Step Pyramid Distribution for Prime Numbers

In this document, we will present a new way to visualize the distribution of Prime Numbers in the number system to spot Prime numbers in a subset of numbers using a simpler algorithm. Then we will look throw a classification algorithm to check if a number is prime using only 7 simple arithmetic operations with an algorithm complexity less than or equal to O (7) operations for any number.

A note on the high-dimensional sparse Fourier transform in the continuous setting

In this paper, we theoretically propose a new hashing scheme to establish the sparse Fourier transform in high-dimension space. The estimation of the algorithm complexity shows that this sparse Fourier transform can overcome the curse of dimensionality. To the best of our knowledge, this is the first polynomial-time algorithm to recover the high-dimensional continuous frequencies.

A Method of CT Image Denoising Based on Residual Encoder-Decoder Network

Low-dose computed tomography (CT) has proved effective in lowering radiation risk for the patients, but the resultant noise and bar artifacts in CT images can be a disturbance for medical diagnosis. The difficulty of modeling statistical features in the image domain makes it impossible for the existing methods that directly process reconstructed images to maintain the detailed texture structure of images while reducing noise, which accounts for the failure in CT diagnostic images in practical application. To overcome this defect, this paper proposes a CT image-denoising method based on an improved residual encoder-decoder network. Firstly, in our approach, the notion of recursion is integrated into the original residual encoder-decoder network to lower the algorithm complexity and boost efficiency in image denoising. The original CT images and the postrecursion result graph output after recursion are used as the input for the next recursion simultaneously, and the shallow encoder-decoder network is recycled. Secondly, the root-mean-square error loss function and perceptual loss function are introduced to ensure the texture of denoised CT images. On this basis, the tissue processing technology based on clustering segmentation is optimized considering that the images after improved RED-CNN training will still have certain artifacts. Finally, the experimental results of the TCGA-COAD clinical data set show that under the same experimental conditions, our method outperforms WGAN in average postdenoising PSNR and SSIM of CT images. Moreover, with a lower algorithm complexity and shorter execution time, our method is a significant improvement on RED-CNN and is applicable for actual scenarios.

Method to Increase Dependability in a Cloud-Fog-Edge Environment

Robots can be very different, from humanoids to intelligent self-driving cars or just IoT systems that collect and process local sensors’ information. This paper presents a way to increase dependability for information exchange and processing in systems with Cloud-Fog-Edge architectures. In an ideal interconnected world, the recognized and registered robots must be able to communicate with each other if they are close enough, or through the Fog access points without overloading the Cloud. In essence, the presented work addresses the Edge area and how the devices can communicate in a safe and secure environment using cryptographic methods for structured systems. The presented work emphasizes the importance of security in a system’s dependability and offers a communication mechanism for several robots without overburdening the Cloud. This solution is ideal to be used where various monitoring and control aspects demand extra degrees of safety. The extra private keys employed by this procedure further enhance algorithm complexity, limiting the probability that the method may be broken by brute force or systemic attacks.

Video transaction algorithm considering FISCO alliance chain and improved trusted computing

With the advent of the era of self media, the demand for video trading is becoming more and more obvious. Alliance blockchain has the characteristics of traceable transaction records, tamper proof transaction records, decentralized transactions and faster transaction speed than public chains. These features make it a trading platform. Trusted computing can solve the problem of non Byzantine attack in the aspect of hardware. This paper proposes a video transaction algorithm considering FISCO alliance chain and improved trusted computing. First, an improved trusted computing algorithm is used to prepare a trusted transaction environment. Second, the video summary information extraction algorithm is used to extract the summary information that can uniquely identify the video. Finally, based on the video transactions algorithm of FISCO alliance chain, the video summary information is traded on the chain. Experimental results show that the proposed algorithm is efficient and robust for video transactions. At the same time, the algorithm has low computational power requirements and algorithm complexity, which can provide technical support for provincial and county financial media centers and relevant media departments.

Improving the Lifetime of an Out-Patient Implanted Medical Device Using a Novel Flower Pollination-Based Optimization Algorithm in WBAN Systems

The new inventions in health care devices have led to a considerable increase in the human lifespan. Miniaturized bio-sensing elements and dedicated wireless communication bands have led to the development of a new arena called Wireless Body Area Network (WBAN) (IEEE 802.11.6). These Implantable Medical Devices (IMDs) are used for monitoring a chronic patient’s medical condition as well as therapeutic and life-saving functions. The aim of this study is to improve the dynamic channel selection algorithm for an increased Out Patient-Body Network Controller (OP-BNC) medical device during visits to the hospital. There is a fixed number of licensed spectra allocated to the In Patient-Body Network Controller (IP-BNC) and Out-Patient Body Network Controller (OP-BNC). When there is an increase in the OP-BNC, there is an availability of idle spectrum in the IP-BNC. An existing rank-based algorithm is used in the allocation of idle spectrum to the increased OP-BNC. This ranking method takes more time for the processing and selection of an idle channel to the registered user. To avoid it, we proposed an EFPOC model to select from the free idle channels of the IP-BNC licensed spectrum. We also discussed the algorithm complexity of the proposed Enhanced Flower Pollination-based Optimized Channel selection (EFPOC) algorithm and obtained a complexity of O(n2), which is a significant improvement over the existing algorithm rank-based algorithm complexity. Our experimental result shows that the proposed EFPOC algorithm improves the Tier-2 systems lifetime by 46.47%. Then, to prove that the proposed model is time efficient in channel selection, a simulated experimented is conducted. When selecting a number of channels from a Look-Up Table (LUT), the proposed EFPOC method takes 25% less time than the existing algorithms.

A Privacy-Preserving Trajectory Publication Method Based on Secure Start-Points and End-Points

By judging whether the start-point and end-point of a trajectory conform to the user’s behavioral habits, an attacker who possesses background knowledge can breach the anonymous trajectory. Traditional trajectory privacy preservation schemes often generate an anonymous set of trajectories without considering the security of the trajectory start- and end-points. To address this problem, this paper proposes a privacy-preserving trajectory publication method based on generating secure start- and end-points. First, a candidate set containing a secure start-point and end-point is generated according to the user’s habits. Second, k−1 anonymous trajectories are generated bidirectionally according to that secure candidate set. Finally, accessibility corrections are made for each anonymous trajectory. This method integrates features such as local geographic reachability and trajectory similarity when generating an anonymized set of trajectories. This provides users with privacy preservation at the k-anonymity level, without relying on the trusted third parties and with low algorithm complexity. Compared with existing methods such as trajectory rotation and unidirectional generation, theoretical analysis and experimental results on the datasets of real trajectories show that the anonymous trajectories generated by the proposed method can ensure the security of trajectory privacy while maintaining a higher trajectory similarity.