Reviewerly/exHarmony huggingface dataset:
Deep Patch-Based Human Segmentation

3D human segmentation has seen noticeable progress in recent years. It, however, still remains a challenge to date. In this paper, we introduce a deep patch-based method for 3D human segmentation. We first extract a local surface patch for each vertex and then parameterize it into a 2D grid (or image). We then embed identified shape descriptors into the 2D grids which are further fed into the powerful 2D Convolutional Neural Network for regressing corresponding semantic labels (e.g., head, torso). Experiments demonstrate that our method is effective in human segmentation, and achieves state-of-the-art accuracy.
Robust Unsupervised Neural Machine Translation with Adversarial Denoising Training

Unsupervised neural machine translation (UNMT) has recently attracted great interest in the machine translation community. The main advantage of the UNMT lies in its easy collection of required large training text sentences while with only a slightly worse performance than supervised neural machine translation which requires expensive annotated translation pairs on some translation tasks. In most studies, the UMNT is trained with clean data without considering its robustness to the noisy data. However, in real-world scenarios, there usually exists noise in the collected input sentences which degrades the performance of the translation system since the UNMT is sensitive to the small perturbations of the input sentences. In this paper, we first time explicitly take the noisy data into consideration to improve the robustness of the UNMT based systems. First of all, we clearly defined two types of noises in training sentences, i.e., word noise and word order noise, and empirically investigate its effect in the UNMT, then we propose adversarial training methods with denoising process in the UNMT. Experimental results on several language pairs show that our proposed methods substantially improved the robustness of the conventional UNMT systems in noisy scenarios.
Navigation of autonomous systems based on situation control with dynamic replanning

The solution to the problem of autonomous mobile systems navigation is a complex task, traditionally presented in the form of solving the sequence of subtasks: perception of information about the environment, localization and mapping, path planning, and motion control. A large number of scientific works are devoted to the solution of the listed subtasks. However, existing research does not pay enough attention to the integration of individual elements of the navigation cycle solutions into a single homogeneous system. This leads to an additional accumulation of errors in the process of a complex solution to the navigation problem. In previous works, a model was proposed that provides homogeneous integration, using for this a multi-level structure of representing an autonomous system's knowledge in the form of sets of fuzzy rules and facts. The five-level model represents the autonomous system's knowledge of goals, paths, an environment map, strategies, and specific controls necessary to achieve the goal. To ensure adequate processing of fuzzy rules, a modified Takagi-Sugeno-Kang fuzzy inference model is proposed. In this work, the previously proposed model is expanded. The model was tested in conditions of noisy sensor data. A method is proposed for the formation of level 2 rules, which describe an autonomous system's cartographic knowledge about the environment, using the well-known methods of global path planning. Extension of the model provides dynamic paths replanning of the autonomous system, using the processing of present knowledge about existing paths. Such replanning is effective in terms of computational time and independent of the completeness of the knowledge base of complete paths.
A Digital Storytelling Model for Increasing Information Security Awareness among Kenyan Smartphone Users

The proliferation of smartphones in Kenya has resulted to smartphone users’ overdependence on their phones for everyday activities. This increased interaction with smartphones poses a threat to users’ privacy and security. The exposure to threats establishes a need to understand users’ security awareness and behavior when using their mobile phones. To investigate user behaviour while using their mobile phones and their understanding of cyber security risks, this study surveyed 393 Kenyan smartphone users on security features that they implement as well as their understanding of potential security threats. The results show that most Kenyan Smartphone users are aware of security threats facing them and are greatly concerned about related security risks. However, users still make poor behavioral choices related to the use of smartphones, making them vulnerable to cyber security attacks. This paper proposes a Digital Storytelling (DST) model that forms a basis of creating a digital storytelling media that can be used to increase cyber security awareness among Kenyan smartphone users.
Enabling identity-aware tracking by vision-RFID fusion

Person identification and tracking (PIT) is an essential research topic in computer vision (CV). A CV-based system typically needs to identify, locate, and track persons appearing in its sight. In this work, we propose RFTrack, an RFID and CV fushion system that enables cameras in public areas (like surveillance cameras) to 'recognize' the physical-identity(ID) of persons in the fields of view and track the persons with specific IDs with no training efforts. By asking the users to perform a simple authentication, the system will be aware of the targets' IDs in its sensing range. Later through comparing the motion trajectories derived from both camera videos and RF signal, we can associate RFID-tagged human objects in videos with their physical IDs. A preliminary study conducted shows that RFTrack can actively identify and track the RFID-tagged target objects using commercial RFID devices and cameras, in complex indoor environments where various multipath reflectors exist.
MULTIMEDIA PACKAGE FOR TEACHING COMPUTER SCIENCE AMONG RURAL AND URBAN STUDENTS AT PLUS ONE: VALIDATION AND ITS EFFECIVENESS

The prime intention of the study is to prepare a multimedia package for developing programming skill of computer science students among rural and urban at plus one standard. And also find out the effectiveness of multimedia package for teaching in computer science. 60 students from Sri Swamy and JAY Matriculation School in Salem district are selected as a sample of this research, in that thirty students were considered as control group students and trained with traditional method of teaching. Rest of the thirty students were considered as experimental group students and trained with multimedia package. Achievement test was used as tool for the study. The results of the study represent that the students learned Computer programming through multimedia package is more effective than students learned through traditional method. The experimental results show that multimedia package was found effective with respect to academic achievement in rural and urban students also.
School Financial Management in Smpit Al-Azhar Banda Aceh

Financial management contributes to determining the realization of educational activities in schools. The financial management is conducted through the process of planning, organizing, leading, coordinating, and controlling. In this research, the researcher used a qualitative approach. The research subject is the school principal, the vice-principal, the treasurer, and the teachers. The techniques of data collection used are observation, interview, and documentation. The results of the study are; (1) The drafting process of the school budget revenue and expenditures (RAPBS) is made by collecting the data from teachers and staff. All the data obtained are the analysis results based on priority scale consideration guided by the previous year’s program. (2) The realization of school budgets originating from the central government is guided by technical guidelines set by the Minister of Education and Culture. However, the funds use sourced from the community is guided by the agreement between the committee and the foundation. (3) The accountability of the RAPBS in SMPIT Al-Azhar Banda Aceh is conducted every three months for budgets originating from the central government, which are then conveyed to the Education and Culture Department of Banda Aceh, while the accountability of budgets from the community and foundations is carried out once a year.&#x0D; Keywords: Management, Financial, and School.
A Neural Network for Distributed Optimization over Multiagent Networks

This paper is concerned with a distributed optimization problem with inequality constraint over a multiagent network. The objective function is the sum of multiple local convex functions, which can be nonsmooth. Based on graph theory and nonsmooth analysis, we propose a neural network with a time-varying auxiliary function. The boundedness of the state solution is demonstrated by using the properties of the auxiliary function. Moreover, it is proved that the designed neural network with any initial conditions reaches a consensus and converges to the global optimal solution. Finally, a numerical simulation is discussed to verify the theoretical results.
Memory of homogeneous sequential visual impressions

Every one of us experienced the following everyday phenomenon. A person hears, lets say, the striking of the clock, but does not pay attention to it and does not count the number of strikes; each sound is perceived (consciously or unconsciously it's all the same) and is immediately forgotten, yielding instead to the next.
Depth-Aware Action Recognition: Pose-Motion Encoding through Temporal Heatmaps

Most state-of-the-art methods for action recognition rely only on 2D spatial features encoding appearance, motion or pose. However, 2D data lacks the depth information, which is crucial for recognizing fine-grained actions. In this paper, we propose a depth-aware volumetric descriptor that encodes pose and motion information in a unified representation for action classification in-the-wild. Our framework is robust to many challenges inherent to action recognition, e.g. variation in viewpoint, scene, clothing and body shape. The key component of our method is the Depth-Aware Pose Motion representation (DA-PoTion), a new video descriptor that encodes the 3D movement of semantic keypoints of the human body. Given a video, we produce human joint heatmaps for each frame using a state-of-the-art 3D human pose regressor and we give each of them a unique color code according to the relative time in the clip. Then, we aggregate such 3D time-encoded heatmaps for all human joints to obtain a fixed-size descriptor (DA-PoTion), which is suitable for classifying actions using a shallow 3D convolutional neural network (CNN). The DA-PoTion alone defines a new state-of-the-art on the Penn Action Dataset. Moreover, we leverage the intrinsic complementarity of our pose motion descriptor with appearance based approaches by combining it with Inflated 3D ConvNet (I3D) to define a new state-of-the-art on the JHMDB Dataset.
Software Engineering of Cyber-Physical Spaces for Sustainable Tourism

Summary form only given, as follows. The complete presentation was not made available for publication as part of the conference proceedings. The term Cyber-Physical Space is used to identify physical spaces that are enriched by digital software and hardware components, such as RFID, IoT devices, NFC, and more. The applications we engineer are becoming more and more cyber-physical spaces related: think to indoor localization and positioning, to crowd management applications, to context-aware applications reacting to people in proximity. This talk will illustrate my team experience in the engineering of software for cyber-physical spaces applied to the tourism industry. I will use the UFFIZI Galleries crowd management project, as well as the Researcher Night application to illustrate the challenges and opportunities in the field. The CAPS modeling language for cyber-physical spaces engineering will be illustrated as well.
RUMAH SAINS BERBASIS SEPARATED WASTE TECHNOLOGY SEBAGAI MEDIA LITERASI EDUKASI PENGKATEGORIAN SAMPAH

Waste is substance or material which inorganic or organic and most of them are produced by human activities. The big population and the human complexity become the biggest supply in the improvement of waste volume. Responding waste problems which have not resolved completely, so it needs innovation to minimize waste. The innovation refers to UU No 18, 2008 about waste management part IV about Right and Duty clause 12 verse one, “Everyone in household waste management and a kind of household waste have to reduce and solve waste in environmental ways”. The education procces of choosing waste category is based on unravel ability. Waste categories could be known by many kind of indicator. One of them through the sensor. This matter becomes the development of education media which make the society at TPST Piyungan easy to understand waste category. This innovation is in the form of science house based on separated waste technology as the literacy education media of waste categorizing (case study TPST Piyungan, Yogyakarta). The method used is description with analysis literature review. The equipments of making prototype are temperature sensor LM35, light sensor LDR, arduino idea, computer. The procedures are literature review, the preparation of arranging and making the prototype, activities schedule, socialization, implementation, evaluation, regeneration of the program. Science house based on separated waste technology is effective on preparing generation to develop the technology and engage the investor and the contributor, hopefully in the future could be the pioneer of zero waste by developing the other media.
THE ROLE AND PLACE OF MATHEMATICAL OLYMPIADS IN THE SYSTEM OF TRAINING STUDENTS OF HIGHER EDUCATIONAL INSTITUTIONS

The article discusses the key stages of preparing students for math contests. The idea that the mathematical Olympiad is an important part of the educational process at a university is grounded. The practical experience of the leading teachers of the Department of Higher Mathematics on the preparation of students – winners of the Olympiads of the all-Russia and international level is summarised. As a result of a comprehensive analysis, the main stages of preparing students for Olympiads, which are aimed at developing skills for solving non-standard problems, are highlighted and characterised. The ability to apply innovative approaches helps future engineers and economists solve technical and economic problems in the future. The huge role of mathematical Olympiads in the development of creative and professional competencies among students, in deepening their knowledge in the field of mathematics and the ability to work individually and as a team is noted. The authors of the article, following the formation of a student participating in the Olympiads as a specialist, came to the conclusion that these students more successfully master their competences, participate more actively in scientific and design work, enter graduate and postgraduate studies, and subsequently build a successful professional career.
Dependency Head Annotation for Myanmar Dependency Treebank

Complete manual annotation of dependency treebank needs resources like annotators and annotation tools and takes long time and has high possibility of inconsistent annotationsfor free word order languages such as Myanmar.This paper describes a dependency head annotation scheme with Universal part-of-speech and Universal Dependencies for Myanmar dependency treebank.Currently 22,810 sentences and 680,218 tokens were annotated from three corpora for Myanmar dependency treebank.Some language specific issues are also described with examples.Raw syntactic structures were annotated automatically by UDPipe according to the Universal Dependencies based on Universalpart-of-speech tag scheme.Then unsupervised annotated dependency head structures have been manually updated in post processing.To be reliable and speedy post process with reduced errors for manual updating, selected sentences were added to the training data after being updated.After that the model has been retrained and the remaining sentences were parsed by UDPipe.Post processing was repeated until all sentences were updated.Some specifications of dependency annotation schemes in sentences encountered in post processing are presented with examples.For parsing performance of annotated data, cross validation tests and parsing experiments were performed.Moreover, annotated treebank data have also been evaluated by CoNLL 2017 evaluation script for parsing performance.Results of parsing experiments and evaluation are also reported by unlabeled and labeled attachment scores and demonstrated that the proposed method is a suitable way for building Myanmar dependency trees.Moreover, syntax structures of treebank are also analyzed and syntax information is also presented.This dependency head annotation for dependency treebank is the first work for Myanmar language as far as we know.
Analisa Certainty Factor Dalam Mendiagnosa Kerusakan Alat Pemancar Radio 87.6 Dass FM Lubuk Pakam

An FM transmitter or FM transmitter is a source of radio vibrations emitted by a device called an oscillator or oscillator. While the oscillator is a device that can produce high frequencies. The scope of this research is an expert system that is built only to discuss the symptoms and damage to radio transmitters and solutions to fix them. The resulting output is radio transmitter malfunction information and solutions to repair it. The programming language used in solving this problem is PHP by using the mysql database. The method used in solving the damage to the radio transmitter is the certainty factor method.
Text Rank for Domain Specific Using Field Association Words

Text Rank is a popular tool for obtaining words or phrases that are important for many Natural Language Processing (NLP) tasks.This paper presents a practical approach for Text Rank domain specific using Field Association (FA) words.We present the keyphrase separation technique not for a single document, although for a particular domain.The former builds a specific domain field.The second collects a list of ideal FA terms and compounds FA terms from the specific domain that are considered to be contender keyword phrases.Therefore, we combine two-word node weights and field tree relationships into a new approach to generate keyphrases from a particular domain.Studies using the changed approach to extract key phrases demonstrate that the latest techniques including FA terms are stronger than the others that use normal words and its precise words reach 90%.
A Deep Residual Network for Geometric Decontouring

Abstract Grayscale images are intensively used to construct or represent geometric details infield of computer graphics. In practice, displacement mapping technique often allows an 8‐bit grayscale image input to manipulate the position of vertices. Human eyes are insensitive to the change of intensity between consecutive gray levels, so a grayscale image only provides 256 levels of luminances. However, when the luminances are converted into geometric elements, certain artifacts such as false contours become obvious. In this paper, we formulate the geometric decontouring as a constrained optimization problem from a geometric perspective. Instead of directly solving this optimization problem, we propose a data‐driven method to learn a residual mapping function. We design a Geometric DeContouring Network (GDCNet) to eliminate the false contours effectively. To this end, we adopt a ResNet‐based network structure and a normal‐based loss function. Extensive experimental results demonstrate that accurate reconstructions can be achieved effectively. Our method can be used as a relief compressed representation and enhance the traditional displacement mapping technique to augment 3D models with high‐quality geometric details using grayscale images efficiently.
Adapted NRC Based Sentiment Analysis in Event Distraction

The paper was trying to extract entities from related tweets collected from twitter. This project first collected real-time tweets from twitter searching API with related topic-based hashtags during the death of American black man George Floyd. We then used two approaches to identify the polarities or emotions of each tweets and generated over-time sentiment flow chart in detecting entities. We found that some extreme sentiment score was correlated with some key entities over time. And our adapted NRC-lexicon based approach obtained better results. This paper revealed that public’s sentiment displayed on tweets was generally consistent with the correlated events previously. It might help researchers in predicting or preventing public events in the future.
W. H. 오든의 문화적 영향 ―대중 매체를 중심으로

The purpose of this paper is to collect and analyze the cultural contents which include the poems of W. H. Auden(1907-73). In the 21st century the cultural contents such as films and popular music are more appealing to the public than literary texts. This trend is not desirable because literature has owned such values as nurturing empathy, imagination and creativity. If literary texts are included in the cultural contents, they can reach the wider public. This paper argues that the poetic work of Auden has been included in many sectors of cultural contents; as a result his poems could trespass the borders of the academic ivory tower.Four BBC documentaries: “The Auden Landscape” (1982), “The Addictions of Sin: W. H. Auden in His Own Words” (2007), “Tell me the Truth about Love” (2012) and “Stop All the Clocks” (2017) dealt with the life and poems of Auden. Meanwhile a famous film, “Four Weddings and a Funeral” (1994) ignited the popularity of Auden''s poems. Several poems including “Stop all the Clocks,” “Lullaby,” “Lady Weeping at the Crossroads” are set to music from classical to popular songs. Lastly lines from his poem “In Memory of W. B. Yeats” and “September 1, 1939” have been included in the addresses of Madonna and presidential candidates of America.The notable fact in the cultural contents including Auden''s poems is that the most prevalent theme is love. Auden has started his literary career as the leader of Auden Generation in the 1930s and finished it as a great poet whose poems become a memorable speech.
Efforts to Improve Learning Outcomes of Class V Students Using Interactive Powerpoint Media

&lt;em&gt;The background of this study is the low learning outcomes of students as evidenced by the low score of evaluation test results. The goal to be achieved is the use of interactive powerpoint media to improve student learning outcomes. The effort made by the writer is improving learning by using interactive powerpoint learning media. This research method uses classroom action research which takes place in three cycles, each cycle consisting of 1) planning; 2) action, 3) observation and 4) reflection. The subjects of this study were 24 students of grade V SD Negeri Cawitali 03. Efforts to improve learning have been successful and end in the third cycle. This can be seen in Cycle I, students who complete learning are 16 students from 24 students = 67%, Cycle II students who complete learning are 19 students out of 24 students = 79.2% and Cycle III students who complete learning are 23 students out of 24. Students = 95.8%. Based on the results obtained, it can be concluded that the learning outcomes of the circulatory system material in grade V SD Negeri Cawitali 03 can be increased by using interactive powerpoint media&lt;/em&gt;