The analytical method to solve nonstationary differential games of pursuit

The game problem of pursuit is studied for dynamic processes evolving under uncertainty and counteraction. The terminal set is supposed to be a cylindrical set-valued mapping. The method of resolving functions is used to establish the sufficient conditions for the game termination in the class of quasi- and stroboscopic strategies for various schemes of the method. The guaranteed times are compared. The results are illustrated using the model with integral control unit and game problems with simple motion.     

IESK-ArDB: a database for handwritten Arabic and an optimized topological segmentation approach

Even though a lot of researches have been conducted in order to solve the problem of unconstrained handwriting recognition, an effective solution is still a serious challenge. In this article, we address two Arabic handwriting recognition-related issues. Firstly, we present IESK-arDB, a new multi-propose off-line Arabic handwritten database. It is publicly available and contains more than 4,000 word images, each equipped with binary version, thinned version as well as a ground truth information stored in separate XML file. Additionally, it contains around 6,000 character images segmented from the database. A letter frequency analysis showed that the database exhibits letter frequencies similar to that of large corpora of digital text, which proof the database usefulness. Secondly, we proposed a multi-phase segmentation approach that starts by detecting and resolving sub-word overlaps, then hypothesizing a large number of segmentation points that are later reduced by a set of heuristic rules. The proposed approach has been successfully tested on IESK-arDB. The results were very promising, indicating the efficiency of the suggested approach.     

Variable Structure Control with Chattering Reduction of a Generalized T‐S Model

In this paper, a fuzzy logic controller (FLC) based variable structure control (VSC) is presented. The main objective is to obtain an improved performance of highly non‐linear unstable systems. New functions for chattering reduction and error convergence without sacrificing invariant properties are proposed. The main feature of the proposed method is that the switching function is added as an additional fuzzy variable and will be introduced in the premise part of the fuzzy rules; together with the state variables. In this work, a tuning of the well known weighting parameters approach is proposed to optimize local and global approximation and modelling capability of the Takagi‐Sugeno (T‐S) fuzzy model to improve the choice of the performance index and minimize it. The main problem encountered is that the T‐S identification method can not be applied when the membership functions are overlapped by pairs. This in turn restricts the application of the T‐S method because this type of membership function has been widely used in control applications. The approach developed here can be considered as a generalized version of the T‐S method. An inverted pendulum mounted on a cart is chosen to evaluate the robustness, effectiveness, accuracy and remarkable performance of the proposed estimation approach in comparison with the original T‐S model. Simulation results indicate the potential, simplicity and generality of the estimation method and the robustness of the chattering reduction algorithm. In this paper, we prove that the proposed estimation algorithm converge the very fast, thereby making it very practical to use. The application of the proposed FLC‐VSC shows that both alleviation of chattering and robust performance are achieved.     

Re-examining the causal structure of information technology impact research

About 20 years ago, Markus and Robey noted that most research on IT impacts had been guided by deterministic perspectives and had neglected to use an emergent perspective, which could account for contradictory findings. They further observed that most research in this area had been carried out using variance theories at the expense of process theories. Finally, they suggested that more emphasis on multilevel theory building would likely improve empirical reliability. In this paper, we reiterate the observations and suggestions made by Markus and Robey on the causal structure of IT impact theories and carry out an analysis of empirical research published in four major IS journals, Management Information Systems Quarterly (MISQ), Information Systems Research (ISR), the European Journal of Information Systems (EJIS), and Information and Organization (I&O), to assess compliance with those recommendations. Our final sample consisted of 161 theory-driven articles, accounting for approximately 21% of all the empirical articles published in these journals. Our results first reveal that 91% of the studies in MISQ, ISR, and EJIS focused on deterministic theories, while 63% of those in I&O adopted an emergent perspective. Furthermore, 91% of the articles in MISQ, ISR, and EJIS adopted a variance model; this compares with 71% from I&O that applied a process model. Lastly, mixed levels of analysis were found in 14% of all the surveyed articles. Implications of these findings for future research are discussed.     

Optimal Deep Learning Based Intruder Identification in Industrial Internet of Things Environment

With the increased advancements of smart industries, cybersecurity has become a vital growth factor in the success of industrial transformation. The Industrial Internet of Things (IIoT) or Industry 4.0 has revolutionized the concepts of manufacturing and production altogether. In industry 4.0, powerful Intrusion Detection Systems (IDS) play a significant role in ensuring network security. Though various intrusion detection techniques have been developed so far, it is challenging to protect the intricate data of networks. This is because conventional Machine Learning (ML) approaches are inadequate and insufficient to address the demands of dynamic IIoT networks. Further, the existing Deep Learning (DL) can be employed to identify anonymous intrusions. Therefore, the current study proposes a Hunger Games Search Optimization with Deep Learning-Driven Intrusion Detection (HGSODL-ID) model for the IIoT environment. The presented HGSODL-ID model exploits the linear normalization approach to transform the input data into a useful format. The HGSO algorithm is employed for Feature Selection (HGSO-FS) to reduce the curse of dimensionality. Moreover, Sparrow Search Optimization (SSO) is utilized with a Graph Convolutional Network (GCN) to classify and identify intrusions in the network. Finally, the SSO technique is exploited to fine-tune the hyper-parameters involved in the GCN model. The proposed HGSODL-ID model was experimentally validated using a benchmark dataset, and the results confirmed the superiority of the proposed HGSODL-ID method over recent approaches.     

High-performance MEMS shutter display with metal-oxide thin-film transistors and optimized MEMS element

Active matrix prestressed microelectromechanical shutter displays enable outstanding optical properties as well as robust operating performance. The microelectromechanical systems (MEMS) shutter elements have been optimized for higher light outcoupling efficiency with lower operation voltage and higher pixel density. The MEMS elements have been co-fabricated with self-aligned metal-oxide thin-film transistors (TFTs). Several optimizations were required to integrate MEMS process without hampering the performance of both elements. The optimized display process requires only seven photolithographic masks with ensuring proper compatibility between MEMS shutter and metal-oxide TFT process.     

GaP/GaNP Heterojunctions for Efficient Solar‐Driven Water Oxidation

The growth and characterization of an n‐GaP/i‐GaNP/p⁺‐GaP thin film heterojunction synthesized using a gas‐source molecular beam epitaxy (MBE) method, and its application for efficient solar‐driven water oxidation is reported. The TiO₂/Ni passivated n‐GaP/i‐GaNP/p⁺‐GaP thin film heterojunction provides much higher photoanodic performance in 1 m KOH solution than the TiO₂/Ni‐coated n‐GaP substrate, leading to much lower onset potential and much higher photocurrent. There is a significant photoanodic potential shift of 764 mV at a photocurrent of 0.34 mA cm^?2, leading to an onset potential of ≈0.4 V versus reversible hydrogen electrode (RHE) at 0.34 mA cm^?2 for the heterojunction. The photocurrent at the water oxidation potential (1.23 V vs RHE) is 1.46 and 7.26 mA cm^?2 for the coated n‐GaP and n‐GaP/i‐GaNP/p⁺‐GaP photoanodes, respectively. The passivated heterojunction offers a maximum applied bias photon‐to‐current efficiency (ABPE) of 1.9% while the ABPE of the coated n‐GaP sample is almost zero. Furthermore, the coated n‐GaP/i‐GaNP/p⁺‐GaP heterojunction photoanode provides a broad absorption spectrum up to ≈620 nm with incident photon‐to‐current efficiencies (IPCEs) of over 40% from ≈400 to ≈560 nm. The high low‐bias performance and broad absorption of the wide‐bandgap GaP/GaNP heterojunctions render them as a promising photoanode material for tandem photoelectrochemical (PEC) cells to carry out overall solar water splitting.     

Some peculiarities of electric discharge between a solid electrode and technical water

We present the results of experimental study of the electric discharge between metal electrodes of various geometry and technical water within the pressure range of 8 × 10³–10⁵ Pa at the saw-tooth voltage generator frequency, f = 40 MHz, and the interelectrode distance, l = 3–30 mm. We consider transfer of the streamer discharge into spark one depending on the geometry of the metal electrode and its material. We investigate the electrical characteristics of the discharge between the plate electrode and the technical water within a wide pressure range. The essential influence of the streamer discharge type on the ozone release within the investigated parameters range is discovered.     

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.     

Effect of Initial Annealing Temperature on Microstructural Development and Microhardness in High‐Purity Copper Processed by High‐Pressure Torsion

The effect of the initial annealing temperature on the evolution of microstructure and microhardness in high purity OFHC Cu is investigated after processing by HPT. Disks of Cu are annealed for 1 h at two different annealing temperatures, 400 and 800 °C, and then processed by HPT at room temperature under a pressure of 6.0 GPa for 1/4, 1/2, 1, 5, and 10 turns. Samples are stored for 6 months after HPT processing to examine the self‐annealing effects. Electron backscattered diffraction (EBSD) measurements are recorded for each disk at three positions: center, mid‐radius, and near edge. Microhardness measurements are also recorded along the diameters of each disk. Both alloys show rapid hardening and then strain softening in the very early stages of straining due to self‐annealing with a clear delay in the onset of softening in the alloy initially annealed at 800 °C. This delay is due to the relatively larger initial grain size compared to the alloy initially annealed at 400 °C. The final microstructures consist of homogeneous fine grains having average sizes of ≈0.28 and ≈0.34 µm for the alloys initially annealed at 400 and 800 °C, respectively. A new model is proposed to describe the behavior of the hardness evolution by HPT in high purity OFHC Cu.