Polymer electrolyte for photoelectrochemical cell and dye-sensitized solar cell: a brief review

This paper reviews the use of solid polymeric electrolyte (SPE) and gel polymeric electrolyte (GPE) in photoelectrochemical cell (PEC) and dye-sensitized solar cell (DSSC). The structure of PEC and its working principle are presented. The various types of polymer electrolytes utilized in PEC and DSSC have been highlighted in this review. It also highlights the comparison of performance of PEC and DSSC utilizing those polymer electrolytes. This review is completed with the list of other SPEs that potentially be tested in DSSC.     

Asymmetric aldol reactions catalyzed by the promiscuous aldo–ketoreductase enzyme

The promiscuous aldo–ketoreductase (AKR) enzyme is used as a sustainable biocatalyst for the first time to catalyze asymmetric aldol reactions in aqueous medium. The reactions between aromatic aldehydes and cyclic/acyclic ketones give the corresponding products in moderate yields and enantioselectivities in the presence of water. The influence of solvents, the mole ratio of substrates, and enzyme concentration are investigated. The mechanism of the AKR1A1-catalyzed aldol reaction is also discussed.     

Effect of Experimental Variables on the Combustion Characteristics of Water-in-Diesel Emulsion Fuels

Water-in-diesel (W/D) emulsion fuels were prepared through an ultrasonic processor by using high energy emulsification method. Accordingly, the physical and chemical properties were analyzed. A decrease in viscosity was found in the emulsion fuel in contrast to the neat diesel which signifies the enhanced fluidity of the fuel. The emulsion fuel was then used to carry combustion tests in an internal combustion engine. A decrease in exhaust temperature was observed when a high surfactant to water ratio was used, which lead to minimal heat loss. As water is emulsified with diesel, effectiveness of combustion is improved rather than neat diesel fuel. It was also explored that the addition of water-in-diesel is influential in terms of reduction in exhaust gas emission such as carbon dioxide, carbon monoxide, ammonia from the internal combustion engine. Therefore, this type of emulsion fuel would be a useful contribution in the fuel economy, but also in making it environmentally friendly since diesel fuel is now considered one of the leading fuels causing ecological contamination.     

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.     

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.     

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.     

Effect of Ge4+ and Mg2+ doping on superconductivity,fluctuation induced conductivity and interplanar coupling of TlSr2CaCu2O7−δ superconductors

Substitution of Ge⁴⁺ in place of Cu in Tl_0.85Cr_0.15Sr₂CaCu_2?xGe_xO_7?δ (x = 0–0.6) showed initial increase in zero critical temperature value, T_{c zero} from 98 K (x = 0) to 100 K (x = 0.1) and in the range of 85–86 K for x = 0.2–0.3. The slow decrease in T_{c zero} is unexpected as tetravalent Ge⁴⁺ substitution is expected to strongly reduce hole concentration in the samples and suppress T_{c zero}. Excess conductivity analyses of resistance versus temperature data based on Asmalazov–Larkin (AL) theory revealed that the substitution induced 2D-to-3D transition of fluctuation induced conductivity with the highest transition temperature, T_2D–3D observed at x = 0.1. FTIR spectroscopy analysis indicates Ge⁴⁺ substitution cause reduction in CuO₂/GeO₂ interplanar distance while our calculation based on Lawrence–Doniach model revealed highest superconducting coherence length, ξ_c(0) and interplanar coupling, J at x = 0.3. On the other hand, substitution of divalent Mg²⁺ for Ca²⁺ in (Tl_0.5Pb_0.5)(Sr_1.8Yb_0.2)(Ca_1?yMg_y)Cu₂O₇ (y = 0–1.0), which is not expected to directly vary hole concentration, surprisingly caused T_{c zero} to increase from 89.6 K (y = 0) to an optimum value of 95.9 K (y = 0.6) before decreasing with further increase in y. Excess conductivity analyses showed 2D-to-3D transition of fluctuation induced conductivity for all samples where the highest T_2D–3D was at y = 0.4. Similar calculation revealed highest values of ξ_c(0) and J also at y = 0.4. FTIR analysis of the samples indicates inequivalent Cu(1)O(2)Pb/Tl lengths and possible tilting of CuO₂ plane as a result of Mg²⁺ substitution. The increased ξ_c(0) and J as a result of the Ge⁴⁺ and Mg²⁺ substitutions are suggested to contributed to sustenance of superconductivity above 80 K in the samples.     

Lattice Sphere Decoding for Data Transmission Systems with Special Channel Matrices

This paper presents the effects of condition number ( \(\tau \) ) in communication system performance. It has been shown that a small condition number ( \(\tau \) ) results a better performance. The proposed scheme is using special kind of matrices with Lattice Sphere Decoding (LSD) technique for Block Data Transmission Systems (BDTS). Hankel and Toeplitz matrices are used separately as a channel matrix (H) while circulant matrix is used in the previous works. The proposed scheme reduced the condition number ( \(\tau \) ) and, therefore, improve the system performance. As a result; LSD-based BDTS with Toeplitz/Hankel matrix outperforms the LSD-based BDTS with circulant matrix. Complexity analysis is also done which based on lattice dimension and initial radius selection.     

Partner Selection Technique for Wireless Cooperative Communication

In wireless cooperative communication scheme, transmit diversity is achieved by coupling the distributed users. In this paper, a new partner selection algorithm is proposed. The selection scheme utilizes the basic work done by Almawgani on RS coded cooperation for wireless network. Users are classified into weak and strong ones based on the signal-to-Noise Ratio (SNR) uplink matrix. Users with good uplink channel SNR (strong users) are coupled with those experiencing weak uplink channel conditions (weak users). The proposed algorithm offers an improvement to the outage probability, \(P_{out}\) and power efficiency as compared to the established work. The algorithm shows a significant improvement of \(P_{out}\) at lower values of uplink SNR.