An ontology-based personalized target advertisement system on interactive TV

We design and implement a personalized target advertisement (PTA) system in IPTV using ontology-based semantic relations between IPTV program and advertisement. In the PTA system, we focus on the development of an ontology reasoning technique of improving advertisement recommendation ability and exploiting efficient information reuse. For this purpose, we first build the IPTV program ontology and viewer profiling ontology based on the IPTV program and viewers’ content consumption behavior, using OWL (Web Ontology Language) standardized by W3C. We then classify each viewer into his/her corresponding reference group using a similarity metric. After that, we define the semantic relations between advertisement and shopping products consumed by the prototype through shopping sites in IPTV. Based on these semantic relations, we infer the preferred advertisements for each viewer through our reasoning process. In the experimental section, we demonstrate a prototype of our system and the algorithm of the PTA system using various cases.     

An enhanced fuzzy c-means algorithm for audio segmentation and classification

Automated audio segmentation and classification play important roles in multimedia content analysis. In this paper, we propose an enhanced approach, called the correlation intensive fuzzy c-means (CIFCM) algorithm, to audio segmentation and classification that is based on audio content analysis. While conventional methods work by considering the attributes of only the current frame or segment, the proposed CIFCM algorithm efficiently incorporates the influence of neighboring frames or segments in the audio stream. With this method, audio-cuts can be detected efficiently even when the signal contains audio effects such as fade-in, fade-out, and cross-fade. A number of audio features are analyzed in this paper to explore the differences between various types of audio data. The proposed CIFCM algorithm works by detecting the boundaries between different kinds of sounds and classifying them into clusters such as silence, speech, music, speech with music, and speech with noise. Our experimental results indicate that the proposed method outperforms the state-of-the-art FCM approach in terms of audio segmentation and classification.     

An object-based middleware supporting efficient interoperability on a smart home network

This paper proposes a novel object-based home network middleware for supporting the interoperability among home devices and smart grid devices. This middleware provides various types of abstract objects for flexible representation of heterogeneous home devices, which are classified based on their characteristics. It is also flexible enough to allow addition of new protocols and message conversion between different protocols through an abstraction layer, which are not supported by existing home network middlewares so that various protocols can be supported. As a result, it can be utilized to provide the interoperability among a variety of devices from sensors to typical home appliances as well as smart grid devices such as a home electric generator and a battery, which adopt different protocols. In order to demonstrate that home devices and smart grid devices are interoperable through the proposed middleware, we implement applications based on the middleware on a target platform consisting of embedded boards, sensors and laptops for emulation purposes of a home network. According to our emulation, this middleware can provide efficient interoperability among home devices and smart grid devices for future energy efficient home.     

A high performance parallel DCT with OpenCL on heterogeneous computing environment

A noteworthy thing in desktop PCs is that they can provide a great opportunity to increase the performance of processing multimedia data by exploiting task- and data-parallelism with multi-core CPU and many-core GPU. This paper presents a high performance parallel implementation of 2D DCT on this heterogeneous computing environment. For this purpose, Intel TBB (threading building blocks) and OpenCL (Open Compute Language) are utilized for task- and data-parallelism, respectively. The simulation result shows that the parallel DCT implementations far the serial ones in processing speed. Especially, OpenCL implementation shows a linear speedup, a typical SIMD characteristic as the increase of 2D data sets.     

Disparate attributes algorithm for semantic assembly design rule management

To expedite a semantic product design environment, the relevant minimal set of design rules could optimally be distilled from the given disparate design rules. However, in disparate design rules, some attributes are frequently unused in other design rules. Treating all the attributes in all the rules increases reasoning complexity. In the situation of incomplete information, treating the attributes, which may be relevant to some rules and not to others, as “missing” ones is found to cause reasoning problems. In this paper, we present a new algorithm, i.e. the disparate attributes algorithm, for managing semantic assembly design rules. The proposed disparate attributes algorithm by identifying “inapplicable” information extends a rough set approach for managing semantic assembly design rules with systematic selection of various minimal sets of rules. To validate the disparate attributes algorithm, the approach is tested with multiple realistic assembly design cases.     

Cognitive evaluation for conceptual design: cognitive role of a 3D sculpture tool in the design thinking process

ABSTRACT

This study focuses on the decisive role played by the digital design environment in the cognitive design process and design thinking. To analyse the cognitive role of digital design tools, we carried out a protocol analysis of conventional design sketching and a 3D sculpture tool. Cognitive evaluation was a differentiating factor when considering the contextual role of the 3D sculpture tool in subsequent evaluations, non-sequential evaluations for conversion, and passive approaches within the design process. Cognitive evaluation played the following roles: validation, extension, navigation, exploration, and confirmation. The navigation, exploration, and extension roles played by non-sequential evaluation were mainly related to inductive design thinking. Finally, the types of cognitive evaluation and their roles when using the 3D sculpture tool were different, according to the design thinking type. This study explored the multidimensional roles of cognitive evaluation using a 3D sculpture tool and its relationship with design thinking types.     

Degradation of organic dye using zero-valent iron prepared from by-product of pickling line

In this study, zero-valent iron (ZVI) was produced using iron oxide that is a by-product of a pickling line at a steel works. The reaction activity of the produced ZVI was evaluated through a series of decomposition experiments of Orange II aqueous solution. The size of ZVI particles increased with reduction temperature due to coalescence. Correspondingly, the specific surface area of ZVI decreased with increasing reduction temperature. The decomposition efficiency of synthesized ZVI particles was higher at a lower pH. In particular, no significant decomposition reaction was observed at pH of 4 and higher. The rate of the ZVI-assisted decomposition of Orange II was increased by addition of H2O2 at pH of 3, whereas it was reduced by addition of H2O2 at a higher pH of 6. Nevertheless, simultaneous use of ZVI, UV and H2O2 led to a considerable increase in the decomposition rate even at a high pH condition (pH = 6).     

Presence, molecular characteristics and geosmin producing ability of actinomycetes isolated from South Korean terrestrial and aquatic environments

The unpleasant odor of drinking water is one of the major problems in many water utilities in the world. Actinomycetes have long been associated with odorous compounds. Considering the paucity of research on Actinomycetes producing odorous compounds in South Korea, presence of Actinomycetes, their molecular characteristics and ability to produce odorous compounds were investigated in this study. Findings confirmed the presence of Actinomycetes in surface soil, sediment, and water samples from four sites: two artificial lakes [Paldang and Cheongpyeong (CP)], and two streams [Gyeongan (GA) and Yangpyeong]. Surface soil and sediment from CP area had the greatest concentration of Actinomycetes (8.2 x 10(7) and 6.8 x 10(6) colony forming units (CFUs)/gram, dry weight, respectively). When water samples are considered, samples from GA had the highest concentration (1.9 x 10(2) CFU/mL). 16S rRNA sequencing and molecular phylogenetic analysis showed that Streptomyces was the dominant genus (64.1%). In addition, the isolated Actinomycetes synthesized 5.4 ng/L geosmin as demonstrated by thermal desorption unit-gas chromatograph/mass spectrometry analysis.     

Biodegradation of estrogen conjugates by bacteria isolated from river sediments

The objective of this study was to investigate the ability of E. coli in river sediments to degrade estrogen conjugates. Biodegradation experiments on glucuronide estrogens (E1-GLU, E2-GLU and E3-GLU) using E. coli, non-E. coli bacteria as well as sediment crude extracts were carried out in batch mode. A pure identified E. coli strain (KCTC 2571) was used for comparison of enzyme activity. The results showed that the degradation rate of estrogen conjugates by KCTC 2571 and E. coli isolated from sediments followed a similar trend. Fecal bacteria showed a high ability to deconjugate glucuronided estrogens. Approximately 50% of glucuronide moieties were cleaved within 4 h of contact time in experiments using pure E. coli. The degradation rate was slower in experiments using crude extracts of sediments, and conjugated estrogens were not completely degraded even after 12 h of reaction. These results provide a clear understanding of the fate and behavior of estrogen by bacteria in the environment.     

A finite memory filtering for end-to-end available bandwidth estimation

In this paper, a finite memory filter is proposed to estimate the available bandwidth through real-time tracking unknown parameters of the sloping straight line while removing undesired system and measurement noises. The finite memory filter is developed under a weighted least square criterion using only the most recent finite probe-packet measurements on the window. The proposed finite memory filtering based available bandwidth estimate is shown to have several inherent properties such as unbiasedness, deadbeat, and robustness. A guideline for choosing appropriate window length is described as it can significantly affect the estimation performance. Finally, computer simulations show that the proposed finite memory filtering based approach can be comparable with the Kalman filtering based approach with infinite memory structure for constantly or slowly changing available bandwidth and outperform that for dynamically changing available bandwidth.