本刊以七大战略性新兴产业——节能环保、新一代信息技术、生物、高端装备制造、新能源、新材料、新能源汽车为研究重点，关注国家高层和各部委的动态，剖析国家和地方的新兴产业政策。本刊设有政策导读、领导讲话、七大战略性新兴产业本周国内外行业动态和重点企业新闻、投资专题四大板块，能够实时监测新兴产业和重点企业动态，把握新兴产业发展方向，研究发展重点，寻求发展机遇。

EMIS consists of hardware, software, and services that help in providing energy information to users such as building energy managers, financial managers, facility managers, and power utilities. The major elements of this system include hardware tools such as meters, sub-meters, and sensors and software tools such as data recording and other energy management software. As EMIS is emerging as a tool for better decision making for its users, the demand for EMISs is expected to remain moderate. EMIS can also be referred to as a systematic process for continual improvement of energy performance.

An industrial automation control system helps organizations, especially those in process and discrete industries, optimize their business operations by effectively controlling the production process. Industrial automation systems include four major types: DCS, PLC, MES, and SCADA. These automation control systems are widely used by different process and discrete industries including the Oil and Gas, Energy and Power, Pharmaceutical, Pulp and Paper, Aerospace, Automotive, Shipbuilding, Machinery Manufacturing, Consumer Durables, and Food and Beverage industries. In addition, they help companies by providing real-time information, which improves the efficiency of the entire plant and thereby reduces the total cost of ownership.

The EDT technologies help to analyze sample elements that are collected from explosives and other hazardous products that could create a threat to human life. EDT technologies analyze sample elements and compare this with an internal database to generate the alert report for use by security and airport authorities, among others. Thus, several security forces across the world prefer EDT technologies to prevent various terrorist activities that could cause heavy loss of life and property.

Web interactions usually require the exchange of personal and confidential information for a variety of purposes, including enabling business transactions and the provisioning of services. A key issue affecting these interactions is the lack of trust and control on how data is going to be used and processed by the entities that receive this data. In the traditional world, this issue is addressed by using contractual agreements that are signed by the involved parties. This could be done electronically as well but there is currently a major gap between the definition of legal contracts, regulating the sharing of data and the software infrastructure required to support and enforce them. How to ensure that legal contracts can be actually enforced by the underlying IT infrastructure? How to ensure that a potentially enforceable version of the contract corresponds to the legal version of the contract? This article describes our work to address this gap through the usage of electronic Data Sharing Agreements (e-DSA). e-DSAs can be formally defined and analysed to identify inconsistencies and contradictory policies/constraints; they can then be deployed within the IT infrastructure and enforced. We specifically show how this can be achieved in a cloud scenario, where e-DSAs are enforced via policy enforcement capabilities developed in the UK EnCoRe [6] collaborative project.

Call a bipartite graph G=(X,Y;E) balanced when |X|=|Y| Given a balanced bipartite graph G with edge costs, the assignment problem asks for a perfect matching in G of minimum total cost. The Hungarian Method can solve assignment problems in time space O(m) and time O(mn + n^2 log n), where n :=|X|=|Y| and m :=|E|. If the edge weights are integers bounded in magnitude by C > 1, then algorithms using weight scaling, such as that of Gabow and Tarjan, can lower the time to O(m sqrt(n) log(nC)).There are important applications in which G is unbalanced, with not equal to and we require a min-cost matching in G of size r := min(|X|, |Y|) or, more generally, of some specified size s <= r. The Hungarian Method extends easily to find such a matching in time O(ms + s^2 log r), but weight-scaling algorithms do not extend so easily. We introduce new machinery that allows us to find such a matching in time O(m sqrt(s) log(sC)) via weight scaling. Our results provide some insight into the design space of efficient weight-scaling matching algorithms.These ideas are presented in greater depth in HPL-2012-40R1.

This document is an official, public delivery of the UK collaborative project EnCoRe (Ensuring Consent and Revocation), coordinated by HP Labs. It describes the final EnCoRe Technical Architecture and solutions to support dynamic consent (whereby data subjects provide or amend informed consent - potentially in a fine- grained way - to govern access and use of their confidential and personal data), policy enforcement and controlled information sharing within and across organizational boundaries. It takes into account technical, legal, user and social requirements. This can include business-specific requirements, and education of end users about privacy risks. This work has been led by HP Labs. HP Labs designed and architected a technical solution to: enable end-users (data subjects) to have better control over their data when (and even after) disclosing this to service providers; enable organisations to enforce authorization and obligation policies when accessing, processing and disclosing data; enable the tracking of data whereabouts; support accountable information- sharing across organizations by means of sticky policy mechanisms and transparency (including notification mechanisms) to the data subject. The EnCoRe architecture and approach has been validated in three case studies. HP Labs has also built a reference implementation of the EnCoRe Architecture, referred to as the HPL EnCoRe Service Framework. This is a generic framework that can be easily configured to different business-specific scenarios. It uses state-of-the-art technology to provide the key EnCoRe capabilities by means of composable, secure services. A fully working prototype and a demonstrator are available. The EnCoRe Service Framework is also available for further exploitation opportunities by HP businesses, customers and business partners. We are currently exploring the opportunity to release a core subset of the EnCoRe Service Framework as Open Source software.

Cloud computing refers to the underlying infrastructure for an emerging model of service provision that has the advantage of reducing cost by sharing computing and storage resources, combined with an on-demand provisioning mechanism relying on a pay- per-use business model. These new features have a direct impact on information technology (IT) budgeting but also affect traditional security, trust and privacy mechanisms. The advantages of cloud computing - its ability to scale rapidly, store data remotely, and share services in a dynamic environment - can become disadvantages in maintaining a level of assurance sufficient to sustain confidence in potential customers. Some core traditional mechanisms for addressing privacy (such as model contracts) are no longer flexible or dynamic enough, so new approaches need to be developed to fit this new paradigm. In this chapter we assess how security, trust and privacy issues occur in the context of cloud computing and discuss ways in which they may be addressed.

We present the results of a multi-phase study to optimize strategies for generating personalized article recommendations at the Forbes.com web site. In the first phase we compared the performance of a variety of recommendation methods on historical data. In the second phase we deployed a live system at Forbes.com for five months on a sample of 82,000 users, each randomly assigned to one of 20 methods. We analyze the live results both in terms of click- through rate (CTR) and user session lengths. The method with the best CTR was a hybrid of collaborative-filtering and a content-based method that leverages Wikipedia-based concept features, post- processed by a novel Bayesian remapping technique that we introduce. It both statistically significantly beat decayed popularity and increased CTR by 37%.

Consider a bipartite graph G = (X,Y;E) with real-valued weights on its edges, and suppose that G is balanced, with |X| = |Y|, The assignment problem asks for a perfect matching in G of minimum total weight. Assignment problems can be solved by linear programming, but fast algorithms have been developed that exploit their special structure. The famous Hungarian Method runs in time O(mn + n^2 log n), where n :=|X|=|Y| and m :=|E|. If the edge weights are integers bounded in absolute value by some constant C > 1, then algorithms based on weight scaling, such as that of Gabow and Tarjan, can lower the time bound to O(m sqrt(n) log(nC)).But the graphs that arise in practice are frequently unbalanced, with r := min(|X|, |Y|) less than n := max(|X|, |Y|). Any matching in an unbalanced graph G has size at most r, and hence must leave at least n - r vertices in the larger part of G unmatched. We might want to find a matching in G of size r and of minimum weight, given that size. We can reduce this problem to finding a minimum-weight perfect matching in a balanced graph G' built from two copies of G. If we use such a doubling reduction when r << n, however, we get no benefit from r being small.

Brain-controlled prostheses have the potential to improve the quality of life of a large number of paralyzed persons by allowing them to control prosthetic limbs simply by thought.An essential requirement for natural use of such neural prostheses is that the user should be provided with somatosensory feedback from the artificial limb. This can be achieved by electrically stimulating small populations of neurons in the cortex; a process known as cortical microstimulation. This dissertation describes the development of novel technologies for experimental neuroscience and their use to explore the neural and perceptual effects of cortical microstimulation in rodents.