Reviewerly/exHarmony huggingface dataset:
Histopathology WSI Encoding based on GCNs for Scalable and Efficient Retrieval of Diagnostically Relevant Regions

Content-based histopathological image retrieval (CBHIR) has become popular in recent years in the domain of histopathological image analysis. CBHIR systems provide auxiliary diagnosis information for pathologists by searching for and returning regions that are contently similar to the region of interest (ROI) from a pre-established database. While, it is challenging and yet significant in clinical applications to retrieve diagnostically relevant regions from a database that consists of histopathological whole slide images (WSIs) for a query ROI. In this paper, we propose a novel framework for regions retrieval from WSI-database based on hierarchical graph convolutional networks (GCNs) and Hash technique. Compared to the present CBHIR framework, the structural information of WSI is preserved through graph embedding of GCNs, which makes the retrieval framework more sensitive to regions that are similar in tissue distribution. Moreover, benefited from the hierarchical GCN structures, the proposed framework has good scalability for both the size and shape variation of ROIs. It allows the pathologist defining query regions using free curves according to the appearance of tissue. Thirdly, the retrieval is achieved based on Hash technique, which ensures the framework is efficient and thereby adequate for practical large-scale WSI-database. The proposed method was validated on two public datasets for histopathological WSI analysis and compared to the state-of-the-art methods. The proposed method achieved mean average precision above 0.857 on the ACDC-LungHP dataset and above 0.864 on the Camelyon16 dataset in the irregular region retrieval tasks, which are superior to the state-of-the-art methods. The average retrieval time from a database within 120 WSIs is 0.802 ms.
A Survey on “Machine translation Approaches for Indian Languages”

Translation has always helped India to knit Indians together with respect to its rich culture and literature. Ideas and concepts like ‘Indian ancient literature’,’Indian rich culture’,’Indian philosophy’ and ‘Indian knowledgeable systems’ would have been impossible in the absence of translations with their natural integrationist mission.Machine Translation assist to translate Information presented in one language to other language. Information can be present in form of text, speech and image translating this information helps for sharing of information and ultimately information gain.Translation process is an extremely complex &amp; challenging process. It requires an in-depth knowledge about grammar of both the languages i.e. Source language and Target language to frame the rules for target language generation. Marathi is a regional Indian language and consists of a lot of literature that could be useful if projected in the universal English language. As manual translation is a tedious task, we propose a literature survey about machine translation systems that translates Indian Languages into English Language using various Machine translation approaches like RBMT, SMT, NMT, Hybrid translation
Trend confidence intervals of parameters required for crop growth model (aquacrop) of Epe Lagos State Nigeria

The development of various models such as Aquacrop gives clue to climate smart agriculture. Climatic daily data used include radiation, maximum temperature, minimum temperature, wind speed, relative humidity and precipitation, and they were sourced from the archive of NASA/POWER SRB/ FLASH flux from 1982 to 2018. All the parameters considered have 99 % and 95 % positive confidence intervals and significance levels with Sen’s estimates of 16.92 MJ/M2 .day, 28.90oC, 23.53oC, 1.55 m/s, 85.11 % and 1559.81 mm forradiation, maximum temperature, minimum temperature, wind speed, relative humidity and precipitation with the mean values of 16.90 MJ/M2 .day, 28.13oC, 22.91oC, 1.51 m/s, 82.74 % and 1558.31 mm respectively. Radiation, maximum temperature and wind speed had 44 %, 91 % and 9 % negative down ward trends respectively, while minimum temperature, relative humidity and precipitation have 9 %, 23 % and 139 % positive upward trends respectively as well. Findings show that increase in precipitation over the years keep the water level relatively stable and provides good natural habitat for fishes, aquatic lives and exotic forestry species. The slope gradients were greater than the mean values for all the parameters which signifies strength and fair weather for agricultural activities. The trend patterns show while agricultural activities such as fishing activity and crop production thrive in the study area.Keywords: AquaCrop, Climatic Parameters, Confidence Intervals, FAO, Sen’s slope and Trend Statistics
A starting point for real-time human action detection

Analyzing videos of human actions involves understanding the spatial and temporal context of the scenes. State-of-the-art approaches have demonstrated impressive results using Convolution Neural Networks (CNNs). However, most of them operate in a non-real-time, offline fashion and are not well-equipped for many emerging real-world scenarios, such as autonomous driving and public surveillance. In addition, they are computationally demanding to be deployed on devices with limited power resources (e.g., embedded systems). This paper reviews state-of-the-art methods based on CNN for human action detection and related topics. Following that, we propose an initial framework to efficiently address action detection using flow-guided appearance features. We validate its performance on the UCF-101-24 dataset, and show that the method can achieve real-time action detection with a processing speed of 40 fps.
Integrating Community Interest and Neighbor Semantic for Microblog Recommendation

As a typical characteristic of microblog information, short text length makes a microblog recommendation hard for new users. Moreover, user cold start makes it difficult to explore accurately the interests of microblog users. Therefore, the authors proposed a microblog recommendation model that integrates both of the users' interest from their communities and the semantic from their neighbors' microblogs. Based on the Kullback-Leibler (KL) language model, the proposed model estimated an interest-based language model and a microblog-based language model. Specifically, the interest-based language model was estimated based on both of the user's word set of interest and that of their community interest. Meanwhile, the microblog-based language model was estimated by combining the word set of a microblog, the neighbor semantic, and the microblog set. Real data from Sina Weibo was crawled to evaluate recommendation performance. Results showed that the proposed model outperforms state-of-art models significantly.
The Development Of Crossword Game Media On Virus Material

PENGEMBANGAN MEDIA GAME CROSSWORD PADA VIRUS MATERIALAbstractCrossword game media was a learning tool that serves features to understand the concept and solve a problem. The media provides many features that facilitate students to learn enjoyably. This study aims to develop a viable and effective product to improve students' problem-solving skills and conceptual understanding. The ADDIE model is used as a type of research and development. The subjects were students of X-grade senior high school in Salatiga. Data collection was carried out through observation, questionnaires, and tests. Media experts and material experts carried out the validation of products. Teachers were involved in giving feedback about the practicality of the media. The validation concluded that the product was feasibly based on the media aspect= 85,5% (feasible) and the material aspect = 81,25% (feasible). The product's development has improved problem-solving skills and conceptual understanding effectively that the t-test showed a significant value with acquisition sig. 2 tailed &lt; 0,05. The results indicate that the crossword game was feasible and effective in improving problem-solving skills and conceptual understanding.AbstrakMedia crossword game merupakan salah satu media belajar siswa, menyediakan fitur untuk menjadikan siswa dapat memahami konsep dan memecahkan masalah. Crossword game menyediakan banyak fitur yang memudahkan siswa untuk belajar dengan menyenangkan. Penelitian ini bertujuan untuk mengembangkan produk yang layak dan efektif untuk meningkatkan keterampilan pemecahan masalah dan pemahaman konseptual siswa. Model ADDIE digunakan sebagai penelitian dan pengembangan. Subjek penelitian adalah siswa SMA kelas X di Salatiga. Pengumpulan data dilakukan melalui observasi, kuesioner, dan tes. Validasi produk melibatkan ahli media dan materi. Guru dilibatkan untuk memberikan umpan balik tentang kepraktisan media. Berdasarkan validasi, disimpulkan bahwa produk layak berdasarkan aspek media = 85,5% (layak) dan aspek material = 81,25% (layak). Pengembangan dari produk telah meningkatkan keterampilan pemecahan masalah dan pemahaman konseptual secara efektif sehingga berdasarkan uji-t menunjukkan nilai yang signifikan dengan perolehan sig. 2 tailed &lt;0,05. Hasil menunjukkan bahwa media crossword game layak dan efektif dalam meningkatkan keterampilan pemecahan masalah dan pemahaman konseptual.
TRANSFORMATION OF HIGHER EDUCATION IN SOUTH AFRICA: THE IMPACT OF SOCIAL SYSTEMS

Ponte Academic JournalApr 2021, Volume 77, Issue 4 TRANSFORMATION OF HIGHER EDUCATION IN SOUTH AFRICA: THE IMPACT OF SOCIAL SYSTEMSAuthor(s): Jeremiah MadzimureJ. Ponte - Apr 2021 - Volume 77 - Issue 4 doi: 10.21506/j.ponte.2021.4.7 Abstract:Transformation of higher education in South Africa cannot be accomplished as a separate entity because education is a dependent variable and does not operate in a vacuum. The purpose of this article is to explore the impact of the following social systems, demographic / environmental systems; socio-economic systems in higher education; science and technological systems; language as medium of facilitation, the role of the state in education and cultural diversities in higher education. This article concludes that these systems are relevant for advancement of higher education. If these systems are effectively used in higher education, the quality of education will be enhanced. This article further demostrated that each system entails that there is a transformation in higher education. Download full text:Check if you have access through your login credentials or your institution Username Password
Proposal for a Data Size Saving Office System That Can Be Stored on a Floppy Disk

With the development of computer software and applications, various types of recording media have emerged and evolved. This is a result of the rapid increase in the amount of data created by computers and the constant demand for large-capacity storage media. As large-capacity recording media have become available at low prices, the number of content production without being aware of the data capacity is increasing. Rather, content production often contains unnecessary features and effects for personal use. In this research, we will examine the feasibility of a practical system by carefully selecting the functions required for general use without excessive modification of effects. A floppy disk is used as the recording medium to limit the data size of the system.
Fully automatic, unified stereo camera and LiDAR-camera calibration

Advanced sensor platforms often contain a wide array of sensors in order to collect and process a diverse range of environmental data. Proper calibration of these sensors is important so that the collected data can be interpreted and fused into an accurate depiction of the environment. Traditionally, LiDAR-stereo camera calibration requires human assistance to manually extract point pairs between the LiDAR and the camera system. Here, we present a fully automated technique for calibrating a visible camera system with a 360⁰ field-of-view LiDAR. This calibration is achieved by using the standard planar checkerboard calibration pattern to calculate the calibration parameters (intrinsic and extrinsic) for the stereo camera system. We then present a novel pipeline to determine accurate rigid-body transformation between LiDAR and the stereo camera coordinate systems with no additional experimental setup or human assistance. Our innovation lies in using the planarity of the checkerboard, whose surface coefficients can be estimated relative to the camera coordinates as well as the LiDAR sensor coordinates. We determine the rigid-body transformation between two sets of coefficients of the same calibration surface through least squares minimization. We then refine the estimate through iterative closest point minimization between the 3D points on the checkerboard pattern viewed from the LiDAR and the camera system. Using measurements from multiple views, we increase the confidence in the transformation estimate. The proposed method is less cumbersome and time consuming, unifying the stereo camera and LiDAR-camera calibration in a single step using only one calibration pattern.
Interactive anomaly detection in mixed tabular data using Bayesian networks

The last decades improvements in processing abilities have quickly led to an increasing use of data analyses implying massive data-sets. To retrieve insightful information from any data driven approach, a pivotal aspect to ensure is good data quality. Manual correction of massive data-sets requires tremendous efforts, is prone to errors, and results being really costly. If knowledge in a specific field can often allow the development of efficient models for anomaly detection and data correction, this knowledge can sometimes be unavailable and a more generic approach should be found. This paper presents a novel approach to anomaly detection and correction in mixed tabular data using Bayesian Networks. We present an algorithm for detecting anomalies and offering correction hints based on Jensen scores computed within the Markov Blankets of considered variables. We also discuss the incremental corrections of detection model using user's feedback, as well as additional aspects related to discretization in mixed data and its effects on detection efficiency. Finally we also discuss how functional dependencies can be managed to detect errors while improving faithfulness and computation speed.
Building Relationships: The Process of Creating Game Music

Even more than writing music for film, composing for video games is founded on the principle of interactive relationships. Of course, interactivity is particularly obvious when games use dynamic music systems to allow music to respond to the players. But it is also reflected more generally in the collaborative nature of game music production and the way that composers produce music to involve players as active participants, rather than simply as passive audience members. This chapter will outline the process of creating video game music from the perspective of the composer. The aim is not to provide a definitive model of game music production that applies for all possible situations. Instead, this chapter will characterize the processes and phases of production that a game composer will likely encounter while working on a project, and highlight some of the factors in play at each stage.
Line Segmentation from Unconstrained Handwritten Text Images using Adaptive Approach

Line segmentation from handwritten text images is one of the challenging task due to diversity and unknown variations as undefined spaces, styles, orientations, stroke heights, overlapping, and alignments. Though abundant researches, there is a need of improvement to achieve robustness and higher segmentation rates. In the present work, an adaptive approach is used for the line segmentation from handwritten text images merging the alignment of connected component coordinates and text height. The mathematical justification is provided for measuring the text height respective to the image size. The novelty of the work lies in the text height calculation dynamically. The experiments are tested on the dataset provided by the Chinese company for the project. The proposed scheme is tested on two different type of datasets; document pages having base lines and plain pages. Dataset is highly complex and consists of abundant and uncommon variations in handwriting patterns. The performance of the proposed method is tested on our datasets as well as benchmark datasets, namely IAM and ICDAR09 to achieve 98.01% detection rate on average. The performance is examined on the above said datasets to observe 91.99% and 96% detection rates, respectively.
Bitcoin and Integration Patterns in the Forex Market

Integration patterns between five leading conventional currencies after the US dollar and Bitcoin boost the investment potential of the latter relative to its hedging potential. We document that conditional Bitcoin volatility does not influence its dynamic pairwise correlations whereas the change in volatility of conventional currencies do affect the forex market integration patterns.
중국인 학습자를 위한 한국어 유사 원인·이유 표현의 기술 방안 연구 - ‘-는 바람에’, ‘-(으)ㄴ/는 탓에’와 ‘-는 통에’를 중심으로 -

There are many grammar items that indicate the cause and reason in Korean, and many of them are distinguished from each other by fine differences which used to be difficult for Chinese learners. Among various causes & reasons expressions, ‘-neun barame’, ‘-(eu)n/neun tasse ’ and ‘-neun tonge’ are not only similar in form, but also semantically express the causes or reasons for negative results. Nevertheless, there are quite a few differences between those three expressions in terms of form and syntactic constraints as well as semantic and pragmatic functions. Korean language speakers naturally have the ability to discern differences between those expressions in the process of language acquisition, while Chinese learners will find it difficult to identify the differences between similar grammar items without explicit teaching. However, when looking at the grammatical description of published textbooks, there is a tendency to deal only with the basic usage of the grammar expressions, and it does not provide learners with the constraints, or the similarities and differences between similar grammar items in need to understand and master the usage of a grammar item. Therefore this study aims to find an effective descriptions for similar cause & reason expressions of Korean for Chinese learners. For this purpose, first, this article reviewed previous studies to analyse the form and syntactic constraints, also semantic and pragmatic functions of ‘-neun barame’, ‘-(eu)n/neun tasse’ and ‘-neun tonge’. Next, this article selected representative Korean textbooks published in Korea and China, analysed the descriptions of these three expressions and pointed out the problems need to be improved. Finally, based on those discussions, the principles of grammatical descriptions were defined and the specific descriptions for those three cause & reason expressions were proposed in stages.
On Missing Mass Variance.

The missing mass refers to the probability of elements not observed in a sample, and since the work of Good and Turing during WWII, has been studied extensively in many areas including ecology, linguistic, networks and information theory. This work determines what is the \emph{maximal variance of the missing mass}, for any sample and alphabet sizes. The result helps in understanding the missing mass concentration properties.
Energy Decay Network

This paper and accompanying Python and C++ Framework is the product of the authors perceived problems with narrow (Discrimination based) AI. (Artificial Intelligence) The Framework attempts to develop a genetic transfer of experience through potential structural expressions using a common regulation/exchange value (energy) to create a model whereby neural architecture and all unit processes are co-dependently developed by genetic and real time signal processing influences; successful routes are defined by stability of the spike distribution per epoch which is influenced by genetically encoded morphological development biases.These principles are aimed towards creating a diverse and robust network that is capable of adapting to general tasks by training within a simulation designed for transfer learning to other mediums at scale.
Image Inpainting with External-internal Learning and Monochromic Bottleneck

Although recent inpainting approaches have demonstrated significant improvements with deep neural networks, they still suffer from artifacts such as blunt structures and abrupt colors when filling in the missing regions. To address these issues, we propose an external-internal inpainting scheme with a monochromic bottleneck that helps image inpainting models remove these artifacts. In the external learning stage, we reconstruct missing structures and details in the monochromic space to reduce the learning dimension. In the internal learning stage, we propose a novel internal color propagation method with progressive learning strategies for consistent color restoration. Extensive experiments demonstrate that our proposed scheme helps image inpainting models produce more structure-preserved and visually compelling results.
Naive Bayes for the Evaluation Standard of Officers’ Fitness

In the classification training and assessment of personnel’s physical fitness, the assessment personnel are classified according to the traditional four-level classification method. However, the traditional method often has some problems, such as the standard is fixed, the quantitative investigation is lack, and the personnel classification is not specific, which leads to the training enthusiasm of the training personnel is not high, and the negative training tendency of “long live the pass, one second waste”. In view of this problem, this paper proposes to apply the k-means algorithm to the system of personnel physical fitness assessment standard, analyzes and processes the personnel physical examination results by using the k-means algorithm, and formulates the classification standard according to the overall assessment results.
Methods for Generating Images with Story Scenes Based on a Dataset with Characters

The article describes the generation of images like the Cynic Mansion comics and generation of texts for the scenes. An important part of the research is that the comics should consist of several consecutive scenes with a text description of what is happening. The solution uses GAN networks and color segmentation. A result was obtained for each of the methods, an error analysis was made to make another attempt to achieve a better result. At the end of the study, it is planned to get a result that can help all people make comics as Cynic Mansion ones. The article provides a complete analysis of the use of GAN networks and segmentation for image generation.
THE ROLE OF MATHEMATICAL MODELLING OF PRODUCTION PROBLEMS IN SPECIALIZED SCHOOL

The article discusses the main directions of the development of the educational environment and the role of mathematical modeling of production problems in a specialized school. The key issue of the modernization of education is described - this is improving its quality, bringing it in line with international standards. The emphasis is not on the knowledge gained, but rather on the process of applying this knowledge. The definition of the concept of pedagogical technology is given - this is information technology, since the basis of the technological process of training is the receipt and transformation of information.