Reviewerly/exHarmony huggingface dataset:
Dual Grid Net: hand mesh vertex regression from single depth maps

We present a method for recovering the dense 3D surface of the hand by regressing the vertex coordinates of a mesh model from a single depth map. To this end, we use a two-stage 2D fully convolutional network architecture. In the first stage, the network estimates a dense correspondence field for every pixel on the depth map or image grid to the mesh grid. In the second stage, we design a differentiable operator to map features learned from the previous stage and regress a 3D coordinate map on the mesh grid. Finally, we sample from the mesh grid to recover the mesh vertices, and fit it an articulated template mesh in closed form. During inference, the network can predict all the mesh vertices, transformation matrices for every joint and the joint coordinates in a single forward pass. When given supervision on the sparse key-point coordinates, our method achieves state-of-the-art accuracy on NYU dataset for key point localization while recovering mesh vertices and a dense correspondence map. Our framework can also be learned through self-supervision by minimizing a set of data fitting and kinematic prior terms. With multi-camera rig during training to resolve self-occlusion, it can perform competitively with strongly supervised methods Without any human annotation.
Cosmic@Web - Astroparticle learning platform for students

Encouraging young people to actively participate in science is a longstanding and important priority at DESY.To provide high-school students with an opportunity to learn more about astroparticle physics, a number of simple experiments were developed at the DESY Zeuthen campus.Data from these experiments are published on the Cosmic@Web learning platform, along with a range of online analysis tools and introductory material.In addition to local experiments, data are provided from a global network of continuously-operating cosmic particle experiments.Diverse sites participate in this network, including the pole-to-pole research vessel Polarstern, the Antarctic Neumayer III station, as well as the high altitude research stations in Aragats, Armenia and Moussala, Bulgaria.Using Cosmic@Web, students without direct access to an experiment can analyse data in a classroom or at home.The learning platform can also be used to participate in the annual International Cosmic Day.With Cosmic@Web, students can work like real scientists and do their own astroparticle physics research.These developments form part of the German outreach network Netzwerk Teilchenwelt.
Analysis of Institutional Context in Curriculum Change: Focused on Innovative Schools in korea

본 연구는 신제도주의 관점에 따라 혁신학교 교육과정 변화의 제도적 맥락을 구조-제도-행위자의 통합적 모형으로 분석한 것이다. 혁신학교 관련 행위자들은 구조 및 제도 수준에서 혁신학교 정책, 교장공모제, 전원학교 정책, 학업성취도 평가와 2009개정교육과정, 2015개정교육과정 등의 정책을 활용하여 교육과정을 변화시켰다. 이 중 혁신학교 정책은 역사적 제도 맥락 관점에서 게임의 규칙 자체를 바꾸는 ‘제도 변화’이며 제도가 행위자들에게 새로운 실천의 기회를 줄 수 있다는 것을 보여주었다. 또 행위자들은 아이디어와 담론을 활용하고 교육과정의 각종 지침이나 규정 등을 적극적으로‘해석’하여 학교교육과정 변화의 기회 요인으로 활용하고 제약 요인은 최소화하는 전략으로 대응하였다. 교육과정 제도의 지속성과 변화라는 관점에서 보면 제도적 맥락과 상호보완성에 의해 기존 제도를 유지하려는 경로의존성과 구조 요인(정권 교체 및 지방분권 체제 강화), 행위자 역할 확대 등 구조, 제도, 행위자 요인 등에 의한 제도 변화 요인이 있다.The purpose of this study is to analyze the institutional context of changes in the curriculum of innovative schools through the integrative model of structure-institution-agent according to the viewpoint of new institutionalism. Innovative school-relevant agents have changed the educational curriculum at the structural and institutional levels utilizing polices like the innovation school policy, the principal recruitment system, and the rural school policy, the academic performance evaluation and the 2009 revised curriculum and 2015 revised curriculum, and others. Among them, the innovative school police us a ‘institutional change’ changing the rule of game itself from the viewpoint of historical, institutional contexts, and showed that this institution could give the opportunity of practice to agent. And agents utilized ideas and discourses, and actively ‘interpreted’ various guidelines or regulations of curriculum to make use of them as an opportunity factor for changing the educational curriculum and responded with strategies minimizing the restrict factors. From the perspective of continuity and change in the educational curriculum system, there are the change factors in institutions due to the structural, institutional and the agent factor such as the path dependency to keep the existing system in the institutional context and complementarity, the structural factor, and the expansion of agent’s role.
Forward-Backward Decoding for Regularizing End-to-End TTS

Neural end-to-end TTS can generate very high-quality synthesized speech, and even close to human recording within similar domain text. However, it performs unsatisfactory when scaling it to challenging test sets. One concern is that the encoder-decoder with attention-based network adopts autoregressive generative sequence model with the limitation of "exposure bias" To address this issue, we propose two novel methods, which learn to predict future by improving agreement between forward and backward decoding sequence. The first one is achieved by introducing divergence regularization terms into model training objective to reduce the mismatch between two directional models, namely L2R and R2L (which generates targets from left-to-right and right-to-left, respectively). While the second one operates on decoder-level and exploits the future information during decoding. In addition, we employ a joint training strategy to allow forward and backward decoding to improve each other in an interactive process. Experimental results show our proposed methods especially the second one (bidirectional decoder regularization), leads a significantly improvement on both robustness and overall naturalness, as outperforming baseline (the revised version of Tacotron2) with a MOS gap of 0.14 in a challenging test, and achieving close to human quality (4.42 vs. 4.49 in MOS) on general test.
INVESTIGATING SECONDARY EDUCATION TEACHERS' TRAINING NEEDS

Appears in: EDULEARN19 Proceedings Publication year: 2019Pages: 2084-2091ISBN: 978-84-09-12031-4ISSN: 2340-1117doi: 10.21125/edulearn.2019.0563Conference name: 11th International Conference on Education and New Learning TechnologiesDates: 1-3 July, 2019Location: Palma, Spain
Visual Tracking Based on Multi-cue Proposals and Long Short-Term Features Learning

Tracking-by-detection frameworks have made significant progress in recent years. However, proposal and classification of this framework could still be severely affected by occlusion and motion. In this paper, we propose a tracking algorithm MPLST to improve the accuracy and robustness of proposal and classification under challenges. First, we provide a multi-cue proposal method, which combines Gaussian sampling utilizing previous target state, and motion and appearance selective search making use of the motion and appearance features of the target respectively. Second, we provide a long short-term features learning approach for target classification and network updating. The long-term features are robust to occlusion, and the short-term features can keep up with the fast motion of the target. Experiments on the OTB100 [1] and VOT2015 [2] datasets demonstrate that our MPLST can effectively deal with occlusion and motion, and achieve competitive performance against state-of-the-art trackers.
Switchable Normalization for Learning-to-Normalize Deep Representation

We address a learning-to-normalize problem by proposing Switchable Normalization (SN), which learns to select different normalizers for different normalization layers of a deep neural network. SN employs three distinct scopes to compute statistics (means and variances) including a channel, a layer, and a minibatch. SN switches between them by learning their importance weights in an end-to-end manner. It has several good properties. First, it adapts to various network architectures and tasks. Second, it is robust to a wide range of batch sizes, maintaining high performance even when small minibatch is presented (e.g. 2 images/GPU). Third, SN does not have sensitive hyper-parameter, unlike group normalization that searches the number of groups as a hyper-parameter. Without bells and whistles, SN outperforms its counterparts on various challenging benchmarks, such as ImageNet, COCO, CityScapes, ADE20K, MegaFace, and Kinetics. Analyses of SN are also presented to answer the following three questions: (a) Is it useful to allow each normalization layer to select its own normalizer? (b) What impacts the choices of normalizers? (c) Do different tasks and datasets prefer different normalizers? We hope SN will help ease the usage and understand the normalization techniques in deep learning. The code of SN has been released at https://github.com/switchablenorms.
A Lightweight First-Level Muon Track Trigger for Future Hadron Collider Experiments

Single muon triggers are crucial for the physics programmes at hadron collider experiments. To keep the trigger rates reasonably low they must be highly selective. Muon systems at LHC experiments and at future colliders use two muon chamber system for triggering: fast trigger chambers to identify the bunch crossing and provide a coarse momentum estimation, and slower precision chambers, for precise measurements of the muon trajectory. A fast lightweight track finding algorithm, based on the Hough Transform and Linear Regression techniques, has been designed and implemented on a Zynq SoC device, reconstructing successfully muon tracks in a single trigger sector.
Communicative and Visual Processes as Indicators of Social Atomization of Society

Under the conditions of destruction of traditional social interaction system the visual cultural processes that manifest themselves within the urban social and environment acquire special importance. The contemporary urban environment that is developing through the pattern of transition from industrial to the postindustrial model with noticeable consequences from the point of socio-cultural paradigms, develops a new communicational environment that relies upon both technologies as well as social pillars.
Solving Two Conjectures regarding Codes for Location in Circulant Graphs

Identifying and locating-dominating codes have been widely studied incirculant graphs of type $C_n(1,2, \ldots, r)$, which can also be viewed aspower graphs of cycles. Recently, Ghebleh and Niepel (2013) consideredidentification and location-domination in the circulant graphs $C_n(1,3)$. Theyshowed that the smallest cardinality of a locating-dominating code in$C_n(1,3)$ is at least $\lceil n/3 \rceil$ and at most $\lceil n/3 \rceil + 1$for all $n \geq 9$. Moreover, they proved that the lower bound is strict when$n \equiv 0, 1, 4 \pmod{6}$ and conjectured that the lower bound can beincreased by one for other $n$. In this paper, we prove their conjecture.Similarly, they showed that the smallest cardinality of an identifying code in$C_n(1,3)$ is at least $\lceil 4n/11 \rceil$ and at most $\lceil 4n/11 \rceil +1$ for all $n \geq 11$. Furthermore, they proved that the lower bound isattained for most of the lengths $n$ and conjectured that in the rest of thecases the lower bound can improved by one. This conjecture is also proved inthe paper. The proofs of the conjectures are based on a novel approach which,instead of making use of the local properties of the graphs as is usual toidentification and location-domination, also manages to take advantage of theglobal properties of the codes and the underlying graphs.
‘Impact taisetsu da!’

Since their first appearance in the 1990s, emoji and kaomoji have represented a tool to express and transmit messages in nonverbal ways. Their use has been increasing and developing over the past few years, especially thanks to the massive diffusion of new media and devices such as computers, smartphones, tablets, and freeware apps for instant communication (Line, WhatsApp, etc.). Emoji and kaomoji could be specifically interpreted as a new language, and especially in Japan, their use represents a current trend in social media and blogs. In this article, I investigate the use of emoji and kaomoji by professional dansō, 男装 (female-to-male crossdresser escorts), in their blogs and Twitter accounts. Crossdresser escort companies require every dansō to keep a weekly updated blog and a daily updated Twitter profile to communicate and share their life experiences and thoughts with (potential) customers and fans. I explain in which ways, and for what reasons, dansō use emoji and kaomoji in virtual interactions, relying on the outcomes of interviews conducted from September 2015 to July 2016 with 14 professional crossdresser escorts and through the examination of blog posts, tweets, and direct messages on LINE. Specifically, drawing upon Butler’s theory of gender performativity (1990), I argue that dansō perform1 their gender identity using (or avoiding the use of) emoji and kaomoji. I also compare their use of emoji and kaomoji on public profiles and in private conversations, to highlight the different gender negotiation required when interacting with customers or coworkers. Moreover, I highlight how emoji and kaomoji are used as tools to manage intimacy in relationships between crossdresser escorts and their customers.
Dissipative Quantum Metrology

Conventional strategies of quantum metrology are built upon POVMs, thereby possessing several general features, including the demolition of the state to be measured, the need of performing a number of measurements, and the degradation of performance under decoherence and dissipation. Here, we propose an innovative measurement scheme, called dissipative adiabatic measurements (DAMs), based on which, we further develop an approach to estimation of parameters characterizing dissipative processes. Unlike a POVM, whose outcome is one of the eigenvalues of an observable, a DAM yields the expectation value of the observable as its outcome, without collapsing the state to be measured. By virtue of the very nature of DAMs, our approach is capable of solving the estimation problem in a state-protective fashion with only $M$ measurements, where $M$ is the number of parameters to be estimated. More importantly, contrary to the common wisdom, it embraces decoherence and dissipation as beneficial effects and offers a Heisenberg-like scaling of precision, thus outperforming conventional strategies. Our DAM-based approach is direct, efficient, and expected to be immensely useful in the context of dissipative quantum information processing.
Kolaborasi dan Produktivitas Pengarang Artikel Jurnal Khizanah Al-Hikmah: Jurnal Ilmu Perpustakaan, Informasi, dan Kearsipan Tahun 2013 – 2020

The purpose of this research is to find out how the level of collaboration and productivity of the author in the Khizanah Al-Hikmah Journal article: Journal of Library, Information and Archive Science 2013-2020 UIN Alauddin Makassar. The population and sample in this study were all articles published in the journal Khizanah Al-Hikmah Journal: Journal of Library, Information and Archive Science in the last eight years 2013-2020. The method used in this research is descriptive quantitative research with a quantitative approach. The results of this study indicate that the results show that the number of articles from 2013-2020 was 142 articles. The average collaboration level is 0.40. The number of authors was 245 people. The most productive authors are Taufik Mathar and Tupan with 7 articles. We found that the top 5 agencies contributing to articles were UIN Alauddin Makassar (25.31%), Padjajaran University (13.47%), PDII LIPI (11.84%), Sunan Kalijaga State Islamic University (6.53%), Brawijaya University (4.9%). Affiliates with public status are 95.51% and private 4.49%. It can be concluded that most of the articles were written collaboratively, namely 56 articles, most of the writers' affiliations came from institutions of higher education libraries (81.63%).
Optical Character Recognition For Invent And Outcome Management At The Batang Toru Camat Office, Tapanuli Selatan

The system for managing incoming and outgoing mail at the Batang TORU Camat Office, Selatan Tapanuli includes incoming letters, outgoing letters, archives, and so on. Archives are a source of information from various fields that will be stored in storage areas. The purpose of writing this final project report is to find out how to handle incoming and outgoing mail manually and computerized at the Batang Toru Camat Office, Selatan Tapanuli filling by using the application and knowing the handlers of hadrcopy documents into softcopy online using optical character recognition (OCR). This Final Project report writing method is carried out by means of literature studies, observations and interviews with resource persons at the Batang Toru Camat Office, Selatan Tapanuli. From the results of observations and interviews, it is known that the handling of incoming and outgoing letters is carried out using a manual and computerized system. Incoming mail flow system starts from the recipient then is followed up to each unit and then archived. Outgoing mail is processed from drafting letters to sending outgoing letters. Electronic filing management (e-filing) using the application. Application of hardcopy documents that will be converted into softcopy using Optical Character Recognition (OCR) software, without having to type as the original. The software can be done online for free without registering first.
Flexible information integration architecture based on cloud native technologies for large cruise ships

This keynote proposes the application of cloud native technologies to the information integration architecture of large cruise ships. Cloud native technologies enable organizations to build and run scalable applications in public, private and hybrid clouds. Features such as containers, service meshes and microservices illustrate this approach and enable the creation of loosely coupled systems that are resilient, manageable and observable. Service mesh from Istio provides a non-intrusive, cross-language service framework for use by cruise ships, and it realizes the communication between services through a sidecar model. It solves the problem of information integration between cruise ship business applications with different development languages, different technology stacks and different communication interfaces. The automated operation and maintenance platform uses Docker and Kubernetes technologies to reduce the need for maintenance. In addition, the keynote discusses how data integration and application integration development specifications enable baseline development of cruise applications.
Path planning for USV based on artificial potential field approach with learning automata

An improved artificial potential field method based on learning automata is proposed to address the problem, which method is easy to fall into local optimum while solving the path planning of unmanned vehicles. The artificial potential field method with the capability of path planning is improved by reasonably integrating reinforcement learning and artificial potential field without changing the potential field function construction. Within the virtual local stabilizing action range, by changing the angle of attraction at the target point, with the combination of optimization results of online adjustment of virtual local stabilizing action radius, angle of attraction change amount and gain parameters by learning automaton, the magnitude of repulsive force is changed to jump out of the local oscillation region, and complete the planning successfully for the case of falling into local minima. The simulation results show that the algorithm converges quickly and does not easily produce oscillation points.
Improved particle swarm optimization and DDQN algorithm for multi-UUV path planning

To solve the path planning problem of UUV, an improved particle swarm optimization algorithm and DDQN algorithm are respectively proposed to solve the global static path planning and local dynamic collision avoidance. Firstly, PSO algorithm is used to address the problems of insufficient real-time obstacle avoidance capability. The inertia weight and learning factor update methods are adjusted. Then the cooperative mechanism is introduced to the PSO and collision evaluation function is set to solve the UUV mutual collision avoidance problem. Secondly, Q algorithm and DDQN combined to realize the UUV’s prediction of environmental state changes. Finally, the performance of A star, PSO, QPSO and PSO-DDQN is compared and analyzed through simulation experiments. Results show that the proposed methods above solve the multi-UUV collision avoidance and path finding problems in complex environments. Meanwhile, the PSO-DDQN algorithm has been improved in processing time and path length compared with the traditional PSO and QPSO algorithms.
Prioritizing skill action recognition of basketball using decision support system

Abstract Human action understanding is vital in many computer vision applications, including sports narrative, virtual reality games, and human computer interaction (HCI) systems. To recognize human actions, a video stream or image sequence must contain many actions. For example, modern video surveillance systems need to recognize human action to improve financial institution security. Human action recognition can help with automatic sports narrative and video captioning. It's important for HCI, notably for virtual reality games, sports storytelling, and video captioning. However, complex backgrounds, action occlusion, and fluctuating lighting conditions make human action identification difficult nowadays. Basketball high-difficulty action recognition technology is used to identify and evaluate player movement. Video recognition is a vital tool for improving basketball instruction. Technology and injury limit traditional sports target recognition, preventing the desired effect. The current study has used decision support system for prioritizing the skill action recognition of basketball. The tool of super decision was used for the process of experimental work. Results of the experiments reveal that the proposed work is effective for prioritizing skill action recognition showed satisfactory results.
Research on the Application of Artificial Intelligence in the Film Industry

With the rapid development of technology today, artificial intelligence is inevitably involved in numerous fields including the film production industry, and helps the industry from all periods of the production cycle. This paper focuses on three areas: script writing, special effects production and video restoration, and highlights the application of technologies such as Benjamin, flux system and ESRGAN in these three areas. By analyzing the positive impacts and potential risks, this paper points out that AI technology and human artistic creation are indispensable for the healthy development of the film industry only when they complement to each other, hoping to offer some references for the future research of the the application of artificial intelligence in the film industry.
School educational software designed for children with special education needs

The research focuses on children with special educational needs, who are unable to access an education either because they do not have a school near their homes or because they are misinformed by parents that they can access an education regardless of their disability. By not receiving an education, children are deprived of their right to education. Therefore, a prototype of an educational software was designed taking advantage of the technological tools for learning of children with special educational needs. A hybrid methodology and the Balsamiq tool were used, as they were the appropriate ones to develop the project. The result is that children with disabilities can learn by interacting with technology and in the same way their parents can visualize some exercises and crafts that can be done at home with their children, since it is based on their educational needs.