Reviewerly/exHarmony huggingface dataset:
Comparison and Evaluation of Cross Platform Mobile Application Development Tools

In order to develop a mobile application, it is necessary to develop software separately for each operating system to be outputted. In response to this problem, frameworks that can give application outputs for more than one operating system by developing applications on only one platform have been developed. With the recent diversification of these systems, which are called cross platform mobile application development tools, which one should be preferred has become a problem for developers. In this study, the cross-platform mobile application development tools that have come to the fore in recent years will be determined and evaluated separately based on the pros and cons of distinguishing parameters. With the help of the applications to be developed, values such as processor, memory, battery and network usage, rendering time, opening time, installation file size, application size will be measured. It is also aimed to help developers find out which framework is more suitable for their needs by comparing them on topics such as popularity, third party software support, operating systems that can be outputted, development languages and ease of use, speed - performance. In the study, it was observed that Flutter and React Native gave more successful results.
Implementation of OMR Technology with the Help of Ordinary WebCam

In this modern time, people don’t want to invest their time in something processing. They just want to give an input and take an output immediately. This project is actually an application that we are developing which enables implementation of OMR using an ordinary WebCam. It provides tools to the user to check and calculate on the base of layout they want. The user can give Input through Webcam of system and take correct checked calculate output, distribute it among others from whom information is desired.. The scanned image files will then be provided as input to the software, processing will be done, value of filled fields will be extracted and then the data will be manipulated as instructed by the user. The implementation is done using Opencv and python. We are using Pycharm IDE so as to easily manage the graphical layout and all the resources. For the GUI Python was chosen mainly because of its platform independence and lightweight of the components in python.
Performance Analysis of a Head and Eye Motion-Based Control Interface for Assistive Robots

Assistive robots support people with limited mobility in their everyday life activities and work. However, most of the assistive systems and technologies for supporting eating and drinking require a residual mobility in arms or hands. For people without residual mobility, different hands-free controls have been developed. For hands-free control, the combination of different modalities can lead to great advantages and improved control. The novelty of this work is a new concept to control a robot using a combination of head and eye motions. The control unit is a mobile, compact and low-cost multimodal sensor system. A Magnetic Angular Rate Gravity (MARG)-sensor is used to detect head motion and an eye tracker enables the system to capture the user’s gaze. To analyze the performance of the two modalities, an experimental evaluation with ten able-bodied subjects and one subject with tetraplegia was performed. To assess discrete control (event-based control), a button activation task was performed. To assess two-dimensional continuous cursor control, a Fitts’s Law task was performed. The usability study was related to a use-case scenario with a collaborative robot assisting a drinking action. The results of the able-bodied subjects show no significant difference between eye motions and head motions for the activation time of the buttons and the throughput, while, using the eye tracker in the Fitts’s Law task, the error rate was significantly higher. The subject with tetraplegia showed slightly better performance for button activation when using the eye tracker. In the use-case, all subjects were able to use the control unit successfully to support the drinking action. Due to the limited head motion of the subject with tetraplegia, button activation with the eye tracker was slightly faster than with the MARG-sensor. A further study with more subjects with tetraplegia is planned, in order to verify these results.
The genesis of art and the digital age

The complete translation of cultural heritage into a digital format acutely poses the question of art’s place in the digital era. The search for an answer is built upon the foundation of proposed evolutionary models of the genesis of art. Transitional periods from one historical cultural era to the next are characterized by a change in the most popular types of art. The establishment of one or another type of art is rigidly connected with the introduction of new data storage media and coding techniques. The constant increase in the variety of genres and media has culminated in the digital display. The appearance of a universal digital media must be reflected in the energetic reconstruction of the artistic world, but the birth of new types of art will lag behind. Moreover, the problem of the existence or non-existence of art also becomes relevant. In parallel with the elimination of literature, a virtual excarnation of object plasticity is occurring. It is possible that art is irreversibly forsaking sensual and bodily language, but the idea that it is using such an unexpected lexicon in an attempt to break through to the individual directly seems more productive. The purpose of art is to expand the space of consciousness. The digital age is distinguished by its possibility to transform this space in surprising ways. Digitalization of a work has a clear basic similarity to the physiological process of convolution of a sensory signal in the depths of the brain. Computer-based dipoles and neural synapses are binary structures, described in binary symbols. A work that has been translated into digits can be seen as the projection of a certain neural configuration that has come together in the depths of consciousness and is revealed in the form of an image. The likely prospects of obtaining, instead of projections, a multi-dimensional digital display, as well as the potential possibility for the psyche to adequately decipher it, portend a holistic reading of the work and even closer contact between the artist and the addressee. Right on the horizon is the path towards a synthesis of images that go beyond the limits of the usual forms and sensations. And nowadays unimaginable classes of feelings are capable of generating many vibrant “types and genres”. At the same time, threatening to the habitual methods of sensory perception and facilitating the liberation of the spirit, the excarnation of art works promise a categorically new stage in the genesis of art as well as a different level of creation and perception.
Understanding of Various Type of Unambiguous Discrimination in View of Coherence Distribution

Unambiguous quantum state discrimination is a strategy where the conclusive result can always be trusted. This strategy is very important, since it can be used for various quantum information protocols, including quantum key distribution. However, in the view of quantumness, it is not clear what is going on in performing unambiguous quantum state discrimination. To answer the question, we investigate coherence distribution when unambiguous discrimination is performed by generalized measurement. Specially, we study coherence distribution in three cases, which consist of unambiguous quantum state discrimination, sequential quantum state discrimination, and assisted optimal discrimination, which are considered to be a family of unambiguous quantum state discrimination. In this investigation, we show that the structure of generalized measurements performing various types of unambiguous quantum state discrimination can be understood in terms of coherence distribution. Our result is not limited to the discrimination of two pure quantum states, but it is extended to the discrimination of two mixed states.
A Typology of Persona as Suggested by Jungian Theory and the Evolving Persona Studies Literature

What is persona? Is there a single definition that all Persona scholars agree on? Are Persona scholars all using it in the same way? These are questions that I set out to answer in this paper, exploring both the contemporary persona studies literature and the Jungian concept of persona that is frequently cited as the intellectual root of the discipline. I begin by looking at the definition of persona in core persona studies texts, move on to Jung’s writings on the topic, and then examining the definition and construction of persona in the early volumes of the Persona Studies journal. On the basis of this literature I draw together a typology of persona that reflects the interests and perspectives of authors who have contributed to the development of this discipline. It comprises four categories: 1) persona in the Jungian tradition, a continuous performance pertaining to an individual; 2) generic persona that relates to a particular group of individuals, such as professional personas; 3) fictitious persona that is created in order to serve a specific purpose as art or entertainment, or to inform product design and marketing; and 4) attributed persona, where the characteristics of human persona are applied to a nonhuman entity such as a product or institution. I conclude with a number of suggested directions for research that builds on the Jungian foundations of persona but that draws on other relevant theory from psychology.
A Sparse Transformer-Based Approach for Image Captioning

Image Captioning is the task of providing a natural language description for an image. It has caught significant amounts of attention from both computer vision and natural language processing communities. Most image captioning models adopt deep encoder-decoder architectures to achieve state-of-the-art performances. However, it is difficult to model knowledge on relationships between input image region pairs in the encoder. Furthermore, the word in the decoder hardly knows the correlation to specific image regions. In this article, a novel deep encoder-decoder model is proposed for image captioning which is developed on sparse Transformer framework. The encoder adopts a multi-level representation of image features based on self-attention to exploit low-level and high-level features, naturally the correlations between image region pairs are adequately modeled as self-attention operation can be seen as a way of encoding pairwise relationships. The decoder improves the concentration of multi-head self-attention on the global context by explicitly selecting the most relevant segments at each row of the attention matrix. It can help the model focus on the more contributing image regions and generate more accurate words in the context. Experiments demonstrate that our model outperforms previous methods and achieves higher performance on MSCOCO and Flickr30k datasets. Our code is available at https://github.com/2014gaokao/ImageCaptioning.
Augmented Reality Electronic Glasses Prototype to Improve Vision in Older Adults

In this article, we focus on the elderly who suffer from low vision.We seek to design Augmented reality electronic glasses to help the elderly who suffer from vision problems, which causes a limitation when performing their daily activities, so this can affect their development in society causing serious physical and emotional damage, so we used a set of scientific articles that analyzed the percentage of visual impairment.Technology has demonstrated on numerous occasions that it can be a great ally for the health and well-being of the elderly.In this work, the objective is to design electronic glasses to help the elderly improve their vision.The methodology used is Design Thinking, which thanks to the phases of this methodology helps us to understand, collect information about the problem and give a solution, the result obtained is a prototype of electronic glasses in which it will benefit adults who suffer from low vision.As for the case study, we will show the design of the mobile application and the detailed development of the prototype.
Web-scale Discovery Service Adoption in Canadian Academic Libraries

This study presents an overview of web-scale discovery service adoption in Canadian academic libraries. Web-scale discovery services (WSDS) have been widely embraced in Canadian academic libraries. EBSCO Discovery Service (EDS) is the most adopted system for colleges and institutes while Primo Central from Ex Libris dominates the university market for web-scale discovery services. Bundling web-scale discovery services with library services platform (LSP) implementations are increasing in Canada. This study shows that Canadian academic libraries that have migrated from a traditional integrated library system (ILS) to an LSP have also opted for their LSP vendor’s corresponding web-scale discovery service. As more Canadian academic libraries implement an LSP bundled with a web-scale discovery service, there may come a time when web-scale discovery services are no longer separated from discussions on LSPs. The choices available for LSP and web-scale discovery services are shrinking due to vendor mergers and acquisitions in this area.&#x0D;
MSNet: A novel end‐to‐end single image dehazing network with multiple inter‐scale dense skip‐connections

Dehazing is a challenging ill-posed image restoration task. Various prior-based and learning-based methods have been proposed. Among them, end-to-end deep models achieve great success on performance improvement. However, most of them are concentrated on feature learning within the same block scale in isolation, and cannot perform associated analysis well on feature characteristics of different scales. Inter-scale information reuse which is especially beneficial to image restoration is often neglected. Therefore, in this paper, a novel end-to-end network with multiple inter-scale dense skip-connections for image dehazing is proposed. Sufficient complementary information combination is considered through dense inter-scale skip-connections among encoder and decoder block layers. Besides avoiding gradient vanishing, a kind of bottleneck residual block is proposed to control the importance of local gradients at different scales over global learning process. Extensive comparisons and ablation studies on public dehazing datasets and real-world images have been conducted. The experiment results demonstrate that the proposed novel elements can ensure more stable training process and superior testing performance with great improvements on PSNR and SSIM. Authors' haze-removal results consistently comply satisfactorily with real situations, having much higher definition and contrast without colour distortion than those from the state-of-the-art methods compared in this paper.
Authentication in E-learning systems: Challenges and Solutions

Digitization is gradually penetrating all aspects of modern society. As it changes the way people communicate, technology has revolutionized education and training in the 21st century. With the advantages of reasonable costs and flexible study time, online training is increasingly seen as an attractive alternative to the full-time on-campus training model. To assure quality of distance training and learning, it is crucial for the online learning management system to make sure the person accessing the course resources and performing learning activities is actually enrolled in the course. One of the important factors determining the security of this process is user authentication. In most cases, this role is done with a password, but the evidence shows that this method is easily compromised. While there are many alternatives available such as biometric methods, user-challenging methods, smart card methods, etc. The strong development of technology that requires confidentiality and authentication must be tightly coupled. A qualitative survey of user authentication systems is being used in today's E-learning systems and a comparative study of various different authentication mechanisms presented in this paper. There are many methods of user authentication for online learning systems, but each method will have different advantages and disadvantages and has not completely solved the challenges of user authentication. The issue of user authentication still has many challenges that need to be solved thoroughly to improve the security of the system as well as the trust of users and society. This paper provides an overview of our approach and recommendations to address the mentioned issues. In addition, we propose a number of feasible approaches to improve user data privacy as well as improve the effectiveness of the authentication process in the online learning system.
Epistemic Logic of Know-Who

The paper suggests a definition of "know who" as a modality using Grove-Halpern semantics of names. It also introduces a logical system that describes the interplay between modalities "knows who", "knows", and "for all agents". The main technical result is a completeness theorem for the proposed system.
Advanced Voting System Using Fingerprint

A Fingerprint is an important identifier for the humans. This paper proposes finger print voting system with Arduino. The majority of the worldwide election were using a paper-based voting rather than using biometric system. The current voting process has safety problems such as authenticity of voters. In proposed system, a voter identity can be proved instantly. All voters’ information was stored securely to register in the system. The main objective is to enhance the security in order to prevent duplication and provide a system which reduce the burden for people on conducting a voting. Thus, by implementing this system, user can put their vote with fingerprint instead of paper without doubting about their security. Voting Using Fingerprint reduce the polling time, it provides easy and accurate counting without human labor.
Water flow speed determining using visualization methods

Despite the variety of means for measuring the flow velocity, it remains relevant to develop new methods and modify the existing ones that will make it possible to obtain more information about the dynamics of the water flow.Currently, flows studies using visualization methods are gaining more and more popularity.The article discusses the developed by the author of the water velocity meter based on the PIV method, capable of working in natural conditions.The use of natural suspended matter particles as tracers can significantly accelerate the experiments performance and reduce the cost of there implementation, which is important while working in the field.A description of the developed methodology and technical means for measuring the flow velocity is given.The results obtained during field tests are presented.Owing to the modern visualization methods use, the created meter has a number of advantages in comparison with other devices for flow studies.In particular, it makes it possible to obtain instantaneous and averaged fields of the flow velocity distribution in a wide spatial and temporal range.
Evaluation of Pre-service Teachers’ Actual use towards Augmented Reality Technology through MARLCardio

Augmented reality (AR) offers an innovative learning space through an active interaction of real world with computer-assisted contextual layer of information to enhance learning experiences.AR is exciting to explore in which it can enhance a user's impression of and interaction with real and virtual world.There have been some attempts to use AR for training and educational purposes; however the potential of AR in education remains unexplored as it seen as a future of education.In addition to the lack of information about AR in education especially in Malaysia, there is also inadequate information about the influencing factors in determining students' decision to use AR in their learning process.Thus, the present paper aims to evaluate factors that might influence pre-service teachers' decision in using AR technology through Mobile Augmented Reality Learning Cardiovascular (MARLCardio).A selfdesigned MARLCardio was used as an experimental tool in data collection process.All respondents were given a chance to explore an AR features in MARLCardio before they responds to a web-based survey.The respondents of the study are 459 pre-service teachers at three public universities in Malaysia with different field of study.All data gathered from the questionnaire was analysed using path coefficients in SmartPLS.As a result of this investigation, results revealed that attitude (ATT) is the main factor in determining the actual use of MARLCardio.Surprisingly, field of study (FOS) was not found as a moderating effect of any relationship.
The Future of AI or AI for the Future

The third hype of AI and enthusiasm for applying last techniques in all fields raise great interest and some important questions on the future directions in AI research and applications. Guiding by the principle of combing the best from human and computers capacities this chapter lists some important challenges to face and related directions in AI research. Multiple interrelated crises such as natural disasters, pandemics and other generated by humans require new approaches, combining existing techniques and set new directions for research. This chapter presents briefly the Artificial General Intelligence (AGI) concept and the challenges to face in sustainability, smart resources management, future connectivity, industry, agriculture, health, economy and education. The presented vision for the future of AI includes both researchers’ dreams and emergencies.
CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions

Humans are able to perceive, understand and reason about causal events.Developing models with similar physical and causal understanding capabilities is a long-standing goal of artificial intelligence.As a step towards this direction, we introduce CRAFT 1 , a new video question answering dataset that requires causal reasoning about physical forces and object interactions.It contains 58K video and question pairs that are generated from 10K videos from 20 different virtual environments, containing various objects in motion that interact with each other and the scene.Two question categories in CRAFT include previously studied descriptive and counterfactual questions.Additionally, inspired by the Force Dynamics Theory in cognitive linguistics, we introduce a new causal question category that involves understanding the causal interactions between objects through notions like cause, enable, and prevent.Our results show that even though the questions in CRAFT are easy for humans, the tested baseline models, including existing state-of-the-art methods, do not yet deal with the challenges posed in our benchmark.* indicates equal contributions. 1 Data and
Urszula Walińska at SemEval-2020 Task 8: Fusion of Text and Image Features Using LSTM and VGG16 for Memotion Analysis

In the paper, we describe the Urszula Walińska's entry to the SemEval-2020 Task 8: Memotion Analysis.The sentiment analysis of memes task, is motivated by a pervasive problem of offensive content spread in social media up to the present time.In fact, memes are an important medium of expressing opinion and emotions, therefore they can be hateful at many times.In order to identify emotions expressed by memes we construct a tool based on neural networks and deep learning methods.It takes an advantage of a multi-modal nature of the task and performs fusion of image and text features extracted by models dedicated to this task.Our solution achieved 0.346 macro F1-score in Task A -Sentiment Classification, which brought us to the 7th place in the official rank of the competition.