Reviewerly/exHarmony huggingface dataset:
An Explainable Autoencoder For Collaborative Filtering Recommendation

Autoencoders are a common building block of Deep Learning architectures, where they are mainly used for representation learning. They have also been successfully used in Collaborative Filtering (CF) recommender systems to predict missing ratings. Unfortunately, like all black box machine learning models, they are unable to explain their outputs. Hence, while predictions from an Autoencoder-based recommender system might be accurate, it might not be clear to the user why a recommendation was generated. In this work, we design an explainable recommendation system using an Autoencoder model whose predictions can be explained using the neighborhood based explanation style. Our preliminary work can be considered to be the first step towards an explainable deep learning architecture based on Autoencoders.
“연안사고예방에 관한 법률” 정책결정과정 분석

The purpose of this research is to clarify the policy decision process on the enactment of “Costal Accident Prevention Act” (marine leisure sports field) and to analyze it empirically by applying the Multiple Stream Framework (MSF) of the policy decision process (Kingdon, 1984). The materials were analyzed and interpreted by adopting the qualitative research methodology, mixing the collection of literature materials, the method of depth interview and connection works with theories. With the above research procedures, the following results were drawn in this research.First, the accident in which five young students were sacrificed at the private Marine Corps camp which is known as a mecca of self-restraint education and the atmosphere of the state policy that valued the safety of the people as the priority formed a policy agenda and grabbed the attention of government officials.Secondly, the disaster of Sewol ferry, a shocking incident that occurred during the legislative process formed the public opinion of social criticism as a hot issue of the society. Such an atmosphere led to the intensive concern of high-ranking government officials and the agreement of the ruling party and opposition party.Third, the choice (legislation of the government, top-down approach) and the aggressive activities up to policy decision of the former National Maritime Police Agency, and the support of invisible participants (Marine Rescue Association, expert members of the National Assembly Secretariat) worked as important nutritional factors, and became motive powers to be delegated of the authority as the ministry and office concerned of the law from the National Assembly.Through this study, Kingdon(1984)''s MSF theory was confirmed as an appropriate theory in applying the case of radical policy to analyze the mechanism of process context throughout the policy making process. Therefore, this research is expected to act as a major theoretical framework for analyzing the process of policies which will be enacted in the future of marine leisure.
The Need to Train Students Intercultural Competence for International Mobility Stage

The concern for the training of intercultural competence has become more and more accentuated because in the contemporary society we are witnessing a significant increase in student mobility.In countries such as France or Germany teachers have created special programs for training this competence for students that studying in a different culture.It was found that such intercultural competence training programs help students to better understand the characteristics of the cultures and the differences between them, to respect them and to integrate better.Possessing intercultural competence allows students to better manage relationships in a multicultural space.The goal of this paper is to explain the notion of intercultural competence and its importance for students who will participate in international mobility.
Education Game As An Effort Delightful Learning In The Elementary School

This study aims to develop a thematic learning media in the era of industrial revolution 4.0 by using educational games for elementary students that are valid, practical and effective. Thematic learning media using educational games is closely related to innovation and the use of technology following the demands of the industrial revolution 4.0 era to increase student attractiveness in learning. Media developed using the help of the Adobe Flash CS 6. program. The material in the form of media thematic which integrates several subjects. The development model used is 4-D (define, design, develop, disseminate). The research data was obtained from the validity test (media validation sheet), practicality (student and teacher response questionnaire), and effectiveness (student learning activities and results). Data were analyzed descriptively. The results showed that the thematic learning media was valid (media content according to curriculum, attractive design and layout, ease of operation, easy to understand students' language, and clear presentation according to student characteristics), practical (clear contents and objectives, easy to read, attractive appearance, and can increase student interest in learning), and effective (can increase student activity and learning outcomes). Learning media using educational games can create a fun learning process.
An Efficient Identity Authentication protocol for layer 2 security sourced on ECC for IoT communications

In IoT communications we have networks comprising of nodes which are capable of sensing a parameter, processing it and transmitting it. Primarily, the networks are employed in environmental sensing and monitoring. As these networks are data centric, the cryptographic parameters like authentication, confidentiality, integrity and availability are strongly needed. The nodes in such networks are resource constrained in terms of memory, bandwidth and power. Due to this limitation traditional Asymmetric Public Key cryptographic algorithms are not well suited for such networks.In this paper, the suitability and usage of ECC in these networks has been discussed. Using TinyOS as platform and Tiny ECC, this paper presents how ECC provides a better Asymmetric alternative compared to other PKI’s in these networks. The paper also presents a light weight node authentication protocol i.e. an Identity Authentication Protocol using ECC. This protocol has been simulated in TinyOS using Tossim and Simulator.
A circular proof system for the hybrid mu-calculus

We present a circular and cut-free proof system for the hybrid mu-calculus and prove its soundness and completeness. The system uses names for fixpoint unfoldings, like the circular proof system for the mu-calculus previously developed by Stirling.
Adversarial vs behavioural-based defensive AI with joint, continual and active learning: automated evaluation of robustness to deception, poisoning and concept drift

Recent advancements in Artificial Intelligence (AI) have brought new capabilities to behavioural analysis (UEBA) for cyber-security consisting in the detection of hostile action based on the unusual nature of events observed on the Information System.In our previous work (presented at C\&amp;ESAR 2018 and FIC 2019), we have associated deep neural networks auto-encoders for anomaly detection and graph-based events correlation to address major limitations in UEBA systems. This resulted in reduced false positive and false negative rates, improved alert explainability, while maintaining real-time performances and scalability. However, we did not address the natural evolution of behaviours through time, also known as concept drift. To maintain effective detection capabilities, an anomaly-based detection system must be continually trained, which opens a door to an adversary that can conduct the so-called "frog-boiling" attack by progressively distilling unnoticed attack traces inside the behavioural models until the complete attack is considered normal. In this paper, we present a solution to effectively mitigate this attack by improving the detection process and efficiently leveraging human expertise. We also present preliminary work on adversarial AI conducting deception attack, which, in term, will be used to help assess and improve the defense system. These defensive and offensive AI implement joint, continual and active learning, in a step that is necessary in assessing, validating and certifying AI-based defensive solutions.
Bispiraloconulus serbicus Schlagintweit, Bucur & Sudar, 2019 (arborescent benthic foraminifer) and Torremiroella hispanica Brun & Canerot, 1979 from the late Barremian of Kopet-Dagh sedimentary basin (NE Iran) and their palaeobiogeographic revisions

during micropaleontological investigations on the lower cretaceous successions of the tirgan Formation in Kopet-dagh sedimentary basin, some new achievements are yielded. in this regards, the first occurrence of Bispiraloconulus serbicus Schlagintweit, Bucur &amp; Sudar in close association with Torremiroella hispanica Brun &amp; canerot is reported for the first time from the upper Barremian of Kopet-dagh sedimentary basin (ne iran). the biostratigraphic investigations were carried out on a 197.5 m thick gelian stratigraphic succession cropping out along the tirgan Formation located 35 km southwest of Shirvan town. this study reviews the palaeogeographical distribution and age of Bispiraloconulus serbicus Schlagintweit, Bucur &amp; Sudar and Torremiroella hispanica Brun &amp; canerot along the northern tethyan margins and extends its pal?eobiogeographical existence.
Research on Particle Swarm Optimization Algorithm Based on Quantum Computing Technology

In view of the shortcomings of particle swarm optimization such as premature convergence to local optimization, particle swarm optimization algorithm based on quantum gate and particle swarm optimization algorithm based on quantum behavior are studied in this paper. The first algorithm uses the random observation method of quantum bit coding particles to simulate quantum particle collapse for generating a population and uses the quantum rotating gate to generate a new population. The adaptive mutation operator is used for ensuring the diversity of the population, effectively reducing the impact of local optimization; therefore, the robustness of the algorithm is improved. The second algorithm uses the probability density function of quantum computation to make the particles jump out of the local extreme points and fulfils the global search, which is more suitable for continuous optimization. The results of computational experiments show that both the two particle swarm optimization algorithms based on quantum technology have a good global convergence.
Set up and management of a Data Science faculty at Shiga University

Shiga University opened the first data science faculty in Japan in April 2017. Beginning with an undergraduate class of 100 students, the Department has since established a Master's degree programme with 20 students in each annual intake. This is the first data science faculty in Japan and the University intends to retain this leading position, the Department is well-placed to do so. The faculty closely monitors international trends concerning data science and Artificial Intelligence (AI) and adapt its education and research accordingly. The genesis of this department marks a change in Japan's attitudes towards dealing with information and reflects a wider, global understanding of the need for further research in this area. Shiga University's Data Science department seeks to produce well-trained data scientists who demonstrate a good balance of knowledge and skills in each of the three key areas of data science.
Contextual Multi-scale Region Convolutional 3D Network for Anomalous Activity Detection in Videos

The importance of the surveillance camera has been greatly increased as a result of increase in the crime rates. The monitoring of the videos recorded is once again challenging. Thus, there is an incredible interest for intelligent surveillance system for security purposes. The proposed work aims at a anomalous activity detection in video using the contextual multi-scale region convolutional 3D network (CMSRC3D) for. The work is deal with different time scale ranges of activity instances; the temporal feature pyramid is used to represent normal and abnormal activities of different temporal scales. In the temporal pyramid are 3 levels, that is short, medium and long for video processing. For each level of the temporal feature pyramid, an activity proposal detector and an activity classifier are learned to detect the normal and abnormal activities of specific temporal scales. Most importantly, the entire system model at all levels can be trained endwise. The activities detected are classified as the normal and the abnormal using the activity class. In the project CMSRC3D, each scale model uses convolutional feature maps of specific temporal resolution to represent activities within specific temporal scale ranges. More importantly, the whole detector can identify anomalities with in all sequential ranges in a single shot, which makes it very efficient for computation. And also provide if any anomalous activities detected in video, we give alert to avoid future mishappening.
The Correlation Between Reading Comprehension Ability and Vocabulary Class IX At SMP N 6 Jambi

The main purpose of this study was to find out whether there is any correlation between Reading Comprehension and vocabulary class IX at SMP N 6 Jambi. The hypotheses of this study are, (1) there is no correlation between reading comprehension and vocabulary (2) there is any correlation between vocabulary mastery and reading comprehension. The problem of this research study was: is there any correlation between reading comprehension and vocabulary class IX at SMP N 6 Jambi? The population of this research was 373 students. The sample of this research was 76 students which were taken cluster random sampling from two classes. To conduct this study, qualitative method was used. The data were analyzed by using, Pearson Moment Product Bivariate with SPSS. Based on the findingit was found that the average score reading comprehension test was 56, 5 and the score vocabulary test was 52, 9 .it means that the students' reading comprehension was fair. And the students' competency in vocabulary was fair. Based on the finding, it was found that the correlation coefficient obtained is 0.001. It shows that there is no correlation between vocabulary mastery and reading comprehension and vocabulary.
Baseline haematological parameters reference ranges of dogs in the Ashanti region of Ghana

This study was conducted using sixty (60) clinically healthy dogs from different districts in the Ashanti Region of Ghana., Haematological parameters reference ranges was established and the influence of sex, breed and age on haematological indices of dogs in the Ashanti, Ghana was equally studied. Blood samples were collected from the dogs and analysed using a Mindray 5 parts automated haematologic analyser. Data obtained were compiled in Excel 2013 and analysed using Graphpad Prism 6. Results of the current study showed significant variations (p<0.05) in some indices from established haematological indices. A higher mean lymphocyte count was recorded. The mean MCV values obtained in this study were notably towards the upper limit of the accepted ranges; whilst the mean MCHC recorded was lower than documented norm. The study recorded significant (p<0.05) sex related differences in RDW, MCHC, MCV and RBC; as well as breed related variations in platelet counts. Results of the current study will provide baseline reference data for haematological tests of dogs and could be very useful in veterinary clinical practice, especially in precise diagnosis of canine problems requiring haematology, in the sub region. Keywords : Reference ranges, Haematological indices, dogs, Ashanti region, Ghana
karakteristik diksi, citraan, dan majas puisi siswa kelas X SMA

ABSTRAK Penelitian ini bertujuan untuk karakteristik diksi, citraan, dan majas dari puisi siswa dalam setiap karya mereka dari kelas yang berbeda tentunya kemampuan mengolah kosakata setiap siswa pun berbeda bergantung pada pemilihan diksi, citraan, dana majasnya. Jenis penelitian ini adalah kualitatif dengan pendekatan deskriptif. Analisis data karakteristik diksi, citraan, dan majas dalam puisi dilakukan dengan analisis dekriptif kualitatif, dianalisis dengan mengumpulkan hasil dari karya puisi siswa. Pengumpulan data menggunakan teknik dokumentasi. Hasil penelitian sudah mencakup kelesuruhan aspek yang ingin dicapai dan menghasilkan tiga temuan. Pertama karakteristik diksi. Kedua, karakteristik citraan. Ketiga, karakteristik majas. Kata kunci : Karakteristik diksi, citraan, majas, puisi ABSTRACT This study aims to characterize diction, image, and level of poetry of students in each of their works from different classes, of course the ability to process vocabulary for each student will also differ depending on the selection of dictionaries, images, and advanced funds. This type of research is qualitative with a descriptive approach. Analysis of data on characteristics of diction, images, and lectures in poetry was carried out by qualitative descriptive analysis, analyzed by collecting results from students' poetry works. Data collection uses documentation data collection techniques. The results of the research carried out in this study have covered all aspects to be achieved and produced three findings. First, diction. Second, images. Third, figure of speech. Keywords : Characteristics of diction, imagery, majas, poetry Normal 0 false false false IN X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable{mso-style-name:Table Normal;mso-tstyle-rowband-size:0;mso-tstyle-colband-size:0;mso-style-noshow:yes;mso-style-priority:99;mso-style-qformat:yes;mso-style-parent:;mso-padding-alt:0cm 5.4pt 0cm 5.4pt;mso-para-margin-top:0cm;mso-para-margin-right:0cm;mso-para-margin-bottom:10.0pt;mso-para-margin-left:0cm;line-height:115%;mso-pagination:widow-orphan;font-size:11.0pt;font-family:Calibri,sans-serif;mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-fareast-font-family:Times New Roman;mso-fareast-theme-font:minor-fareast;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;mso-bidi-font-family:Times New Roman;mso-bidi-theme-font:minor-bidi;}
A Comparative Study for Non-rigid Image Registration and Rigid Image Registration

Image registration algorithms can be generally categorized into two groups: non-rigid and rigid. Recently, many deep learning-based algorithms employ a neural net to characterize non-rigid image registration function. However, do they always perform better? In this study, we compare the state-of-art deep learning-based non-rigid registration approach with rigid registration approach. The data is generated from Kaggle Dog vs Cat Competition \url{https://www.kaggle.com/c/dogs-vs-cats/} and we test the algorithms' performance on rigid transformation including translation, rotation, scaling, shearing and pixelwise non-rigid transformation. The Voxelmorph is trained on rigidset and nonrigidset separately for comparison and we also add a gaussian blur layer to its original architecture to improve registration performance. The best quantitative results in both root-mean-square error (RMSE) and mean absolute error (MAE) metrics for rigid registration are produced by SimpleElastix and non-rigid registration by Voxelmorph. We select representative samples for visual assessment.
Deep Learning Enabled Uncorrelated Space Observation Association

Uncorrelated optical space observation association represents a classic needle in a haystack problem. The objective being to find small groups of observations that are likely of the same resident space objects (RSOs) from amongst the much larger population of all uncorrelated observations. These observations being potentially widely disparate both temporally and with respect to the observing sensor position. By training on a large representative data set this paper shows that a deep learning enabled learned model with no encoded knowledge of physics or orbital mechanics can learn a model for identifying observations of common objects. When presented with balanced input sets of 50% matching observation pairs the learned model was able to correctly identify if the observation pairs were of the same RSO 83.1% of the time. The resulting learned model is then used in conjunction with a search algorithm on an unbalanced demonstration set of 1,000 disparate simulated uncorrelated observations and is shown to be able to successfully identify true three observation sets representing 111 out of 142 objects in the population. With most objects being identified in multiple three observation triplets. This is accomplished while only exploring 0.06% of the search space of 1.66e8 possible unique triplet combinations.
Leemos textos instructivos

The learning session entitled “we read instructions to make a kite”, is developed for students of the first grade of primary education in the area of Communication, within the framework of the National Curriculum of Regular Basic Education, where competition has been considered reads various types of texts, specifying the ability to obtain information from the written text, it has also adapted to the characteristics of children between approximately six and seven years of age in the city of Trujillo. In the development of the scheduled activities, the teaching processes according to the area of Communication and the pedagogical processes to obtain optimal learning achievements were taken into account. Active methodological strategies were also used to promote the constant participation of students.
FORMULATION AND EVALUATION OF CREATIVE-WRITING TEXTBOOKS FOR EDUCATION STUDIES

Purpose of the study: This study aimed to formulate and evaluate the effectiveness of creative writing poetry textbooks with problem-based learning on local wisdom for Indonesian Education Language and Literature students in IKIP PGRI Pontianak and STKIP PGRI Sintang West Kalimantan.&#x0D; Methodology: This study used the quantitative approach of quasi-experimental research by dividing subjects into two groups, treatment and control groups.&#x0D; Main Findings: Expected to be able to fulfill the needs of textbooks in creative poetry writing based on local wisdom in private universities in West Kalimantan.&#x0D; Applications of this study: Indonesian Language and Literature Education at IKIP PGRI Pontianak and STKIP PGRI Sintang West Kalimantan.&#x0D; Novelty/Originality of this study: By all means, the use of modified teaching material on creative writing poetry with the problem-based learning model on local wisdom was more effective than the previous textbooks.
Taylor Moment Expansion for Continuous-Discrete Gaussian Filtering and Smoothing

The paper is concerned with non-linear Gaussian filtering and smoothing in continuous-discrete state-space models, where the dynamic model is formulated as an It\^{o} stochastic differential equation (SDE), and the measurements are obtained at discrete time instants. We propose novel Taylor moment expansion (TME) Gaussian filter and smoother which approximate the moments of the SDE with a temporal Taylor expansion. Differently from classical linearisation or It\^{o}--Taylor approaches, the Taylor expansion is formed for the moment functions directly and in time variable, not by using a Taylor expansion on the non-linear functions in the model. We analyse the theoretical properties, including the positive definiteness of the covariance estimate and stability of the TME Gaussian filter and smoother. By numerical experiments, we demonstrate that the proposed TME Gaussian filter and smoother significantly outperform the state-of-the-art methods in terms of estimation accuracy and numerical stability.