Reviewerly/exHarmony huggingface dataset:
Unified Proof of Work: Delegating and Solving Customized Computationally Bounded Problems in a Privacy-Preserving Way

Proof of work (PoW), which was initially introduced for combating junk email spam, is extremely energy-thirsty, but the computed outcomes are of very little relevance to any practical usage. Some existing works tackle this issue by replacing the useless cryptographic puzzles with some pre-determined practical problems. However, the allowable problem types are usually limited and fixed, and some problems are of no significant value. This paper presents a Unified Proof of Work (UPoW) mechanism using flexible problems as puzzles, which features a computation-trading platform where delegators post their problems and PoW executors compute them as a by-product. The proposed UPoW puts known problem types together and frames them as verifiable computation problems using Fully Homomorphic Encryptions (FHE) techniques to replace PoW puzzles. It also secures and preserves the functionality of the delegated problems, which is showcased by delegating a Private Set Intersection (PSI) problem.
Artificial intelligence for molecular mechanism discovery

We develop a machine learning algorithm to extract the mechanism of transitions between metastable states from molecular dynamics simulations. Our algorithm combines transition path sampling (TPS), deep learning, and statistical inference to simulate the dynamics of complex molecular reorganizations. We iteratively train a deep learning model on the outcomes of the shooting moves used in TPS. By learning to predict the transition dynamics, the artificial intelligence (AI) system at the center of the algorithm gradually reveals the underlying mechanism of the transition dynamics, and at the same time increases the efficiency of the rare-event sampling. The AI system can simultaneously learn from and guide multiple TPS simulations running in parallel. In a second step, we then distill the knowledge about the transition mechanism encoded in the deep learning model into a reduced mathematical model. The reduced model concisely represents the key features of the mechanism in an explicit analytical, human-understandable form. We apply the algorithm to molecular systems ranging from ion dissociation in aqueous solution over gas hydrate formation to the oligomerization of a transmembrane alpha helix involved in membrane sensing. In all cases, the AI system accurately predicts the transition dynamics and extracts reduced mathematical models of the underlying mechanisms.
Minimizing variance of reaction rate estimation in weighted ensemble simulation using synthetic molecular dynamics

Weighted ensemble (WE) simulation employs multiple trajectories which intermittently are replicated or pruned to enhance the sampling of rare events. WE has recently attracted interest due to its conceptual simplicity, sampling power, toolkit accessibility, versatility for any type of stochastic process, and statistical exactness. However, although WE is unbiased, its performance as measured by run-to-run variance can depend significantly on the two types of hyperparameters: WE bins, which partition the conformation space, and WE allocation, which determines how many trajectories are maintained in each bin. Recent mathematical developments have shed light on how different steps of the WE procedure contribute to the overall variance and suggested parametrization strategies to minimize the variance of flux estimation. However, these results are based on asymptotic behaviors that are not achievable in simulations of realistic molecular systems. In this work, we explore the efficacy of a range of WE optimization strategies using synthetic molecular dynamics, a tractable yet nontrivial proxy to explicit MD based on fine-grained Markov state models.
PRNU Anonymous Algorithm Used for Privacy Protection in Biometric Authentication Systems

The photo response non-uniformity (PRNU) is used to connect an image to its source sensor. In this paper, researchers propose a PRNU anonymity method based on image segmentation to cut the relationship between the image and its source camera. According to the distribution rule of PRNU in the high and low frequency band of the image, the high and low frequency information of the part is also processed differently, which ensures the quality of the output image to a large extent. Experiments on the datasets show that the proposed method can preserve the biometric characteristics of the device while maintaining the anonymity of the device. Comparing with prior art, peak signal to noise ratio (PSNR) and cosine similarity are improved by 1.9 dB and 0.02 points, respectively.
Frank Wolfe Algorithm for Nonmonotone One-Sided Smooth Function Maximization Problem

In this paper, we study the problem of maximizing a nonmonotone one-sided- $$\eta $$ smooth (OSS for short) function $$\psi (x)$$ under a downwards-closed convex polytope constraint. The concept of OSS was first proposed by Mehrdad et al. [1, 2] to express the properties of multilinear extension of some set functions. It is a generalization of the continuous DR submodular function. The OSS property guarantees an alternative bound based on Taylor expansion. If the objective function is nonmonotone diminishing return (DR) submodular, Bian et al. [3] gave a 1/e approximation algorithm with a regret bound $$O(\frac{LD^{2}}{2K})$$ . On general convex sets, D $$\ddot{u}$$ rr et al. [4] gave a $$\frac{1}{3\sqrt{3}}$$ approximation solution with $$O(\frac{LD^{2}}{(\ln K)^{2}})$$ regrets. In this paper, we consider maximizing the more general OSS function, and by adjusting the iterative step of the Jump-Start Frank Wolfe algorithm, an approximation of 1/e can still be obtained in the case of a larger regret bound $$O(\frac{L(\mu D)^{2}}{2K})$$ . (where $$L,\mu , D$$ are some parameters, see Table 1). The larger the parameter $$\eta $$ we choose, the more regrets we will receive, because of $$\mu =\left( \frac{\beta }{\beta +1}\right) ^{-2\eta }$$ $$(\beta \in (0,1])$$ .
An Implementation and Evaluation of Layer 2 for Ethereum with zk-Rollup

Ethereum is a very popular blockchain platform. However, due to the limit of the Transaction Per Second (TPS) of this platform, the transaction processing time in Ethereum is very slow, which greatly affects the user experience and wastes time and other fees. Therefore, the scalability of Ethereum becomes an urgent problem to be solved. In this study, we try to improve the scalability problem of Ethereum by building a layer 2 with the zk-Rollup protocol. An evaluation of the implementation is also conducted. Experimental results show that the cost of transactions decreases depending on the batch size, with the gas cost decreasing by more than 85% for a batch size of 50 transactions. Other evaluation results reveal that deposits incur the most cost and increase faster with the batch size.
Understanding the complexities of operational technology security

Many of the computer systems and networks most essential to our daily lives are invisible. They manage crucial infrastructure on which society depends. And yet many of these systems are surprisingly difficult to protect. Securing industrial control system (ICS) solutions and operational technology (OT) networks requires different approaches and tools compared to most conventional technology.
The perfect cyber storm – security budgets, skills shortages and automated attacks

A combination of economic pressures, sophisticated assaults that maximise returns and a shortage of skilled professionals now mean that businesses can expect to become increasingly vulnerable to attack as they enter 2023.
AI and Computational Design Advance Protein Engineering

Genetic Engineering & Biotechnology NewsVol. 43, No. 2 Artificial IntelligenceAI and Computational Design Advance Protein EngineeringWith data-driven methods such as de novo protein design and iterative engineering, drug development is becoming more deliberate and systematicGareth John MacdonaldGareth John MacdonaldSearch for more papers by this authorPublished Online:10 Feb 2023https://doi.org/10.1089/gen.43.02.10AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 43Issue 2Feb 2023 Information© 2023 by GEN PublishingTo cite this article:Gareth John Macdonald.AI and Computational Design Advance Protein Engineering.Genetic Engineering & Biotechnology News.Feb 2023.26-28.http://doi.org/10.1089/gen.43.02.10Published in Volume: 43 Issue 2: February 10, 2023PDF download
Fully Dynamic No-Back-Edge-Traversal Forest via 2D-Range Queries

Orthogonal range search is ubiquitous nowadays, with natural applications in databases, data mining, and text indexing. Very recently, yet another application was discovered, which is to maintain a DFS forest in a dynamic graph. In this paper, we want to extend the above recent study, by applying orthogonal range search to efficient maintenance of a BFS-like forest, called no-back-edge-traversal (NBET) forest, which refers to a spanning forest obtained from a traversal that does not create any back edge. The study of such a problem is motivated by the fact that NBET forest can be used as a strong certificate of 2-connectivity of an undirected graph, which is more general than a spanning forest obtained from a scan-first search traversal.
HyperspectrACE: a Human Vision Inspired Hyperspectral Color and Contrast Adjustment

The automatic color equalization (ACE) algorithm, part of the Retinex-derived family of spatial color algorithms (SCAs), is an image enhancement algorithm that mimics the adjustment behavior of the human visual system (HVS). It is commonly used on a unique channel for black &amp; white images or independently on the three channels for color images. In this work, we introduce a novel application of ACE on hyperspectral images, referred to as HyperspectrACE. Here the goal is not to introduce the most performing hyperspectral image enhancer in the field, but to discuss the performance of a qualitative model of human color sensation when applied on more than the standard RGB channels. For this reason, we present the test of the proposed approach compared with classic ACE and other classic methods, to assess the differences in image dynamic stretching and global and local filtering contrast adjustment.
Key technologies of cross-domain authentication for big data security applications based on blockchain technology

As the human economy and society enter the era of big data, and the application of big data analysis is booming, the value of data analysis has doubled. The design and application of big data systems have shown unprecedented complexity. Traditional protection methods have been unable to adapt to the new security requirements of the big data processing environment, so security issues have become increasingly prominent. Research on data verification methods and cross-domain applications is great significance to the secure sharing of big data across regions, industries and companies. In the paper, the big data security application and cross-regional verification technology of blockchain technology are discussed, and the relevant theoretical knowledge is understood on the basis of the research literature, and then the big data security application using blockchain technology is cross-regional. The verification method was conceived, and the design method was tested. The test concluded the privacy protection-oriented service invocation authentication protocol proposed in this paper is compared with the invocation authentication protocol based on the PKI mechanism. When the number of transmissions reaches more than 6 the message the length reduction rate a tends to 0.90.
Adaptive japanese learning system based on computer network

With the rapid development of the application of digital information technology in China in recent years, and the gradual popularization and application of mobile communication technology, the emergence of digital language online learning application system becomes a natural course. The digital language learning system is very closely related to the theory of modern education in China. It will create and develop a new form of digital education technology facilities by establishing such a new concept of digital language laboratory and using the latest advanced network technology. The formal emergence of digital language online learning and training system will undoubtedly have a huge impact on the fundamental change in the development mode of primary and secondary education in China, and will strongly promote the modernization of language teaching in China. With the emergence of more and more online learning systems, users can learn online anytime and anywhere in the learning system environment.
Energy management system of papermaking process based on data mining

With the rapid economic development, the paper industry will still be in a production situation of high growth and development, and the demand for energy will further increase. The purpose of this paper is to study the papermaking process energy management system based on data mining. Firstly, a large amount of historical data is obtained from the energy management system of the enterprise, and data preprocessing is performed on the original data set, which provides support for the analysis of the energy consumption status of the research object, and also provides support for the subsequent data mining, process monitoring and abnormal diagnosis model establishment. More targeted basic data. Then, based on the historical data, the energy usage of a typical papermaking production line was analyzed, and the power distribution and energy flow of key energy-consuming processes were expounded, and the influence of environmental temperature and humidity on production energy consumption was quantitatively analyzed. The correlation coefficients with production power consumption are -0.135 respectively, indicating that there is a certain positive correlation between weather humidity and production power consumption.
English intelligent translation pattern recognition system on account of improved GLR algorithm

The existing traditional algorithms often have problems of inaccurate results and incorrect data processing. Now it is proposed to adopt the improved GLR algorithm to construct the intelligent recognition mode of English translation, so as to improve the accuracy of the intelligent translation mode. This algorithm facilitates the formation of a corpus of tens of thousands of English words that can be searched by themselves. This model consists of data collection, data processing and data output. Through the strict logic to collect the English signal, and extract the feature vector, finally achieve the purpose of automatic recognition of English words. In the whole process, the algorithm will record the data intelligently and process the recorded data. At the same time, it will record the accuracy of the previous English translation and conduct intelligent learning to gradually improve the accuracy of English translation. This paper studies the improved GLR algorithm, proposes the pattern recognition suitable for English intelligent translation, and analyzes the internal working principle. Data show that GLR algorithm can greatly improve the performance of pattern recognition in intelligent English translation.
Video salience detection algorithm based on visual psychology in virtual environment

With the rapid development of Internet and image acquisition equipment, the number of digital videos and images is increasing explosively. This paper summarizes the virtual environment and human visual physiology, discusses the research status of video saliency detection algorithms, proposes singular value decomposition, and makes experimental research on traffic scene saliency detection. The results show that the reason for missing detection is the serious color distortion caused by the change of light. The reason for the false report is that there are buildings with high color characteristics in the background.
Design of management information system of municipal engineering project based on GIS

With the rapid development of computer and network technology, GIS technology is widely used in various fields and industries such as transportation planning, land resource management and utilization and protection, environment and public safety, etc. Departments of fire protection, electric power, energy development, etc. have been established own work system, especially in the management of municipal engineering projects. This article aims to study the design of GIS-based municipal engineering project management information system. On the basis of analyzing the main functions of GIS, the problems of municipal engineering project management and system performance requirements, the municipal engineering project management information system is designed. Finally The performance of the system was tested. The test results show that the system response time is faster when the load is 20 users, and at most 50 simultaneous load access system users, to a certain extent, it can be seen that the performance of the system is in line with expectations.
Investigation and research on the construction of library VR intelligent system

Virtual technology is more and more widely used in all walks of life. VR technology which can present simulated virtual reality scenes is an important technical means for smart libraries to implement human-computer interaction, realize immersive reading and complete virtual experience in the future. Starting from the literature and questionnaire survey, this paper puts forward some suggestions on the construction of VR intelligent system in the library of higher vocational colleges, in order to help teachers and students in higher vocational colleges get a better and efficient sense of experience.
Collision detection system of dual manipulator based on differential evolution algorithm

At present, the double manipulator is widely used in manufacturing industry because of its high efficiency and performance. The cooperative action scenarios of the two manipulator are more and more. However, the interference collision between the arms needs to be solved, the obstacle avoidance and the path optimization are optimized. Some cooperative tasks also require the relative position and posture of the two end tools of the manipulator, avoiding collision between two manipulator is one of the most important problems to be solved in the production and manufacturing stage of double manipulator. Traditional intelligent trajectory planning method is widely used to predict and optimize the motion trajectory of manipulator. But the differential evolution algorithm has strong convergence and robustness in theory, and also plays a better optimization performance in the collision detection of manipulator. This paper introduces the theory of differential evolution algorithm, adopts computer simulation to compensate friction force and speed feedback. According to the simulation results, a collision detection system of double manipulator is established, and corresponding measures are taken to ensure that the collision of the two manipulator is reduced during the use. This is not only of great theoretical significance to reduce collision between multi manipulator arms, but also has important practical significance in manufacturing industry
Medical emergency language intelligent corpus on account of ant colony optimization algorithm

According to the needs of many emergency language intelligent corpora, professionals in the field have carried out data search, data acquisition, data de-falsification, noise removal and other processing steps, analyzed the characteristics of the corpus, and developed and designed an intelligent corpus system according to the characteristics of the corpus. At present, the database has stored more than 1.1 million words, 26,000 Chinese medical words, and 3000 sentences aligned with the corpus. These saved data are of great reference value to general corpora and of great significance to medical corpora. Corpus arrangement promotes the progress of natural language processing technology, which can solve a variety of medical communication difficulties in medical scenarios and remove obstacles for medical treatment. This paper studies the construction of medical emergency language intelligent corpus based on ant colony optimization algorithm to accelerate the construction process of medical emergency language intelligent corpus. The data test shows that the ant colony optimization algorithm based on the medical emergency language intelligent corpus construction has high performance in emergency language intelligent corpus construction.
Image semantic segmentation system based on optimized neural network algorithm

With the development of computer vision, neural network algorithms must be optimized. As an important recognition task of computer vision, image semantic segmentation system is to estimate the pixel-level target tags in the image. It must keep pace with the development and optimize the corresponding neural network algorithm. Recently, deep convolutional neural network is the main solution of image semantic segmentation system. This paper mainly studies the image semantic segmentation system based on optimized neural network algorithm, focusing onoptimized neural network algorithm, definition, classification, principle, future development theory, etc. By means of data demonstration, the superiority of the algorithm based on optimized neural network is proved, and the image semantic segmentation system using this algorithm has more application value. Based on the optimized neural network algorithm, the image semantic segmentation system must constantly strengthen the optimization and iteration algorithm, so that the algorithm is more flexible and changeable complex environment. In this paper, the image segmentation effect data obtained by data reached 88%, 78%,and80% in Pixel accurancy, IoU, and MIoU respectively.
A new mathematical probability based card counting strategy for blackjack using phyton

Blackjack, further known as twenty-one and pontoon, is a world-known casino banked game. This study elucidates a new card counting strategy based on mathematical probabilities where an edge could be gained on the house. While the existing strategies predominantly focus on overcoming the casino house edge in the interest of betting higher or lower, our strategy, PyCount, not only achieves this but also calculates whether a player ought to hit or stand. Python Module Random was used to construct the model. We compared PyCount with six of the most successful existing strategies. The results validate that the win plus draw rate is 58.61% for our approach, which is approximately 7% more than the figures of the other strategies.
Application of remote digital video monitoring and image recognition technology in power system

With the rapid development of digital image technology, image recognition technology has been applied to all areas of society, and people&apos;s lives have been greatly affected. After the establishment and implementation of the new power system, the power sector has become increasingly demanding in terms of the quality, reliability, and safety of power supply from the power grid. In view of this, this article studies the application of remote digital video surveillance and image recognition technology in power systems. This article first introduces the current research status and results of Chinese researchers on power systems, then analyzes the key technologies and methods of digital image processing, and finally conducts experiments with transformer fans and transformer thermometers as the research objects. The test results show that this paper proposes. The accuracy of remote digital video surveillance and image recognition technology in the power system can reach more than 95%, and it can be well adapted to different environments.