Reviewerly/exHarmony huggingface dataset:
Domain-Specific Lexical Grounding in Noisy Visual-Textual Documents

Images can give us insights into the contextual meanings of words, but current imagetext grounding approaches require detailed annotations.Such granular annotation is rare, expensive, and unavailable in most domainspecific contexts.In contrast, unlabeled multiimage, multi-sentence documents are abundant.Can lexical grounding be learned from such documents, even though they have significant lexical and visual overlap?Working with a case study dataset of real estate listings, we demonstrate the challenge of distinguishing highly correlated grounded terms, such as "kitchen" and "bedroom", and introduce metrics to assess this document similarity.We present a simple unsupervised clusteringbased method that increases precision and recall beyond object detection and image tagging baselines when evaluated on labeled subsets of the dataset.The proposed method is particularly effective for local contextual meanings of a word, for example associating "granite" with countertops in the real estate dataset and with rocky landscapes in a Wikipedia dataset."kitchen" (18.4% labeled true) E: 72.9 AUC W: 52.7 AUC R: 21.1 AUC "outdoor" (16.9% labeled true) E: 68.5 AUC W: 20.0 AUC R: 13.2 AUC "washer" (1.6% labeled true) E: 70.7 AUC W: 49.3 AUC R: 62.1 AUC "pool" (1.3% labeled true)
Novel hybrid framework for image compression for supportive hardware design of boosting compression

Performing the image compression over the resource constrained hardware is quite a challenging task. Although, there has been various approaches being carried out towards image compression considering the hardware aspect of it, but still there are problems associated with the memory acceleration associated with the entire operation that downgrade the performance of the hardware device. Therefore, the proposed approach presents a cost effective image compression mechanism which offers lossless compression using a unique combination of the non-linear filtering, segmentation, contour detection, followed by the optimization. The compression mechanism adapts analytical approach for significant image compression. The execution of the compression mechanism yields faster response time, reduced mean square error, improved signal quality and significant compression ratio performance.
Paneurhythmy exercises for developing partner and social skills

Paneurhythmy is a group psycho-physical practice created in Europe, involving marked social interaction. The purpose of this paper is to provide information about Paneurhythmy, and to discuss its potential as a means of development of partnership and social skills. This article offers a brief introduction into Paneurhythmy. The basic characteristics of Paneurhythmy practices providing appropriate conditions for the improvement of partnership skills are formulated and explained. By means of analysis, discussion and examples, it is shown how Paneurhythmy for beginners and its further practice can develop skills for successful partnership with children and adults. The existent empirical and theoretical studies on the subject to date have been specified, confirming the cultivation of partnership and social skills through Paneurhythmy. Paneurhythmy has an extremely big potential for the development of partnership skills and for the improvement of social functioning. In this respect, the most important characteristics of Paneurhythmy are the following: group practice in pairs, an appropriate aim of the practice, the right music, common rhythm and synchronization of movements, specific distances between participants, typical characteristics and expressiveness of participants’ movements, Paneurhythmy philosophy, sharing space, suitable lyrics of Paneurhythmy songs, figures for the arrangement of participants, acting social roles and broadening the range of awareness. Paneurhythmy is a widely-accessible new instrument for personal and social development. This is confirmed by the existent scientific studies, revealing that, with children and adults, both initial training and further practising Paneurhythmy leads to the improvement of interpersonal relations and social skills.
Ordinal Regression Modeling of Mother to Infant HIV Transmission in Nyeri County, Kenya

The transmission rates of HIV from a HIV-positive mother to her child during pregnancy, delivery or breastfeeding remains of much concern.Various governments and non-governmental organizations have aimed at coming up with policies aimed at minimizing the transmissions.For this to be achievable, there is a need for sound statistical procedures in the analysis of the mother to infant HIV transmission data.The study gives an application of the ordinal regression to the modeling of such data, a case of Nyeri County-Kenya.The logistic regression has been described as the best methodology for modeling binary response variables.However it does not provide a best fit for an ordered categorical variable with more than two categories.This calls for the extensions of the logistic regression which can be used when modeling such kind of variables, such an extension is the ordinal regression methodology.This study proposes the use of the ordinal regression methodology with probit and logit link functions to model infant feeding, arv regimen, maternal cell count and maternal viral load effect on mother to infant HIV transmission in Nyeri county, Kenya a case of Karatina sub-county referral hospital.An aspect of the ordinal link models, which can be useful for this implementation is particularly emphasized as it is in their interpretation that the classes of the dependent variable can be considered from the partition of the variation interval of an underlying continuous random variable.Data to be used shall be secondary data collected from Karatina sub-county referral hospital.Inference on parameters and model diagnostics is also provided.
A BUMP IN THE ROAD

Roads to Reference offers a highly valuable contribution to the theory of reference.The arguments in this book are quite convincing and the overall picture presented in it is quite attractive.In what follows I would like to present some critical comments regarding the first chapter of the book, Demonstratives and Conflicting Intentions.In this contribution I would like to focus on what the book has to say about demonstrative reference.In Roads to Reference Gomez-Torrente criticises theories according to which the semantic conventions of demonstratives determine necessary and sufficient conditions for reference.Needless to say, most theories in the market are targeted by Gomez-Torrente's criticisms.Once the terrain is clear, the book puts forward a novel theory of demonstrative reference.The key feature of this theory is that, according to it, the semantic conventions governing demonstrative reference only provide sufficient conditions for reference
The Effect of Using Service Automation and Robotic Technologies (SART) in Egyptian Hotels

Introduction: Service automation and robotic technologies (SART) are now the most important strategic technologies for hospitality; satisfy guests, Employees’ knowledge and efficiency: investigate SWOT” strategic planning analysis to evaluate the SART in Egyptian hotels.Objectives: The research objective was to shed light on the importance of SART in Egyptian hotels and its policy in entitles workers to the importance of service automation and robotic in ensuring Guest satisfaction and safety.Methodology: A survey was carried out on (28) Five Star Egyptian hotels. Results: The major contribution findings of this research showed that the effectiveness of the SART in assessing decisions, Increase Guest Satisfaction in Egyptian hotels.Recommendations: The study recommended the need to apply the SART in Egyptian hotels. Therefore, management should be sensitive to the SART applications that were already going on within the hotels and seek means to support them. Hotels management in Egypt should direct some of their budgets to SART.
Hyper-Sphere Support Vector Classifier with Hybrid Decision Strategy

If all bounding hyper-spheres for training data of every class are independent, classification for any test sample is easy to compute with high classification accuracy. But real application data are very complicated and relationships between classification bounding spheres are very complicated too. Based on detailed analysis of relationships between bounding hyper-spheres, a hybrid decision strategy is put forward to solve classification problem of the intersections for multi-class classification based on hyper-sphere support vector machines. First, characteristics of data distribution in the intersections are analyzed and then decision class is decided by different strategies. If training samples of two classes in the intersection can be classified by intersection hyper-plane for two hyper-spheres, then new test samples can be decided by this plane. If training samples of two classes in the intersection can be approximately linearly classified, new test samples can be classified by standard optimal binary-SVM hyper-plane. If training samples of two classes in the intersection cannot be linearly classified, new test samples can be decided by introducing kernel function to get optimal classification hyper-plane. If training examples belong to only one class, then new test samples can be classified by exclusion method. Experimental results show performance of our algorithm is more optimal than hyper-sphere support vector machines with only one decision strategy with relatively low computation cost.
Fiction in the context of cultural education (Some comments concerning modern oriental literature)

This research focuses on modern foreign literature which introduces readers to the socio-cultural field and widens the outlook of future professionals. Cultural knowledge allows to embrace both the values of the past and the best achievements of the present, which contributes to the formation of a well-rounded personality. Fiction is an important component of cultural knowledge thanks to its polyfunctional nature — it is a harmonious synthesis of science, technology and art, it facilitates personal growth and self-fulfillment. There are several strategies represented in foreign fiction. The article focuses on the following aspects vividly described in the 20th century literature: self-realization, self-development, self-discovery, the identification of “the other/ another” in social dimension, the relations between the person and the family, the person and the society as well as person to person relations. The evidence is taken from Eastern literature, which is less known to Russian readers. The article features examples that, in our opinion, highlight the socio-cultural issues that concern modern student audience. The article concludes that the world of fiction shapes a citizen and a highly cultured person. It develops heuristic thinking, esthetic taste and ideals and facilitates a more effective adaptation of a university graduate in market economy. Not only fiction as a whole, but also everyday realia provide for an integrated function of fiction in the educational process. As a whole, fiction forms students’ need for self-realization and self-assertion as an individual creative agent of culture, as a definite personality.
IMPLICIT LOGICAL-SEMANTIC RELATIONS AND A METHOD OF THEIR IDENTIFICATION IN PARALLEL TEXTS

One of the main characteristics of logical-semantic relations (LSRs) between two fragments of a text is that these relations can be either explicit (expressed by some marker, e.g. a connective) or implicit (derived from the interrelation of these fragments’ semantics). Since implicit LSRs do not have any marker, it is difficult to find them in a text (whether automatically or not). In this paper, approaches to analysing implicit LSRs are compared, an original definition for them is offered and differences between implicit LSRs and LSRs expressed by non-prototypical means are described. A method is proposed to identify implicit LSRs using a parallel corpus and a supracorpora database of connectives. Based on the well-known statement that LSRs can be explicitated by adding connectives in the translation, it is argued here that through selecting pairs in which fragments where a connective is used to express an LSR in the translation correspond to those containing any of the translation stimuli standard for this connective in the source language, it is possible to get an array of contexts in which this LSR is implicit in the source text (or expressed by means other than connectives). This method is then applied to study the French causal connectives car, parce que and puisque using a Russian-French parallel corpus. The corpus data are analysed to obtain information about LSRs particularly about cases where the causal LSR in Russian is implicit, as well as about the use of causal connectives in French. These results are used to show that the method proposed allows to quickly create a representative array of contexts with implicit LSRs, which can be useful in both text analysis and in machine learning.
PGS1, a new low cost and low power Portable Geo-physical Station “All in One”. Design and test

PGS1 is a new compact portable seismic station, designed at INGV OBS and Earth Lab, that is specifically intended for the deployment of dense arrays of seismographs on-shore. With its low cost, compact design, high data-quality and long battery life, PGS1 is a perfect solution for seismic monitoring networks. PGS1 design is based on a solid polypropylene suitcase, containing a complete data acquisition system, two battery packs and a photovoltaic panel. The new Earth Lab 5s medium-period seismic sensor is included. The whole system meets the IP67 standard requirements both in transport and in acquisition configuration. PGS1 is normally equipped with one battery pack, one more pack can be added inside the suitcase achieving 40 days of battery life. The station is equipped with a photovoltaic panel, useful to extend the deployment length. Inside the suitcase, there are compartments where to store the seismic sensor, the photovoltaic panel and all the cables. Therefore, the station is very easy to transport.
INOVASI PEMBELAJARAN PENULISAN NASKAH DRAMA ANAK DENGAN MENGGUNAKAN STRATEGI IDCD (IDENTIFICATION, DESIGN, CHANGE, DAN DEVELOPMENT)

The writing children's drama scripts is an underdeveloped skill. This happens because students not understand who children and how characteristic children. One way to solve this problem is to innovate learning strategies. The strategic innovation is IDCD (identification, design, change, and development). This strategy was created for the needs of writing skills, especially writing children's drama scripts for students. Strategies were created to create learning more creative, innovative children's drama script writing, and children's drama scripts that are created according to the child's level of development.
YOUNG PEOPLE’S ATTITUDES AND FINANCIAL BEHAVIOUR. EVIDENCE FROM ROMANIA

Nowadays, it is well known that money, through the means of obtaining and saving, has a major influence on the good functioning of the economy in society and implicitly in the process of its development. This influence has an impact on every individual in our society, on our decisions, choices, plans and preferences. At the same time, however, each participant in the economy of a state, whether it be individuals, companies, corporations or business partners, competes in the evolution of the economy through the type of management of the finances it adopts. In this regard, the present research aims to establish what is the young peoples' behavior (aged between 18 and 40) in terms of how to save money as well as the peoples' inclination to call a financial advisor for making decisions regarding the management of personal income and expenses. Therefore, with the help of survey type research, based on a questionnaire, the results of the study reveal an increased interest of Romanian young people in terms of the tendency to save money. It also highlights the awareness of the importance of financial knowledge in the process of saving money, as well as the tendency of respondents to constantly update this information, with the help of financial experts.
Top-K Human Activity Recognition Dataset

&lt;span lang="EN-US"&gt;The availability of Smartphones has increased the possibility of self-monitoring to increase physical activity and behavior change to prevent obesity. However self-monitoring on a Smartphtone comes with some challenges such as unavailability of lightweight classification algorithm, personalized dataset to completely capture bodily postures, subject sensitivity, limited storage and computational power. However, most classification algorithms such as Support Vector Machines, C4.5, Naïve Bayes and K Neighbor relies on larger dataset to accurately predict human activities. In this paper, we present top-k of compressed small personalized dataset to reduce computational cost with increased accuracy. We collected top-k personalized dataset from 13 recruited subjects. After benchmarking our collected dataset we found that the dataset is suitable for tree-oriented algorithm, especially the Random Forest, C4.5 and Boosted tree with accuracy and precision of 100% except for KNN, Support Vector and Naïve Bayes. Further, our top-k personalized dataset improves pruning and overfitting of tree-oriented algorithms. Moreover, the linear consistence of static human activities reveals the potential of our top-k dataset to be replicated to multiple-subject to close subject sensitivity challenge.&lt;/span&gt;
Individual educational trajectory of future teachers’self-organization development

The article reveals the features of building an individual educational trajectory in order to develop the level of future teachers’self-organization. For the purpose of conducting scientific research, we used the following methods: A. D. Ishkov's methodology "Diagnostics of the characteristics of self-organization", as well as the analysis of psychological and pedagogical literature on the issue of building an individual educational trajectory in order to develop the level of self-organization among students. As a result of diagnostics of the characteristics of the development of self-organization in future teachers, it was found that this level in students is not fully formed.
Demographic Factors Influencing the Adoption of Mobile Phones in the Utilization of Formal Financial Services by Smallholder Farmers in Kenya

The study aimed at assessing the demographic factors influencing adoption of mobile phones in the utilization of formal financial services by smallholder farmers in Kenya. Financial access household survey showed that 80 percent of Kenyan adults own a formal bank account. Whilst significant advances have been made in financial technology products, their penetration and usage among smallholder farmers in utilizing financial services and particularly the demographic factors influencing them remains unestablished. Research into more innovative, intermediated solutions, effective participation and inclusion of appropriate community-based groups in mobile financial services is, therefore, necessary. The target population for this study were smallholder farmers from Nakuru, Busia and Kirinyaga Counties in Kenya. Simple random sampling and Convenience sampling techniques were used to select 496 smallholder farmers as respondents for the study. Data was collected using copies of a researcher developed questionnaire and data collection sheet. Quantitative data was analysed using multiple linear regression analysis with the aid of SPSS software. The findings revealed that demographic factors were important in predicting mobile phone utilization for formal financial services among smallholder farmers in Kenya. Therefore, the study recommends that mobile phone mobile service providers should collaborate with financial service providers to enable the farmers upgrade their phones to access more financial services platforms.
Hardware Detection Method of Transmission Line Patrol Inspection Image Based on Improved YOLOV4 Model

In order to solve the problem of intelligent hardware detection in aerial images, a hardware target detection method based on improved YOLOV4 model is proposed. In order to solve the problems of dense hardware and occlusion in aerial images, the improved network based on channel and spatial hybrid attention mechanism can further improve the detection effect of dense occlusion hardware and reduce image false detection and missed detection. In order to solve the problem that there is a great error in the position of the detection frame caused by the interference between the hardware and the hardware and between the hardware and the background, the prior frame is optimized by K-means++, and it is determined that the anchors generated by K=12 is the best, and the detection boxes are more suitable for the target. The experimental results show that the proposed method solves the problems of missing detection, misdetection and inaccurate detection frame to some extent, in which the mAP (mean Average Precision) value of the performance index is increased from 65.03% to 70.72%. The research can lay a good foundation for further state detection and fault diagnosis of typical hardware.
PENERAPAN ALGORITMA J48 UNTUK DETEKSI PENYAKIT TIROID

Impaired thyroid function is often difficult to identify because the symptoms are not specific. The symptoms of thyroid disorder are very similar to various complaints due to modern lifestyles so it is often overlooked. As a result, patients often do not notice a problem and do not have to consult a doctor. Therefore, there is a study that implements methods to predict the disease which will facilitate the patient in diagnosing and early detection of thyroid levels. This research aims to predict against thyroid disease with the data used is the secondary data obtained from the UCI repository, this data is about the patient data affected by thyroid disease, while the method uses the J48 algorithm because in some studies, the J48 algorithm is proven to have good performance in detecting an illness, as well as producing high value of Accuasy and AUC. The stage of data analysis is based on the CRISP-DM method while algorithm testing is done with Weka tools. Results of the test obtained an accuracy value of 99.645%, and a AUC value of 0.992 thus the accuracy has Excellent Classification level.
PENERAPAN METODE STRUKTURAL ANALITIK SINTETIK (SAS) DALAM MEMBACA PERMULAAN SISWA KELAS II SDN 004 BATURIJAL HULU KECAMATAN PERANAP

This research was motivated by the low ability of students to read at the beginning, so the researchers applied the SAS method in order to help students who still had difficulty reading. This study aims to determine the difference between the pretest and posttest by applying the synthetic analytical structural method (SAS) in reading the beginning of grade II elementary school students and to determine the increase in the pretest and posttest in reading the beginning of students. This type of research is a type of pretest-posttest one group pre-experimental design, which is an experiment that is only carried out in one group, without comparison. This research was carried out in class II SDN 004 Baturijal Hulu, Peranap sub-district with a total of 29 students. Based on the research results, it was found that the average value of reading ability before being treated (pretest) was 51.68 while the average value of reading ability after treatment (posttest) was 88.65 and the average value of normality gain was 0.76 which including the high category and the results of hypothesis testing using t-test with t = 47.191 and t table = 2.045, it is concluded that t count&gt; t table, then reject H0 means significant. This means that there is a significant increase in pre-test reading in grade II students between before (pretest) and after (posttest) applying the Synthetic Structural Analytical (SAS) method.