EMITTER-International Journal of Engineering Technology

Scope & Guideline

Connecting Academics and Industry for Enhanced Technological Development

Introduction

Welcome to your portal for understanding EMITTER-International Journal of Engineering Technology, featuring guidelines for its aims and scope. Our guidelines cover trending and emerging topics, identifying the forefront of research. Additionally, we track declining topics, offering insights into areas experiencing reduced scholarly attention. Key highlights include highly cited topics and recently published papers, curated within these guidelines to assist you in navigating influential academic dialogues.
LanguageEnglish
ISSN2355-391x
PublisherPOLITEKNIK ELEKTRONIKA NEGERI SURABAYA
Support Open AccessNo
Country-
Type-
Converge-
AbbreviationEMITTER / EMITTER
Frequency2 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressJL RAYA ITS, KAMPUS PENS SUKOLILO, SURABAYA 60111, INDONESIA

Aims and Scopes

The EMITTER-International Journal of Engineering Technology focuses on the intersection of engineering and technology, emphasizing innovative solutions and advancements in various fields. The journal aims to publish high-quality research that contributes to the development of engineering practices and technologies.
  1. Engineering Innovations:
    The journal publishes research on novel engineering methodologies and technologies, including the design, analysis, and implementation of innovative systems.
  2. Applied Technology Research:
    Studies often focus on practical applications of technology across various sectors, such as telecommunications, robotics, and renewable energy.
  3. Interdisciplinary Approaches:
    Encourages research that combines principles from different engineering disciplines, fostering collaboration and integration of technologies.
  4. Machine Learning and AI Applications:
    With a growing emphasis on AI, the journal explores the use of machine learning techniques in engineering problems, including image processing and predictive analytics.
  5. Sensor and IoT Technologies:
    Research on the development and application of sensors, IoT devices, and their integration into systems for enhanced monitoring and automation.
Recent publications in the EMITTER journal indicate a clear trend towards modern, technological advancements in engineering. Emerging themes reflect the journal's responsiveness to current technological challenges and innovations.
  1. Deep Learning and AI Integration:
    There's a marked increase in research utilizing deep learning techniques across various applications, from medical imaging to automated systems, indicating a strong trend toward AI integration in engineering.
  2. 5G and Next-Generation Networks:
    Research on 5G technology and its applications is gaining momentum, with studies focusing on network slicing, performance analysis, and machine learning integration.
  3. Environmental and Sustainable Engineering:
    An emerging focus on sustainability, particularly in renewable energy systems and smart technology solutions, reflects a growing concern for environmental impact.
  4. Smart IoT Solutions:
    The development of smart solutions leveraging IoT technology is increasingly prominent, addressing real-time monitoring and automation challenges.
  5. Health Informatics and Biomedical Engineering:
    The rise in studies related to health informatics, particularly in utilizing AI for diagnostics and patient monitoring, showcases the intersection of technology and healthcare.

Declining or Waning

As the journal evolves, certain themes that were previously prominent are becoming less frequent in recent publications. This trend highlights a shift in focus towards more contemporary and pressing topics within engineering technology.
  1. Traditional Energy Systems:
    Research related to traditional energy systems, such as fossil fuels, is being overshadowed by a shift towards renewable energy and sustainability.
  2. Basic Communication Protocols:
    Studies focusing solely on basic communication protocols are declining as researchers now prefer exploring advanced networking techniques, especially in the context of 5G and beyond.
  3. Static Data Analysis:
    The trend is moving away from static data analysis methods towards dynamic and real-time data processing, particularly in machine learning applications.
  4. Conventional Manufacturing Techniques:
    Interest in conventional manufacturing methods is diminishing in favor of advanced manufacturing technologies, such as 3D printing and automation.
  5. Simple Predictive Models:
    There is a noticeable decline in the use of simple predictive models, as the focus shifts to more complex, hybrid models that incorporate machine learning.

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