A. Srivatsa, Kavya A.P., F. Fareesha, Lekhana G., Gowthami V. and Chandanashree Y.K., “Prototype for Stress-Based Viral Fever Prediction,” Trans. Appl. Sci. Eng. Technol., vol. 1, no. 2, pp. 1-12, 2025.

This paper presents the development of a prototype device for predicting viral fever by monitoring stress levels through cortisol detection. Research indicates a negative correlation between the immune system’s strength and prolonged high stress levels. As stress increases, the immune system weakens, making individuals more susceptible to viral fevers and infections. The primary goal of this study is to design a device that tracks stress levels by measuring cortisol, a neuroendocrine hormone released during stress. Our approach utilizes a synthetic form of cortisol to construct the prototype, employing infrared (IR) sensing technology with IR LEDs and photodiodes to detect cortisol levels. This innovative device aims to provide an early warning system for viral infections by continuously monitoring and analyzing stress-induced hormonal changes.

Z.B. Akhtar and A.T. Rawol, “Invigorating Internet of Things (IoT) Security within the Era of Artificial Intelligence (AI): Challenges, Innovations, and Future Pathways,” Insight. Electr. Electron. Eng., vol. 2, no. 2, pp. 1-14, 2025.

As the accretion towards Internet of Things (IoT) expands and artificial intelligence (AI) becomes increasingly integrated into everyday technologies, safeguarding the security and privacy of IoT devices has become critical. This research exploration investigation presents a comprehensive analysis of the intersection between IoT, AI, and cybersecurity, identifying key challenges, proposing innovative strategies, and envisioning a secure future for IoT ecosystems. By exploring the intricate dynamics of IoT security within the realms of AI, cloud computing, and mobile internet, this research also highlights the evolving threats and emerging solutions. It offers a multidimensional perspective on the interplay between these technologies, providing valuable insights into building robust and secure IoT infrastructures in the age of AI.

C.A. Alexander and L. Wang, “Integrating Technology Risks, Compliance, Audits, and Privacy,” Insight. Electr. Electron. Eng., vol. 2, no. 1, pp. 1-6, 2025.

Technologies such as the cloud, information and communications technology (ICT), the Internet of Things (IoT), and wearable wireless medical sensor networks have brought benefits and opportunities; however, they have also introduced increased risks and challenges. This paper introduces technology risks, compliance, audits, and privacy. ICT-based assets, cloud, IoT, wearable wireless medical sensor networks, etc., often suffer from cyberattacks. A compliance audit is often needed. Privacy and security issues can arise in various areas, including devices, storage, and communication. This paper will also present a case study of integrating technology risks, compliance, audits, and privacy in the Emerald Healthcare System. Advanced technologies, adherence to compliance, regular auditing, privacy protection, and related controls for vulnerabilities and cyber risks help Emerald Healthcare System practice robust cybersecurity.

K. Jones, “A Comparison of Two Schemes, Based upon Multi-Level LUTs and Second-Order Recursion, for Parallel Computation of FFT Twiddle Factors,” Trans. Appl. Sci. Eng. Technol., vol. 1, no. 1, pp. 1-11, 2025.

The paper describes two schemes, together with architectures, for the resource-efficient parallel computation of twiddle factors for the fixed-radix version of the fast Fourier transform (FFT) algorithm. Assuming a silicon-based hardware implementation with suitably chosen parallel computing equipment, the two schemes considered provide one with the facility for trading off the arithmetic component of the resource requirements, as expressed in terms of the numbers of multipliers and adders, against the memory component, as expressed in terms of the amount of memory required for constructing the look-up tables (LUTs) needed for their storage. With a separate processing element (PE) being assigned to the computation of each twiddle factor, the first scheme is based upon the adoption of the single instruction multiple data (SIMD) technique, as applied in the ‘spatial’ domain, whereby the PEs operate independently upon their own individual LUTs and may thus be executed simultaneously; the second scheme is based upon the adoption of the pipelining technique, as applied in the ‘temporal’ domain, whereby the operation of all but the first LUT-based PE is based upon second-order recursion using previously computed PE outputs. Although the FFT radix and LUT level (where the LUT may be of either single-level or multi-level type) may each take on arbitrary integer values, we will be particularly concerned with the radix-4 version of the FFT algorithm, together with the two-level version of the LUT, as these two algorithmic choices facilitate ease of illustration and offer the potential for flexible computationally-efficient FFT designs. A brief comparison of the resource requirements for the two schemes is provided for various parameter sets that cater, in particular, for those big data memory-intensive applications involving the use of long (with length of order one million) to ultra-long (with length of order one billion) FFTs.

P. Lu, “Technological Exploration and Case Analysis of Using SAP IBP's Demand Sensing and Statistical Model for Demand Forecasting, Inventory Reduction, and Supply Chain Improvement,” Trans. Appl. Sci. Eng. Technol., vol. 1, no. 1, pp. 1-5, 2025.

This paper explores the innovative use of SAP Integrated Business Planning (IBP)'s demand sensing and statistical model to enhance demand forecasting accuracy, reduce inventory levels, and improve the overall efficiency of the supply chain. Through a real-world case study, we demonstrate the effectiveness of this approach and provide quantitative data, visualizations, and tables to support our findings. The proposed method shows significant potential in revolutionizing traditional supply chain management practices.

S. Osmanagich, “The Bosnian Pyramids as Prehistoric Energy Machines: Multidisciplinary Evidence for Ancient Technology and Focused Energy Beams,” Trans. Appl. Sci. Eng. Technol., vol. 1, no. 1, pp. 1-13, 2025.

This study challenges long-held assumptions about the function of pyramidal structures by presenting multidisciplinary evidence from the Bosnian Pyramid Complex in Visoko, Bosnia-Herzegovina. Contrary to the conventional interpretation of pyramids as funerary monuments, this research suggests that these structures were deliberately designed as energy machines, amplifying natural electromagnetic fields, generating focused energy beams, and exhibiting geometric and material properties that defy natural formation. Through satellite imaging, LiDAR analysis, archaeological excavation, field measurements, Monte Carlo simulations, and comparative studies with global megalithic sites, this article explores the hypothesis that the Bosnian pyramids were part of a technologically sophisticated prehistoric infrastructure. Findings include: true north orientation to within 12 arc seconds, organized concrete-like construction blocks, electromagnetic and ultrasound emissions at 28.5 kHz, and geometric site planning consistent with sacred geometry and the golden section. These converging lines of evidence suggest intentional design for energy generation, positioning the Bosnian Pyramid of the Sun as a case study in re-evaluating ancient technological capabilities.