Journal of Techniques

Metaheuristic algorithms have become dominant in solving different kinds of optimization problems due to their simplicity, adaptability and derivative-free approach. The Smell Agent Optimization (SAO) algorithm is a recent metaheuristic algorithm that is inspired by the concept of smell perception. The algorithm operates in three modes known as sniffing, trailing and random mode. The sniffing mode was modelled based on how an agent perceives the smell molecules. The trailing mode was modelled based on how an agent trails a smell molecule to identify its source. The random mode is a strategy employed by the algorithm to escape the state of confusion known as the local minimum. The SAO just like other metaheuristic algorithms has the problem of local minima, imbalance between exploration and exploitation and slow convergence as a result of the different modes involved. Chaotic maps have been shown to improve the performance of metaheuristic algorithms. The sinusoidal, logistic and singer maps were introduced in each of the modes of SAO to form a new algorithm known as chaotic smell agent optimization (cSAO). This modification was to improve its general performance and convergence of the original SAO. The cSAO was tested on seventeen benchmark functions and the results obtained were compared with SAO and PSO. The statistical result showed that cSAO and SAO obtained the best solution in 12 functions and PSO in 10 functions but cSAO is ranked higher than SAO and PSO with final rank values of 1.33, 1.66 and 1.86 respectively. The cSAO also converges faster than SAO by 25% but fails with PSO due to the number of function evaluations and high exploitation rate of PSO.

The Quadruple Tank Process (QTP) is a laboratory model consisting of four interconnected water tanks, commonly used for control training and research purposes. The proficient regulation of the QTP is imperative, and a variety of controllers, including decentralized proportional-integral controllers, proportional controllers, integral controllers, derivative controllers, and integral-derivative-proportional controllers, are extensively utilized. A Fractional Order PID (FOPID) controller's effectiveness is largely determined by the precise organization of its parameters. This manuscript presents a Multi-Objective Gray Wolf Optimization Fractional Order PID (MOGWO-FOPID) framework, which employs the MOGWO algorithm to enhance the optimization of FOPID controller parameters for the QTP. The suggested methodology was executed and evaluated utilizing MATLAB, with its performance benchmarked against pre-existing, well-established tuning methodologies. Simulation findings indicated that the MOGWO-FOPID technique surpassed conventional methods. This superiority was corroborated through a variety of evaluation metrics, particularly emphasizing the Spacing Metric (SP) and Non-uniformity of Pareto Front (NPF) analysis. The outcomes reveal considerable advancements in both system stability and performance when employing the proposed methodology, thereby offering a more efficacious strategy for the optimization of FOPID parameters in the QTP.

The dual-band microstrip is designed to be compatible with Internet of Things (IoT) applications, Bluetooth, and Wi-Fi standards, ensuring reliable communication for short- and medium-range IoT devices. Utilizing an FR4 substrate, the antenna achieves excellent return loss, satisfactory gain, and near-omnidirectional radiation patterns, making it ideal for compact IoT devices. This paper presents a dual-band Vivaldi antenna for IoT applications operating at 2.4 GHz and 5.8 GHz. Designed and optimized using ADS software, the antenna achieves a compact layout on FR4 with enhanced return loss and radiation performance. The proposed design achieves a return loss of –32 dB at 2.4 GHz and –17.6 dB at 5.8 GHz, with bandwidths of 660 MHz and 640 MHz, respectively. Radiation efficiencies reached 80% and 78%. These results confirm the antenna’s suitability for short- and mid-range wireless protocols such as Wi-Fi and Bluetooth. Future work may explore integration with RF energy harvesting and real-world multipath testing.

Virtual Private Networks are essential for securing Internet communication, but the selection of a VPN protocol can substantially affect overall network performance. Nonetheless, typical VPN protocols (e.g., OpenVPN) are too secure relative to their worst-case latency and computational overhead. New-generation VPN protocols, such as WireGuard, are promising to offer greater efficiency due to a lightweight cryptographic design. This paper depicts a comparison trial of OpenVPN and WireGuard throughput under controlled cooperation. Download and upload speeds, latency, and CPU and RAM utilization were measured using a Speedtest application on a Windows 11 platform. The results reveal that WireGuard achieved network performance approaching the baseline, with 50.4 Mbps download speeds, low latency (8.01 ms), and low CPU consumption (3%). In contrast, OpenVPN decreased download speeds to 22.1 Mbps and was accompanied by high latency (160.38 ms). The results imply that WireGuard is a valid choice for latency-sensitive and throughput-demanding use cases. In contrast, OpenVPN is appropriate for use cases that focus on interoperability and established security.

The growing issue of energy shortages has been exacerbated by the increasing demand for air conditioning in tropical regions. This has highlighted the need for supplementary methods to reduce the load on air conditioning systems and thereby lower energy consumption. The objective of this study is to evaluate the effectiveness of silica gel-Blue as a dehumidifying agent for removing moisture generated from sources such as human respiration, perspiration, and household activities like ironing. To address this problem, a dehumidification system was designed consisting of several shelves loaded with silica gel-blue to help absorb moisture. Experimental tests were conducted using a dehumidification system in conjunction with an air conditioning system, measuring its moisture absorption capacity and its impact on relative humidity and energy consumption. The results showed that relative humidity levels decreased to 33%, 29%, and 25% in June, July, and August, respectively, when using the combined system. The moisture absorption rates of silica gel-Blue were recorded as 83.39 g/h in June, 70.82 g/h in July, and 65 g/h in August. It was also found that approximately 750 g of silica gel-blue was required to remove the moisture produced by one person. Furthermore, the electrical energy consumption was reduced to 3.5 kWh with the dehumidification system, compared to 5.1 kWh without it. These findings confirm the efficiency of silica gel-Blue in humidity control and demonstrate its potential for reducing energy usage when integrated with air conditioning.

This study investigates the resistance spot welding (RSW) of two different steels, AISI 1005 and AISI 304L, using both experiments and computer simulations. Researchers used a Taguchi L16 design to test how welding current, squeeze time, welding time, and hold time affect tensile-shear strength (TSF). The best welding setup reached a TSF of 78.86 MPa, while the lowest settings gave 44.31 MPa. Simulations in COMSOL Multiphysics modeled the thermal, electrical, and mechanical behavior of the welds. The predicted TSF values matched the experiments closely, with less than 5% difference. Free-vibration modal analysis was also done for cantilever and fixed-fixed setups. The experimental and simulated eigenfrequencies were similar, with errors within ±3%, supporting the accuracy of the model. These results show that choosing the right RSW parameters can greatly improve both the strength and stiffness of AISI 1005/AISI 304L joints.

This work aims to reuse waste from drinking water treatment plants that use alum, called alum sludge (AS). By calcining alum sludge (CAS) at 550 °C for two hours, then using it to adsorb the heavy metals copper and cadmium from their aqueous solutions with the batch adsorption method. The ability of CAS to remove Cd (II) and Cu (II) was studied under the influence of several factors (i.e., initial concentration of metal ions, contact time and CAS dosage) by using Box-Behnken experimental designs (BBD) for the response surface methodology (RSM) and with statistical analysis (ANOVA). Then, identify the optimal conditions that produce the maximum removal. The AS, which has been dried and ground was characterized by chemical method analysis (SEM, XRD, and EDX). At optimum conditions, the maximum removal percentages of Cu and Cd reached 92.5% and 98.8%, respectively. The adsorption isotherms for Cu data followed the Langmuir model, while the Cd data fitted well with the Freundlich and the Langmuir models. For each Cd (II) and Cu (II), the maximum monolayer adsorption capacity was 29.101 and12.45 mg/g, respectively. The pseudo-second-order kinetic model provided a good match to the kinetic data. It was found that water treatment sludge is a good source from which to create an inexpensive adsorbent to remove heavy metal ions from wastewater.

The inherent heterogeneity of Renal Cell Carcinoma (RCC) is a major obstacle to its treatment which necessitates the implementation of precision medicine approaches. The presented work introduces a full-scale computational model for quantitative modeling and evaluation of therapy plans by means of multi-omics data integration. A scaled synthetic dataset of 1,200 RCC patients was generated, including clinical information, gene expression data, and patient somatic mutation data, which carry intrinsic molecular signals of simulated treatment efficacy and patient survival. In order to predict treatment response, trained three machine learning models: Logistic Regression (accuracy, the Random Forest (accuracy and the Gradient Boosting (area under the curve (AUC)). All models achieved an ideal value of 1.00. This validated their good ability to determine molecular drivers and they ran a good analysis using Random Forest feature importance analysis to determine the important genes affecting their prediction. Treatment efficacy was therapeutically relevant, showing a highly significant difference in prognosis between Non-Responders and Responders (p<0.005) as shown by the survival comparison analysis based on Kaplan-Meier curves and using a Log-rank test. Multi-omics characteristics were also tested to be prognostically independent of survival in a Cox Proportional Hazards model. Unsupervised K-Means clustering has revealed that various groups of patients existed and that UMAP visualization showed an excellent level of agreement with such molecular groupings and response to treatment. This article demonstrates a successful proof of principle of an integrative computational approach that is able to accurately predict the outcome of a treatment protocol, discover important biomarkers and characterize a population into physiologically meaningful subpopulations. These findings demonstrate the tremendous potential of the multi-omics model to improve patient care for individuals with renal cell carcinoma.

As the intelligent era advances at a rapid pace, the increasingly intricate electromagnetic environment is generating an urgent demand for high-performance, intelligent electromagnetic interference (EMI) shielding materials. Endowed with intrinsic high conductivity, superior hydrophilicity, abundant surface chemistry, and tailorable microstructure, MXenes serve as an ideal platform for constructing next-generation intelligent EMI shielding materials. This review elaborates on the design strategies and response mechanisms of MXene-based intelligent EMI shielding materials with different response types. It specifically clarifies the structure-activity relationship between the evolution of material microstructure and the dynamic modulation of electromagnetic parameters. It reveals the advantages and limitations of different systems through comparative analysis

This study investigated the effect of varying bioactive glass (BG) concentrations (8–14 g/L) on the structural, electrochemical, and adhesive properties of coatings deposited on Ti-6Al-7Nb substrates via electrophoretic deposition (EPD). The SEM and EDS analyses demonstrated that rising BG concentration from 8 g/L to 14 g/L enhanced the coating uniformity, reduced the porosity and enhanced the particle packing. The coating thickness increased from 41.1 μm to 57.3 μm. Zeta potential measurements showed increased suspension stability with higher BG content, reaching 18.47 mV at 14 g/L. Corrosion resistance is enhanced with BG content, with the 14 g/L coating reaching the lowest corrosion current density (5.19 × 10⁻⁸ A) and rate (4.509 × 10⁻⁴ mmpy). Adhesion tests rated the 14 g/L BG coating as 1B due to better interlocking.