an ambient intelligence application. The simulation results show its effectiveness in dealing with dynamic situations and its performance when compared with existing approaches.     

实体Bean容器管理持久化研究与实现

实体Bean是一种重要的J2EE应用组件,具有持久保存状态的特性。实体Bean容器是实体Bean的运行环境,持久化管理器是其中具体负责持久化的组件。本文研究了以关系数据库作为存储介质实现容器管理持久化的理论,提出了一种灵活高效的实现方法。该持久化管理器通过静态映射模型创建持久化方案,并创建动态模型以响应客户请求。在实体Bean容器并发访问控制机制的帮助下,该持久化管理器能够保证实体Bean高效可靠的运行。该持久化管理器和容器已经在中科院软件所自主研制的J2EE应用服务器OnceAS中得到实现。     

基于环绕智能的智能家居控制系统研究

绕智能(AmI)的概念体现在技术上是计算系统的高嵌入性、智能性和移动性，具体表现形式为嵌入式计算智能、网络通信和多通道传感等技术的智能环境。智能家居控制系统作为AmI的主要支撑子系统之一，它主要用于实现用户通过手持设备或联网电脑对冰箱、微波炉、电视机、空调、灯具等家用电器的控制和实时获取被控制家电的必要信息。该文重点讨论了基于AmI的智能家居控制系统的实现功能和体系结构以及在设计中解决的关键问题。     

基于RoBERTa-WWM的中文电子病历命名实体识别

电子病历(EMRs)中包含着丰富的信息,如临床症状、诊断结果和药物疗效.命名实体识别(Named Entity Recognition,NER)旨在从非结构化文本中抽取命名实体,这也是从电子病历中抽取有价值信息的初始步骤.本文提出一种基于预训练模型RoBERTa-WWM (A Robustly Optimized BE...     

CMOS-MEMS Capacitive Humidity Sensor

A high-sensitivity capacitive humidity sensor intended for use as part of a respirator end-of-service-life indicator system is presented. This paper reports a method for improving the sensitivity of integrated capacitive chemical sensors by removing the underlying substrate. The sensor is integrated with CMOS testing electronics using maskless postprocessing followed by ink-jet deposition of a sensitive polymer. Two different methods of depositing polymer, namely, capillary wicking and coating the top surface directly, were investigated. The sensors had measured sensitivities of 0.16% to 0.18% change in capacitance per percent relative humidity, which is the highest demonstrated for an integrated capacitive humidity sensor. Temperature sensitivity of the sensor, which is an important criterion for a sensor intended for a variety of different ambient conditions, was measured to be $0.07%/^{circ}hbox{C}$. The cross sensitivities to toluene and acetone, which are two common industrial solvents that are filtered by respirator cartridges, were measured to be $2.4 times 10^{-4}$ and $9.0 times 10^{-5}%/hbox{ppm}$, respectively.$hfill$ [2009-0165]      

Optimized data rate allocation for dynamic sensor fusion over resource constrained communication networks

This article presents a new method to solve a dynamic sensor fusion problem. We consider a large number of remote sensors which measure a common Gauss–Markov process. Each sensor encodes and transmits its measurement to a data fusion center through a resource restricted communication network. The communication cost incurred by a given sensor is quantified as the expected bitrate from the sensor to the fusion center. We propose an approach that attempts to minimize a weighted sum of these communication costs subject to a constraint on the state estimation error at the fusion center. We formulate the problem as a difference-of-convex program and apply the convex-concave procedure (CCP) to obtain a heuristic solution. We consider a 1D heat transfer model and a model for 2D target tracking by a drone swarm for numerical studies. Through these simulations, we observe that our proposed approach has a tendency to assign zero data rate to unnecessary sensors indicating that our approach is sparsity-promoting, and an effective sensor selection heuristic.     

基于COM的国民经济动员仿真系统研究

常规的手段和方法无法准确判断不同动员工作机制对国民经济动员工作的影响,因此,采用计算机仿真手段来研究动员工作机制是国民经济动员信息化的一个重要问题.首先,分析构建了开放式的、能够兼容多种组织形式和工作机制的动员组织元模型,并采用UML语言建立了国民经济动员仿真演练系统的模型.然后,利用组件对象模型技术(COM)可重用和互操作的特性,采用常规和动态方法对仿真通信与仿真逻辑接口进行封装,继而设计了适应对多种动员机制仿真需求的指挥实体组件和资源实体组件,最终实现了基于COM的国民经济动员仿真原型系统.实际仿真结果表明该仿真系统满足了复杂的国民经济动员仿真中较高的可重用性和扩展性要求,能够兼容多种动员工作机制的运行.