Reviewerly/exHarmony huggingface dataset:
Biomedical Images Processing Using Maxeler DataFlow Engines

Image segmentation is one of the most common procedures in medical imaging applications. It is also very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of region of interest from a breast image, after which the identification of suspicious mass regions, their classification, and comparison with the existing image database follows. It is often the case that already existing image databases have large sets of data for which processing requires a lot of time, thus the acceleration of each of the processing stages in breast cancer detection is a very important issue. Image filtering is also one of the most common and important tasks in image processing applications. It is, in most cases, preprocessing procedure for 3D visualization of an image stack. In order to achieve high-quality 3D visualization of a 2D image stack, it is of particular importance that all the images of the input stack are clear and sharp, thus their filtering should be executed carefully. There are also many algorithms for 3D visualization, so it is important to choose the right one which will execute fast enough and produce satisfied quality. In this chapter, the implementation of the already existing algorithm for region-of-interest-based image segmentation for mammogram images on High-Performance Reconfigurable DataFlow Computers (HPRDC) is proposed. As a DataFlow Engine (DFE) of such HPRDC, Maxeler’s acceleration card is used. The experiments for examining the acceleration of that algorithm on the Reconfigurable DataFlow Computers (RDC) are performed with two types of mammogram images with different resolutions. There were, also, several DFE configurations and each of them gave different acceleration of algorithm execution. Those accelerations are presented and experimental results have been shown good acceleration. Also, image processing using a mean filtering algorithm combined with thresholding and binarization algorithms and 3D visualization of murine lungs using marching cubes method are explained. These algorithms are mapped on the Maxeler’s DFE to significantly increase calculation speed. Optimal algorithm calculation speed was up to 20-fold baseline calculation speed.
Fast Light Field Disparity Estimation via a Parallel Filtered Cost Volume Approach

The Guided Light Field Cost Volume (GLFCV) is a light field disparity estimation algorithm designed for (GPU) parallelization by refactoring the process, such that costly optimizations that combine and refine depth maps are simplified. The algorithm involves shearing the light field over a range of disparities and computing a cost volume for each sheared sub-aperture image. A guided filter is then run on the computed cost for each disparity. For the final disparity estimate, each pixel is assigned disparity associated with the lowest filtered cost. Execution time and accuracy were evalulated on Lytro Illum imagery and also on synthetic light fields from the HCI 4D light field benchmark. The approach presented executes in four seconds (on an NVIDIA Titan XP), with only 10% of pixels in the disparity estimate deviating from ground truth. This compares favourably to existing accurate approaches, whose execution time is in the order of minutes.
L' idioma gentile di Edmondo De Amicis nella didattica dell’italiano (1868-1940)

On the basis of studies on Italian teaching after Italian Unification, this paper analyzes the dissemination of Edmondo De Amicis’ literary works in scholastic handbooks published between 1868 and 1940. This study aims also to focus on the pedagogical and linguistic finalities of these Deamicisian extracts. Grammars, writing handbooks, anthologies and reading books show that De Amicis’ Cuore is not his only literary work incorporated in the scholastic canon, which actually includes many other works, whose extracts are used for different purposes. Furthermore, this overview shows that the relationships between linguistic standard and author’s language, even though exemplary, have not always exploited the linguistic peculiarities of the literary text. In extreme cases, the original text is modified to adapt it to the new linguistic and pedagogical standard.
Iterative Relation Reasoning for Multiple Object Recognition

Abstract We present a novel model for multiple object recognition. Our model combines current deep learning recognition systems with object category relation information. This model is mainly inspired by spatial memory network [1], which treats multiple object recognition task as an iterative process, reusing some region feature as context information. We extend this work by presenting a statistical-based category relation model to measure object category semantic relevance. With the spatial memory and category relation model as relation reasoning modules, our model takes in context information. Our model achieves 4.4% per-instance and 4.9% per-class absolute improvement of average classification accuracy over plain convolutional neural networks on ADE dataset.
The Effect of Team Work Quality on Team Performance in Global Software Engineering

Global software engineering (SE) has increased in popularity and is now commonplace in most software organizations. This is due to the fact that business and technology have evolved, which has had an impact on the borderless world. As a consequence, software teams are often geographically dispersed, though they all have the same goal—to produce high-quality software. In order to achieve that goal, quality teamwork is important to build a high-performance team. This study aims to get an in-depth understanding of what quality teamwork is, as well as investigate how communication and socialization can have an impact on team performance. This study took a qualitative approach to the data collection process by carrying out interviews with three experts of agile distributed teams. The results of this study demonstrate that active communication stimulates socialization, and thus increases and maintains morale and motivation among team members. Future studies could focus on the impact of other quality teamwork, such as the influence of trust on team performance among global SE teams.
Memory-Enhanced Abstractive Summarization

The RNN network has been widely investigated in automatic abstractive summarization and has achieved good results in previous studies. However, in the process of processing and storing information in the RNN structure, the problem of losing long-term information may occur, resulting in the inability to generate high-quality summaries containing comprehensive information about the corresponding documents. In this paper, in order to overcome this problem as well as enhance the global information, we propose a memory-enhanced abstractive summarization (MEAS) model consisting of a memory enhancement module and a Seq2Seq module. Our model is able to capture and store global information about the entire document, such as the relationship between sentences and sentences, resulting in a richer representation of information to the Seq2Seq module to generate higher quality summaries. Our experimental results indicate that on the CNN/DailyMail corpus, our MEAS model achieve improvements of up to 1.17, 0.27 and 0.85 on the R-1, R-2, and R-L score, respectively, when compared with the related state-of-the-art baseline.
TEACHER’S PROBLEMS IN TEACHING ENGLISH USING 2013 CURRICULUM 2017 REVISION AT SMK MUHAMMADIYAH 3 BANJARMASIN

This research discussed Teacher's Problems in Teaching English Using the 2013 Curriculum 2017 Revision at SMK Muhammadiyah 3 Banjarmasin. This research used a Case Study using the Descriptive Qualitative method. The technique of Data Collection here was the interview. The result of this research indicated that English teacher faced some problems relating to assessment, the primary condition of students, growing of PPK (Penguatan Pendidikan Karakter), growing literacy, growing 4C (Creative, Critical Thinking, Communicative, Collaborative), which lead them to be creative, critical in thinking, and also in growing HOTS (Higher Order of Thinking Skill). They were less explanation or description about assessment, the students' ability in English was low, the lack of teaching time and information, the transition of students from SMP to SMK, the students' lack of vocabulary, the students were not through filtering. There were some solutions to the teacher's problems . First, learning should develop for better quality, so all essential aspects of the latest curriculum revision are covered when learning. The second is to report or consult the problems in implementation to the principal. The third is to invite an expert in the English Curriculum when the MGMP of English cannot solve it. The fourth is to handle the problems by the teacher and students internally.
ImaGAN: Unsupervised Training of Conditional Joint CycleGAN for Transferring Style with Core Structures in Content Preserved

This paper considers conditional image generation that merges the structure of one object with the style of another. In short, the style of an image has been substituted or replaced by the style of another image. An architecture for extracting the structure of one image and another architecture for merging the extracted structure and the style of another image is considered. The proposed ImaGAN architecture consists of two networks: (1) style removal network R that removes style information and leaves only the edge information and (2) the generation network G that fills the extracted structure with the style of another image. This architecture allows various pairing of style and structure which would not have been possible with image-to-image translation method. This architecture incurs minimal classification error compared prior style transfer and domain transfer algorithms. Experimental result using edges2handbags and edges2shoes dataset reveal that ImaGAN can transfer the style of one image to another without distorting the target structure.
Image Super-Resolution based NCSs Model with Packet Loss

Abstract There are many ways to super-resolution reconstruction of a single image. This method require the association between low-resolution images and high-resolution images, and has achieved good results in different applications. This article also pursues the correlation between low-resolution images and high-resolution images, but we combine images with linear networks to explore the possibilities of combining the two domains. In order to achieve the purpose of restoring image details, we used a method of combining image and network, different from the traditional single-picture super-resolution, we using network delay and packet loss compensation, fully retain the data packets before and after, and find the internal similarity from low-resolution images. Experiments show that inputting images into a network system is affected by system packet loss and has a large impact. It also shows that it is feasible and effective to combine images with network packet loss in the networked control systems model, and specific image effects will be shown in the paper. Our algorithm has achieve a certain expected effect, by superimposing the image super-resolution reconstruction is more extensive, and it is also convenient for future research based on image super-resolution.
Application of Overhauser Magnetometers in the Search for Ore and Placer Gold and Diamonds Deposits

Summary We present the results of using modern nuclear precession magnetometers based on the Processor Overhauser Sensor overhead processor POS sensor for the study of primary and loose gold and diamond deposits in various regions of Russia and in the Republic of Angola. The developed method of the pedestrian magnetic survey with the definition of coordinates using a GPS navigation receiver allows you to effectively isolate the field from lowcontrast magnetic objects against the background of more extensive and intensive anomalies of the geological environment. A ground magnetic survey is effective in detailing and sorting out the anomalies detected using aeromagnetic survey when searching for primary and loose diamond deposits. Micromagnetic anomalies detected as a result of detailed shooting in continuous mode make it possible to localize heterogeneities of the geological structure in the upper part of the section.We present the results of using modern nuclear precession magnetometers based on the Processor Overhauser Sensor for the study of ore and placer gold and diamond deposits in various regions of Russia and in Angola. The developed method of the ground magnetic survey with GPS navigation receiver allows you to effectively separate the field from low-contrast magnetic objects on the background of more intensive anomalies of the geological environment. A ground magnetic survey is effective in detailing and separating the anomalies detected using aeromagnetic survey. Micromagnetic anomalies makes possible to localize geological structures in the upper part of the geological section.
Methods of teaching by means of informational technology for geometry lessons in 10th grade

This article is about teaching methods by means of IT. The given examples are all about different teaching methods of incorporating IT in the process of studying geometry in 10th grade. In the final part the authors came to the conclusion made on the basis of showcased material.
Education of University Student Staff Members through Implementation of a Regional Vitalization Event

The need for a regional vitalization event to develop local society is increasing, and trials in cooperation with universities, communities, and self-governing bodies are performed actively to resolve this. In research seeking a solution to the problem of human resource education, which each local self-governing body holds, the education of enthusiastic and motivated leaders has been identified as a necessity. Authors planned and implemented the 10th commemoration event in the children′s science school for regional vitalization with university students. To continue this event, an enthusiastic and motivated leader is needed. This article reports on how students felt and grew after the implementation of this event.
Towards an Upper Ontology and Hybrid Ontology Matching for Pervasive Environments

Pervasive environments include sensors, actuators, handheld devices, set of protocols and services. The specialty of this environment is its power to manage with any device at any time anywhere and work autonomously for providing customized services to user. The different entities of pervasive environment collaborate with each other to accomplish an objective by sharing data among them. It raises an interesting problem called semantic heterogeneity. To address this problem, a hybrid ontology matching technique which combines direct and indirect matching techniques is proposed in this paper. To share and integrate data semantically, ontology matching technique establishes a semantic correspondence among various entities of pervasive application ontologies. To find the efficiency of proposed approach, we carried out set of experiments with real world pervasive applications. Experimental results prove that the proposed approach shows excellent performance in hybrid ontology matching. Results also proved that the use of background knowledge has influence over the performance of ontology matching technique.
Efficient, Risk-Encoding Octrees for Path Planning with a Robot Manipulator

Recent research in robotics envisions shared human-robot workspaces to combine individual advantages of humans and robots. As part of this vision, robot manipulators must avoid collisions with humans and other a priori unknown obstacles in the shared workspace. State-of-art approaches (e.g. certainty grids, bounding volume hierarchies) test robot poses for collisions under individual limitations (e.g. memory or processing overhead, assumption of global views or noiseless sensors). In contrast, we contribute a sample-based pose test alongside a hierarchical representation of risk over the shared workspace. Our contribution has low memory and processing overhead, and allows for local, outdated, or noisy sensor views. Experiments with real-world data validate this claim and show advantages and limits of our approach over competing variants. We conclude that our pose test and risk representation enhance real-time path planning for robot manipulators in current and future use cases.
Smart Technologies’ Application for International Taxation

This paper describes an innovative application of smart technologies to administration of taxation in accordance with the new transfer pricing rules, recently introduced by the Organization of Economic Cooperation and Development (OECD) in 2015. The new rules, introduced by the OECD, relate not only to the tax legislation of the 36 OECD countries - the total number of countries that currently are modifying their taxation rules is 116. This paper describes the innovative tax administration system - the ONESOURCE BEPS Action Manager system; it complies with the most recent OECD rules and regulations in international taxation. The results of system analysis, design, development, testing and pilot utilization by a multinational enterprises, and a summary of the obtained user feedback are presented in the paper.
22‐1: Image Enhancement with Visual Saturation Preserving on Adaptive Histogram Model

A novel algorithm based on histogram equalization (HE) is proposed, which has saturation preservation and obtain more suitable visual perception. This method can solve the problem of visual perception saturation decrease and color distortion caused by conventional histogram methods. The results show excellent performance in LDR image enhancement.
Research on the Image Feature Matching Technology and Its Application in the Computer Vision System

The research content of the computer vision includes the imaging equipment and the digital equipment. The ultimate goal of the computer vision is to enable the computers, like the human beings, to observe and understand the world through the vision and have the ability to adapt to the environment independently. With the rapid development of the mobile Internet technology, the digital storage devices and the computer communication devices, we should have the abilities to browse and select the image data that people are interested in from the massive image database, and extract the structured and the meaningful logic, entity and even the relational network from these unstructured data, so as to forecast the trend of the social groups and the individual behaviors.
Practice of Social Implementation Education through Product Development in Collaboration with Industry, Academia, and Government

This report describes the results of social implementation education program through the product development in collaboration with agriculture, industry, academia, and government from 2016-2017. As many as 10 groups of these organizations were involved in this program. Embarking students in this program led to improve and accelerate the collaboration of agriculture, industry and government. As a result, the students participated in this program realized the necessity of engineering for industry. Furthermore, this program contributed to change the consciousness of students that some of them decided to deepen their study by entering further education or take employment in the home-grown company participated in this program. In this report, I discussed about the process, methods and important points when collaborating with students and showed the effectiveness of collaboration on social implementation education.
57‐1: <i>Invited Paper:</i> AirTouch System: Hand Skeleton Modelling for Augmented HMI Interactions

This paper presents a high‐performance capacitive touch system enhanced by a 3D vision‐based engine, the "AirTouch". The system is based on multiple 3D cameras that analyze the 50 cm near‐field volume above the screen surface. A real‐time 50 Hz 3D reconstruction engine with millimetric precision enables the sensing and tracking of several users and multiple hands or objects. The system identifies a preliminary set of hand poses: open palm, closed fist and pointing. For the pointing pose, the pointing target is estimated. It also determines the hand location, angle and movement of the fingers through advanced algorithms. The system aims to characterize the skeleton key elements including joints and segments of the hand, and reconstruct its mechanical properties (movement restrictions, angle correlations, etc.).
Fostering Foreign Language Learning Through a Telecollaborative Social Media-Based Tandem Language Learning Approach

Traditional tandem language learning (involving two students learning each other’s mother tongue) is not a new concept. In fact, it has long been practiced in foreign language classrooms. However, a tandem approach involving learners of different countries using social media is something that has not been fully understood. Theoretically speaking, language acquisition occurs when rich comprehensible input is provided to language learners. Unfortunately, not all language learning contexts can provide this vital input, primarily owing to an inadequate language proficiency level of both teachers and students. In fact, this situation is not uncommon in the English as a Foreign Language (hereafter EFL) context. As a result, foreign language learning is hampered or impeded and little learning can occur, if at all. This paper argues that employing a telecollaborative social media-based tandem language learning approach could help to provide the missing input. With this approach, language learners of different linguistic backgrounds (i.e. native English speakers learning Indonesian and native Indonesian speakers learning English) work collaboratively using social media and assist one another in their learning - following the principle of mutual benefit and reciprocity. Teachers of both groups work together to design learning activities for the students with the aim being to provide ample opportunity for language learners to interact with native speakers of the target language and receive comprehensible input accordingly. Thus, a tandem approach by means of social media, such as Facebook, could help provide input critical to foreign language learning at times when input from the language learning environment is so inadequate. More importantly, a tandem language learning approach is compatible with and attuned to contemporary language learning theories such as Language Acquisition Theory and Constructivism. Finally, a tandem approach also promotes a fruitful collaboration among a wide array of educational institutions worldwide which, in turn, foster an international collaboration and networking.
Exploring Active Learning for Student Behavior Classification

Selection of high-quality ground truth data is a critical step for machine learning. Conventionally, a human-centered strategy is utilized to label the data. While this technique provides accurate annotations of task-specific behaviors, it is difficult, costly and error-prone. One method explored to solve these problems is active learning, a model-centered approach that minimizes human involvement. In this work, we conduct an experiment to compare the performance of active learning and passive learning strategies in selecting ground truth data for a classification task to detect the incidence of task persistent behavior from students' interaction logs. Our findings suggest that active learning tends to be more effective and efficient than passive learning in achieving a certain level of performance. However, the overall performance comparison shows that passive selection for ground truth data is as effective as the active learning approach for applications with relatively small sample size.