Optimally Embedding 3-Ary n-Cubes into Grids

This paper presents the novel multi-bit bitwise adaptive embedding algorithms for data hiding. These embedding algorithms can embed multi-bit (k-bit, k>=1 ) secret data into cover data only introduce minimum embedding error smaller than (2^(k-1)-1)*2^(i-k) according to the embedding location i. To achieve such a goal, the proposed embedding algorithm adaptively evaluates the most similar value to replace the original one and which can be divided into three steps: (1) embed logo data into cover data, (2) adaptively adjust the least-significant bits (LSBs) of cover data, and (3) adaptively adjust the maximum-significant bits (MSBs) of cover data. The proposed embedding algorithms are not only achieving minimum error but also suitable to hardware implementation due to it is based on logic, algebraic, and bit operations. Many simulations show that the proposed embedding algorithms perform good embedding quality for watermarking and steganography applications.

This paper presents the novel multi-bit watermarking using adaptive embedding algorithms with minimum error. These embedding algorithms can embed multi-bit (k-bit, k≥1 ) logo data into cover data only introduce minimum embedding errors which are restricted to ±(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k-1</sup> -1)2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i-k</sup> according to the embedding location i. To achieve the goal of minimum embedding error, we introduced the adaptive embedding algorithms to adaptively evaluate the most similar value to replace the original one and which can be divided into three steps: (1) embed logo data into cover data, (2) adaptively adjust the least-significant bits (LSBs) of cover data, and (3) adaptively adjust the maximum-significant bits (MSBs) of cover data. Thus, we called them as adaptive 3-step embedding algorithms. The proposed embedding algorithms are not only achieving minimum error but also suitable to hardware implementation due to they are bit wise and based on logic, arithmetic and bit operations. Many simulations show that the proposed adaptive 3-step embedding algorithms perform good embedding quality for watermarking applications.

The wirelength is one of the key parameters of the quality of embedding graphs into host graphs. To our knowledge, no results for computing the wirelength of embedding irregular graphs into irregular graphs are known in the literature. We develop an algorithm that determines the wirelength of embedding of the Turán graph $T(\ell, 2^p)$, where $2^{n-1} \leq \ell &lt; 2^{n}$ and $1\le p\le \lceil \log_2 \ell\rceil\leq n$, into the incomplete hypercube $I^{\ell}_{n}$. Incomplete hypercubes form an important generalization of hypercubes because they eliminate the restriction on the number of nodes in a system.

g-Good-neighbor conditional diagnosability measures for 3-ary n-cube networks

Medical images are more typical than any other ordinary images, since it stores patient’s information for diagnosis purpose. Such images need more security and confidentiality as total diagnosis depends on it. In telemedicine applications, transmission of medical image via open channel, demands strong security and copyright protection. In our proposed robust watermarking model, a double layer security is introduced to ensure the robustness of embedded data. The embedded data is scrambled using a unique key and then a transform domain based hybrid watermarking technique is used to embed the scrambled data into the transform coefficients of the host image. The data embedding in medical images involves more attention, so that the diagnosis part must not be affected by any modification. Therefore, Support Vector Machine (SVM) is used as a classifier, which classify a medical image into two regions i.e. Non Region of Interest (NROI) and Region of Interest (ROI) to embed watermark data into the NROI part of the medical image, using the proposed embedding algorithm. The objective of the proposed model is to avoid any quality degradation to the medical image. The simulation is performed to measure the Peak Signal to Noise Ratio (PSNR) for imperceptibility and Structural Similarity Index (SSIM) to test the robustness. The experimented result shows, robustness and imperceptibility with SSIM of more than 0.50 and PSNR of more than 35 dB for proposed watermarking model.

The incrementally extensible hypercube (IEH) graph is a generalization of binary hypercube networks in that the number of nodes can be arbitrary in contrast to a strict power of 2. In this paper, the authors present an efficient model to fulfill the embedding of a full binary tree into a full IEH graph. As the model the authors proposed, an algorithm is developed for the embedding with expansion 1, load 1, congestion 2, and dilation 2. Moreover, the embedding algorithm can be also applied into hypercubes with one faulty node.

Hamiltonian cycle and path embeddings in 3-ary [formula omitted]-cubes based on [formula omitted]-structure faults

A novel negative feedback information dissemination model based on online social network

In Cyber-Physical Networked Systems (CPNS), attackers could inject false measurements to the controller through compromised sensor nodes, which not only threaten the security of the system, but also consumes network resources. To deal with this issue, a number of en-route filtering schemes have been designed for wireless sensor networks. However, these schemes either lack resilience to the number of compromised nodes or depend on the statically configured routes and node localization, which are not suitable for CPNS. In this paper, we propose a Polynomial-based Compromised-Resilient En-route Filtering scheme (PCREF), which can filter false injected data effectively and achieve a high resilience to the number of compromised nodes without relying on static routes and node localization. Particularly, PCREF adopts polynomials instead of MACs (message authentication codes) for endorsing measurement reports to achieve the resilience to attacks. Each node stores two types of polynomials: authentication polynomial and check polynomial derived from the primitive polynomial, and used for endorsing and verifying the measurement reports. Via extensive theoretical analysis and simulation experiments, our data show that PCREF achieves better filtering capacity and resilience to the large number of compromised nodes in comparison to the existing schemes.

Distances on merge trees facilitate visual comparison of collections of scalar fields. Two desirable properties for these distances to exhibit are 1) the ability to discern between scalar fields which other, less complex topological summaries cannot and 2) to still be robust to perturbations in the dataset. The combination of these two properties, known respectively as stability and discriminativity, has led to theoretical distances which are either thought to be or shown to be computationally complex and thus their implementations have been scarce. In order to design similarity measures on merge trees which are computationally feasible for more complex merge trees, many researchers have elected to loosen the restrictions on at least one of these two properties. The question still remains, however, if there are practical situations where trading these desirable properties is necessary. Here we construct a distance between merge trees which is designed to retain both discriminativity and stability. While our approach can be expensive for large merge trees, we illustrate its use in a setting where the number of nodes is small. This setting can be made more practical since we also provide a proof that persistence simplification increases the outputted distance by at most half of the simplified value. We demonstrate our distance measure on applications in shape comparison and on detection of periodicity in the von Kármán vortex street.

We formally specify the data link layer of the Controller Area Network (CAN), a high-speed serial bus system with real-time capabilities, widely used in embedded systems. CAN's primary application domain is automotive, and the physical and data link layers of the CAN architecture were the subject of the ISO 11898 international standard. We checked our specification against 12 important properties of CAN, eight of which are gleaned from the ISO standard; the other four are desirable properties not directly mentioned in the standard. Our results indicate that not all properties can be expected to hold of a CAN implementation and we discuss the implications of these findings. Moreover, we have conducted a number of experiments aimed at determining how the size of the protocol's state space is affected by the introduction of various features of the data link layer, the number of nodes in the network the number of distinct message types, and other parameters.

Pagoda[5]arene (P5), which is composed of five 2,6-dimethoxylanthracene (2,6-DMA) subunits bridged by methylene groups at 1,5 positions, was conveniently synthesized in 43% by trifluoroacetic acid ...

Internet of Things (IoT) devices and services have become increasingly ubiquitous in recent years as they greatly facilitate our daily life. To promote IoT data and semantic interoperability, we propose an edge–cloud framework. The edge end is responsible for handling customized data processing tasks and transferring the processed data, while the cloud end deals with semantic information processing. Additionally, we present an entity tree embedding algorithm at the cloud end to convert IoT entities and attributes into embedding vectors in a tree-structured way. Consequently, entity embeddings could reflect the semantic information at both Class and Property levels, which ameliorates our previous entity embedding method, leading to better embedding results and clustering effects. Finally, the entity tree embedding algorithm and the corresponding compression algorithm are evaluated. Results indicate that the Whitening algorithm is the best method to compress embedding vectors. More importantly, the entity tree embedding algorithm captures both the semantic and structural information of entities and attributes. Additionally, the clustering experiments show that the proposed embedding algorithm achieves better clustering results compared with the original entity embeddings and the uncompressed averaging method.

Stochastic configuration network (SCN) is a powerful prediction model whose performance is significantly influenced by the configuration of the network parameters. To improve the prediction accuracy of the network, a cooperative stochastic configuration network (CSCN) based on a novel differential evolutionary sparrow search algorithm (DESSA), termed as DESSA-CSCN, is proposed. In the CSCN, the number of hidden layer nodes is adaptively adjusted according to the number of iterations, and the parameters of hidden nodes are cooperatively optimized by using a population-based metaheuristic algorithm. A sparse matrix is introduced to mitigate parameter overfitting caused by the increased number of hidden layer nodes. During parameter optimization, the fitness function is constructed by using the supervision mechanism of the SCN, and the DESSA is utilized as the metaheuristic algorithm to update the weights and biases. In order to verify the effectiveness of the DESSA-CSCN, several simulation experiments have been conducted. The performance of the DESSA is evaluated by the CEC2017 test suit, and the simulation results show that the DESSA exhibits better convergence accuracy and can jump out of local optima more effectively than other algorithms. The performance of the DESSA-CSCN is evaluated by 4 datasets from KEEL, and the simulation results indicate that the DESSA-CSCN achieves better prediction accuracy and faster prediction speed than other models.

With the rapid development of blockchain technology, it shows great potential in data owner rights protection and digital identity management. In this study, a shared rights protection system for data owners and a digital identity management system were constructed using the blockchain architecture system, combined with cryptography technology. Additionally, the functional module design is implemented for both groups of systems, and the performance of the data owner rights protection system and digital identity management system is verified through simulation experiments. The throughput of the PBFT consensus algorithm used in this paper’s entitlement protection system is 1281, 1319, 1205, 1348, and 1346 in order when the number of nodes is 10, 20, 30, 40, and 50.The entitlement protection system proposed in this paper is tested on trusted preprocessing, audit file encryption, audit cipher uploading, audit cipher downloading, audit file decrypting, and trusted root verification. 150 times with an average time consumption (ms) of 6.50, 460.43, 28.99, 37.43, 240.09, and 6.47, respectively. In addition, the proposed digital identity management system has a less average time consumption for individual credential issuance. The time consumption of this system in the authentication phase is 0~163.71ms faster than the comparison system and it can improve the security of the management system by using multi-signature technique.