Reviewerly/exHarmony huggingface dataset:
A Performance Analysis and Evaluation of SIDH Applied Several Implementation-Friendly Quadratic Extension Fields

It is well-known that quadratic extension fields (QEFs) based on optimal extension fields (OEFs) are typically used for supersingular isogeny Diffie-Hellman (SIDH) key exchange protocol. On the other hand, there is a possibility of the performance improvement of SIDH by employing other attractive choices of QEFs with efficient performing arithmetics which are based on all-one polynomial extension fields (AOPFs) and extension fields with normal basis representation (EFNs). Thus, the authors confirm that the applicability of the new candidates of QEFs for SIDH and evaluate SIDH applied the possible choices of QEFs. As a result of the experiment, the authors found that the performances of SIDH applied the QEFs based on AOPF and EFN are comparable to that of the previous QEF. Moreover, one of the QEFs based on EFN result in a new efficient implementation of the SIDH with SIDH-friendly prime given as p= 2^{e_A}3^{e_B}f+1 where e_A, e_B and $f$ are positive integers.
An approach to an intelligent training system for cochlea implant users - how to motivate hearing

Introduction The combination of digital games and educational tools is a new development in the therapist´s work with hearing-impairments. In the scope of an interdisciplinary research project we aim to develop the prototype of a digital game for cochlea-implant users. We integrate an interactive storytelling design and an educational tool with dynamic difficulty adaption depending on the individual performance of the user.
언간 연구의 국어사적 성과와 전망

The purpose of this study is to review the accomplishments of Eon''gan study in the Language History based on Eon''gan data of Joseon Dynasty and to predict future studies. The main reasons of gathering interest in Eon''gan data are the excavation of family letters such as and and the publication of translated books of Eon''gan. Furthermore, the interpretation book of Eon''gan has played a key role in enhancing the reliability of Eon''gan data. Regarding writing and phonographical matters, palatalization and liquid consonant along with ‘ㆍ’, ‘ㅸ’ and ‘ㅿ’ were main interest. The most active discussion among them is the phenomenon of palatalization, and it is noticeable that not only was the practice of palatalization discussed but also the change by various factors of sociolinguistics was discussed. The grammar part is the most actively discussed among Eon''gan studies. Especially, such matters as nominative marker and relative honorific expressions can be considered as the most meaningful accomplishments in Eon''gan data. In addition, there is active discussion on pronouns, individual ending words and individual morpheme. Studies on vocabulary based on Eon''gan data show high interest in Eon''gan''s own vocabularies that do not appear in printed books. Recently, names of articles, disease related words, unit nouns and names of places are also objects of main interest. Meanwhile, the number of Eon''gan data introduced to the academic world is 3,296, and there is a need for expansion of Eon''gan data through deep learning. There should be active sociolinguistic discussion that can highlight the strengths of Eon''gan data while the necessity of computational linguistics for establishment of corpus is discussed. The difference between males and females can be a future research subject. It is necessary to elaboratize the details of the existing language history through Eon''gan data, along with the description of tentatively named Korean language history of Eon''gan''.
DYNAMIC MACHINE LEARNING TECHNIQUES FOR FEATURE SELECTION UPS AND DOWNS

We know that humans learn from there past experiences and machines follow instructions given byhumans. Humans can train the machines from the past data. That type of learning is called machinelearning. Dataset plays a key role which contains different features. Features are nothing but attributes in atable. For classification model we conside features selection, we may have Ân‟ number of features butselecting best features is a challenging issue now a days. We may require few features among the allfeatures. For feature selection engineering we have a univariate model to select best Âk‟ features from largedataset with Ân‟ features. By working with univariate selection model the accuracy is 92%.
Explainable AI - Visualization of Neuron Functionality in Recurrent Neural Networks for Text Prediction

Artificial Neural Networks are successfully solving a wide range of problems with impressive performance. Nevertheless, often very little or nothing is understood in the workings behind these black ...
Geodesic Kernel embedding Distribution Alignment for domain adaptation

Domain adaptation is a method to classify the new domain accurately by using the marked image of the old domain. It shows a good but a challenging application prospect in computer vision. In this article, we propose a unified and optimized problem modeling method, which is called as Geodesic Kernel embedding Distribution Alignment (GKDA). Specifically, GKDA aims to reduce the domain differences. GKDA avoids degenerated feature transformation by using geodesic kernel mapping feature, and then adjusts the weight of cross-domain instances in the process of dimensionality reduction in principle, finally, constructs a new feature to represent the difference of distribution and unrelated instances. The experiment result shows that GKDA has obvious superiority in cross-domain image recognition.
Visual Tracking by TridentAlign and Context Embedding.

Recent advances in Siamese network-based visual tracking methods have enabled high performance on numerous tracking benchmarks. However, extensive scale variations of the target object and distractor objects with similar categories have consistently posed challenges in visual tracking. To address these persisting issues, we propose novel TridentAlign and context embedding modules for Siamese network-based visual tracking methods. The TridentAlign module facilitates adaptability to extensive scale variations and large deformations of the target, where it pools the feature representation of the target object into multiple spatial dimensions to form a feature pyramid, which is then utilized in the region proposal stage. Meanwhile, context embedding module aims to discriminate the target from distractor objects by accounting for the global context information among objects. The context embedding module extracts and embeds the global context information of a given frame into a local feature representation such that the information can be utilized in the final classification stage. Experimental results obtained on multiple benchmark datasets show that the performance of the proposed tracker is comparable to that of state-of-the-art trackers, while the proposed tracker runs at real-time speed.
Development of a Quick Speech-in-Noise Test in andldquo;Rioplatenseandrdquo; Spanish, Based on Quick -SINandreg;

The development of a quick Speech - in - Noise test, based con Quick SIN, in the Rio de la Plata variant of Spanish is shown, for the measurement of the signal-to-noise ratio. The result was the generation of 8 lists, each of them with 6 sentences, containing 5 keywords that are counted as responses. In the tracks of each list, the phrases are mixed with noise (four-talkers babble with three female speakers and one male) so that each phrase has a signal to noise ratio decreasing, in steps of 5 dB. Three preliminary tests were carried out to select the material to be included in the lists. The first two trials served to select the sentences which are more appropriate to be part of the test while the third test was used to select the best conformation of the lists. The first experiment evaluated the results of the 8 final lists with low pass filtering at 750 Hz, 1400Hz and without filter in normal hearing subjects. The second experiment evaluated the homogeneity of the results of the different lists in groups of normal hearing people and subjects with different levels of hearing impairment.
Geno: A Developer Tool for Authoring Multimodal Interaction on Existing Web Applications

Supporting voice commands in applications presents significant benefits to users. However, adding such support to existing GUI-based web apps is effort-consuming with a high learning barrier, as shown in our formative study, due to the lack of unified support for creating multimodal interfaces. We present Geno---a developer tool for adding the voice input modality to existing web apps without requiring significant NLP expertise. Geno provides a high-level workflow for developers to specify functionalities to be supported by voice (intents), create language models for detecting intents and the relevant information (parameters) from user utterances, and fulfill the intents by either programmatically invoking the corresponding functions or replaying GUI actions on the web app. Geno further supports multimodal references to GUI context in voice commands (e.g. "move this [event] to next week" while pointing at an event with the cursor). In a study, developers with little NLP expertise were able to add multimodal voice command support for two existing web apps using Geno.
Simulating drug effects on blood glucose laboratory test time series with a conditional WGAN

Abstract The unexpected effects of medications has led to more than 14 million drug adverse events reported to the Food and Drug Administration (FDA) over the past 10 years in the United States alone, with a little over 1.3 million of them linked to death, and represents a medical and financial burden on our healthcare. Laboratory tests have the potential to capture inter-individual variability in drug responses, but a significant portion of the patient population has unique treatment pathways that impedes forecasting and optimal decision making. Generative Adversarial Networks (GANs) are flexible implicit generative models that have demonstrated their ability to capture complex correlations in field like computer vision and natural language. Their latent representation capacity is an opportunity for drug effect simulation on laboratory test trajectories. In this paper, we developed and evaluated conditional GANs on glucose laboratory tests in patients exposed to drug combinations and showed a proof of concept for these models in the simulation of unseen drug combinations. By using conditional Wasserstein GANs (WGANs) to simulate drug effects in laboratory tests, we hope to pave the way for novel clinical decision support (CDM) systems and enable the development of better predictive models for rare cohorts of patients.
Humanitarian component of formation of communicative competences of students of technical university

In the article, the authors consider education as a decisive condition for the formation of key personality competencies. The issue of the humanization of technical education is very relevant today. The authors believe that the generation of a technogenic type of culture leads to the spiritual impoverishment of the individual. There is a dehumanization of education, which turns into the development of future engineers only professional skills. The authors believe that the restriction of the humanitarian cycle of disciplines in technical universities casts doubt on the possibility of training engineers who combine high professionalism with well-developed communicative competencies. Particular attention is paid to the place and role of the study of philosophy, which, according to I. Kant, poses its task so that “a person has the courage to live with his own mind.” The authors note that the issue of awareness of oneself as a person, the society in which they live, the values on which relationships between people and children are raised, may arise precisely in the situation if the future engineer is given the opportunity to become acquainted with the philosophy of Platon, Kant or Hegel, with Marx and Heidegger. Most of the students, who are not interested in the issues of the world and the place of the person in it, are the ones who need an explanation of the real state of affairs and those issues that academic philosophy says.The authors reveal the content of the concept of the human factor - that means, first of all, to understand a person, enter the world of his interests, needs, expectations, comprehend many of his actions. , i.e. see his personality. The authors proceed from the fact that the selection of competencies at the moment remains one of the urgent problems of education in the context of a competency-based approach. Accordingly, the purpose of education is related to the formation of key competencies (competencies). It is concluded that the positioning of education (primarily professional) in the field of social meanings depends on the competence content of education.
Deep Doubly Supervised Transfer Network for Diagnosis of Breast Cancer with Imbalanced Ultrasound Imaging Modalities

Elastography ultrasound (EUS) provides additional bio-mechanical in-formation about lesion for B-mode ultrasound (BUS) in the diagnosis of breast cancers. However, joint utilization of both BUS and EUS is not popular due to the lack of EUS devices in rural hospitals, which arouses a novel modality im-balance problem in computer-aided diagnosis (CAD) for breast cancers. Current transfer learning (TL) pay little attention to this special issue of clinical modality imbalance, that is, the source domain (EUS modality) has fewer labeled samples than those in the target domain (BUS modality). Moreover, these TL methods cannot fully use the label information to explore the intrinsic relation between two modalities and then guide the promoted knowledge transfer. To this end, we propose a novel doubly supervised TL network (DDSTN) that integrates the Learning Using Privileged Information (LUPI) paradigm and the Maximum Mean Discrepancy (MMD) criterion into a unified deep TL framework. The proposed algorithm can not only make full use of the shared labels to effectively guide knowledge transfer by LUPI paradigm, but also perform additional super-vised transfer between unpaired data. We further introduce the MMD criterion to enhance the knowledge transfer. The experimental results on the breast ultra-sound dataset indicate that the proposed DDSTN outperforms all the compared state-of-the-art algorithms for the BUS-based CAD.
HDNet: Human Depth Estimation for Multi-Person Camera-Space Localization

Current works on multi-person 3D pose estimation mainly focus on the estimation of the 3D joint locations relative to the root joint and ignore the absolute locations of each pose. In this paper, we propose the Human Depth Estimation Network (HDNet), an end-to-end framework for absolute root joint localization in the camera coordinate space. Our HDNet first estimates the 2D human pose with heatmaps of the joints. These estimated heatmaps serve as attention masks for pooling features from image regions corresponding to the target person. A skeleton-based Graph Neural Network (GNN) is utilized to propagate features among joints. We formulate the target depth regression as a bin index estimation problem, which can be transformed with a soft-argmax operation from the classification output of our HDNet. We evaluate our HDNet on the root joint localization and root-relative 3D pose estimation tasks with two benchmark datasets, i.e., Human3.6M and MuPoTS-3D. The experimental results show that we outperform the previous state-of-the-art consistently under multiple evaluation metrics. Our source code is available at: https://github.com/jiahaoLjh/HumanDepth.
Algoritma K-Medoids Untuk Menentukan Calon Mahasiswa Yang Layak Mendapatkan Beasiswa Bidikmisi di Universitas Budi Darma

Bidikmisi scholarship is a government program to help prospective new students who are academically capable and economically incapable. The Bidikmisi scholarship is a form of tuition assistance and living expenses. Starting in 2018 Budi Darma University began accepting new students through the bidikmisi scholarship path, admission of new students through the bidikmisi path must meet the requirements set by the government. Determination of whether or not a prospective new student is a recipient of bidikmisi based on report cards, school performance, results of selection tests and interviews. During this time the organizers and managers of bidikmisi at Budi Darma University have had difficulty determining prospective students who are truly eligible to receive bidikmisi scholarships in addition to the very limited quota and the large number of prospective students receiving bidikmisi scholarships as well as the value of each criteria for prospective students receiving bidikmisi which is almost the same or similar to one another. To make it easier to determine prospective students receiving the Bidikmisi scholarship, the K-Medoids algorithm is used. K-Medoids algorithm is one of the algorithms in data mining to group data based on the closest criteria value
The Use of Javanese Traditional Games as Learning Media of Writing Javanese Script in The Elementary School

According to the results of the field observations, many elementary school students in Central Java still had difficulty in reading and writing Javanese script.It was caused by teachers' tendency to use the teacher-centered approach in teaching.This approach led the students into being passive.They also felt bored during the learning process.Besides, the use of a teachercentered approach created one-way learning which was unable to trigger students' critical thinking.Based on the finding explained above, some efforts to stimulate Javanese script learning at the elementary level need to be made.One of which is by improving the learning method.The learning method has to be fun and meaningful.Fun learning or so-called joyful learning in this study was conducted by involving traditional Javanese game activities in the learning process.Traditional games which can be used as a learning medium for Javanese script is ABC 5 Dasar game.The use of ABC 5 Dasar game in learning to write Javanese script has many benefit such as (1) being used as a medium for memorizing Javanese characters in a fun way, (2) reducing student anxiety in learning, (3) making learning more meaningful, (4) motivating students not to be afraid of being wrong in writing Javanese script, (5) fostering a sense of solidarity and cooperation, and (6) creating impressive learning which is memorable for the students.
Service Composition in Mobile Ad Hoc Networks (MANET’s) with the Help of Optimal QoS Constraints

In recent year’s usage of mobiles, laptops, PDA’s etc., are greatly increased. Usage of implementation SOA (service oriented architecture) is to increase flexibility in providing the services in MANET’s (Mobile Ad hoc networks). Due to dynamic topology, resource heterogeneity, bandwidth, providing a service provider is a critical challenge. Existing composition services are not suitable for the usage of constraints consideration while choosing a service in the proposed system we uses Response time, throughput, energy consumption, hop count as a QoS constraints to provide the respective services. Based on fuzzy logic we are evaluating rating of a service according to QoS service constraints. From rating we can able to provide the services. Nodes in the MANET’s can provide more than one service. In the simulation results we used to compare our proposed method with the AODV protocol and we got better performance results in respective of average packet delay, Energy constraint, Throughput and Turnaround time.
Continuous Assimilation of Change in Agile Software Development : An empirical study on the role of the knowledge-based resources

As the software value chain is knowledge-based due to the high dependency on people, the lack of practice to manage knowledge as a resource might jeopardize its application in software development. ...
Photo-registration: a novel method for patient registration prior to electromagnetic navigation

Surgical navigation is increasingly used for challenging ENT operations in order to reduce potential complications. To enable the use of navigation, patient registration is conducted to define the patient position relative to the pre-operative imaging data. The most commonly used registration method is tactile registration, where referencing anatomical landmarks are touched with a navigated instrument. With tactile registration, the skin is manipulated, which could affect accuracy. Novel photo-registration technology allows touchless registration using multiple camera scanning and is hypothesized to be more accurate due to the avoidance of skin manipulation and a faster registration process.
Embodied Information in Face-To-Face Interaction

An individual may give information through the linguistic means formally established in society for this purpose, namely, speech or recognized speech substitutes such as writing and pictorial signs or gestures. Ordinarily, however, in using the naked senses to receive embodied messages from others, the individual also makes himself available as a source of embodied information for them. Then, is a second crucial communication condition of face-to-face interaction: not only are the receiving and conveying of the naked and embodied kind, but each giver is himself a receiver, and each receiver is a giver. The linkage of naked senses on side and embodied transmission on the other provides of the crucial communication conditions of face-to-face interaction. Under this condition any message that an individual sends is likely to be qualified and modified by much additional information that others glean from him simultaneously, often unbeknownst to him; further, a very large number of brief messages may be sent.
THE COMPARISON BETWEEN ERROR-LESS LEARNING AND ERRORFUL LEARNING IN VIRTUAL REALITY ON POKÉMON THEME

We discuss the feasibility of cognitive training in the virtual reality (VR) environment by comparing both error-less (EL) and errorful (EF) ways with Pokémon characters as training material. We developed a VR environment for experiencing the procedural and a questionnaire for collecting data. We tested the performance of this application as a preliminary study and received the feedbacks from participants, who are young student. We found firstly that they could be engaged in the cognitive training with Pokémon theme. Secondly, they showed a better training effect under EL condition although they found the training under EF condition more fun than that under EL condition. Thirdly, participants were fond of the VR device as a presenting way. We plan to carry out another experiment with a modified version to collect feedbacks from the healthy elderly. Accordingly, we believe that the proposed approach is acceptable in practice. From this perspective, we expect that our work can benefit the elderly by attracting them to take part in such EL-based exercises.