Reviewerly/exHarmony huggingface dataset:
More Accurate Division Property Propagations Based on Optimized Implementations of Linear Layers

As a generalized integral property, the division property can be used to search integral distinguishers of symmetric ciphers by taking the advantage of automatic tools, such as Mixed Integer Linear Programming (MILP) and Boolean Satisfiability Problem (SAT) solvers. In this case, the accuracy of corresponding models will influence the resulting distinguishers. In this paper, we present a new technique to characterize the division property propagation of linear layers. Firstly, we study the impact of a linear layer implementation on its division property propagations. We found that division trails derived from an optimized implementation of a linear layer can be more accurate than the \(\mathcal {S}\) method, and different implementations can eliminate some different invalid division trails. Thus, we can eliminate a large number of invalid division trails by combining different implementations. As an application of our technique, we have searched distinguishers for Midori64, Skinny64 and LED. As a result, we can obtain the same longest distinguishers as the \(\mathcal {ZR}\) method and the \(\mathcal {HW}\) method, which are the exact modeling of linear layers. Moreover, our method can be used with both MILP and SAT, while the \(\mathcal {HW}\) method can only work with SAT. In addition, the number of constraints with the \(\mathcal {HW}\) method increases quadratically, however it increases linearly with our method.
Athlete Behavior Recognition Technology Based on Siamese-RPN Tracker Model

With the rapid development of deep learning algorithms, it is gradually applied in UAV (Unmanned Aerial Vehicle) driving, visual recognition, target tracking, behavior recognition, and other fields. In the field of sports, many scientists put forward the research of target tracking and recognition technology based on deep learning algorithms for athletes' trajectory and behavior capture. Based on the target tracking algorithm, a regional proposal network RPN algorithm combined with the twin regional proposal network Siamese algorithm is proposed to study the tracking and recognition technology of athletes' behavior. Then, the adaptive updating network is used to track the behavior target of athletes, and the simulation model of behavior recognition is established. This algorithm is different from the traditional twin network algorithm. It can accurately take the athlete's behavior as the target candidate box in model training and reduce the interference of environment and other factors on model recognition. The results show that the Siamese-RPN algorithm can reduce the interference from the background and environment when tracking the athletes' target behavior trajectory. This algorithm can improve the training behavior recognition model, ignore the background interference elements of the behavior image, and improve the accuracy and overall performance of the model. Compared with the traditional twin network method for sports behavior recognition, the Siamese-RPN algorithm studied in this paper can perform offline operations and distinguish the interference factors of athletes' background environment. It can quickly capture the characteristic points of athletes' behavior as the data input of the tracking model, so it has excellent popularization and application value.
Foreign Financial Flows, Human Capital and Economic Growth in North African Countries

The purpose of this study is to analyze the relationship between foreign financial flows (i.e., FDI inflows and remittances), human capital, and its effects on economic growth in 4 North African countries. Annual panel data from 2000 to 2018 are examined using the system GMM. First, we found strong evidence of a positive link between FDI and economic growth. Moreover, the results indicate that the complementarity between FDI and human capital positively influences economic growth. Second, the remittances are found to be positive factors for economic growth. In fact, higher human capital accumulation of receiving countries increases these positive impacts. Overall, the results indicate that foreign financial flows are positively correlated with human capital in influencing economic growth in the North African countries. Therefore, it becomes pertinent for policymakers to pursue a human capital policy to improve their absorptive capacities to exploit full benefits of foreign financial flows.
The Color Image Digital Watermarking Algorithm Based on Coordinate Transformation and Quaternion Fourier Transform

With the rapid development of information technology and Internet technology, people can easily exchange and transmit digital information, which not only brings convenience to people's work and life, but also brings rampant piracy of digital media.In the face of the temptation that pirated digital media can obtain huge benefits, some people are desperate to steal digital media works without copyright and sell and spread them at will.In this case, digital media copyright protection and anti-theft version authentication are very important measures to solve the current problems, and digital watermarking(DW) technology is an important method of digital media copyright protection and authentication, so it is more and more concerned and studied by researchers.This paper mainly studies the color image DW algorithm based on coordinate transformation and quaternion Fourier transform, including quaternion representation of color image, Fourier transform analysis, log polar transformation, watermark embedding and watermark extraction.Experimental results show that in the noise range, the smaller the compression ratio is, the more complete the watermark information can be extracted.When the image compression ratio reaches 80%, the watermark information can be completely extracted.
MoHRiPA—An Architecture for Hybrid Resources Management of Private Cloud Environments

The high demand for data processing in web applications has grown in recent years due to the increased computing infrastructure supply as a service in a cloud computing ecosystem. This ecosystem offers benefits such as broad network access, elasticity, and resource sharing, among others. However, properly exploiting these benefits requires optimized provisioning of computational resources in the target infrastructure. Several studies in the literature improve the quality of this management, which involves enhancing the scalability of the infrastructure, either through cost management policies or strategies aimed at resource scaling. However, few studies adequately explore performance evaluation mechanisms. In this context, we present the MoHRiPA-Management of Hybrid Resources in Private cloud Architecture. MoHRiPA has a modular design encompassing scheduling algorithms, virtualization tools, and monitoring tools. The proposed architecture solution allows assessing the overall system's performance by using complete factorial planning to identify the general behavior of architecture under high demand of requests. It also evaluates workload behavior, the number of virtualized resources, and provides an elastic resource manager. A composite metric is also proposed and adopted as a criterion for resource scaling. This work presents a performance evaluation by using formal techniques, which analyses the scheduling algorithms of architecture and the experiment bottlenecks analysis, average response time, and latency. In summary, the proposed MoHRiPA mapping resources algorithm (HashRefresh) showed significant improvement results than the analyzed competitor, decreasing about 7% percent in the uniform average compared to ListSheduling (LS).
Implementation of Semantic Web in the Companies: Human Resources Ontology

Today, data which is growing exponentially; has become very important in the both backup and analysis phase. For this reason, it is necessary to store, transfer and examine the data in a correct structure according to the semantic web principles. In addition, the aim of the computers to automatically infer some operations without the need for human intervention and to be more beneficial to people in this state is being worked on. An example of the human resources ontology developed with the Protégé tool is described in order to accelerate and correct the semantic network processes with the ontologies created for this purpose. In addition, the developed ontology was queried using SPARQL language. In this study, it is aimed to query different types of heterogeneous data together with RDF queries. Thus, in addition to relational databases, which are still indispensable today, many heterogeneous data will be queried and inferences can be made by computers.
SRL Video Recommender for Syllabus Driven E-Learning Platforms

“Acharya: community learning platform” is an intelligent online community-contributed learning platform with an integrated set of interactive online services that provides the teachers, learners, and others involved in education with information, tools, and resources to support and enhance educational delivery and management. Acharya includes study materials, including multiple videos on the same topic, with multiple languages so that students can choose their behavioral content to study. Educators can post their videos on related topics through the portal. They can also improve existing videos. Acharya automatically rates each content quality and recommends to each student according to their preference and taste. The paper describes the SRL algorithm used to address the challenges in recommending content in the Acharya platform.
Calibration method of multi-projector display system with extra-large FOV and quantitative registration accuracy analysis

The calibration of multi-projector display with extra-large field of view (FOV) and quantitative registration analysis for realizing perfect visual splicing is crucial and difficult. In this paper, we present a novel calibration method to realize the seamless splicing for a multi-projector display system with extra-large FOV. The display consists of 24 projectors, covering the range of 360 degrees in the longitude direction and 210 degrees in the latitude direction. A wide-angle camera fixed on a rotating optical system is used to scan the entire display scene and establish point-to-point correspondence between projector pixels and spatial points using the longitude and latitude information. Local longitude table and latitude table are established on the target of the wide-angle camera. A deterministic method is proposed to locate the North Pole of the display. The local tables corresponding to different camera views can be unified based on the image of the North Pole to form global longitude and latitude tables of arbitrary free-form surface. The mapping between the projector pixels and the camera pixels is established by inverse projection technique, and then each pixel of each projector can be appointed a pair of unique longitude and latitude values. A quantitative registration accuracy analysis method is proposed for multi-projector display system, in which, three-frequency temporal unwrapping method based on coded longitude and latitude values is applied to calculate the registration accuracy. Experiments prove that the registration error of the multi-projector system is less than 0.4 pixels.
Using Sentinel-2 MSI for mapping iron oxide minerals on a continental and global scale

Iron is the fourth most common element found in the earth crust. Although it may not be as important for soil fertility as, e.g., phosphorus, nitrogen and organic matter, its absence would be detrimental to plant growth. At the same time, iron oxides are highly correlated with phosphorus availability. Iron is thus an indicator for soil fertility and the usability of an area for cultivation of crop. A relatively high spectral resolution is needed for mapping iron oxide contents with spectral reflectance data, and remote sensing is the only suitable tool for surveying large areas at a high temporal and spatial interval. Sentinel-2 MSI (MultiSpectral Instrument) is the Landsat-like spatial resolution (10–60 m) super-spectral instrument of the European Space Agency (ESA), aimed at additional data continuity for global land surface monitoring with Landsat and Satellite Pour l’Observation de la Terre (SPOT) missions. Several studies with simulated and real data have been conducted in the last several years to show the potential of Sentinel-2 MSI, including its use for geological remote sensing, mineral mapping in particular. Sentinel-2 has several bands that cover the 0.9 μm iron absorption feature, while space-borne sensors traditionally used for geologic remote sensing, like ASTER and Landsat, had only one band in this feature. In this paper, we show a comparison of Sentinel-2 and AVIRIS to demonstrate the usability of the VNIR bands for mapping the near-infrared iron absorption feature. Next, we present spectral indices for mapping iron minerals that are important in soil fertility and mineral exploration.
Clear imaging specular surface and fringe patterns by using a concave mirror in phase measuring deflectometry

Phase measuring deflectometry (PMD) has been widely used to measure three-dimensional (3D) shape of specular objects because of its advantages of non-contact, large dynamic range, high-precision and fast-acquisition. However, due to the limited depth of field (DOF) of a camera lens, a liquid crystal display (LCD) screen and a tested specular object cannot be clearly imaged together, which affects the measurement accuracy. To tackle this issue, this paper proposes a novel PMD method of auxiliary imaging LCD screen by using a concave mirror. The LCD screen and a reference are in the same plane via the center of the concave mirror, and are perpendicular to the optical axis of the mirror. Both the LCD screen and the reference are symmetric each other through the optical axis, so that the imaging of one is the location of the other. Based on the imaging principle of concave mirror, the LCD screen is reflected and an inverted real image of the equal size is formed at the reference, and then reflected into the camera by the reference mirror during calibration. During the measuring procedure, a tested specular object is placed at the position of the reference. The displayed fringe patterns on the LCD screen are modulated by the tested specular object and the deformed fringes are captured by the camera. After phase calculation from the captured fringe patterns, 3D shape of the tested specular object can be obtained. The proposed PMD method can avoid the limited DOF of the camera lens, because fringe patterns displayed on the LCD screen and the tested specular surface can be clearly imaged together at the same position. Some simulated experiments on measuring specular objects have been carried out and the results demonstrate that the proposed PMD method can effectively and accurately measure 3D shape of specular surfaces.
Near-duplicate handwritten document detection without text recognition

The paper presents a novel method for near-duplicate detection in handwritten document collections of school essays.A large amount of online resources with available academic essays currently makes it possible to cheat and reuse them during high school final exams.Despite the importance of the problem, at the moment there is no automatic method for near-duplicate detection for handwritten documents, such as school essays.The school essay is represented as a sequence of scanned images of handwritten essay text.Despite advances in recognition of handwritten printed text, the use of these methods for the current task is a challenge.The proposed method of near-duplicate detection does not require detailed markup text, which makes it possible to use it in a large number of tasks related to the information extraction in zero-shot regime, i.e. without any specific resources written in the processed language.The paper presents a method based on series analysis.The image is segmented into words.The text is characterized by a sequence of features, which are invariant to the author's writing style: normalized lengths of the segmented words.These features can be used for both handwritten and machine-readable texts.The computational experiment is conducted on IAM dataset of English handwritten texts and the dataset of real images of handwritten school essays.
Trade secrecy, factual secrecy and the hype surrounding AI

Access to and sharing of anonymized machine-generated data and the transparency of data analysis techniques has taken on vital importance in a world characterized by artificial intelligence, particularly machine learning. This chapter interrogates the extent to which such data and algorithms may qualify as 'trade secrets' under US and EU trade secrets law, focusing in particular on whether the definition of a 'trade secret' is met. We show, through the use of two case studies - involving autonomous vehicles and credit scoring - and a close analysis of the trade secrets definition, that the claim of trade secrets protection is overstated. The greater risk relates to factual secrecy rather than legally protected trade secrets and the policy debate needs to shift to assess what regulation, if any, there should be of data that is simply kept secret.
A Probe into the Modernization of Rural Governance Structure in Ethnic Regions in the New Era

China has entered a new era, and problems in ethnic areas have become prominent.The structure of "township governance and village governance" in ethnic areas can no longer meet the needs of rural modernization, and it is difficult to effectively provide social integration and motivation for the main body to participate in governance.The structure and action of rural governance in ethnic areas increased dispersion increases the risk of failure of rural governance.The modernization of the rural governance structure in ethnic areas needs to fully grasp the inherent requirements for effective governance, strengthen the leadership function of the grassroots party organization, the social management and public service functions of the grassroots government, the grassroots social autonomy, the economic development function, and the social organization function, and actively adapt to and leading changes in the characteristics of rural actions, strengthening structural social integration, using strong structure to promote orderly actions, and orderly actions to promote effective governance.
Dark Channel Based Multiframe Super-Resolution Reconstruction

Multiframe super-resolution (MFSR) can obtain a high-resolution image from a set of low-resolution images. The performance of super-resolution is affected by the image prior information. The current super-resolution algorithms typically use total variation prior and its improved version, restoring the image edges well. However, it will produce artifacts and stair effects in the smooth region of the image. Therefore, we propose a dark channel-based MFSR algorithm to achieve edge-preserving and noise-suppressing. Firstly, the total variation prior is used to ensure the edge-preserving ability of the algorithm. Secondly, the dark channel prior is added to suppress artifacts and stair effects. Finally, the weights of the prior terms are iteratively adapted to obtain the final high-resolution image. Experiments show that the proposed algorithm can achieve a better result in objective and subjective visual evaluations.
The Role of Imaginative Fairy Tales in Reading Literacy

The School Literacy Movement program in Indonesia which has been run in elementary schools was still minimal with current reading resources, less inviting students to think ahead, and developing a monotonous attitude. It was necessary to produce the latest children's reading books such as imaginative tales that present stories related to technological developments. Producing imaginative fairy tales was the aim of this research. The study was conducted using a mixed-method with the Plomp development model. The Plomp development model has three steps: preliminary research, prototyping phase, and assessment stage. The research results at the preliminary research that students like imaginative tales and need new stories every morning before learning begins. In the prototyping phase is produced a valid and practical imaginative fairy tale book. Imaginative fairy tale book was designed using the Adobe Photoshop program. The imaginative fairy tale book that was developed was able to provide new ideas for students who read it. Besides, the development of a positive attitude is also included in the story, making it easier for teachers to educate students in elementary school
Deep Learning and Multivariate Time Series for Cheat Detection in Video Games

Online video games drive a multi-billion dollar industry dedicated to maintaining a competitive and enjoyable experience for players. Traditional cheat detection systems struggle when facing new exploits or sophisticated fraudsters. More advanced solutions based on machine learning are more adaptive but rely heavily on in-game data, which means that each game has to develop its own cheat detection system. In this work, we propose a novel approach to cheat detection that doesn&#x0027;t require in-game data. Firstly, we treat the multimodal interactions between the player and the platform as multivariate time series. We then use convolutional neural networks to classify these time series as corresponding to legitimate or fraudulent gameplay. Our models achieve an average accuracy of respectively 99.2&#x0025; and 98.9&#x0025; in triggerbot and aimbot (two widespread cheats), in an experiment to validate the system&#x0027;s ability to detect cheating in players never seen before. Because this approach is based solely on player behavior, it can be applied to any game or input method, and even various tasks related to modeling human activity.
Exploration on the Application of Exquisite Corpus in English Grammar Teaching

Exquisite corpora like lyrics, proverbs, tongue twisters, not only contain a lot of authentic language expressions, but also include interesting contexts and catchy rhythms.Besides, these exquisite corpora are often interesting and closed to life, which can greatly arouse students' enthusiasm in study, and ease their stress in studying grammar.In the potential sense, exquisite language materials are conducive to the cultivation of the aesthetic sense of language, as well as students' intercultural communication ability and cultural accomplishment.This essay chooses Class 11, Senior 1, No. 1 Middle School of Zaoyang, Hubei Province as research object, through empirical research, so as to explore the effect which grammar teaching with exquisite corpus has brought on students' grammar learning, grammar application ability, and their language competence.It is also expected that this teaching way could make a difference to students' cultural awareness, artistic appreciation and the level of intercultural communication.