Reviewerly/exHarmony huggingface dataset:
Theoretical Framework of Constructivist Web-Based Learning Environment Model to Enhance Mathematical Problem Solving

The purpose of this research was to synthesize theoretical framework of constructivist web-based learning environment model to enhance mathematical problem solving. The design and development research model is employed in this study. The research procedure consists of four main steps: first step document analysis and examination of learning and teaching context. Second step examining and analyzing the related principles and theories such as learning theory, constructivist theories, mathematical problem solving, media theory, and technology. Third step to study instructional context. The fourth step to synthesize the theoretical framework. The result revealed that: the theoretical framework consisted of 7 bases were as follows: (a) Basic contextual: (i) the education core curriculum, (ii) basic mathematics belong learning area of mathematics in secondary high school, (ii) context for high school mathematics learning focused on thinking and mathematical process skills for higher education. (b) Basic of mathematical problem solving: (i) how to solve it of Polya, (ii) problem solving of Krulik and Rudnick (c) Basic teaching sciences: (i) constructivist theory is cognitive constructivism and social constructivism, (ii) cognitive Theory is information processing theory, schema theory, mental model theory, metacognition theory and cognitive load theory. (d) Basics of learning psychology of constructivist learning environment model: (i) OLEs model, (ii) CLEs model, (iii) SOI model, (iv) cognitive apprenticeship, (v) situated learning. (e) Foundations of media theory: (i) media symbol system, (ii) learning with multimedia. (f) Fundamentals of technology: (i) web-based learning environment, (ii) Facebooks, Line, Google Classrooms. (g) Basic of neuroscience.
Students Internet usage: psychological and pedagogical aspects

The article presents the results of studying the psychological characteristics of students in connection with their digital behavior. Authors assume that digital behavior of students can be associated with the features of their self-awareness, self-appraisal and value-semantic sphere. In addition, the importance of individual components in the hierarchy of educational values is studied in connection with personality characteristics. The study involved 102 people - students specializing in the social sciences and humanities. As a result, the authors found that students’ digital behavior in terms of the online presence is associated with their self-awareness, self-appraisal and value-semantic sphere. Students who spend online less than three hours a day will be more active, extroverted and confident in their real life (offline) than those who spend more time online. The importance of individual components in the hierarchy of educational values is associated with the features of self-awareness, self-attitude. Self-appraisal, self-confidence, sense of independence and high appreciation of one’s individuality are associated with a greater intellectual need, a more active and conscious desire to improve their own competence.
SecureGBM: Secure Multi-Party Gradient Boosting

Federated machine learning systems have been widely used to facilitate the joint data analytics across the distributed datasets owned by the different parties that do not trust each others. In this paper, we proposed a novel Gradient Boosting Machines (GBM) framework SecureGBM built-up with a multi-party computation model based on semi-homomorphic encryption, where every involved party can jointly obtain a shared Gradient Boosting machines model while protecting their own data from the potential privacy leakage and inferential identification. More specific, our work focused on a specific "dual--party" secure learning scenario based on two parties -- both party own an unique view (i.e., attributes or features) to the sample group of samples while only one party owns the labels. In such scenario, feature and label data are not allowed to share with others. To achieve the above goal, we firstly extent -- LightGBM -- a well known implementation of tree-based GBM through covering its key operations for training and inference with SEAL homomorphic encryption schemes. However, the performance of such re-implementation is significantly bottle-necked by the explosive inflation of the communication payloads, based on ciphertexts subject to the increasing length of plaintexts. In this way, we then proposed to use stochastic approximation techniques to reduced the communication payloads while accelerating the overall training procedure in a statistical manner. Our experiments using the real-world data showed that SecureGBM can well secure the communication and computation of LightGBM training and inference procedures for the both parties while only losing less than 3% AUC, using the same number of iterations for gradient boosting, on a wide range of benchmark datasets.
Bibliotherapy for Emotional Literacy

One way to help teens manage their emotions is by using emotional literacy. Emotional literacy is a person's ability to understand, express emotions to people, respond to the expression of the feelings of others, and take responsibility for their actions. Emotional literacy can be done through pedagogical strategies, as well as the use of the application of theory and various other learning strategies. Counselors need a method to develop emotional literacy skills in students either by media bibliotherapy or better known as biblikonseling. In this case, the counselor gave the book or story. The utilization of the book as a medium of therapy is called bibliotherapy. Bibliotherapy is psychotherapeutic support through reading material to help someone who is experiencing personal problems. This treatment method is highly recommended, especially for patients who are challenging to express issues verbally. The subjects were students' Universitas Kanjuruhan Malang Department Guidance and Counseling in 2015, 2016. The reason for choosing Guidance and Counseling Student Universitas Kanjuruhan Malang, as guidance and counseling student, is a candidate for school counselors, and they are required to have a good personality and need to be developed early on. This study aims to determine the effectiveness of bibliotherapy techniques to improve the skills of emotional literacy student guidance and counseling Universitas Kanjuruhan Malang. The method used in this study is the technique of pre-experimental design with one group pretest-posttest design. This design is a design study to test the effectiveness of a treatment on an individual basis.
Writing Style Adversarial Network for Handwritten Chinese Character Recognition

The performance of handwritten Chinese character recognition (HCCR) has been greatly improved by using deep learning methods in recent years. But few people pay attention to the influence of writing style on it. In this paper, we aim to improve the performance of HCCR further by weakening the influence of different writing styles. We propose a writing style adversarial network (WSAN) which includes three parts: feature extractor, character classifier and writer classifier. In the training process, we first preprocess raw image with feature extractor. Afterwards, the learned features are fed into both the character classifier and the writer classifier. We apply joint optimization on the top of these two classifiers. Specifically, we minimize the loss value of the character classifier to achieve character recognition function. At the same time, we maximize the loss value of the writer classifier to reduce the influence of writing style in HCCR. The experimental results on CASIA-HWDB1.1 prove that the proposed WSAN has a promoting effect on HCCR. And the experiments on the offline HCCR competition dataset of ICDAR-2013 also give competitive results compared with other methods.
Many-Core Algorithm of the Embedded Zerotree Wavelet Encoder

In the literature, the image compression was implemented using a variety of algorithms; such as vector quantization and subband coding and transform-based schemes. The current problem is that the selection of an image compression algorithm depends on criteria of compression ratio, but the quality of reconstructed images depends on the technology used. Some papers about of the wavelet transform-based coding show this field as an emerging option for image compression with high coding efficiency. It is well known that the new wavelet-based image compression scheme JPEG-2000 has been standardized. This chapter shows the developed novel algorithm executed in parallel using the embedded Zerotree wavelet coding scheme, in which the programs integrate parallelism techniques to be implemented and executed in the many-core system Epiphany III.
Experimental Visualization of Vascular Structures with Microsoft Hololens – Set-Up for Navigated Contrast Agent and Radiation-Sparing Endovascular Procedures (NAV-CARS EVAR)

Introduction - Over the last two decades, endovascular therapy has become an integral part of vascular surgery. One of the most difficulty in learning and performing this minimally invasive therapy is the fact, the vascular surgeon has to mentally overlay the three-dimensional vascular tree with the two-dimensional angiographic scene. While endovascular techniques are improving, the imaging during the procedure is still dependent on contrast agents and X-Rays with their known disadvantages. Looking at actual development trends towards radiation free localization of endovascular tools, the visualization and proper integration of this spatial information will become a key technology. Methods - We report the development of a real-time navigation software, which allows a three-dimensional view of the vascular system without any need of radiation. We used a vascular phantom model (Blue phantom FAST Trauma Full Torso Ultrasound Training Model) and an augmented reality (AR) headset (Microsoft HoloLens) to display the vascular structures in the field of view of the surgeon. Using simple landmark-based surface registration of a CT scan and marching cubes segmentation of the vessel tree, it is straightforward to visualize both the surface and the vessels in the AR display. Using a magnetic tracking system (i.e. AURORA, Northern Digital Inc.) it is possible to also display the position and orientation of a catheter inside the vessels. Results - Our preliminary results of the virtual real time navigation in endovascular procedures are promising. The presented technique allows a three-dimensional holographic view of the vascular system without any need of radiation. Using extrinsic landmark-based calibrations, the virtual objects are precisely aligned with the real world, resulting in a convincing holographic illusion. The prototype also offers the possibility of intervention planning and simulation, which in turn will lead to a reduced learning curve and therefore increased patient safety. Conclusion - The “virtual angioscope” may improve intraoperative visualization, placement of guide-wires and stents. It may reduce the amount of contrast agents and exposure to X-rays.
BERT for Large-scale Video Segment Classification with Test-time Augmentation

This paper presents our approach to the third YouTube-8M video understanding competition that challenges par-ticipants to localize video-level labels at scale to the pre-cise time in the video where the label actually occurs. Ourmodel is an ensemble of frame-level models such as GatedNetVLAD and NeXtVLAD and various BERT models withtest-time augmentation. We explore multiple ways to ag-gregate BERT outputs as video representation and variousways to combine visual and audio information. We proposetest-time augmentation as shifting video frames to one leftor right unit, which adds variety to the predictions and em-pirically shows improvement in evaluation metrics. We firstpre-train the model on the 4M training video-level data, andthen fine-tune the model on 237K annotated video segment-level data. We achieve MAP@100K 0.7871 on private test-ing video segment data, which is ranked 9th over 283 teams.
Energy Minimization over &lt;i&gt;m&lt;/i&gt;-Branched Enumeration for Generalized Linear Subspace Clustering

In this paper, we consider the clustering problem of independent general subspaces. That is, with given data points lay near or on the union of independent low-dimensional linear subspaces, we aim to recover the subspaces and assign the corresponding label to each data point. To settle this problem, we take advantages of both greedy strategy and energy minimization strategy to propose a simple yet effective algorithm based on the assumption that an m-branched (i.e., perfect m-ary) tree which is constructed by collecting m-nearest neighbor points in each node has a high probability of containing the near-exact subspace. Specifically, at first, subspace candidates are enumerated by multiple m-branched trees. Each tree starts with a data point and grows by collecting nearest neighbors in the breadth-first search order. Then, subspace proposals are further selected from the enumeration to initialize the energy minimization algorithm. Eventually, both the proposals and the labeling result are finalized by iterative re-estimation and labeling. Experiments with both synthetic and real-world data show that the proposed method can outperform state-of-the-art methods and is practical in real application.
Automatic Image Enhancement Taking into Account User Preference

In these days, we can take many pictures everyday and everywhere with mobile devices such as smartphones. After taking a picture, we often modify it by using some image enhancement tools so that the appearance of the picture becomes favorable to his/her own preference. However, since there are many parameters in the enhancement functions, it is not an easy task to find an appropriate parameter set to obtain the desired result. Some tools have a function that automatically determine the parameters but they do not take into account the user's preference. In this paper, we present a system to address this problem. Our system first estimates the user's preference by using RankNet. Next, the image enhancement parameters are optimized to maximize the estimated preference. We show some experimental results to demonstrate the usefulness of our system.
Research on the Collection Method of Financial Blockchain Risk Prompt Information from Sandbox Perspective

In view of the low accuracy of the current collection method of financial blockchain risk prompt information, the collection method of financial blockchain risk prompt information under the sandbox view threshold is proposed. Under the sandbox vision, the parser parses the URL of financial blockchain risk prompt message and USES the buron filtering algorithm to de-weight the URL. The URL after weight removal is added into the library to be crawled, and the crawling URL is clustered by using the clustering algorithm to calculate the similarity between URL and noise URL in the cluster, and the URL with high similarity is removed. The web crawler collects the URL queue after denoising, saves the collected URL to the database, and runs the URL resolution program to complete the collection of risk warning information. Through the comparison test with the current information collection method, it proves that the designed method of financial block chain risk prompt information collection under the sandbox vision threshold has higher collection accuracy and advantages.
Potential applications of quantum computing in upstream

Summary Advancements in nano-fabrication as well as improved control over quantum states has brought quantum technologies to the technological readiness level where large business took increased interest in this technology and started playing an active role in its development. Perhaps as a result of that, quantum computing has received a lot of media attention in the recent years, which makes it very important to understand what quantum computers (once sufficiently powerful one gets built) could or could not do and separate science from the hype which starts to surround this field. In this talk I will attempt to address these opportunities as well as challenges and suggest a few possible areas within upstream business where quantum computing could make an impact.
On the issue of fuzzy timing estimations of the algorithms running at GPU and CPU architectures

We consider the task of comparing fuzzy estimates of the execution parameters of genetic algorithms implemented at GPU (graphics processing unit’ GPU) and CPU (central processing unit) architectures. Fuzzy estimates are calculated based on the averaged dependencies of the genetic algorithms running time at GPU and CPU architectures from the number of individuals in the populations processed by the algorithm. The analysis of the averaged dependences of the genetic algorithms running time at GPU and CPU-architectures showed that it is possible to process 10’000 chromosomes at GPU-architecture or 5’000 chromosomes at CPUarchitecture by genetic algorithm in approximately 2’500 ms. The following is correct for the cases under consideration: “Genetic algorithms (GA) are performed in approximately 2, 500 ms (on average), ” and a sections of fuzzy sets, with a = 0.5, correspond to the intervals [2, 000.2399] for GA performed at the GPU-architecture, and [1, 400.1799] for GA performed at the CPU-architecture. Thereby, it can be said that in this case, the actual execution time of the algorithm at the GPU architecture deviates in a lesser extent from the average value than at the CPU.
A FIJI Macro for quantifying pattern in extracellular matrix

Abstract Diverse extracellular matrix patterns are observed in both normal and pathological tissue. However, most current tools for quantitative analysis focus on a single aspect of matrix patterning. Thus, an automated pipeline that simultaneously quantifies a broad range of metrics and enables a comprehensive description of varied matrix patterns is needed. To this end we have developed an ImageJ plugin called TWOMBLI, which stands for T he W orkflow O f M atrix B io L ogy I nformatics. TWOMBLI is designed to be quick, versatile and easy-to-use particularly for non-computational scientists. TWOMBLI can be downloaded from https://github.com/wershofe/TWOMBLI together with detailed documentation. Here we present an overview of the pipeline together with examples from a wide range of contexts where matrix patterns are generated.
EMOTIONAL ORIENTATION IN THE STRUCTURE OF FACILITATIVE ACTIVITY OF FUTURE PSYCHOLOGISTS

The article presents theoretical substantiation and empirical research of the development of emotional orientation in the structure of facilitation activities of future psychologists. The development of students-psychologists’ readiness for facilitative activities and related problemsd are actualized. In the context of facilitate support it is possible to provide the full development of future psychologists’ facilitative abilities: self-actualization, comprehension of life, internal motivation, reflexivity, self-esteem and self-understanding, authenticity, empathy, self-confidence, responsibility, the ability to accept, respect and understand others; the ability to create special conditions for personal development. The essential basis for psychologists-facilitators’ professional formation is their professional self-determination, which correlates with meanings of their personal self-determination.&nbsp; An individual’s emotional orientation is an indicator of future specialists’ value and general orientations. We analyzed B.I Dodonov’s approach, according to which individuals’ emotional orientations are determined by their need in emotional colouring of their actions, when individuals’ experiences pbtain self-sufficient values; and it expressed in individuals’ activities, motivates them and influences a professional choice and professional procedural moments. Our empirical study was based on B.I Dodonov’s classification of value emotions: altruistic emotions, communicative emotions, glorious emotions, praxic emotions, pugnantic emotions, romantic emotions, gnostic emotions, aesthetic emotions, hedonistic emotions, and acquisitive emotions. The empirical study of future psychologists’ emotional orientations shows that the studied students are mostly characterised by high altruistic, hedonistic, communicative and romantic emotional orientations. We can assume that these particular features of future psychologists’ emotional orientation correspond to the essence and structure of their facilitation activities and, in the future, they will help ensure their work effectiveness. &nbsp
Parallels Between Phase Transitions and Circuit Complexity

In many natural average-case problems, there are or there are believed to be critical values in the parameter space where the structure of the space of solutions changes in a fundamental way. These phase transitions are often believed to coincide with drastic changes in the computational complexity of the associated problem. \n In this work, we study the circuit complexity of inference in the broadcast tree model, which has important applications in phylogenetic reconstruction and close connections to community detection. We establish a number of qualitative connections between phase transitions and circuit complexity in this model. Specifically we show that there is a $\mathbf{TC}^0$ circuit that competes with the Bayes optimal predictor in some range of parameters above the Kesten-Stigum bound. We also show that there is a $16$ label broadcast tree model beneath the Kesten-Stigum bound in which it is possible to accurately guess the label of the root, but beating random guessing is $\mathbf{NC}^1$-hard on average. The key to locating phase transitions is often to study some intrinsic notions of complexity associated with belief propagation \--- e.g. where do linear statistics fail, or when is the posterior sensitive to noise? Ours is the first work to study the complexity of belief propagation in a way that is grounded in circuit complexity.
Analysis of the SA-like selection operator in differential evolution-simulated annealing (DESA) optimization algorithm

This paper presents a mathematical analysis of the hybrid algorithm DESA, a combination of Di↵erential Evolution (DE) and Simulated Annealing (SA) algorithm. DESA is a DE-based algorithm with SA-like selection operator. The discussion includes the detailed algorithmic frameworks and characteristics of the DESA-population and its comparison with the classical DE algorithm.
Learning Norms from Stories: A Prior for Value Aligned Agents

Value alignment is a property of an intelligent agent indicating that it can only pursue goals and activities that are beneficial to humans. Traditional approaches to value alignment use imitation learning or preference learning to infer the values of humans by observing their behavior. We introduce a complementary technique in which a value aligned prior is learned from naturally occurring stories which encode societal norms. Training data is sourced from the childrens educational comic strip, Goofus and Gallant. In this work, we train multiple machine learning models to classify natural language descriptions of situations found in the comic strip as normative or non normative by identifying if they align with the main characters behavior. We also report the models performance when transferring to two unrelated tasks with little to no additional training on the new task.
Informative Path Planning (IPP)

The previous chapter presented a school of path planning algorithms that focuses on wide-area coverage or, in some cases, exhaustive area coverage as well. This chapter takes a slightly different approach. In this chapter, a new class of path planning algorithms is summarized, called Informative Path Planning (IPP), or alternatively known as Information Theoretic Path Planning. In this setting, the agent or the robot explores the environment of interest by following the gradient of information.