Effects of CF4 plasma treatment on the moisture uptake,diffusion, and WVTR of poly(ethylene terephthalate) flexible films

We studied the effects of CF₄ plasma surface treatment on moisture uptake, diffusion, and the water-vapor-transmission-rate (WVTR) of poly(ethylene terephthalate) (PET) films using a CF₄ plasma generated by a radio-frequency (13.56 MHz) reactive ion etcher at 60 W. After CF₄ plasma treatment, moisture uptake in PET film was reduced with increasing treatment time due to (1) lower adsorption of water molecules onto the hydrophobic surface, as confirmed by contact angle measurement and XPS analysis, and (2) reduced diffusion coefficient through the denser fluorinated top-layer as detected by XRR. In addition, the WVTR of untreated PET is found to be 2.7 g/m²/day, while a significant reduction (84%) of WVTR to 0.43 g/m²/day, is achieved for CF₄ plasma-treated PET film (60 W, 15 min), which alters the surface hydrophobicity (~ 107°) and simultaneously builds a denser, fluorinated top-layer (47 nm). The surface fluorinated layer has a diffusivity of to 8.7 × 10^?12 m²/s and a WVTR of ~ 1.0 × 10^?4 g/m²/day based on a series resistance model.     

Adaptive frame synchronization for surveillance system across a heterogeneous network

As mobile techniques are booming, the surveillance function is extended from a stationary mode to a mobile mode. In a heterogeneous network environment, cameras and viewers are located in different networks so that frame synchronization may span across diverse network domains with different transmission capabilities. The mismatch of transmission capabilities may affect the viewing continuity and playback liveness between cameras and viewers. In the article, we propose an adaptive frame synchronization mechanism for frame capturing at cameras based on the network condition to improve the frame synchronization between two sides across a heterogeneous network. Based on a brief theoretical analysis of the asynchronization effect for video communication in a heterogeneous network environment, the proposed adaptive pause time mechanism can be an effective solution to relieve the asynchronization effect in the unmatched transmission rate situation. The evaluation results show that the proposed scheme can achieve a shorter time delay between the captured frames at the camera site and the viewer site.     

Deploying a massively multiplayer online game with a low-latency server infrastructure

The massively multiplayer online game (MMOG) industry has become an important e-commerce segment due to its impact on the economy. A MMOG requires the deployment of dozens to hundreds of n-tiered servers around the world to support millions of concurrent players. A slow response time stemming from an ill-designed network infrastructure could render the game noncompetitive in the marketplace. This study proposes a mixed integer program aimed at identifying nodes on a broadband provider’s backbone network for hosting a MMOG so that the game distributor’s revenue is maximized while meeting the throughput, the latency, and the budget requirements. A heuristic for solving the model is presented with an experiment to measure its solution quality and speed.     

A new logic correlation rule for HIV-1 protease mutation

Mining association rule in a large database is a technique for finding relations among attributes. In the last decade, most studies have been devoted to boost the efficiency, but few of them have been concentrated on the analysis of logic correlation among variables. Furthermore, mining association rules in a large database, when applied on a bio-sequence data set, is generally medically irrelevant and difficult to analyze. In this paper, a pre and post-processing approach through discovering a logic correlation rule by combining Apriori-based method and Boolean function simplification technique called Apriori_BFS method is presented. The objective of the proposed method is to effectively reduce the number of rules and present an integration logic correlation rule to readers. The experiment was conducted by using a real-world case, the HIV Drug Resistance Database, and its results unveil that the proposed method, Apriori_BFS, can not only present the logic correlation among variables but also provide more condensed rules than the Apriori method alone.     

Network Bandwidth-aware job scheduling with dynamic information model for Grid resource brokers

A resource broker with a user-friendly interface for job submission developed on a platform constructed using the Globus toolkit is proposed. The broker employs a domain-based network information model and dynamic version to measure network statuses, and also monitors and collects resource statuses and network-related information as the basis of its brokerage. A network bandwidth-aware job scheduling algorithm for brokering suitable Grid resources to communication-intensive jobs based on improving and preserving the advantages of our previously developed network information model is also proposed. Using timely information, the resource broker effectively matches Grid resources and user requests, thus improving job execution efficiency.     

First branchial cleft anomalies: report of 12 cases

First branchial cleft anomalies account for only 1-8% of all branchial anomalies. Several classification systems have been proposed to aid in the diagnosis of these defects. We present a series of 12 patients with first branchial cleft anomalies classified according to anatomic criteria. The preferred treatment is complete excision. For patients with acutely inflamed masses, surgery should be performed only after resolution of the infection has been achieved with adequate drainage in combination with antibiotic therapy.     

Predictable texts and interactive-compensatory hypotheses: Evaluating individual differences in reading ability, context use, and comprehension.

Examined the word-recognition and comprehension processes of 36 1st graders as they read a predictable text. Interactive-compensatory predictions related to comprehension were evaluated. Results suggest that when reading predictable texts, attention for both good and poor readers is available for comprehension processing but for different reasons. Consistent with predictions from the interactive-compensatory model by K. E. Stanovich (1980), good readers were able to attend to the meaning of a story because of automatic, context-free word-recognition skills. Poor readers were able to attend to the meaning of a story because of their automatic use of repetitive sentence context to facilitate word recognition. Thus, predictable texts may be appropriately used to provide comprehension opportunities for poorer readers. Predictable texts may give these students opportunities to engage in inferential reasoning and other comprehension processes, opportunities that infrequently occur because poor readers' attention is usually occupied by word-recognition demands. (20 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The simulation of an emotional robot implemented with fuzzy logic

Recently, researchers have tried to better understand human behaviors so as to let robots act in more human ways, which means a robot may have its own emotions defined by its designers. To achieve this goal, in this study, we designed and simulated a robot, named Shiau_Lu, which is empowered with six universal human emotions, including happiness, anger, fear, sadness, disgust and surprise. When we input a sentence to Shiau_Lu through voice, it recognizes the sentence by invoking the Google speech recognition method running on an Android system, and outputs a sentence to reveal its current emotional states. Each input sentence affects the strength of the six emotional variables used to represent the six emotions, one corresponding to one. After that, the emotional variables will change into new states. The consequent fuzzy inference process infers and determines the most significant emotion as the primary emotion, with which an appropriate output sentence as a response of the input is chosen from its Output-sentence database. With the new states of the six emotional variables, when the robot encounters another sentence, the above process repeats and another output sentence is then selected and replied. Artificial intelligence and psychological theories of human behaviors have been applied to the robot to simulate how emotions are influenced by the outside world through languages. In fact, the robot may help autistic children to interact more with the world around them and relate themselves well to the outside world.