An adaptive watermarking scheme for e-government document images

This paper proposes an adaptive watermarking scheme for e-government document images. The adaptive scheme combines the discrete cosine transform (DCT) and the singular value decomposition (SVD) using luminance masking. As a core of masking model in the human visual system (HVS), luminance masking is implemented to improve noise sensitivity. Genetic algorithm (GA), subsequently, is employed for the optimization of the scaling factor of the masking. Involving a number of steps, the scheme proposed through this study begins by calculating the mask of the host image using luminance masking. It is then continued by transforming the mask on each area into all frequencies domain. The watermark image, following this, is embedded by modifying the singular values of DCT-transformed host image with singular values of mask coefficient of host image and the control parameter of DCT-transformed watermark image using Genetic Algorithm (GA). The use of both the singular values and the control parameter respectively, in this case, is not only to improve the sensitivity of the watermark performance but also to avoid the false positive problem. The watermark image, afterwards, is extracted from the distorted images. The experiment results show the improved adaptive performance of the proposed scheme is in resistant to several types of attacks in comparison with the previous schemes; the adaptive performance refers to the adaptive parameter of the luminance masking functioned to improve the performance or robustness of an image from any attacks.     

Exploiting Ontology for Software License Agreements

Software end-users need to sign licenses to seal an agreement with the product providers. Habitually, users agree with the license (i.e. terms and conditions) without fully understanding the agreement. To address this issue, an ontological model is developed to formulate the user requirements and license agreements formally. This paper, introduces ontological model that includes the abstract license ontology of common features found in di?erent license agreements. The abstract license ontology is then extended to a few real world license agreements. The resulting model can be used for di?erent purposes such as querying the appropriate licenses for a speciˉc requirement or checking the license terms and conditions with user requirements.     

移动自组织网中基于最优距离的概率广播方案

广播是移动Adhoc网络提供路由发现、地址解析等网络功能的一项重要操作．为了减少了泛洪广播算法中的端到端延迟,有效利用有限的带宽资源,解决广播风暴问题,文中提出了一种距离感知的广播技术,即基于最优距离的概率广播方案．本方案通过结合概率算法和距离感知来解决广播风暴问题,以高可达率和低延迟在网络中传播广播数据包．仿真结果显示与主流的泛洪算法和概率广播算法相比,本方案在可到达率、端到端延迟及重播概率等方面的性能有所提高．     

Characterization of Pheromone Blend for Grapevine Moth, Lobesia botrana by Using Flight Track Recording

The behavioral responses of Lobesia botrana males to calling females, pheromone gland extracts, and synthetic sex pheromones were recorded in a wind tunnel. Gland extracts and synthetic pheromones were released from a pheromone evaporator. The numbers of males reaching the source and their flight tracks in response to calling females and pheromone gland extracts were compared to those of synthetic blends. Upwind flights to natural sex pheromone were straighter and faster than to a three-component blend of (E)-7,(Z)-9-dodecadienyl acetate (E7,Z9–12:Ac), (E)-7,(Z)-9-dodecadien-1-ol (E7,Z9–12:OH), and (Z)-9-docecenyl acetate (Z9–12:Ac) (100:20:5). The optimum ratio of E7,Z9–12:OH and Z9–12:Ac to E7,Z9–12:Ac was found to be 5% and 1%, respectively. An additional seven compounds identified in the sex pheromone gland were investigated for their biological activity. Two unsaturated acetates, i.e., (E)-9-dodecenyl acetate (E9–12:Ac) and 11-dodecenyl acetate (11–12:Ac), increased the number of males reaching the source as well as straightness, linear velocity, and decreased the track angle of upwind flight. Optimum response was obtained by releasing 10 pg/min E7,Z9–12:Ac in a mixture with 0.5 pg/min E7,Z9–12:OH, 0.1 pg/min Z9–12:Ac, 0.1 pg/min E9– 12:Ac and 1 pg/min 11-12–Ac. The saturated acetates previously identified in the female glands were biologically inactive.     

A secure and improved multi server authentication protocol using fuzzy commitment

Multimedia Tools and Applications - The advancement in communication and computation technologies has paved a way for connecting large number of heterogeneous devices to offer specified services....     

Enhanced halftone-based secure and improved visual cryptography scheme for colour/binary Images

Visual Cryptography (VC) is gaining attraction during the past few years to secure the visual information in the transmission network. It enables the visual data i.e. handwritten notes, photos, printed text, etc. to encrypt in such a way that their decryption can be done through the human visual framework. Hence, no computational assistance is required for the decryption of the secret images they can be seen through naked eye. In this paper, a novel enhanced halftoning-based VC scheme is proposed that works for both binary and color images. Fake share is generated by the combination of random black and white pixels. The proposed algorithm consists of 3 stages i.e., detection, encryption, and decryption. Halftoning, Encryption, (2, 2) visual cryptography and the novel idea of fake share, make it even more secure and improved. As a result, it facilitates the original restored image to the authentic user, however, the one who enters the wrong password gets the combination of fake share with any real share. Both colored and black images can be processed with minimal capacity using the proposed scheme.

     

Light weight model for intra mode selection in HEVC

Multimedia Tools and Applications - The High Efficiency Video Coding (HEVC) efficiently reduces the size of the multimedia contents, but at the cost of high computation complexity. In order to make...     

KP-Rank: a semantic-based unsupervised approach for keyphrase extraction from text data

Automatic key concept identification from text is the main challenging task in information extraction, information retrieval, digital libraries, ontology learning, and text analysis. The main difficulty lies in the issues with the text data itself, such as noise in text, diversity, scale of data, context dependency and word sense ambiguity. To cope with this challenge, numerous supervised and unsupervised approaches have been devised. The existing topical clustering-based approaches for keyphrase extraction are domain dependent and overlooks semantic similarity between candidate features while extracting the topical phrases. In this paper, a semantic based unsupervised approach (KP-Rank) is proposed for keyphrase extraction. In the proposed approach, we exploited Latent Semantic Analysis (LSA) and clustering techniques and a novel frequency-based algorithm for candidate ranking is introduced which considers locality-based sentence, paragraph and section frequencies. To evaluate the performance of the proposed method, three benchmark datasets (i.e. Inspec, 500N-KPCrowed and SemEval-2010) from different domains are used. The experimental results show that overall, the KP-Rank achieved significant improvements over the existing approaches on the selected performance measures.