AUTHENTICATION OF DIGITAL DOCUMENTS USING SECRET KEY BIOMETRIC WATERMARKING

2012 ◽  
pp. 5-11
Author(s):  
V. ANITHA ◽  
R.LEELA VELUSAMY
Keyword(s):  
Experimental Results ◽  
Direct Relation ◽  
Secret Key ◽  
Biometric Data ◽  
The Real ◽  
Digital Documents ◽  
Digital Document ◽  
Modern Era

Digital documents play a major role in modern era. They are easy to generate, modify and manage. The easy modifiable property of digital document makes it more vulnerable to forgery. It can be easily tampered or forged. So the challenge is to produce digital documents that are highly resistant to forgery and reliably confirms the real owner of the document. This can be resolved by biometric watermarking which make a direct relation between the document and its owner. A new biometric watermarking technique with secret key is proposed to digitize the authoritative documents issued by government / other organizations as a part of UID / Aadhar card project of India using biometric watermarking. Biometric code is generated from the biometric data collected from the owner of the document. The biometric code is watermarked in the document with a secret key to generate a biometric watermarked document that authenticates the real owner. Dewatermarking the document with the same key yields the biometric code that can be used for authentication of the document. If the document is tampered in any way it will be indicated in the extracted watermark. Experimental results show that 100% accuracy is obtained in authenticating the genuine documents.

scholarly journals A New Scheme for the Polynomial Based Biometric Cryptosystems

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Amioy Kumar ◽  
M. Hanmandlu ◽  
Hari M. Gupta
Keyword(s):  
Feature Extraction ◽  
Gabor Filter ◽  
Error Rates ◽  
Experimental Results ◽  
Feature Points ◽  
Secret Key ◽  
Biometric Data ◽  
Fuzzy Vault ◽  
Palm Vein ◽  
Ordered Pairs

This paper presents a new scheme for the fuzzy vault based biometric cryptosystems which explore the feasibility of a polynomial based vault for the biometric traits like iris, palm, vein, and so forth. Gabor filter is used for the feature extraction from the biometric data and the extracted feature points are transformed into Eigen spaces using Karhunen Loeve (K-L) transform. A polynomial obtained from the secret key is used to generate projections from the transformed features and the randomly generated points, known as chaff points. The points and their corresponding projections form the ordered pairs. The union of the ordered pairs from the features and the chaff points creates a fuzzy vault. At the time of decoding, matching scores are computed by comparing the stored and the claimed biometric traits, which are further tested against a predefined threshold. The number of matched scores should be greater than a tolerance value for the successful decoding of the vault. The threshold and the tolerance value are learned from the transformed features at the encoding stage and chosen according to the tradeoff in the error rates. The proposed scheme is tested on a variety of biometric databases and error rates obtained from the experimental results confirm the utility of the new scheme.

The real concept of substitution in Ayurveda literature and adulteration the misleading concept of modern era

2018 ◽  
Vol 3 (3) ◽  
Author(s):  
Ashashri Shinde ◽  
Pankaj Gupta ◽  
Sudipt Rath
Keyword(s):  
Medicinal Plant ◽  
Plant Material ◽  
Genetic Parameters ◽  
Herbal Drugs ◽  
Material Identification ◽  
The Real ◽  
Physical Chemical ◽  
Unfair Trade ◽  
Modern Era

A quality drug is central to the success of any therapeutic plan. The quality of drug is determined right from the collection to delivery to the patients. The commonest problem involving the medicinal plant stating materials is intentional or unintentional substitution and adulteration owing to multiple reasons like unavailability, higher costs, unfair trade etc. This trend was also present in the olden days, as evident from the concept of substitute drugs (Pratinidhi Dravya) as available in Yogratanakara, Bhavaprakasha and Bhaishajyaratnawali. Therefore, Charka and later Acharyas also have dealt with authentication and standardization of herbal drugs and formulations in detail by using four Pramanas (tools of knowledge) Ch.Vi.8/87. Nowadays the concept of substitution is entirely converted into intentional and unintentional malpractices of adulteration. The established authenticity parameters for plant material identification and standardization like organoleptic, physical, chemical and genetic parameters are relatively inaccessible for routine use. Not withstanding the accuracy and usefulness of these lab parameters and delay in the development of easy to perform parameters for reasonable drug authentication. These adulteration malpractices spoils the market of herbal industries. In this article we discuss about concept of substitution in ancient Ayurveda and at present intentional and unintentional adulteration practices.

scholarly journals A Multi-Resolution Approach to GAN-Based Speech Enhancement

2021 ◽  
Vol 11 (2) ◽  
pp. 721
Author(s):  
Hyung Yong Kim ◽  
Ji Won Yoon ◽  
Sung Jun Cheon ◽  
Woo Hyun Kang ◽  
Nam Soo Kim
Keyword(s):  
Speech Enhancement ◽  
Optimal Solution ◽  
Experimental Results ◽  
Generative Adversarial Networks ◽  
The Real ◽  
Multi Scale ◽  
Adversarial Networks ◽  
Speech Characteristics ◽  
Conventional Methods ◽  
Convex Property

Recently, generative adversarial networks (GANs) have been successfully applied to speech enhancement. However, there still remain two issues that need to be addressed: (1) GAN-based training is typically unstable due to its non-convex property, and (2) most of the conventional methods do not fully take advantage of the speech characteristics, which could result in a sub-optimal solution. In order to deal with these problems, we propose a progressive generator that can handle the speech in a multi-resolution fashion. Additionally, we propose a multi-scale discriminator that discriminates the real and generated speech at various sampling rates to stabilize GAN training. The proposed structure was compared with the conventional GAN-based speech enhancement algorithms using the VoiceBank-DEMAND dataset. Experimental results showed that the proposed approach can make the training faster and more stable, which improves the performance on various metrics for speech enhancement.

scholarly journals GazeEMD: Detecting Visual Intention in Gaze-Based Human-Robot Interaction

Robotics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 68
Author(s):  
Lei Shi ◽  
Cosmin Copot ◽  
Steve Vanlanduit
Keyword(s):  
Cognitive Load ◽  
Real World ◽  
Robotic Manipulator ◽  
Similarity Score ◽  
Human Robot Interaction ◽  
Experimental Results ◽  
The Other ◽  
Robot Interaction ◽  
Run Length ◽  
The Real

In gaze-based Human-Robot Interaction (HRI), it is important to determine human visual intention for interacting with robots. One typical HRI interaction scenario is that a human selects an object by gaze and a robotic manipulator will pick up the object. In this work, we propose an approach, GazeEMD, that can be used to detect whether a human is looking at an object for HRI application. We use Earth Mover’s Distance (EMD) to measure the similarity between the hypothetical gazes at objects and the actual gazes. Then, the similarity score is used to determine if the human visual intention is on the object. We compare our approach with a fixation-based method and HitScan with a run length in the scenario of selecting daily objects by gaze. Our experimental results indicate that the GazeEMD approach has higher accuracy and is more robust to noises than the other approaches. Hence, the users can lessen cognitive load by using our approach in the real-world HRI scenario.

scholarly journals وسطية الإسلام في التعامل بين الحاكم والمحكوم

2014 ◽  
Vol 9 (10) ◽  
Author(s):  
Najm Abd Rahman Khalaf
Keyword(s):  
Good Care ◽  
Problem Statement ◽  
Political Issues ◽  
Islamic History ◽  
The Real ◽  
Islamic Religion ◽  
Push And Pull ◽  
Modern Era

Islamic religion has been taking good care of political issues as well as other issues. Therefore, we can find verses in Quran about governance, judiciary and peace, with other verses about prayers, zakat and decency. All those verses can be linked together with one common link, true devotion to Almighty Allah, unity in accepting everything from Him, a righteous attemption to build life according to the best standard, similar to what have been prepared to our hereafter and for meeting our Lord. There are many verses in Quran about governance and succession, as well as managing people justly. Political sides of Islamic nation in the modern era are imponderable between push and pull, and between bickering and hypocritical. It has been identified that the moderation, balance and moderation of what Allah intended to have been lost. Hence, examples of cooperation between the ruler and the rule in Islamic history that embodied three case: 1. moderation and balance, 2. flattery and adulation, and 3. resistance and brawl. These are the major problem statement for this paper. This paper focuses on bringing back all muslims to the moderate model of politic that has been prescribed and legislated by Islamic teachings. Political issues such as the responsibilities of the ruler and his specifications, as well as the responsibilities of the followers and their obeyance, are described in this paper according to Quranic verses, Prophet's traditions, and traditions of the first three centuries of this Islamic nation, as these sources contributed to the real understanding of Islamic teaching.

scholarly journals A Systematic Analysis on the Admissibility of Digital Documents as Evidence in Malaysian Syariah Courts

2021 ◽  
Vol 29 (3) ◽  
Author(s):  
Wan Abdul Fattah Wan Ismail ◽  
Ahmad Syukran Baharuddin ◽  
Lukman Abdul Mutalib ◽  
Mohamad Aniq Aiman Alias
Keyword(s):  
Qualitative Study ◽  
Islamic Law ◽  
Systematic Analysis ◽  
The Public ◽  
Digital Documents ◽  
Digital Document ◽  
New Form ◽  
Court Proceedings ◽  
Civil Courts ◽  
The Web

Digital document is a relatively new form of evidence, particularly for use in the Malaysian Syariah courts. This scenario contrasts with civil courts, which started using digital documents in court proceedings as early as the 1950s. The use of the digital document as evidence is intended to strengthen other methods of proof further. However, the Syariah courts are still less exposed to a new proofing method because there are no specific provisions according to Islamic law to allow it. Not only that, but Syariah law practitioners are also rarely exposed to cases related to the use of digital documents. Therefore, this qualitative study will analyse the admissibility of the digital document as evidence under Islamic law through a systematic analysis. This study uses the PRISMA methodology with the range of data stored on the web at www.scopus.com and http://myjurnal.my, which brings together thousands of scientific writings worldwide. The final screening results found a total of 21 articles that discussed the practice of digital documents as evidence under Islamic law. Furthermore, from the final filter, the researchers found several works of literature that previously discussed the usage of digital documents as evidence in a trial proceeding, which indirectly shows that the Syariah court has begun to accept this type of evidence. It is expected that the results of this study will assist legal practitioners in the Syariah court and become a reference point for researchers, academics and the public in Malaysia.

Forecasting Groundwater Level Based on Relevance Vector Machine

2010 ◽  
Vol 121-122 ◽  
pp. 43-47 ◽  
Author(s):  
Li Ying Wang ◽  
Wei Guo Zhao
Keyword(s):  
Groundwater Level ◽  
Kernel Method ◽  
Nonlinear Problems ◽  
Relevance Vector Machine ◽  
Kernel Functions ◽  
Experimental Results ◽  
The Real

Relevance Vector Machine (RVM) is a novel kernel method based on sparse Bayesian, which has many advantages such as its kernel functions without the restriction of Mercer’s conditions, and the relevance vectors are automatically determined and have fewer parameters. In this paper, the RVM model is applied to forecasting groundwater level. The experimental results show the final RVM model achieved is sparser, the prediction precision is higher and the prediction values are in better agreement with the real values. It can be concluded that this technique can be seen as a very promising option to solve nonlinear problems such as forecasting groundwater level.

Semi-supervised learning for raindrop removal on a single image

2021 ◽  
pp. 1-9
Author(s):  
Juan Zhang ◽  
Wenbin Guo
Keyword(s):  
Supervised Learning ◽  
Experimental Results ◽  
Real Image ◽  
Single Image ◽  
The Real ◽  
Rainy Weather

This article propose s a network that is mainly used to deal with a single image polluted by raindrops in rainy weather to get a clean image without raindrops. In the existing solutions, most of the methods rely on paired images, that is, the rain image and the real image without rain in the same scene. However, in many cases, the paired images are difficult to obtain, which makes it impossible to apply the raindrop removal network in many scenarios. Therefore this article proposes a semi-supervised rain-removing network apply to unpaired images. The model contains two parts: a supervised network and an unsupervised network. After the model is trained, the unsupervised network does not require paired images and it can get a clean image without raindrops. In particular, our network can perform training on paired and unpaired samples. The experimental results show that the best results are achieved not only on the supervised rain-removing network, but also on the unsupervised rain-removing network.

Semantic Analysis of Bloggers Experiences as a Knowledge Source of Average Human Morality

2015 ◽  
pp. 73-95 ◽  
Author(s):  
Rafal Rzepka ◽  
Kenji Araki
Keyword(s):  
Text Mining ◽  
Knowledge Base ◽  
Real World ◽  
Semantic Analysis ◽  
Experimental Results ◽  
Artificial Agents ◽  
Knowledge Source ◽  
The Real ◽  
Long Run

This chapter introduces an approach and methods for creating a system that refers to human experiences and thoughts about these experiences in order to ethically evaluate other parties', and in a long run, its own actions. It is shown how applying text mining techniques can enrich machine's knowledge about the real world and how this knowledge could be helpful in the difficult realm of moral relativity. Possibilities of simulating empathy and applying proposed methods to various approaches are introduced together with discussion on the possibility of applying growing knowledge base to artificial agents for particular purposes, from simple housework robots to moral advisors, which could refer to millions of different experiences had by people in various cultures. The experimental results show efficiency improvements when compared to previous research and also discuss the problems with fair evaluation of moral and immoral acts.

scholarly journals Keywords-Driven and Popularity-Aware Paper Recommendation Based on Undirected Paper Citation Graph

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Hanwen Liu ◽  
Huaizhen Kou ◽  
Chao Yan ◽  
Lianyong Qi
Keyword(s):  
Recommender Systems ◽  
Recommender System ◽  
Large Scale ◽  
Real Life ◽  
Research Field ◽  
Experimental Results ◽  
The Real ◽  
Matching Technique ◽  
Paper Citation ◽  
Citation Graph

Nowadays, scholar recommender systems often recommend academic papers based on users’ personalized retrieval demands. Typically, a recommender system analyzes the keywords typed by a user and then returns his or her preferred papers, in an efficient and economic manner. In practice, one paper often contains partial keywords that a user is interested in. Therefore, the recommender system needs to return the user a set of papers that collectively covers all the queried keywords. However, existing recommender systems only use the exact keyword matching technique for recommendation decisions, while neglecting the correlation relationships among different papers. As a consequence, it may output a set of papers from multiple disciplines that are different from the user’s real research field. In view of this shortcoming, we propose a keyword-driven and popularity-aware paper recommendation approach based on an undirected paper citation graph, named PRkeyword+pop. At last, we conduct large-scale experiments on the real-life Hep-Th dataset to further demonstrate the usefulness and feasibility of PRkeyword+pop. Experimental results prove the advantages of PRkeyword+pop in searching for a set of satisfactory papers compared with other competitive approaches.

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