The growing advancement of modern digital technologies, including cloud computing systems, data centers, and high-performance computing infrastructures, has led to an increased requirement for reliable high-speed data communication. To support efficient data transfer, Serializer/Deserializer (SerDes) technology is extensively utilized, as it converts parallel data into serial data for transmission and reconstructs it back into parallel form at the receiving end. This process helps minimize interconnection complexity while enabling faster communication speeds. Conventional high-speed communication systems generally use Non-Return-to-Zero (NRZ) signaling, where one symbol carries a single bit of data. However, with the continuous increase in communication speed, NRZ signaling faces challenges such as limited bandwidth availability and signal degradation in high-speed channels. To overcome these drawbacks, modern communication architectures have adopted Pulse Amplitude Modulation with four levels (PAM4). PAM4 improves transmission efficiency by using four distinct voltage levels, allowing each symbol to represent two bits of information and thereby increasing the effective data rate without expanding the required bandwidth. In this project, a configurable PAM4 SerDes simulation platform is developed using a Field Programmable Gate Array (FPGA). FPGA-based implementations provide improved hardware acceleration and enable faster analysis of communication architectures compared to software-based simulation methods. The designed system includes important modules such as a Pseudo-Random Binary Sequence (PRBS) generator and checker, scrambler and descrambler blocks, Gray coding logic, and PAM4 encoding and decoding units to replicate the operation of a high-speed serial communication system. Furthermore, clock gating techniques are incorporated to optimize power efficiency by minimizing unnecessary switching operations in digital circuits. In synchronous systems, clock gating is commonly applied to reduce switching power in sequential logic components while preserving normal circuit functionality. The developed FPGA-based PAM4 SerDes simulation system offers a flexible platform for studying high-speed communication architectures and analyzing system performance under various channel conditions.

The rapid growth of electric vehicles has increased the demand for efficient and reliable battery thermal management systems, especially for lithium-ion batteries used in electric bikes. During charging and discharging, lithium-ion batteries generate a significant amount of heat, which can lead to reduced efficiency, uneven temperature distribution, battery degradation, and severe safety issues such as thermal runaway. Conventional cooling systems used in electric vehicles are often expensive, bulky, non adaptive, and unsuitable for compact applications like e-bikes. To address these challenges, this project proposes an Adaptive Embedded Thermal Control System for Lithium-Ion Batteries in E-Bike that combines embedded control, liquid cooling, and IoT-based monitoring into a compact and energy-efficient solution. The proposed system utilizes an ESP32 microcontroller as the central control unit for real-time monitoring and adaptive thermal regulation. Temperature, current, and voltage sensors continuously monitor the operating condition of the battery pack, while a microchannel liquid cooling system using aluminium cold plates and water-ethylene glycol coolant effectively dissipates excess heat. Based on the sensed battery temperature, a Pulse Width Modulation (PWM)-based adaptive control algorithm dynamically adjusts the coolant pump speed, ensuring efficient cooling only when required and thereby reducing unnecessary power consumption. To validate the effectiveness of the proposed design, thermal simulations and performance analysis were carried out using ANSYS Fluent. The simulation results demonstrated a significant reduction in battery temperature from nearly 50°C to approximately 34°C, while also maintaining uniform temperature distribution across the battery pack with minimal thermal variation. The optimized microchannel cooling structure improved heat transfer performance and reduced hotspot formation, thereby enhancing battery safety, reliability, and lifespan. The developed system provides a practical, low-cost, and scalable thermal management solution specifically suitable for electric bikes and other compact electric mobility applications. By integrating adaptive cooling, embedded intelligence, and IoT-based monitoring into a single platform.

Spectrum sensing is a critical function in cognitive radio and next-generation wireless systems, where reliable detection of available frequency bands must be achieved under strict power and latency constraints. This paper presents an AI-assisted low-power spectrum sensing architecture implemented as a hardware co-processor on FPGA, combining conventional energy detection with a selective TinyML-based classifier. The proposed design performs primary user detection using energy detection (ED) with early stopping, while a lightweight multi-layer perceptron (MLP) neural network is invoked only in uncertain decision regions, significantly reducing computational overhead. The TinyML model is trained offline in MATLAB and deployed for inference using fixed point arithmetic, making the architecture suitable for resource-constrained hardware. A 3-element feature vector comprising signal energy, variance, and zero-crossing rate (ZCR) is used as classifier input. The RTL design is synthesized and verified in Xilinx Vivado with post-mapping and post fitting technology maps confirming successful device implementation. Functional simulation in ModelSim validates correct detection pipeline behaviour. Experimental evaluation demonstrates a detection accuracy of 94.88% with an average AI invocation rate of only 6.72%, and the FPGA-based implementation achieves sub-microjoule energy consumption of 0.1152 µJ per detection (ED-only) and 0.2048 µJ in the worst-case AI-assisted scenario, resulting in nearly 95× lower sensing energy compared to conventional collaborative spectrum sensing. Operating at 50 MHz, the system achieves microsecond-level detection latency.

This project presented the design and implementation of an IoT-based predictive condition monitoring system for CNC machines, specifically the MTAB XLTurn lathe. CNC machines are prone to failures due to excessive vibration, temperature rise, and misalignment, which can lead to reduced productivity and increased maintenance costs. The objective of this work was to develop a cost-effective system capable of real-time monitoring, early fault detection, and estimation of machine health. The system utilized an ESP32 microcontroller integrated with ADXL345 (vibration), LM35 (temperature), and MPU6050 (tilt) sensors for data acquisition. Sensor data was transmitted to MATLAB through serial communication, where signal processing techniques such as Root Mean Square (RMS) and Fast Fourier Transform (FFT) were applied for fault detection and analysis. A multi-sensor threshold-based approach was implemented to reduce false alarms, and Remaining Useful Life (RUL) was estimated based on degradation trends. ThingSpeak was used for real-time data visualization, and Twilio was used for alert notifications. The results demonstrated accurate fault detection, improved monitoring efficiency, and reduced false alarms compared to single-parameter systems. The proposed system provided a scalable and economical solution for predictive maintenance in industrial applications.

This research article explores the role of media, cinema, and literature in fostering professional and vocational development. The study aims to investigate how these forms of expression contribute to skill acquisition, knowledge enhancement, and personal growth, ultimately shaping individuals' professional trajectories. By exploring the impact of media, cinema, and literature on various aspects of professional development, such as skill acquisition, networking, personal branding, and cultural competence, this research highlights the significance of integrating these mediums into educational and training programs. The findings of this research indicate that media, cinema, and literature play a crucial role in skill acquisition and knowledge enhancement. Through exposure to diverse narratives and perspectives, individuals develop critical thinking skills, creativity, and problem-solving abilities. Media literacy skills enable individuals to critically analyse and interpret media messages, while cinema serves as an educational tool that enhances understanding of different cultures and perspectives. Literature, on the other hand, enhances communication skills, including reading comprehension, critical thinking, and verbal expression. The implications of this research are significant for educators, trainers, and policymakers. Integrating media, cinema, and literature into educational and training programs can create a more holistic and enriching learning environment.

Teachers may create a stimulating learning environment where students can develop important intellectual and social skills that will benefit them for the rest of their lives by using the correct teaching strategies. A teacher can assist students with a variety of interests, talents, and learning preferences by implementing one of the available frameworks. To increase your student's chances of succeeding in the classroom, whether you work in the education sector as a teacher or another professional, you might find it helpful to learn about cutting-edge instructional practices. Teaching techniques are approaches that teachers can use to make learning easier and pique students' motivation and interest in the material. Different teaching philosophies include game-based study, differentiated study, lecture-based method, technology-based pedagogy, group and individual study, inquiry-based study, kinesthetic study, game-based study, and expeditionary study. You can enhance your methods by trying out various teaching techniques while presenting the same course, communicating with other educators to acquire their insights, and being flexible. Due to the quick changes in the modern world, the Education System is currently dealing with a wide range of problems. An excellent teaching strategy helps students overcome their preconceptions and motivates them to study by putting them in a situation where they start to believe that they are the ones who come up with the solutions and who are responsible for the change. Professors that are respected both nationally and locally serve as ideal role models for educators who are enthusiastic about effective teaching methods of professional courses, providing them with ideas, insights, and the best teaching methods.(Journal of Advances in Medical Education & Professionalism v.4(4); 2016 Oct PMC5065908)

Language is one of the most marked, conspicuous, as well as fundamental characteristics of the faculties of man. Language is a system of sounds, words, patterns, etc., used by humans to communicate thoughts and feelings. Language is a system of communication which consists of a set of sounds and written symbols which are used by the people of a particular country or region for talking or writing in. The importance of language for man and society cannot be minimized. Language is not only a mode of communication between individuals but also a way for the expression of their personality. Man is remarkably distinguished from animals not only in his use of language but also in his thought process. This use has been termed by Chomsky as “the creative aspect of language; Chomsky suggests that “the normal use of language is innovative, in sense that much of what we say in the course of normal language use is entirely new, not a reception of anything that we have heard before and not even “similar” in “pattern” to sentences or discourse that we have heard in the past” (Chomsky, p.10). Language has its true being in conversation in the exercise and promotion and understanding between peoples. Language should not be a means to impose or transmit my will to another. Above all, language is a living process in which a community of life is lived out. It should be thought that human language as a special and unique living process, in that in linguistic communication, world and human worldview is disclosed. This disclosure, this function of language means that language does not draw attention to itself but transparent to the realities that are manifested through it. Since learning a language is part of our knowledge, it becomes one of the key factors in competitiveness. In the advanced industrial society of today, the basic knowledge of a single or more language has become indispensable.