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308 articles for “Memory”
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Research ArticleOpen accessEvery word in the titleImplementation of Low-Memory Reference FFT on Digital Signal ProcessorYi-Pin Hsu, Shin-Yu LinProblem statement: In order to improve and implement Fast Fourier Transform (FFT), in general, an efficient parallel form in digital signal processor is necessary. The butterfly structure is an important role in FFT, because its symmetry form is suitable for hardware implementation. Although it can perform a symmetric structure, the performance will be reduced under the data-dependent flow characteristic. Even … …Journal of Computer Science, Vol. 4, Issue 7 · 31 Jul 2008 · 7,142 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA New Three-Term Preconditioned Gradient memory Algorithm for Nonlinear Optimization ProblemsAbbas Y. AL-Bayati, Ivan S. LatifIn the present study, we proposed a three-term of preconditioned gradient memory algorithms to solve a nonlinear optimization problem. The new algorithm subsumes some other families of nonlinear preconditioned gradient memory algorithms as its subfamilies with Powell's Restart Criterion and inexact Armijo line searches. Numerical experiments on twenty one well-known test functions with various dimensions generally encouraged and showed that … …Journal of Mathematics and Statistics, Vol. 4, Issue 2 · 30 Jun 2008 · 6,781 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Generalized Discrete-Time Long Memory Volatility Model for Financial Stock ExchangeChin Wen CheongWe proposed a simple way to combine a few long memory models in financial market volatility modeling using daily, range and high frequency data. This model was able to fit the return, range of daily return or realized volatility under a parametric heavy-tailed distribution. Model was flexible to include additional volatility information as the contemporaneous variables. Empirical results found that … …American Journal of Applied Sciences, Vol. 4, Issue 12 · 31 Dec 2007 · 6,869 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Hybrid Method of Long Short-Term Memory and Auto-Encoder Architectures for Sarcasm DetectionMohammed M. AL-Ani, Nazlia Omar, Ahmed Adil NafeaSarcasm detection is considered one of the most challenging tasks in sentiment analysis and opinion mining applications in the social media. Sarcasm identification is therefore essential for a good public opinion decision. There are some studies on sarcasm detection that apply standard word2vec model and have shown great performance with word-level analysis. However, once a sequence of terms is being … …Journal of Computer Science, Vol. 17, Issue 11 · 1 Dec 2021 · 7,187 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Multi Layer Perceptron Along with Memory Efficient Feature Extraction Approach for Bengali Document CategorizationQuazi Ishtiaque Mahmud, Noymul Islam Chowdhury, Md MasumIn terms of the total number of speakers in the world Bengali stands as the seventh language and it has been used by approximately 265 million people worldwide. Day by day more people are expressing their views and opinions in Bengali in digital platforms like blogs and social media on various topics. Despite this, very little work has been done … …Journal of Computer Science, Vol. 16, Issue 3 · 28 Mar 2020 · 7,815 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMemory Convergence and Optimization with Fuzzy PSO and ACSSubhash C. Pandey, Dr. P. MisraAssociative neural memories are models of biological phenomena that allow for the storage of pattern associations and the retrieval of the desired output pattern upon presentation of a possibly noisy or incomplete version of an input pattern. In this study, we introduce fuzzy swarm particle optimization technique for convergence of associative neural memories based on fuzzy set theory. A Fuzzy … …Journal of Computer Science, Vol. 4, Issue 2 · 28 Feb 2008 · 7,169 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIntranasal Administration of Quercetin Liposome Decreases Anxiety-like Behavior and Increases Spatial MemoryJintanaporn Wattanathorn, Wathita Phachonpai, Aroonsri Priprem, Saengrawee SuthiparinyanontAt present, the effects of quercetin liposome on anxiolytic activity and cognitive function are unclearly known. In this study, male Wistar rats were administered quercetin liposome via intranasal route once daily continually for 4 weeks. The anxiolytic activity and cognitive enhancing effect were determined after single administration, 1, 2, 3 and 4 weeks of treatment using elevated plus maze test … …American Journal of Agricultural and Biological Sciences, Vol. 2, Issue 1 · 31 Mar 2007 · 9,091 accessesView PDFCite
Research ArticleOpen accessIn the keywordsGait Analysis Combining Sports Biomechanics and ImagingChao ZhuAiming at the problems of marker positioning error, soft tissue interference, and insufficient personalized modeling ability in traditional gait analysis, this study proposes a gait assessment method that integrates sports biomechanics and multimodal imaging analysis. Firstly, based on the public OU-ISIR gait database, a Convolutional Neural Network (CNN) is used to extract the key gait features in the human silhouette … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 20 Jul 2026 · 850 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAddressing Emergency Communication Challenges: Deep Learning Solutions for the Speech and Hearing- ImpairedPoornima B V, Srinath S et al.Emergency communication plays a very important role in ensuring that help reaches people promptly and safely in case of any emergency. However, the biggest problem faced by those who cannot speak and hear properly is to convey their message clearly and understand others. In this regard, the proposed research work focuses on recognizing emergency gestures made in the Indian Sign … …Journal of Computer Science, Vol. 22, Issue 5 · 1 Jun 2026 · 1,063 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,747 accessesView PDFCite