Research Highlights in Science and Technology Vol. 3

This chapter aims to highlights the use of Photovoltaic substrates, or as a filler sheet for thin-film CIGS solar cells application. Nanotechnology is a technique that is projected to lead to dramatic improvements in many areas of the application to new materials, electronics and goods. Thin films of the zinc sulphide nanoparticle are deposited on glass substrates by thermal evaporation from ZnS NPs millimetric crystals. The alteration in the optical and structural properties of the films deposited at different (100-200 and 300)°C annealed substrates was investigated by XRD, SEM, and EDX. The findings obtained reveal that the films are structured in a cubic zinc blend with (111) preferential orientation. The visible wavelength ranges from (22 -12) nm. The strong cubic structure taken as thin layers allowed us to infer that the ZnS NPs films synthesize can be used as a buffer layer to replace the damaging CdS in CIGS thin-film solar cells. The films became more uniform and dense as the substrate temperature increased. The nanoscale size of zinc sulfide reduces as temperature rises.

The effect of Radopholus similis on banana (Musa AAA cv. Grande Naine) leaf photosynthesis was determined throughout four experiments that were carried out under lathhouse conditions. In vitro plants were sown in pots of 1.8 L volume containing sterilized or unsterilized soil from a commercial banana farm. In the first experiment during the three measuring times (7 am, 10 am, and 1 pm), at 45 days after inoculation, the highest photosynthesis rate was observed in the plants free of nematodes and the lowest in those plants inoculated with 500 (506 ± 18) R. similis per pot. In the evaluation at 10 am a reduction of 46% (P= 0.0307) in the photosynthesis rate was found on plants inoculated with R. similis that were grown in the sterilized banana soil. In the second experiment, after 75 days of the inoculation, from the six photosynthesis evaluation times (6-7, 8-9, and 10-11 am or 12-1, 1-2 and 2-3 pm) with exception of that at 2-3 pm, the highest photosynthesis rate was observed in the plants free of nematodes. Reductions in the photosynthesis rate with nematode inoculation varied between 12 and 36% at 6-7 am, between 13 and 57% at 8-9 am, between 32 and 57% at 10-11 am, and between 16 and 65% at 12-1 pm, and between 13 and 47% at 1-2 pm. The photosynthesis rate decreased linearly as the number of R. similis inoculated increased in the evaluations of 8-9 (P= 0.0070) and 10-11 am (P= 0.0049) or 12-1 pm (P= 0.0048) and 1-2 pm (P= 0.0255). In the third experiment, a photosynthetic light response curve was determined at 75 days after inoculation showing that the area under curve of the potential assimilation rate of the plants inoculated with 1500 (1564 ± 49) R. similis was reduced (P= 0.0153) by 70% compared to non-inoculated plants.  At the last experiment, the net assimilation rate curve at 4 (P< 0.0001), 11 (P= 0.0340) and 25 (P= 0.0127) days after nematode inoculation was higher on the plants free of nematodes. So, in the four experiments, the lowest photosynthetic rate was found in the plants infected by R. similis.

There are currently different bonded joint geometries that the designer can choose from, including the single-lap joint, double-lap joint, stepped-joint, scarf joint, and tubular joint. Other geometries are designed to sustain peel loads, such as T-joints and L-joints. T-joints are used in different scenarios, including in aircraft (stiffener/skin joints) and in vehicles (B-pillar/rocker joints). The present work consists of a numerical analysis on the adhesive type effect in aluminium T-joints under peel loads, by cohesive zone modelling (CZM). However, CZM validation is previously accomplished. The joints’ assessment initiates with stress analysis, and prediction of maximum load (P_m), while geometrical modifications are also tested, to enable proposing the best solution for the joint. CZM revealed to be an accurate tool for these joints, and a significant geometric and adhesive influence was detected on the joint performance, which enabled to propose the best joint solution.

The present article deals with the 2D unsteady an incompressible heat absorption fluid past a semi-infinite vertical moving permeable plate in a uniform pressure grading by means of variable suction in terms of viscous dissipation. The novelty of the present investigation is to assess the impact of inclination angle on flow phenomena in heat source/sink behavior. The governing equations have been solved using the multiple regular perturbation approach. "Exemplifies velocity, temperature along with concentration in graphical form" from the present assessment.  With the increased Prandtl number values, temperature clearly decreased, but velocity saw the opposite effect. Temperature and velocity both decreased as radiation absorption values increased. Additionally, increasing Eckert number values cause velocity to decrease.

The aim of this chapter is to propose an efficient retrieval method that can retrieve appropriate information from the gigantic collections of images utilized in heterogeneous applications which has a pronounced impact on retrieval performance when compared to standard and customary Gabor filter methods. In recent times, there is a magnificent technical progression in the research area related to image retrieval, in specific the Query By Image Content (QBIC) system. Retrieval of information has become a very challenging area of research in various applications like databases related to multimedia, Google retrieval and digital libraries. The study developed a hybrid QBIC retrieval system that depicts the impact of PSO on retrieval performance in QBIC system by retrieving color features, texture features and shape features of the images in three consecutive stages. In the suggested technique, color features are initially extracted using a color histogram. In the following step, Log Gabor filters are tuned using Particle Swarm Optimization (PSO), retrieving the texture characteristics. The extraction of shape features is completed by using a polygonal fitting technique. When compared to the current standard systems, the suggested method shows a superior retrieval rate in terms of mean recall and mean precision. The novelty is that it can exploit global minima features that result in high accuracy without affecting the computation.

Taking an occasional recreational vacation is essential for many individuals, as it provides a much-needed break for both the body and mind from the pressures of daily life. However, the high cost of vacationing, both internationally and locally, prevents many from affording a vacation. This leads to many individuals choosing to spend their holidays with extended family or in their rural homes. To promote domestic tourism, initiatives such as 'Tembea Kenya' have been introduced to boost the tourism sector in the country. However, there are other challenges associated with traditional accommodation facilities, such as a lack of privacy, limited space, numerous restrictions, and hygiene concerns, particularly during the COVID-19 crisis. This study aims to address these challenges by developing a technological solution that allows individuals to make reservations for vacation homes, eliminating the cost of renting a house. The solution is a web-based application that utilizes the K-Nearest Neighbors machine learning algorithm to classify homes based on available features. The goal is to provide an affordable and personalized vacation experience for all.

To be able to evaluate the performance and strength of an adhesive joint, numerical methodologies based on the Finite Element Method (FEM) are used. In real cases, adhesive joints are also subjected to dynamic loads, such as impact. This work aims to predict the behaviour and strength of double-lap composite adhesive joints under impact loads, under different overlap lengths (L_O). For this purpose, numerical simulations by FEM and cohesive zone models (CZM) are considered. The adhesives used for this numerical study are the Araldite^® AV138 and the Sikaforce^® 7752. As adherend, the pre-preg Seal^® Texipreg HS 160 RM was used. Initially, a study was carried out with single-lap joint (SLJ) experimental data, to validate the proposed technique for analysing impact-adhesive joints. Double-lap joint (DLJ) analysis was based on elastic peel (s_y) and shear (t_xy) stresses, and strength prediction. Validation of the proposed numerical technique was successfully accomplished to model bonded joints under impact loads. Between the tested adhesives, stiff and strong adhesives work better under impact, leading to higher performance, although bigger L_O than those tested in this work can benefit from less strong but more ductile adhesives.

The article describes the design and simulation of a cylindrical dielectric resonator antenna (CDRA) for 5G communications with a frequency range of 2-6 GHz. The CDRA is made of alumina ceramic with a permittivity of DRA=9.9 and a resonant frequency of fr=4GHz. The antenna is excited by a microstrip line and is coupled electromagnetically to the substrate, which is Rogers RT 5880 with \(\epsilon\)r=2.2 and tan\(\delta\)=0.0009, and a thickness of 1.52mm. The CDRA operates in hybrid HEM11\(\delta\) mode and has a radius of 10mm and a height of 10mm. The ground plane below the substrate is made of annealed alumina to minimize radiation below the substrate, and all radiation is directed towards the top of the CDRA. The article suggests that the designed CDRA can be used for 5G applications and massive MIMO antenna array configurations. The channel capacity of the antenna can achieve a high data rate given by the formula C=B log₂(1+SNR), where C is the channel capacity and B is the bandwidth of the channel.

In the field of agriculture, timely investigation and recognition of plant leaf diseases assures high crop quality and yield. Due to a lack of knowledge about the most cutting-edge sophisticated approaches in the field of leaf disease detection, one of the largest obstacles for rice farmers is the identification of leaf diseases. Due to the frequency of rice leaf diseases, a large portion of rice growth is disrupted. Early detection of rice leaf diseases is now done manually by farmers, which is extremely time-consuming and labor-intensive. However, the requirement of automatic disease detection in rice leaves aids farmers in more effectively preserving their agricultural harvests. In this review, the major focus is on performance analysis of detection of rice leaf diseases based on the architectures employed. Convolutional neural networks are the best method for classifying rice leaf diseases, and advances in computer vision and deep learning satisfy predictions and turn out to be the greatest method for doing so. Numerous CNN architectures have been analyzed for finding best classification performance based on training from scratch, fine tuning or through transfer learning. Here, right selection of Deep CNN architectures for classification purposes provides high performance rates based on the type of learning employed.

The major goal of the effort is to detect suspicious activities in surveillance video.  The approach created entails a number of stages of suspicious frame recognition and verification, as well as suspicious activity-related analysis of human motions inside a set of discovered suspicious frames. In the work presented here, different types of features are extracted to detect the suspicious activity. The technique includes GLCM feature extraction, which includes features like energy, prominence, contrast, entropy, and homogeneity type of features, matching using Euclidian distance, and descriptor features acquired by using Harris corner features and cosine similarity index estimation. The successful suspicious activity identification rate is examined, demonstrating a better performance and time-saving technique when evaluating a sizable collection of surveillance video.

The adhesive bonding technique is employed from the aeronautical/aerospace industry to current house products. To comply with the requirements of distinct applications, different joint configurations are available to the designer. T-joints are seldom studied in the literature, but these are used, for instance, in aircraft to bond the stiffener beams to the skin, or in the cars between the B-pillar and the rocker. This work initially aims to validate the cohesive zone modelling (CZM) technique with experiments, and then use it to numerically evaluate and optimize the performance of T-joints subjected to peel loads. CZM is nowadays regarded as the most powerful strength prediction tool for adhesive joints, and can be a valuable tool to improve T-joints. Different features are addressed for a complete analysis: adhesive type, geometrical parameters, dual-adhesive technique for strength improvement, and composite joints. The evaluated geometrical parameters are the base adherend thickness (a), T-part thickness (t), overlap or bonding length (l) and curvature radius (r). As a result of this work, the model was successfully validated, and clear design guidelines were provided to define the ideal geometric and material (adhesive) conditions for best performance.

This paper examined properties that focussed on the microphotographs structure, physical properties, and mechanical characterization of the heat-treated 10-year-old cultivated Tectona grandis wood. The harvested wood was subjected to the heat treatment process at 160°C, 200°C, and 240°C for two hours in an electrically powered oil heat-treatment machine. The heat-treated and the control untreated samples were subsequently exposed in the two (2) years grave-yard tests ground. Selected teak wood was taken out after undergoing a certain period of testing. Moreover, the physical properties, such as the moisture content, maximum density, basic density, and volumetric shrinkage were determined. The mechanical properties were assessed using static bending and compression tests focusing on the modulus of elasticity (MOE) and modulus of rupture (MOR). The physicomechanical test was carried out according to the ASTM standard.  The study revealed that the oil heat-treatment process altered the cell structure of the teak wood, particularly at those exposed to elevated temperatures. Changes were observed in the fibre and parenchyma cells of the wood, and the heat treatment process generally improved the properties of the wood, particularly in the physical properties. The Scanning Electron Microscope (SEM) was used to study changes in the wood's anatomy and microstructures especially on treated, untreated, and ground test samples. The study results showed that the oil heat-treatment process improved the durability of teak wood against wood-decaying fungi. Nonetheless, extreme heat treatment temperatures altered the teak wood's cells’ structure, leading to reduced strength in the cell walls but at an acceptable level.

Tubular adhesive connections are mostly subjected to axial or torsional loads. Under axial loads, tubular lap joints (TLJ) lead to peak stresses in the adhesive identically to single-lap joints. An alternative to mitigate peak stresses is to consider a tubular scarf joint (TSJ). This joint enables joining tubes with identical diameters, and the chamfer geometry provides a large bonding area, if the scarf angle (a) is sufficiently small. The proposed work is mainly numerical, and it addresses the tensile behaviour of TSJ between aluminium alloy adherends, and a between 45° and 3.43°, considering different adhesive types. Initial validation of the cohesive zone model (CZM) is accomplished by comparing experimental and numerical data of TLJ. The numerical CZM study that follows addresses the failure path and maximum load (P_m), as a function of a and the adhesive type. The CZM was successfully validated, and clear guidelines were found regarding the best a and adhesive combinations.

This paper examines the evolution of training methods and its historical context. The paper highlights the major changes and innovations that have shaped the training methodology and discusses the implications of these changes for the future of learning and development. The purpose of the research is to identify the roles and functions of the teacher and the student under conditions of the new paradigm in the learning process of adaptive e-Learning. The problem we explore in the paper concerns a paradigm shift in teaching from a bipolar process to a tripolar process. Adaptive e-Learning is a new stage in the evolution of the learning process, where adaptation is achieved between subjects (trainers and learners) and objects (software systems). In adaptive e-Learning environments, the software system that assists and replaces part of the functions of the training teacher takes on an increasingly important role. The role of the teacher has been elevated to a higher organizational, pedagogical and methodical level. The paper outlines these trends by examining learning approaches from a modern perspective, roles and functions of the teacher in e-Learning environment, roles and functions of the student in an e-Environment, models of learning and the characteristics of adaptivity and adaptability e-Learning Systems. Finally conclusions are drawn based on the presented analysis.