​In the realm of advanced natural language processing (NLP) architectures, the Push-Pull Transformer stands out as a cutting-edge innovation. Born from the fusion of traditional Transformers and novel information exchange mechanisms, this hybrid model breaks away from conventional self-attention paradigms. The core idea is to introduce a push operation that actively shares context-rich representations between encoder and decoder, while a pull mechanism retrieves selective information for improved efficiency.

​In the era of Industry 4.0, the integration of magnetic latching relays (MLRs) with current transformers (CTs) is revolutionizing the way we control and manage power systems. These innovative combinations are fostering smart manufacturing and improving overall system efficiency.

​Transformers have revolutionized the field of power electronics, transforming the way we transmit and utilize electrical energy. This versatile technology finds application in various sectors, from power distribution to telecommunications.

As the industrial landscape transitions into the era of Industry 4.0, current transformers (CTs) are experiencing a transformational shift. They serve as vital components in the modernization of power systems, energy management, and automation.

​DC Current Transformers (DCCT), also known as direct current transformers, play a pivotal role in the efficient and reliable monitoring of direct current (DC) power systems. These devices are designed to transform high-level DC currents into measurable secondary signals that can be read by instruments or control systems without being affected by electromagnetic interference.

The medical field, known for its strict regulations concerning patient confidentiality, has long sought innovative solutions to leverage big data without compromising privacy. This article focuses on the role of isolation transformers in addressing these challenges, showcasing how they enable secure and efficient analysis of sensitive health data.

In the rapidly evolving landscape of data science and machine learning, isolation transformers have emerged as a pivotal technology, particularly in scenarios requiring robust data privacy. This paper delves into the innovative design principles of isolation transformers and their significant contributions to distributed systems. We will explore how these models, originally proposed by researchers in the field of deep learning, facilitate secure data processing without the need for direct data sharing or exposure.

​High frequency transformers are crucial components in various electronic devices, ranging from power supplies and converters to telecommunications systems. These transformers operate at frequencies above 20 kHz, necessitating the selection of suitable materials that can efficiently handle high frequency signals. Ferrite materials have emerged as a popular choice due to their unique properties and advantages in high frequency transformer applications. This article delves into the role of ferrite materials in high frequency transformers, highlighting their benefits and characteristics.