The Winning New Issues: A Case Study

Why do some early stage ventures perform remarkably well while others fail? Is there a fairly accurate way to predict which emerging growth business will become a high performing success story and which a low performing disaster? Is there a way for investors to increase the likelihood of investing in “winners” and decrease the likelihood of investing in “losers”? These are the central questions addressed in this article

The Formal and Informal Venture Capital Industry

This article examines the nature and activity of the formal and informal venture capital industry. Combined, there is a pool of nearly $100 billion in formal and informal venture capital in this country that is available for investment in emerging growth businesses. Although traditionally venture capital investments were targeted to early stage - and often "high tech" - companies, there has been a  growing  tendency  on  the part  of  venture  capitalists  to invest  in "low tech," later stage  businesses  as  well  as  in LBOs.  This article also examines the criteria used by venture  capitalists  in making  investment  decisions

Adaptive Screen Layouts Based on Viewer Proximity from Home Devices

Smart devices in the form of personal assistants are becoming more common and more dynamic. In addition to audibly exchanging information with a user via a mechanism such as a smart speaker, a personal assistant may now include a display to present useful ambient information to a user, such as time, weather, calendar information, or upcoming events. Techniques are described for adapting a screen layout of such a display based on proximity of a viewer relative to the display, allowing an effective and efficient presentation of the useful, ambient information

Smart-Voice Invocation of Scenes in Home-Automation Systems

Home environments are rapidly becoming more and more automated via the use of voice-recognizing personal assistants. Home-automation systems using a voice-recognizing personal assistant are capable of configuring smart devices of a home, such as lighting, security systems, or environmental controls, to particular operational settings which, when aggregated across multiple smart devices, constitute a particular scene. Techniques for a home-automation system to configure, or “set”, a scene using smart-voice invocation are described

Triggering information by context

With the increased availability of personal computers with attached sensors to capture their environment, there is a big opportunity for context-aware applications; these automatically provide information and/or take actions according to the user's present context, as detected by sensors. When wel l designed, these applications provide an opportunity to tailor the provision of information closely to the user's current needs. A sub-set of context-a ware applications are discrete applications, where discrete pieces of i nformation are attached to individual contexts, to be triggered when the user enters those contexts. The advantage of discrete applications is that authori ng them can be solely a creative process rather than a programming process: it can be a task akin to creating simple web pages. This paper looks at a general system that can be used in any discrete context- aware application. It propounds a general triggering rule, and investigates how this rule applies in practical applications

Designing Universally Accessible Networking Services for a Mobile Personal Assistant

At present, a tendency towards smaller computer sizes and at the same time increasingly inaccessible web content can be noted. Despite the worldwide recognized importance of Web accessibility, the lack of accessibility of web services has an increasingly negative impact on all users. In order to address this issue, W3C has released a recommendation on Mobile Web Best Practices, supplementary to the Web Content Accessibility Guidelines. This paper presents the design and prototype development of universally accessible networking services that fully comply with those standards. Validation and expert accessibility evaluation on the XHTML Basic prototypes present 100% compliance. The followed design process is presented in details, outlining general as well as specific issues and related solutions that may be of interest to other designers. The results will be further verified through user tests on implemented services

Hybrid On-Device Cloud Scheme for Re-Identification of Persons Based on Shared Embedding Gallery

Generally, the present disclosure is directed to a system of facial and/or person recognition via machine learning and Internet of Things (IoT). In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage a machine learning and IoT system or device to track and/or identify a person based on video images taken by one or more device(s). For example, a hybrid on-device and cloud scheme can enable locally-derived embeddings from multiple camera devices to be sent to a shared cloud space which can cluster the embeddings to generate a person model for a given person. Later, a camera device participating in the scheme can again detect a face and can match an embedding generated for the face against the shared gallery of person models to (potentially) re-identify the previously observed person

The MELD Programming Language: User Manual

This manual is divided into two parts, a tutorial introduction to the MELD programming language, and a language reference manual. The index spans both parts. A bibliography of MELD publications and technical reports is available in Appendix II. If you are interested in the decisions leading to the current design you should refer to this literature; the intent of this manual is to provide a working description of the current language and its implementation, and not an exposition of the language issues. Chapter 9 describes the language features which are not yet implemented

Smart Learning Services Based on Smart Cloud Computing

Context-aware technologies can make e-learning services smarter and more efficient since context-aware services are based on the user’s behavior. To add those technologies into existing e-learning services, a service architecture model is needed to transform the existing e-learning environment, which is situation-aware, into the environment that understands context as well. The context-awareness in e-learning may include the awareness of user profile and terminal context. In this paper, we propose a new notion of service that provides context-awareness to smart learning content in a cloud computing environment. We suggest the elastic four smarts (E4S)—smart pull, smart prospect, smart content, and smart push—concept to the cloud services so smart learning services are possible. The E4S focuses on meeting the users’ needs by collecting and analyzing users’ behavior, prospecting future services, building corresponding contents, and delivering the contents through cloud computing environment. Users’ behavior can be collected through mobile devices such as smart phones that have built-in sensors. As results, the proposed smart e-learning model in cloud computing environment provides personalized and customized learning services to its users