Reviewerly/exHarmony huggingface dataset:
A domain-invariant feature learning framework for histopathology images

In clinical practice, deep learning models commonly encounter performance degradation in actual applications, mainly due to domain shifts caused by heterogeneity from various sources such as scanners, stains, and medical sites. To address this issue, we examine the single-source domain generalization problem - developing a deep network that can withstand unseen domains, using training data from only one source domain. Our solution involves a novel domain-invariant feature learning model, integrating attention normalization and style enhancement modules at shallow layers of the network while exploring the optimal combination strategy in the convolution block. Furthermore, we use color transformation technology to randomly convert images to produce images with different color distributions to eliminate the effects of stains. The experiments demonstrate that our proposed approach achieves state-of-the-art performance in pathological classification tasks and can be extended to unseen domains.
Research competencies in university students: Intertwining complex thinking and Education 4.0

Research competencies are skills that university students must develop to create and socialize scientific products during their academic live. In this research, an experience was implemented to improve the students’ competency levels through its imbrication with complex thinking and the use of Education 4.0 applications, such as remote team workflow development apps, web-based virtual reality, and social robotics. The study was sequential-quantitative and descriptive. A questionnaire was applied before and after the experience to know the perception of 105 Mexican university students, later a rubric was implemented for the teacher’s assessment. The results indicate that the students perceived an improvement in their research skills, however, the evaluation showed a difference between the student’s perception and the teacher’s regarding improvement in said skills. The experience can be scaled to other scenarios, where disruptive teaching strategies can support research skills development.
Research on real time hyper-resolution image recognition based on urban level large scale vehicle network interaction

With the continuous expansion of urban transportation networks and the increase in the number of vehicles, real-time monitoring and identification of urban transportation networks has become an important research direction. This article proposes a real-time super-resolution image recognition method based on large-scale urban vehicle network interaction. This method improves the efficiency of traffic management and control by monitoring and identifying vehicles in the urban transportation network in real time. This article adopts deep learning and image super-resolution techniques, and uses large-scale datasets for experimental verification, achieving good results.
Endogenous gold of the russian Altai

The Altai of Russia in the geological and metallogenic sense includes the Altai Mountains and the northwestern part of Rudny Altai, and in administrative terms - the Altai Territory and the Altai Republic. Gorny Altai has experienced a complex history of geological development, including subduction, accretion-collision and rifting processes with the formation of various types of magmatism and endogenous gold mineralization. The history of gold mining in the region is associated mainly with placers and currently the reserve of placer gold deposits is almost exhausted, and the prospects for primary mineralization have been little studied. In this regard, the problem of assessing the potential of ore gold in known ore occurrences and promising areas of ore clusters has become urgent in the region.In the Russian part of Rudny Altai, gold reserves are mainly associated with gold-bearing pyrite-polymetallic deposits and less with small gold ore occurrences.Gold-sulfide-skarn, epithermal gold-silver, copper-gold-porphyry and gold-mercury types of mineralization may have important practical significance for the region. The increase in ore gold reserves in the Russian part of Rudny Altai is mainly due to additional exploration of pyrite-polymetallic deposits.
Under the Background of Industry-Education Integration--Real-Time Environmental Inspection--Exploration and Practice of Teaching Mode

This article mainly discusses the application of real-time environmental monitoring technology in educational practices. It begins by introducing the basic principles of this technology, which involves real-time monitoring of environmental parameters through sensors and the use of data analysis and processing for real-time evaluation and feedback. It then delves into the specific applications of real-time environmental monitoring technology in teaching, including classroom instruction and laboratory practices. The article analyzes the advantages of this technology in teaching, such as real-time monitoring, objectivity, and personalization, while also addressing challenges such as sensor reliability and accuracy, teacher training, and strategy improvement. Finally, it provides methods and strategies to address the challenges in the application of real-time environmental monitoring technology, including improving sensor technology, enhancing teacher training, and refining teaching strategies. Overall, real-time environmental monitoring technology has significant potential for application in education, but it also requires addressing various technological and educational challenges.
Research on the contribution rate of higher education to economic growth in the Yangtze River Delta

Based on the C-D growth function and utilizing the Denison factor analysis method, this paper calculates the contribution rate of higher education in the Yangtze River Delta region, consisting of three provinces and one municipality, to economic growth from 2002 to 2021. The results indicate that higher education in the Yangtze River Delta region plays a crucial role in driving economic growth, with contribution rates exceeding 4% consistently. While the educational levels in the three provinces and one municipality have improved, and the educational structure has been optimized, there are variations in the contribution rates of higher education to economic growth, with Shanghai standing out prominently. Therefore, the Yangtze River Delta region should increase the duration of education, enhance the overall level of education, continuously optimize educational institutions, improve the overall educational quality, strengthen regional cooperation and communication, promote knowledge sharing, and foster economic development.
Evaluation of Higher Vocational English Curriculum Toward Enhanced Program Implementation

This descriptive-comparative research aims to examine the difficulties encountered by educators and students during the implementation of the English curriculum. This research examines the survey data collected from both instructors and students in order to get a thorough comprehension of the factors that impact curriculum delivery and learning experiences. The results of the study provide significant insights on the distribution of gender, age groups, teaching experience, student categories, and college affiliations. Prominent observations reveal significant disparities in perspectives between educators and students with regards to several aspects of the curriculum, such as its design, characteristics, objectives, material applicability, teaching methods, and assessment approaches. The findings of this study indicate that gender and categorization did not have a significant effect on the observed disparities. However, it was observed that college affiliation had a major role in influencing these discrepancies. Educators and students encounter a range of hurdles that include deficiencies in linguistic foundation, restrictions in vocabulary, complexity in grammar, difficulty in pronunciation, concerns with confidence and motivation, impediments in independent learning, and the significance of cross-cultural understanding. The implications derived from the results underscore the need for enhanced cooperation and communication between educators and learners. This research highlights the need of developing flexible courses that accommodate the varied interests and requirements of students. This research offers a comprehensive examination of the intricacies involved in the implementation of English curriculum in Chinese educational contexts. Moreover, it puts forward practical suggestions for improving the quality of teaching and learning in these settings.
Research on the Application of Cloud Computing in University Library Management System

At present, most libraries have to build their own library management system, which is undoubtedly a high-input work for large libraries or small and medium-sized libraries in developed areas. As a newly emerging technology in recent years, the huge advantages of cloud computing are incomparable to many traditional technologies. The biggest feature of cloud computing is that it can transfer the computing power of the computer to the corresponding software, from which customers can access the computer's storage system to obtain the information they need, so that resources can be shared and users can get it in time. Therefore, the traditional library management system architecture will also be challenged, and it is urgent to develop a library management system based on cloud computing. This paper studies the architecture of university library management system based on cloud computing.
Research on Strategies for the Innovative Teaching Design of College English in the New Era Based on Case Studies

In this new era, the economic globalization and rapid development of science and technology are calling an innovation of college English teaching in higher education. Based on the study on the teaching designs in FLTRP Star Teacher Contest and papers relating to college English teaching innovation, this paper is trying to find useful strategies for the innovative teaching design of college English curricula, hoping to make a contribution to the exploration of English teaching innovation in higher education.
Akuntabilitas dan Transparansi Pengelolaan Dana Bantuan Operasional Sekolah (BOS)

The research conducted at state madrasa aliya 5 Ciamis aims to determine accountability and transparency in the management of school operational assistance funds. The problem with this research is that there are schools that are not yet transparent and accountable for managing school operational assistance funds. The method used in this study is a qualitative descriptive method where data collection uses interview techniques with the principal and treasurer as well as observation of documents related to school operational assistance funds. Qualitative descriptive data analysis technique The results of this study indicate that state madrasa aliya 5 Ciamis, in managing school operational assistance funds, has implemented the principles of accountability and transparency quite well. This can be seen from the accountability reports of school operational assistance funds to related parties from the regional to the central level, as well as the form of transparency to the public, even though the media is limited. However, there are still shortcomings or the need for improvement in several aspects, such as transparency and the absence of digital media used to disseminate reports on the use and receipt of school operational assistance funds.
Unlocking Algeria's Economic Potential

The distinction between entrepreneurship and rent-seeking is acknowledged, highlighting the significant role that entrepreneurship education plays in fostering employment opportunities, productivity, economic growth, innovation, and competitiveness. This approach ultimately enhances a country's standing in the global market. This study aims to evaluate the effect of entrepreneurship on Algeria's economic development. Using annual data from 2006 to 2020, the Autoregressive Distributed Lag (ARDL) co-integration methodology is used to accomplish this. The analysis's main conclusions show that the variables of interest have a consistent, long-term relationship. Furthermore, the findings show that tertiary education (as a percentage of gross enrollment), new business density, and school enrolment all positively influence GDP growth over the short and long terms. These results offer strong proof of the beneficial impact of entrepreneurship on economic growth.
Driving Economic Development

This chapter aims to provide insights into the importance of empowering women in entrepreneurship and its potential impact on economic growth. In this study, the authors analyze the influence of women's entrepreneurship on economic growth with a particular focus on Algeria's environment. The research highlights the significant role played by Algerian women in contributing to the country's economic development. To conduct this empirical investigation, they employed five variables: GDP, businesswomen ownership, women in the industrial sector, force labor women, and women's unemployment. The findings shed light on the crucial need to empower women in entrepreneurship and its potential benefits to economic growth 1990 to 2019 using annual data. According to the Johansen test, they found a long-run association between the GDP and the rest of the variables based on the vector error correction model and the co-integration test. The outputs of the VECM model confirmed the first results with a significant and negative coefficient, which means a long-run relationship between the variables.
Development of Sparkol Videoscribe-Based Learning Media in Fourth-Grade of Elementary School Science Lessons

Learning media that are generally used are less attractive and cannot be used optimally independently. Meanwhile, at the fourth-grade level of elementary school, students need engaging media that can be used independently at home. Sparkol Videoscribe-based learning media can help students understand the material and foster interest in learning and independent learning. This study aims to develop Sparkol Videoscribe-based learning media in science lessons for fourth-grade of elementary schools and determine its feasibility. The research method used is Research and Development (RD) which was conducted in two elementary schools in Jakarta. The research model used is 4D with define, design, develop, and disseminate stages. The data collection technique used was a questionnaire. The results related to media expert validation were 86.1%, material expert validation results were 88.8%, and linguist validation results were 94.7%, so overall, it became 89.7% with a very decent category. The results of user trials conducted by teachers and students obtained a value of 92.5% for teacher trials and 92.3% for students. These results make Sparkol Videoscribe-based learning media in the fourth grade of elementary school science lessons feasible. If implemented, it will increase learning effectiveness and motivate learners to be more active and creative.
Principles of self-calibration and visual effects for digital camera distortion

Abstract Producing accurate spatial data with stereo photogrammetric techniques is a challenging task, and the central projection of the space needs to be defined as closely as possible to its real form in each image taken for the relevant production. Interior camera parameters that define the exact imaging geometry of the camera and the exterior orientation parameters that locate and rotate the imaging directions in a coordinate system have to be known accurately for this correct definition. All distortions sourcing from lens and sensor planes and their recording geometry are significant as they are not suitable for detection with manual measurements. It is of vital importance to clearly understand the camera self-calibration concept with respect to the lens and the sensor plane geometry and include every possible distortion source as an unknown parameter in the calibration adjustments as they are all modellable systematic errors. In this study, possible distortion sources and self-calibration adjustments are explained in detail with a recently developed visualization software. The distortion sources investigated in the study are radial, tangential, differential scale, and axial skewing distortion. Thanks to the developed software, image center point, distorted grids, undistorted grids, and principal points were visualized. As a result, the most important element of obtaining accurate and precise photogrammetric productions is the correct definition of the central projection of the space for each image, and therefore, the study explains an accurate and robust procedure with the correct definition and use of correct camera internal parameters.
A Feature Fusion Network for Skeleton-Based Gesture Recognition

With the development of the times, the requirements for human-computer interaction methods have gradually increased, and naturalness and comfort are constantly pursued on the basis of traditional precision. Gesture is one of the innate ways of human communication, which is highly intuitive and can be employed as an effective means of natural human-computer interaction. In this paper, dynamic gestures are investigated based on the 3D skeletal information of gestures, and different cropping boxes are placed at generate global and local datasets respectively according to whether they depend on the motion trajectory of the gesture. By analyzing the geometric features of skeletal sequences, a dual-stream 3D CNN (Double_C3D) framework is proposed for fusion at the feature level, which relies on 3D heat map video streams and uses the video streams as the input to the network. Finally, the Double_C3D framework was evaluated on the SHREC dynamic gesture recognition dataset and the JHMBD dynamic behavior recognition dataset with an accuracy of 91.72% and 70.54%, respectively.
Trajectory Planning of Aerial Manipulators Based on Inertial Decomposition

Aerial manipulator poses a challenging trajectory planning problem because of the dynamical coupling between the quadrotor and the robotic arms. Aiming at the system trajectory planning problems of the center of mass(CoM) offset after the dynamic swing of manipulator, this paper proposes a trajectory planning method based on inertial decomposition. Meanwhile, in the proposed method, the dynamic constraints of the quadrotor are also taken into account to ensure the pitch angle and angular velocity of quadrotors are suitable and feasible. A geometry controller is used to ensure accurate tracking of the planned trajectory. Simulations are carried out to verify the proposed method.
Investigation of a Possible Link between Solar Activity and Climate Change in Saudi Arabia: Rainfall Patterns

In this study, annual, quarterly, and monthly mean precipitation data in Saudi Arabia were correlated with sunspot number (SSN) and galactic cosmic ray (CR) flux over 35 years (1985-2019). The results show that the strength, magnitude, proportion and statistical significance of the relationship between precipitation and the two variables varied by season and month. We find that mean annual precipitation in Saudi Arabia, from May to November, and summer and autumn are correlated with cosmic rays and inversely correlated with SSN. Correlations of varying intensities and scales were found during the remaining months and during winter and spring. The relationships between the rainfall and SSN and CR for each solar cycle were investigated and showed that for all three cycles, the annual rainfall over Saudi Arabia has a positive correlation with CR. Different results were obtained when the seasonal rainfall data correlated with the SSNs and CRs during each cycle. The results obtained, in terms of their strength and magnitude, are affected by terrestrial and extra-terrestrial factors. These factors have been briefly presented and discussed. These findings represent a step towards understanding the possible role of solar activity in climate change for future meteorological phenomenon forecasting, even if the physical mechanism is still poorly quantified.
An Amended Time-Scaling Algorithm for Kino-Dynamic Trajectories

This paper presents a computational geometry-based implementation of the time scaling algorithm, with a linear-time complexity. The proposed method involves sampling N points along a robot’s motion path and scaling their speed profiles to meet the kino-dynamic constraints at those points. The method consists of two steps. First, it decomposes the original problem into $$N-1$$ 2-D subproblems, and describes the feasible domain of each subproblem using a closure that does not have redundant constraints. The algorithm considers both linear and quadratic radical constraints, and the feasible domain of every subproblem is the intersection of the discretized constraints from forward, backward and central difference schemes. Second, it solves the original problem by recursively updating the domain of the subproblems twice in two oppressive directions, and guarantees optimality when constraints of every subproblem are peaked ones. Numerical experiments show that this method can not only provide the same solution as the original forward-backward algorithm in peaked-constraint cases with similar time complexity, but also be used to handle general kinodynamic trajectories with a sparse sampling strategy.
Adapted Mapping Estimator in Visual Servoing Control for Model-Free Robotics Manipulator

This paper presents a model-free approach to visual servoing control of a robotic manipulator operated in unknown environments. A mapping estimator with the learning network is applied to visual servoing control of model-free robotic manipulator, which can online estimate the vision-motor relationship in a stochastic environment without knowledge of noise statistics. The dynamic mapping identification problems are solved by incorporating the improved Kalman filtering (KF) and network learning techniques, moreover, an observation correlation updating method is used to estimate the variance of the noises via online learning. Various grasping positioning experiments are conducted to verify the proposed approach by using an eye-in-hand robotic manipulator without calibration.
All-in-One Image Dehazing Based on Attention Mechanism

The objective of image dehazing is to restore the clear content from a hazy image. However, different parts of the same image pose varying degrees of difficulty for recovery. Existing image dehazing networks treat channel and pixel features equally, making it challenging to handle images with non-uniform haze distribution and weighted channels. To address this limitation, we propose a feature attention module for all-in-one image dehazing. The feature attention module comprises channel attention and pixel attention, offering enhanced flexibility in processing different types of information. Specifically, we perform stitching between adjacent layers in the channel dimension during feature extraction. Subsequently, we apply channel attention and pixel attention on the stitching layer with a large channel dimension. To preserve detailed texture features and minimize information loss from the attention mechanism, we use summation operations between the feature layer obtained after each attention operation and the input layer. Our model prioritizes attention to the dense haze region while maintaining overall brightness. Extensive experiments demonstrate that our method surpasses state-of-the-art dehazing techniques in terms of performance, requiring fewer parameters and FLOPs.