Reviewerly/exHarmony huggingface dataset:
Lithology identification based on interpretability integration learning

An interpretability model for intelligent lithology identification is proposed, which utilizes Ensemble Learning Stacking, Permutation Importance (PI), and Local Interpretable Model-agnostic Explanations (LIME) techniques. The aim of this method is to provide more accurate geological information and scientific support for oil and gas resource exploration. Two logging datasets from the public domain were used as experiments, and support vector machine (SVM), random forest (RF), and naive Bayes (NB) were employed as base learners, while SVM was utilized as the meta learner for lithology classification via stacking algorithm. The accuracy of the model was verified using evaluation metrics such as Area Under Curve (AUC), precision, recall, and F1-score. The PI and LIME techniques were employed to explain the lithology identification model. The results indicate that the stacking algorithm produced the best indexes and highest prediction accuracy. With respect to overall interpretation, PHIND, GR, and RT were found to have the most significant influence on lithology identification in a natural gas protection area in the United States, while DEN, CAL, and PEF were observed to be the most influential variables for lithology identification in the Daqing Oilfield in China. From the perspective of a single sample, the LIME algorithm can provide a quantitative prediction probability and degree of influence of the characteristic variables.
Dynamic Model Based Research on Intelligent Vehicle Steering and Obstacle Avoidance

In order to improve road safety, promote the development of autonomous driving, and realize the stability of unmanned vehicles during steering and obstacle avoidance, this paper establishes a lateral dynamic model and a cyclotron curve model based on the 3-degree-freedom vehicle dynamics model. Taking no collision between cars and timely obstacle avoidance as the optimization goal, this paper discretizes the model, a prediction model is established, a soft constraint solver is designed, and a relaxation factor is added to the performance index function. Based on the model prediction and control principle, the obstacle avoidance trajectory planning and tracking of unmanned vehicles is integrated and controlled, and the solution is converted into a quadratic programming problem according to the constraints and rolling optimization characteristics. Finally Matlab/Prescan joint simulation is used to verify the steering and obstacle avoidance quality of the model. The results show that the model has excellent safety, stability and comfort in non-highspeed situations.
The Application of Bayesian Theorem

Bayesian theorem is an outstanding theorem in probability theory. With the development of technology and the progress of society, the advantages of Bayesian theorem gradually show, which let us better utilize existing resources to make more accurate judgments. Further understanding of the application of Bayesian theorem in different fields will help us to clarify the future development trend and deficiency of this theorem. Numerous studies have explored this theorem's advantages and developments in several heated areas. In this study, the link between Bayesian theorem and three main fields, which are finance, computer science, and medicine, is carefully studied. In finance, the distribution, , aiding investors to make decisions in terms of both prior information and sample information are studied, as its mean balances two kinds of information. In computer science, an algorithm based on the Naive Bayes model is used to effectively filter spam, and TAN. Besides, one of naive Bayes model’s improvements is also discussed and compared. In medicine, the theorem upgrades the accuracy of diagnosis. In addition, a practical example is adopted to prove its function in breast lump disease. With abundant investigations and extensive applications, Bayesian theorem will be deeply rooted in human lives in various fields and greatly facilitates further research in these fields soon.
Some explorations of linear algebra

It is a fundamental problem in quantum information whether a particular quantum state of a composite system is entangled. It has enormous potential in quantum error correction, quantum cryptography, and quantum teleportation applications. This problem can be transferred in the form of a mathematical conjecture in language of linear algebra. In this paper, the authors explain the important applications, convenience, efficiency of using linear algebra in math physics, and computer science. The authors give some examples of linear algebra used in various areas, including datum coordinate system finding a location, encryption and decryption algorithm, storage of images, classical mechanics, and quantum physics. The authors list the definition of the matrix, real matrix, complex matrix, diagonal matrix, identity matrix, scalar matrix, trace, rank, and determinants of matrices. The authors explored Laplace expansion, transpose, inverse, conjugate of a matrix and addition, multiplication between matrices and between a scalar and a matrix, Kronecker product and their properties of matrices, the definitions and solving method of eigenvalue and eigenvector, and the diagonalisation and its conditions of matrices. The authors introduce the applications of matrix transformations and operations in programs. The authors explain two encryption and decryption algorithms based on linear algebra and their strengths and weaknesses.
Immersive narrative design in VR game

VR game is to simulate a false world and substitute the player's consciousness into the game to make the player feel more real. Compared with traditional games, VR game is freer. In order to provide a good immersive game, this paper develops a game called “Defer our homeland”. The purpose is to find out how to refine the details better, so as to improve the immersive experience of players. Therefore, we refined the details of background music, interaction design and scene respectively. In terms of background music, different from other games, the concert changes with the change of the plot. For example, the music is low and depressed at the beginning of the plot, and will gradually turn into passionate after the victory. In terms of scene design, considering some factors in the background story, in order to set off other details, the dilapidation degree of each map is different. As the map gets more and more dilapidated, the light will gradually dim. This means that the player is close to the boss. After players' feedback, the conclusion is that almost details of the game itself will affect the players' immersive experience. Especially in interactive design and background music, it is deeply praised and loved by players.
Analysis of the Number of Likes obtained by Sending Short Videos

The Internet is now an important part of people’s lives. Short video delivery is also an important branch of online activities. Getting more attention and likes is also an important purpose of sending. Based on the “like” data of videos, this paper focuses on the situation of attention in different periods and makes a statistical analysis of it. The data used in this paper mainly comes from TikTok. After statistical description of the data of different time periods of the same type of videos, finally the conclusion is drawn: posting at 8 o’clock or 24 o’clock to get more likes within one hour after sending the video, preferably not at 3 o’clock or 4 o’clock. Posting at 8 o’clock, not at 19 o’clock, to get more likes within five hours of sending a video. The results could provide some guidance or reference for online video publishers on when to post.
High-Frequency Time Series Data Regression Based on the Functional Bayesian Model Averaging

Regression analysis of high-frequency time series data has been an important problem in the field of statistical learning. In this paper, we propose a novel approach based on multiple basis function expansions and Bayesian model averaging when the predictor variable is a high-frequency time series and the response variable is continuous scalar data. On the one hand, the proposed method avoids the curse of dimensionality and extracts the functional information of the original sequence by transforming the discrete data into continuous functions in a function space consisting of some fixed basis functions. On the other hand, for the choice of basis functions, this paper proposes to adaptively determine the optimal solution using Bayesian model averaging, effectively balancing the variance and bias of the predictive model. The real data analysis shows that the proposed method has smaller mean squared error and absolute error, and is robust compared to other methods. Finally, the proposed method can be further extended to time series data applications such as weather forecasting and stock price prediction.
Reliability Modeling Method of Fresh Food Supply Chain System based on Bayesian Network

By referring to the method of system reliability modeling in reliability engineering theory, the abstract problem of system operation failure of fresh supply chain is concretized. By constructing the operation sequence of each link in the system and the causal logic of event existence, the Bayesian network topology is constructed. The reliability model of the supply chain system is established to analyze the ability of the fresh supply chain from the production end to the consumption end of the supply chain system to operate smoothly. From the perspective of system reliability, the weak links of fresh supply chain are determined, which provides an effective model for accurately evaluating the system reliability of fresh supply chain.
Study on the Coupling and Coordination of Chinese Medicine Development and Rural Revitalization from the Perspective of Regional Division

By constructing an ecological complex of Chinese medicine specialty industries, it can help farmers to increase their income and prosperity and promote rural revitalization. This study takes the spatio-temporal subjects of 30 provinces, cities and autonomous regions (excluding Hong Kong, Macao, Taiwan and Tibet) from 2011-2021 as the research objects. Firstly, a coupled and coordinated evaluation index system of Chinese medicine industry and rural revitalization is established and a comprehensive evaluation model based on entropy value method is used to explore the development level of both; secondly, based on the index system and development level, a density-based spatial clustering method with noise is used to divide the 30 provinces into regions; finally, the coordination relationship between the two is explored in the regional division as well as in the spatio-temporal perspective with the help of coupled coordination degree model. At the same time, this paper also analyzes the obstacle factors in the process of coupling and coordination between TCM development and rural revitalization by using the obstacle degree model, and puts forward reasonable suggestions for TCM development in each region to help rural revitalization. In terms of spatial dimension, the level of coupling and coordination between TCM development and rural revitalization is characterized by the spatial distribution of "high in coastal areas and low inland areas"; in terms of regional division, the level of coupling and coordination between TCM development and rural revitalization is characterized by In terms of regional division, the level of coupling and coordination between the two is characterized by the regional distribution of "low level of development and low level of coordination, high level of development and high level of coordination"; in terms of obstacle factors, industrial prosperity is the key obstacle factor affecting the coupling and coordination of TCM development and rural revitalization.
Modern New Media Drive Which Development in Poor Areas

Nowadays, the world has changed a lot and many cities had made remarkable leaps and bounds, whether it is the economy, the level of medical care or the quality of teaching and learning have all made great progress. But among the many developed areas, there are still other areas that have not been well improved, not only the economy has not been improved, but slowly withdrawn from the trend circle of this modern and fast developing era. Then nowadays new media communication is a good solution to this problem, not only can increase the number of tourists through video propaganda, but also through live with goods, video with goods and other ways to solve the problem of poor areas with a single sales channel and low attention, thus driving the local development and economic improvement.
Analysis of the Historical Origin of Ancient Chinese Poetry and Art Songs

The successful combination of poetry and dynamic beauty in poetry and dynamic beauty in music often brings vitality to people with transcendent aesthetic enjoyment. Classical poetry is an important cultural treasure in ancient Chinese literature, and it also has a relatively broad cultural value in the context of the current era, and is a brilliant pearl of Chinese culture. Ancient Chinese poetry and art songs refer to a relatively unique form of music genre produced by taking the poetry of Chinese literati and scholars as the singing content, adding scores and soundtracks by composers, and skillfully integrating poetry, rhyme and vocal emotion. After thousands of years of development, Chinese modern art songs combine literary art and musical art, precipitating thousands of years of cultural connotations of the Chinese nation; It embodies the spiritual feelings of thousands of people and is an important part of the excellent traditional culture of the Chinese nation. It is not only a perfect combination of traditional culture and elegant art, but also the symbiotic link between poetry and music. It has been spread for thousands of years in the long river of literature and art of the Chinese nation for a long time, and has profound historical connotation and high research value.
Research Advanced in the Recommendation Algorithms

In this era of explosive growth of information resources, how to efficiently access the needed resources has become a problem for people. In response to the above practical application requirements, the recommendation system has gradually become a new research hotspot, whose basic task to provide users with efficient and accurate recommendations by modeling the historical behavior of users. In this paper, based on detailed literature research and analysis, we present a comprehensive review of the research work on recommendation technology. Specifically, we summarize three representative methods of recommender systems according to different design ideas, which mainly includes collaborative filtering recommendation algorithm, deep learning recommendation algorithm, and cross-domain recommendation algorithm. Then we analyze the respective advantages of different algorithms and give an outlook on the future research directions of recommendation system.
An empirical user-study of text-based nonverbal annotation systems for human–human conversations

With the substantial increase in the number of online human–human conversations and the usefulness of multimodal transcripts, there is a rising need for automated multimodal transcription systems to help us better understand the conversations. In this paper, we evaluated our automated system (MONAH and its enhanced version MONAH＋) against the prevalent Jefferson manual system to perform multimodal transcription, which is widely used by the linguistics community but also very labor intensive. Our previous work, MONAH (Multimodal Narratives for Human) aims to make multimodal transcripts accessible and automated, whilst MONAH＋ expands MONAH to visualize machine attention — in other words, what words are deemed to be important to a machine classifier and draw the users’ attention towards them. Based on 104 participants’ responses, we found that (1) all text-based methods significantly reduced the amount of information for the human users, (2) MONAH was found to be more usable than Jefferson, (3) Jefferson’s relative strength was in chronemics (pace/delay) and paralinguistics (pitch/volume) annotations, whilst MONAH’s relative strength was in kinesics (body language) annotations, (4) enlarging words’ font-size based on machine attention was confusing human users as loudness. These results pose considerations for researchers designing a multimodal annotation system for the masses or who would like a fully-automated or human-augmented conversational analysis system.
PMST: A parallel and miniature Swin transformer for logo detection

With the popularity of online shopping and the rise of various brands, logo detection is gradually coming to the forefront of researchers' minds. However, accurately detecting multiscale, similar, diverse and shape-shifting logos poses a challenge for this technology. The Swin transformer has created a milestone as a high-performance deep learning method across modalities, domains and tasks in various tasks of computer vision. We improve the Swin transformer for better image feature extraction and enhance the robustness for its application to logo detection. In this paper, we propose the PMST as the backbone of logo detection, and design a bypass-parallelizable shift module and a miniature window tandem shift strategy to further enhance image feature fusion and transfer between windows. The PMST achieves a 79.2 box AP on the LogoData dataset, surpassing most detection models. According to existing known methods, in logo detection, the PMST is the first backbone to put transformer to the detection. The results achieved state-of-the-art on the FlickrLogos-32 and FoodLogoDet-1500 datasets. It also achieves excellent efficiency on the ImageNet-1K, OpenBrands-80 and MS-COCO datasets. The code is available at https://github.com/blowhen/PMST.
Design of Secure Reversible Select, Cross and Variation (RSCV) Architecture in Quantum Computing

The principles of quantum physics serve as the foundation for the power of quantum computing technologies. Since these events lack a classical counterpart, conventional computers cannot provide comparable outcomes. Future studies are dominated by the rapidly expanding field of quantum technology application. Its popularity has increased as a result of several unique features that are missing in traditional domains. Real-time quantum computing makes it easy to design and apply unique quantum layouts on accessible quantum computing platforms. Quantum machines claim to possess high computing power in the field of cryptography. Expertise in communication security has helped this area grow significantly over time. A novel method of data encryption termed SCV (select, cross, and variation), based on input data halves swapping, is shown here utilizing the reversible quantum logic. Using a variety of quantum gates, we created this technique in this study in IBM Quantum. The developed method is applied to several quantum simulators; the quality is compared concerning frequency, no. of qubits, run time, and quantum volume (QV).
Global horizontal irradiance and wind speed prediction using ANN: Comprehensive Study

Nowadays renewable energy resources such as wind and solar fulfill the requirement of electricity without the emission of greenhouse gases. Wind and solar have a highly irregular and fluctuating nature. It is very difficult to predict them accurately. In this study, we are predicting two meteorological parameters; global horizontal irradiance and wind speed. Additionally, a comparison is carried out among different Artificial neural network (ANN) algorithms; Levenberg marquardt (LM), bayesian regularization (BR), one step secant (OSS), Polack Riebere conjugate gradient (CGP) and Resilient Propagation (RP) in terms of mean square error (MSE), root mean square error (RMSE) and correlation coefficient (R) value. The results show that BR outperformed in terms of MSE (0.3023), RMSE (0.54981), and R-value (0.83533). LM also provided less error with fast speed. The OSS algorithm provided least performance compared to other models i.e. MSE (0.34968), RMSE (0.591337), and R-value (0.80629).
Design of a Reliable Copyright Management System Based on Blockchain

Although data exchange and transparency are encouraged by the Internet, digital information is not protected by it. It has become challenging to publish the Digital Rights Management system in today’s digital environment that can be regarded as well-protected. The value of digital work that is quickly accessible in open-source settings will eventually be zero to the creator. Nonetheless, anyone can download and make copies of content because it is available online. Since the value of data is typically based on how difficult it is to access, the worth of online content gradually declines.It may serve as a good alternative to the aforementioned issues. In this paper, we suggest a blockchain-based approach for a DCM system. In order to keep information transparent and secure, we store thedetails of copyright transactions on the blockchain. Smart Contact replaces the requirement for centralised servers to validate identities and issue licences by ensuring the validity of copyright transactions and issuing licences automatically. The possibility for using blockchain based to address the issue of managing digital copyright. This paper outlines a complete digital copyright management system (DCMS) centred on a public blockchain.
Implementation of the Quantum BCD-to-Excess-3 Code Converter using New Quantum Reversible Circuit Block

In this article, a new quantum reversible circuit or QRC block has been proposed to implement the quantum BCD-to-Excess-3 code converter using Qiskit, which is used to convert quantum BCD code to Excess-3 code. The proposed quantum BCD-to-Excess-3 or QBEC is most important for quantum information processing. It can be used for quantum cryptography, quantum communication etc. The proposed new quantum reversible circuit is also used to realize the different logic functions such as OR, XOR, XNOR, NOR, NAND, NOT and other logic functions. The proposed QRC is represented by quantum implementation with quantum cost 8. The QRC is implemented and verified using IBM Qiskit. The quantum cost, garbage output and delay of the QBEC converter circuit are 8, 1 and 1. The improvement % of quantum cost and delay w.r.t. previously reported results are 27.27% and 50% respectively.
Collaborative Design to Support Mutual Awareness in Single-Pilot Operation and Remote Collaboration

For economic reasons, manufacturers have been considering dedicating commercial flights to a single pilot for the last ten years. In order to ensure a certain redundancy, this pilot could be assisted by a ground pilot. In the absence of appropriate collaboration tools, the physical separation of these pilots will lead to a degradation of the mutual understanding of behaviors (observable fact on a person) and activities (i.e. mutual awareness). In order to restore mutual awareness, indicators of each pilot’s behavior (i.e. design element) need to be integrated into future flight tools. In this paper, we study the modalities of design elements in two new interfaces (ground and onboard) developed by iterations. These collaborative interfaces contain two types of elements: a remote display of the pilot’s eye movements, via an eye-tracking system, and an indicator of the activities performed in the tool (moving in the map, navigation in the tabs). Two remote collaboration scenarios were proposed to four professional pilots. They allowed to identify the cues to be transmitted, such as the availability of the pilots, and to test the transmission modalities: capture (eye-tracking, audio, interface inputs), temporality (continuous transmission) and representation (graphic, audio).