IAES Institute of Advanced Engineering and Science

30/10/2024

https://youtu.be/YuR0r-E7FJI
The study proposes an improved Random Forest (RF) algorithm based on hierarchical clustering (HCRF). HCRF optimizes feature selection by establishing similar feature groups based on the GINI index and selecting features proportionally to construct a feature subset. This process reduces the impact of useless and redundant features, improving the model's generalization ability and overall performance. The HCRF algorithm showed significant improvements in all evaluation indicators, making it superior to other classifiers.



Master Program of Electrical Engineering (MEE), UAD
https://mee.uad.ac.id/

Authors: Wang Zhuo, Azlin Ahmad (IJEECS ID 38396)Random Forest (RF) selects feature subsets randomly. Useless and redundant features will lower the quality ...

24/10/2024

Electro-capacitive cancer therapy using wearable electric field detector: a review
DOI: https://doi.org/10.11591/csit.v5i3.p292-305

ECCT, or Electro-capacitive Cancer Therapy, is a non-invasive, personalized approach to cancer treatment using wearable electric field detectors. These devices detect changes in electric fields, providing real-time monitoring for personalized treatment plans. The safety and efficacy of electric field exposure in vital organs are being investigated, contributing to improved diagnostic techniques and safety measures in medical and engineering fields. This technology enhances personalized medicine, improving treatment outcomes and patient quality of life.

Electro-capacitive cancer therapy using wearable electric field detector: a review

24/10/2024

Capabilities of cellebrite universal forensics extraction device in mobile device forensics
DOI: https://doi.org/10.11591/csit.v5i3.p254-264

Cellebrite UFED is a digital forensics tool that aids investigators in solving criminal and cybersecurity cases by extracting and analyzing mobile device data. It can recover data from erased or obscured devices, including call logs, texts, emails, and social media. The intuitive user interface speeds up data extraction, revealing crucial information. Legal and ethical considerations are crucial in mobile device forensics, with AI and ML algorithms potentially automating data extraction in future tools.

Capabilities of cellebrite universal forensics extraction device in mobile device forensics

24/10/2024

Securing DNS over HTTPS traffic: a real-time analysis tool
DOI: https://doi.org/10.11591/csit.v5i3.p227-234

A study developed a live tool to analyze DNS over HTTPS (DoH) traffic and classify it as benign or malicious. Using machine learning algorithms like K-NN, RF, DT, DNN, and SVM, the tool achieved exceptional performance. It integrates with the Mallory tool for local DNS resolution, allowing for more accurate simulation of DoH queries. The tool's effectiveness in network security and threat detection is confirmed.

Securing DNS over HTTPS traffic: a real-time analysis tool

24/10/2024

Adversarial attacks in signature verification: a deep learning approach
DOI: https://doi.org/10.11591/csit.v5i3.p215-226

This study develops a handwritten signature verification system using a convolutional neural network (CNN) and hand-crafted adversarial attacks. The model achieved a testing accuracy of 91.35% and a robust validation accuracy of nearly 98%. However, the model's accuracy is reduced to nearly 80% when manually constructed adversarial assaults are introduced. The study emphasizes the need for considering adversarial resilience in deep learning models for classification tasks.

Adversarial attacks in signature verification: a deep learning approach

20/09/2024

Congratulations to all the authors!!
The Bulletin of Electrical Engineering and Informatics has just released its December 2024 issue (early access).

Alhamdulillah, all published papers in this journal until the October 2024 issue have been indexed by Scopus and can be found at https://www.scopus.com/sourceid/21100826382.

This open-access peer-reviewed journal publishes the results of original research, reviews, surveys, or new data/concepts in all fields of interest, including electrical engineering, electronics, instrumentation, control, robotics, telecommunication, computer engineering, information systems, information technology, and informatics (computer science).

20/09/2024

Congratulations!! The International Journal of Evaluation and Research in Education (IJERE) has just published its December 2024 issue (for early access), and the published papers are available until the October 2024 issue (previous issue) at https://www.scopus.com/sourceid/21100934092.

07/09/2024

https://youtu.be/ePfhmapme4s
A three-phase model for detecting keywords in Arabic corpus

The study focuses on detecting keywords in Arabic text data, addressing the growing demand for refined techniques. It introduces a novel corpus and approach consolidating three candidate lists: frequency-based, vector space, and machine-learning. Experimental validation confirms the pipeline's effectiveness, with F1-scores exceeding 91%.

Authors: Driss Namly, Karim Bouzoubaa, Ridouane Tachicart (IJEECS ID 38741)The exponential growth of Arabic text data in recent years highlights the necessit...

30/08/2024

Scopus.com has indexed all 84 papers published in 2024 ❤️🤝.
The International Journal of Reconfigurable and Embedded Systems (IJRES) https://ijres.iaescore.com p-ISSN 2089-4864, e-ISSN 2722-2608.
The IJRES is an open access and peer-reviewed journal. This journal has a SCImago Journal Rank (SJR) of 0.159 (Q3). It has a CiteScore of 1.5 and SNIP of 0.374.

International Journal of Reconfigurable and Embedded Systems

19/08/2024

Convolutional neural networks breast cancer classification using Palestinian mammogram dataset
https://youtu.be/dDsSDReWVcE

Breast cancer is a global issue, with mammogram screening being the most common method for diagnosing abnormalities. However, the lack of skilled experts makes it challenging to interpret mammograms accurately. Machine learning can help in early detection, especially when treatment is less expensive and available. A study using six CNN models on a Palestinian Ministry of Health dataset showed DenseNet121 outperformed other models in testing accuracy and AUC. Future work could combine the model with other patient data to evaluate the risk of specific diseases, increasing survival rates and enabling proactive measures.

Authors: Hanin Saadah, Amani Yousef Owda, Majdi Owda (IJEECS ID 36997)Breast cancer is widespread across the globe. It’s the primary cause of death in cancer...

19/08/2024

Integrating Computing Techniques in Preserving Makassar's Pakarena Dance Heritage
https://youtu.be/c950SWHfED8

The study explores the Pakarena Dance, a cultural heritage of Makassar ethnicity, using digital technologies for data collection, analysis, and dissemination. The research uses a qualitative framework, digital ethnography, in-depth interviews, and advanced data analysis to preserve the dance's narrative and expression. The study highlights the potential of computing and informatics in cultural preservation and advocates for technology's use to enhance and perpetuate cultural heritage, especially for younger generations in the digital era.

Authors: Nurlina Syahrir, Alimuddin Alimuddin (IJEECS ID # 38130)This interdisciplinary study bridges the cultural heritage of the Pakarena Dance, a key eleme...

19/08/2024

Modified -Vehicle Detection and Localization model for Autonomous Vehicle Traffic System
https://youtu.be/J-ax2yM3-yM

An evolving trend in India is the modification of vehicles for financial gain. Recognizing and detecting these modified illicit cars is an important but critical task in autonomous vehicles. It is always possible for a cyclist or pedestrian to traverse obstacles or other fixed objects that appear in front of any moving vehicle. Vehicles that are autonomous or self-driving require a different system to quickly identify both stationary and moving objects. We propose a deep learning model, YOLOv5-CBAM, for the Indian traffic system, based on YOLOv5m. The proposed algorithm, YOLOv5-CBAM, has three major components. We employ the first module, the backbone module, for feature extraction. The second module simultaneously detects static and dynamic objects, while the backbone and neck parts adopt the third CBAM module, primarily focusing on the more prominent features. We used two CSP modules after each convolutional layer, creating an additional head for the proposed model. Four head modules equipped with anchor boxes performed the final detection. For the present dataset, the proposed model showed 98.2% mAP, 98.4% precision, and 94.8% recall as compared to the original YOLOv5m.

Authors: Amit Juyal, Sachin Sharma, Shuchi Bhadula (IJEECS ID 37474)An evolving trend in India is the modification of vehicles for financial gain. Recognizin...

19/08/2024

https://youtu.be/niEqan1qv9U

In this paper, we aim to develop a Trusted Secured Routing Ad-hoc On-Demand Distance Vector Protocol to fight against blackhole attacks within the wireless body area network. The trusted secure routing protocol integrates a trust value-based routing strategy to identify malicious nodes, a node residual energy-based routing technique to identify the node with the highest residual energy during communication, and a hybrid cryptography algorithm that combines the Affine cipher and the modified RSA cipher algorithm to safeguard communication against malicious biomedical sensor attacks. The results of the simulation show that the suggested protocol works better than the standard ad hoc on-demand distance vector routing protocol in every test metric, such as data rate, energy use, packet delivery ratio, and delay. Its main strength is that it considers several factors, unlike similar secured routing protocols, such as illegitimate medical sensor detection, efficient network energy use, and secure data transmission. Furthermore, the hybrid cipher algorithm improves the effectiveness and increases the security level of sensitive data compared to traditional cipher algorithms such as the Affine cipher and the RSA cipher.

Authors: Mohammed Abdessamad GOUMIDI, Ehlem Zigh, Adda Belkacem Ali-Pacha (IJEECS ID 37822)In this paper, we aim to develop a Trusted Secured Routing Ad-hoc ...

24/07/2024

ADMISSION OPEN | Empower Your Future, Apply Now!
https://mee.uad.ac.id/pendaftaran/

21/07/2024

20/07/2024

Are there full scholarships for international students?
https://mee.uad.ac.id/pendaftaran/

26/06/2024

Dear colleagues,

We cordially invite you to the 2024 11th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI) that will be held on 26-27 September 2024 as virtual conference. The conference is hosted by Universitas Ahmad Dahlan and is jointly organized with Universitas Islam Sultan Agung, Universitas Diponegoro, Universitas Sriwijaya, Universiti Teknikal Malaysia Malaka (UTeM), Universiti Teknologi Malaysia (UTM) and IAES Indonesia Section. This Conference is aimed to bring researchers, students, engineers and practitioners together to participate and present their latest research finding and developments related to the various aspects of electrical, electronics, power electronics, instrumentation, control, robotics, computer & telecommunication engineering, signal, image & video processing, soft computing, computer science and informatics.

The EECSI 2024 has been approved by IEEE for Technical co-sponsorship with conference record number #63442 (https://conferences.ieee.org/conferences_events/conferences/conferencedetails/63442). All accepted, registered and presented papers will be submitted to IEEE Xplore® Digital Library.

In addition, we are happy to announce that the proceedings of the previous series of conference (2017-2023) have been indexed in Scopus and IEEE Xplore as well.

Paper Submission Link: https://edas.info/N32097

--- IMPORTANT DATES (EXTENDED) ---

Papers Submission Deadline (extended): July 15, 2024
Acceptance Notification (extended): August 10, 2024
Camera Ready Submission Deadline: August 20, 2024
Registration Deadline: Sept 01, 2024
Conference Date: September 26-27, 2024

For further information, please visit: https://eecsi.org/2024

Kindly forward this email to other interested parties.

Best Regards, Prof. Ir. Tole Sutikno, Ph.D.
Chair, EECSI 2024

17/06/2024

SCOPUS indexed and OPEN ACCESS JOURNALS:
International Journal of Informatics and Communication Technology
https://ijict.iaescore.com
IAES International Journal of Robotics and Automation
https://ijra.iaescore.com
International Journal of Advances in Applied Sciences
https://ijaas.iaescore.com
International Journal of Applied Power Engineering
https://ijape.iaescore.com
Journal of Education and Learning (EduLearn)
https://edulearn.intelektual.org

ACCREDITED and OPEN ACCESS JOURNALS:
Computer Science and Information Technologies
https://iaesprime.com/index.php/csit

Journal on Computer Science and Information Technologies