{"title":"Optimal quality-aware predictor-based adaptation of multimedia messages","authors":"S. Pigeon, S. Coulombe","doi":"10.1109/IDAACS.2011.6072803","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072803","url":null,"abstract":"Multimedia Messaging Services (MMS) allow messages composed of different media attachments to be exchanged between heterogeneous devices. In this work, we consider the special case of image-only messages, where the challenge is to adapt messages so that the receiving device constraints are satisfied while maximizing the user's perceived quality of adapted messages. We propose an adaptation algorithm based on predictors for file size and quality resulting from transcoding parameters that explicitly maximizes an objective function based on the structural similarity image quality index. We show that the proposed method is not only resilient to the imprecision of predictors, but also yields significantly better quality at reduced computational complexity compared to other methods proposed in prior art.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128422158","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":"WSN testing environment with energy consumption monitoring and simulation of sensed data","authors":"G. Girban, M. Popa","doi":"10.1109/IDAACS.2011.6072890","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072890","url":null,"abstract":"Design and development of wireless sensor networks implies software simulations and hardware tests. Through this paper, the testing environment developed in the lab for WSN nodes energy consumption monitoring and hardware simulation of the nodes behavior in a small scaled network is presented. It is designed to individually control the sensed data and the power supply of each sensor node from the network using a wired network of microcontroller based modules that are assigned to one or several sensors. These modules are linked on the same CAN bus used as communication media together with a computer system which manage the message flow. This system can be easily expanded to support more nodes, only by connecting the pairs of microcontroller boards — wireless sensors to the CAN bus. It was designed to support new features by defining and implementing related CAN messages and updating the software running on microcontroller boards.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133086020","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}
D. Heras, Francisco Argüello, J. L. Gómez, J. Becerra, R. Duro
{"title":"Towards real-time hyperspectral image processing, a GP-GPU implementation of target identification","authors":"D. Heras, Francisco Argüello, J. L. Gómez, J. Becerra, R. Duro","doi":"10.1109/IDAACS.2011.6072765","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072765","url":null,"abstract":"In the quest for real time processing of hyperspectral images, this paper presents two artificial intelligence algorithms for target detection specially developed for their implementation over GPU and applied to a search-and-rescue scenario. Both algorithms are based on the application of artificial neural networks to the hyperspectral data. In the first algorithm the neural networks are applied at the level of individual pixels of the image. The second algorithm is a multiresolution based approach to scale invariant target identification using a hierarchical artificial neural network architecture. We have studied the main issues for the efficient implementation of the algorithms in GPU: the exploitation of thousands of threads that are available in this architecture and the adequate use of bandwidth of the device. The tests we have performed show both the effectiveness of detection of the algorithms and the efficiency of the GPU implementation in terms of execution times.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129313318","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":"Direct magnitude spectrum analysis algorithm for tone identification in polyphonic music transcription","authors":"M. Bohac, J. Nouza","doi":"10.1109/IDAACS.2011.6072798","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072798","url":null,"abstract":"This paper proposes a bottom-up (data-driven) algorithm for estimating of the fundamental frequencies (F0) of concurrent musical sounds and for detecting their onsets from single-channel recordings. The algorithm is aimed at transcribing notes played with pitched musical instruments. The complexity of the solved problem is caused by the fact that multiple sound sources create one composite sound wave. Hence, the separation of individual tones is an ambiguous task. The proposed algorithm minimizes the use of traditionally employed perception models. It estimates fundamental frequencies directly from the DFT applied on short signal frames. As the algorithm does not use any musical instrument models, it is instrument-independent. The basic algorithm is complemented by an onset detector so that all pieces of information needed for musical transcription are available, i.e. the onset time, the pitch and the duration of detected tones. The algorithm accuracy has been evaluated using a set of synthesized recordings. The results are compared with those presented by other authors. Our method is straightforward and its results are quite promising: the accuracy of F0 estimation gets over 92 %, that of onset detection is better than 85 %.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122280770","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":"Virtual instrumentation based power quality analyzer","authors":"D. Kaminsky, J. Zidek, P. Bilik","doi":"10.1109/IDAACS.2011.6072736","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072736","url":null,"abstract":"Paper deals with the architecture of Power Quality Analyzer based on CompactRIO platform. The Power Quality Analyzer functionality is based on requirements of the latest power quality standards e.g. IEC 61000–4–30, 61000–4–7, 61000–4–15, EN 50160. There are many vendors of such an instrument worldwide, most of them use proprietary solutions based on microcomputers or DSPs. Such instruments are small and have low consumption however they do not bring flexibility and modularity of analyzers based on virtual instrumentation. The trend for complex measurement instrument over the last years moved towards measurement instruments that define their capability through software. Virtual instrumentation is at the forefront of this trend.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130170081","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":"Fault detection and diagnosis of a motor bearing shield","authors":"J. Suwatthikul, S. Sornmuang","doi":"10.1109/IDAACS.2011.6072768","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072768","url":null,"abstract":"Recent years have seen increased attention to the Preventive Maintenance (PM) where corrective actions are promptly taken before small faults manifest themselves to be serious failures. Also, these undetected incipient faults present in an unhealthy machine can result in unnecessary waste of energy. Therefore, fault detection and diagnosis at the very early stage have become important. This paper presents an application of an Adaptive-Network-based Fuzzy Inference System (ANFIS) for diagnosing faults in the bearing shield of an induction motor. The experimental results show that the vibration parameters can efficiently indicate the occurrence of the faults which can be detected by the system.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130267378","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 novel approach to sentence alignment from comparable corpora","authors":"M. Li, V. Klyuev, Shih-Hung Wu","doi":"10.1109/IDAACS.2011.6072842","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072842","url":null,"abstract":"This paper introduces a new technique to select candidate sentences for alignment from bilingual comparable corpora. Tests were done utilizing Wikipedia as a source for bilingual data. Our test languages are English and Chinese. A high quality of sentence alignment is illustrated by a machine translation application.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128825510","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}
Saowaluck Kaewkamnerd, A. Intarapanich, Montri Pannarut, Sastra Chaotheing, C. Uthaipibull, S. Tongsima
{"title":"Detection and classification device for malaria parasites in thick-blood films","authors":"Saowaluck Kaewkamnerd, A. Intarapanich, Montri Pannarut, Sastra Chaotheing, C. Uthaipibull, S. Tongsima","doi":"10.1109/IDAACS.2011.6072791","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072791","url":null,"abstract":"In Thailand, malaria diagnosis still relies primarily on microscopic examination of Giemsa-stained thick and thin blood films. However, the method requires vigorously trained technicians to correctly identify the disease, and is known to be error-prone due to human fatigue. The limited number of such technicians further reduces the effectiveness of the attempt to control malaria. Thus, this project aims to develop an automated system to identify and analyze parasite species on thick blood films by image analysis techniques. The system comprises two main components: (1) Image acquisition unit and (2) Image analysis module. In our work, we have developed an image acquisition system that can be easily mounted on most conventional light microscopes. It automatically controls the movement of microscope stage in 3-directional planes. The vertical adjustment (focusing) can be made in a nanometer range (7–9 nm). Images are acquired with a digital camera that is installed at the top of microscope. The captured images are analyzed by our image analysis software which utilizes the state-of-the-art algorithms to detect and identify malaria parasites.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"123 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129524823","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":"New feature selection method for multi-class data: Iteratively weighted AUC (IWA)","authors":"P. Honzík, P. Kucera, O. Hyncica, Daniel Haupt","doi":"10.1109/IDAACS.2011.6072769","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072769","url":null,"abstract":"This paper deals with the new filter feature selection method Iteratively Weighted Area under Receiver Operating Characteristic (IWA). It is aimed for the multi-class problems with quantitative inputs. The experiments prove its superior quality in comparison to the equivalent methods.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129687090","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}
I. Paliy, V. Dovgan, O. Boumbarov, Stanislav Panev, A. Sachenko, Y. Kurylyak, Diana Zagorodnya
{"title":"Fast and robust face detection and tracking framework","authors":"I. Paliy, V. Dovgan, O. Boumbarov, Stanislav Panev, A. Sachenko, Y. Kurylyak, Diana Zagorodnya","doi":"10.1109/IDAACS.2011.6072790","DOIUrl":"https://doi.org/10.1109/IDAACS.2011.6072790","url":null,"abstract":"Face detection and tracking framework is described in the paper. Face detection is based on combined cascade of neural network-classifiers. Tracking is performed using Kalman filter. The framework was experimentally researched on a test video sequence and adjusted to obtain high processing speed.","PeriodicalId":106306,"journal":{"name":"Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129447183","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}