4 resultados para First in First out (FIFO)

em Boston University Digital Common


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Recent measurement based studies reveal that most of the Internet connections are short in terms of the amount of traffic they carry (mice), while a small fraction of the connections are carrying a large portion of the traffic (elephants). A careful study of the TCP protocol shows that without help from an Active Queue Management (AQM) policy, short connections tend to lose to long connections in their competition for bandwidth. This is because short connections do not gain detailed knowledge of the network state, and therefore they are doomed to be less competitive due to the conservative nature of the TCP congestion control algorithm. Inspired by the Differentiated Services (Diffserv) architecture, we propose to give preferential treatment to short connections inside the bottleneck queue, so that short connections experience less packet drop rate than long connections. This is done by employing the RIO (RED with In and Out) queue management policy which uses different drop functions for different classes of traffic. Our simulation results show that: (1) in a highly loaded network, preferential treatment is necessary to provide short TCP connections with better response time and fairness without hurting the performance of long TCP connections; (2) the proposed scheme still delivers packets in FIFO manner at each link, thus it maintains statistical multiplexing gain and does not misorder packets; (3) choosing a smaller default initial timeout value for TCP can help enhance the performance of short TCP flows, however not as effectively as our scheme and at the risk of congestion collapse; (4) in the worst case, our proposal works as well as a regular RED scheme, in terms of response time and goodput.

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Supported housing for individuals with severe mental illness strives to provide the services necessary to place and keep individuals in independent housing that is integrated into the community and in which the consumer has choice and control over his or her services and supports. Supported housing can be contrasted to an earlier model called the “linear residential approach” in which individuals are moved from the most restrictive settings (e.g., inpatient settings) through a series of more independent settings (e.g., group homes, supervised apartments) and then finally to independent housing. This approach has been criticized as punishing the client due to frequent moves, and as being less likely to result in independent housing. In the supported housing model (Anthony & Blanch, 1988) consumers have choice and control over their living environment, their treatment, and supports (e.g., case management, mental health and substance abuse services). Supports are flexible and faded in and out depending on needs. Results of this systematic review of supported housing suggest that there are several well-controlled studies of supported housing and several studies conducted with less rigorous designs. Overall, our synthesis suggests that supported housing can improve the living situation of individuals who are psychiatrically disabled, homeless and with substance abuse problems. Results show that supported housing can help people stay in apartments or homes up to about 80% of the time over an extended period. These results are contrary to concerns expressed by proponents of the linear residential model and housing models that espoused more restrictive environments. Results also show that housing subsidies or vouchers are helpful in getting and keeping individuals housed. Housing services appear to be cost effective and to reduce the costs of other social and clinical services. In order to be most effective, intensive case management services (rather than traditional case management) are needed and will generally lead to better housing outcomes. Having access to affordable housing and having a service system that is well-integrated is also important. Providing a person with supported housing reduces the likelihood that they will be re-hospitalized, although supported housing does not always lead to reduced psychiatric symptoms. Supported housing can improve clients’ quality of life and satisfaction with their living situation. Providing supported housing options that are of decent quality is important in order to keep people housed and satisfied with their housing. In addition, rapid entry into housing, with the provision of choices is critical. Program and clinical supports may be able to mitigate the social isolation that has sometimes been associated with supported housing.

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A novel approach for real-time skin segmentation in video sequences is described. The approach enables reliable skin segmentation despite wide variation in illumination during tracking. An explicit second order Markov model is used to predict evolution of the skin-color (HSV) histogram over time. Histograms are dynamically updated based on feedback from the current segmentation and predictions of the Markov model. The evolution of the skin-color distribution at each frame is parameterized by translation, scaling and rotation in color space. Consequent changes in geometric parameterization of the distribution are propagated by warping and resampling the histogram. The parameters of the discrete-time dynamic Markov model are estimated using Maximum Likelihood Estimation, and also evolve over time. The accuracy of the new dynamic skin color segmentation algorithm is compared to that obtained via a static color model. Segmentation accuracy is evaluated using labeled ground-truth video sequences taken from staged experiments and popular movies. An overall increase in segmentation accuracy of up to 24% is observed in 17 out of 21 test sequences. In all but one case the skin-color classification rates for our system were higher, with background classification rates comparable to those of the static segmentation.

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Accurate head tilt detection has a large potential to aid people with disabilities in the use of human-computer interfaces and provide universal access to communication software. We show how it can be utilized to tab through links on a web page or control a video game with head motions. It may also be useful as a correction method for currently available video-based assistive technology that requires upright facial poses. Few of the existing computer vision methods that detect head rotations in and out of the image plane with reasonable accuracy can operate within the context of a real-time communication interface because the computational expense that they incur is too great. Our method uses a variety of metrics to obtain a robust head tilt estimate without incurring the computational cost of previous methods. Our system runs in real time on a computer with a 2.53 GHz processor, 256 MB of RAM and an inexpensive webcam, using only 55% of the processor cycles.