Reviewerly/exHarmony huggingface dataset:
Controllable Image Generation via Collage Representations

Recent advances in conditional generative image models have enabled impressive results. On the one hand, text-based conditional models have achieved remarkable generation quality, by leveraging large-scale datasets of image-text pairs. To enable fine-grained controllability, however, text-based models require long prompts, whose details may be ignored by the model. On the other hand, layout-based conditional models have also witnessed significant advances. These models rely on bounding boxes or segmentation maps for precise spatial conditioning in combination with coarse semantic labels. The semantic labels, however, cannot be used to express detailed appearance characteristics. In this paper, we approach fine-grained scene controllability through image collages which allow a rich visual description of the desired scene as well as the appearance and location of the objects therein, without the need of class nor attribute labels. We introduce "mixing and matching scenes" (M&Ms), an approach that consists of an adversarially trained generative image model which is conditioned on appearance features and spatial positions of the different elements in a collage, and integrates these into a coherent image. We train our model on the OpenImages (OI) dataset and evaluate it on collages derived from OI and MS-COCO datasets. Our experiments on the OI dataset show that M&Ms outperforms baselines in terms of fine-grained scene controllability while being very competitive in terms of image quality and sample diversity. On the MS-COCO dataset, we highlight the generalization ability of our model by outperforming DALL-E in terms of the zero-shot FID metric, despite using two magnitudes fewer parameters and data. Collage based generative models have the potential to advance content creation in an efficient and effective way as they are intuitive to use and yield high quality generations.
Hopfield model with planted patterns: a teacher-student self-supervised learning model

While Hopfield networks are known as paradigmatic models for memory storage and retrieval, modern artificial intelligence systems mainly stand on the machine learning paradigm. We show that it is possible to formulate a teacher-student self-supervised learning problem with Boltzmann machines in terms of a suitable generalization of the Hopfield model with structured patterns, where the spin variables are the machine weights and patterns correspond to the training set's examples. We analyze the learning performance by studying the phase diagram in terms of the training set size, the dataset noise and the inference temperature (i.e. the weight regularization). With a small but informative dataset the machine can learn by memorization. With a noisy dataset, an extensive number of examples above a critical threshold is needed. In this regime the memory storage limits of the system becomes an opportunity for the occurrence of a learning regime in which the system can generalize.
Automated calibration of consensus weighted distance-based clustering approaches using sharp

In consensus clustering, a clustering algorithm is used in combination with a subsampling procedure to detect stable clusters. Previous studies on both simulated and real data suggest that consensus clustering outperforms native algorithms. We extend here consensus clustering to allow for attribute weighting in the calculation of pairwise distances using existing regularised approaches. We propose a procedure for the calibration of the number of clusters (and regularisation parameter) by maximising a novel consensus score calculated directly from consensus clustering outputs, making it extremely computationally competitive. Our simulation study shows better clustering performances of (i) models calibrated by maximising our consensus score compared to existing calibration scores, and (ii) weighted compared to unweighted approaches in the presence of features that do not contribute to cluster definition. Application on real gene expression data measured in lung tissue reveals clear clusters corresponding to different lung cancer subtypes. The R package sharp (version 1.4.0) is available on CRAN.
Sound and voice information transfer enhancement of OLED TV in OTT environment

People get a lot of information around them through visual, auditory, and various senses. In particular, audiovisual data is a very important information transfer factor and has developed various technologies and methods for a long time . In previous studies, we have found that a better effect is achieved when the focus of the screen matches the focus of the sound. To that end, it is now possible to create a sound by vibrating a modern display panel, such as an OLED (Organic Light-Emitting Diode). In our previous research, we have studied the research of creating a stereo sound by directly vibrating a single plane, the reason why the sound of this method is better than the ordinary audio system, the position of the exciter optimized for sound quality, the shape of the exciter and the enclosure of speakers. In this study, a research was conducted on the understanding of the audience's voice by the sound composition in an over the top (OTT) environment that supplies a lot of content recently. In the OTT environment, we try to provide picture quality and sound similar to that of a theater. However, the traditional audio method rather lowers the ability to transmit information of voice. The sound system using the proposed sound radiation system overcomes this problem and creates a clear voice, thereby solving the viewer's discomfort with the sound.
Breast Ultrasound vs Mammography: Is the Former a Better Replacement for the Latter? A Comparative Study

Breast cancer is the most commonly occurring cancer in women. It is also the second leading cause of cancer death in women. Breast Cancer is the most common and most lethal cancer in Nigeria with an estimated 27,304 new cases in 2012 and which is estimated to increase in further years despite the lack of adequate data. Mortality rates are very high in our locality with approximately 13,960 deaths annually. Mammography is the gold standard for breast cancer screening in developed countries with some evidence showing improved survival particularly among women 50–69 years in some randomized controlled trials in developed countries where breast cancer prevalence is high. Studies gives a mammography sensitivity of (83-86%), a specificity of (48-55.5%), and a diagnostic accuracy of 56-68%. However, mammograms still pose the risk of exposing the breasts to radiation, and is also not well suited for women with dense breasts, implants, fibrocystic breasts, or those on hormone replacement therapy. Breast ultrasound has been used for many years in the characterization of breast lesions, and can also be used to help guide a biopsy needle into an area of the breast for testing. Ultrasound is relied upon significantly since mammographic facilities are few and breast magnetic resonance imaging is either too expensive or unavailable and is it also not limited by breast density. Studies show ultrasound has a sensitivity of (72.2% - 86.3%), and a specificity of (79.8-93.6%). Ultrasound is unable to screen for many types of breast cancer. It is also difficult to detect calcification in the ultrasound of the breast, and this is an early sign of breast cancer. Therefore ultrasound is mainly used in LMIC, where late presentation is most common due to lack of funds because it is cheaper and more portable and it also has a higher sensitivity in women greater than 40 years. In conclusion, this study aims to compare ultrasound and mammography if the former is a better replacement for the latter.
Educational space as object of socio-geographical research

The relevance of the study of the general educational space is strengthened by the fact that significant transformations are currently taking place in the general educational space as a component of the social space, which are taking place in parallel with the implementation of the decentralization reform. The article analyzes socio-geographical approaches to the study of the concept of general educational space, which we propose to consider as a component of educational space, from the point of view of general secondary education institutions. The place of educational space, as a component of geospace, is outlined in the socio-economic space, because it is the result of the interaction of social and economic spaces. The study identified local centers of the educational space that belong to educational institutions. The concept of "general educational space" is characterized, which we propose to define as the territory on which general secondary education institutions of various types and forms, as well as participants of the educational process, which ensure the implementation of educational activities, function, organize the general educational process and interact with each other. We determined the structure and properties of the general educational space. We propose to consider the structure of the general educational space as three-dimensional, highlighting at the same time such components (dimensions) as: territorial placement of educational institutions; participants in the general education process; the quality of providing educational services. General educational space, as a component of geospace, is characterized by such indicators as: length, dynamism, structure and continuity. Quantitative and qualitative indicators of the functioning of the general educational space were described. Characterization of the structure of the general educational space of the regional region, which plays a special role in the study of the development of education, was carried out. The general educational space has the potential that creates the foundation of national security, ensures the competitiveness of the country, the region among other national state bodies.
Adaptive Kalman Filter based on Variational Bayesian Approach for One-step Randomly Delayed Measurements

This article addresses the state estimation problem for dynamic systems with linear models wherein covariance matrices of the process and measurement noise are unknown and one step delay randomly occurs in the measurements. Due to network congestion, limited bandwidth during transmission of sensor data to the central processing unit the probability of measurements getting randomly delayed is high and this phenomenon is ignored for conventional adaptive Kalman filters. A new algorithm for Adaptive Kalman filter with one step randomly delayed measurements is proposed here wherein the randomly delayed measurements are modelled using Bernoulli’s distribution. The adaptation algorithm has been mathematically derived for such situations following the variational Bayesian approach and subsequently a recursive algorithm for variational Bayesian adaptive delayed Kalman filter is formulated. Monte Carlo simulation demonstrates the excellence of the proposed filter over the conventional Kalman filter for the estimation problem addressed in this work. The comparative study with the competing MLE-based variant also reveals the superiority of the proposed filter. To exemplify the effectiveness of the proposed algorithm for real world applications validation with the real measurement data has been carried out for offline harmonics estimation which ensures satisfactory estimation results.
The Effect of Self Regulated Learning, Self Efficacy and Learning Motivation on Economic Learning Achievement with Gender as Moderating Variable

The Effect of Self Regulated Learning, Self Efficacy and Learning Motivation on Economic Learning Achievement with Gender as Moderating Variable. Objective: This study analyzes whether gender moderates the effect of self-regulated learning, self-efficacy, and learning motivation on economic achievement. Methods: This research is a quantitative research with a correlational. The population in this study was students of Social Studies XI in Boyolali, as many as 1,284 students. This research uses cluster random sampling. The number of samples is 308 students. Data collection techniques using a questionnaire. Data analysis technique uses moderated regression analysis (MRA). Findings: The self-regulated learning variable obtained a t-count: 1.385 &lt;1.656 with a sig. 0.167 &gt; 0.05, self-efficacy variable, t-count: 1.929 &gt; 1.656 with a sig. 0.055 &gt; 0.05. The learning motivation variable obtained a t-count: 2.122 &gt; 1.656 with a sig. 0.035 &lt;0.05. Conclusion: There is no difference in self-regulated learning between male and female students. Gender has a positive but not significant effect on self-efficacy. Gender has a positive and significant influence on learning motivation. Keywords: self regulated learning, self efficacy, motivation, learning achievement, gender Abstrak: Pengaruh Self Regulated Learning, Self Efficacy dan Motivasi Belajar terhadap Prestasi Belajar Ekonomi dengan Jenis Kelamin sebagai Variabel Moderasi. Tujuan: penelitian ini untuk menganalisis apakah jenis kelamin memoderasi pengaruh self-regulated learning, self-efficacy, dan motivasi belajar terhadap prestasi belajar ekonomi. Metode: Penelitian ini merupakan penelitian kuantitatif dengan jenis korelasional. Populasi dalam penelitian ini adalah seluruh siswa kelas XI IPS jenjang SMA di Kabupaten Boyolali sebanyak 1.284 siswa. Penelitian ini menggunakan cluster random sampling. Jumlah sampel 308 siswa. Teknik pengumpulan data menggunakan angket. Teknik analisis data menggunakan Moderated Regression Analysis (MRA). Temuan: Berdasarkan uji MRA diperoleh variabel self-regulated learning memperoleh t-hitung 1,385 &lt; 1,656 dengan tingkat sig. 0,167 &gt; 0,05. Variabel self-efficacy, t-hitung: 1,929 &gt; 1,656 dengan nilai sig. 0,055 &gt; 0,05. Variabel motivasi belajar memperoleh t-hitung 2,122 &gt; 1,656 dengan nilai sig. 0,035 &lt; 0,05. Kesimpulan: Tidak ada perbedaan self -regulated learning antara siswa laki-laki dan perempuan. Jenis kelamin memiliki pengaruh positif namun tidak signifikan pada self-efficacy. Jenis kelamin memiliki pengaruh positif dan signifikan motivasi belajar terhadap. Kata kunci: self regulated learning, self efficacy, motivasi, prestasi belajar, jenis kelamin. DOI: http://dx.doi.org/10.23960/jpp.v13.i2.202303
Blended Learning in Russian Higher Education: The Evolution of the Term in Science and Practice

Background/purpose -The concept of "blended learning" was adopted into Russian education from other countries.However, under the new conditions, the authors' original idea of combining different forms of learning has been transformed into a mixture of online and offline learning.This study aims to analyze the factors that led to the transformation of this concept in Russian research papers and the practice of teaching in Russian universities.The observation method was necessary to describe how the term is applied and to draw conclusions about how it is understood by teachers.Materials/methods -The study is based on the comparative method, which includes a selection, description, and analysis of different interpretations of the studied concept in more than 90 Russian and foreign scientific publications.The results of the analysis are presented diagrammatically, allowing for consolidation of a new perspective on this area of research.Results -The study showed that Russian researchers understand blended learning to be a combination of online and offline lessons, while the true meaning of the term is the combination of electronic learning and traditional face-to-face tools that can be used both synchronously and asynchronously.Conclusion -Prospects for the use of blended learning in Russian universities lie in the understanding that it requires a special form of learning process, in which students interact either with a teacher or with an electronic learning resource, depending on what is considered to help achieve the learning objectives most effectively.This requires the development of new educational technology based on innovative software.
Consumers’ Perception toward Brand Preferences while Purchasing Personal Care Products: A Study on Rajshahi City

This study conducted to focus the consumers’ perception of international brand over local brand while purchasing personal care products. Consumers’ perception highlighted on customer’s psychology that determines their viewing attitude towards using the local or international brand. Globalization makes the foreign trade easier than before and the availability of international brands confused the consumers’ ethnocentrism towards local brand but it is also true that using too much foreign products can destroy the employment opportunity of local people and also the country may face of security issues from foreigners. To examine the topic a convenient sampling method was applied to collect response from 280 customers from which 268 found free from errors; those respondents were used for the final study. The findings highlighted some factors that influence customers’ perception toward choosing brand while purchasing personal care products. Data were collected from local customer of new market and Shaheb Bazar area of Rajshahi city. Study reveals that according to the perception of the customer, product quality of local brands, price consideration, country of origin, availability of foreign brands and promotional actions have a significant role toward customer mind while purchasing products. Moreover the findings suggest that, for the wellbeing of the society, local products need foremost priority to expand their business. As it is known that more demand of local products lead more production that create more job opportunity in the market and to build the country as self-sufficient, a customer focused local market should be enhanced. The major contribution of the current study is that it focuses consumer’s observation and suggestion to create more opportunities for local brand in market place.
On Low-Resolution Face Re-identification with High-Resolution-Mapping

Low-resolution face re-identification refers to the problem of identifying if the same person’s face appears in two images: one image is low resolution (LR), e.g., from a surveillance camera, and the another one is high resolution (HR), e.g., from a government-issued identification. Research in low-resolution face re-identification has been increasing in the past few years. It can be divided into three categories: i) methods upscaling the LR image to the HR space (HR-mapping), ii) methods employing LR and HR robust features, and iii) methods learning a unified space representation. In this work, we focus on face re-identification using HR-mapping because it yields better results. Our main contribution is an experimental protocol that can be used as guideline in this task. In research, protocols are often neglected and researchers that utilize previous work on their projects have to allocate a significant amount of time to replicating inadequately described methods. We use our experimental protocol as a guideline to create a set of training and testing pairs for face re-identification using dataset VGG-Face-2. In addition, we conducted 18 experiments to validate the experimental protocol. In our experiments, we measured “d-prime” ( $$d'$$ ) and the area under the ROC curve ( $$A_z$$ ). We obtained: $$d'=1.236$$ and $$A_z=0.81$$ for a 14 $$\times $$ 14 LR pixel size set, $$d'=1.900$$ and $$A_z=0.91$$ for a 28 $$\times $$ 28 LR pixel size set and $$d'=2.787$$ and $$A_z=0.97$$ for a 56 $$\times $$ 56 LR pixel size set. We believe that our protocol can be very helpful for researchers in the field because it can be used as a set of guidelines for building comparable and replicable work of their own.
Classroom Language: Preparing the Pre-Service Teachers for Successful Classroom Interactions

Classroom Language: Preparing the Pre-Service Teachers for Successful Classroom Interactions. Objective: This study aims to investigate how pre-service teachers (PSTs) employ classroom language for Opening, Running, and Closing the Lesson in the classroom. Methods: A qualitative method was applied where the data were gathered through questionnaire sheets and an observation checklist. Thirty students in the second year of the English Education Study Program in Surabaya, Indonesia, participated in this study. Findings: The findings reveal that PSTs have applied classroom languages appropriately and successfully for eight components of basic teaching skills. Nevertheless, three components that do not vary are the language expressions attributed to opening the lesson for checking attendance, varying stimuli for setting and cleaning up teaching media, and organizing the small group discussion. Conclusion: The findings can be valuable input for the teacher of an education program to be more concerned with the teacher candidates’ language variations to prepare them for successful classroom interactions. Keywords: classroom language, pre-service teachers, classroom interactions Abstrak: Bahasa Kelas: Mempersiapkan Calon Guru untuk Keberhasilan Interaksi Kelas. Tujuan: Penelitian ini bertujuan untuk menginvestigasi bagaimana mahasiswa calon guru menerapkan bahasa kelas (classroom language) untuk membuka, melaksanakan, dan menutup pembelajaran dalam kelas. Metode: Metode kualitatif diterapkan dimana data dikumpulkan melalui lembar kuesioner dan observasi kelas. Tiga puluh siswa di tahun kedua dari program studi pendidikan bahasa Inggris di Surabaya, Indonesia, berpartisipasi dalam penelitian ini. Temuan: Hasil penelitian menunjukkan bahwa partisipan telah menerapkan bahasa kelas dengan tepat dan sukses untuk enam komponen dari ketrampilan dasar mengajar. Namun, tiga komponen yang terkait ungkapan bahasa yang tidak partisipan variasikan meliputi membuka pelajaran untuk memeriksa kehadiran, mengatur dan membersihkan media pengajaran, dan mengorganisasikan diskusi kelompok kecil. Kesimpulan: Temuan ini dapat menjadi masukan yang berharga bagi program pendidikan guru untuk lebih memperhatikan variasi bahasa yang calon guru gunakan dalam menyiapkan mereka untuk kesuksesan berinteraksi dengan peserta didik di kelas. Kata kunci: bahasa kelas, calon guru, interaksi kelas. DOI: http://dx.doi.org/10.23960/jpp.v13.i2.202304
DESIGNING A THEATRICAL COSTUME IN THE ALGORITHM OF COMMUNICATION BETWEEN THE ARTIST AND THE THEATER

The article considers the process of creating a stage costume as a multi-factor personalized design of a garment.Clothing for the stage is subject to increased aesthetic, psychological, social and functional requirements.Women's stage costume should emphasize the features of the figure, give the image elegance, conform to fashion and style, and show the vulnerability of nature.The authors' analysis of the operating conditions of stage garments, carried out at the stage of the technical task, showed the priority of the image aesthetics over the hygienic indicators of this garment.According to the results conducted by the authors monitoring of consumer preferences found that in the artistic environment consumer demands antropotehnicheskaya compliance of the costume correlated with psychophysical performance in the hierarchy of the properties, confirmed the primacy of compliance products for the scene style and modern fashion colours.The spatial organization of a clothing form for a scene is determined by the relationship between the materials that create it, and depends on their properties and structure.The study confirmed that modern form-resistant synthetic materials based on neoprene have the desired characteristics that allow for the projected complex spatial shape of the stage costume.The study developed a suit singers of the band Guru Groove Foundation Tatyana Shamanina for performances at the concert hall special architectural solutions.Testing of the stage costume showed that garments made of innovative form-resistant materials have the desired characteristics and are attractive in appearance.Clothing made of neoprene does not require special care, the color coating is resistant to the external environment, Soaps, chemicals, so the products will be in demand in the target group of consumers.