Huaguo Huang, Jinqing Jiang, Haitang Zhang, Ziliang Wang, Xin-peng Li
{"title":"Development of a polyclonal antibody based immunoassay for detection of molybdenum levels in environmental water","authors":"Huaguo Huang, Jinqing Jiang, Haitang Zhang, Ziliang Wang, Xin-peng Li","doi":"10.1109/ICAWST.2011.6163121","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163121","url":null,"abstract":"An indirect competitive ELISA (icELISA) based on anti-mice polyclonal antibody has been developed for the determination of molybdenum (Mo) levels in environmental water. For this reason, isothiocyanate method was employed to synthesize the artificial antigen of Mo-ITCBE-BSA, and Balb/C mice were used to prepare the polyclonal antibody. Based on the square matrix titration, an icELISA method was developed. The dynamic range was from 0.16 to 78 ng/mL, with LOD and IC50 value of 0.08 ng/mL and 3.2 ng/mL, respectively. Except for cross-reactivity to Co2+ (36.3%) and Hg2+ (42.5%), negligible cross-reactivity to other metal ions was observed. Under optimization dilution folds, the recoveries of Mo2+ were in the range of 95.3–117.5%, 88.7–113.5% and 97.5–104.2% for tap water, river water and lake water, respectively. Therefore, this assay has the potential to be incorporated into a quantitative monitoring program for the rapid screening of molybdenum levels in water.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128652283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Awareness promoting visualization of biasedness of discussion progress of microblogs","authors":"Yasuyuki Hatoh, K. Takeuchi, Kiyota Hashimoto","doi":"10.1109/ICAWST.2011.6163108","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163108","url":null,"abstract":"Microblogs like Twitter presents users with the others postings they choose to follow by themselves and related postings that are re-posted by the others. It raises a problem that they see only what they think favorable, although there is a wide variation of opinions. To cultivate a better information literacy, such biases should be presented to promote awareness on the biasedness not only of what they see and read but also of themselves. This study proposes a new method to detect the biased progress of discussion on a given topic on Twitter without a prepared set of keywords or dictionaries, and to visualize the pattern of the discussion progress. We employ the principal component analysis to capture the pattern of biasedness, and our contrastive experiment with human judgment shows that our method captures the real biasedness effectively.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130781547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Detection of audio interpolation based on singular value decomposition","authors":"Qian Shi, Xiaohong Ma","doi":"10.1109/ICAWST.2011.6163157","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163157","url":null,"abstract":"Interpolation attack, as a kind of tampering manipulation, is a common issue in digital audio forgeries. A new blind forensic approach for detecting interpolation forgery is proposed in this paper. As interpolation can lead to the statistical changes in the linear dependencies among digital audio sample points, singular value decomposition which can well express linear dependencies is used in the method. After audio is analyzed by singular value decomposition, a feature, counting the average number of zero singular values, is produced to describe the statistical changes. The proposed method based on singular value decomposition can locate the interpolation forgeries simply and fast compared to existing methods. The experiments conducted demonstrate the validity of the proposed method.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128581893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A steering kernel based nonlocal-means method for image denoising","authors":"Wenchao Jin, Jinqing Qi","doi":"10.1109/ICAWST.2011.6163125","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163125","url":null,"abstract":"The nonlocal-means (NLM) is a powerful method for image denoising which takes advantage of the redundancy of similar patches in the image. The steering kernel regression is a non-parametric estimation for image restoration that develops a data-adapted steering kernel based on local orientation estimate. In this paper, a steering kernel based nonlocal-means filter (SK-NLM) has been developed which not only exploits the self-similarity of the image, but also considering the structural information by the steering kernel. Experimental results show that the proposed method effectively improve the PSNR while preserving local structures.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125005661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Image enhancement method based on fuzzy set and subdivision","authors":"Guo Xian Jiu, Jiang Feng Jiao, L. Xiang","doi":"10.1109/ICAWST.2011.6163135","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163135","url":null,"abstract":"Alga microscopic image usually has a lot of noises and blurs. So a proper image enhancement algorithm which can remove noise and retain detail information is very important for alga microscopic image disposal. In the paper a new image enhancement method based on fuzzy set and subdivision is proposed. It is effective for alga microscopic image disposal. Subdivision scheme's good similarity among different subdivision layers makes the multi-resolution analysis has better approximation between the decomposed signals and the initial image. Subdivision method has strong ability to suppress noise through decomposing the initial image into low pass part. The image can be reconstructed through subdividing the low pass part of the initial image. Then the fuzzy set method is used for enhancement the reconstructed image. A special function is used as membership function in the process of fuzzification. The experimental results demonstrate the effectiveness of the proposed method for alga microscope image diaposal.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133799123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The method of android application speed up by using NDK","authors":"Ki-Cheol Son, Jong-Yeol Lee","doi":"10.1109/ICAWST.2011.6163104","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163104","url":null,"abstract":"The Android platform is one of the most popular used embedded OS, is mounted on robot, TVs, especially on Smart phones. Because general android applications are developed by the JAVA language, it is very slow in case which requires many calculational operations such as image processing. To overcome these defects, the Android OS is supporting JNI with the Android NDK, which makes available to use the C libraries in the android at application level. Through NDK, the Android applications can approach hardware and is able to developed high speed application. In this paper, we consider that how to enhance performance of the JAVA applications by using the Android NDK. We compared original NyARToolKit, which is augmented reality engine, with the improved NyARToolKit using the NDK. Through this experiment, we confirmed that android application programmers can make their application efficiently by using the NDK. We could increase speed of NyARToolKit by 1.869 times in our experiment. This paper presents a guideline for an effective way to use native code libraries in Android applications.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133026272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Target shift awareness in balanced ensemble learning","authors":"Y. Liu","doi":"10.1109/ICAWST.2011.6163133","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163133","url":null,"abstract":"In the balanced ensemble learning for a two-class classification problem, the target values are shifted between [1 ∶ 0.5) or (0.5 ∶ 0] instead of 1 and 0 in the learned error function. Such shifted error function could let the ensemble avoid from unnecessary further learning on the well-learned data points. Therefore, the learning direction could be shifted away from the well-learned data points, and turned to the other not-yet-learned data points. By shifting away from well-learned data and focusing on not-yet-learned data, a good balanced learning could be achieved in the ensemble. Through examining both individual learners and the combined ensembles, this paper is to explore how the target shift awareness could help to decide a decision boundary that is neither too close nor too further to all training samples.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115915414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kyu Ik Kim, C. Jin, Y. Lee, Kwang Deuk Kim, K. Ryu
{"title":"Forecasting wind power generation patterns based on SOM clustering","authors":"Kyu Ik Kim, C. Jin, Y. Lee, Kwang Deuk Kim, K. Ryu","doi":"10.1109/ICAWST.2011.6163181","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163181","url":null,"abstract":"Due to incontinent use of fossil fuels all over the world, it comes to be exhausted and also causes serious environmental pollutions and global warming. Therefore, people begin to find renewable energy which is clean, no limit and reproducible. Among several renewable energies, wind power is the most promising one which can be connected to the electric power system. However, it is very important to predict the wind power generation patterns in the electric power system to balance the load and generation. In this paper, we propose a framework to predict the wind power generation patterns with classification models. This framework consists of the following steps: (1) data preprocessing to handle noise data, missing values, (2) assignment of class labels to wind power generation patterns using SOM clustering, (3) classification model construction to predict the wind power generation patterns. The experiment result shows that the rules from decision tree are simple and easy to interpret. And it is possible to predict wind generation patterns.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114408293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Robust object tracking by adaptive models combination","authors":"Gang Yang, D. Wang, Yutao Wang, Zunyi Wang","doi":"10.1109/ICAWST.2011.6163132","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163132","url":null,"abstract":"Robust tracking is a challenging problem, due to intrinsic appearance variability of objects caused by in-plane or out-plane rotation and extrinsic factors change such as illumination, occlusion, background clutter and local blur. A tracker based on a single cue may be robust to certain distractions but vulnerable to some others. Therefore, it is appealing to fuse multiple cues into one tracker. In this paper, we propose an adaptive models combination framework for visual tracking. The color cue, texture cue and global representation of object are fused into one tracker by combination of three individual models. Then a simple yet effective adaptive weights strategy is proposed for evaluating weights of different models based on their performance. Experiments are performed on some changeling video sequences, both public and our own, show that our proposed framework achieve good performance.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121679742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mi-Yeong Hwang, C. Jin, Y. Lee, Kwang Deuk Kim, Jungpil Shin, K. Ryu
{"title":"Prediction of wind power generation and power ramp rate with time series analysis","authors":"Mi-Yeong Hwang, C. Jin, Y. Lee, Kwang Deuk Kim, Jungpil Shin, K. Ryu","doi":"10.1109/ICAWST.2011.6163182","DOIUrl":"https://doi.org/10.1109/ICAWST.2011.6163182","url":null,"abstract":"The use of fossil fuel in the world has been increasing and it generates lots of greenhouse gases. As a result, environmental pollution brought us a serious weather change. In order to reduce the environmental pollution, we should use renewable energy that does not produce any pollution such as wind data. However, wind data can change much in a short time, which is called ramp event. It can make the demand and response imbalance and also cause damages to the wind turbines. Therefore, we should predict the power generation and power ramp rate (PRR) to avoid these problems. In this paper, we predicted the wind power generation and PRR with exponential smoothing method and ARIMA. The prediction method predict wind power generation and PRR after 1 minute using data measured 1 hour ago at 10 intervals. We got forecasting error rate such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), and then we compared two results of ARIMA and exponential smoothing method. The comparison results showed that exponential smoothing method gets better prediction accuracy than ARIMA.","PeriodicalId":126169,"journal":{"name":"2011 3rd International Conference on Awareness Science and Technology (iCAST)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122869225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}