Multi-Scale Memetic Image Registration

Many technological applications of our time rely on images captured by multiple cameras. Such applications include the detection and recognition of objects in captured images, the tracking of objects and analysis of their motion, and the detection of changes in appearance. The alignment of images captured at different times and/or from different angles is a key processing step in these applications. One of the most challenging tasks is to develop fast algorithms to accurately align images perturbed by various types of transformations. The paper reports a new method used to register images in the case of geometric perturbations that include rotations, translations, and non-uniform scaling. The input images can be monochrome or colored, and they are preprocessed by a noise-insensitive edge detector to obtain binarized versions. Isotropic scaling transformations are used to compute multi-scale representations of the binarized inputs. The algorithm is of memetic type and exploits the fact that the computation carried out in reduced representations usually produces promising initial solutions very fast. The proposed method combines bio-inspired and evolutionary computation techniques with clustered search and implements a procedure specially tailored to address the premature convergence issue in various scaled representations. A long series of tests on perturbed images were performed, evidencing the efficiency of our memetic multi-scale approach. In addition, a comparative analysis has proved that the proposed algorithm outperforms some well-known registration procedures both in terms of accuracy and runtime.

Semantic Conceptual Framework for Environmental Monitoring and Surveillance—A Case Study on Forest Fire Video Monitoring and Surveillance

This paper presents a semantic conceptual framework and definition of environmental monitoring and surveillance and demonstrates an ontology implementation of the framework. This framework is defined in a mathematical formulation and is built upon and focused on the notation of observation systems. This formulation is utilized in the analysis of the observation system. Three taxonomies are presented, namely, the taxonomy of (1) the sampling method, (2) the value format and (3) the functionality. The definition of concepts and their relationships in the conceptual framework clarifies the task of querying for information related to the state of the environment or conditions related to specific events. This framework aims to make the observation system more queryable and therefore more interactive for users or other systems. Using the proposed semantic conceptual framework, we derive definitions of the distinguished tasks of monitoring and surveillance. Monitoring is focused on the continuous assessment of an environment state and surveillance is focused on the collection of all data relevant for specific events. The proposed mathematical formulation is implemented in the format of the computer readable ontology. The presented ontology provides a general framework for the semantic retrieval of relevant environmental information. For the implementation of the proposed framework, we present a description of the Intelligent Forest Fire Video Monitoring and Surveillance system in Croatia. We present the implementation of the tasks of monitoring and surveillance in the application domain of forest fire management.

Novel Motor-Kinetic-Energy-Based Power Pulsation Buffer Concept for Single-Phase-Input Electrolytic-Capacitor-Less Motor-Integrated Inverter System

The motor integration of singe-phase-supplied Variable-Speed Drives (VSDs) is prevented by the significant volume, short lifetime, and operating temperature limit of the electrolytic capacitors required to buffer the pulsating power grid. The DC-link energy storage requirement is eliminated by using the kinetic energy of the motor as a buffer. The proposed concept is called the Motor-Integrated Power Pulsation Buffer (MPPB), and a control technique and structure are detailed that meet the requirements for nominal and faulted operation with a simple reconfiguration of existing controller blocks. A 7.5 KW, motor-integrated hardware demonstrator validated the proposed MPPB concept and loss models for a scroll compressor drive used in auxiliary railway applications. The MPPB drive with a front-end CISPR 11/Class A EMI filter, PFC rectifier stage, and output-side inverter stage achieved a power density of 0.91 KW L−1 (15 W in−3). The grid-to-motor-shaft efficiency exceeded 90% for all loads over 5 kW or 66% of nominal load, with a worst-case loss penalty over a conventional system of only 17%.

C-V2X Centralized Resource Allocation with Spectrum Re-Partitioning in Highway Scenario

Cellular Vehicle-to-Everything communication is an important scenario of 5G technologies. Modes 3 and 4 of the wireless systems introduced in Release 14 of 3GPP standards are intended to support vehicular communication with and without cellular infrastructure. In the case of Mode 3, dynamic resource selection and semi-persistent resource scheduling algorithms result in a signalling cost problem between vehicles and infrastructure, therefore, we propose a means to decrease it. This paper employs Re-selection Counter in centralized resource allocation as a decremental counter of new resource requests. Furthermore, two new spectrum re-partitioning and frequency reuse techniques in Roadside Units (RSUs) are considered to avoid resource collisions and diminish high interference impact via increasing the frequency reuse distance. The two techniques, full and partial frequency reuse, partition the bandwidth into two sub-bands. Two adjacent RSUs apply these sub-bands with the Full Frequency Reuse (FFR) technique. In the Partial Frequency Reuse (PFR) technique, the sub-bands are further re-partitioned among vehicles located in the central and edge parts of the RSU coverage. The sub-bands assignment in the nearest RSUs using the same sub-bands is inverted concerning the current RSU to increase the frequency reuse distance. The PFR technique shows promising results compared with the FFR technique. Both techniques are compared with the single band system for different vehicle densities.

Impact of Molecular Electrostatics on Field-Coupled Nanocomputing and Quantum-Dot Cellular Automata Circuits

The molecular Field-Coupled Nanocomputing (FCN) is a promising implementation of the Quantum-dot Cellular Automata (QCA) paradigm for future low-power digital electronics. However, most of the literature assumes all the QCA devices as possible molecular FCN devices, ignoring the molecular physics. Indeed, the electrostatic molecular characteristics play a relevant role in the interaction and consequently influence the functioning of the circuits. In this work, by considering three reference molecular species, namely neutral, oxidized, and zwitterionic, we analyze the fundamental devices, aiming to clarify how molecule physics impacts architectural behavior. We thus examine through energy analysis the fundamental cell-to-cell interactions involved in the layouts. Additionally, we simulate a set of circuits using two available simulators: SCERPA and QCADesigner. In fact, ignoring the molecular characteristics and assuming the molecules copying the QCA behavior lead to controversial molecular circuit proposals. This work demonstrates the importance of considering the molecular type during the design process, thus declaring the simulators working scope and facilitating the assessment of molecular FCN as a possible candidate for future digital electronics.

Research on Design and Monitoring of a Development Index of an Industrial Internet Platform Based on a Fixed-Base Index Method

Accelerating the innovation and development of the Industrial Internet Platform is inevitably necessary for the integration of new-generation information technology and the manufacturing industry. It is also the key point for promoting the construction of manufacturing power and network power. In this paper, based on the comprehensive analysis of the relevant problems of China’s Industrial Internet Platform development monitoring, the development index of the Industrial Internet Platform is designed. Taking a typical domestic Industrial Internet Platform as an example, the development index of the Industrial Internet Platform in 2018, 2019, and 2020 are comprehensively calculated in this paper. The results show that China’s Industrial Internet Platform is rapidly growing in many aspects, such as industrial equipment cloud and industrial APP. There is a large space for improving the industrial knowledge accumulation reuse and the application promotion of small/medium-sized enterprises. The results in this paper can provide scientific suggestions and practical references for the government, enterprises, scientific research institutions, which is of great significance in promoting the healthiness and sustainability of the Industrial Internet Platform.

The Structural and Dielectric Properties of Bi3−xNdxTi1.5W0.5O9 (x = 0.25, 0.5, 0.75, 1.0)

A new series of layered perovskite-like oxides Bi3−xNdxTi1.5W0.5O9 (x = 0.25, 0.5, 0.75, 1.0) was synthesized by the method of high-temperature solid-state reaction, in which partial substitution of bismuth (Bi) atoms in the dodecahedra of the perovskite layer (A-positions) by Nd atoms takes place. X-ray structural studies have shown that all compounds are single-phase and have the structure of Aurivillius phases (APs), with close parameters of orthorhombic unit cells corresponding to space group A21am. The dependences of the relative permittivity ε/ε0 and the tangent of loss tgσ at different frequencies on temperature were measured. The piezoelectric constant d33 was measured for Bi3−xNdxTi1.5W0.5O9 (x = 0.25, 0.5, 0.75) compounds of the synthesized series.

AMROFloor: An Efficient Aging Mitigation and Resource Optimization Floorplanner for Virtual Coarse-Grained Runtime Reconfigurable FPGAs

With the rapid reduction of CMOS process size, the FPGAs with high-silicon accumulation technology are becoming more sensitive to aging effects. This reduces the reliability and service life of the device. The offline aging-aware layout planning based on balance stress is an effective solution. However, the existing methods need to take a long time to solve the floorplanner, and the corresponding layout solutions occupy many on-chip resources. To this end, we proposed an efficient Aging Mitigation and Resource Optimization Floorplanner (AMROFloor) for FPGAs. First, the layout solution is implemented on the Virtual Coarse-Grained Runtime Reconfigurable Architecture, which contributes to avoiding rule constraints for placement and routing. Second, the Maximize Reconfigurable Regions Algorithm (MRRA) is proposed to quickly determine the RRs’ number and size to save the solving time and ensure an effective solution. Furthermore, the Resource Combination Algorithm (RCA) is proposed to optimize the on-chip resources, reducing the on-Chip Resource Utilization (CRU) while achieving the same aging relief effect. Experiments were simulated and implemented on Xilinx FPGA. The results demonstrate that the AMROFloor method designed in this paper can extend the Mean Time to Failure (MTTF) by 13.8% and optimize the resource overhead by 19.2% on average compared to the existing aging-aware layout solutions.

Strengthening Quality of Chaotic Bit Sequences

We discuss chaos and its quality as measured through the 0-1 test for chaos. When the 0-1 test indicates deteriorating quality of chaos, because of the finite precision representations of real numbers in digital implementations, then the process may eventually lead to a periodic sequence. A simple method for improving the quality of a chaotic signal is to mix the signal with another signal by using the XOR operation. In this paper, such mixing of weak chaotic signals is considered, yielding new signals with improved quality (with K values from the 0-1 test close to 1). In some sense, such a mixing of signals could be considered as a two-layer prevention strategy to maintain chaos. That fact may be important in those applications when the hardware resources are limited. The 0-1 test is used to show the improved chaotic behavior in the case when a continuous signal (for example, from the Chua, Rössler or Lorenz system) intermingles with a discrete signal (for example, from the logistic, Tinkerbell or Henon map). The analysis is presented for chaotic bit sequences. Our approach can further lead to hardware applications, and possibly, to improvements in the design of chaotic bit generators. Several illustrative examples are included.

P1OVD: Patch-Based 1-Day Out-of-Bounds Vulnerabilities Detection Tool for Downstream Binaries

In the past decades, due to the popularity of cloning open-source software, 1-day vulnerabilities are prevalent among cyber-physical devices. Detection tools for 1-day vulnerabilities effectively protect users who fail to adopt 1-day vulnerability patches in time. However, manufacturers can non-standardly build the binaries from customized source codes to multiple architectures. The code variants in the downstream binaries decrease the accuracy of 1-day vulnerability detections, especially when signatures of out-of-bounds vulnerabilities contain incomplete information of vulnerabilities and patches. Motivated by the above observations, in this paper, we propose P1OVD, an effective patch-based 1-day out-of-bounds vulnerability detection tool for downstream binaries. P1OVD first generates signatures containing patch information and vulnerability root cause information. Then, P1OVD uses an accurate and robust matching algorithm to scan target binaries. We have evaluated P1OVD on 104 different versions of 30 out-of-bounds vulnerable functions and 620 target binaries in six different compilation environments. The results show that P1OVD achieved an accuracy of 83.06%. Compared to the widely used patch-level vulnerability detection tool ReDeBug, P1OVD ignores 4.07 unnecessary lines on average. The experiments on the x86_64 platform and the O0 optimization show that P1OVD increases the accuracy of the state-of-the-art tool, BinXray, by 8.74%. Besides, it can analyze a single binary in 4 s after a 20-s offline signature extraction on average.