JOIV : International Journal on Informatics Visualization
JOIV : International Journal on Informatics Visualization is an international peer-reviewed journal dedicated to interchange for the results of high quality research in all aspect of Computer Science, Computer Engineering, Information Technology and Visualization. The journal publishes state-of-art papers in fundamental theory, experiments and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion and concise conclusion. As our commitment to the advancement of science and technology, the JOIV follows the open access policy that allows the published articles freely available online without any subscription.
Articles
20 Documents
Search results for
, issue
"Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation"
:
20 Documents
clear
<![CDATA[A Multi-Agent Simulation Evacuation Model Using The Social Force Model: A Large Room Simulation Study ]]>
<![CDATA[Hussain, Norhaida]]>;
<![CDATA[Shiang, Cheah Wai]]>;
<![CDATA[Loke, Seng]]>;
<![CDATA[Khairuddin, Muhammad Asyraf bin]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30630/joiv.6.1-2.929
<![CDATA[Research on evacuation simulation has received significant attention over the past few decades. Disasters, whether they were caused by nature or by humans, which claimed lives were also the impetus for the establishment of various evacuation studies. Numerous research points to the possibility of simulating an evacuation utilizing the Social Force Model (SFM) and a leading person or leader, but without using the multi-agent architecture. Within the scope of this article, the multi-agent architecture for crowd steering that we suggest will be investigated. The architecture will utilize a model known as the Social Force Model to figure out how evacuees will move around the area. After this step, the model is simulated in NetLogo to determine whether the architecture can model the evacuation scenario. A simulation test is carried out for us to investigate the degree to which the behavior of the original SFM and the message-passing model is comparable to one another. The result demonstrates that the proposed architecture can simulate the evacuation of pedestrians. In addition, the simulation model can simulate utilizing the grouping strategy as well as the no grouping technique. The findings also showed that the model can capture many evacuation patterns, such as an arch-shaped pattern at the opening of the exit.]]>
<![CDATA[How to Deeply Analyze the Content of Online Newspapers Using Clustering and Correlation ]]>
<![CDATA[Rokhayati, Yeni]]>;
<![CDATA[Sartikha, -]]>;
<![CDATA[Janah, Nur Zahrati]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30630/joiv.6.1-2.942
<![CDATA[The increase in the number of visitors is one of the keys to increasing income for online newspapers, whether to increase the number of ads, Google AdSense, or customer trust. Therefore, finding which news categories increase the number of visitors needs to be known and analyzed more deeply. Because it is very common to add content to online newspaper sites every day, even for hours, this pattern analysis is not the same as analyzing regular website content patterns. This study intends to add methods in the world of research on how to analyze website content, especially online news, by using the clustering method to classify what news categories bring high, medium, or a low number of visitors and then analyzing the correlation to explore the depth of the relationship between the variables, namely which parameters have a large or low effect on the increase in the number of visitors. A local Batam-based online newspaper company is used as a case study for this research. Data is collected, preprocessed first, and analyzed using the clustering and correlation method. This analysis of the news content readership suggests what news categories should be optimized because it provides an increase in the number of visitors. A summary of the analysis steps in this study is presented. We also provided some suggestions if other online newspaper owners or researchers are interested in a similar analysis of online news content.]]>
<![CDATA[An Intelligent Missing Data Imputation Techniques: A Review ]]>
<![CDATA[Seu, Kimseth]]>;
<![CDATA[Kang, Mi-Sun]]>;
<![CDATA[Lee, HwaMin]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30630/joiv.6.1-2.935
<![CDATA[The incomplete dataset is an unescapable problem in data preprocessing that primarily machine learning algorithms could not employ to train the model. Various data imputation approaches were proposed and challenged each other to resolve this problem. These imputations were established to predict the most appropriate value using different machine learning algorithms with various concepts. Furthermore, accurate estimation of the imputation method is exceptionally critical for some datasets to complete the missing value, especially imputing datasets in medical data. The purpose of this paper is to express the power of the distinguished state-of-the-art benchmarks, which have included the K-nearest Neighbors Imputation (KNNImputer) method, Bayesian Principal Component Analysis (BPCA) Imputation method, Multiple Imputation by Center Equation (MICE) Imputation method, Multiple Imputation with denoising autoencoder neural network (MIDAS) method. These methods have contributed to the achievable resolution to optimize and evaluate the appropriate data points for imputing the missing value. We demonstrate the experiment with all these imputation techniques based on the same four datasets which are collected from the hospital. Both Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) are utilized to measure the outcome of implementation and compare with each other to prove an extremely robust and appropriate method that overcomes missing data problems. As a result of the experiment, the KNNImputer and MICE have performed better than BPCA and MIDAS imputation, and BPCA has performed better than the MIDAS algorithm.]]>
<![CDATA[Smart Automation Aquaponics Monitoring System ]]>
<![CDATA[Muhammad Saef Tarqani Abdullah]]>;
<![CDATA[Lucyantie Mazalan]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30630/joiv.6.1-2.925
<![CDATA[Modern agriculture, such as aquaponics, has become a well-known solution nowadays for farming, especially in Asia countries. It provides an alternative to support food demands and maintain environmental sustainability. However, it requires manpower and time to maintain and monitor the system. This research proposes a smart automation aquaponic monitoring system that helps users maintain and monitor the system through smartphone applications. The system uses DHT11 to record temperature and humidity, HC-SR04 for water level, and FC-28 to maintain soil moisture. The sensors are integrated with WeMos D1 Wi-Fi Uno based ESP8266 microcontroller to process the data. The data collected is stored in the cloud and retrieved via the Blynk application, which also performs as an actuator and allows users to control the parameters involved. The application helps to monitor the humidity, temperature, and water level in the fish tank and control the actuator for feeding fish. The system also sends a notification to the user for any activities performed, such as watering plants, feeding fish, and abnormality of temperature in the surroundings. The performance of the system was evaluated using regression modeling. The result indicates positive growth for both plants and fish during the monitoring duration, suggesting the proposed system's effectiveness. Overall, this solution helps to reduce manpower and operation costs as well as alternatives for food demand and stabilize environmental sustainability, especially in the urban residency.]]>
<![CDATA[A Framework for Personalized Training at Home Based on Motion Capture ]]>
<![CDATA[Hyunjoo Park]]>;
<![CDATA[Seungdo Jeong]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30630/joiv.6.1-2.940
<![CDATA[As the number of single-person households continues to increase, contents related to exercise at home are increasing. Therefore, this paper proposes a framework for efficient home fitness. The home fitness framework proposed in this paper is based on a method of acquiring expert motion information and providing it to users. To this end, content creation and provision are implemented by using Kinect and Unreal game engine. In addition, it is possible to provide customized home fitness in consideration of the user's athletic ability. The proposed system first captures the expert's motion and stores it. We propose a method that can efficiently store stop motion and dynamic motion storage. In the case of each user, since there is a difference in exercise ability for each individual, an adverse effect may occur if an excessively accurate motion is requested. Therefore, to solve these problems, we present the parts that can be considered for each joint. For the exercise motion provided by the expert, a method was provided that allows the user to adjust the degree of matching for each joint in consideration of user's own exercise ability. That is, joint parts that do not require exact matching could be completely excluded from matching. For parts that would be subject to large changes, a range of errors is specified. As the training progresses, the error range is reduced, and the excluded parts are presented to be matched gradually. Such adjustments are made based on expert feedback. In this way, it was possible to improve the exercise effect gradually. This paper proposes an effective method for personalized home fitness according to the user's athletic ability. This will apply to various fields besides home fitness.]]>
<![CDATA[Applications of Big Data Analytics in Traffic Management in Intelligent Transportation Systems ]]>
<![CDATA[Hoang Phuong Nguyen]]>;
<![CDATA[Phuoc Quy Phong Nguyen]]>;
<![CDATA[Viet Duc Bui]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30630/joiv.6.1-2.882
<![CDATA[Big Data technology is emerging as a mass technology that can be applied to many industries in life. Decisions in a wide range of fields may benefit greatly from the information provided by Big Data and Analytics research. One of the areas that have benefited the most from this technology is transportation, which is known as an important field in the development of each nation and possesses a huge treasure of data that traditional technologies cannot handle. Indeed, many countries have applied Big Data-based intelligent transportation systems because it is a traffic system that interacts with vehicles and people on the road, thereby reducing traffic congestion and traffic accidents year by year in many countries. The article presents the applications of Big Data technology in smart traffic systems, thereby providing the perspective of a smart city with a smart traffic system as a critical factor. This paper's analysis indicated that smart cities could be born and further developed through the linkage of Big Data technology and smart traffic systems with smart traffic systems as the core. In addition, the results also showed that the obstacle that needs to be studied at this time is the policy and legal framework for Big Data technology. Therefore, a system managed by the state or shared between the state and the private sector should be studied in the future, aiming to harmonize interests and develop the system extensively.]]>
<![CDATA[Development on Deaf Support Application Based on Daily Sound Classification Using Image-based Deep Learning ]]>
<![CDATA[An, Ji-Hee]]>;
<![CDATA[Koo, Na-Kyoung]]>;
<![CDATA[Son, Ju-Hye]]>;
<![CDATA[Joo, Hye-Min]]>;
<![CDATA[Jeong, Seungdo]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30630/joiv.6.1-2.936
<![CDATA[According to statistics, the number of hearing-impaired persons among the disabled in Korea accounts for 27% of all persons with disabilities. However, there is insufficient support for the deaf and hard of hearing's protective devices and life aids compared to the large number. In particular, the hearing impaired misses much information obtained through sound and causes inconvenience in daily life. Therefore, in this paper, we propose a method to relieve the discomfort in the daily life of the hearing impaired. It analyzes sounds that can occur frequently and must be recognized in daily life and guide them to the hearing impaired through applications and vibration bracelets. Sound analysis was learned by using deep learning by converting sounds that often occur in daily life into the Mel-Spectrogram. The sound that actually occurs is recorded through the application, and then it is identified based on the learning result. According to the identification result, predefined alarms and vibrations are provided differently so that the hearing impaired can easily recognize it. As a result of the recognition of the four major sounds occurring in real life in the experiment, the performance showed an average of 85% and an average of 80% of the classification rate for mixed sounds. It was confirmed that the proposed method can be applied to real-life through experiments. Through the proposed method, the quality of life can be improved by allowing the hearing impaired to recognize and respond to sounds that are essential in daily life.]]>
<![CDATA[Hand Gesture Recognition Based on Continuous Wave (CW) Radar Using Principal Component Analysis (PCA) and K-Nearest Neighbor (KNN) Methods ]]>
<![CDATA[Rahman, Muhammad Khairani Abdul]]>;
<![CDATA[Abdul Rashid, Nur Emileen]]>;
<![CDATA[Ismail, Nor Najwa]]>;
<![CDATA[Zakaria, Nor Ayu Zalina]]>;
<![CDATA[Khan, Zuhani Ismail]]>;
<![CDATA[Enche Ab Rahim, Siti Amalina]]>;
<![CDATA[Mohd Isa, Farah Nadia]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30630/joiv.6.1-2.926
<![CDATA[Human-computer interaction (HCI) is a field of study studying how people and computers interact. One of the most critical branches of HCI is hand gesture recognition, with most research concentrating on a single direction. A slight change in the angle of hand gestures might cause the motion to be misclassified, thereby degrading the performance of hand gesture detection. Therefore, to improve the accuracy of hand gesture detection, this paper focuses on analyzing hand gestures based on the reflected signals from two directions, which are front and side views. The radar system employed in this paper is equipped with two sets of 24 GHz continuous wave (CW) monostatic radar sensors with a sampling rate of 44.1 kHz. Four different hand gestures, namely close hand, open hand, OK sign, and pointing down, are collected using SignalViewer software. The data is stored as a waveform audio file format (WAV) where one data consists of 20 segments, and the data is then examined by using MATLAB software to be segmented. To evaluate the effectiveness of the classification system, principal component analysis (PCA) and k-nearest neighbor (KNN) are integrated. The PCA findings are depicted in Pareto and 2-D scatter plot for both radar directions. The Leave-One-Out (LOO) method is then used in this analysis to verify the accuracy of the classification method, which is represented in the confusion matrix. At the end of the analysis, the classification results indicated that both angles achieved near-perfect accuracy for most hand gestures.]]>
<![CDATA[Malware Authorship Attribution Model using Runtime Modules based on Automated Analysis ]]>
<![CDATA[Lee, Sangwoo]]>;
<![CDATA[Cho, Jungwon]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30630/joiv.6.1-2.941
<![CDATA[Malware authorship attribution is a research field that identifies the author of malware by extracting and analyzing features that relate the authors from the source code or binary code of malware. Currently, it is being used as one of the detection techniques based on malware forensics or identifying patterns of continuous attacks such as APT attacks. The analysis methods to identify the author are as follows. One is a source code-based analysis method that extracts features from the source code, and the other is a binary-based analysis method that extracts features from the binary. However, to handle the modularization and the increasing amount of malicious code with these methods, both time and manpower are insufficient to figure out the characteristics of the malware. Therefore, we propose the model for malware authorship attribution by rapidly extracting and analyzing features using automated analysis. Automated analysis uses a tool and can be analyzed through a file of malware and the specific hash values without experts. Furthermore, it is the fastest to figure out among other malware analysis methods. We have experimented by applying various machine learning classification algorithms to six malware author groups, and Runtime Modules and Kernel32.dll API extracted from the automated analysis were selected as features for author identification. The result shows more high accuracy than the previous studies. By using the automated analysis, it extracts features of malware faster than source code and binary-based analysis methods.]]>
<![CDATA[Study the Field of View Influence on the Monchromatic and Polychromatic Image Quality of a Human Eye ]]>
<![CDATA[Qasim, Adeeb Mansoor]]>;
<![CDATA[Aljanabi, Mohammad]]>;
<![CDATA[Kasim, Shahreen]]>;
<![CDATA[Ismail, Mohd Arfian]]>;
<![CDATA[Gusman, Taufik]]>
<![CDATA[ JOIV : International Journal on Informatics Visualization Vol 6, No 1-2 (2022): Data Visualization, Modeling, and Representation ]]>
Publisher : <![CDATA[Society of Visual Informatics ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30630/joiv.6.1-2.931
<![CDATA[In this paper, the effect of the eye field of view (known as F.O.V.) on the performance and quality of the image of the human eye is studied, analyzed, and presented in detail. The image quality of the retinal is numerically analyzed using the eye model of Liou and Brennan with this polymer contact lens. The image, which is in digital form were collected from various sources such as from photos, text structure, manuscripts, and graphics. These images were obtained from scanned documents or from a scene. The color fringing which is chromatic aberration addition to polychromatic effect was studied and analyzed. The Point Spreads Function or (known as PSF) as well as The Modulation Transfers Function (known as MTF) were measured as the most appropriate measure of image quality. The calculations of the image quality were made by using Zemax software. Then, the result of the calculation demonstrates the value of correcting the chromatic aberration. The results presented in this paper had shown that the form of image is so precise to the eye (F.O.V.). The image quality is degraded as (F.O.V.) increase due to the increment in spherical aberration and distortion aberration respectively. In conclusion, then Zemax software that was used in this study assist the researcher potential to design human eye and correct the aberration by using external optics.]]>
