Public administration: digitalization of strategic planning tasks

The article was prepared within the framework of the RFBR scientific project «Interdisciplinary study of the processes of digitalization, computerization and measurement of the role of science in the development and implementation of political decisions» (RFBR grant No. 20-010-00179). The main part of this article is related to conceptual and software developments on automating the process of managing the textual and semantic content of strategies. At this stage, scientific work is aimed at developing software modeling and automation of the control process. It includes a number of functions focused on digitalization and programming of the interdisciplinary and multifunctional task of developing, implementing and monitoring various types of strategies of the Russian Federation. When developing software modeling, the authors adopt a basic block diagram in the form of an industry strategy, the content structure of which can be transformed depending on the type of strategy (socio-economic, scientific and technological, etc.). The system management model for automating the preparation of textual strategy proposals includes the participation of specialized experts and well- known scientists who digitally evaluate strategy texts, including also an analytical mechanism for digitalizing the selection of the final text and its editing by the relevant ministries responsible for strategy development.

ULASAN: PEMBANGUNAN TEKNOLOGI PENGGASAN DAN PENGGUNAAN

Gasification technologies have the potential to produce clean and efficient energy sources. This technology is capable of producing synthesis gas from low or negative carbon -based raw materials such as coal, petroleum coke, high sulfur fuel oil, waste or waste materials and biomass. The gas produced from the process is used to replace natural gas to generate electrical power, or acts as basic raw material for producing chemicals and liquid fuels. Gasification is a process which utilizes heat, pressure, and steam to convert materials directly into gases, such as carbon monoxide and hydrogen gases. Despite differing in various aspects, gasification technologies have four common engineering factors such as atmospheric gasification reactors (oxygen or air content level), internal and external heating, reactor design and operating temperature. Raw materials, either in dry form or small granules, are fed into the reactor chamber called gasifier. Raw materials subjected to heat, pressure as well as an environment with rich or low oxygen content. Hydrocarbon gas (also known as Syngas), liquid hydrocarbon (oil) and coal (carbon black and ash) are the three main products of gasification. Syngas can be used as a fuel to produce electricity or steam, or acts as a basic block for various types of chemicals. When mixed with air, Syngas can be used in petrol or diesel engines with slight modifications to the engine.

Simulation of the movement of hedge cutter links in the Simulink application of the Matlab package

Simulation modeling allows researching a mechanism consisting of many links interacting with each other according to complex laws. In order not to write a model for each node of the investigated mechanism, it is advisable to use ready-made blocks of the Simulink application. To simplify the process of creating blocks responsible for the links of the mechanism, we used the Solidworks computer-aided design system. 3d models of each link were designed, kinematic connections between them were established. Thus, the mass characteristics of the links, their geometric parameters, moments of inertia and kinematic pairs were obtained. After exporting the model from the computer-aided design system to Simulink of the Matlab package, a basic block diagram was obtained which was supplemented with disturbing input signals, virtual oscilloscopes for characterizing, mechanical transmission units, etc. Based on the obtained coordinates of the frame links and the rotor knives, dependencies were constructed to determine the kinematics of their movement in three planes, which made it possible to clearly demonstrate the top and rear view of the mechanism under study in the considered time interval. The developed simulation model can be upgraded to study the dynamic characteristics of the mechanism.

Large-Capacity Image Data Hiding based on Table Look-up

In previous data hiding techniques, binary rules are usually used to guide the fine-tuning of the values of basic objects in the host media to hide bit 0 and bit 1. In this paper, we propose a new data hiding technique for gray images based on querying a 256x256 information table. The information table is constructed by cloning a 3x3 basic block, which we call seed block. Eight unsigned integer values between 0 and 7, i.e., 3 bit binary data, are assigned to different elements of the seed block. Each time, a pair of pixels are chosen from a host image, and their pixel values are used as row and column numbers to look up the information table. If element value obtained by looking up the table is equal to the 3 bit binary data to be hidden, the values of the pixel pair will remain unchanged. Otherwise, take this element as the central point, we call it the focus element, to enclose a 3x3 window in the information table. Then in the window, find the element which is equal to the data to be hidden. Finally, update the pixel values of the pair with the row and column numbers of the found element in the window. Since the row and column numbers are in the range of 0-255, the updated pixel values will not overflow. In the proposed algorithm, a pair of pixels can hide 3 bits of information, so the embedding capacity is very high. Since the adjustment of pixel values is constrained in a 3x3 window, the modification amount of pixel values is small. The proposed technique belongs to fragile digital watermarking, so it can be used for image authentication and tamper localization. By the evaluation of data hiding capacity, security, imperceptibility, computational cost and extensibility, this algorithm is superior to existing information hiding techniques. The proposed technique can also be used in color image and audio data hiding.

StFuzzer: Contribution-Aware Coverage-Guided Fuzzing for Smart Devices

The root cause of the insecurity for smart devices is the potential vulnerabilities in smart devices. There are many approaches to find the potential bugs in smart devices. Fuzzing is the most effective vulnerability finding technique, especially the coverage-guided fuzzing. The coverage-guided fuzzing identifies the high-quality seeds according to the corresponding code coverage triggered by these seeds. Existing coverage-guided fuzzers consider that the higher the code coverage of seeds, the greater the probability of triggering potential bugs. However, in real-world applications running on smart devices or the operation system of the smart device, the logic of these programs is very complex. Basic blocks of these programs play a different role in the process of application exploration. This observation is ignored by existing seed selection strategies, which reduces the efficiency of bug discovery on smart devices. In this paper, we propose a contribution-aware coverage-guided fuzzing, which estimates the contributions of basic blocks for the process of smart device exploration. According to the control flow of the target on any smart device and the runtime information during the fuzzing process, we propose the static contribution of a basic block and the dynamic contribution built on the execution frequency of each block. The contribution-aware optimization approach does not require any prior knowledge of the target device, which ensures our optimization adapting gray-box fuzzing and white-box fuzzing. We designed and implemented a contribution-aware coverage-guided fuzzer for smart devices, called StFuzzer. We evaluated StFuzzer on four real-world applications that are often applied on smart devices to demonstrate the efficiency of our contribution-aware optimization. The result of our trials shows that the contribution-aware approach significantly improves the capability of bug discovery and obtains better execution speed than state-of-the-art fuzzers.

A Novel Deep Convolutional Neural Network Based on ResNet-18 and Transfer Learning for Detection of Wood Knot Defects

Wood defects are quickly identified from an optical image based on deep learning methodology, which effectively improves wood utilization. Traditional neural network techniques have not yet been employed for wood defect detection due to long training time, low recognition accuracy, and nonautomatical extraction of defect image features. In this work, a model (so-called ReSENet-18) for wood knot defect detection that combined deep learning and transfer learning is proposed. The “squeeze-and-excitation” (SE) module is firstly embedded into the “residual basic block” structure for a “SE-Basic-Block” module construction. This model has the advantages of the features that are extracted in the channel dimension, and it is fused in multiscale with original features. Instantaneously, the fully connected layer is replaced with a global average pooling; consequently, the model parameters could be reduced effectively. The experimental results show that the accuracy has reached 99.02%, meanwhile the training time is also reduced. It shows that the proposed deep convolutional neural network based on ReSENet-18 combined with transfer learning can improve the accuracy of defect recognition and has a potential application in the detection of wood knot defects.

Design and Simulation of Reliable and Fast Nanomagnetic Conservative Quantum-dot Cellular Automata (NCQCA) Gate ​

Nanomagnetic Logic (NML) is a promising candidate for the real implementation of quantum-dot cellular automata (QCA) circuits and can be a proper alternative or complement to CMOS circuits. Like any other nanoscale technologies, NML circuits are also subject to fabrication variations. These variations along with fluctuations caused by thermal noise can affect the performance of these circuits. Therefore, design of NML circuits with high testability is an absolute necessity. Circuits based on conservative logic are inherently testable because of their specific properties. In this paper, considering the physical and geometrical properties of nanomagnets, a nanomagnetic conservative quantum-dot cellular automata (NCQCA) gate is designed and evaluated. This circuit can be used as the basic block for the realization of more complex conservative NML circuits. To implement this circuit, the design of the clocked nanomagnetic majority gate is also provided. The OOMMF physical simulation tool is used for simulation and evaluation. The results show the correct functionality of the proposed conservative gate at room temperature. It operates about 34% faster than the NML Fredkin gate. Moreover, the NML version of the conventional Fredkin gate takes 90% more area than the proposed design.

Hierarchical Attention Graph Embedding Networks for Binary Code Similarity against Compilation Diversity

Binary code similarity comparison is the technique that determines if two functions are similar by only considering their compiled form, which has many applications, including clone detection, malware classification, and vulnerability discovery. However, it is challenging to design a robust code similarity comparison engine since different compilation settings that make logically similar assembly functions appear to be very different. Moreover, existing approaches suffer from high-performance overheads, lower robustness, or poor scalability. In this paper, a novel solution HBinSim is proposed by employing the multiview features of the function to address these challenges. It first extracts the syntactic and semantic features of each basic block by static analysis. HBinSim further analyzes the function and constructs a syntactic attribute control flow graph and a semantic attribute control flow graph for each function. Then, a hierarchical attention graph embedding network is designed for graph-structured data processing. The network model has a hierarchical structure that mirrors the hierarchical structure of the function. It has three levels of attention mechanisms applied at the instruction, basic block, and function level, enabling it to attend differentially to more and less critical content when constructing the function representation. We conduct extensive experiments to evaluate its effectiveness and efficiency. The results show that our tool outperforms the state-of-the-art binary code similarity comparison tools by a large margin against compilation diversity clone searching. A real-world vulnerabilities search case further demonstrates the usefulness of our system.

Design and implementation of C-MEX S-functions in an Android-based networked control system laboratory

The Android-based networked control system laboratory (NCSLab) is a remote control laboratory that adopts an extensible architecture, mainly including Android mobile devices, MATLAB servers, controllers and test rigs. In order to conduct various simulations and experiments more effectively in NCSLab, the first key issue that needs to be solved is to enable users to design their own control algorithms or functional blocks on the Android client, rather than just using the basic block libraries provided by the system. So, this paper proposes and implements a scheme for Android-based compilation of C-MEX S-functions. With this new feature, users can design personalized algorithm according to their requirements in the form of S-functions, which can be called and executed after being compiled by MATLAB server. Finally, through the experiment validation of the three-degree-of-freedom air bearing spacecraft platform, it is proved that the method of Android-based C-MEX S-functions is reliable and efficient, and this scheme well enhances the functionality and mobility of Android-based NCSLab.

Detailed Study of AI/ML in Smart Agriculture

This work explores the tools and technologies used in smart agriculture. Artificial Intelligence and Machine Learning techniques, including basic block models that are used to do smart agriculture. How can we use fuzzy logic and Artificial Neural Network, is also covered in this paper. We have explored some of the IOT based irrigation systems including crop prediction systems. The necessary hardware, software and sensors that can be used to make precision agriculture are also included. The main motto of this paper is to get a detailed literature review that is required for smart agriculture.