• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3856-3872
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• 2018

HTTP-based adaptive streaming (HAS) has recently been widely deployed on the Internet. In the HAS system, a video content is encoded at multiple bitrates and the encoded video content is segmented into small parts of fixed durations. The HAS client requests a video segment and stores it in the playout buffer. The rate adaptation algorithm employed in HAS clients dynamically determines the video bitrate depending on the time-varying bandwidth. Many studies have shown that an efficient rate adaptation algorithm is critical to ensuring quality-of-experience in HAS systems. However, existing algorithms have problems estimating the network bandwidth because bandwidth estimation is performed on the client-side application stack. Without the help of transport layer protocols, it is difficult to achieve accurate bandwidth estimation due to the inherent segment-based transmission of the HAS. In this paper, we propose an alternative approach that utilizes the playout buffer occupancy rather than using bandwidth estimates obtained from the application layer. We start with a queueing analysis of the playout buffer. Then, we present a buffer-aware rate adaptation algorithm that is solely based on the mean buffer occupancy. Our simulation results show that compared to conventional algorithms, the proposed algorithm achieves very smooth video quality while delivering a similar average video bitrate.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.823-828
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• 2003

The main objective of this paper is to provide a methodology of feature extraction using shape of image objects for content-based image retrieval. The shape of most real-life objects is irregular, and hence there is no universal approach to quantify the shape of an arbitrary object. In particular. electronic catalogs contain many image objects for their products. In this paper, we perform feature extraction based on individual objects in images rather than on the whole image itself, since our method uses a shape-based approach of objects using RLC lines within an image. Experiments show that shape parameters distinctly represented image objects and provided better classification and discrimination among image objects in an image database compared to Texture.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.303-316
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• 2021

Digital content protection has recently become an important requirement in biometrics-based authentication systems due to the challenges involved in designing a feasible and effective user authentication method. Biometric approaches are more effective than traditional methods, and simultaneously, they cannot be considered entirely reliable. This study develops a reliable and trustworthy method for verifying that the owner of the biometric traits is the actual user and not an impostor. Watermarking-based approaches are developed using a combination of a color face image of the user and a mobile equipment identifier (MEID). Employing watermark techniques that cannot be easily removed or destroyed, a blind image watermarking scheme based on fast discrete curvelet transform (FDCuT) and discrete cosine transform (DCT) is proposed. FDCuT is applied to the color face image to obtain various frequency coefficients of the image curvelet decomposition, and for high frequency curvelet coefficients DCT is applied to obtain various frequency coefficients. Furthermore, mid-band frequency coefficients are modified using two uncorrelated noise sequences with the MEID watermark bits to obtain a watermarked image. An analysis is carried out to verify the performance of the proposed schema using conventional performance metrics. Compared with an existing approach, the proposed approach is better able to protect multimedia data from unauthorized access and will effectively prevent anyone other than the actual user from using the identity or images.

• ETRI Journal
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• v.38 no.6
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• pp.1190-1196
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• 2016

We propose a new bandpass filter (BPF)-based online channel normalization method to dynamically suppress channel distortion when the speech and channel noise components are unknown. In this method, an adaptive modulation frequency filter is used to perform channel normalization, whereas conventional modulation filtering methods apply the same filter form to each utterance. In this paper, we only normalize the two mel frequency cepstral coefficients (C0 and C1) with large dynamic ranges; the computational complexity is thus decreased, and channel normalization accuracy is improved. Additionally, to update the filter weights dynamically, we normalize the learning rates using the dimensional power of each frame. Our speech recognition experiments using the proposed BPF-based blind channel normalization method show that this approach effectively removes channel distortion and results in only a minor decline in accuracy when online channel normalization processing is used instead of batch processing

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.211-227
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• 2011

Content Based Image Retrieval (CBIR) is an approach for retrieving similar images from an image database based on automatically-derived image features. The quality of a retrieval system depends on the features used to describe image content. In this paper, we propose an image clustering system that takes a database of images as input and clusters them using k-means clustering algorithm taking into consideration color, texture and shape features. Experimental results show that the combination of the three features brings about higher values of accuracy and precision.

• Journal of Multimedia Information System
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• v.7 no.4
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• pp.263-268
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• 2020

This paper introduces an event modeling and simulation system using behavior trees. The system aims to overcome the limitations of existing fixed, simple scenario-based training content, and to extend the behavior of objects to enable various experience deployments. To achieve this goal, we made specific tasks of behavior trees can change according to users' reaction and developed an adaptive simulation module that can analyze and execute behavior trees that changes at runtime. In order to validate our approach, we applied the adaptive behavior tree simulation to the scenarios in our virtual reality simulation-based fire training system we have been developing and demonstrated the implementation results.

• Journal of Korean Elementary Science Education
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• v.35 no.2
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• pp.166-180
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• 2016

This paper examines the effects on academic achievement, scientific process skills and affective domain for elementary students learning the 'Chicken life cycle' through traditional science class versus a smart media based STEAM approach. Students designed and built a hatching jar and created a smart media content for chickens using time-lapse technology. This STEAM program was developed to improve their scientific concepts of animals over nine periods of classes using integrated education methods. The experimental study took place in the third grade of public schools in a province, with the STEAM approach applied in 2 classes (44 students) and the traditional discipline approach implemented in 2 classes (46 students). The STEAM education significantly influenced the improvement of academic achievements, basic scientific process skills and affective domain. The results suggest that this STEAM approach for teaching scientific concepts of animal life cycles has the performance in terms of knowledge, skills and affect gain achievements in elementary school students' learning when compared to a traditional approach. Moreover, the smart media based STEAM program is helpful to lead students to engage in integrated problem-solving designs and learning science and technology.

• Journal of Engineering Education Research
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• v.11 no.2
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• pp.90-101
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• 2008

This study was conducted to develop pre-engineering educational program model based on STEM integration approach. To accomplish this purpose literature review and content validity ratio survey were carried out. The main results of this study were as follows: First, the conceptual model of STEM integration approach was constituted. Second, the conceptual model of pre-engineering educational program model based on STEM integration approach was proposed. Third, the formation steps of inquiry project activity, problem solving activity, and creative engineering design activity were developed to structure the educational program.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.25-40
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• 2023

Recommendation systems are frequently used by users to generate intelligent automatic decisions. In the study of movie recommendation system, the existing approach uses largely collaboration and content-based filtering techniques. Collaborative filtering considers user similarity, while content-based filtering focuses on the activity of a single user. Also, mixed filtering approaches that combine collaborative filtering and content-based filtering are being used to compensate for each other's limitations. Recently, several AI-based similarity techniques have been used to find similarities between users to provide better recommendation services. This paper aims to provide the prospective expansion by deriving possible solutions through the analysis of various existing movie recommendation systems and their challenges.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.175-186
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• 2022

This research article develops an Arabic books' recommendation system, which is based on the content similarity that assists users to search for the right book and predict the appropriate and suitable books pertaining to their literary style. In fact, the system directs its users toward books, which can meet their needs from a large dataset of Information. Further, this system makes its predictions based on a set of data that is gathered from different books and converts it to vectors by using the TF-IDF system. After that, the recommendation algorithms such as the cosine similarity, the sequence matcher similarity, and the semantic similarity aggregate data to produce an efficient and effective recommendation. This approach is advantageous in recommending previously unrated books to users with unique interests. It is found to be proven from the obtained results that the results of the cosine similarity of the full content of books, the results of the sequence matcher similarity of Arabic titles of the books, and the results of the semantic similarity of English titles of the books are the best obtained results, and extremely close to the average of the result related to the human assigned/annotated similarity. Flask web application is developed with a simple interface to show the recommended Arabic books by using cosine similarity, sequence matcher similarity, and semantic similarity algorithms with all experiments that are conducted.