Effects of Random Material Properties on Buckling of Composite Plates

Composites exhibit a considerable amount of variation in their material properties because their fabrication∕manufacturing process involves a large number of parameters that cannot be controlled effectively. In the present study, the material properties have been modeled as random variables for better prediction of the system behavior. The classical laminate theory and first-order and higher-order shear deformation theories have been employed in deriving the governing equations for buckling of laminated rectangular plates. A mean-centered first-order perturbation technique has been used to find the second-order statistics of the buckling load. The approach has been validated by comparison with results of Monte Carlo simulation. Typical results have been presented for a plate with all edges simply supported. The effectiveness of the theories in predicting the buckling load dispersions has been examined. The sensitivity of buckling loads to change in the standard deviation of random material properties and to system parameters—side-to-thickness ratio and aspect ratio—has been examined for cross-ply symmetric and antisymmetric laminates.     

Deterministic built-in test pattern generation for high-performancecircuits using twisted-ring counters

We present a new approach for built-in test pattern generation based on the reseeding of twisted-ring counters (TRCs). The proposed technique embeds a precomputed deterministic test set for the circuit under test (CUT) in a short test sequence produced by a TRC. The TRC is designed using existing circuit flip-flops and does not add to hardware overhead beyond what is required for basic scan design. The test control logic is simple, uniform for all circuits, and can be shared among multiple CUTs. Furthermore, the proposed method requires no mapping logic between the test generator circuit and the CUT; hence it imposes no additional performance penalty. Experimental results for the ISCAS benchmark circuits show that it is indeed possible to embed the entire precomputed test set in a TRC sequence using only a small number of seeds     

A Biased Random Instruction Generation Environment for Architectural Verification of Pipelined Processors

Architectural verification is a critical aspect of the microprocessor design cycle. In this paper, we present a design verification environment centered around a biased random instruction generator for simulation-based architectural verification of pipelined microprocessors. The instruction generator uses biases specified by the user to generate instruction sequences for simulation. These biases are not hard-coded and can thus be changed depending on the specific areas in the design and type of design errors being targeted. Correctness checking is achieved using assertion checking and end-of-state comparison with a high-level architectural model. Several architectural-level errors are introduced into a behavioral model of the DLX processor to investigate the processor's response in the presence of design errors. Simulation experiments conducted using the behavioral model show that biased random instruction sequences provide higher coverage of RTL conditional branches and design errors than random instruction sequences or manually-generated test programs. Furthermore, instruction sequences containing a high percentage of read-after-write (RAW) and control dependencies are the most useful.     

High Performance Adaptive Fidelity Algorithms for Multi-Modality Optic Nerve Head Image Fusion

A high performance adaptive fidelity approach for multi-modality Optic Nerve Head (ONH) image fusion is presented. The new image fusion method, which consists of the Adaptive Fidelity Exploratory Algorithm (AFEA) and the Heuristic Optimization Algorithm (HOA), is reliable and time efficient. It has achieved an optimal fusion result by giving the visualization of fundus image with a maximum angiogram overlay. Control points are detected at the vessel bifurcations using the AFEA. Shape similarity criteria are used to match the control points that represent same salient features of different images. HOA adjusts the initial good-guess of control points at the sub-pixel level in order to maximize the objective function Mutual-Pixel-Count (MPC). In addition, the performance of the AFEA and HOA algorithms was compared to the Centerline Control Point Detection Algorithm, Root Mean Square Error (RMSE) minimization objective function employed by the traditional Iterative Closest Point (ICP) algorithm, Genetic Algorithm, and some other existing image fusion approaches. The evaluation results strengthen the AFEA and HOA algorithms in terms of novelty, automation, accuracy, and efficiency.     

Mobile learning object authoring tool and management system for mobile ad hoc wireless networks

Mobile learning can augment formal education and bridge the gap between formal and informal education by creating extended learning communities using any digital technology in connected or infrastructure‐less environments. With the use of ad hoc networks and mobile authoring tools, we can now create an ‘on‐the‐fly’ learning scenario, where learners can create, share, and view content from their mobile devices without the need for server–client or infrastructure‐based liaisons. Mobile learning, however, is not just about sharing content or learning using mobile, wireless, and portable devices. Rather, it is learning across spatiotemporal contexts that enables learners to form knowledge and understanding in different scenarios. When facing limited resources stemming from the characteristics of mobility and wireless technologies, determining the best practices for content creation and delivery becomes a challenge. This paper describes the architecture of a mobile‐focused learning network designed so that learning tools, activities, contexts, and interactions are created as necessary over time and space while adhering to traditional learning object standards. Copyright © 2015 John Wiley & Sons, Ltd.     

Why Are “Others” So Polarized? Perceived Political Polarization and Media Use in 10 Countries

This study tests the associations between news media use and perceived political polarization, conceptualized as citizens' beliefs about partisan divides among major political parties. Relying on representative surveys in Canada, Colombia, Greece, India, Italy, Japan, South Korea, Norway, the United Kingdom, and the United States, we test whether perceived polarization is related to the use of television news, newspaper, radio news, and online news media. Data show that online news consumption is systematically and consistently related to perceived polarization, but not to attitude polarization, understood as individual attitude extremity. In contrast, the relationships between traditional media use and perceived and attitude polarization is mostly country dependent. An explanation of these findings based on exemplification is proposed and tested in an experimental design.     

Space and time efficiency of the forest-of-quadtrees representation

A forest of quadtrees is a refinement of a quadtree data structure that is used to represent planar regions. A forest of quadtrees provides space savings over regular quadtrees by concentrating vital information. The paper presents some of the properties of a forest of quadtrees and studies the storage requirements for the case in which a single 2^m × 2^m region is equally likely to occur in any position within a 2ⁿ × 2ⁿ image. Space and time efficiency are investigated for the forest-of-quadtrees representation as compared with the quadtree representation for various cases.     

Biomedical and psychiatric risk factors for retinopathy among children with IDDM

OBJECTIVE: Illness duration and glycemic control influence the development of retinopathy in childhood-onset insulin-dependent diabetes mellitus (IDDM). Psychiatric disorders and sociodemographic factors also affect diabetes-related outcomes. However, biomedical and psychosocial factors have not been examined together in modeling the risk of retinopathy. RESEARCH DESIGN AND METHODS: We conducted a single-site prospective longitudinal study of 66 children (aged 8-13 years) newly diagnosed with IDDM. Repeated assessments served to derive psychiatric diagnoses. Poor glycemic control was defined as the upper 15th percentile of all HbA1 values. After a median follow-up of 10 years, severity of retinopathy was determined. It was modeled with a stepwise polychotomous regression procedure using antecedent biomedical and psychosocial variables. RESULTS: Young adults with childhood-onset IDDM were found to be at increased risk of retinopathy the longer they had IDDM, the more persistently they evidenced poor antecedent glycemic control, and the longer they suffered from depressive illness. These three factors operated individually and additively, with duration of IDDM conferring a baseline level of risk. In depressed patients (27%), depression onset antedated the detection of retinopathy generally by 7 years. CONCLUSIONS: Duration of childhood-onset IDDM confers a baseline level of risk of retinopathy irrespective of glycemic control; antecedent clinical depression is also a risk factor. Depression therefore may serve as a marker of vulnerability and help to identify a subgroup of patients at risk for complications. The findings raise the question whether timely treatment of depression could forestall diabetic retinopathy.