Reviewerly/exHarmony huggingface dataset:
Human Activity Recognition Using Semi-supervised Multi-modal DEC for Instagram Data

Human Activity Recognition (HAR) using social media provides a solid basis for a variety of context-aware applications. Existing HAR approaches have adopted supervised machine learning algorithms using texts and their meta-data such as time, venue, and keywords. However, their recognition accuracy may decrease when applied to image-sharing social media where users mostly describe their daily activities and thoughts using both texts and images. In this paper, we propose a semi-supervised multi-modal deep embedding clustering method to recognize human activities on Instagram. Our proposed method learns multi-modal feature representations by alternating a supervised learning phase and an unsupervised learning phase. By utilizing a large number of unlabeled data, it learns a more generalized feature distribution for each HAR class and avoids overfitting to limited labeled data. Evaluation results show that leveraging multi-modality and unlabeled data is effective for HAR and our method outperforms existing approaches.
Information Technology Issues in Canada

The information technology (IT) industry is an irrevocable part of the Canadian economy. It has adapted well to the needs of the global market. Security and privacy are considered top-organizational issues. This is not surprising since ensuring security is vital for the widespread adoption of IT products and services. The Canadian public has always been concerned with their privacy, which was reflected in the present study. Networks and telecommunications are considered top-technology issues, followed by virtualization and enterprise application integration. Overall, a majority of Canadian IT professionals are satisfied with their jobs and report an acceptable level of work pressure, work–life balance, workload, and burnout. Nevertheless, some are likely to leave their current organizations. Despite a high demand on IT jobs, some IT workers may also leave the IT profession.
Joint Embedding of Words and Category Labels for Hierarchical Multi-label Text Classification

Text classification has become increasingly challenging due to the continuous refinement of classification label granularity and the expansion of classification label scale. To address that, some research has been applied onto strategies that exploit the hierarchical structure in problems with a large number of categories. At present, hierarchical text classification (HTC) has received extensive attention and has broad application prospects. Making full use of the relationship between parent category and child category in text classification task can greatly improve the performance of classification. In this paper, We propose a joint embedding of text and parent category based on hierarchical fine-tuning ordered neurons LSTM (HFT-ONLSTM) for HTC. Our method makes full use of the connection between the upper-level and lower-level labels. Experiments show that our model outperforms the state-of-the-art hierarchical model at a lower computation cost.
PEDAGOGICAL PLATFORM FOR THE DEVELOPMENT OF PROFESSIONAL AND SPIRITUAL QUALITIES OF FUTURE DOCTORS

&#x0D; &#x0D; &#x0D; The article considers the effective impact of professional and spiritual qualities on the life of society in the future, and in connection with this the need to improve the educational system in higher educational institutions and expand its methodological support. It is also said that the development of professional and spiritual qualities of students of medical universities is a complex, lengthy and consistently developing process that requires the cooperation of all participants in the educational process - the teaching staff and students.&#x0D; &#x0D; &#x0D;
On the normalized power prior

The power prior is a popular tool for constructing informative prior distributions based on historical data. The method consists of raising the likelihood to a discounting factor in order to control the amount of information borrowed from the historical data. It is customary to perform a sensitivity analysis reporting results for a range of values of the discounting factor. However, one often wishes to assign it a prior distribution and estimate it jointly with the parameters, which in turn necessitates the computation of a normalising constant. In this paper we are concerned with how to recycle computations from a sensitivity analysis in order to approximately sample from joint posterior of the parameters and the discounting factor. We first show a few important properties of the normalising constant and then use these results to motivate a bisection-type algorithm for computing it on a fixed budget of evaluations. We give a large array of illustrations and discuss cases where the normalising constant is known in closed-form and where it is not. We show that the proposed method produces approximate posteriors that are very close to the exact distributions when those are available and also produces posteriors that cover the data-generating parameters with higher probability in the intractable case. Our results show that proper inclusion the normalising constant is crucial to the correct quantification of uncertainty and that the proposed method is an accurate and easy to implement technique to include this normalisation, being applicable to a large class of models. Key-words: Doubly-intractable; elicitation; historical data; normalisation; power prior; sensitivity analysis.
Model Compression for ResNet via Layer Erasure and Re-training

Residual Networks with convolutional layers are widely used in the field of machine learning. Since they effectively extract features from input data by stacking multiple layers, they can achieve high accuracy in many applications. However, the stacking of many layers raises their computation costs. To address this problem, we propose Network Implosion, it erases multiple layers from Residual Networks without degrading accuracy. Our key idea is to introduce a priority term that identifies the importance of a layer; we can select unimportant layers according to the priority and erase them after the training. In addition, we retrain the networks to avoid critical drops in accuracy after layer erasure. Our experiments show that Network Implosion can, for classification on CIFAR10/100 and ImageNet, reduce the number of layers by 24.00% ～ 42.86% without any drop in accuracy.
Stochastic Neighbor Embedding of Multimodal Relational Data for Image-Text Simultaneous Visualization

Multimodal relational data analysis has become of increasing importance in recent years, for exploring across different domains of data, such as images and their text tags obtained from social networking services (e.g., Flickr). A variety of data analysis methods have been developed for visualization; to give an example, t-Stochastic Neighbor Embedding (t-SNE) computes low-dimensional feature vectors so that their similarities keep those of the observed data vectors. However, t-SNE is designed only for a single domain of data but not for multimodal data; this paper aims at visualizing multimodal relational data consisting of data vectors in multiple domains with relations across these vectors. By extending t-SNE, we herein propose Multimodal Relational Stochastic Neighbor Embedding (MR-SNE), that (1) first computes augmented relations, where we observe the relations across domains and compute those within each of domains via the observed data vectors, and (2) jointly embeds the augmented relations to a low-dimensional space. Through visualization of Flickr and Animal with Attributes 2 datasets, proposed MR-SNE is compared with other graph embedding-based approaches; MR-SNE demonstrates the promising performance.
THE PORTRAY OF AUTISTIC INDIVIDUALS IN ONLINE NEWS ARTICLE DISCOURSE: A CRITICAL DISCOURSE ANALYSIS

The paper reports on the negative portrayal of autistic individuals in online news articles.It investigates the way such easily accessible global discourse can portray a sensitive group, namely, the autistic individuals.The focus is on the ideological content of online news about autism, using Van Leeuwen's social actor determination approach.The analysis of ten online news articles from the BBC News leads to the identification of a real social problem.Although the online articles analyzed portray autistic individuals in a broad context, their status is imbued with several other (social) roles that have ideological negative connotations.Such negativity is a critical issue for family members and caretakers of autistic individuals who struggle with this negative image when trying to adapt to living and caring for an autistic individual.
An Automated Approach for Constructing Framework Instantiation Documentation

A substantial effort, in general, is required for understanding APIs of application frameworks. High-quality API documentation may alleviate the effort, but the production of such documentation still poses a major challenge for modern frameworks. To facilitate the production of framework instantiation documentation, we hypothesize that the framework code itself and the code of existing instantiations provide useful information. However, given the size and complexity of existent code, automated approaches are required to assist the documentation production. Our goal is to assess an automated approach for constructing relevant documentation for framework instantiation based on source code analysis of the framework itself and of existing instantiations. The criterion for defining whether documentation is relevant would be to compare the documentation with an traditional framework documentation, considering the time spent and correctness during instantiation activities, information usefulness, complexity of the activity, navigation, satisfaction, information localization and clarity. We propose an automated approach for constructing relevant documentation for framework instantiation based on source code analysis of the framework itself and of existing instantiations. The proposed approach generates documentation in a cookbook style, where the recipes are programming activities using the necessary API elements driven by the framework features. We performed an empirical study, consisting of three experiments with 44 human subjects executing real framework instantiations aimed at comparing the use of the proposed cookbooks to traditional manual framework documentation (baseline). Our empirical assessment shows that the generated cookbooks performed better or, at least, with non-significant difference when compared to the traditional documentation, evidencing the effectiveness of the approach.
R4C: A Benchmark for Evaluating RC Systems to Get the Right Answer for the Right Reason

Recent studies have revealed that reading comprehension (RC) systems learn to exploit annotation artifacts and other biases in current datasets. This prevents the community from reliably measuring the progress of RC systems. To address this issue, we introduce R4C, a new task for evaluating RC systems' internal reasoning. R4C requires giving not only answers but also derivations: explanations that justify predicted answers. We present a reliable, crowdsourced framework for scalably annotating RC datasets with derivations. We create and publicly release the R4C dataset, the first, quality-assured dataset consisting of 4.6k questions, each of which is annotated with 3 reference derivations (i.e. 13.8k derivations). Experiments show that our automatic evaluation metrics using multiple reference derivations are reliable, and that R4C assesses different skills from an existing benchmark.
METHODOLOGY OF COMPLEX AND INTERDISCIPLINARY RESEARCHES IN MODERN PSYCHOLOGY

The article is devoted to the evaluation of perspectives of interdisciplinary researches using in psychological science in modern conditions. There are formulated approaches that let to improve the efficiency of interdisciplinary researches. Although this issue has received considerable attention of researchers, the problem is not solved at the moment. The theory of complex psychological researches as a scientific concept, reflecting the specificity of psychological research has not been developed yet. The reason for this is that researchers try to develop the principles of organization and procedure of this kind of researches. It is possible to develop the methodology and theory of complex psychological researches, based on the understanding of the subject of psychology. It is alleged that at present time the most adequate understanding of the subject of psychology is his interpretation like the subjective world of human.
Design Depth and Balanced Control System of an Autonomous Underwater Vehicle with Fuzzy logic

Underwater vehicles are the vehicle that can be moved and controlled in water by remotely.Autonomous Underw ater Vehicle (AUV) is one type of underwater robot that is being developed lately.Unlike Remotely Operated Vehicle (ROV) which can be controlled manually using the remote.AUV can move automatically without being controlled directly by the user as long as the conditions of the robot program are met.With the movement and disturbance that is difficult to predict can make the stability of the robot one is very vulnerable, so it takes a condition that can stabilize the movement both at any depth.In practice, the on / off control system is still not able to balance the AUV properly if the robot is disturbed by water movement.Therefore, the purpose of this paper, we want to design a system using fuzzy logic with Takagi Sugeno method to stabilize its movement in the roll position and adjust the height of the robot from the bottom of the water.This study uses the IMU MPU6050 sensor hardware and sonar sensor as input, Arduino as a microcontroller and 2 brushed DC motors as actuators.
Learning-based Tracking of Fast Moving Objects

Tracking fast moving objects, which appear as blurred streaks in video sequences, is a difficult task for standard trackers as the object position does not overlap in consecutive video frames and texture information of the objects is blurred. Up-to-date approaches tuned for this task are based on background subtraction with static background and slow deblurring algorithms. In this paper, we present a tracking-by-segmentation approach implemented using state-of-the-art deep learning methods that performs near-realtime tracking on real-world video sequences. We implemented a physically plausible FMO sequence generator to be a robust foundation for our training pipeline and demonstrate the ease of fast generator and network adaptation for different FMO scenarios in terms of foreground variations.
One or Two Katherines in Henry VIII?

Word frequency can distinguish parts of Henry VIII by Fletcher and by Shakespeare: using the combined raw frequencies of eighteen words preferred by Fletcher, again, all, are, can, dare, do, may, more, must, now, only, still, sure, there, these, too, ye, yet, and a second set of eighteen Shakespeare-preferred words, which includes the combined raw frequencies of being, did, doth, each, hath, hence, in, itself, might, of, rather, that, the, to, very, which, who, with. A simple discriminating ratio is obtained by dividing Set 1 by (Set 1 + Set 2 combined).1 Although Spedding’s division of the play in 1850, with I.i, I.ii, II.iii, II.iv, III.ii.1–203, V.i assigned to Shakespeare and I.iii, I.iv, II.i, II.ii, III.i, III.ii.204–459, IV.i, IV.ii, V.ii, V.iii, V.iv assigned to Fletcher, is the generally accepted authorship attribution endorsed by the New Oxford Shakespeare, suspicions have been raised concerning the co-authorship of several of the listed scenes. Cyrus Hoy questioned the homogeneity of II.i, II.ii, III.ii.204–459, IV.i, and IV.ii.2 More recently, Petr Plecháč applied R Stylo’s rolling attribution to the play and detected mixed authorship in II.i, II.ii, IV.i., and IV.ii, much in agreement with Hoy’s findings.3
UKRAINIAN UNIVERSITIES IN 2019 PUBLICATION ACTIVITY RANKINGS

The article deals with publication activity as a part of the set of scientometric indicators used to assess national scientific potential. The international and national ratings of the publishing activity, in which the Ukrainian universities are involved, have been presented and analyzed, as well as with the help of some analytical and search tools of the scientific platform Web of Science, the publishing activity of the leading universities of the country have been studied. The dynamics of inclusion of Ukrainian higher education institutions in SCImago Institutional Ranking has been monitored and their most significant achievements have been determined by major groups of rating indicators – “Innovation”, “Social Impact” and “Research”. Identity of SCImago rating and all-Ukrainian Osvita.ua rating has been demonstrated for Ukrainian universities. The methodology and principles of CWTS Leiden Ranking and National Taiwan University Ranking, which are based on Web of Science, have been reviewed. With input from the Essential Science Indicators (ESI) Web of Science tool the publication activity of Ukrainian scientific organizations on the whole has been identified, and by means of “Result Analysis” tools the 2019 scientific periodicals have been identified where the researchers from four largest educational institutions in our country were published. It has been concluded that among Ukrainian scientists the trend towards increasing the total number of publications in periodicals with a low level of scientific influence and citation, as well as with their general misunderstanding of the importance of scientific and publication collaborations with researchers from foreign universities is still prevailing. Suggestions have been formulated to increase publication activity and to represent better the university's scientific results in international citation indices.
Dissemination of instructional book on catfish cultivation: An effort for illiteracy eradication in minapolitan area

Probolinggo Regency has a low literacy rate (78.09%) which is below the average of the East Java Province (88.34%). This data is supported by the recapitulation results of the Directorate of Literacy and Equality Education in 2014 which states that the illiteracy rate in Probolinggo Regency is 64.163 people. Meanwhile, this regency is considered having a high potential in the field of fisheries through catfish farming, located in Sumberasih District. This article discusses the results of the dissemination of illiteracy eradication using instructional book of catfish cultivation. The empowerment method implemented was Empowerment and Development. The instruments used were interview, observation, document, questionnaire, and test. On trial phase, a mentoring was done to the learning community that was called WB. Prior to the mentoring session, pretest was implemented then posttest afterwards which were all done to the WB. Results show that there was an improvement on class average grade, previously it was 58,5 subsequently after the use of illiteracy eradication book, the average grade has improved to 79. The responses gathered from the WB towards the instructional book were very positive. Thus, instructional book of catfish cultivation can be used as a textbook in illiteracy tutorial in minapolitan area.
New families of self-dual codes

In the recent paper entitled "Explicit constructions of MDS self-dual codes" accepted in { IEEE Transactions on Information Theory}, doi: 10.1109/TIT.2019.2954877, the author has constructed families of MDS self-dual codes from genus zero algebraic geometry (AG) codes, where the AG codes of length $n$ were defined using two divisors $G$ and $D=P_1+\cdots+P_n.$ In the present correspondence, we explore more families of optimal self-dual codes from AG codes. New families of MDS self-dual codes with odd characteristics and those of almost MDS self-dual codes are constructed explicitly from genus zero and genus one curves, respectively. More families of self-dual codes are constructed from algebraic curves of higher genus.
Petrological characteristics of some cretaceous igneous rocks, in Southwest of Gboko, Southern Benue Trough, Nigeria

Detailed field geological mapping, outcrop petrography and thin-section microscopy are employed to delineate and describe igneous rocks, and to infer the tectono-magmatic and geochemical constraints affecting their emplacement in the Tse-Agberagba area, Southwest of Gboko, Southern Benue Trough.&nbsp; Magmatic activity, coupled with folding and deformation were the effects of the Santonian tectonic episode in the area. Petrological (outcrop and thin section) data on these rocks indicate that they are mainly dioritic and doleritic to basaltic on hand specimens. Thin-section microscopy reveals that the dioritic rocks are generally medium-grained and mesocratic, characterized by randomly oriented laths of plagioclase and hornblende. The doleritic rocks are generally melanocratic, fine-grained and porphyritic, and are characterized by randomly oriented microlites of plagioclase of labradorite composition, with olivine and augite in a groundmass of aphanitic plagioclase, olivine and nepheline. The rocks are characterized by sub-ophitic to intersertal relationships between plagioclase and clinopyroxene which develops calcite as an alteration product. The mineralogical assemblages in these rocks suggest crystallization from an alkali-enriched magma, in a divergent tectono-magmatic setting.&nbsp;&nbsp; Key words: Southern Benue Trough, magmatism, dioritic, doleritic, alkali-enriched magma, divergent tectonic setting. &nbsp
Peranan Taman Bacaan Masyarakat Sebagai Sumber Belajar Rumah Singgah Anak Mandiri Yogyakarta

This research studies the role of TBM as a source of learning, an effort made by TBM to make children interested in learning at TBM, namely by providing learning that makes the horizon of knowledge more broad and developing. Data collection techniques used are through interviews, observation and documentation. The role of TBM as a learning resource by supporting the pursuit of learning packages that are currently being carried out by children in preparation for the exam. In supporting children to get chase packages, foundation management must provide supporting books available at TBM. Activities undertaken by TBM in order to be close to street children are by making direct visits to the location of street children who usually gather and do storytelling activities so that children who cannot read can be helped and understand the meaning of the story. Constraints that have occurred namely regarding the compilation of children who are difficult to read because of differences in nature.