Reviewerly/exHarmony huggingface dataset:
An active contour model for medical image segmentation using a quaternion framework

This paper presents a new method for segmenting medical images is based on Hamiltonian quaternions and the associative algebra, method of the active contour model and LPA-ICI (local polynomial approximation - the intersection of confidence intervals) anisotropic gradient. Since for segmentation tasks, the image is usually converted to grayscale, this leads to the loss of important information about color, saturation, and other important information associated color. To solve this problem, we use the quaternion framework to represent a color image to consider all three channels simultaneously when segmenting the RGB image. As a method of noise reduction, adaptive filtering based on local polynomial estimates using the ICI rule is used. The presented new approach allows obtaining clearer and more detailed boundaries of objects of interest. The experiments performed on real medical images (Z-line detection) show that our segmentation method of more efficient compared with the current state-of-art methods.
BWCFace: Open-set Face Recognition using Body-worn Camera

With computer vision reaching an inflection point in the past decade, face recognition technology has become pervasive in policing, intelligence gathering, and consumer applications. Recently, face recognition technology has been deployed on bodyworn cameras to keep officers safe, enabling situational awareness and providing evidence for trial. However, limited academic research has been conducted on this topic using traditional techniques on datasets with small sample size. This paper aims to bridge the gap in the state-of-the-art face recognition using bodyworn cameras (BWC). To this aim, the contribution of this work is two-fold: (1) collection of a dataset called BWCFace consisting of a total of 178K facial images of 132 subjects captured using the body-worn camera in in-door and daylight conditions, and (2) open-set evaluation of the latest deep-learning-based Convolutional Neural Network (CNN) architectures combined with five different loss functions for face identification, on the collected dataset. Experimental results on our BWCFace dataset suggest a maximum of 33.89% Rank-1 accuracy obtained when facial features are extracted using SENet-50 trained on a large scale VGGFace2 facial image dataset. However, performance improved up to a maximum of 99.00% Rank-1 accuracy when pretrained CNN models are fine-tuned on a subset of identities in our BWCFace dataset. Equivalent performances were obtained across body-worn camera sensor models used in existing face datasets. The collected BWCFace dataset and the pretrained/ fine-tuned algorithms are publicly available to promote further research and development in this area. A downloadable link of this dataset and the algorithms is available by contacting the authors.
Using ROC and Unlabeled Data for Increasing Low-Shot Transfer Learning Classification Accuracy.

One of the most important characteristics of human visual intelligence is the ability to identify objects. The capability to distinguish between a substance which a human mind has no previous experience of and a familiar object, is innate to every human. In everyday life, within seconds of seeing an unknown object, we are able to categorize it as such without any substantial effort. Convolutional Neural Networks, regardless of how they are trained (i.e. in a conventional manner or through transfer learning) can recognize only the classes that they are trained for. When using them for classification, any candidate image will be placed in one of the available classes. We propose a low-shot classifier which can serve as the top layer to any existing CNN that the feature extractor was already trained. Using a limited amount of labeled data for the type of images which need to be specifically classified along with unlabeled data for all other images, a unique target matrix and a Receiver Operator Curve (ROC) criterion, we are able to increase identification accuracy by up to 30% for the images that do not belong to any specific classes, while retaining the ability to identify images that belong to the specific classes of interest.
Research on Power Quality Data Placement Strategy Based on Clustering-Genetic Algorithm

Data placement in multiple data centers is the key to optimizing computing performance. The power quality monitoring system of State Grid uses data centers of all provinces to store monitoring data nearby, and realize data calculation across provinces by workflow. This type of placement based on the area has the problem that the data transmission time is too long. In view of the above problem, a data placement strategy based on clustering-genetic algorithm is proposed. In this algorithm, the initial population generation algorithm based on data correlation clustering makes the individuals in the initial population have a certain degree of clustering accuracy and strong diversity. The initial population generation algorithm and the adaptive operator of genetic algorithm cooperate with each other, which effectively enhances the algorithm's ability to find the best. Compared with the traditional data placement strategy, the experimental results show that the data placement strategy based on clustering-genetic algorithm is more efficient than the traditional genetic algorithm strategy. Compared with the traditional clustering algorithm, it can effectively reduce the data transmission time of the workflow runtime, the average reduction of about 15%.
처격조사 ‘에’, ‘에서’의 사용 양상 고찰 -한국어 문법 교육을 중심으로-

It is difficult for a Korean language learner to understand the difference between the use of locative case markers ‘-e(에)’ and ‘-eseo(에서)’ in most cases, when used as the meaning of ‘place, scope,’ and so on.In general, it is likely that most learners have been taught that ‘-e(에)’ is combined with a static verb and ‘-eseo(에서)’ is combined with a dynamic verb during the early stage of second language acquisition. However, in practice, this kind of ‘selectional restriction’ is not effective in distinguishing ‘-e(에)’ from ‘-eseo(에서)’, especially when the predicate is an adjective or an intransitive verb. This study suggests that educators should avoid the traditional way of distinction, which is centered on predicates, and encourages the teachers of Korean to provide learners with information about the differences in ‘subtle nuances’ of the two locative case markers, focusing on the perspective of the deep semantic structure of the sentence and the semantic elements(meaning of the context，the spatial meaning of the previous noun phrase, time semanteme). The semantic map model, which is a useful tool for inducing the implicative universality of language types, is an effective way to help teachers grasp the difference between the learner''s native language and the target language from a cognitive point of view before they conduct a multi-national Korean lesson.(Hankuk University of Foreign Studies)
Design of Wheeled Robot Based on Visual Navigation

With the rapid development and innovation of science technology, the traffic intelligence level is improved day by day. In order to enable the wheeled robot to drive autonomously, STM32F103RCT6 MCU was selected as the controller of the path recognition wheeled robot, OV7670 digital CMOS image sensor was selected as the path information acquisition sensor, and SCA60C inclination sensor is selected as the road slope information acquisition sensor, A wheeled robot based on visual navigation was designed. In addition, in this paper, we compiled the control program of the wheeled robot for path recognition through Keil μVision5 IDE development software, and realized the automatic path recognition and autonomous operation of the robot with hardware circuit, and improved the mechanical structure and control algorithm of the robot in debugging. It was proved that the robot designed in this paper has the advantages of reasonable structure, CMOS image sensor foresight, and image binarization is stable with visual navigation algorithm, which has obvious advantages compared with traditional path recognition robot.
진대(晉代) 곽박(郭璞)의 음주(音注)에 나타난 성모 체계

In this study we reconstruct the phonological system of initials as reflected in the Sound Glosses of Guo Pu[郭璞] of the Jin Dynasty[晉代]. His Sound Glosses include the direct phonetic notaions[直音法] and the fanqie spellings[反切注音法]. We have examined more than 1,600 cases of his glosses to find out which stage his initial system was placed in between Old Chinese[OC] and Middle Chinese[MC]. The result of each predecessor is not showing exactly the unified trends with regard to the Guo’s initial system, but each of them mostly claims that his initial system was making its way close to MC and was simultaneously being away from that of OC. We investigate whether the major following changes had been completed in the Guo’s system, i.e., palatalisation of zhang series[章組], glottalisation of ying series[影組], fricativisation of xie initial[邪母], zero initialisation of yi initial[以母], and the split of ri initial[日 母] from ni initial[泥母] or niang initial[娘母]. If many of the above phenomena had been realised in his glosses, his system could be closer to that of MC as many of the previous studies concluded. But unlike the other studies, our close examination reveals that there are less cases of convincing evidence as for the completion of the above changes than for the preservation of OC phonology. Consequently, we can postulate that phonology of the initials in the Guo’s had not much evolved from that of OC. Besides, we also discover the vestiges of some of initial clusters which were still preserved as of his time although they did not exist in great quantities.
Modeling of physical education in the e-learning system for the physical culture discipline

At the present dynamic development of education, distance learning is increasingly popular due to its mobility and a variety of different information. There are certain difficulties in organizing the educational process using electronic educational resources. The article describes the modeling of the physical education process in non-sports institutes of Udmurt State University. The developed e-learning system at the University based on the Moodle platform allowed us to simulate the process of physical education and create an e-learning course based on it. The training course has a block system for organizing the physical education model. Using the e-learning system in the educational process of higher education allows to modernize the process of students’ physical education non-sports institutions, and lay a solid foundation for further self-education. This material is useful for University teachers who have an electronic educational environment.
PENGGUNAAN LAS ASETILEN DAN PERMASALAHANNYA DI KAPAL KN. SUAR 007 DISTRIK NAVIGASI KELAS III CILACAP

oxygen acetylene welding ( OAW) welding is welding done by burning acetylene gas with oxygen, causing a flame with a temperature that can melt the parent metal and filler metal. In applications, oxygen acetylene welding (OAW) welding results are very satisfying for welding carbon steel, especially sheet metal and thin-walled pipes. Working with oxygen acetylene welding (OAW) welding must be in accordance with the procedure, so that the results of a good weld are obtained and the person working can be safe and healthy. The core or neutral flame is the onset of burning of carbon (carbon) from acetylene. External flame is the result of combustion of carbon monoxide (CO) and hydrogen (H2) gas with acid from the air (02). the usefulness of this flame is, for ordinary welding and for welding steel or cast iron. The limitation of the problem with this screening is to overcome the clogged tip of the welding gun. The burner that is used continuously, will cause the burner tip to become dirty and clogged. The burning tip that is blocked will cause an abnormal flame.Keywords: Las acetylene, the problem, neutral flame
Analyzing task-specific patterns in human scanpaths

Humans gather high-resolution visual information only in the fovea, therefore they must make eye movements to explore the visual world. The spatio-temporal fixation patterns (scanpaths) of observers carry information about which aspects of the environment are currently relevant. Most of the recent progress on predicting the spatial and spatio-temporal patterns of human scanpaths has been focused on free-viewing conditions. However, fixations and scanpaths are known to be strongly influenced by the task performed by observers. The purpose of this work is to analyze those influences in a quantitative way. The DeepGaze III model for scanpath prediction (Kümmerer et al, VSS 2017) has been shown to achieve high performance in predicting free-viewing scanpaths. DeepGaze III extracts features from the VGG deep neural network that are used in a readout network to predict a saliency map, which is then processed in a second readout network together with information on the scanpath history to predict upcoming saccade landing positions. Here, we train different task-specific versions of DeepGaze III on human scanpath data of subjects performing different tasks on the same images (freeviewing, objectsearch, saliencysearch; Koehler et al., JoV 2014). Prediction performances show that the models successfully adapt to the task-specific scanpaths. We find and visualize cases where the model predictions differ substantially for the different tasks. The task-specific models can be used to detect the task of a given scanpath via maximum-likelihood classification. We find that while purely spatial task-specific models (finetuned versions of DeepGaze II) perform above-chance (43%) at task recognition, changing to the scanpath-aware DeepGaze III models improves performance further to 45%. This quantifies spatial and temporal contributions to task-specific differences in human scanpaths. In the future, we plan to extend our analysis towards quantifying differences in the way scene content and scanpath history interact in fixation selection in different tasks.
Cross-species representations of dynamic facial expression

Primates’ facial expressions represent an important channel of emotional communication. Human and monkey expressions of the same emotion can be quite different. How efficiently can we learn to recognize facial expressions of another primate species, and can we understand human facial movements, even if they are linked to faces of another species? METHODS: To clarify these questions, exploiting state-of-the-art technology in computer animation, we have developed highly realistic models of dynamically moving macaque and human heads. These faces were animated using human and monkey motion capture data. Using a hierarchical generative Bayesian model (combining GP-LVMs and GPDMs), we interpolated continuously in space-time between the facial movements representing emotional expressions in humans and monkeys. In addition, this technique allows to modify continuously the expressiveness of such facial movements. Exploiting these stimuli, we categorized facial movements from a two-dimensional morphing space, including two expressions from humans and monkeys in terms of expression and species. Movements were presented on the monkey and the human face model. RESULTS: Representation of facial movement was largely independent of the basic form of the face (human or monkey). For natural expressions we found no own-species advantage in the categorization, but instead higher expressiveness of the monkey expressions. This effect is diminished if stimuli are balanced in terms of expressiveness by equating their optic flow content. This supports a joint perceptual representation for dynamic expressions from different species with a separate encoding of the basic shape of the face and its motion. Also, it suggests a critical role of optic flow in the processing of dynamic facial expressions.
Application of Deep Neural Networks to Model Omnidirectional Gaze Behavior in Immersive VR

Convolutional neural networks (CNNs) are powerful computational tools for understanding visual cognition, including human gaze behavior (O’Connell et al., 2018). Traditionally, CNNs are designed to model visual images that typically represent a single field-of-view. Yet, the naturalistic visual world extends 360° around us, and information often extends beyond one discrete field-of-view to surrounding areas of the environment. Recent advances in virtual reality (VR) head-mounted displays, integrated with in-headset eyetrackers, provide the ability to emulate the natural 360° environment with greater stimulus control while simultaneously recording participant’s gaze. Here, we illustrate a method of leveraging any existing, pre-trained CNN to provide inferences about 360° naturalistic scenes, and demonstrate the application of these omnidirectional CNN activation maps in providing insight about gaze behavior in immersive virtual environments. First, single fields-of-view are evenly sampled from the equirectangular projection of the omnidirectional image and spherical distortions are removed through gnomonic projection. Next, CNN activation maps are generated for each field-of-view, and CNN layer activations in response to these images are recombined to create an aggregate equirectangular image. Finally, the aggregated equirectangular image is smoothed using a variable width gaussian kernel to account for projection distortions to produce maps. In a set of 20 individuals, we demonstrate comparisons of 360° gaze behavior with CNN layer activations of image salience (SalNet; Pan et al., 2016), memorability (AMNet; Fajtl et al., 2018), and semantically meaningful image features (VGG; Simonyan et al., 2014). All in all, we outline a method for extending existing CNN activation maps to omnidirectional images, and show the utility of these maps for predicting gaze behavior in real-world, omnidirectional environments.
‘놂[游]’으로서의 순례 ―‘대장정(大長程) 인문학’ 구축을 위한 현장법사의 서역(西域) 순례 다시 읽기

This study was designed as part of the work to build ‘humanities of great journey’. ‘Great journey’ refers to a journey in which one journey engendered text, and that caused another text and different humanities. Therefore, the humanities of great journey is composed of the journey that can be regarded as great journey, the resulting text, and other texts and humanities created by them. Specifically, in this article, I first presumed journey as a kind of ‘游[ludus]’. Next, I clarified the nature of 游[ludus]. Then, through the Xuanzang(玄奘)’s pilgrimage to the Western Regions[西域], the assertion that the journey would be reborn as a great journey when such nature was fully realized. To this end, I established the concept of the great journey, and at the same time, exemplified the practice of great journey on the basis of the corresponding cases in the history of China. This article has four chapters. Chapter 1 is an introduction. In Chapter 1, I explained the reason why I named the journey that created the ‘texts of civilization’ as great journey, and presented the topic of humanities of great journey’ as a subject of the human achievement achieved by great journey, As a first step for the construction of humanities of great journey, a brief explanation was given of the pilgrimage to the Western Regions and the reason to deal with the Datang Xiyouji大唐西域記. However, in order to achieve the purpose of this study, it is necessary to define the concept of key terms necessary for the construction of humanities of great journey. I think ‘游[ludus]’ is one of the key terms. In chapter 2, I dealt with the case of great journey in the history of humanity in China, and based on this, we built the concept of ‘游 [ludus]’. Through this, I identified the reason why ‘游[ludus]’ was chosen as a key concept in the construction of humanities of great journey. In chapter 3, the pilgrimage to the Western Regions which created the texts of civilization, Datang Xiyouji大唐西域記, was re-examined from the angle of ‘游[ludus]’. In this process, I considered the reason why the pilgrimage to the West Regions was ‘游[ludus]’ and what made the pilgrimage to the truth into ‘游[ludus]’. Chapter 4, as a conclusion, I summarizes the previous discussions and highlights the current implications of constructing humanities of great journey’.
Суб’єкти прав інтелектуальної власності

The article is devoted to the topical problem of determining the range of intellectual property subjects. The analysis of norms of the current Ukrainian legislation in the field of intellectual property is carried out. It is proposed to supplement the articles of the Civil Code of Ukraine on the definition of intellectual property by such categories as animal and “electronic person”.
Measuring the importance of temporal features in video saliency

Models predicting human gaze positions on still images have been greatly improved in the last years. Since motion patterns are an important factor driving human gaze as well (Rosenholtz 1999, Itti 2005, Dorr et al. 2010), there is growing interest in modelling human gaze positions on videos. In our work, we explore to what extent human gaze positions on recent video saliency benchmarks can be explained by static features. We apply models that cannot learn temporal patterns by design on the LEDOV and DIEM datasets and compare them to a gold standard model as an estimate of the explainable information. We first consider DeepGaze II (Kümmerer et al. 2017), the current state-of-the-art model for images, by applying it to every frame individually. To incorporate the time lag in human responses we consider two adaptations of DeepGaze II that predict gaze positions on the last frame of a fixed length window: First, we temporally average the predictions of DeepGaze II. Additionally we propose a new model "DeepGaze MR" that temporally averages image features and uses an adapted, nonlinear readout network to predict gaze positions. By design, all model variants are still not able to detect movements, appearances or interactions of objects. Our new model substantially outperforms previous video saliency models and explains 75% of the information on the LEDOV and 43% on the DIEM dataset. By analyzing failure cases of our model, we find that clear temporal effects on human gaze placement exist, but are rare in the benchmarks considered. Moreover, none of the recent video saliency models considered is able to predict human gaze in those cases better than our static baselines. To foster the data-driven modelling of temporal features affecting human gaze, we propose a meta-benchmark consisting of the hard cases found by our analysis.
『詩經』에 대한 雜感性 문장, 『詩廣傳』 考察

The purpose of this paper is twofold. First, look at the special composition features of the Shi Guang Zhuan(詩廣傳) which extensively explored the Shi Jing (詩經), one of Six Confucian classics(儒家六經), as ‘Guang Zhuan(廣傳)’ an original ‘an essay style.’ Second, consider the inherent core content that penetrates the core of the philosophy and literary assertions of the Shi Guang Zhuan(詩廣傳). Wang Fuzhi(王夫之)’s Shi Guang Zhuan(詩廣傳) is very unique away from traditional books and interpretations of the Shi Jing(詩經). Under the influence of early Qing Dynasty(淸朝)’s Thought of Practical application(經世致用), This book consists of the sentence Mixed Feeling(雜感), which expounds the original meaning of each of the Shi Jing(詩經) and writes down one’s arguments freely and widely. Wang Fuzhi(王夫之) made his point, looking at these works from an individual's philosophy, history, politics, ethics and literature perspective. Wang Fuzhi(王夫之) argued in the Shi Guang Zhuan(詩廣傳) that: The essence of poetry lies in the Qing(情), which is the Qing(情) of Xing(性) downloaded from heavenly principles(天理), not instinctively the Seven feelings(七情). Wang Fuzhi(王夫之)’s this opinion is a succession of Cheng Zhu studies(程朱理 學)’ views. However, in order to realize the Shi Jing(詩經)'s Educational Purpose(詩 敎), the Placid and gentry(溫柔敦厚) of the confucian Poetics(儒家詩學), it has made an unusual opinion to moderation and generosity in Qing(情). This particular argument has had the effect of greatly expanding the even logical fence of the placid and gentry of rigid confucian Poetics.