Implementation and Optimization of Image Processing on the Map of SABRE i.MX_6

Vision relieves humans to understand the environmental deviations over a period. These deviations are seen by capturing the images. The digital image plays a dynamic role in everyday life. One of the processes of optimizing the details of an image whilst removing the random noise is image denoising. It is a well-explored research topic in the field of image processing. In the past, the progress made in image denoising has advanced from the improved modeling of digital images. Hence, the major challenges of the image process denoising algorithm is to advance the visual appearance whilst preserving the other details of the real image. Significant research today focuses on wavelet-based denoising methods. This research paper presents a new approach to understand the Sobel imaging process algorithm on the Linux platform and develop an effective algorithm by using different optimization techniques on SABRE i.MX_6. Our work concentrated more on the image process algorithm optimization. By using the OpenCV environment, this paper is intended to simulate a Salt and Pepper noisy phenomenon and remove the noisy pixels by using Median Filter Algorithm. The Sobel convolution method included and used in the design of a Sobel Filter and then process the image following the median filter, to achieve an effective edge detection result. Finally, this paper optimizes the algorithm on SABRE i.MX_6 Linux environment. By using algorithmic optimization (lower complexity algorithm in the mathematical sense, using appropriate data structures), optimization for RISC (loop unrolling) processors, including optimization for efficient use of hardware resources (access to data, cache management and multi-thread), this paper analyzed the different response parameters of the system with varied inputs, different compiler options (O1, O2, or O3), and different doping degrees. The proposed denoising algorithm shows the meaningful addition of the visual quality of the images and the algorithmic optimization assessment.

Energy-Saving D2D Wireless Networking Based on ACO and AIA Fusion Algorithm

Lower energy consumption and higher data rate have been becoming the key factors of modern wireless mobile communication for the improvement of user experiences. At present, the commercialization of 5G communications is gradually promoting the development of Internet of things (IoT) techniques. Due to the limited coverage capability of direct wireless communications, the indirect device-to-device (D2D) communications using information relay, in addition to the single 5G base station deployment, have been introduced. Along with the increase of information nodes, the relay devices have to undertake the nonnegligible extra data traffic. In order to adjust and optimize the information routing in D2D services, we present an algorithmic investigation referring to the ant colony optimization (ACO) algorithm and the artificial immune algorithm (AIA). By analyzing the characteristics of these algorithms, we propose a combined algorithm that enables the improved the iterative convergence speed and the calculation robustness of routing path determination. Meanwhile, the D2D optimization pursuing energy saving is numerically demonstrated to be improved than the original algorithms. Based on the simulation results under a typical architecture of 5G cellular network including various information nodes (devices), we show that the algorithmic optimization of D2D routing is potentially valid for the realization of primitive wireless IoT networks.

Secure Air Traffic Control at the Hub of Multiplexing on the Centrifugo-Pneumatic Lab-On-a-Disc Platform

Fluidic larger-scale integration (LSI) resides at the heart of comprehensive sample-to-answer automation and parallelization of assay panels for frequent and ubiquitous bioanalytical testing in decentralized point-of-use/point-of-care settings. This paper develops a novel “digital twin” strategy with an emphasis on rotational, centrifugo-pneumatic flow control. The underlying model systematically connects retention rates of rotationally actuated valves as a key element of LSI to experimental input parameters; for the first time, the concept of band widths in frequency space as the decisive quantity characterizing operational robustness is introduced, a set of quantitative performance metrics guiding algorithmic optimization of disc layouts is defined, and the engineering principles of advanced, logical flow control and timing are elucidated. Overall, the digital twin enables efficient design for automating multiplexed bioassay protocols on such “Lab-on-a-Disc” (LoaD) systems featuring high packing density, reliability, configurability, modularity, and manufacturability to eventually minimize cost, time, and risk of development and production.

Secure Air Traffic Control at the Hub of Multiplexing on the Centrifugo-Pneumatic Lab-on-a-Disc Platform

Fluidic larger-scale integration (LSI) resides at the heart of comprehensive sample-to-answer automation and parallelization of assay panels for frequent and ubiquitous bioanalytical testing in decentralized the point-of-use / point-of-care settings. This paper develops a novel “digital twin” strategy with an emphasis on rotational, centrifugo-pneumatic flow control. The underlying model systematically connects retention rates of rotationally actuated valves as a key element of LSI to experimental input parameters; for the first time, the concept of band widths in frequency space as the decisive quantity characterizing operationally robustness is introduced, a set of quantitative performance metrics guiding algorithmic optimization of disc layouts is defined, and the engineering principles of advanced, logical flow control and timing are elucidated. Overall, the digital twin enables efficient design for automating multiplexed bioassay protocols on such “Lab-on-a-Disc” (LoaD) systems featuring high packing density, reliability, configurability, modularity and manufacturability to eventually minimize cost, time and risk of development and production.

V-DaT: A Robust method for Vehicle Detection and Tracking

Vision-based traffic surveillance has been one of the most promising fields for improvement and research. Still, many challenging problems remain unsolved, such as addressing vehicle occlusions and reducing false detection. In this work, a method for vehicle detection and tracking is proposed. The proposed model considers background subtraction concept for moving vehicle detection but unlike conventional approaches, here numerous algorithmic optimization approaches have been applied such as multi-directional filtering and fusion based background subtraction, thresholding, directional filtering and morphological operations for moving vehicle detection. In addition, blob analysis and adaptive bounding box is used for Detection and Tracking. The Performance of Proposed work is measured on Standard Dataset and results are encouraging.

Algorithmic Optimization of the Calculation with the Consideration of the Interconnection of the Basic Economic Parameters of the Flight Route of the Model Air Carrier

The load factor is the determining factor for airlines in economic terms and the prediction of the future development of the flight route. The combination of load factor and break-even point provides the airline with a comprehensive picture of the business of the flight route and the optimization of pricing for the flight route. The purpose of the article is to propose and adapt the development of air transport prices on a given line using maximally recalculated values and maximize profit. The optimized calculation algorithm then facilitates the understanding of the individual steps of the load factor calculation and the monitoring of price development by means of the chi-square mathematical method by which we observed the interconnection of the ticket price and the load factor. To describe the problem, we chose the Bratislava – Larnaca route.

Mechanical model of muscle contraction 2. Kinematic and dynamic aspects of a myosin II head during the working stroke

The condition of a myosin II head during which force and movement are generated is commonly referred to as Working Stroke (WS). During the WS, the myosin head is mechanically modelled by 3 two by two articulated segments, the motor domain (S1a) strongly fixed to an actin molecule, the lever (S1b) on which a motor moment is exerted, and the rod (S2) pulling the myosin filament (Mfil). When the half-sarcomere (hs) is shortened or lengthened by a few nanometers, it is assumed that the lever of a myosin head in WS state moves in a fixed plane including the longitudinal axis of the actin filament (Afil). As a result, the 5 rigid segments, i.e. Afil, S1a, S1b, S2 and Mfil, follow deterministic and configurable trajectories. The orientation of S1b in the fixed plane is characterized by the angle θ. After deriving the geometric equations singularizing the WS state, we obtain an analytical relationship between the hs shortening velocity (u) and the angular velocity of the lever . The principles of classical mechanics applied to the 3 solids, S1a, S1b and S2, lead to a relationship between the motor moment exerted on the lever (MB) and the tangential force dragging the actin filament (TA). We distinguish θup and θdown, the two boundaries framing the angle θ during the WS, relating to up and down conformations. With the usual data assigned to the cross-bridge elements, a linearization procedure of the relationships between u and , on the one hand, and between MB and TA, on the other hand, is performed. This algorithmic optimization leads to theoretical values of θup and θdown equal to +28° (−28°) and −42° (+42°) respectively with a variability of ±5° in a hs on the right (left), data in accordance with the commonly accepted experimental values for vertebrate muscle fibers.