iosr-JCE   Volume-23 ~ Issue-6 ~ Nov. - Dec. 2021

Abstract: This paper presents an interesting methodology for a class of nonlinear system identification via the recurrent Extreme Learning Machine (ELM). The recurrent ELM has been used for training single hidden layer feed-forward neural networks. Vis-à-vis to various feed-forward NN the ELM is remarkably efficient and tends to reach global optimum with high convergence speed. For many real applications, in control system of view point can be represented by nonlinear autoregressive with external input (NARX) models. The recurrent ELM presents efficient tools for working with dynamical recurrent data. Recurrent Neural Network (RNN) is an adequate structure for NARX models and can be trained in online context.......

Key Word: adaptive identification, extreme learning machine, recurrent neural network, process modeling.

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[2]. Narendra KS, Parthasaraty K.Neural networks and dynamical systems. J Approx Reason 1992;6:109-131.
[3]. O. Taouali, I. Elaissi, and H. Messaoud 2012 Design and comparative study of online method identification of nonlinear system in RKHS space. Artificial Intelligence Review 2012; 4-37:289-300
[4]. Wang L, Zeng Y, Chen T. Back propagation neural network with adaptive differential evolution algorithm for time series forecasting. J Expert syst Appl 2015; 42: 855-863.
[5]. G.-B. Huang, L. Chen, and C.-K. Siew, "Universal approximation using incremental constructive feedforward networks with random hidden nodes," IEEE Transactions on Neural Networks, 2006; 7- 4 : 879–892.

Abstract: This article proposes a novel reduced fault detection method based on the data-driven approaches for process monitoring. An overview on machine learning methods took place to illustrate the efficiencies for Fault Detection (FD). The concept, the original ideas, the reduced steps, data storage and implementation conditions are discussed. The performance from the application viewpoint of the proposed Reduced Rank KPLS technique and all discussed methods are validated using an industrial benchmark.

Key Word: Machine learning, KPCA, RKPCA, Reduced Rank-KPCA, KPLS, RKPLS, Reduced Rank-KPLS, Fault detection.

[1]. Jafel I, Taouali O, Elaissi E, Messaoud H (2014) A new online fault detection method based on PCA technique. IMA Journal of Mathematical Control and Information 31(4):487-499
[2]. Tharrault Y, Mourot G, Ragot J, Maquin D (2008) Fault detection and isolation with robust principal component analysis. International Journal of Applied Mathematics and Computer Science 18(4):429-442
[3]. Muradore R, Fiorini P (2011) A PLS-based statistical approach for fault detection and isolation of robotic manipulators. IEEE Transactions on Industrial Electronics 59(8):3167-3175
[4]. Taouali O, Elaissi E, Messaoud H (2012) Design and comparative study of online kernel methods identi_cation of nonlinear system in RKHS space. Arti_cial Intelligence Review 37(4):289-300
[5]. Jiao J, Zhao N, Wang G, Yin S (2017) A nonlinear quality-related fault detection approach based on modi_ed kernel partial least squares.ISA transactions 66:275-283

Abstract: GNOME desktop environment stores user's credentials in process memory, which poses an obvious danger and needs to be fixed. The competitive advantage of the proposed security tool (MimiDove) includes its ability to quickly detect and remove passwords containing both ASCII characters and Unicode characters.

Key words: Linux passwords; application security; MimiPenguin; Mimipy;

[1]. F. Besson, A. Dang, T. Jensen (2018). Securing Compilation Against Memory Probing. PLAS '18 – 13th Workshop on Programming Languages and Analysis for Security
[2]. H. Gregal. (2017). Mimipenguin. https://github.com/huntergregal/mimipenguin
[3]. N. Verdier, (2017). Mimipy. https://github.com/n1nj4sec/mimipy
[4]. S. Golub. (2021). MimiDove. https://github.com/SvetlanaGolub/MimiDove

Abstract: Many researchers in medical science studied the similarity between the left and right retina of a patient. On the contrary, many retina-based biometric researchers consider that an individual's left and right retinas are different. Therefore, few works were reported in retina-based biometric for finding similarities between the left and right retina of an individual. This research intends to find similarities between an individual's left and right retina using orthogonal Legendre moments from a biometric perspective. Here, we use orthogonal Legendre moments for feature extraction and dimensionality reduction and cosine distance to measure similarity between the........

Key Word: Legendre moments, retina, cosine similarity, biometric

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Abstract: Digital images become popular for transferring visual information. There are many advantages for using these images instead of traditional camera film. Digital cameras produce instant images. These images can be viewed without the delay of waiting for film processing. There is no need of external development or processing. They can be stored easily because digital images do not take additional physical space. It can also be widely distributed electronically without time delay. But it is important to check the authenticity of digital images while using them. Because comparing to conventional images, the alteration in digital images are much easier. Many techniques are available in the field of image forensics to detect manipulations done in an image. In this paper, we discuss the various image tampering detection techniques used to find manipulations done in an image.

Key words: Digital images,image forensics, authenticity, tampering, manipulations

[1]. Sintayehu Dehnie, Taha Sencar, and Nasir Memon, "Digital image forensics for identifying computer generated and digital camera images," IEEE Conference Publications, Pages:2313-2316, Year: 2006.
[2]. Liu Zhulong, Li Xianghua, and Zhao Yuqian, "Passive detection of copy-paste tampering for digital image forensics," IEEE 4th International Conference on Intelligent Computation Technology Publications, Pages:649-652, Year: 2011.
[3]. Zhipeng Chen, Yao Zhao, and Rongrong Ni, "Forensics of blurred images based on no-reference image quality assessment,"IEEE Conference Publications, Pages:437-441, Year: 2013.
[4]. Xiaobo Zhai, Rongrong Ni, and Yao Zhao,"Recapture image detection based on texture features," IEEE 9th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, Pages:234-237, Year: 2013.
[5]. Huang Yan-li, Niu Shao-zhang, Zou Jian-cheng, and Zhou Lin-na, "Forensics of image tampering based on the consistency of illuminant chromaticity,"IEEE Conference Publications, Year: 2014

Abstract: Today, Real Time Video activity detection techniques are widely used for suspicious activity detection or for abnormal activity detection. This study paper has shed its light on different related work of real-time video activity detection technologies in the context of machine learning purposes. Moreover, this research study focused on video detection techniques such as face detection technology which is the most used technology of real time video activity detection with the help of CNN technology. In addition, it showed there are three different methods in human detection or video activity detection as Handcrafted motion features, Deep learning and Depth sensor. On the other hand, depth sensor is frequently using to develop the system of fall detection. The technique of depth senor is help to indicate potential fall as well as Kinect sensor has been used for authenticates the form of fall alert....

Keywords: Machine Learning, Deep Learning

[1]. Haritaoglu, I., Harwood, D. and Davis, L.S. "W/sup 4: real-time surveillance of people and their activities". IEEE Transactions on pattern analysis and machine intelligence, 22(8), 2017, pp.809 830.
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[3]. Tango, F. and Botta, M. "Real-time detection system of driver distraction using machine learning". IEEE Transactions on Intelligent Transportation Systems, 14(2), 2017, pp.894-905.L. von Rueden et al., "Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems," in IEEE Transactions on Knowledge and Data Engineering.
doi: 10.1109/TKDE.2021.3079836.
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[5]. G. A. Tahir and C. K. Loo, "An Open-Ended Continual Learning for Food Recognition Using Class Incremental Extreme Learning Machines," in IEEE Access, vol. 8, 2020, pp. 82328-82346, doi: 10.1109/ACCESS.2020.2991810

Abstract: This paper is part of a PhD study focusing on the creation of an object that has the ability of motion that runs on a computer, follows certain rules, entertains, communicates and reaches a specific goal of revitalising, preserving and enhancing intergeneration transfer of vast knowledge involved with artifacts, representations and instruments. Data was collected using interviews that had structured questions. The data was collected from the custodians of the Hurungwe tradition to shape the building process of the game design. This study outlined the significance of ICH and its great need to be preserved in all living generations....

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Abstract: The worldwide community has as of late become cognizant that ICH needs and merits universal guarding, setting off a legal interaction which concluded with the assembly in 2003 of the UNESCO Convention on the shielding of the Intangible Cultural Heritage. The utilization of heritage happens in different areas and takes on significance as a vehicle for political, social, and imaginative purposes, fair as teacher and emancipator, to provide a few cases. Step by step enlightening to decode heritage to comprehend its centrality to different social occasions is subsequently an imperative errand. Intangible and tangible cultural heritage has all major forms of culture tending as the best vehicle of social differences.However, little endeavours have been done to advance picture imaging in the form of panoramas......

Keywords: Intangible cultural heritage, ICT, Hurungwe Online Panorama, Local communities, Safeguarding, Transmission

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Abstract: itisshownthatthepermanentfunctionof (0,1) matricesisacompleteproblemfor the class of counting problems associated with non-deterministic polynomial time computations. Related counting problems are also considered. The reductions used are characterized by their nontrivial use of arithmetic.....

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Abstract: Cloud setting is a way of delivering hosted services over the internet. These services can include anything from setting power and data storage to software applications and development tools. Cloud setting security is a critical issue for businesses of all sizes. As more and more data is stored and processed in the cloud, it is important to take steps to protect that data from unauthorized access, disclosure, disruption, modification, or destruction. Physical security is also an important security mechanism in the cloud. Physical security measures such as access control, video surveillance, and environmental monitoring can help to protect cloud data centers from unauthorized access, theft, and damage. These are just some of the most important security mechanisms used in the cloud. By implementing these and other security measures, organizations can help to protect their cloud data from unauthorized access, theft, and misuse.

KEYWORDS: Cloud, Setting, Security, Storage

[1]. Adeel Hashmi" Cloud Computing: VM placement & Load Balancing" International Journal Of Engineering And Computer Science ISSN:2319-7242 Volume 3 Issue 11 November, 2014 Page No. 9197-9200
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Abstract: Image segmentation is the process of dividing an image into multiple segments, each of which represents a different object or region of interest. This can be done using a variety of techniques, such as thresholding, clustering, and edge detection. Image segmentation is an important step in image detection because it allows us to identify the objects in an image. Once the objects have been identified, we can then use other techniques to classify them, track them, or measure them...........

KEYWORDS: Image, Segmentation, Detection

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