Work of fracture of high impact polystyrene (HIPS) film under plane stress conditions

Essential work of fracture methodology was used to determine plane-stress ductile fracture toughness of high impact polystyrene film of thickness 0.26 mm. Results obtained indicated that specific essential work of fracture, w _e, is independent of loading rate, and for certain specimen sizes, independent of both gauge length and width of the specimen. On the other hand, w _e was found to be affected by the temperature, molecular anisotropy and the geometry of the test specimens. Reasonable estimate of w _e was obtained via crack opening displacement value.     

Single and multi-specimenR-curve methods forJ IC determination of toughened nylons

For characterization of the fracture resistance of materials used in the upper shelf toughness regime,J-R curves are widely considered the most promising candidates. However, there still remain problems concerning both the generation and measurement ofJ-R curves as material characterizing parameters and their application in ductile fracture analyses for failure prediction in polymeric materials. This paper reports the results of investigations conducted on two rubbertoughened nylons at room temperature. Two different methods ofJ-R curve determination are covered, namely multi-specimen and single specimen test methods. The resultingJ-R curves have also been evaluated to obtain values of the initiation toughness,J _IC, following the extrapolation and interpolation schemes prescribed by ASTM E813-81 and ASTM E813-87 test procedures, respectively. The results show that the multiple specimen unloading method and the single specimen partial unloading compliance method can be used to generate comparable crack growth resistanceJ-R curves of the toughened nylons. The value ofJ _IC for the crystalline rubber-toughened nylon was approximately twice the value obtained for the amorphous rubber-toughened nylon. The former material also exhibited a greater resistance to ductile crack growth.     

High-breakdown-voltage AlInAs/GaInAs junction-modulated HEMT's(JHEMT's) with regrown ohmic contacts by MOCVD

A technology for increasing both the two-terminal gate-drain breakdown and subsequently the three-terminal-off-state breakdown of AlInAs/GaInAs high-electron-mobility transistors (HEMTs) to record values without substantial impact on other parameters is presented. The breakdown in these structures is dependent on the multiplication of electrons injected from the source (channel current) and the gate (gate leakage) into the channel. In addition, holes are generated by high fields at the drain and are injected back into the gate and source electrodes. These phenomena can be suppressed by increasing the gate barrier height and alleviating the fields at the drain. Both have been achieved by incorporating a p⁺-2DEG junction as the gate that modulates the 2DEG gas and by utilizing selective regrowth of the source and drain regions by MOCVD. The 1-μm-gate-length devices fabricated have two-terminal gate-drain and three-terminal-off-state breakdown voltages of 31 V and 28 V, respectively     

ECFGM: enriched control flow graph miner for unknown vicious infected code detection

Vicious codes, especially viruses, as a kind of impressive malware have caused many disasters and continue to exploit more vulnerabilities. These codes are injected inside benign programs in order to abuse their hosts and ease their propagation. The offsets of injected virus codes are unknown and their targets usually are latent until they are executed and activated, what in turn makes viruses very hard to detect. In this paper enriched control flow graph miner, ECFGM in short, is presented to detect infected files corrupted by unknown viruses. ECFGM uses enriched control flow graph model to represent the benign and vicious codes. This model has more information than traditional control flow graph (CFG) by utilizing statistical information of dependent assembly instructions and API calls. To the best of our knowledge, the presented approach in this paper, for the first time, can recognize the offset of infected code of unknown viruses in the victim files. The main contributions of this paper are two folds: first, the presented model is able to detect unknown vicious code using ECFG model with reasonable complexity and desirable accuracy. Second, our approach is resistant against metamorphic viruses which utilize dead code insertion, variable renaming and instruction reordering methods.     

Numerical study of the one-dimensional coupled nonlinear sine-Gordon equations by a novel geometric meshless method

Engineering with Computers - In the paper, we derive a geometric meshless method for coupled nonlinear sine-Gordon (CNSG) equations. Approximate solutions of the CNSG equations are supposed to be...     

An FEC scheme combined with weighted scheduling to reduce multicast packet loss in IPTV over PON

Congestion is one of the most important challenges in optical networks. In a Passive Optical Network (PON), the Optical Line Terminal (OLT) is a bottleneck and congestion prone. In this paper, a framework is proposed with Forward Error Correction (FEC) at the IP layer combined with Weighted Round Robin (WRR) at the scheduling level to overcome packet-loss due to congestion in the OLT in order to achieve efficient video multicasting over PON. In the FEC scheme, Reed-Solomon (RS(n,k)) with erasure coding is used, where (n−k) erroneous symbols per n symbol blocks can be corrected. In our framework, an Internet Protocol TeleVision (IPTV) service provider uses the mentioned RS coding and generates redundant packets from regular IPTV packets in such a way that an Optical Network Unit (ONU) can recover lost packets from received packets, thus resulting in a better video quality. Simulation results show that using the proposed framework, an ONU can recover many lost packets and achieve better video quality under different traffic loads for its users. For instance, the proposed method can reduce packet loss rate by almost 55% and 10% under traffic load 0.9, respectively, compared with the Round Robin (RR) and WRR methods under symmetric traffic load. When High Receivers Queue (HRQ) traffic (i.e., traffic received by many users) is twice Low Receivers Queue (LRQ) traffic (i.e., traffic received by a small number of users), this reduction is almost 86% and 30% under traffic load 0.9. Finally, when LRQ traffic is twice HRQ traffic, the reduction in packet loss rate is almost 70% and 91% at traffic load 0.5.     

Correction to: Bismuth Yttrium Oxide (Bi3YO6), A New Electrode Material For Asymmetric Aqueous Supercapacitors

Journal of Inorganic and Organometallic Polymers and Materials - The original version of this article unfortunately contained mistakes. In line 9 of the abstract, 5% should read as 2%. The...     

Hybrid effects on mechanical properties of polyoxymethylene

The present study investigated fracture and various mechanical properties of polyoxymethylene (POM) hybrids in tension and in flexure. The hybrids examined consisted of short glass fibers (GF) and spherical glass beads (GB). Comparisons are made between experimentally observed values and predictions based on the rule-of-hybrid mixtures for hybrid strength, modulus, impact strength, fracture toughness, and strain energy release rates. Results indicated that tensile strength, flexural modulus, and fracture toughness of POM/GB/GF hybrid composites can be estimated from the following rule-of-hybrid mixtures where P_POM/GB and P_POM/GF are the measured properties of the POM/GB and POM/GF composites, and χ_POM/GB and χ_POM/GF are the hybrid ratio (by volume) of the glass bead and that of glass fiber, respectively. In view of this, none of the aforementioned properties show any signs of a hybrid effect. Flexural strengths, impact strengths, and strain energy release rate all showed the existence of a negative hybrid effect where negative deviation from the rule-of-mixtures behavior was observed. The latter was closer to the estimation based on the inverse rule-of mixtures.     

HMM-based state classification of a user with a walking support system using visual PCA features

The improvement of safety and dependability in systems that physically interact with humans requires investigation with respect to the possible states of the user’s motion and an attempt to recognize these states. In this study, we propose a method for real-time visual state classification of a user with a walking support system. The visual features are extracted using principal component analysis and classification is performed by hidden Markov models, both for real-time fall detection (one-class classification) and real-time state recognition (multi-class classification). The algorithms are used in experiments with a passive-type walker robot called “RT Walker” equipped with servo brakes and a depth sensor (Microsoft Kinect). The experiments are performed with 10 subjects, including an experienced physiotherapist who can imitate the walking pattern of the elderly and people with disabilities. The results of the state classification can be used to improve fall-prevention control algorithms for walking support systems. The proposed method can also be used for other vision-based classification applications, which require real-time abnormality detection or state recognition.     

A game attention model for efficient bit rate allocation in cloud gaming

The widespread availability of broadband internet access and the growth in server-based processing have provided an opportunity to run games away from the player into the cloud and offer a new promising service known as cloud gaming. The concept of cloud gaming is to render a game in the cloud and stream the resulting game scenes to the player as a video sequence over a broadband connection. To meet the stringent network bandwidth requirements of cloud gaming and support more players, efficient bit rate reduction techniques are needed. In this paper, we introduce the concept of game attention model (GAM), which is basically a game context-based visual attention model, as a means for reducing the bit rate of the streaming video more efficiently. GAM estimates the importance of each macro-block in a game frame from the player’s perspective and allows encoding the less important macro-blocks with lower bit rate. We have evaluated nine game video sequences, covering a wide range of game genre and a spectrum of scene content in terms of details, motion and brightness. Our subjective assessment shows that by integrating this model into the cloud gaming framework, it is possible to decrease the required bit rate by nearly 25 % on average, while maintaining a relatively high user quality of experience. This clearly enables players with limited communication resources to benefit from cloud gaming with acceptable quality.