cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
International Journal of Informatics and Communication Technology (IJ-ICT)
Published by Institute of Advanced Engineering and Science
ISSN : 22528776     EISSN : 27222616     DOI : -
Core Subject : Science,
Computer Science & IT
International Journal of Informatics and Communication Technology (IJ-ICT) is a common platform for publishing quality research paper as well as other intellectual outputs. This Journal is published by Institute of Advanced Engineering and Science (IAES) whose aims is to promote the dissemination of scientific knowledge and technology on the Information and Communication Technology areas, in front of international audience of scientific community, to encourage the progress and innovation of the technology for human life and also to be a best platform for proliferation of ideas and thought for all scientists, regardless of their locations or nationalities. The journal covers all areas of Informatics and Communication Technology (ICT) focuses on integrating hardware and software solutions for the storage, retrieval, sharing and manipulation management, analysis, visualization, interpretation and it applications for human services programs and practices, publishing refereed original research articles and technical notes. It is designed to serve researchers, developers, managers, strategic planners, graduate students and others interested in state-of-the art research activities in ICT.
Arjuna Subject : -
Articles 462 Documents
 21   22   23   24   25 
Forensic steganalysis for identification of steganography software tools using multiple format image S. T. Veena; A. Selvaraj
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 10, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v10i3.pp188-197

Abstract

Today many steganographic software tools are freely available on the Internet, which helps even callow users to have covert communication through digital images. Targeted structural image steganalysers identify only a particular steganographic software tool by tracing the unique fingerprint left in the stego images by the steganographic process. Image steganalysis proves to be a tough challenging task if the process is blind and universal, the secret payload is very less and the cover image is in lossless compression format. A payload independent universal steganalyser which identifies the steganographic software tools by exploiting the traces of artefacts left in the image and in its metadata for five different image formats is proposed. First, the artefacts in image metadata are identified and clustered to form distinct groups by extended K-means clustering. The group that is identical to the cover is further processed by extracting the artefacts in the image data. This is done by developing a signature of the steganographic software tool from its stego images. They are then matched for steganographic software tool identification. Thus, the steganalyser successfully identifies the stego images in five different image formats, out of which four are lossless, even for a payload of 1 byte. Its performance is also compared with the existing steganalyser software tool.
On the Evaluation and Implementation of LSTM Model for Speech Emotion Recognition using MFCC Bhandari, Sheetal
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 10, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v10i3.pp%p

Abstract

Speech Emotion Recognition is an emerging research field and is expected to benefit many application domains by providing effective Human Computer Interface. Researchers are extensively working towards decoding of human emotions through speech signal in order to achieve effective interface and smart response by computers. The perfection of speech emotion recognition greatly depends upon the types of features used and also on the classifier employed for recognition. The contribution of this paper is to evaluate twelve different Long Short Term Memory (LSTM) networks models as classifier based on Mel-Frequency Cepstrum Coefficients (MFCC) feature. The paper presents performance evaluation in terms of important parameters such as: precision, recall, F-measure and accuracy for four emotions like happy, neutral, sad and angry using the emotional speech databases namely Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS). The measurement accuracy obtained is 89% which is 9.5% more than reported in recent literature. The suitable LSTM model is further successfully implemented on Raspberry PI board creating standalone Speech Emotion Recognition system.
Guard lines conformal slotted antenna array for multiband application Brajlata Chauhan; Suresh Chandra Gupta; Sandip Vijay
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 10, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v10i2.pp140-147

Abstract

This work investigated a miniaturized slotted conformal antenna array for multiband application. Three guard lines are incorporated to the side of main patch and top of main patch to reduce surface current for planner surface and observe the effect of guard line due to which it resonate at three frequencies in X band and Ku band to be useful for multiband. A rectangular slot is etched at center of patches to increase the current path for wide band application. A quarter wavelength feeding network is used with good agreement of impedance matching. The main lobe width and direction shows through the radiation pattern which remains stable even it is significantly curved. This structure is wrapped around a cylinder with a diameter of 41.4 mm in the circumferential direction. It is observed that the planner antenna array operating at 8.4 GHz, 11.2 GHz &18.2 GHz with a return loss of -20 dB to -45 dB with fractional BW of 25% at 3rd frequency range and the directivity from 3.4 dBi-6.8 dBi. By doing some alteration in dimensions for the conformal antenna producing fractional BW of 20% and the directivity 5.5 to 9.1 dBi at resonating frequencies of 8.4 GHz, 11.4 GHz, and 17.5 GHz. This proposed array is simulated on CST software.
Narrow-band filter for satellite communication systems Alexander Vladimirovich Strizhachenko; Sergey Nikolayevich Shulga
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 10, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v10i3.pp198-203

Abstract

Design narrow-band compact filters, based on high-quality waveguide-dielectric resonators with anisotropic materials is the subject of this paper. Filter represents a segment of a rectangular waveguide rotated around the longitudinal axis of the waveguide 90 degrees and containing one or more dielectric inserts that completely fill the resonator along the narrow wall of the waveguide and partially along the wide one. A distinctive feature of the proposed filter is higher slope steepness of the amplitude-frequency characteristic, and high manufacturability in the centimeter range. The designed narrow-band filter satisfies contradictory requirements: it combines narrow bandwidth (≈ 0.1% of center frequency f0) with low passband insertion loss (≤ 1 dB).
An approach to partial occlusion using deep metric learning Chethana Hadya Thammaiah; Trisiladevi Chandrakant Nagavi
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 10, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v10i3.pp204-211

Abstract

The human face can be used as an identification and authentication tool in biometric systems. Face recognition in forensics is a challenging task due to the presence of partial occlusion features like wearing a hat, sunglasses, scarf, and beard. In forensics, criminal identification having partial occlusion features is the most difficult task to perform. In this paper, a combination of the histogram of gradients (HOG) with Euclidean distance is proposed. Deep metric learning is the process of measuring the similarity between the samples using optimal distance metrics for learning tasks. In the proposed system, a deep metric learning technique like HOG is used to generate a 128d real feature vector. Euclidean distance is then applied between the feature vectors and a tolerance threshold is set to decide whether it is a match or mismatch. Experiments are carried out on disguised faces in the wild (DFW) dataset collected from IIIT Delhi which consists of 1000 subjects in which 600 subjects were used for testing and the remaining 400 subjects were used for training purposes. The proposed system provides a recognition accuracy of 89.8% and it outperforms compared with other existing methods.
Detection of myocardial infarction on recent dataset using machine learning Nusrat Parveen; Satish R Devane; Shamim Akthar
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp20-31

Abstract

In developing countries such as India, with a large aging population and limited access to medical facilities, remote and timely diagnosis of myocardial infarction (MI) has the potential to save the life of many. An electrocardiogram is the primary clinical tool utilized in the onset or detection of a previous MI incident. Artificial intelligence has made a great impact on every area of research as well as in medical diagnosis. In medical diagnosis, the hypothesis might be doctors' experience which would be used as input to predict a disease that saves the life of mankind. It is been observed that a properly cleaned and pruned dataset provides far better accuracy than an unclean one with missing values. Selection of suitable techniques for data cleaning alongside proper classification algorithms will cause the event of prediction systems that give enhanced accuracy. In this proposal detection of myocardial infarction using new parameters is proposed with increased accuracy and efficiency of the existing model. Additional parameters are used to predict MI with more accuracy. The proposed model is used to predict an early diagnosis of MI with the help of expertise experiences and data gathered from hospitals.
Heart disease prediction model with k-nearest neighbor algorithm Tssehay Admassu Assegie
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 10, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v10i3.pp225-230

Abstract

In this study, the author proposed k-nearest neighbor (KNN) based heart disease prediction model. The author conducted an experiment to evaluate the performance of the proposed model. Moreover, the result of the experimental evaluation of the predictive performance of the proposed model is analyzed. To conduct the study, the author obtained heart disease data from Kaggle machine learning data repository. The dataset consists of 1025 observations of which 499 or 48.68% is heart disease negative and 526 or 51.32% is heart disease positive. Finally, the performance of KNN algorithm is analyzed on the test set. The result of performance analysis on the experimental results on the Kaggle heart disease data repository shows that the accuracy of the KNN is 91.99%
A novel enhanced algorithm for efficient human tracking Mehdi Gheisari; Zohreh Safari; Mohammad Almasi; Amir Hossein Pourishaban Najafabadi; Abel Sridharan; Ragesh G K; Yang Liu; Aaqif Afzaal Abbasi
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp1-7

Abstract

Tracking moving objects has been an issue in recent years of computer vision and image processing and human tracking makes it a more significant challenge. This category has various aspects and wide applications, such as autonomous deriving, human-robot interactions, and human movement analysis. One of the issues that have always made tracking algorithms difficult is their interaction with goal recognition methods, the mutable appearance of variable aims, and simultaneous tracking of multiple goals. In this paper, a method with high efficiency and higher accuracy was compared to the previous methods for tracking just objects using imaging with the fixed camera is introduced. The proposed algorithm operates in four steps in such a way as to identify a fixed background and remove noise from that. This background is used to subtract from movable objects. After that, while the image is being filtered, the shadows and noises of the filmed image are removed, and finally, using the bubble routing method, the mobile object will be separated and tracked. Experimental results indicated that the proposed model for detecting and tracking mobile objects works well and can improve the motion and trajectory estimation of objects in terms of speed and accuracy to a desirable level up to in terms of accuracy compared with previous methods.
A review on notification sending methods to the recipients in different technology-based women safety solutions A. Z. M. Tahmidul Kabir; Al Mamun Mizan; Plabon kumar Saha; Nirmal Debnath; Tasnuva Tasneem
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 11, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v11i1.pp57-64

Abstract

Women have progressed a lot in terms of social empowerment and economics. They are going for higher education, jobs, and many other similar endeavors, but harassment cases have also been on the rise. So, women’s safety is a big concern nowadays, especially in developing countries. Many previous studies and attempts were made to create a feasible safety solution for women. Out of various features to ensure women’s safety in critical situations, location tracking is a very common and key feature in most previously proposed solutions. This study found mechanisms of sending the location to different types of recipients in various women safety solutions. In addition, the advantages and drawbacks of location sending methods in women's safety solutions were analyzed.
ZigBee based data collection in wireless sensor networks Cuong V. Nguyen; Alberto E. Coboi; Nam V. Bach; Anh TN. Dang; Trang TH. Le; Huy P. Nguyen; Minh Tuan Nguyen
International Journal of Informatics and Communication Technology (IJ-ICT) Vol 10, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijict.v10i3.pp212-224

Abstract

Wireless sensor networks (WSN), referring to groups of technologies wirelessly controlled, are widely used in many different fields, agriculture, medical, military, etc. These technologies are mainly used for monitoring physical or environmental conditions, such as temperatures, sound, pressure, and so on. In WSN fields, there are technologies as Wi-Fi, radio frequency (RF), Bluetooth, ZigBee, Z-Wave, and so on. Furthermore, there is one of this technology that offers more outstanding futures to provide more energy-saving and long distances of transmissions compared to other technologies, and that is Zigbee technology, and this had become for many applications, the first high-quality to use and consequently the most used in WSNs. In Zigbee aided WSNs, are included three main devices used to communicate data, that is a Zig-Bee coordinator (network coordinator), ZigBee router, and ZigBee end-devices. The data sensed is transmitted from sensor nodes through coordinators to a base-station (BS), this device (coordinator), collects the data, stores it in a memory, processes, and finally forward to the next suitable nodes or the BS. This research presents the concepts and discussions of Zigbee technologies used in WSNs. Utmost ZigBee communication technologies are revised and analyzed, as well as simulation results with different scenarios are addressed comprehensively. Proposals for advance applications in WSNs are presented. Suggestions for future developments are provided

Page 23 of 47 | Total Record : 462

 21   22   23   24   25 

Filter by Year

2012 2025


Reset
Filter By Issues
All Issue Vol 14, No 3: December 2025 Vol 14, No 2: August 2025 Vol 14, No 1: April 2025 Vol 13, No 3: December 2024 Vol 13, No 2: August 2024 Vol 13, No 1: April 2024 Vol 12, No 3: December 2023 Vol 12, No 2: August 2023 Vol 12, No 1: April 2023 Vol 11, No 3: December 2022 Vol 11, No 2: August 2022 Vol 11, No 1: April 2022 Vol 10, No 3: December 2021 Vol 10, No 2: August 2021 Vol 10, No 1: April 2021 Vol 9, No 3: December 2020 Vol 9, No 2: August 2020 Vol 9, No 1: April 2020 Vol 8, No 3: December 2019 Vol 8, No 2: August 2019 Vol 8, No 1: April 2019 Vol 7, No 3: December 2018 Vol 7, No 2: August 2018 Vol 7, No 1: April 2018 Vol 6, No 3: December 2017 Vol 6, No 2: August 2017 Vol 6, No 1: April 2017 Vol 5, No 3: December 2016 Vol 5, No 2: August 2016 Vol 5, No 1: April 2016 Vol 4, No 3: December 2015 Vol 4, No 2: August 2015 Vol 4, No 1: April 2015 Vol 3, No 3: December 2014 Vol 3, No 2: August 2014 Vol 3, No 1: April 2014 Vol 2, No 3: December 2013 Vol 2, No 2: August 2013 Vol 2, No 1: April 2013 Vol 1, No 2: December 2012 Vol 1, No 1: June 2012 More Issue