Design of a compact dual‐band folded‐waveguide bandpass filter using multilayer waveguide resonators

A novel compact dual‐band bandpass filter based on multilayer folded‐waveguide (FWG) structure is presented in this article.In this design, slots are used to realize direct coupling between adjacent resonators and apertures are adopted to implement cross coupling between non‐adjacent resonators.A new technique of external quality factor of FWG resonator and coupling coefficients between different resonators are studied using full‐wave simulator. In order to demonstrate the proposed technique, a four‐pole dual‐band bandpass filter is designed, fabricated and measured using vector network analyzer. Measurement results which are well agreed with simulation results are presented. Moreover, four‐pole substrate integrated folded waveguide SIFW dual‐band bandpass filter, using two layers of slotted folded waveguide resonators, is demonstrated. The proposed filter has a compact size and it is excellent candidate for the application of wireless communication systems. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:780–788, 2015.     

Emotional Loneliness and Coping Strategies: A Reference to Older Malaysians at Nursing Homes

This article presents an in-depth qualitative study using a phenomenological approach to understand loneliness among elderly individuals in Malaysia. The objective of the study was to understand how the Malaysian elderly perceive and understand social isolation as well as loneliness, with the aim of identifying the factors that cause emotional loneliness among the elderly in nursing homes. In addition, this study also explored their coping strategies when dealing with loneliness. Semi-structured interviews were conducted with ten elderly participants from two different nursing homes in Kuala Lumpur and Selangor with representatives from the three major ethnic groups of Malaysia. Based on the results, there are several factors that cause the elderly to feel lonely – health factors, lack of family ties, and the lack of communication and cognitive factors, such as memory and perception. It was also found that internal (expectations and optimism) and external (work and activities) coping strategies play major roles in overcoming loneliness. In conclusion, some recommendations are made to respective party families and the government to consider when developing plans to help the elderly overcome loneliness, which could strengthen the family and social support system in Malaysia.     

Mass spectrometric immunoassay and MRM as targeted MS-based quantitative approaches in biomarker development: Potential applications to cardiovascular disease and diabetes

Type 2 diabetes mellitus (T2DM) is an important risk factor for cardiovascular disease (CVD)—the leading cause of death in the United States. Yet not all subjects with T2DM are at equal risk for CVD complications; the challenge lies in identifying those at greatest risk. Therapies directed toward treating conventional risk factors have failed to significantly reduce this residual risk in T2DM patients. Thus newer targets and markers are needed for the development and testing of novel therapies. Herein we review two complementary MS-based approaches—mass spectrometric immunoassay (MSIA) and MS/MS as MRM—for the analysis of plasma proteins and PTMs of relevance to T2DM and CVD. Together, these complementary approaches allow for high-throughput monitoring of many PTMs and the absolute quantification of proteins near the low picomolar range. In this review article, we discuss the clinical relevance of the high density lipoprotein (HDL) proteome and Apolipoprotein A-I PTMs to T2DM and CVD as well as provide illustrative MSIA and MRM data on HDL proteins from T2DM patients to provide examples of how these MS approaches can be applied to gain new insight regarding cardiovascular risk factors. Also discussed are the reproducibility, interpretation, and limitations of each technique with an emphasis on their capacities to facilitate the translation of new biomarkers into clinical practice.     

Toward an efficient and scalable feature selection approach for internet traffic classification

There is significant interest in the network management and industrial security community about the need to identify the “best” and most relevant features for network traffic in order to properly characterize user behaviour and predict future traffic. The ability to eliminate redundant features is an important Machine Learning (ML) task because it helps to identify the best features in order to improve the classification accuracy as well as to reduce the computational complexity related to the construction of the classifier. In practice, feature selection (FS) techniques can be used as a preprocessing step to eliminate irrelevant features and as a knowledge discovery tool to reveal the “best” features in many soft computing applications. In this paper, we investigate the advantages and disadvantages of such FS techniques with new proposed metrics (namely goodness, stability and similarity). We continue our efforts toward developing an integrated FS technique that is built on the key strengths of existing FS techniques. A novel way is proposed to identify efficiently and accurately the “best” features by first combining the results of some well-known FS techniques to find consistent features, and then use the proposed concept of support to select a smallest set of features and cover data optimality. The empirical study over ten high-dimensional network traffic data sets demonstrates significant gain in accuracy and improved run-time performance of a classifier compared to individual results produced by some well-known FS techniques.     

Interleaving Guidance in Evolutionary Multi-Objective Optimization

In this paper, we propose a framework that uses localization for multi-objective optimization to simultaneously guide an evolutionary algorithm in both the decision and objective spaces. The localization is built using a limited number of adaptive spheres （local models） in the decision space. These spheres axe usually guided, using some direction information, in the decision space towards the areas with non-dominated solutions. We use a second mechanism to adjust the spheres to specialize on different parts of the Paxeto front by using a guided dominance technique in the objective space. Through this interleaved guidance in both spaces, the spheres will be guided towards different parts of the Paxeto front while also exploring the decision space efficiently. The experimental results showed good performance for the local models using this dual guidance, in comparison with their original version.     

Interfacial Connections between Organic Perovskite/n+ Silicon/Catalyst that Allow Integration of Solar Cell and Catalyst for Hydrogen Evolution from Water

The rapidly increasing solar conversion efficiency (PCE) of hybrid organic–inorganic perovskite (HOIP) thin-film semiconductors has triggered interest in their use for direct solar-driven water splitting to produce hydrogen. However, application of these low-cost, electronic-structure-tunable HOIP tandem photoabsorbers has been hindered by the instability of the photovoltaic-catalyst-electrolyte (PV+E) interfaces. Here, photolytic water splitting is demonstrated using an integrated configuration consisting of an HOIP/n⁺silicon single junction photoabsorber and a platinum (Pt) thin film catalyst. An extended electrochemical (EC) lifetime in alkaline media is achieved using titanium nitride on both sides of the Si support to eliminate formation of insulating silicon oxide, and as an effective diffusion barrier to allow high-temperature annealing of the catalyst/TiO₂-protected-n⁺silicon interface necessary to retard electrolytic corrosion. Halide composition is examined in the (FA_1-xCs_x)PbI₃ system with a bandgap suitable for tandem operation. A fill factor of 72.5% is achieved using a Spiro-OMeTAD-hole-transport-layer (HTL)-based HOIP/n⁺Si solar cell, and a high photocurrent density of −15.9 mA cm⁻² (at 0 V vs reversible hydrogen electrode) is attained for the HOIP/n⁺Si/Pt photocathode in 1 m NaOH under simulated 1-sun illumination. While this thin-film design creates stable interfaces, the intrinsic photo- and electro-degradation of the HOIP photoabsorber remains the main obstacle for future HOIP/Si tandem PEC devices.     

Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

Internet Protocol version 6 (IPv6) is the latest version of IP that goal to host 3.4 × 10³⁸ unique IP addresses of devices in the network. IPv6 has introduced new features like Neighbour Discovery Protocol (NDP) and Address Auto-configuration Scheme. IPv6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol (ICMPv6). IPv6 is vulnerable to numerous attacks like Denial of Service (DoS) and Distributed Denial of Service (DDoS) which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial implications. Therefore, an Intrusion Detection System (IDS) is a monitoring system of the security of a network that detects suspicious activities and deals with a massive amount of data comprised of repetitive and inappropriate features which affect the detection rate. A feature selection (FS) technique helps to reduce the computation time and complexity by selecting the optimum subset of features. This paper proposes a method for detecting DDoS flooding attacks (FA) based on ICMPv6 messages using a Binary Flower Pollination Algorithm (BFPA-FA). The proposed method (BFPA-FA) employs FS technology with a support vector machine (SVM) to identify the most relevant, influential features. Moreover, The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack scenarios. The results show that the proposed method BFPA-FA achieved the best accuracy rate (97.96%) for the ICMPv6 DDoS detection with a reduced number of features (9) to half the total (19) features. The proven proposed method BFPA-FA is effective in the ICMPv6 DDoS attacks via IDS.     

Hybrid image steganography method using Lempel Ziv Welch and genetic algorithms for hiding confidential data

Multidimensional Systems and Signal Processing - Digital images are commonly used in steganography due to the popularity of digital image transfer and exchange through the Internet. However, the...     

Quantification of the inherent uncertainty in the relaxation modulus and creep compliance of asphalt mixes

Advanced material characterization of asphalt concrete is essential for realistic and accurate performance prediction of flexible pavements. However, such characterization requires rigorous testing regimes that involve mechanical testing of a large number of laboratory samples at various conditions and set-ups. Advanced measurement instrumentation in addition to meticulous and accurate data analysis and analytical representation are also of high importance. Such steps as well as the heterogeneous nature of asphalt concrete (AC) constitute major factors of inherent variability. Thus, it is imperative to model and quantify the variability of the needed asphalt material’s properties, mainly the linear viscoelastic response functions such as: relaxation modulus, \(E(t)\), and creep compliance, \(D(t)\). The objective of this paper is to characterize the inherent uncertainty of both \(E(t)\) and \(D(t)\) over the time domain of their master curves. This is achieved through a probabilistic framework using Monte Carlo simulations and First Order approximations, utilizing \(E^{*}\) data for six AC mixes with at least eight replicates per mix. The study shows that the inherent variability, presented by the coefficient of variation (COV), in \(E(t)\) and \(D(t)\) is low at small reduced times, and increases with the increase in reduced time. At small reduced times, the COV in \(E(t)\) and \(D(t)\) are similar in magnitude; however, differences become significant at large reduced times. Additionally, the probability distributions and COVs of \(E(t)\) and \(D(t)\) are mix dependent. Finally, a case study is considered in which the inherent uncertainty in \(D(t)\) is forward propagated to assess the effect of variability on the predicted number of cycles to fatigue failure of an asphalt mix.