Provided is a system for building and validating an application (including e.g., various software versions and revisions, programming languages, code segments, among other examples) without any scripting required by a system user. In one embodiment, an SDLC system is configured to construct a build and test environment, by automatically analyzing a submitted project. The build environment is configured to assemble existing user code, for example, to generate an application to test. Code building can include any one or more of code compilation, assembly, and code interpretation. The system can include a user interface provided to clients, users, and/or customer environments to facilitate user interaction and control of build and test validation. The system can accept user specification of configurations that controls the way the system runs the user's tests. The system can also provide flexible billing models for different customers.

System of distributed software quality improvement

The Wireless Integrated Network Sensor Next Generation (WINS NG) nodes provide distributed network and Internet access to sensors, controls, and processors that are deeply embedded in equipment, facilities, and the environment. The WINS NG network is a new monitoring and control capability for applications in transportation, manufacturing, health care, environmental monitoring, and safety and security. The WINS NG nodes combine microsensor technology, low power distributed signal processing, low power computation, and low power, low cost wireless and/or wired networking capability in a compact system. The WINS NG networks provide sensing, local control, remote reconfigurability, and embedded intelligent systems in structures, materials, and environments.

Apparatus for compact internetworked wireless integrated network sensors (WINS)

Method for internetworked hybrid wireless integrated network sensors (WINS)

A system and method of scheduling tasks, comprising receiving activity and performance data from registers or storage locations maintained by hardware and an operating system; storing calibration coefficients associated with the activity and performance data; computing an energy dissipation rate based on at least the activity and performance data; and scheduling tasks under the operating system based on the computed energy dissipation rate.

Apparatus and method for efficient estimation of the energy dissipation of processor based systems

A system and method for recognizing data access patterns in large data sets and for preloading a cache based on the recognized patterns is provided. In some embodiments, the method includes receiving a data transaction directed to an address space and recording the data transaction in a first set of counters and in a second set of counters. The first set of counters divides the address space into address ranges of a first size, whereas the second set of counters divides the address space into address ranges of a second size that is different from the first size. One of a storage device or a cache thereof is selected to service the data transaction based on the first set of counters, and data is preloaded into the cache based on the second set of counters.

Cache optimization technique for large working data sets

Traditionally, providing parallel processing within a multi-core system has been very difficult. Here, however, a system in provided where serial source code is automatically converted into parallel source code, and a processing cluster is reconfigured “on the fly” to accommodate the parallelized code based on an allocation of memory and compute resources. Thus, the processing cluster and its corresponding system programming tool provide a system that can perform parallel processing from a serial program that is transparent to a user.

High-performance, scalable mutlicore hardware and software system

An example embodiment provides a resizer in an image processing system. The resizer includes a receiving module that receives pixel data representative of an image. A triple line buffer is coupled to the receiving module that stores the pixel data in response to a write control signal from control logic. The triple line buffer is operated as a circular buffer. The resizer further includes a resizer core that reads pixel data from the triple line buffer in response to a read control signal from the control logic. The pixel data is replicated to up-scale the image vertically according to a vertical up-scale ratio such that the resizer achieves a maximum input data rate and also eliminates an overflow condition in the resizer. The vertical up-scale ratio is a fraction.

System and method for maintaining maximum input rate while up-scaling an image vertically

A system includes multiple master devices and at least one memory refresh scheduler. When a master device needs higher priority for memory access, the master device sends a dynamic priority signal to the memory refresh scheduler and in response, the memory refresh scheduler changes its policy for issuing refresh commands.

Dynamic priority management of memory access

Master circuits having dynamic priority leads coupled with memory controller

An apparatus is provided. The apparatus includes a message bus and a control node (1406). The control node (1406) has a host interface (1405), a plurality of partition message pipelines (6134- 1 to 6134-R, 6136-1 to 6136-R, and 6138-1 to 6138-R), a load/store message pipeline (6134- (R+2), 6136-(R+2), and 6138-(R+2)), a message queue (6102), a sequential processor (6140), and a control node memory (6114). The host interface (1405) is configured to communicate with a host processor. The plurality of partition message pipelines (6134-1 to 6134-R, 6136-1 to 6136-R, and 6138-1 to 6138-R) are each coupled to the message bus. The load/store message pipeline (6134-(R+2), 6136-(R+2), and 6138-(R+2)) is coupled to the message bus. The message queue (6102) is coupled to each partition message pipeline (6134-1 to 6134-R, 6136-1 to 6136-R, and 6138-1 to 6138-R), the load/store message pipeline (6134-(R+2), 6136-(R+2), and 6138-(R+2), and the host interface (1405). The sequential processor (6140) is coupled to each partition message pipeline (6134-1 to 6134-R, 6136-1 to 6136-R, and 6138-1 to 6138-R) and the load/store message pipeline (6134-(R+2), 6136-(R+2), and 6138-(R+2)), and the control node memory (6114) is coupled to the host interface (1405) and the message queue (6102).

Control node for a processing cluster

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Stephen Busch

Author Tools

Chat about Author