Over the last several years, computing systems based on adaptive learning with fine-grained parallel architectures have moved from obscurity to front-page prominence. These systems derive some of their novel architecture from ideas gleaned from biology, hence the name “neural network”. Although many of the ideas behind this field are not new, improved computing hardware, better understanding of learning algorithms, and limitations of traditional approaches have combined to renew interest in neural nets.
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Borland Delphi is known to be a great environment for the development of stand-alone and client-server applications on the Microsoft Windows platform. Its virtues range from full OOP support to visual development, in a unique combination of power and ease. However, the new frontier of development is now Internet programming. What has Delphi got to offer in this new context? Which are the features you can rely upon to build great Internet applications with Delphi? That’s what this paper intends to reveal. We’ll see that Delphi can be used:
• For direct socket and TCP/IP programming;
• In conjunction with third-party components that implement the most common Internet protocols, on the client or the server side;
• To produce HTML pages on the server side, with the WebBroker and Internet Express architectures;
• As well as to work with Microsoft’s core technologies, including MTS, COM, ASP, and ActiveX.
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Application server platforms are the most important category of application platform software for most enterprises. An application server platform is infrastructure software for building Web and composite applications and, increasingly, applications based on service-oriented architecture (SOA) design principles. An application server platform integrates an application server, which manages user requests, data access, and business logic, with portal servers and integration/business process management (BPM) servers — and often additional features, as well.
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Adaptive algorithms are an important technique to achieve portable high performance. They choose among solution methods and optimizations according to expected performance on a particular machine. Grid environments make the adaptation problem harder, because the optimal decision may change across runs and even during runtime. Therefore, the performance model used by an adaptive algorithm must be able to change decisions without high overhead. In this paper, we present work that is modifying previous research into rapid performance modeling to support adaptive grid applications through sampling and high granularity modeling. We also outline preliminary results that show the ability to predict differences in performance among algorithms in the same program.
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Texture caching systems are designed to overcome the texture budget limitations of 3D games. Only the textures required to display the current scene are held in RAM. When new textures need to appear in the scene, they are loaded from a larger and slower repository, or they are dynamically generated.
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Solutions | J2EE to .NET 2.0 Migration
Since almost two years, there has been an active debate over the endurance of the two giant enterprise platforms, Microsoft‘s .NET and Sun‘s Java 2 Platform, Enterprise Edition (J2EE). Which technology would emerge as the leading platform for developing new web applications?

Now that the combat has settled down a bit, each platform has managed to capture a substantial share of market for itself. In fact, many organizations have arranged for a strategy for one or the other of these frameworks. But many (e.g. those which have large investments in the legacy systems) are still evaluating the merits of the two platforms. The IT personnel in those businesses is questioning as to what extent would choosing .NET or J2EE influence their host strategy, etc.
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Wireless systems have evolved to successfully penetrate the world of personal communications, where virtually all people can talk as needed on-demand with a feature rich and flexible set of alternatives. This world of people talking is now being complemented with a wireless world of all things “talking” – in other words, all things are becoming wireless. As these new systems continue to evolve to meet their best-fit applications in the enterprise, matching each one’s unique characteristics to the application is not always clear to the prospective end user or even to a providing system integrator.
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There is an ongoing information war raging in the software world. Despite free software developers’ best efforts, new proprietary software continues to proliferate. Improved techniques must be developed to reverse engineer efficiently closed data formats so that free, interoperable solutions can be deployed under Linux.

Software reverse engineering occurs on various levels. It may be necessary to study a piece of poorly written, poorly commented code developed in a high-level language such as C++ and understand what the original program was supposed to accomplish. It may also be necessary to disassemble a program that has been compiled into machine language and express it as a higher-level language. In doing this, the underlying algorithms can eventually be expressed as higher-level concepts in a human language. After obtaining an algorithmic description via reverse engineering, the algorithm can be reimplemented for any language on any computing platform.
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