Reviewerly/exHarmony huggingface dataset:
Automatic liver segmentation in abdominal CT images using combined 2.5D and 3D segmentation networks with high-score shape prior for radiotherapy treatment planning

Liver segmentation is a prerequisite for measuring hepatic volume in liver transplantation, modeling of the liver anatomy in hepatic surgery planning, and contouring in radiotherapy treatment planning. The main challenges of liver segmentation are the appearance similarity of liver and surrounding stomach, heart, and spleen in 2D images and are the large shape variations of liver in 3D volume. Therefore, we propose a deep learning-based liver segmentation method by using global context of three orthogonal planes to localize the liver in whole abdomen and by using local context of targeted liver bounding volume and high-score shape prior to delineate the liver without leakage to the surrounding structures. To localize the liver within the whole abdomen and exclude outliers through the global context, three 2D segmentation networks are learned on each axial, coronal, and sagittal planes. To consider the shape information obtained from the 2D segmentation network in the next 3D segmentation network, the high-score shape prior is generated by a weighted fusion of three score maps. To correct the fine details of the liver in the targeted liver bounding volume and to be less affected by shape variation, the 3D segmentation network is learned based on 3D U-Net with highscore shape prior. Experimental results show that the DSC of the proposed segmentation network with high-score shape prior (LiverNet-WS) was 94.3%, which is 5.4% higher than LiverNet without high-score shape prior. The proposed method accurately localized the liver within the whole abdomen by using global contexts of three orthogonal planes. Moreover, segmentation accuracy improved fine details considering local context and avoided over-segmentation considering high-score shape prior.
The Effectiveness Of Using Gakushuugoi Module to Enhance Students Japanese Vocabulary Skills

This research aims to determine the effectiveness of gakushuugoi module usage to improve Japanese vocabulary mastery for learners. The method used in this study is an experimental quantitative method, a pre-test and a post-test. The population of sample data in this study is the Japanese elementary level learners (Shokyuu A) of Bimbel AEC Semarang. To determine the effect of Gakushuugoi module usage in the use of Japanese vocabulary, the data analysis was carried out before and after the treatment. From the results of data analysis, it is known that the t count is 7.78 and the df is 9. It happens since the value of t table for df 9 is 2.26 at a significant level of 5% t table and 3.25 at a significant level of 1% t table. Thus, the value of the t count is greater than the t table. This shows that there are significant differences between the variables X (post-test) and variable Y (pre-test). Based on the analysis, it can be concluded that the use of effective gakushuugoi module can improve the mastery of Japanese vocabulary.&#x0D; &#x0D;
Graph Convolutional Auto-encoder with Bi-decoder and Adaptive-sharing Adjacency.

Graph autoencoders (GAEs) are the effective unsupervised learning frameworks to learn the latent representations of graph data for network embedding. Most exiting GAE approaches typically focus on the graph reconstruction but neglect the node features reconstruction, which often results in overfitting due to the capacity of the autoencoders. Additionally, the adjacency matrix of these methods cannot accurately represent the connections among nodes in latent space when the prior information is contaminated. To address these problems, we propose a novel Graph Convolutional Auto-encoder with Bi-decoder and Adaptive-sharing Adjacency method, namely BAGE. The framework encodes the graph construction and node features into latent representations, upon which the bi-decoder is trained to reconstruct the graph construction and node features simultaneously. Moreover, the convolutional adjacency matrix is shared with the embedded graph optimization and can be adaptively learned by constructing the Laplacian, leading to more accurate connections. Consequently, the proposed method can be applied to more general datasets than the existing GAEs, i.e., data without a pre-given graph construction to prevent the GAEs from excessive dependence on the prior adjacency information. Experimental results validate the superiority of our method to the state-of-the-art network embedding methods.
СИСТЕМИ ЗАХОПЛЕННЯ РУХУ В ДОДАНІЙ РЕАЛЬНОСТІ: РІЗНОВИДИ ТА СПЕЦИФІКА ЇХ ЗАСТОСУВАННЯ У ПРАКТИЦІ ПРОМОЦІЙНИХ КОМУНІКАЦІЙ

&lt;div&gt;&lt;p&gt;&lt;em&gt;In this study there were identified the main varieties of existing motion capture systems (mocap) that can be used primarily to create three-dimensional animation for augmented reality; as well as established their specific features, and also demonstrated the examples of the practical use of certain types of such systems in promotional communications.&lt;/em&gt;&lt;/p&gt;&lt;/div&gt;&lt;p&gt;&lt;em&gt;This study unleashes the specificity of the functioning of non-marker and all types of marker motion capture systems – optical (optically passive and optically active, including «performance capture» as well as hybrid) and non-optical (acoustic, magnetic, mechanical and inertial).&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;There were analyzed two practical promotional cases: the American social PR project «Love Has No Labels» and the Japanese commercial brand «ZozoTown» («ZozoSuit»).&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;It has been found that in the practice of promotional communications inertial-type mocap systems with full magnetic interference are most actively used, since they can be used directly during mass AR-actions, primarily due to their portability and ability to function in a limited space.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;It has also been revealed that AR-actions using motion capture systems are conducted primarily to create positive WOM and media resonances, allowing to significantly diversify the arsenal of communication tools with the target audience, as well as to increase the quality and efficiency of promotional messages, which in sum boosts the publicity capital.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;Other varieties of mocap systems (with exception of non-marking one, which works through computer vision) are not used in real time regime for promotional events primarily due to their cumbersome nature. However, they can be employed to create realistic 3D animation for future utilization in promotional campaigns, projects, and actions using augmented reality technologies.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Key words:&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; motion capture systems (mocap), augmented reality (AR), promotion, empirical marketing.&lt;/em&gt;&lt;/p&gt;
The Development of Interactive Computer-Based Learning Models to Improve Student Learning Outcomes in Integrated Social Studies Education at SMP Negeri 4 Tarutung

This study aims to: produce visual based learning media products that are appropriate to use, easy to learn by students and can be used for early childhood.This type of research develops the ADDIE model from the Dick and Carey learning design model.The results showed: (1) the expert test material qualifications were very good (89%), ( 2) the learning design expert qualifications were very good (97%), (3) the instructor learning media qualification test was very good (89%), (4) individual qualification trials are very good (95.16%), ( 5) small group trials with very good qualifications (96.01%), ( 6) field trials are limited to very good qualifications (96.12%) , and suitable for use in the learning process early on.Hypothesis testing results prove that there are significant differences between student learning outcomes that are learned using media products with student learning outcomes that are learned without using media products.This is indicated by the results of data processing obtained by t-count = 3.678> t table = 1.79, with dk = 2 at the significance level α = 0.05.It was concluded that the learning outcomes of students taught using interactive computer-based "Wesli" learning models was 83% higher than the group of students taught without 81 learning media products.
Output entropy calculation of neural biometric code converters

The purpose of the work was to find out various types of neural biometric-code converters, and methods for calculating their output entropy.As a result, it was decided that to calculate the entropy, it is more logical to use the Hamming convolution space.
A Multi-Task Framework for Action Prediction

Predicting the categories of actions in partially observed videos is a challenging task in the computer vision field. The temporal progress of an ongoing action is of great importance for action prediction, since actions can present different characteristics at different temporal stages. To this end, we propose a novel multi-task deep forest framework, which treats temporal progress analysis as a relevant task to action prediction and takes advantage of observation ratio labels of incomplete videos during training. The proposed multi-task deep forest is a cascade structure of random forests and multi-task random forests. Unlike the traditional single-task random forests, multi-task random forests are built upon incomplete training videos annotated with action labels as well as temporal progress labels. Meanwhile, incorporating both random forests and multi-task random forests can increase the diversity of classifiers and improve the discriminative power of the multi-task deep forest. Experiments on the UT-Interaction and the BIT-Interaction datasets demonstrate the effectiveness of the proposed multi-task deep forest.
PERAMALAN DATA PENUMPANG KERETA API DENGAN MENGGUNAKAN MAXIMAL OVERLAP DISCRETE WAVELET TRANSFORM- RECURRENT NEURAL NETWORK (MODWT-RNN)

The train is one of the public transportation that is very popular because it is affordable and free of congestion. There is often a buildup of train passengers at the station so that it sometimes causes an accumulation of passengers at the station and makes the situation at the station to be not conducive. In order to avoid a buildup of passengers, forecasting the number of passengers can be done. Forecasting is determined based on data in previous times. Data of train passengers in Java (excluding Jabodetabek) forms a non-stationary and contains nonlinear relationships between the lags. One of the nonlinear models that can be used is Recurrent Neural Network (RNN). Before RNN modeling, Maximal Overlap Wavelet Transform (MODWT) was used to make data more stationary. Forecasting model of train passengers in Java excluding Jabodetabek, Indonesia using MODWT-RNN results forecasting with RMSE is 252.85, while RMSE of SARIMA and RNN are 434.97 and 320.48. These results indicate that the MODWT-RNN model gives a more accurate result than SARIMA and RNN.
A Privacy-Preserving DNN Pruning and Mobile Acceleration Framework.

Weight pruning of deep neural networks (DNNs) has been proposed to satisfy the limited storage and computing capability of mobile edge devices. However, previous pruning methods mainly focus on reducing the model size and/or improving performance without considering the privacy of user data. To mitigate this concern, we propose a privacy-preserving-oriented pruning and mobile acceleration framework that does not require the private training dataset. At the algorithm level of the proposed framework, a systematic weight pruning technique based on the alternating direction method of multipliers (ADMM) is designed to iteratively solve the pattern-based pruning problem for each layer with randomly generated synthetic data. In addition, corresponding optimizations at the compiler level are leveraged for inference accelerations on devices. With the proposed framework, users could avoid the time-consuming pruning process for non-experts and directly benefit from compressed models. Experimental results show that the proposed framework outperforms three state-of-art end-to-end DNN frameworks, i.e., TensorFlow-Lite, TVM, and MNN, with speedup up to 4.2X, 2.5X, and 2.0X, respectively, with almost no accuracy loss, while preserving data privacy.
JDream Expert Finder: A Search Engine to Find Young Promising Researchers

The authors and G-Search Limited are collaborating to develop a search engine "JDream Expert Finder" (JDEF) as an outcome of the project-8 in the Life Intelligence Consortium (LINC). JDEF has a function to find young promising researchers, who, so far, have only a little publication in the literature database of Japan Science and Technology Agency (JST). Using conventional citation indicators such as h-Index, it is inadequate to measuring young researchers' performances. Therefore, we have focused on the betweenness centrality in co-authorship networks as an alternative indicator. As JDEF has utilized a growth model of Japan Society for the Promotion of Science (JSPS) research fellows, thus, it is able to search the other young promising researchers from the JST database.
The Contribution of Reading Strategy and Self Efficacy to the Reading Comprehension of College Students

This research is aimed to know how strong the contribution of readingstrategy and self-efficacy to students’ reading comprehension. Quantitativeapproach with correlational research design used in this research. Correlationalresearch design is chosen to find out the contribution of independent to thedependent variable. The population of English Department of Faculty of TeacherTraining and Education of UNISKA Kediri consisting of 240 students werechosen as the subject of research and 150 of them were selected as the sample.Simple random sampling using lottery was used as the method of taking sample.The data was gotten by applying three instruments, questionnaire for readingstrategy and self-efficacy, especially for self-regulated learning of reading subject,and also reading comprehension test. Then regression formula was used to analysethe contribution of reading strategies and self-efficacy to reading comprehensionof the students.The result states the reading strategy and self-efficacy significantlycontribute to the students’ reading comprehension.
Reference Face Based Technique for Unconstrained Face Recognition from Images Gallery

This paper represents the Id Quality of un-constrained face inside an unconstrained environment. It provides capabilities like discrepancy, illumination, and expression difference techniques. It might be useful for both retrieve image (Face) and identification (Recognition). At present plenty of way of top view face recognition can be found. In last few years, for Computer vision, numerous face recognition techniques have been organized. But, actualworld face detection demands a difficult works. The curiosity about unconstrained helpful face recognition keeps growing utilizing the detonation of online press for instance community methods, and video surveillance recording wherever experience analysis is of great importance.In this analysis, it is appeared to handle status inside the scenario of chart assumption.We're in a position to determine a magical experience employing a Varied Technique.This study lights out the choices suggested for unconstrained face recognition quality area and suggesting the solution to be utilized by Reference Face Based Technique (From Gallery Image) centered face recognition.RFG recognition is used in grouping with DCT locality sensitive hashing for efficient recovery to guarantee scalability.Objective of this research is Reference Face Based Technique focused on unconstrained face recognition to enhance the demonstration quality.The Simulation of proposed techniques will be completed through the use of MATLAB.
Tinjauan Pelaksanaan Retensi Sesuai Dengan Permenkes Ri No. 269 Tahun 2008 Dan Akreditasi Snars Di RSUD Kanjuruhan Kabupaten Malang

Retention of medical record documents is an activity separating active medical record documents with medical record documents inactive by looking at the period of storage medical record documents. Implementation of retention in Kanjuruhan Hospital Malang Regency carried out gradually starting from sorting, moving, and destroying but the processes don’t use Records Retention Schedule, the storage of inactive medical record documents overload and the absence of a special shelf to store the documents and the absence of special officers for carrying out medical record documents retention. The purpose of study was to find out The Retension to Conform Permenkes RI No. 269 Year 2008 and Standards of Accreditation of SNARS in RSUD Kanjuruhan Malang Regency. This research method was descriptive with a qualitative approach. The informants in this study were 1 key informant and 2 regular informants. Data collection techniques were interview observation and documentation study. Based on research results in Kanjuruhan Hospital Malang Regency, the process of implementing retention don’t use the Records Retention Schedule to determine the period of storage of medical record documents. The retention process wasn’t accordance with the existing SPO. The process of implementing retention wasn’t in accordance with Permenkes RI No. 269 Year 2008 because there was no special officer carrying out the retention process. The process of implementing retention wasn’t in accordance with Accreditation of SNARS MIRM 10 because there was no special shelf for storing medical record documents and one of the officers still didn’t understand the contents of the accreditation standards.
Toward a rich phonology

A radically new conception of linguistic representations is proposed.The claim is that language is stored in memory in the form of large distributions of specific utterances in a rich high-dimensional space, sometimes called exemplar memory.This is the form the brain uses for understanding and creating utterances in real time.In contrast, the abstract, speaker-independent description of language (as modelled by alphabetical orthographies and by linguistic descriptions using phonemes, etc.) exhibits many structures and patterns that comprise a social institution, maintained by speakers over time, and approximating a discrete system made from components.However, these phenomena, shaped by social as well as articulatory/auditory factors, play no clear role in real-time language processing.
PENGARUH MINAT DAN MOTIVASI BELAJAR TERHADAP PRESTASI BELAJAR ILMU PENGETAHUAN SOSIAL (Survei pada siswa kelas VIII MTs Swasta di Jakarta Timur)

The purpose of this research is knowing how far effect of learning interest and learning motivation toward learning achievement, learning interest toward learning achievement, learning motivation toward learning achievement on social sciences subject. The Research method is using survey with correlation analysis and regression. Data about motivation study variabel and study motivation obtain by questionnairre which is prepared by researcher, that is measuring related two things above. Meanwhile data about studi achievement social subject obtain by direct test by researcher towards respondent. The results of the analysis state: (1) There is a significant influence together of interest and motivation to study on students' social studies learning achievement, this is evidenced by the Sig 0,000 &lt;0,05 and F count = 66,487. While the magnitude of the contribution of interest and motivation to learn together on social studies learning achievement is shown by the coefficient of determination that is equal to 70% while the remaining 30% is due to other factors not examined. (2) There is a significant effect of learning interest on students' social studies learning outcomes. This is evidenced by the Sig 0,000 &lt;0,05 and t count = 4,724. (3) There is a significant effect of students 'learning motivation on students' social studies learning outcomes. This is proven by the Sig 0,001 &lt;0,05 and t count= 3,457.
Information and Analytical Support of Education as a Scope of Scientific Activity of a V.O. Sukhomlynskyi State Scientific and Pedagogical Library of Ukraine

The author reveals the main aspects of the scientific and information activities of the V.O. Sukhomlynskyi State Scientific and Pedagogical Library of Ukraine, in particular, pays attention to the development of a structural unit that carries out scientific information and analytical activities to support the education of Ukraine.&#x0D; The article provides an analysis of recent studies and publications on informatization and technological education, presents scientists who have made a significant contribution to the development of this area.&#x0D; According to the purpose of the article, the scientific community is presented for familiarization with information and analytical resources of the V.O. Sukhomlynskyi State Scientific and Pedagogical Library of Ukraine and revealed the main aspects of information and analytical activities of the V.O. Sukhomlynskyi State Scientific and Pedagogical Library of Ukraine.&#x0D; Information and analytical resources are characterized by such basic components as – Scientific papers of the V.O. Sukhomlynskyi State Scientific and Pedagogical Library of Ukraine; Analytical Bulletin in the field of education and science ;. Analytical reviews of the V.O. Sukhomlynskyi State Scientific and Pedagogical Library of Ukraine; Reviews of the results of scientific activities of institutions of the National Academy of Sciences of Ukraine and others.&#x0D; The author emphasizes the relevance of the creation and functioning in the V.O. Sukhomlynskyi State Scientific and Pedagogical Library of Ukraine Department of Scientific Information and Analytical Support of Education (DSIASE). It is noted that DSIASE was created to provide basic and applied research in the vector of planned research work of the library.&#x0D; It is argued that in the V.O. Sukhomlynskyi State Scientific and Pedagogical Library of Ukraine there is an organizational and production system for the implementation of information and analytical support of education, which provides the scope of scientific activities of the institution.&#x0D; In the perspective of information and analytical activities of the library, the author notes the research search for innovative sources and support for education on the effective modernization and reform of education in Ukraine.