Reviewerly/exHarmony huggingface dataset:
Real-Time Intelligent Facial Expression Recognition System

Facial expression plays an important role in conveying the non-verbal cues of any person. In this research, a real-time detection of emotions has been performed by training the model into different data sets and then emotional state of a person is displayed. The aim of the project is to recognize human emotions in real-time which are based on their facial expressions. Tremendous work has been done in recognizing emotions using facial expression but little work is done on recognizing eight emotions in real-time. For this purpose, a real-time system to judge eight emotions using facial expression has been designed. Further, the performance of the proposed method is evaluated by using trained database using Convolution Neural Network (CNN) and Support vector machines (SVM). Experimental results and prototype show the accuracy of detected emotions in real-time. This research work has been conducted to recognize human emotions in Real-time and increased the accuracy for CNN algorithm. The study is concluded which results in recognition of eight universal emotions; neutral, happy, sad, anger, disturbed, fear, surprised, nervous in real time by the proposed system.
Face frontalization with deep GAN via multi-attention mechanism

In recent years, the development of deep learning has led to some advances in face synthesis approaches, but the significant pose remains one of the factors that are difficult to overcome. Benefiting from the proposal and development of the generative adversarial network, the level of face frontalization technology has reached new heights. In this paper, we propose a deep generative adversarial network based on the multi-attention mechanism for multi-pose face frontalization. Specifically, we add a deep feature encoder based on the attention mechanism and residual blocks in the generator. Meanwhile, to carry the global and local facial information, the discriminator of our model consists of four independent discriminators. The results from quantitative and qualitative experiments on CAS-PEAL-R1 dataset show that our model proves effective. The recognition of our model exceeds or equals the highest recognition rate of other models at some angles, such as 100% at β = 0°, α = 15° and 99.78% at β = 30°, α = 0°.
Keefektifan Metode Practice Rehearsal Pairs dan Media Animasi Powtoon Pada Keterampilan Bercerita (The Effectiveness of the Practice Rehearsal Pairs Method and Powtoon Animation Media on Storytelling Skills)

This study aims to examine the effectiveness of the practice rehearsal pairs method and Powtoon animation on storytelling skills. This quasi-experimental research has control and experimental classes. The experimental group received treatment in the form of a practice rehearsal pairs method with Powtoon media and the control group received treatment with a storytelling model with picture media. Both get pretest and posttest for. The prerequisite test uses SPSS 26. The result is a Sig. (2-tailed) 0.0000 &lt;0.005 indicates that Ho is rejected. Storytelling skills in learning Indonesian for the two classes are slightly different. The experimental class pretest mean was 59.75 while the posttest was 82.25. The mean of the control class pretest was 57.50 while the posttest was 75.00. There are differences in the results of the experimental and control classes. The class that was given the treatment had higher results compared to the class that was not given the treatment. Penelitian ini bertujuan untuk menguji keefektifan metode practice rehearsal pairs dan animasi Powtoon pada keterampilan bercerita. Penelitian quasi experiment ini memiliki kelas kontrol dan eksperimen. Kelompok eksperimen mendapatkan perlakuan berupa metode practice rehearsal pairs dengan media Powtoon dan kelompok kontrol mendapatkan perlakuan dengan model story telling dengan media gambar. Keduanya mendapatkan pretes dan postes untuk. Uji prasyarat menggunakan SPSS 26. Hasilnya Diperoleh nilai Sig. (2-tailed) 0,0000 &lt; 0,005 menunjukkan bahwa H o ditolak. Keterampilan bercerita dalam pembelajaran Bahasa Indonesia terhadap kedua kelas sedikit berbeda. Rerata pretes kelas eksperimen adalah 59,75 sedangkan postes 82,25. Rerata pretes kelas kontrol 57,50 sedangkan postes 75,00. Ada perbedaan hasil dari kelas eksperimen dan kontrol. Kelas yang diberi perlakuan, hasilnya lebih tinggi dibandingkan dengan kelas yang tidak diberi perlakuan.
Hand action recognition in rehabilitation exercise method using R(2+1)D deep learning network and interactive object information

Hand action recognition in rehabilitation exercises is to automatically recognize what exercises the patient has done. This is an important step in an AI system to assist doctors to handle, monitor and assess the patient’s rehabilitation. The expected system uses videos obtained from the patient's body-worn camera to recognize hand action automatically. In this paper, we propose a model to recognize the patient's hand action in rehabilitation exercises, which is a combination of the results of a deep learning network recognizing actions on Video RGB, R(2+1)D, and a main interactive object in the exercises detection algorithm. The proposed model is implemented, trained, and tested on a dataset of rehabilitation exercises collected from wearable cameras of patients. The experimental results show that the accuracy in exercise recognition is practicable, averaging 88.43% on the test data independent of the training data. The action recognition results of the proposed method outperform the results of a single R(2+1)D network. Furthermore, the better results show the reduced rate of confusion between exercises with similar hand gestures. They also prove that the combination of interactive object information and the action recognition improve the accuracy significantly.
Research on Multi-target Coverage UAV Network Layout Method Based on Data Analysis Algorithm

Multi-objective overlay is a new comprehensive concept that can satisfy multiple constraints and performance metrics while having multiple objective functions independent of the system and is widely used in many fields such as military, aerospace and industry. At the same time, it can meet various requirements for system resources and security in different situations. This paper firstly analyzes the application of data analysis method in UAV network layout method, which mainly performs data screening, data pre-processing, decision tree classification on the collected data, and then plans the UAV network by decision tree classification; secondly, it introduces the multi-objective coverage model of UAV sensors and introduces two commonly used models; finally, this paper studies the data analysis algorithm based on the multi- target coverage UAV network layout method based on data analysis algorithm.
THE ESSENCE OF THE DIGITAL IMAGE OF AN EDUCATIONAL ORGANIZATION

Interest in studying the development of the digital image of an educational organization as a psychological and pedagogical problem is growing in the context of the digital transformation of education in Russia. In its understanding, the image plays a very important role in attracting the attention of an audience focused on the consumption of services to a particular object. Education is also one of the most important human activities in which educational services are consumed at various levels. The attractiveness and need for a particular educational service depends directly on the positive image of an educational organization, including in the digital environment. In modern science and in practical image-making, there are a lot of works related to the issue of image, which allows us to explore the phenomenon of a digital image from the standpoint of its content and structure (species, functional, component, level characteristics. Also, as part of the study of the phenomenon of the digital image, the following definition of the content of the image should be singled out, which means that the image is holistic and consistent, the conditions for implementation are also taken into account here, and those individual features that are present do not contradict each other. The systemic nature of the image allows one visible feature to evoke accompanying characteristics in the mass consciousness. image is the positioning of an organization or a person, created using certain digital technologies, implemented on various media online or offline. At the same time, far from any image, text, etc. is a digital image, it is a whole set of techniques that are aimed at fulfilling a specific goal — to broadcast to others in digital form a certain message, a message. Understanding the effectiveness factors of the influence of the digital image on the behavior and consciousness of the target audience expands the understanding of the managerial resources of this phenomenon. The results of the study can be useful for drawing attention to the problem of using a digital image to manipulate the behavior and consciousness of the target audience, which will allow its members to become less controllable and programmable and help resist mass manipulations carried out by the basic subjects of image communication in the era of new media.
Identifying Tweets with Personal Medication Intake Mentions using Attentive Character and Localized Context Representations

Individuals with health anomalies often share their experiences on social media sites, such as Twitter, which yields an abundance of data on a global scale. Nowadays, social media data constitutes a leading source to build drug monitoring and surveillance systems. However, a proper assessment of such data requires discarding mentions which do not express drug-related personal health experiences. We automate this process by introducing a novel deep learning model. The model includes character-level and word-level embeddings, embedding-level attention, convolu- tional neural networks (CNN), bidirectional gated recurrent units (BiGRU), and context-aware attentions. An embedding for a word is produced by integrating both word-level and character-level embeddings using an embedding-level attention mechanism, which selects the salient features from both embeddings without expanding dimensionality. The resultant embedding is further analyzed by three CNN layers independently, where each extracts unique n-grams. BiGRUs followed by attention layers further process the outputs from each CNN layer. Besides, the resultant embedding is also encoded by a BiGRU with attention. Our model is developed to cope with the intricate attributes inherent to tweets such as vernacular texts, descriptive medical phrases, frequently misspelt words, abbreviations, short messages, and others. All these four outputs are summed and sent to a softmax classifier. We built a dataset by incorporating tweets from two benchmark datasets designed for the same objective to evaluate the performance. Our model performs substantially better than existing models, including several customized Bidirectional Encoder Representations from Transformers (BERT) models with an F1-score of 0.772.
The Lousing Method to Increase Students Learning Motivation in Learning English

This study aims to know the effectiveness of the lousing method in increasing the motivation to learn English in the seventh-grade students of MTs Nurul Jadid. This study used a pre-experimental design using one group pre-test and post-test. Based on the results of the pre-test with a value of 32.77 and a post-test value of 67, it was proven that the post-test value is greater than the pre-test value. Meaning, there is an increase in student learning motivation. While, the results of the t-test (40.575) &gt; t-table (2.060) indicates that H0 is rejected and H1 is accepted. Meaning, the lousing method is very effective in increasing students' motivation to learn English. This is also evidenced by the results of observations which show that students always enjoy, are active, have energy, feel happy, interactive in class and focus on the material. Therefore, the use of the lousing method really effective to be enthusiastic in learning English in a good and fun.
A study on the gap between the new novel theory in China and the creative reality, and the discourse beyond it. : Focused on the verification of 「The development in Japanese novels last 30years」 by Zhouzuoren

This study examines the discourses of various scholars in the discourse of Chinese new novels, looks at the trend of the formation of the realm of Chinese modern literary theory, and tries to establish a literary aesthetic system for Chinese new novels. Therefore, as the first step in the step-by-step study, Zhouzuoren(周作人) tried to open a chapter in the field of modern literary theory in China by disproving the point claimed in 「The development in Japanese novels last 30years(日本近三十年小說之發達)」. In other words, retrospectively from 1918, when Zhouzuoren(周作人) spoke, the flow of 20 years of development of Chinese novel novels was considered. To this end, the materials of Chinese novel theory were selected and the discourses of various scholars were analyzed, and the verification of the points of his remarks was taken as the beginning of the study. The detailed research contents are as follows. To this end, first, as a preliminary review to verify Zhouzuoren (周作人)'s point, the literary and artistic aspects of Meiji(明治) 17-18 were considered, and the gap between the current status of Chinese new novels and the discourse achievements of 20 years was verified.. Specifically, in Verification 1), looking back on the achievements of the search for the transformation of Chinese novels over the past 20 years since the late 1890s, it was discussed whether the Chinese novel industry was stagnant in the Meiji(明治) 17-18 years at this time. In Verification 2), in relation to Zhouzuoren(周作人)’s argument that the current must-read for the development of new Chinese novels and the Japanese 『Shosetsu Shinzui(小說神髓)』 should be embarked on, among the achievements of the discourse of Chinese new novels, the novel is a field of art. The verification work was carried out based on the discourse of Chinese scholars who share the perception and context of Tsubouchi Shoyo(坪内逍遥), who has established itself as a And through these works and discussions, the discourse on the new Chinese novels has been deduced to disprove the claim of the Zhouzuoren(周作人).
Long-Term Assessment of the Spatial Temporal Trends in Selected Cloud Physical Properties over the Three Distinct Sites in Kenya

The presence of clouds in the Earth's atmosphere plays a pivotal role in regulating the Earth's energy budget.Increased anthropogenic activities and emissions can significantly lead to changes in cloud composition and cloud structure affecting the clouds physical characteristics, hence causing alterations in the climatic conditions over Kenya.Given this, the present study examined the spatial temporal physical properties of clouds over three study sites, by paying a special consideration on cloud parameters, such as: Cloud Effective Radius (CER), Cloud Top Pressure (CTP), Cloud Top Temperature (CTT) and the Cloud Fraction (CF).These cloud parameters were retrieved from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor and the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) model between January 2005 and December 2020.The data retrieved on clouds physical properties was utilized to estimate the trends and spatial variations and assess their statistical significance on climate over the study domain.The Spatial patterns of seasonal mean of cloud parameters from the sensors and the model were generally characterized with positive and negative trends over Kenya observed during the four seasons.Trends in CER were found as follows: Nairobi (0.04, 0, -0.04 and -0.01) for the four seasons respectively, Malindi (0.04, 0.01, 0.04 and 0.01) and lastly Mbita (-0.06, -0.06, 0.04 and -0.05); for CTT, Nairobi, -0.1, -0.2, -0.1 and -0.2, Malindi, 0.1, -0.2, 0.1 and 0.05 and Mbita, 0.2, 0.2, -0.2 and 0.15 respectively for every season.Trends in CTP were observed to vary seasonally as follows: Nairobi -0.5, -1, 0.5 and -0.5, Malindi -0.5, -3, 1, and 0.5 and lastly Mbita 0.5, 0, -1 and -1 respectively.And finally, the spatial trends in CF observed over the four seasons over the study domains were obtained a follows: Nairobi (0.3, 0, -0.002 and 0), Malindi (0.3, 0.002, 0 and 0.001) and lastly for Mbita (0.3,
A Trans-East Asian Study on Li He's Poems: Through Comparison with Isekai Light Novels

This paper analyzes Li He's fantastic, convoluted, and absurd poems through an unprecedented method, namely comparing them with Japanese light novels which are popular in East Asia. It organizes the conventional contents and cliché of isekai light novels and uses them as clues for a deeper understanding of Li He's poems. The protagonists of isekai light novels usually move to isekai via death or teleportation. Then they quickly achieve great success and earn others' respect and recognition. They also take many females as spouses to form a harem and overcome difficulties with them. Similar contents can be found in Li He's poems. He also dreams of living in isekai and sometimes shows a compulsion to die in order to go there. Li He's inferiority complex about his looks due to Marfan's syndrome and his low salary due to low position make him long for love from women. Therefore, he presents various female images in his poems to experience womanizing in his imagination. Moreover, he hopes someone recognize his abilities and employ him, so he entrusts this feeling to the lonely female images. As such, the dissatisfaction with reality, a longing for a second chance through death, a craving for others' recognition, vicarious satisfaction and sexual gratification through presenting female and harem images, and using female images to represent the author himself are all common in both isekai light novels and Li He's poems, and they are the key similarities that shed light on the understanding of Li He's poems.
Covid Pandemic: Web Based Information Services in College Library

The purpose of the study was to examine the various innovative web based information services, also known as online information services rendered by Vivekananda College library in support of online teaching-learning during Covid lockdown period. The spread of Covid pandemic has led to change in the nature of teaching and learning and libraries also needed to change services provision to their academic community. The college library being a part of academic institution needs to cater its community in online teaching and learning during covid lockdown. The Vivekananda College Library also did provide web based information services. Various web 2.0 tools were used by the library and access to digital was facilitated in different formats. This paper also studies the satisfaction of its patrons. The case study revealed that 91% of the surveyed faculty was satisfied with the services.
Characterizing Elite Scholars of Library and Information Science: A Bibliometric Analysis

Publication metrics have become crucial to measure the productivity and impact of individuals and organizations for highlighting their influence upon the knowledge world. This study aims to present a bibliometric analysis of the top two percent highly cited Library and Information Science (LIS) researchers in the Stanford University list of the top two percent researchers of various disciplines published in 2021. We have used the bibliometric method to analyze 254 highly cited LIS researchers. The findings show male dominance and female underrepresentation in LIS research. Leydesdorff, Loet is the most highly cited researcher of the LIS field. The Amsterdam School of Communications Research, Netherlands, is the most highly cited organization of LIS based on the highly cited researchers affiliated with it. The majority of LIS researchers belong to USA and UK. There is a meager contribution of Asian, Australian, and African countries producing highly cited LIS researchers. Highly cited LIS researchers are more familiar with publishing research in information retrieval, information seeking, and bibliometrics. Positions of researchers at different ranks by different measures depict their productivity, impact, h- index, and a composite score. A strong correlation exists between total publications and total citations. The study, in its nature, is unique and will provide an insight for young and emerging researchers for selection of research direction, persons for research collaboration, and a motivation to invest more efforts for impactful research.
Heterogeneity of Attitudes toward Robots in Healthcare among the Chinese Public: A Latent Profile Analysis

Attitudes are deemed critical psychological variables that can determine end users' acceptance and adoption of robots. This study explored the heterogeneity of the Chinese public's attitudes toward robots in healthcare and examined demographic characteristics associated with the derived profile membership. The data were collected from a sample of 428 Chinese who participated in an online survey. Latent profile analysis identified three distinct subgroups regarding attitudes toward robots-optimistic (36.9%), neutral (47.2%), and ambivalent (15.9%). Interestingly, although participants in the ambivalent attitude profile held more negative attitudes toward interaction with or social influence of healthcare robots, their attitudes tended to be positive when it came to emotional interactions with healthcare robots. All the respondents reported negative attitudes toward the social influence of healthcare robots. Multivariable regression analysis results showed that there were significant differences in age, education level, monthly income, experience with computers, experience with wearable devices, and whether to follow robot-related news or not. This study confirmed the heterogeneity of the Chinese public's attitudes toward robots in healthcare and highlighted the importance of emotional interaction with and social influence of healthcare robots, which might facilitate a better understanding of the needs and expectations of potential end users for robots in healthcare to make them more acceptable in different situations.
Footwear Sketches Colorization Method based on Generative Adversarial Network

The coloring of sketches has a constant market demand in the area of research.The difficulty of the coloring sketch outline is its lack of texture and color.Take footwear design as an example, it is difficult for designers to complete a colorful sketch in a limited time, so an artificial intelligence technology for coloring shoes is required.Though we do not build a new GAN, which is based on pix2pix.We try to integrate the existing model in four ways, including generator, discriminator, loss function and comparison.In this paper, given a set of edges-to-shoes that have 50,025 shoe images, our approach produces an image with vivid shoes images.Unlike the recent research, our approach is not based on a unique adversarial training.We show that shoe sketches can be synthesized from simple lines by a GAN into a high-resolution picture.In particular, we offer a new model to synthesize highresolution photo-realistic images of shoes, and apply a multidiscriminator to train and distinguish the generated images.Our model enables the shoe designer to benefit from the colorization design.