• The Journal of Art Theory & Practice
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• no.13
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• pp.73-95
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• 2012

In terms of element and process, art today has already been fully systemized, yet tends to become even more systemized. All phases of creation and exhibition, appreciation and education, promotion and marketing are planned, adjusted, and decided within the order of a globalized, networked system. Each phase is executed, depending on the system of management and control and diverse means corresponding to the system. From the step of education, artists are guided to determine their styles and not be motivated by their desire to become star artists or running counter to mainstream tendency and fashion. In the process of planning an exhibition, the level of artist awareness is considered more significant than work quality. It is impossible to avoid such systems and institutions today. No one can escape or be freed from the influence of such system. This discussion addresses a serious distortion in the selection system as part of the system connotatively called "art museum system," especially to evaluate artistic achievement and aesthetic quality. Called "studio system" or "art star system," the system distinguishes successful minority from failed absolute majority and justifies the results, deciding discriminative compensations. The discussion begins from work by Hunter Jonakin and Dan Perjovschi. The key point of this discussion is not their art worlds but the shared truth referred by the two as the collusive "art market" and "art star system." Through works based on their experiences, the two artists refer to these systems which restrict and confine them. Jonakin's Jeff Koons Must Die! is avideo game conveying a critical comment on authoritative operation of the museum system and star system. In this work, participants, whether viewer or artist, are destined to lose: the game is unwinnable. Players take the role of a person locked in a museum where artist Jeff Koons' retrospective is held. The player can either look around and quietly observe the works, which causes a game-over, or he can blow the classical paintings to pieces and cause the artist Koons to come out and reprimand the player, also resulting in a game-over. Like Jonakin, Dan Perjovschi's some drawings also focuses on the status of the artist shrunken by the system. Most artists are ruined in a process of competition to survive within the museum system. As John Burger properly pointed out, out of the art systems today, public collections (art museums) and private collections have become "something unbearable." The system justifies the selection system of art stars and its frame of reference, disregarding the problem of producing numerable victims in its process. What should be underlined above all else is that the present selection system seriously shrinks art's creative function and its function of generating meaning. In this situation, art might fall to the level of entertainment, accessible to more people and compromising with popularity. This discussion is based on assumption and consciousness on the matter that this situation might cause catastrophic results for not only explicit victims of the system but also winners, or ones defined as winners. The system of art is probably possible only by desire or distortion stemmed from such desire. The system can be flourished only under the economic system of avarice: quantitatively expanding economy, abundant style, resort economy in Venice and Miami, and luxurious shopping malls with up-to-date facilities. The catastrophe here is ongoing, not a sudden emergence, and dynamic, leading the system itself to a devastating end.

• Asia pacific journal of information systems
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• v.23 no.3
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• pp.25-53
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• 2013

This study analyzes the effect of Computer Aided Innovation (CAI) to improve R&D Capabilities empirically. Survey was distributed by e-mail and Google Docs, targeting CTO of 235 SMEs. 142 surveys were returned back (rate of return 60.4%) from companies. Survey results from 119 companies (83.8%) which are effective samples except no-response, insincere response, estimated value, etc. were used for statistics analysis. Companies with less than 50billion KRW sales of entire researched companies occupy 76.5% in terms of sample traits. Companies with less than 300 employees occupy 83.2%. In terms of the type of company business Partners (called 'partners with big companies' hereunder) who work with big companies for business occupy 68.1%. SMEs based on their own business (called 'independent small companies') appear to occupy 31.9%. The present status of holding IT system according to traits of company business was classified into partners with big companies versus independent SMEs. The present status of ERP is 18.5% to 34.5%. QMS is 11.8% to 9.2%. And PLM (Product Life-cycle Management) is 6.7% to 2.5%. The holding of 3D CAD is 47.1% to 21%. IT system-holding and its application of independent SMEs seemed very vulnerable, compared with partner companies of big companies. This study is comprised of IT infra and IT Utilization as CAI capacity factors which are independent variables. factors of R&D capabilities which are independent variables are organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability. The highest average value of variables was 4.24 in organization capability 2. The lowest average value was 3.01 in IT infra which makes users access to data and information in other areas and use them with ease when required during new product development. It seems that the inferior environment of IT infra of general SMEs is reflected in CAI itself. In order to review the validity used to measure variables, Factors have been analyzed. 7 factors which have over 1.0 pure value of their dependent and independent variables were extracted. These factors appear to explain 71.167% in total of total variances. From the result of factor analysis about measurable variables in this study, reliability of each item was checked by Cronbach's Alpha coefficient. All measurable factors at least over 0.611 seemed to acquire reliability. Next, correlation has been done to explain certain phenomenon by correlation analysis between variables. As R&D capabilities factors which are arranged as dependent variables, organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability turned out that they acquire significant correlation at 99% reliability level in all variables of IT infra and IT Utilization which are independent variables. In addition, correlation coefficient between each factor is less than 0.8, which proves that the validity of this study judgement has been acquired. The pair with the highest coefficient had 0.628 for IT utilization and technology-accumulating capability. Regression model which can estimate independent variables was used in this study under the hypothesis that there is linear relation between independent variables and dependent variables so as to identify CAI capability's impact factors on R&D. The total explanations of IT infra among CAI capability for independent variables such as organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability are 10.3%, 7%, 11.9%, 30.9%, and 10.5% respectively. IT Utilization exposes comprehensively low explanatory capability with 12.4%, 5.9%, 11.1%, 38.9%, and 13.4% for organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability respectively. However, both factors of independent variables expose very high explanatory capability relatively for technology-accumulating capability among independent variable. Regression formula which is comprised of independent variables and dependent variables are all significant (P<0.005). The suitability of regression model seems high. When the results of test for dependent variables and independent variables are estimated, the hypothesis of 10 different factors appeared all significant in regression analysis model coefficient (P<0.01) which is estimated to affect in the hypothesis. As a result of liner regression analysis between two independent variables drawn by influence factor analysis for R&D capability and R&D capability. IT infra and IT Utilization which are CAI capability factors has positive correlation to organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability with inside and outside which are dependent variables, R&D capability factors. It was identified as a significant factor which affects R&D capability. However, considering adjustable variables, a big gap is found, compared to entire company. First of all, in case of partner companies with big companies, in IT infra as CAI capability, organization capability, process capability, human resources capability, and technology capability out of R&D capacities seems to have positive correlation. However, collaboration capability appeared insignificance. IT utilization which is a CAI capability factor seemed to have positive relation to organization capability, process capability, human resources capability, and internal/external collaboration capability just as those of entire companies. Next, by analyzing independent types of SMEs as an adjustable variable, very different results were found from those of entire companies or partner companies with big companies. First of all, all factors in IT infra except technology-accumulating capability were rejected. IT utilization was rejected except technology-accumulating capability and collaboration capability. Comprehending the above adjustable variables, the following results were drawn in this study. First, in case of big companies or partner companies with big companies, IT infra and IT utilization affect improving R&D Capabilities positively. It was because most of big companies encourage innovation by using IT utilization and IT infra building over certain level to their partner companies. Second, in all companies, IT infra and IT utilization as CAI capability affect improving technology-accumulating capability positively at least as R&D capability factor. The most of factor explanation is low at around 10%. However, technology-accumulating capability is rather high around 25.6% to 38.4%. It was found that CAI capability contributes to technology-accumulating capability highly. Companies shouldn't consider IT infra and IT utilization as a simple product developing tool in R&D section. However, they have to consider to use them as a management innovating strategy tool which proceeds entire-company management innovation centered in new product development. Not only the improvement of technology-accumulating capability in department of R&D. Centered in new product development, it has to be used as original management innovative strategy which proceeds entire company management innovation. It suggests that it can be a method to improve technology-accumulating capability in R&D section and Dynamic capability to acquire sustainable competitive advantage.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.1-18
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• 2016

Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.5_6
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• pp.257-266
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• 2007

In On-Chip bus, the arbitration scheme is one of the critical factors that decide the overall system performance. The arbitration scheme used in traditional shared bus is the master-side arbitration based on the request and grant signals between multiple masters and single arbiter. In the case of the master-side arbitration, only one master and one slave can transfer the data at a time. Therefore the throughput of total bus system and the utilization of resources are decreased in the master-side arbitration. However in the slave-side arbitration, there is an arbiter at each slave port and the master just starts a transaction and waits for the slave response to proceed to the next transfer. Thus, the unit of arbitration can be a transaction or a transfer. Besides the throughput of total bus system and the utilization of resources are increased since the multiple masters can simultaneously perform transfers with independent slaves. In this paper, we implement and analyze the arbitration schemes for the Multi-Layer AHB BusMatrix based on the slave-side arbitration. We implement the slave-side arbitration schemes based on fixed priority, round robin and dynamic priority and accomplish the performance simulation to compare and analyze the performance of each arbitration scheme according to the characteristics of the master and slave. With the performance simulation, we observed that when there are few masters on critical path in a bus system, the arbitration scheme based on dynamic priority shows the maximum performance and in other cases, the arbitration scheme based on round robin shows the highest performance. In addition, the arbitration scheme with transaction based multiplexing shows higher performance than the same arbitration scheme with single transfer based switching in an application with frequent accesses to the long latency devices or memories such as SDRAM. The improvements of the arbitration scheme with transaction based multiplexing are 26%, 42% and 51%, respectively when the latency times of SDRAM are 1, 2 and 3 clock cycles.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.154-166
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• 2009

Database query and reporting tools, OLAP tools and data mining tools are typical front-end tools in Business Intelligence environment which is able to support gathering, consolidating and analyzing data produced from business operation activities and provide access to the result to enterprise's users. Traditional reporting tools have an advantage of creating sophisticated dynamic reports including SQL query result sets, which look like documents produced by word processors, and publishing the reports to the Web environment, but data source for the tools is limited to RDBMS. On the other hand, OLAP tools and data mining tools have an advantage of providing powerful information analysis functions on each own way, but built-in visualization components for analysis results are limited to tables or some charts. Thus, this paper presents a system that integrates three typical front-end tools to complement one another for BI environment. Traditional reporting tools only have a query editor for generating SQL statements to bring data from RDBMS. However, the reporting tool presented by this paper can extract data also from OLAP and data mining servers, because editors for OLAP and data mining query requests are added into this tool. Traditional systems produce all documents in the server side. This structure enables reporting tools to avoid repetitive process to generate documents, when many clients intend to access the same dynamic document. But, because this system targets that a few users generate documents for data analysis, this tool generates documents at the client side. Therefore, the tool has a processing mechanism to deal with a number of data despite the limited memory capacity of the report viewer in the client side. Also, this reporting tool has data structure for integrating data from three kinds of data sources into one document. Finally, most of traditional front-end tools for BI are dependent on data source architecture from specific vendor. To overcome the problem, this system uses XMLA that is a protocol based on web service to access to data sources for OLAP and data mining services from various vendors.

• Korean Journal of Agricultural Science
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• v.11 no.1
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• pp.160-175
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• 1984

This study was carried out to analyze the effects of the revolution and forwarding speed of the rotary blade and the edge curves which were $30^{\circ}$ and $40^{\circ}$, on the power requirement of rotary tillage. In this study, the revolutions of the rotary blade considered were 204, 243, 285, 360 rpm, and the forwarding speeds of the rotary system considered were 29.40cm/sec, 46.93em/sec. The power requirements of rotary blade were measured by a dynamic strain gage systems at the soil bin which was filled with artificial soil. The results of the study were summarized as follows: 1. The response surface analysis showed that the revolution and forwarding speed of the rotary shaft had an interacting influence on the torque requirement of the rotary blade. The mathematical model developed by the above was repersented as follow. $$T=a_0+a_1V+a_2R +a_3VR+a_4VR^2$$ where, $a_0=constant$ $a_1,\;a_2,\;a_3,\;a_4=coefficients$ V=forwarding speed of the rotary system. (em/sec) R=revolution of the rotary shaft. (rpm) T=tilling torque requirement. (kg-m) 2. When the maximum tilling torque requirement was analyzed, ${\partial}T/{\partial}R$ was decreased with the increasing revolution of rotary shaft, while ${\partial}T/{\partial}V$ was increased, which was minimum at 200~220 rpm. When the forwarding speeds were increased, ${\partial}T/{\partial}R$ was decreased with increasing rate. 3. When the mean tilling torque requirement was analyzed, ${\partial}T/{\partial}V$ was constant at 320~360 rpm and ${\partial}T/{\partial}R$ was decreased with increasing rate along with the increasing revolution of rotary shaft. 4. When the mean tilling torgue requirement per unit volume of soil was analyzed, ${\partial}T/{\partial}V$ was minimum at 270~300 rpm. ${\partial}T/{\partial}R$ for the forwarding speeds of 29.40cm/sec and 46.93cm/sec was same as that for 280~290 rpm. 5. Increasing the edge curves of the rotary blades, the tilling torque requirement was increased. But other studies showed that the smaller the edge curve, the more straw could be wrapped on blades which resulted in increasing torque requirements. Therefore, the edge curve of rotary blade should be considered for the future study.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.391-401
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• 2004

3D imaging systems using 2D phased arrays have a large number of active channels, compelling to use a very expensive and bulky beamforming hardware, and suffer from low volume rate because, in principle, at least one ultrasound transmit-receive event is necessary to construct each scanline. A high speed 3D imaging method using a cross array proposed previously to solve the above limitations can implement fast scanning and dynamic focusing in the lateral direction but suffer from low resolution except at the fixed transmit focusing along the elevational direction. To overcome these limitations, we propose a new real-time volumetric imaging method using a cross array based on the synthetic aperture technique. In the proposed method, ultrasound wave is transmitted successively using each elements of an 1D transmit array transducer, one at a time, which is placed along the elevational direction and for each firing, the returning pulse echoes are received using all elements of an 1D receive array transducer placed along the lateral direction. On receive, by employing the conventional dynamic focusing and synthetic aperture method along lateral and elevational directions, respectively, ultrasound waves can be focused effectively at all imaging points. In addition, in the proposed method, a volume of interest consisting of any required number of slice images, can be constructed with the same number of transmit-receive steps as the total number of transmit array elements. Computer simulation results show that the proposed method can provide the same and greatly improved resolutions in the lateral and elevational directions, respectively, compared with the 3D imaging method using a cross array based on the conventional fixed focusing. In the accompanying paper, we will also propose a new real-time 3D imaging method using a cross array for improving transmit power and elevational spatial resolution, which uses linear wave fronts on transmit.

• Proceedings of the KOR-KST Conference
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• 1995.12a
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• pp.45-73
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• 1995

The current paper presents a system dynamics model which can generate the land use anq transportation system performance simultaneously is proposed. The model system consists of 7 submodels (population, migration of population, household, job growth-employment-land availability, housing development, travel demand, and traffic congestion level), and each of them is designed based on the causality functions and feedback loop structure between a large number of physical, socio-economic, and policy variables. The important advantages of the system dynamics model are as follows. First, the model can address the complex interactions between land use and transportation system performance dynamically. Therefore, it can be an effective tool for evaluating the time-by-time effect of a policy over time horizons. Secondly, the system dynamics model is not relied on the assumption of equilibrium state of urban systems as in conventional models since it determines the state of model components directly through dynamic system simulation. Thirdly, the system dynamics model is very flexible in reflecting new features, such as a policy, a new phenomenon which has not existed in the past, a special event, or a useful concept from other methodology, since it consists of a lots of separated equations. In Chapter I, II, and III, overall approach and structure of the model system are discussed with causal-loop diagrams and major equations. In Chapter V _, the performance of the developed model is applied to the analysis of the impact of highway capacity expansion on land use for the area of Montgomery County, MD. The year-by-year impacts of highway capacity expansion on congestion level and land use are analyzed with some possible scenarios for the highway capacity expansion. This is a first comprehensive attempt to use dynamic system simulation modeling in simultaneous treatment of land use and transportation system interactions. The model structure is not very elaborate mainly due to the problem of the availability of behavioral data, but the model performance results indicate that the proposed approach can be a promising one in dealing comprehensively with complicated urban land use/transportation system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8B
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• pp.509-520
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• 2007

In this paper, we propose a real-time sensor node platform that guarantees the real-time scheduling of periodic and aperiodic tasks through a multitask-based software decomposition technique. Since existing sensor networking operation systems available in literature are not capable of supporting the real-time scheduling of periodic and aperiodic tasks, the preemption of aperiodic task with high priority can block periodic tasks, and so periodic tasks are likely to miss their deadlines. This paper presents a comprehensive evaluation of how to structure periodic or aperiodic task decomposition in real-time sensor-networking platforms as regard to guaranteeing the deadlines of all the periodic tasks and aiming to providing aperiodic tasks with average good response time. A case study based on real system experiments is conducted to illustrate the application and efficiency of the multitask-based dynamic component execution environment in the sensor node equipped with a low-power 8-bit microcontroller, an IEEE802.15.4 compliant 2.4GHz RF transceiver, and several sensors. It shows that our periodic and aperiodic task decomposition technique yields efficient performance in terms of three significant, objective goals: deadline miss ratio of periodic tasks, average response time of aperiodic tasks, and processor utilization of periodic and aperiodic tasks.