媒体资产管理系统设计与实现

媒体资产建设是一项关系到电视台未来综合发展的关键任务，一个好的媒体资产管理系统能极大地提高电视节目制作的效率和质量，同时有效地降低媒体资产管理的成本。提出了一套完整的媒体资产管理解决方案，它使用MPEG—2格式统一存储视频数据，采用能够实现高可扩展性的以存储为中心的存储体系，提供了将关键字检索、静止图像浏览以及低码率活动图像浏览相结合的检索系统，实现了以非线性编辑系统为核心的采编播一体化系统。     

Circular interpretation of bijective transformations in lossless watermarking for media asset management

The need for reversible or lossless watermarking methods has been highlighted in the literature to associate subliminal management information with losslessly processed media and to enable their authentication. The paper first analyzes the specificity and the application scope of lossless watermarking methods. It explains why early attempts to achieve reversibility are not satisfactory. They are restricted to well-chosen images, strictly lossless context and/or suffer from annoying visual artifacts. Circular interpretation of bijective transformations is proposed to implement a method that fulfills all quality and functionality requirements of lossless watermarking. Results of several bench tests demonstrate the validity of the approach.     

Dismountable media management in tertiary storage systems

We describe an adaptive algorithm for tertiary storage media mount management. This predictive longest next reference mount management algorithm attempts to approximate the optimal page replacement policy, OPT     

Semantic technologies for open interaction systems

Open interaction systems play a crucial role in agreement technologies because they are software devised for enabling autonomous agents (software or human) to interact, negotiate, collaborate, and coordinate their activities in order to establish agreements and manage their execution. Following the approach proposed by the recent literature on agent environments those open distributed systems can be efficiently and effectively modeled as a set of correlated physical and institutional spaces of interaction where objects and agents are situated. In our view in distributed open systems, spaces are fundamental for modeling the fact that events, actions, and social concepts (like norms and institutional objects) should be perceivable only by the agents situated in the spaces where they happen or where they are situated. Institutional spaces are also crucial for their active functional role of keeping track of the state of the interaction, and for monitoring and enforcing norms. Given that in an open distributed and dynamic system it is fundamental to be able to create and destroy spaces of interaction at run-time, in this paper we propose to create them using Artificial Institutions (AIs) specified at design time. This dynamic creation is a complex task that deserves to be studied in all details. For doing that, in this paper, we will first define the various components of AIs and spaces using Semantic Web Technologies, then we will describe the mechanisms for using AIs specification for realizing spaces of interaction. We will exemplify this process by formalizing the components of the auction Artificial Institution and of the spaces created for running concrete auctions.     

BP''s multi-enterprise asset management system

BP is one of the largest energy companies in the world with 2003 revenues of $233 billion. In this paper, we analyse its use of an innovative ‘multi-enterprise asset management system’ that supports and enables the asset management strategy of BP's exploration and production division on the UK continental shelf (UKCS). The analysis focuses on how BP connects its business processes with over 1500 suppliers to co-ordinate the maintenance, operation and repair of specialised exploration and production equipment. The systems strategy is novel because it takes the enterprise computing concept and implements it across organisational boundaries—hence the term ‘multi-enterprise system’. This use of a shared system with all of its suppliers is distinctive from the most common way of connecting with economic partners which is to use shared data systems based on common data standards and communication technologies such as EDI and more recently XML-based systems within vertical industries such as RosettaNet. The design of the multi-enterprise system is based on a sophisticated business process management system called Maximo and this is used to illustrate the systems design aspect of the overall information system in the broader contexts of business strategy and information technology infrastructure.     

Semantic association enhancement transformer with relative position for image captioning

Transformer-based architectures have shown encouraging results in image captioning. They usually utilize self-attention based methods to establish the semantic association between objects in an image for predicting caption. However, when appearance features between the candidate object and query object show weak dependence, the self-attention based methods are hard to capture the semantic association between them. In this paper, a Semantic Association Enhancement Transformer model is proposed to address the above challenge. First, an Appearance-Geometry Multi-Head Attention is introduced to model a visual relationship by integrating the geometry features and appearance features of the objects. The visual relationship characterizes the semantic association and relative position among the objects. Secondly, a Visual Relationship Improving module is presented to weigh the importance of appearance feature and geometry feature of query object to the modeled visual relationship. Then, the visual relationship among different objects is adaptively improved according to the constructed importance, especially the objects with weak dependence on appearance features, thereby enhancing their semantic association. Extensive experiments on MS COCO dataset demonstrate that the proposed method outperforms the state-of-the-art methods.

     

Supervision and hybrid control accommodation for water asset management

The paper presents a supervision and hybrid control accommodation strategy applied to the online water asset management of a canal. This strategy is organized in a conceptual framework based on two principal operating modules. The discharge supervision module carries out the monitoring of discrepancies between the expected and measured values and makes the resource state diagnosis. The hybrid control accommodation module allows the setpoint calculation to be given according to the detected discrepancies, the resource state and the time delays. The design method of a water asset management of a canal network is presented and the strategy performance is evaluated in presence of the usual disturbances of a canal showing its effectiveness.     

Semantic annotation of narrative media objects

This paper addresses the annotation of the narrative features of media objects. Based on a relevant narratological and computational background, we introduce an ontology?Cbased model called Drammar, an annotation schema for the narrative features of media objects based on Drammar and a software tool, Cinematic, for annotating these objects and validating the annotation. Annotated media objects can also be automatically edited into sequences, with the twofold goal of testing the validity of the annotation??through the reconstruction of the baseline sequence??and exploring the possibility of alternative sequences. The software tool encodes both the narrative model and the annotation itself in ontological format, and relies on external ontologies for representing world knowledge and limit the arbitrariness of the annotation. The paper opens the way to the design of a general annotation schema for narrative multimedia with the long?Cterm goal of building large corpora of annotated video material and of bridging the gap between the low?Clevel signal analysis and the high?Clevel semantic representation of the narrative content of the media objects. Finally, the paper illustrates a few projects elaborated with the Drammar annotation and the Cinematic tool, with purposes of artistic research and cross?Cmedia analysis, that provide an empirical validation of the annotation process.     

Getting started with IT asset management

Asset management is a combination of tools and processes that proactively manage a company's entire asset base from a cost, contractual, support, and inventory viewpoint. This definition stems from the basics of a company's business functions; several common threads lead to a fundamental definition. At the root of business you find a basic equation: assets+people=profits. Since this equation underlies basic business fundamentals, business managers must support each aspect of the equation, and asset management tools and processes must address each area. Companies must possess certain competencies to maximize their effectiveness in each area. Ownership data allows companies to look at their asset base from a strategic business perspective. Help desk and deployment tools remain tactical tools to solve today's problems. Separately or together they do not constitute asset management. To truly manage assets we need all three competencies. Help desks support people and deployment tools support the assets. Ownership management tools support the process by maximizing asset use while lowering the cost of ownership     

运营商安全资产管理技术研究

目前运营商资产管理主要为传统意义上的固定资产管理,资产的安全状况、安全基线等安全信息缺失严重,无法应对日益严峻的安全形势.本文从资产脆弱性、资产威胁、系统定级、安全评估、KPI考核等多个层面,探讨运营商资产安全管理如何实现,安全资产管理系统如何设计.     

企业固定资产信息化管理体系

核电企业具有高投入、高产出的特点。高投入转化为价值高、数量大、种类多的固定资产,高产出的前提是机组的安全运行,这就要求对企业已有的固定资产进行更新改造,同时不断扩大对新的固定资产的投入。因此,如何对固定资产进行有效地管理和控制,就成为大亚湾核电站保证安全运行、提高经济和管理效益的重要手段之一。对于固定资产管理体系的重要组成部分——生产离线固定资产的信息系统的开发和实施也成为企业固定资产信息化管理体系的重要内容之一。     

问渠哪得清如许,为有源头活水来——数据库管理是媒体资产管理系统运转的保障

系统建设目标是收集保存电视音视频素材、开发与再利用节目资料,同时收集和保护广播媒体资源。系统的建成满足了重庆台对历史的、现实的具有保存价值的资料进行收集、整理、存储和再利用的需求,同时为多种电视广播相关业务提供支持。     

Semantic oriented ontology cohesion metrics for ontology-based systems

Ontologies play a core role to provide shared knowledge models to semantic-driven applications targeted by Semantic Web. Ontology metrics become an important area because they can help ontology engineers to assess ontology and better control project management and development of ontology based systems, and therefore reduce the risk of project failures. In this paper, we propose a set of ontology cohesion metrics which focuses on measuring (possibly inconsistent) ontologies in the context of dynamic and changing Web. They are: Number of Ontology Partitions (NOP), Number of Minimally Inconsistent Subsets (NMIS) and Average Value of Axiom Inconsistencies (AVAI). These ontology metrics are used to measure ontological semantics rather than ontological structure. They are theoretically validated for ensuring their theoretical soundness, and further empirically validated by a standard test set of debugging ontologies. The related algorithms to compute these ontology metrics also are discussed. These metrics proposed in this paper can be used as a very useful complementarity of existing ontology cohesion metrics.     

Neural network applications in financial asset management

Modelling of financial systems has traditionally been done in partial equilibrium. Such models have been very useful in expanding our understanding of the capital markets; nevertheless, many empirical financial anomalies have remained unexplainable. It is possible that this may be due to the partial equilibrium nature of these models. Attempting to model financial markets in a general equilibrium framework still remains analytically intractable. Because of their inductive nature, dynamical systems such as neural networks can bypass the step of theory formulation, and they can infer complex non-linear relationships between input and output variables. Neural networks have now been applied to a number of live systems, and have demonstrated far better performance than conventional approaches. This paper reviews the state-of-the-art in financial modelling using neural networks, and describes typical applications in key areas of forecasting, classification and pattern recognition. The applications cover areas such as asset allocation, foreign exchange, stock ranking and bond trading.Formerly, with Department of Computer Science, University College London, Gower Street, London WC1 6BT, UK.     

Graceful extensibility in asset management: extending the capacity to adapt in managing cyber-physical railway systems

Cognition, Technology & Work - Graceful extensibility has been recently introduced and can be defined as the ability of a system to extend its capacity to adapt when surprise events challenge...     

Semantic query optimization for query plans of heterogeneousmultidatabase systems

New applications of information systems need to integrate a large number of heterogeneous databases over computer networks. Answering a query in these applications usually involves selecting relevant information sources and generating a query plan to combine the data automatically. As significant progress has been made in source selection and plan generation, the critical issue has been shifting to query optimization. This paper presents a semantic query optimization (SQO) approach to optimizing query plans of heterogeneous multidatabase systems. This approach provides global optimization for query plans as well as local optimization for subqueries that retrieve data from individual database sources. An important feature of our local optimization algorithm is that we prove necessary and sufficient conditions to eliminate an unnecessary join in a conjunctive query of arbitrary join topology. This feature allows our optimizer to utilize more expressive relational rules to provide a wider range of possible optimizations than previous work in SQO. The local optimization algorithm also features a new data structure called AND-OR implication graphs to facilitate the search for optimal queries. These features allow the global optimization to effectively use semantic knowledge to reduce the data transmission cost. We have implemented this approach in the PESTO (Plan Enhancement by SemanTic Optimization) query plan optimizer as a part of the SIMS information mediator. Experimental results demonstrate that PESTO can provide significant savings in query execution cost over query plan execution without optimization     

Semantic network management for next‐generation networks

To accommodate the proliferation of heterogeneous network models and protocols, the use of semantic technologies to enable an abstract treatment of networks is proposed. Network adapters are employed to lift network specific data into a semantic representation. Semantic reasoning integrates the disparate network models and protocols into a common data model by making intelligent inferences from low‐level network and device details. Automatic discovery of new devices, monitoring of device state, and invocation of device actions in a generic fashion that is agnostic of network types is enabled. A prototype system called SNoMAC is described that employs the proposed approach operating over UPnP, TR‐069, and heterogeneous sensors. These sensors are integrated by means of a sensor middleware named SIXTH that augments the capabilities of SNoMAC to allow for intelligent management and configuration of a wide variety of sensor devices. A major benefit of this approach is that the addition of new models, protocols, or sensor types merely involves the development of a new network adapter based on an ontology. Additionally, the semantic representation of the network and associated data allows for a variety of client interfaces to facilitate human input to the management and monitoring of the system.