Iterated Local Search (ILS) is a well-established metaheuristic that has been widely applied to combinatorial optimization problems owing to its balance between solution diversification and intensification. This work emphasizes ILS for the scope of the Asymmetrical Traveling Salesman Problem (ATSP) and the Asymmetrical Generalized Traveling Salesman Problem (AGTSP) respectively, which accounts for the directionally dependent costs of routes and cluster of nodes recognized in the routing difficulties of real-world applications. The experiment also assesses whether ILS can explore difficult search regions while also conserving solution quality and avoiding rapid convergence. This study examines the feasibility of ILS when using TSPLIB benchmark instances subject to directed route costs, time windows and load capacity constraints, while including a realistic routing network, including depots, customers and stops, alongside an examination of the systematic conversion of symmetric TSP instances into asymmetric representations to accurately capture directionally dependent travel costs. The results demonstrate that ILS can produce high quality solutions to both the ATSP and AGTSP under conditions of increasingly complicated routing. Future research will be directed towards improving ILS with a hybrid metaheuristic framework and subject to large scale logistics datasets to improve viability and scale capability.
This paper presents a small, scalable, and affordable solar-powered inverter system, designed to provide a continuous power supply in off-grid settings and during grid outages worldwide. The proposed system utilizes lithium-ion batteries charged by solar energy to power a high-efficient and low power dissipation inverter constructed using durable power transistors, a step-up transformer, and a custom-designed filter circuit. The inverter generates a near-sinusoidal AC output capable of supporting a wide range of loads, thereby reducing dependency on fuel-generated grid electricity, particularly in underserved regions. The system emphasizes cost-free energy storage and reducing energy losses within components. It maintains a stable near-sinusoidal voltage under practical load conditions. The modular design integrates energy conversion, storage, and AC power delivery into a unified system. With a Total Harmonic Distortion (THD) of only 2.17%, the inverter delivers high-quality voltage output with a near-sinusoidal waveshape at lower complexity compared to conventional systems. The system is suitable for mobile applications, emergency supply of power during outages, disaster relief, and rural electrification. The proposed solution demonstrates the accessibility and effectiveness of solar technology in practical, real-world applications.
In this work, various stationary objects were detected within a room measuring 4.88 × 3.91 m². The data were captured by a 24 GHz commercial radar module, OPS243-C. The experiments were performed in two scenarios: over each wall or at different angles of the radar positions, and, secondly, by mounting this radar module on a rotating motor to scan each object over a 360° coverage. In addition, to suppress background noise and filter out strong signals in the heatmap results, a noise threshold and a Gaussian smoothing filter were applied. The predicted distances of objects were then obtained by applying suitable curve-fitting models to radar data captured in each scenario. The corresponding images captured in each scenario were used to validate the 2D and 3D heatmaps for object distances after curve fitting. Thus, for each wall scan, a linear curve-fitting model was found to be sufficient, whereas for entire-room scanning, a 6th-order polynomial curve-fitting model was found to provide the best predicted distances by the module. The methodology discussed in this work is useful for analyzing field-grown crops and continuously monitoring their health.
The increasing complexity of electronic components and their stringent performance requirements necessitate precise and reliable testing methodologies. This study explores the development and implementation of a pin electronic system with level specification using Automated Test Equipment (ATE) testers. The purpose of ATE implementation is to drastically reduce human error, increase test throughput, and provide precise, real time data analysis. By utilizing advanced ATE platforms, the study evaluates the accuracy, repeatability, and scalability of the testing process. The proposed approach for the creation of the DTI board is to study the behavior of components that contribute to the levels of VIH, VIHH, and VIL values, thus, influencing the measurement of the PE electronic pins. The results demonstrate significant improvements in measurement precision and test cycle efficiency, offering a robust solution for quality assurance in semiconductor manufacturing. These findings provide valuable insights into optimizing test protocols for high-performance electronic components and pave the way for future advancements in ATE-driven testing methodologies.
In the modern digital environment, where vast amounts of multimedia data are continuously exchanged across global networks, ensuring secure and covert communication has become a critical challenge. Steganography plays a crucial role in this context by allowing the imperceptible embedding of secret information into digital media, including images, audio, and video signals. However, most state-of-the-art steganographic methods rely on computationally intensive mathematical transforms, including the Discrete Cosine Transform (DCT), Singular Value Decomposition, and various wavelet-based or deep-learning-based approaches. While these techniques achieve high robustness and embedding capacity, their high computational complexity limits practical implementation on resource-constrained platforms such as mobile devices, embedded systems, and Internet-of-Things environments. A promising direction for overcoming these limitations is the development of code-controlled steganographic methods, which operate directly in the spatial domain. Their efficiency is based on establishing deterministic relationships between DCT coefficients and those of the Walsh-Hadamard Transform (WHT), enabling precise code-based control of the embedding process. To date, such research has been limited to classical Sylvester-type Hadamard matrices. However, multiple non-equivalent classes of Hadamard matrices exist, and exploring their properties may unlock new opportunities for efficient and secure information embedding. This paper presents a comprehensive analysis of the correspondence between DCT coefficients and WHT coefficients derived from five non-equivalent classes of Hadamard matrices of order 16. Large-scale experimental research was performed using 530 images from the NRCS public database. Each image was processed in 16×16 blocks, with controlled perturbations applied to individual DCT coefficients. The resulting changes in WHT coefficients were analyzed to determine the mappings between the transform domains. The results reveal that while the classical Sylvester matrix preserves a one-to-one correspondence with DCT, non-classical Hadamard matrix constructions exhibit overlapping mappings, particularly in the high-frequency range. This overlap, although reducing spectral resolution, introduces beneficial redundancy for steganographic applications, enhancing robustness and resistance to steganalysis. The findings provide a foundation for developing high-performance, spatial-domain steganographic schemes that exploit the structural diversity of non-classical Hadamard matrices for improved efficiency and security.
