Reviewerly/exHarmony huggingface dataset:
A Hybrid Approach for Learning Program Representations

Learning neural program embeddings is key to utilizing deep neural networks in program languages research --- precise and efficient program representations enable the application of deep models to a wide range of program analysis tasks. Existing approaches predominately learn to embed programs from their source code, and, as a result, they do not capture deep, precise program semantics. On the other hand, models learned from runtime information critically depend on the quality of program executions, thus leading to trained models with highly variant quality. This paper tackles these inherent weaknesses of prior approaches by introducing a new deep neural network, \liger, which learns program representations from a mixture of symbolic and concrete execution traces. We have evaluated \liger on \coset, a recently proposed benchmark suite for evaluating neural program embeddings. Results show \liger (1) is significantly more accurate than the state-of-the-art syntax-based models Gated Graph Neural Network and code2vec in classifying program semantics, and (2) requires on average 10x fewer executions covering 74\% fewer paths than the state-of-the-art dynamic model \dypro. Furthermore, we extend \liger to predict the name for a method from its body's vector representation. Learning on the same set of functions (more than 170K in total), \liger significantly outperforms code2seq, the previous state-of-the-art for method name prediction.
Life is Beautiful. Always: Using virtual reality to share the experience of disability

This paper discusses 'Life is Beautiful. Always.'; a virtual reality (VR) experience created as part of an ongoing research collaboration between practitioners in film and experiential design and multi-disciplinary expressionist artist, Marcel Schreur. Incorporating extracts from recorded interviews, 3D capture of Schreur's studio, painting and sculpture, original pieces of 3D sculpture work created within VR by Schreur, motion capture, 3D animation, randomisation and user responsiveness, the experience generates a cyclical, non-linear narrative that explores Schreur's unique life experience and approach to art practice as a thirty year oral cancer and seven year vascular dementia survivor. Developed through an iterative process of interviews, prototyping and personal responses from Schreur, the work generates a space that allows participants to consider aspects of their own mental process through a lens of difference and disability, to embody some of the physical characteristics of Schreur’s condition and to help facilitate communication about the experience of living with life-altering disability between sufferers, non-sufferers and medical professionals.The creative process has enabled Schreur and collaborators to develop a shared conceptual framework with which to understand and communicate core physical, mental and emotional aspects of Schreur’s condition and the impact this has on his life and art. This feeds into a broader research project that questions the use of VR as a platform to translate and communicate experience, and how this may be used to problematise and encourage dialogue on the relationships between self, environment, presence, memory and experience.
POTENSI ARTIKEL UNTUK DIMUAT DI JURNAL NASIONAL DAN INTERNASIONAL Studi Kasus Di Fakultas Sains Dan Teknologi (Dalam Rangka Pengembangan Manajemen Jurnal Pendidikan Matematika UIN Sunan Kalijaga/JPMSUKA)

This study aims to find out how the potential articles in the Mathematics Education Study Program at the Faculty of Science and Technology UIN Sunan Kalijaga to be published in the nationa l journal of accreditation and international journal. The type of research used in this study is qualitative research with a case study approach. The sample in this study are 25 articles selected from a total of 247 articles in the population. The research instruments use d in this study includ e article rating scales, interview guidelines, and observation guidelines. Data triangulation is done to test the validity of the data obtained. The data analysis technique use d in this study is descriptive quantitative and qualitative descriptive. The results showe s that (1) articles written by students of the Mathematics Education Study Program at UIN Sunan Kalijaga Yogyakarta have high potential to be published in reputable national journals and international journals in the abstract, preliminary aspects, aspects of research methods, outcome aspects, discussion, and conclusions, as well as aspects of language and display format; (2) articles written by students of the Mathematics Education Study Program at UIN Sunan Kalijaga Yogyakarta have the potential to be published in reputable national and international journals in the library aspect.
Review Sentiment Orientation Analysis based on Deep Learning

Abstract The increase of network users has led to a large number of commentary languages on various network platforms. Traditional manual processing is time-consuming and labor-intensive. We need a mechanized way to process these commentary corpora and quickly uncover the emotional tendencies. A method of sentimental orientation analysis of comment text based on deep learning is proposed. First, we used GloVe model to train the word vector. Then, Give the different weight on word vector by using TF-IDF. Finally, the processed word vectors would be classificated by TextCNN. Experiments were carried out on the six categories of commodity review data crawled by Jingdong. This method can effectively identify the emotional tendency of the review text, which is more accurate than the traditional deep learning method.
Integration of Augmented Reality with Pressing Evaluation and Training System for Finger Force Training

One major concern for the elderly is the decline in their ability to control their hands, which can significantly affect their ability to perform activities of daily living. One of the important hand functions that deteriorate over time is the ability to control finger force exertion, due to the gradual decrease in finger muscle strength as people age. Previous studies have shown that with proper training, it is possible to regain finger strength. However, when designing training systems for finger force control, visualization of the finger forces plays an important role in its effectiveness. In this paper, we describe the development of the augmented reality pressing and evaluation system (AR-PETS), an augmented reality based prototype system for finger force control training. We discuss the development of the system, as well as the design considerations during the development of the system.
Putting some “sense” into our research

Purpose This paper aims to propose using human senses as a means of thinking about the contributions of this research. Design/methodology/approach Based upon the metaphor of human senses, the model describes different aspects of research, such as topic selection, theory and method, providing suggestions for enhancing relevance and expanding the audience for the research. The model is applied to a current working paper on cyber security and then more broadly to provide suggestions for researchers who are interested in conducting research on risk. Findings The model can be used to frame different types of research projects in a way that helps to increase the interest in and impact of this research. Research limitations/implications The model in the paper is ad hoc but provides a fresh way to view this research. Social implications Increasing interest in accounting research can result in a broader audience for this work. Originality/value The paper provides a means for researchers to step back from their research and think about what makes their research original and interesting.
Interval Search with Quadratic Interpolation and Stable Deviation Quantum-Behaved Particle Swarm Optimization (IQS-QPSO)

In this article, in order to enhance the rate of convergence and scattering of particles at the same time, simple techniques are introduced.These techniques include: (1) Using the interval search to select a new particle candidate, (2) Replacement of three candidate particles instead to worst the particles in the population, (3) Using the best result of learning coefficients, (4) using a simple method to control the convergence of the algorithm in a high number of repetitions.In this article, the performance of Quantum-Behaved Particle Swarm Optimization (QPSO) algorithm has been upgraded with using the interval search method.The proposed method of interval search of quantumbehaved particle swarm optimization algorithm has achieved better results than in the past with the use of quadratic interpolation recombination operator and stable deviation and interval search.Moreover, the results of the proposed algorithm of Interval Search with Quadratic Interpolation and Stable Deviation Quantum-Behaved Particle Swarm Optimization (IQS-QPSO) is compared with the other former algorithms such as Quantum-Behaved Particle Swarm Optimization (QPSO), Quadratic Interpolation Quantum-Behaved Particle Swarm Optimization (Q-QPSO) and Stable Deviation Quantum-Behaved Particle Swarm Optimization (SD-QPSO).Then the performance improvement is reported.In order to compare the results of each algorithm, five famous functions are used and consequently the results are reported separately for each function.
The Vehicle Pattern for Simplifying Cross-Platform Virtual Reality Development

Maintaining an application across different virtual reality systems can be difficult and time-consuming. Different systems require different strategies for implementing simple interactions such as locomotion and object manipulation. In this chapter, we describe a pattern that we have used to minimize the interactions betweenthe interaction style (behaviour) with the scene elements, and the specific interaction devices. The vehicle pattern allows the programmer to ignore most of the implementation details of hardware and interaction, and focus on the scene description. They can then easily generate versions of the scene for different systems. Wedemonstrate the principles of the vehicle pattern with an outline implementation in Unity
THE DEVELOPMENT OF UNIVERSITY COMPETITIVENESS: IMPROVING THE LEVEL OF FACULTY RESEARCH ACTIVITIES

This article discusses ways to improve the University faculty research activities and the role of the University library as a center of information resources, which identifies the modern University library development trends, aimed at increasing the publication activity of University faculty.The improvement of the system of access to information resources is a traditional vector of the development of information technologies in the University library.Currently, it is important to preserve the crucial role of library services in learning and research.Thus, one of the most important areas of our activity is the integration of the library access system with its electronic catalog.The library accumulates electronic educational and scientific content of university researchers and provides open access to it for its users.The article identifies the key components that make it possible to ensure the University international competitiveness.The task of the library in the Project 5-100 is to promote the mission of the University and its academic community, support its best practices and innovations in education and research, management and provision of information, preservation of intellectual and cultural heritage.To this end, the modern library should improve its activities, promptly respond to the changes in the external environment and be involved in university activities, aimed to increase its competitiveness.
An Adaptive Tai-Chi-Chuan AR Guiding System Based on Speed Estimation of Movement

Augmented Reality (AR) headsets has become a potential device as an auxiliary tool for practicing physical activities such like Tai-Chi Chuan (TCC). Although some learning systems can display the virtual coach movement in AR headsets, the playing speed cannot be adjusted appropriately just like a real coach stand next to you. In most of the learning system, the common approach is using controller to control the playback system under a specific speed. Once user want to speed up or speed down, he has to do these commands via a controller. In this work, we propose a TCC learning system which will real time detect the delay time between current action of user and virtual coach. After obtaining the delay time, our learning system will adjust speed of virtual coach automatically. With real time speed adjustment, learners can practice TCC with their own pace and virtual coach will slow down or speed up to follow learners’ movement.
From Painting to Widgets, 6-DOF and Bimanual Input Beyond Pointing

This chapter presents an approach to designing expressive three-dimensional (3D) user interfaces that make use of handheld input devices tracked in 3D space to go beyond a simple pointing metaphor. It considers a series of three examples that build upon each other to demonstrate how sophisticated 6-degree-of-freedom, beyond-pointing, bimanual virtual reality (VR) user interfaces can be built upon this framework. Although event-based user interfaces are common in desktop computing, there are several important nuances in VR. The state machine design pattern that developers suggest for programming VR interfaces helps programmers to track and respond appropriately to changes in context. The user interface to select curves must be flexible and controlled enough that users are able to indicate their desired selection regardless of the particular texture. The chapter describes how to implement contextual constraints to improve control of 3D User Interfaces.
Why and Why Not Use My Face?—A Case Study of Face Recognition Solutions in the Workplace

Face recognition (FR) technology is permeating and changing our lives from mobile phone to public space in China. Baidu utilizes advanced FR technology to support tens of thousands of employees in their daily access and payments. However, as a new way of human–machine interaction, a handful of researches of face interaction in the field of HCI were conducted. This study aimed to solve three issues: Users’ behavior during face interaction; What are the reasons for using and not using FR? What are the advantages of user experience of FR? With the methodology of field observation and interviews, we studied the face interaction on five typical scenarios, including the gate barriers, corridors, canteen, supermarket, and vending machines. Through the analysis of these issues, we had a comprehensive and in-depth understanding of experience problems and advantages of face interaction in public space. Basing on our findings, design implications were given focusing on reducing or avoiding these problems, and strengthen the advantages of face interaction. We believe it would be beneficial for the FR which is at the early stage of HCI research.
Evolving planar mechanisms for the conceptual stage of mechanical design

This study presents a method to evolve planar mechanism prototypes using an evolutionary computing approach. Ultimately, the idea is to provide drafts for designers at the conceptual design stage of mechanism design which meet their design brief. The designers can review, analyze and incorporate the drafts into the development of a mechanical system. This work proposes a stepping stone towards a generative design system which is capable of evolving such planar mechanisms with a focus on the configuration and shape of their components. In this paper, we present a use-case of evolving four-bar linkages with attached shaped component to study the evolutionary approach. In addition to kinematics, we consider properties such as the shape of levers, placement of rotation joints, torque, friction, restitution, and mass. The design aim was to move a mechanism as fast as possible in the forward direction whilst overcoming obstacles in a virtual environment involving gravity. Our method was evaluated using complex environments with different obstacles. The results verify that it was able to evolve a variety of high performing mechanism drafts. The study provides a promising outlook of using this method to support the conceptual stage of mechanical design.
Reinforcement Learning with Chromatic Networks

We present a new algorithm for finding compact neural networks encodingreinforcement learning (RL) policies. To do it, we leverage in the novel RLsetting the theory of pointer networks and ENAS-type algorithms forcombinatorial optimization of RL policies as well as recent evolutionstrategies (ES) optimization methods, and propose to define the combinatorialsearch space to be the the set of different edge-partitionings (colorings) intosame-weight classes. For several RL tasks, we manage to learn coloringstranslating to effective policies parameterized by as few as 17 weightparameters, providing 6x compression over state-of-the-art compact policiesbased on Toeplitz matrices. We believe that our work is one of the firstattempts to propose a rigorous approach to training structured neural networkarchitectures for RL problems that are of interest especially in mobilerobotics with limited storage and computational resources.
The interpolation effect on the spare sinogram for 3D image reconstruction

The effect of using three different interpolation methods (nearest neighbour, linear and non-linear) on a 3D sinogram to restore the missing data due to using angular difference greater than 1° (considered as optimum 3D sinogram) is presented. Two reconstruction methods are adopted in this study, the back-projection method and Fourier slice theorem method, from the results the second reconstruction proven to be a promising reconstruction with the linear interpolation method when the angular difference is less than 20°.
Upstream, Downstream or Competitor? Detecting Company Relations for Commercial Activities

Due to intricate network in industry business and high cost of supervision, financial institutions usually focus on supervising core enterprises in a supply chain instead of all corporations, which indirectly lower the strength and efficiency of financial institutions as a role of capital supervisor and credit-risk transformer. Furthermore, banks require these corporations to provide correct information by themselves, which lacks of the objectivity of the source information and increases the supervision cost for these banks. Thus, we summarize a company relation detection task in hope to exposing more information about companies to investors and banks by learning a system from public available datasets. We regard this task as an classification problem, and our system can predict relations between any two companies by learning on both structured and unstructured data. To the best of our knowledge, it’s the first time to implement deep learning technique to this task. A F1 score 0.769 is achieved from our system.
Contextualization And Entextualization Mandarese Patriotism In Kalindaqdaq Pettomuaneang Performance

Kalindaqdaq is one literary work of Mandarese, the majority ethnic in West Sulawesi. It is categorized as an old poem, and nowadays Kalindaqdaq is only shown in a few cultural events. The objective of this research is to explore Mandarese local wisdom related to patriotism through contextualizing and entextualizing Kalindaqdaq Pettomuaneang. This research used a qualitative method with two approaches; systemic functional and ethnographical approach. The result shows that the emergence of Kalindaqdaq Pettomuaneang was influenced by the political situation. Based on its contextualization, there are three characteristics of an ideal leader. They must have sincerity, consistency, and firmness. Next, intextuality involved some contexts. Texts in manetteq context are decontextualized such as manetteq (weave), lipaq (sarong), bannang pute (white yarn), lango-lango (dye), sureq (motif), and pucca (center of motif), and after that, they are recontextualized in patriotism as its new context. Leadership is seen as the same as weaving process, not only be carefulness, a good leader should be creative. So seeing the success of contextualization and entextualization in Kalindaqdaq Pettomuaneang, it can be concluded that Mandarese is ethnic with high cognitive characteristics. Because of to do contextualization and entextualization, people should have specific competence in language and logic.
Tangible Map: Designing and Assessing Spatial Information Retrieval Through a Tactile Interface

This paper addresses the design, development and evaluation of an interactive Tangible Map as a way to collect, display, and provide various information about a public space (in this case, a university campus) for easy retrieval and access. Through its ability to (a) display multiple sets of information upon tactile inputs, and (b) encourage interactions through 3D features and visual stimuli, the Tangible Map acts as a bridge between abstract campus data (e.g. classes hours and locations, faculty offices, shuttle hours) and the physical spaces the data refers to. The Map’s effectiveness in easing access to information and its potential for encouraging data exploration, compared to existing mediums, is evaluated through a preliminary user study. Results suggest that the map’s 3D tangible features and tactile interactions can facilitate information retrieval and can support the exploration of abstract data.
Efficient On-Chip Randomness Testing Utilizing Machine Learning Techniques

Randomness testing is an important procedure that bit streams, produced by critical cryptographic primitives such as encryption functions and hash functions, have to undergo. In this paper, a new hardware platform for the randomness testing is proposed. The platform exploits the principles of genetic programming, which is a machine learning technique developed for the automated program and circuit design. The platform is capable of evolving efficient randomness distinguishers directly on a chip. Each distinguisher is represented as a Boolean polynomial in the algebraic normal form. The randomness testing is conducted for bit streams that are either stored in an on-chip memory or generated by a circuit placed on the chip. The platform is developed with a Xilinx Zynq-7000 All Programmable System on Chip that integrates a field programmable gate array with on-chip ARM processors. The platform is evaluated in terms of the quality of randomness testing, performance, and resources utilization. With power budget less than 3 W, the platform provides comparable randomness testing capabilities with the standard testing batteries running on a personal computer.
Evaluation of Web Usability Requirement Model and Web Application Interface Components

In web application, being a non-quality requirement, usability has been quite a concern for a product to be more successful and efficient for users in the competitive market. User centric design methodology is also based on usability design. Even usability is just a nonfunctional requirement but usability analysis and design can impact the behavioral requirement of a web application in a great extent. The review and feedback sessions are done during prototype design and sometimes like in agile XP process during the user interface designing step. A web application is built on collection of defined HTML controls and components. Our ultimate goal would be to model a guideline of usability requirements for different web application components based on different characteristics of usability like learnability, efficiency, memorability, error recovery, flexibility. In this paper we have evaluated a composite usability requirements model based on the usability requirement attributes & principals and categorization the web application components based on web application design and interaction context.