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The ECG signal, has attracted more attention due to its importance in diagnosing conditions. Now days T-wave alternans (TWA) has been used to forecast Sudden Cardiac death (SCD). TWA is the beat-to-beat alterations changing in the T-wave amplitude. A new method is used in this paper to detect these alternans waves more exactly and quickly with heart rate calculation by RR-interval in ECG. This algorithm...
In India, now-a-days 95% of Indians are expected to use the bank transactions even for day-to-day requirements. Recognizing the genuine signature and finding out the fraud signature is the challenging task. Here, we have used an approach of Artificial Neural Network (ANN) to recognize the signature. In this method a signature is collected from the bank cheque by cropping the area of interest. Further...
Trademark retrieval systems have been a well researched field however majority of these researches have been done on device trademarks and do not consider the presence of text embedded within trademark images as in case of composite marks. In this work a unified retrieval system has been proposed and implemented for composite trademarks. The technique is invariant to font size, font style and orientations,...
In this paper a novel technique of fragment visible mosaic image is proposed. It is a unique and novel kind of computer art called Mosaic tile image steganography technique, which transforms a color secret image into a so called secret fragment visible mosaic image of the same size. Initially choose randomly any color cover image from the existing database, which looks similar to secret color image...
Parallelization of BLAST at the software level usually segments either the query or the database but not both. In this paper, we investigate a hybrid segmentation approach that combines database segmentation with query segmentation. By organizing the nodes into groups, splitting the queries among groups, and replicating the entire database at each group, we take advantage of both database segmentation...
Memcached is an in-memory key-value caching system, which is used to resolve the principal contradiction of the disk-based database between the CPU and input/output, has been widely used as an effective way to solve the distance and improve the capacity of the source server. We optimize the performance of Memcached memory access through two ways: improve the density of memory storage and ameliorate...
In this paper, we introduce algorithms for pruning and aging user ratings in collaborative filtering systems, based on their oldness, under the rationale that aged user ratings may not accurately reflect the current state of users regarding their preferences. The aging algorithm reduces the importance of aged ratings, while the pruning algorithm removes them from the database. The algorithms are evaluated...
In recent years, many financial sectors are evolving with huge numbers of web applications, which plays a crucial role in organizations to make important decisions. Considering this, the data has to be secured in order to prevent it from any attacks which lead to a huge loss. One of the topmost attacks in the database is SQL injection attack, is injecting some malicious query into the database causing...
Long intergenic non-coding RNAs (lincRNAs) are associated with a wide variety of human diseases. Piles of data about the lincRNAs are becoming available, thanks to the High Throughput Sequencing (HTS) platforms, which open opportunity for cutting-edge machine learning and data mining approaches to analyze the disease association better. However, there are only a few in silico association inference...
Facial aging is a biological phenomenon that can be affected by various factors. Although it is inexorable, a strong correlation is found between face age and lifestyle. Drug addiction can significantly change the manner of the face ageing, therefore the awareness of its negative effects and risks may help avoid addiction and reduce the number of the addicts. Unlike numerous studies dealing with the...
Sentiment negation and negation scoring can be considered as major aspects of sentiment analysis. Social media sentiment analysis can be considered as an excellent source of information in today's business. But there is very minimal work has been done in sentiment negation scoring. All the existing negation scoring mechanisms are based on an adjective intensity approach. This research proposes a novel...
In this paper, we introduce a formulation for a folding sum transformation and then investigate into its impact on binary classification. The proposed folding sum transformation can reduce dimension of data without a training process. The least squares estimation and a full multivariate polynomial expansion are utilized to apply the folding sum transformation for binary classification. Twelve binary...
Although iris is known as the most accurate and face as the most accepted in biometrics, these distinct modalities encounter variability in data in real-world applications. Such limitation can be overcome by a multimodal system based on both traits. Additionally, by conditioning the multimodal fusion on quality, useful information can be extracted from lower quality measures rather than rejecting...
Every company stores more and more product data. Most of the data are not analyzed and possible findings cannot be used. But the utilization of existing knowledge can make the system development process more efficient. Therefore, this paper focuses on the data analysis of system architectures. It develops a concept to identify patterns between system architectures of different products in a database...
When learning a new word in language learning, there are two problems. One is how difficult the word itself is. The second is, in what kind of situation, it will be used. There is a research that defined quantitative ambiguity of words based on the structure of WordNet, then investigated the relationship between the ambiguity and the difficulty level of words. In this paper, we re-define ambiguity...
Document Analysis and Recognition (DAR) has two main objectives, first the analysis of the physical structure of the input image of the document, which should lead to the correct identification of the corresponding different homogeneous components and their boundaries in terms of XY coordinates. Second, each of these homogeneous components should be recognized in such a way that, if it is a text image,...
Determining Voice Onset Time (V OT) in speech is a challenging problem, because it combines temporal and very short duration. VOT is important to detect and classify languages and dialects. This paper is important because of the lack of research in the field of speech processing in Arabic language. Detection of VOT by manually is feasible, but it becomes a time consume when the database is large....
Being able to automatically predict digital picture quality, as perceived by human observers, has become important in many applications where humans are the ultimate consumers of displayed visual information. Standard dynamic range (SDR) images provide 8 bits/color/pixel. High dynamic range (HDR) images which are usually created from multiple exposures of the same scene, can provide 16 or 32 bits/color/pixel,...
In this paper, we investigate the effect of transfer of emotion-rich features between source and target networks on classification accuracy and training time in a multimodal setting for vision based emotion recognition. First, we propose emosource-a 6-layer Deep Belief Network (DBN), trained on popular emotion corpora for emotion classification. Second, we propose two 6-layer DBNs — emotarget and...
We present a publicly available benchmark database for the problem of hand posture recognition from noisy depth data and fused RGB-D data obtained from low-cost time-of-flight (ToF) sensors. The database is the most extensive database of this kind containing over a million data samples (point clouds) recorded from 35 different individuals for ten different static hand postures. This captures a great...
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