Smart-Fragile Authentication Scheme for Robust Detecting of Tampering Attacks on English Text

Content authentication, integrity verification, and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication technology. In this paper, a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking (SFASCDW) is proposed for content authentication and tampering detection of English text. A first-level order of alphanumeric mechanism, based on hidden Markov model, is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed approach. The researcher uses the first-level order and alphanumeric mechanism of Markov model as a soft computing technique to analyze English text. Moreover, he extracts the features of the interrelationship among the contexts of the text, utilizes the extracted features as watermark information, and validates it later with the studied English text to detect any tampering. SFASCDW has been implemented using PHP with VS code IDE. The robustness, effectiveness, and applicability of SFASCDW are proved with experiments involving four datasets of various lengths in random locations using the three common attacks, namely insertion, reorder, and deletion. The SFASCDW was found to be effective and could be applicable in detecting any possible tampering.     

A Hybrid Intelligent Approach for Content Authentication and Tampering Detection of Arabic Text Transmitted via Internet

In this paper, a hybrid intelligent text zero-watermarking approach has been proposed by integrating text zero-watermarking and hidden Markov model as natural language processing techniques for the content authentication and tampering detection of Arabic text contents. The proposed approach known as Second order of Alphanumeric Mechanism of Markov model and Zero-Watermarking Approach (SAMMZWA). Second level order of alphanumeric mechanism based on hidden Markov model is integrated with text zero-watermarking techniques to improve the overall performance and tampering detection accuracy of the proposed approach. The SAMMZWA approach embeds and detects the watermark logically without altering the original text document. The extracted features are used as a watermark information and integrated with digital zero-watermarking techniques. To detect eventual tampering, SAMMZWA has been implemented and validated with attacked Arabic text. Experiments were performed on four datasets of varying lengths under multiple random locations of insertion, reorder and deletion attacks. The experimental results show that our method is more sensitive for all kinds of tampering attacks with high level accuracy of tampering detection than compared methods.     

A Smart English Text Zero-Watermarking Approach Based on Third-Level Order and Word Mechanism of Markov Model

Text information is principally dependent on the natural languages. Therefore, improving security and reliability of text information exchanged via internet network has become the most difficult challenge that researchers encounter. Content authentication and tampering detection of digital contents have become a major concern in the area of communication and information exchange via the Internet. In this paper, an intelligent text Zero-Watermarking approach SETZWMWMM (Smart English Text Zero-Watermarking Approach Based on Mid-Level Order and Word Mechanism of Markov Model) has been proposed for the content authentication and tampering detection of English text contents. The SETZWMWMM approach embeds and detects the watermark logically without altering the original English text document. Based on Hidden Markov Model (HMM), Third level order of word mechanism is used to analyze the interrelationship between contexts of given English texts. The extracted features are used as a watermark information and integrated with digital zero-watermarking techniques. To detect eventual tampering, SETZWMWMM has been implemented and validated with attacked English text. Experiments were performed on four datasets of varying lengths under multiple random locations of insertion, reorder and deletion attacks. The experimental results show that our method is more sensitive and efficient for all kinds of tampering attacks with high level accuracy of tampering detection than compared methods.     

基于贪心EM算法的HMRF遥感影像变化检测

提出一种基于贪心EM算法的HMRF遥感影像变化检测算法.该算法采取PCA与差值法相结合的方式来构造差分影像.首先,采用隐马尔可夫随机场( Hidden Markov Random Field,HMRF)模型描述空间上下文信息,并构造系统能量函数;然后,利用贪心EM算法克服EM算法假定混合成分数为已知、迭代结果过分依赖初...     

The State of the Art of Hidden Markov Models for Predictive Maintenance of Diesel Engines

The maintenance of diesel Engines is usually scheduled according to the maintenance procedures defined by manufacturers. However, the state of the art shows that the condition monitoring maintenance associated with adequate prediction algorithms allows performance improvement both by increasing the intervals between interventions and by helping to maintain reliability levels. There are many types of variables that can be used to measure equipment condition, as is the case of several types of pollutant emissions such as NO_x, CO2, HC, PM, and NOISE, among others. This is a typical problem that can be solved through a hidden Markov model, taking into account the specificity of this type of equipment. The paper describes two algorithms that can help to increase the quality of assessment of engine states and the efficiency of maintenance planning. Those are the Viterbi and Baum–Welch algorithms. The importance of how to calculate the performance index of the model by the use of the perplexity algorithm is also emphasized. In this paper, a new paradigm is proposed, designated as ecological predictive maintenance. Copyright © 2017 John Wiley & Sons, Ltd.     

Fault diagnosis method for an Aeroengine Based on Independent Component Analysis and the Discrete Hidden Markov Model

The vibration signals of an aeroengine are a very important information source for fault diagnosis and condition monitoring. Considering the nonstationarity and low repeatability of the vibration signals, it is necessary to find a corresponding method for feature extraction and fault recognition. In this paper, based on Independent Component Analysis (ICA) and the Discrete Hidden Markov Model (DHMM), a new fault diagnosis approach named ICA-DHMM is proposed. In this method, ICA separates the source signals ...     

A Hybrid Algorithm for the Reliability Evaluation Models of Chemical Systems

Chemical processes are complex dynamic systems. With the chemical industry under pressure to introduce improvements through the greater use of automation and intelligence, the need for comprehensive reliability evaluation has become more urgent both theoretically and practically. The employment of intelligent algorithms based on factory data has been the recent research hotspots. But for complex systems with available data on a smaller scale, reliability evaluation models have suffered on such problems as a result of instability and over‐fitting, which have to be resolved. The GRA–GA–BP–MCRC hybrid algorithm was proposed. It combined the two‐step genetic algorithm (GA)–back propagation (BP) and grey relational analysis (GRA) with Markov chain residual correction (MCRC). Based on the technical characteristics and the management demands, 46 influential factors of process reliability were introduced, which covered man, machine, material, method, and environment. For model convergence to be assured, GRA and attribute reduction rule were introduced. Meanwhile, based on the correlation of the factors, the two‐step GA–BP was proposed to resolve the over‐fitting problem of artificial neural network with complex input parameters. As well, MCRC was applied to modify the GA–BP error. The resulting average relative error of the hybrid algorithm was 2.36%, while the conventional algorithm was 10.28%. Copyright © 2016 John Wiley & Sons, Ltd.     

采用马氏模型的点状动目标快速检测方法

提出了一种视频序列图像中点状运动目标三维快速检测方法。该方法利用目标运动的时域连续性假设,将目标在相邻多帧上的位置状态模型化为二阶马尔可夫数据链;依照该模型采用沿轨迹集成的检测算法,克服了传统三维检测造成搜索次数巨大的弱点,同时也避免了二维投影检测带来的信噪比下降。理论分析和仿真试验表明,该检测方法能稳定地检测出信号杂波噪声比（SCNR）超过3的缓动点状运动目标,而且在采用5帧集成时计算量比传统的穷尽轨迹匹配检测减少100倍。     

一种基于YOLOv3算法的3D打印点阵结构缺陷识别方法

针对3D打印点阵结构中缺陷目标因尺寸小、缺陷特征微弱而难以准确自动识别的问题,提出了一种基于YOLOv3算法的点阵结构缺陷智能识别新方法.该方法利用深度学习网络模型在特征提取方面的优势,采用多尺度网络进行预测,将缺陷的分类和定位问题作为回归问题处理.实验结果表明,所提算法实现了一种3D打印点阵结构内部典型缺陷的识别,缺...     

Hidden Markov model-based approach for generation of Pitman shorthand language symbols for consonants and vowels from spoken english

Pitman shorthand language (PSL) is a widely practised medium for transcribing/recording speech to text (StT) in English. This recording medium continues to exist in spite of considerable development in speech processing systems (SPS), because of its ability to record spoken/dictated text at high speeds of more than 120 words per minute. Hence, scope exists for exploiting this potential of PSL in present SPS. In this paper, an approach for feature extraction using Mel frequency cepstral coefficients (MFCC) and classification using hidden Markov models (HMM) for generating strokes comprising consonants and vowels (CV) in the process of production of Pitman shorthand language from spoken English is proposed. The proposed method is tested on a large number of samples, drawn from different speakers and the results are encouraging. The work is useful in total automation of PSL processing.     

Safety analysis of safety-critical systems for their applicability on NPP systems: A state-of-the-art review

Since any risk in the safety-critical systems (SCSs) might lead to a terrible disaster, the utmost quality attribute of these systems is safety. Researchers are putting their efforts to ensure the safety of such systems. This paper summarizes the state-of-the-art in the area of the safety attribute of such critical systems. The in depth literature survey is performed to explore the several methods/models used for safety analysis of the SCS. The limitations of such methods are also shown regarding their applicability in SCS of the nuclear power plant (NPP). We also propose a framework to perform safety analysis, which can deal with these limitations and demonstrated the approach on a case study of NPP. Further, the direction for future work is advised to extend the further scope of research based on the case study.     

分段切换模型参数寻优的车道检测算法

车道检测算法的研究是智能车辆基于道路标识线或边界信息自主导航的首要环节。根据道路先验知识和驾驶员视觉处理经验,将道路图像分为近景和远景区域,近景区使用直线模型拟合车道线,远景区切换直线模型或三次曲线模型匹配车道线。融合道路图像的梯度幅值、梯度方向和灰度特征信息,建立概率判别函数,采用基于遗传算法操作的改进粒子群优化算法,快速搜索关于概率函数的最优模型参数,实现对车道的检测。对实际道路图像的试验结果表明,在路面存在阴影、光照不均匀、车辆遮挡以及车道标识线污损情况下,该算法都能很好地识别车道,具有很强的鲁棒性。     

Structure Preserving Algorithm for Fractional Order Mathematical Model of COVID-19

In this article, a brief biological structure and some basic properties of COVID-19 are described. A classical integer order model is modified and converted into a fractional order model with as order of the fractional derivative. Moreover, a valued structure preserving the numerical design, coined as Grunwald–Letnikov non-standard finite difference scheme, is developed for the fractional COVID-19 model. Taking into account the importance of the positivity and boundedness of the state variables, some productive results have been proved to ensure these essential features. Stability of the model at a corona free and a corona existing equilibrium points is investigated on the basis of Eigen values. The Routh–Hurwitz criterion is applied for the local stability analysis. An appropriate example with fitted and estimated set of parametric values is presented for the simulations. Graphical solutions are displayed for the chosen values of (fractional order of the derivatives). The role of quarantined policy is also determined gradually to highlight its significance and relevancy in controlling infectious diseases. In the end, outcomes of the study are presented.