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1 - Shifted Tietz–Wei oscillator for simulating the atomic interaction in diatomic molecules
Babatunde J. Falaye Sameer M. Ikhdair Majid HamzaviAbstractThe shifted Tietz–Wei (sTW) oscillator is as good as traditional Morse potential in simulating the atomic interaction in diatomic molecules. By using the Pekeris-type approximation, to deal with the centrifugal term, we obtain the bound-state solutions of the ra أکثرAbstractThe shifted Tietz–Wei (sTW) oscillator is as good as traditional Morse potential in simulating the atomic interaction in diatomic molecules. By using the Pekeris-type approximation, to deal with the centrifugal term, we obtain the bound-state solutions of the radial Schrödinger equation with this typical molecular model via the exact quantization rule (EQR). The energy spectrum for a set of diatomic molecules (NOa4Πidocumentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} egin{document}$${ m NO} left( a^4Pi _i ight) $$end{document}, NOB2Πrdocumentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} egin{document}$${ m NO} left( B^2Pi _r ight) $$end{document}, NOL′2ϕdocumentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} egin{document}$${ m NO} left( L'^2phi ight) $$end{document}, NOb4Σ-documentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} egin{document}$${ m NO} left( b^4Sigma ^{-} ight) $$end{document}, IClX1Σg+documentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} egin{document}$${ m ICl}left( X^1Sigma _g^{+} ight) $$end{document}, IClA3Π1documentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} egin{document}$${ m ICl}left( A^3Pi _1 ight) $$end{document} and IClA′3Π2documentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} egin{document}$${ m ICl}left( A'^3Pi _2 ight) $$end{document} for arbitrary values of ndocumentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} egin{document}$$n$$end{document} and ℓdocumentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} egin{document}$$ell $$end{document} quantum numbers are obtained. For the sake of completeness, we study the corresponding wavefunctions using the formula method. تفاصيل المقالة -
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2 - Analysis, Simulation and Optimization of LVQ Neural Network Algorithm and Comparison with SOM
Saeed Talati Mohammadreza Hassani AhangarThe neural network learning vector quantization can be understood as a special case of an artificial neural network, more precisely, a learning-based approach - winner takes all. In this paper, we investigate this algorithm and find that this algorithm is a supervised v أکثرThe neural network learning vector quantization can be understood as a special case of an artificial neural network, more precisely, a learning-based approach - winner takes all. In this paper, we investigate this algorithm and find that this algorithm is a supervised version of the vector quantization algorithm, which should check which input belongs to the class (to update) and improve it according to the distance and class in question. To give. A common problem with other neural network algorithms is the speed vector learning algorithm, which has twice the speed of synchronous updating, which performs better where we need fast enough. The simulation results show the same problem and it is shown that in MATLAB software the learning vector quantization simulation speed is higher than the self-organized neural network. تفاصيل المقالة -
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3 - Quantization Watermarking in Three-Dimensional Wavelet Transform Domain
Mohsen AshourianQuantization watermarking is a technique for embedding hidden copyright information based on dithered quantization. This non-blind scheme is only practical for watermarking applications, where the original signal is available to the detector as for a fingerprinting purp أکثرQuantization watermarking is a technique for embedding hidden copyright information based on dithered quantization. This non-blind scheme is only practical for watermarking applications, where the original signal is available to the detector as for a fingerprinting purpose. The goal of this paper is to analyse the quantization watermarking in the three-dimensional wavelet transform. We consider the nonlinear effect of dithered quantization in the time-domain representation of the filter bank. We derive a compact and general form for distortion in the host video due to the encoding and embedding process. The formulation has the capacity to be simplified and optimized for different filter banks and dither signals. We provide some supporting experiments for the three-dimensional wavelet analysis of video signal. تفاصيل المقالة -
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4 - طراحی و پیادهسازی سامانه امنیتی نظارتی مبتنی بر الگوریتم YOLO و فناوری اینترنت اشیاء برپایه شبکه داده همراه
محمدرضا مسائلی سید محمدعلی زنجانیافزایش چشمگیر امنیت، بهره¬وری مقیاس¬پذیری، پاسخگویی سریع و قابلیت اطمینان از مزایای طراحی و پیادهسازی سامانه امنیتی نظارتی مبتنی بر الگوریتم YOLO و فناوری اینترنت اشیا، در مقایسه با روشهای سنتی است. در این مقاله، به جنبه¬های ایجاد یک سامانه امنیتی نوین پرداخته می¬شود أکثرافزایش چشمگیر امنیت، بهره¬وری مقیاس¬پذیری، پاسخگویی سریع و قابلیت اطمینان از مزایای طراحی و پیادهسازی سامانه امنیتی نظارتی مبتنی بر الگوریتم YOLO و فناوری اینترنت اشیا، در مقایسه با روشهای سنتی است. در این مقاله، به جنبه¬های ایجاد یک سامانه امنیتی نوین پرداخته می¬شود که با تشخیص پنج رده شامل انسان، سر انسان، تفنگ، چاقو و تشخیص سقوط، هشدار را فعال می¬کند. نظارت بر عملکرد سامانه، بهصورت برخط است. این سامانه در هر نقطه به کمک شبکه داده تلفن همراه، قابلیت اتصال به اینترنت را دارد تا در صورت شناسایی تهدیدات، تصاویر را در پنل مدیریتی بارگذاری و گزارش آن را به کاربر ارسال کند. برای تعلیم اشیاء از الگوریتم YOLOv8 استفاده شده است تا از مزایایی مانند رابط خط فرمان کاربرپسند، پشتیبانی آن از شناسایی اشیاء، تقسیمبندی نمونه و طبقهبندی تصاویر بهره گیرد. برای افزایش سرعت پردازش، ضمن حفظ دقت، مدل بهینهسازیشده در بورد رزبری¬پای نسل چهارم استفاده شده است. واضح است که بهینهسازی سرعت پردازش و استفاده از تکنیکهای کمّیسازی منجر به کاهش مصرف انرژی (سامانه انرژی سبز) و کاهش هزینههای عملیاتی سامانه می¬شود. بهمنظور بهبود سرعت مدل در فرایند تشخیص اشیاء، از تکنیک صادرکردن، کمّی¬سازی وزنهای تعلیمی و افزایش فرکانس پردازنده (اورکلاک) استفاده می¬شود. مقایسه وزنهای صادرشده جدید با وزن اصلی تعلیمی، در شاخص دقت و سرعت، بیانگر آن است که دو تکنیک صادرکردن و کمّی¬سازی، منجر به افزایش سرعت پردازش، به¬ازای کاهش دقت در تشخیص می¬شود. درنهایت، در مدل تعلیمی با روشهای بهبود مطرح شده می¬توان بهدقت متوسط mAP ≅ 0.67 با تعداد قابِ تصویر در ثانیه FPS ≅ 4.3 دستیافت. تفاصيل المقالة -
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5 - Diagnosis of brain tumor using PNN neural networks
elahe alipoor azar Nasser LotfivandCells grow and then need a very neat method to create new cells that work properly to maintain the health of the body. When the ability to control the growth of the cells is lost, they are unconsidered and often divided without order. Exemplified cells form a tissue mas أکثرCells grow and then need a very neat method to create new cells that work properly to maintain the health of the body. When the ability to control the growth of the cells is lost, they are unconsidered and often divided without order. Exemplified cells form a tissue mass called the tumor. In fact, brain tumors are abnormal and uncontrolled cell proliferations. Segmentation methods are used in biomedical image processing and examines the methods used for better segmentation. Critical assessment of the current state of the automated and automated methods for categorizing anatomical medical pictures with emphasis on the benefits and disadvantages. In this project, we recognize brain tumors and classify tumor stages using database testing and training. Segmentation is used for testing purpose by FCM space. Neural networks are also used for its segmentation, which yields acceptable results in PNN neural networks. تفاصيل المقالة -
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6 - A Way to Reduce Effects of Packet Loss in Video Streaming Using Multiple Description Coding
Mahboobe Shabanyan Ehsan AkhtarkavanMultiple description (MD) coding has appeared to be an attractive technique to decrease impact of network failures and increase the robustness of multimedia communications. Very common model of this technique is multiple-description lattice vector quantization, which is أکثرMultiple description (MD) coding has appeared to be an attractive technique to decrease impact of network failures and increase the robustness of multimedia communications. Very common model of this technique is multiple-description lattice vector quantization, which is the best choice for robust data transmission over the unreliable network channels. However, MD coinciding lattice vector quantizer (MDCLVQ) is not considered discrete network conditions, so in this scheme, all videos are received or are not received. In this paper, this scheme is implemented in real network environment. So, raw video will be send in various packet, packets send independently and packets lose independently. The possibility of lossing all packets together is close to zero. Our object for increasing of resistance transfer in error- prone communication channels are used. This technique has been tested for standard videos "Akiyo", "Carphone", "Miss-America" and "Foreman". This results show that the quality of the reconstructed videos from the average PSNR values of the central decoder and the side decoders has been reached to grate degree, so increases error resilience over error-prone communication channels. تفاصيل المقالة -
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7 - A Method to Reduce Effects of Packet Loss in Video Streaming Using Multiple Description Coding
Mahboobe Shabaniyan Ehsan AkhtarkavanMultiple description (MD) coding has evolved as a promising technique for promoting error resiliency of multimedia system in real-time application programs over error-prone communicational channels. Although multiple description lattice vector quantization (MDCLVQ) is a أکثرMultiple description (MD) coding has evolved as a promising technique for promoting error resiliency of multimedia system in real-time application programs over error-prone communicational channels. Although multiple description lattice vector quantization (MDCLVQ) is an efficient method for transmitting reliable data in the context of potential error channels, this method doesn’t consider discreteness of network so that losing all descriptions is highly possible. It means all videos may be removed. In this study, we have implemented scheme of MDCLVQ in real-time environment of network, in a method that, raw video (i.e. video with no standard encoding (like MPEG)) is transmitted through independent packets inside of network. This technique leads in low or close to zero loss of all packets. Our purpose is to increase error resiliency and reliable data transmission in error-prone channels. The technique has been tested on some videos sources of Akiyo, Carphone, Foreman and Miss-America. The experimental results indicate that quality of reconstructed videos are substantially improved in terms of central and side PSNR. تفاصيل المقالة -
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8 - Disguised Face Recognition by Using Local Phase Quantization and Singular Value Decomposition
Fatemeh Jafari Hamidreza Rashidy KananDisguised face recognition is a major challenge in the field of face recognition which has been taken less attention. Therefore, in this paper a disguised face recognition algorithm based on Local Phase Quantization (LPQ) method and Singular Value Decomposition (SVD) is أکثرDisguised face recognition is a major challenge in the field of face recognition which has been taken less attention. Therefore, in this paper a disguised face recognition algorithm based on Local Phase Quantization (LPQ) method and Singular Value Decomposition (SVD) is presented which deals with two main challenges. The first challenge is when an individual intentionally alters the appearance by using disguise accessories, and the second one is when gallery images are limited for recognition. LPQ has been used for extraction of the statistical feature of the phase in windows with different sizes for each pixel of the image. SVD is used to cope with the challenge of the gallery images limitation and also with the help of original images extracted from that, every single image turns to three renovated images. In this study, disguise is intended as a blur in the image and Local phase quantization method is robust against the disguised mode, due to the use of the statistical feature of the Fourier transform phase. Also the use of different-sized window instead of fixed window in feature extraction stage, the performance of the proposed method has increased. The distance of images from each other is computed by using Manhattan and Euclidean distance for recognition in the proposed method. The Performance of the proposed algorithm has been evaluated by using three series of experiments on two real and synthesized databases. The first test has been performed by evaluating all the possible combinations of the different-sized windows created in the feature extraction stage, and the second experiment has been done by reducing the number of gallery images and then the third one has been carried out in different disguise. In all cases, the proposed method is competitive with to several existing well-known algorithms and when there is only an image of the person it even outperforms them. تفاصيل المقالة -
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9 - A New Compression Method based on Jpeg2000 and Contourlet Transform
Farima Jafari Reza JavidanThis paper presents a new coding method for image compression based on jpeg2000 and contourlet transform. Jpeg2000 standard is a common standard that uses Discrete Wavelet Transform (DWT) in the compression process. The main problems of DWT are failure to detect curved أکثرThis paper presents a new coding method for image compression based on jpeg2000 and contourlet transform. Jpeg2000 standard is a common standard that uses Discrete Wavelet Transform (DWT) in the compression process. The main problems of DWT are failure to detect curved edges in image and its shortage representation of the ridge and furrow patterns which cause deficiency and block artifacts remain in the decompressed image. Contourlet transform however, is a new two dimensional extension of the wavelet transform with multidirectional and multiscale filter banks. In this paper, jpeg2000 standard is improved by using contourlet transform and scalar quantization. The results obtained are compared with those of the wavelet based ones which show the superiority of the proposed method. In addition for images containing fine-textured, PSNR obtained by contourlet transform is higher than that of the wavelet transform, while texture and edge are reconstructed better than that of the Jpeg2000 standard. تفاصيل المقالة
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