Neighbourhood preserving discriminant embedding in face recognition

In this paper, we present an effective technique on discriminative feature extraction for face recognition. The proposed technique incorporates Graph Embedding and the Fisher’s criterion where we call it as Neighbourhood Preserving Discriminant Embedding (NPDE). Utilizing the Graph Embedding criterion, the underlying nonlinear face data structure is revealed as representative and discriminative features for analysis. We employ Neighbourhood Preserving Embedding (NPE) for the purpose. NPE takes into account the restriction that neighbouring points in the high-dimensional space must remain within the same neighbourhood in the low dimension space and be located in a similar relative spatial situation (without changing the local structure of the nearest neighbours of each data point). Furthermore, by taking the advantage of the Fisher’s criterion, the discriminating power of NPDE is further boosted. Based on this intuition, NPDE obtains better discriminative capability and experimentally verified in ORL, PIE and FRGC.     

Effects of Pretreatment on Properties of Gelatin from Perch (Lates Niloticus) Skin

Fish gelatins obtained from perch fish skin pretreated with various solutions containing acetic acid, sodium hydroxide (NaOH) and sodium chloride (NaCl) were successfully characterized for their nanostructure pattern using field emission scanning electron microscopy. Each pretreatment transformed collagen to gelatin with fibril, zigzag cracks, straight rods, and cross-linked rods nanostructure patterns. Pretreatment solutions also affect the gel yield, gel strength, amino acid profile, and functional groups in perch gelatin as analyzed by Fourier transform infrared spectroscopy. Samples pretreated with NaCl, NaOH, and acetic acid solution showed the highest gel yield (22.84%) and gel strength (179.84 g). Fourier transform infrared spectra for perch gelatins also revealed weak C–N amide II and III bond stretches as well as weak C=O bond stretch.     

Single-Row Transformation of Complete Graphs

A complete graph is a fully-connected graph where every node is adjacent to all other nodes in the graph. Very often, many applications in science and engineering are reducible to this type of graph. Hence, a simplified form of a complete graph contributes in providing the solutions to these problems. In this paper, we present a technique for transforming a complete graph into a single-row routing problem. Single-row routing is a classical technique in the VLSI design that is known to be NP-complete. We solved this problem earlier using a method called ESSR, and, the same technique is applied to the present work to transform a complete graph into its single-row routing representation. A parallel computing model is proposed which contributes in making the problem modular and scalable. We also discuss the application of this work on the channel assignment problem in the wireless cellular telephone networks.     

Enhanced Simulated Annealing Technique for the Single-Row Routing Problem

This paper presents ESSR (Enhanced Simulated annealing for Single-row Routing) model for solving the single-row routing problem. The main objective in this problem is to produce a realization that minimizes both the street congestion and the number of doglegs. Simulated annealing (SA) is a stochastic, hill-climbing and gradient-descent technique based on the statistical properties of particles undergoing thermal annealing. By performing slow cooling, the nets in the single-row routing problem align themselves according to a configuration with the lowest energy. The model has been known to produce reasonably good solutions for many NP-complete optimization problems, such as the single-row routing problem. In ESSR, our strategy is to minimize both the street congestion and the number of interstreet crossings (doglegs) by expressing a single energy function as their collective properties. This objective is achieved by representing the energy as the absolute sum of the heights of the net segments. To speed up convergence, we pivot the street congestion value while having the energy drops directly proportional to the number of doglegs. This action has the effect of minimizing the number of doglegs as the energy stabilizes. Our simulation work on ESSR produces optimal results in most cases for both the street congestion and the number of doglegs. Our experimental results compare well against results obtained from our earlier model (SRR-7) and two other methods reported in the literature.     

Synthesis of high purity Tl1212 superconductor with ultrafine grains from coprecipitated Tl-free precursor route

In this study, high purity and fine-grained Tl1212 superconductor samples were successfully synthesized from Tl_0.8Bi_0.2Sr₂Ca_0.8Y_0.2Cu₂O₇ starting composition by a two-step solid-state reaction method using Tl-free precursor powder prepared from coprecipitation method. XRD pattern of the sample, which was sintered at 1,000 °C for 6 min essentially showed formation of high purity 1212 phase. The sample’s zero resistance critical temperature, T _{c zero} was 91 K and bulk critical current density, J _c measured at 40 K in zero magnetic field was 11.2 A/cm². SEM investigation on the sample revealed ultrafine homogeneous grains that are randomly orientated with grain sizes of approximately 0.5–1 μm. Resintering the sample did not affect its superconducting properties but induced clustering of grains as observed by SEM. It is suggested that the sample be used in specialized measurement techniques such as in ultrasonic studies where high purity and ultrafine-grained samples are required.     

Learning Automata-Based Algorithms for Solving the Target Coverage Problem in Directional Sensor Networks

Recently, directional sensor networks have received a great deal of attention due to their wide range of applications in different fields. A unique characteristic of directional sensors is their limitation in both sensing angle and battery power, which highlights the significance of covering all the targets and, at the same time, extending the network lifetime. It is known as the target coverage problem that has been proved as an NP-complete problem. In this paper, we propose four learning automata-based algorithms to solve this problem. Additionally, several pruning rules are designed to improve the performance of these algorithms. To evaluate the performance of the proposed algorithms, several experiments were carried out. The theoretical maximum was used as a baseline to which the results of all the proposed algorithms are compared. The obtained results showed that the proposed algorithms could solve efficiently the target coverage problem.     

Enhancement of stack ventilation in hot and humid climate using a combination of roof solar collector and vertical stack

In the hot and humid climate, stack ventilation is inefficient due to small temperature difference between the inside and outside of naturally ventilated buildings. Hence, solar induced ventilation is a feasible alternative in enhancing the stack ventilation. This paper aims to investigate the effectiveness of a proposed solar induced ventilation strategy, which combines a roof solar collector and a vertical stack, in enhancing the stack ventilation performance in the hot and humid climate. The methodology selected for the investigation is physical experimental modelling which was carried out in the actual environment. The results are presented and discussed in terms of two performance variables: air temperature and air velocity. The findings indicate that the proposed strategy is able to enhance the stack ventilation, both in semi-clear sky and overcast sky conditions. The highest air temperature difference between the air inside the stack and the ambient air (T_i−T_o) is achieved in the semi-clear sky condition, which is about 9.9 °C (45.8 °C–35.9 °C). Meanwhile, in the overcast sky condition, the highest air temperature difference (T_i−T_o) is 6.2 °C (39.3 °C–33.1 °C). The experimental results also indicate good agreement with the theoretical results for the glass temperature, the air temperature in the roof solar collector’s channel and the absorber temperature. The findings also show that wind has significant effect to the induced air velocity by the proposed strategy.     

Throughput and Delay Analysis of IEEE 802.11 DCF in the Presence of Hidden Nodes for Multi-hop Wireless Networks

Hidden node collision in a contention-based medium access control protocol contributes to poor wireless network performance. This paper extended the Bianchi’s study and introduces a mathematical model that can be used to calculate throughput and delay for the IEEE 802.11 distributed coordination function of a multihop wireless network infrastructure assuming the presence of hidden node collision. This research investigates three essential parameters of multi-hop wireless networks. More specifically, this paper aims to analyze the effect of hidden nodes, network size, and maximum backoff stage on the overall system throughput and packet delay. Results clearly reveal the effect of large wireless network size, maximum backoff stage, and collision probability on throughput and packet delay. On one hand, throughput does not depend on the maximum backoff stage (m) for a small network size (e.g., n \(=\) 10). On the other hand, throughput does not strongly depend on the number of nodes when the backoff stage values are high. Comparing our proposed model in case single-hop with the Bianchi model, the analysis results indicate that the throughput values in our model when the numbers of nodes are 10, 50, and 100 are 0.6031, 0.4172 and 0.3433 respectively; whereas the throughput values are respectively 0.8370, 0.8317 and 0.8255 at the same number of nodes for the Bianchi model. The difference can be attributed to several assumptions made in our proposed model that were not considered in the Bianchi model.     

Testosterone Reduces Knee Passive Range of Motion and Expression of Relaxin Receptor Isoforms via 5α-Dihydrotestosterone and Androgen Receptor Binding

Ovarian steroids such as estrogen and progesterone have been reported to influence knee laxity. The effect of testosterone, however, remains unknown. This study investigated the effect of testosterone on the knee range of motion (ROM) and the molecular mechanisms that might involve changes in the expression of relaxin receptor isoforms, Rxfp1 and Rxfp2 in the patella tendon and lateral collateral ligament of the female rat knee. Ovariectomized adult female Wistar rats received three days treatment with peanut oil (control), testosterone (125 and 250 μg/kg) and testosterone (125 and 250 μg/kg) plus flutamide, an androgen receptor blocker or finasteride, a 5α-reductase inhibitor. Duplicate groups received similar treatment however in the presence of relaxin (25 ng/kg). A day after the last drug injection, knee passive ROM was measured by using a digital miniature goniometer. Both tendon and ligament were harvested and then analysed for protein and mRNA expression for Rxfp1 and Rxfp2 respectively. Knee passive ROM, Rxfp1 and Rxfp2 expression were significantly reduced following treatment with testosterone. Flutamide or finasteride administration antagonized the testosterone effect. Concomitant administration of testosterone and relaxin did not result in a significant change in knee ROM as compared to testosterone only treatment; however this was significantly increased following flutamide or finasteride addition. Testosterone effect on knee passive ROM is likely mediated via dihydro-testosterone (DHT), and involves downregulation of Rxfp1 and Rxfp2 expression, which may provide the mechanism underlying testosterone-induced decrease in female knee laxity.