An analytical investigation of elastic–plastic behaviors of 3D warp and woof auxetic structures

International Journal of Mechanics and Materials in Design - The present paper was conducted to calculate Young's modulus and Negative Poisson's ratio (NPR) of a warp and woof (WAW) 3D...     

A Novel Auto-Annotation Technique for Aspect Level Sentiment Analysis

In machine learning, sentiment analysis is a technique to find and analyze the sentiments hidden in the text. For sentiment analysis, annotated data is a basic requirement. Generally, this data is manually annotated. Manual annotation is time consuming, costly and laborious process. To overcome these resource constraints this research has proposed a fully automated annotation technique for aspect level sentiment analysis. Dataset is created from the reviews of ten most popular songs on YouTube. Reviews of five aspects—voice, video, music, lyrics and song, are extracted. An N-Gram based technique is proposed. Complete dataset consists of 369436 reviews that took 173.53 s to annotate using the proposed technique while this dataset might have taken approximately 2.07 million seconds (575 h) if it was annotated manually. For the validation of the proposed technique, a sub-dataset—Voice, is annotated manually as well as with the proposed technique. Cohen's Kappa statistics is used to evaluate the degree of agreement between the two annotations. The high Kappa value (i.e., 0.9571%) shows the high level of agreement between the two. This validates that the quality of annotation of the proposed technique is as good as manual annotation even with far less computational cost. This research also contributes in consolidating the guidelines for the manual annotation process.     

Effect of size on the dynamic behaviors of atomic force microscopes

Microsystem Technologies - Accurate mathematical modeling and simulation of cantilever dynamics are crucial to design and fabrication of the atomic force microscope (AFM). Thickness of AFM...     

Printing Reconfigurable Bundles of Dielectric Elastomer Fibers

Active soft materials that change shape on demand are of interest for a myriad of applications, including soft robotics, biomedical devices, and adaptive systems. Despite recent advances, the ability to rapidly design and fabricate active matter in complex, reconfigurable layouts remains challenging. Here, the 3D printing of core-sheath-shell dielectric elastomer fibers (DEF) and fiber bundles with programmable actuation is reported. Complex shape morphing responses are achieved by printing individually addressable fibers within 3D architectures, including vertical coils and fiber bundles. These DEF devices exhibit resonance frequencies up to 700 Hz and lifetimes exceeding 2.6 million cycles. The multimaterial, multicore-shell 3D printing method opens new avenues for creating active soft matter with fast programable actuation.     

A Framework on the Performance Analysis of Cooperative Wireless Body Area Networks

Wireless body area networks (WBANs) are deal with wireless networks in the human body. We describe the performance analysis of dual-hop cooperative relaying systems employing amplify-and-forward (AF) technique in WBANs over independent and nonnecessary identically distributed Gamma fading channels. More specifically, we present closed-form derivations of the outage probabilities (OP), symbol error probabilities (SEP) and ergodic capacity (EC) for fixed gain and channel state information (CSI)-assisted relaying techniques at arbitrary signal-to-noise-ratios (SNRs). We also deduce novel expressions in the high SNR region. By doing so, we can quantify the performance of system by the diversity and coding gains. Using the derived expressions as a starting point and for the case of Exponential fading, we consider three practical optimization scenarios. They are optimal relay position with fixed power allocation, power allocation under the fixed location of the relay and joint optimization of power allocation and relay position under a transmit power constraint. The Monte Carlo simulations are used to validate the accuracy of our derivations, where it is demonstrated that the proposed adaptive allocation method significantly outperforms the fixed allocation method.

     

A Dual Ring Connectivity Model for VANET Under Heterogeneous Traffic Flow

Vehicular ad-hoc network (VANET) is characterized as a highly dynamic wireless network due to the dynamic connectivity of the network nodes. To achieve better connectivity under such dynamic conditions, an optimal transmission strategy is required to direct the information flow between the nodes. Earlier studies on VANET’s overlook the characteristics of heterogeneity in vehicle types, traffic structure, flow for density estimation, and connectivity observation. In this paper, we have proposed a heterogeneous traffic flow based dual ring connectivity model to enhance both the message disseminations and network connectivity. In our proposed model the availability of different types of vehicles on the road, such as, cars, buses, etc., are introduced in an attempt to propose a new communication structure for moving vehicles in VANETl under cooperative transmission in heterogeneous traffic flow. The model is based on the dual-ring structure that forms the primary and secondary rings of vehicular communication. During message disseminations, Slow speed vehicles (buses) on the secondary ring provide a backup path of communication for high speed vehicles (cars) moving on the primary ring. The Slow speed vehicles act as the intermediate nodes in the aforementioned connectivity model that helps improve the network coverage and end-to-end data delivery. For the evaluation and the implementation of dual-ring model a clustering routing scheme warning energy aware cluster-head is adopted that also caters for the energy optimization. The implemented dual-ring message delivery scheme under the cluster-head based routing technique does show improved network coverage and connectivity dynamics even under the multi-hop communication system.     

A Multiply Connected Belief Network approach for schedule risk analysis of metropolitan construction projects

Metropolitan construction projects may be distinguished from other types of projects due to their specific nature. Issues with regard to purchase of property obstacles, a lack of accurate layout drawings for some underground facilities and, therefore, following probable changes in designs make it vital to have specific studies on risk analysis of such engineering projects. However, conventional methods offered in literature of risk analysis fail to consider the interactional mechanisms of risks and their simultaneous occurrence. This paper exploits the Multiply Connected Belief Network approach in MATLAB environment to analyse the simultaneous occurrence of risk factors on schedule delay of a highway project. The method of inference is through Junction Tree Algorithm due to existence of multiply connections in the developed network of the project. The findings for schedule delay were tested in a different space using Monte Carlo simulation and had satisfactory results.     

Side-Channel Information Characterisation Based on Cascade-Forward Back-Propagation Neural Network

Traditional cryptanalysis assumes that an adversary only has access to input and output pairs, but has no knowledge about internal states of the device. However, the advent of side-channel analysis showed that a cryptographic device can leak critical information. In this circumstance, Machine learning is known as a powerful and promising method of analysing of side-channel information. In this paper, an experimental investigation on a FPGA implementation of elliptic curve cryptography (ECC) was conducted to explore the efficiency of side-channel information characterisation based on machine learning techniques. In this work, machine learning is used in terms of principal component analysis (PCA) for the preprocessing stage and a Cascade-Forward Back-Propagation Neural Network (CFBP) as a multi-class classifier. The experimental results show that CFBP can be a promising approach in characterisation of side-channel information.     

MIMO satellite communication with accelerated dual paths asynchronous design

This paper presents a novel asynchronous design approach for multiple input multiple output (MIMO) satellite communication (SatCom) systems. One of the main challenges for MIMO SatCom systems is that these are prone to transient faults that typically are attributable to radiation hazards. Hence, instead of using conventional synchronous circuits, we conceive our design using asynchronous circuits since it inherently has a high tolerance to transient fault. Additionally, we adopt accelerated dual paths (ADP) design into our system. By carefully arranging the data flow between the two paths, the ADP design approach can help to further accelerate the asynchronous system and increase the reliability of the system by circumventing transient faults induced delay, as well as tolerating latch-ups and other permanent faults. The numerical results show that this design approach provides promising results. For example, the proposed design can decrease the delay overhead of the entire system from 43.5 to 19.8 % at the fault rate of 400/clock cycle.