Search for: alarm-systems
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    Using and evaluating new confidence measures in word-based isolated word recognizers

    , Article 2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Sharjah, 12 February 2007 through 15 February 2007 ; 2007 ; 1424407796 (ISBN); 9781424407798 (ISBN) Vaisipour, S ; Babaali, B ; Sameti, H ; Sharif University of Technology
    In this paper a method for detecting out of vocabulary words in isolated word recognizers is introduced, our method utilized new kinds of confidence measure. After recognition task was completed and consequently confidence measure was extracted, a classifier would accept or reject result of recognition task using this CM. We used two different kinds of confidence measure where for extracting each one a different information source was used. Amount of competition between hypotheses through the recognition task was used for extracting first CM. The second one was extracted using information about manner of distribution of feature vectors in the states of winner HMM model. Both of these CMs... 

    Modeling Tsunami Wavesand Designinga Warning Systemfor This Phenomenon by UseofIT (Case Study the Sea of Oman)

    , M.Sc. Thesis Sharif University of Technology Namdar, Khashayar (Author) ; Abbaspour Tehrani, Majid (Supervisor)
    Tsunami, like many other natural disasters leaves people a short time for escape. When talking about Tsunami, the escape time is the period it takes for the wave to start moving from the epicenter, change into a giant wave gradually and reach to a cost. In order to minimize damages of this phenomenon, the escaped time has to be estimated without delay. For this purpose the first needed action is modeling the Tsunami waves. Analytical and numerical models and software that are designed based on them do exist. To have an efficient and rapid Tsunami alarming system all of these options are examined in this project. Then having a reliable model quite a few probable scenarios are propounded. The... 

    False alarm reduction by improved filler model and post-processing in speech keyword spotting

    , Article IEEE International Workshop on Machine Learning for Signal Processing, 18 September 2011 through 21 September 2011, Beijing ; 2011 ; 9781457716232 (ISBN) Tavanaei, A ; Sameti, H ; Mohammadi, S. H ; IEEE; IEEE Signal Processing Society ; Sharif University of Technology
    This paper proposes four methods for improving the performance of keyword spotting (KWS) systems. Keyword models are usually created by concatenating the phoneme HMMs and garbage models consist of all phonemes HMMs. We present the results of investigations involving the use of skips in states of keyword HMMs and we focus on improving the hit ratio; then for false alarm reduction in KWS we model the words that are similar to keywords and we create HMMs for highly frequent words. These models help to improve the performance of the filler model. Two post-processing steps based on phoneme and word probabilities are used on the results of KWS to reduce the false alarms. We evaluate the... 

    Some comments on wireless sensor networks for natural hazards

    , Article ACWR 2011 - Proceedings of the International Conference on Wireless Technologies for Humanitarian Relief, 18 December 2011 through 21 December 2011 ; December , 2011 , Pages 315-322 Grado Caffaro, M. A ; Grado Caffaro, M ; Ebrahimi, M. S ; Sharif University of Technology
    Presently, the urgency of creating efficient system to tackle natural hazards such as tsunamis, earthquakes, landslides and floods to cite just a few, have originated that Wireless Sensor Networks (WSNs) play an increasingly important role in the natural hazards scenario as an efficient early warning system, sometimes in synergy with satellites-GMES (Global Monitoring Earth Systems) and also with mobile robotics. Their integration into the web scenario, giving rise to the sensor-web technology, provides even more power to the intrinsic strengths of WSNs. The WSNs application in post-disaster scenarios is also an emerging challenging issue. In this paper the fundamental technology concepts of... 

    RTECA: Real time episode correlation algorithm for multi-step attack scenarios detection

    , Article Computers and Security ; Volume 49 , March , 2015 , Pages 206-219 ; 01674048 (ISSN) Ahmadian Ramaki, A ; Amini, M ; Ebrahimi Atani, R ; Sharif University of Technology
    Elsevier Ltd  2015
    Today, from information security perspective, prevention methods are not enough solely. Early Warning Systems (EWSs) are in the category of reactive methods. These systems are complementing Intrusion Detection Systems (IDSs) where their main goals include early detection of potential malicious behavior in large scale environments such as national level. An important process in EWSs is the analysis and correlation of alerts aggregated from the installed sensors (e.g., IDSs, IP telescopes, and botnet detection systems). In this paper, an efficient framework for alert correlation in EWSs is proposed. The framework includes a correlation scheme based on a combination of statistical and stream... 

    Fast and high-resolution PCL radar detection in noisy environment

    , Article 2nd Microwave and Radar Week in Poland - International Radar Symposium, IRS 2006, Krakow, 24 May 2006 through 26 May 2006 ; 2006 ; 8372076219 (ISBN); 9788372076212 (ISBN) Bayat, S ; Emadi, M ; Mousavi, M. R ; Jafargholi, A ; Nayebi, M. M ; Sharif University of Technology
    Multiple target detection in conventional PCL (Passive Coherent Location) radar systems by means of Ambiguity Function Processing and without any powerful algorithm is impossible. Presented Gradual Clean Algorithm (GCA) is a new and simple method, which could provide the perfect detection in noisy environment and heavy clutter condition up to SNR=-15 dB and SCR=-100 dB (clutter is assumed as a distributed target with large RCS). Determining the number of real targets and keeping the false alarm probability approximately constant are the presented algorithm capabilities  

    Multi-antenna assisted spectrum sensing in spatially correlated noise environments

    , Article Signal Processing ; Volume 108 , December , 2015 , Pages 69-76 ; 01651684 (ISSN) Koochakzadeh, A ; Malek Mohammadi, M ; Babaie Zadeh, M ; Skoglund, M ; Sharif University of Technology
    Elsevier  2015
    A significant challenge in spectrum sensing is to lessen the signal to noise ratio needed to detect the presence of primary users while the noise level may also be unknown. To meet this challenge, multi-antenna based techniques possess a greater efficiency compared to other algorithms. In a typical compact multi-antenna system, due to small interelement spacing, mutual coupling between thermal noises of adjacent receivers is significant. In this paper, unlike most of the spectrum sensing algorithms which assume spatially uncorrelated noise, the noises on the adjacent antennas can have arbitrary correlations. Also, in contrast to some other algorithms, no prior assumption is made on the... 

    A Vacuum arc diagnosis method for the high voltage power supply of vacuum tubes

    , Article 2019 International Vacuum Electronics Conference, IVEC 2019, 28 April 2019 through 1 May 2019 ; 2019 ; 9781538675342 (ISBN) Ayoubi, R ; Rahmanian, M ; Kaboli, S ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Vacuum tubes are widely used for various applications. These vacuum tubes are supplied by high voltage power supplies. The amount of delivered energy from the high voltage power supply to the vacuum tube is an important issue during the vacuum arc in the tube. The protection mechanism consists of a shunt crowbar which diverts the fault current from the tube to itself as a parallel path. Detection of the vacuum arc is crucial and only one sensor is usually employed to detect the vacuum arc. This characteristic intensifies the interference susceptibility of the vacuum arc diagnosis system in a noisy environment. As a result of the noise, the arc detection system can report false alarms. False...