Reviewerly/exHarmony huggingface dataset:
Bibo the Dancing Cup: Reminding People with Dementia to Drink

We present the concept and technical realisation for a cup that moves and lights up so as to bring itself to the attention of a person with dementia, to trigger taking a sip as a response. The concept is aimed at people with dementia in home or resident care who still have the ability to act, but tend to mentally drift away and thus require external impulses and triggers. The cup moves and lights up in regular intervals if it has not been picked up recently. Once it is emptied, it alerts a caregiver to refill. Moreover, the degree or level of movement and light can be configured, depending on the person’s needs and reactions. This paper describes the core idea and focuses on the technical aspects of building a prototype on Technology Readiness Level (TRL) 3.
Preservation of Privacy using Multidimensional K-Anonymity Method for Non-Relational Data

Mining of huge data having complexity is a challenging issue also maintaining Privacy of data is also equally important ,sometimes there is a need to release data for use of researchers or for the purpose of gaining knowledge or earn money this release of data includes releas e of all attributes of personal data. when this type of data like Insurance record data, Medical diagnosis data, funding scheme data is release even if we remove sensitive attribute like Name for hiding personal details still data re-identification is possible by linking public data like voters data with these released data and by linking the quasi identifiers we are able to get sensitive information about person like critical disease, financial position etc. by applying k–Anonymization using multiple dimensions of attributes we are able to hide these sensitive attributes by generalising and suppressing the Quasi identifiers so that when linking with public database is done no records are re-identified, also we obtained results for quality measures for anonymisation and observed that the value of k once we start increase after some threshold anonymity starts decreasing so there is a need to choose proper value of k on non-relational data
Efficient View Synthesis Algorithm Using View Selection for Generating 6DoF Images

We propose an efficient virtual synthesizer for omnidirectional and windowed six degrees of freedom (6DoF) images. We introduce a novel view-selection-based method suitable for processing numerous input images. The experimental results demonstrate that our method reduces the execution time and improves the resulting image quality.
Egocentric Smaller-person Experience through a Change in Visual Perspective

This paper explores how human perceptions, actions, and interactions can be changed through an embodied and active experience of being a smaller person in a real-world environment, which we call an egocentric smaller person experience. We developed a wearable visual translator that provides the perspective of a smaller person by shifting the wearer's eyesight level down to their waist using a head-mounted display and a stereo camera module, while allowing for field of view control through head movements. In this study, we investigated how the developed device can modify the wearer's body representation and experiences based on a field study conducted at a nursing school and museums, and through lab studies. Using this device, designers and teachers can understand the perspectives of a smaller-person including a child in an existing environment.
Using Mobile Technologies in Education

The acquisition of reading skills is decisive for the academic achievement of students. However, learning to read is a complex process. With this in mind, several attempts have been made to find new educational approaches to enhance students' reading motivation. Considering the enormous potential of ICT for education and training, we have developed a digital repository of teaching and learning materials and a multiplatform application that runs on mobile devices: Letrinhas. This information system was designed to promote the development of reading and to provide tools for monitoring and assessing reading skills against the curricular targets set by the Ministry of Education. Letrinhas was evaluated by specialists and users and a high level of satisfaction was observed among students and teachers as time and effort spent to consolidate reading is considerably reduced with this application. This evaluation also enabled to identify features that will be available in the future.
WatchPen

WatchPen illustrates how cross-device interactions can inspire and extend the design space of pen-based interactions into new, expressive directions. We demonstrate WatchPen, a smartwatch mounted on a passive, capacitive stylus that: (1) senses the usage context and leverages it for expression (e.g., changing colour), (2) contains tools and parameters within the display, and (3) acts as an on-demand output. As a result, it provides users with a dynamic relationship between inputs and outputs, awareness of current tool selection and parameters, and increased expressive match (e.g., added ability to mimic physical tools, showing clipboard contents). Our demonstration includes a series of interaction techniques within a drawing application.
Mobile Forensics

Mobile Forensics is a branch of Digital Forensics. It is about the acquisition and analysis of mobile devices to recover digital evidence for forensics investigations.
Squashing Functions

In fuzzy logic, the most commonly used membership functions are triangular and trapezoid ones. A crucial drawback of these functions is the lack of differentiability; a property that would be useful for learning systems. In this chapter, we introduce the so-called squashing functions; a differentiable parametrized family of functions that can not only be used for approximating piecewise linear membership functions but also Łukasiewicz-type logical operators. We show that the derivative of a squashing function is the difference of two sigmoid functions. This fact will come useful in gradient-based applications.
The improvement of hand gesture recognition based on sEMG by moving average filtering for features

Surface electromyographic signal (sEMG) is a kind of bioelectrical signal, which records the data of muscle activity intensity. Hand gesture recognition based on sEMG plays an important role in the hand rehabilitation robotics. Improving the recognition accuracy of hand gesture is the goal always pursued by researchers. This study purposes to evaluate the performance of moving average filtering for features in improving the accuracy of hand gesture recognition based on sEMG. Firstly, empirical mode decomposition was applied on the effective motion segments extracted by sliding windows with different size and stride. Afterward, 21 features were extracted from original signal and each of the intrinsic mode function. Subsequently, moving average filtering with different orders were used to further suppress the noise in each feature series to improve the recognition performance. Finally, two representative machine learning methods (including decision tree and K nearest neighbor) were used to evaluate the performance. Compared with the original features, the intra-subject recognition accuracy rate after feature processing for KNN and DT increase by 17%, and 6%, respectively. The accuracy of the inter-subject across five subjects after feature processing increase by 28% (KNN), and 12% (DT), respectively. The above results prove that the moving average filtering for features could effectively improve the performance of hand gesture recognition.
Imaginary Use

We have been using tools and technology to achieve our goals for millions of years, reaching back from the earliest tools of stone or wood or bone artefacts to the latest 3D printed parts or microfabricated semiconductor. Our use of these tools is based, in part, on our ability to formulate a goal and to imagine a technological solution (that is, tools plus appropriate skills). However, since the advent of digital technology, use has changed. Once we would have picked up an axe and swung it, chopping wood for home and hearth, now we use tools indirectly via a user interface. We pick up our phones and tap an icon—a little picture—which we are invited to make-believe stands for access to a service, or contact with other people, or the world as a whole including someone else who will chop and deliver logs for us. In using digital technology, the importance of our imaginations has become paramount. This chapter identifies the interplay between use and imagination in a number of ways. Firstly, most digital technology which is used by people is either the result of a prototyping approach or a methodology which employs prototyping. A prototype is an early, unfinished version of the target technology and is frequently used during its development on the basis of pretence. Users of prototypes agree to make-believe its use, is to a greater or less extent, close enough to the finished (or next) version. This is particular true of low-fidelity prototypes. Secondly, our use of digital technology is indirect as it relies on an interface of some kind. Very many (and possibly most) user interfaces rely on the metaphorical portrayal of the technology and in turn, metaphor relies unequivocally on imagination. Next, our experience with digital technology (according to the ISO definition at least) includes imaginary use. Here, experience is thought to be the product of anticipated or expected or the imagined use of technology, which does not, of course, require the involvement of technology itself. Then there are those technologies which are expressly imaginary. We end this chapter with a discussion of VR and wonder why there is no mention of imagination or make-believe in the various accounts of it.
A Hybrid Watermarking Technique for Copyright Protection of Medical Signals in Teleradiology

Today, an individual's health is being monitored for diagnosis and treatment of diseases upon analyzing various medical data such as images and signals. Modifications of this medical data when it is transferred over an open communication channel or network leads to deviations in diagnosis and creates a serious health issue for any individual. Digital watermarking techniques are one of the solutions for providing protection to multimedia contents. This chapter gives requirements and various techniques for the security of medical data using watermarking. This chapter also demonstrates a novel hybrid watermarking technique based on fast discrete curvelet transform (FDCuT), redundant discrete wavelet transform (RDWT), and discrete cosine transform (DCT). This watermarking technique can be used for securing medical various types of medical images and ECG signals over an open communication channel.
Issue of Innovative Potential of Students of Industrial Universities - «Rosatom» State Corporation Partners

The paper presents a study of the student interest level at VETI NRNU MEPhI in the development of their own innovative potential. It considers the formal side of youth involvement in the implementation of research projects and the improvement of their own intellectual forces. A sociological survey showed a fairly high level of students' innovative charge noted the difficulties of using an innovative resource, and formulated possible causes of problems of self-realization in this direction. It is found that most of the young people surveyed do not have a steady motivation to reveal their own innovative potential explaining this by increased complexity and laboriousness. The problem of formal and informal employment of students is noted, its causes are revealed. The given data indicate the importance of the development of scientific research skills and confirms the idea that the problem of inefficient use of innovative potential is quite significant, covers a significant part of students and requires further study and system monitoring.
PENGEMBANGAN MEDIA PEMBELAJARAN VIDEO TUTORIAL PADA MATA PELAJARAN SISTEM OPERASI KELAS X MULTIMEDIA SMK NEGERI 6 SURAKARTA TAHUN AJARAN 2015/2016

The purpose of this research is to develop media with video technology tutorials that can use in learning of operating system subjects in class X MM 1 6th Vocational High School Surakarta. The method used in this research was Research and Development, in the form of the development of media-based instructional video tutorials and tried out the media in class X Multimedia 1 6th Vocational High School Surakarta. The design was done with a procedure analysis, design, development and workout. The series of product development done by decided the teaching materials and the requirement, design layout and create storyboard, instructional media supporting objects collection, workout of product and revision. Data analysis techniques used in this study was a simple descriptive analysis, which modifying the interval mean of score. These results indicate that ratings matter from content expert who claim that the learning media video tutorial met both criteria once with a percentage of 78,7%. Media expert assessment of the learning media video tutorials with the overall percentage of 87,5% that met both criteria at all. Learning practitioners expert assessment of the learning media video tutorials with the overall percentage of 83,6% that met both criteria. While the responses of students X Multimedia I 6th Vocational High School Surakarta gained the score percentage about 90%, which mean the learning media video tutorials met both criteria at all. It can be concluded that the learning media video tutorials reasonably and can use in learning of operating system subject class X Multimedia I 6th Vocational High School Surakarta.
Systems of Electronic Document Management in Russian Education. Pros and Cons

Systems of electronic document management are wide spread in Russia. However, each university tries to use its own version or specific program for it. As a result, there are many bugs in these systems. Nevertheless, each of these systems has its own benefits for document management. Each document can simultaneously be revised by different people, it helps intensify the process of working with it. Usually the system does not allow losing any document or signature. Such systems help to improve quality management in Russian universities.
Semi-supervised Adversarial Domain Adaptation Based on Maximum Mean Discrepancy

Domain adaptation aims to transfer knowledge from a source domain to a new but related target domain. Most adversarial training methods align feature distributions thus both domains can share the same classifier. However, compared to unsupervised adversarial domain adaptation, supervised information from the labeled target domain can better guide the transfer process by learning transferable as well as discriminative features. In this paper, we propose a novel semi-supervised adversarial domain adaptation (SSADA) method that can align the feature distributions across domains. In SSADA, labeled target samples are used to learn discriminative features while unlabeled target samples are used to learn transferable features based on Maximum Mean Discrepancy. The experiments on public datasets demonstrate the effectiveness and efficiency of our proposed method.
A PSO-RBF neural network for BOD multi-step prediction in wastewater treatment process

The single-step prediction of the effluent biochemical oxygen demand (BOD) in wastewater treatment process (WWTP) cannot provide the information for future trends, which will affect the decision-making for subsequent control strategies in WWTP. To solve this problem, a radial basis function (RBF) neural network soft-sensing model based on PSO algorithm (PSO-RBF) is proposed for multi-step prediction of the biochemical oxygen demand (BOD) in WWTP. First, we propose an RBF model for multi-step prediction based on MIMO strategy. Then, the PSO algorithm is used to optimize the RBF parameters. Finally, the proposed model is applied to a four-step BOD prediction in WWTP. Experimental results show that this model can better predict BOD in multiple steps compared to traditional models.
An Evaluation of Chinese Human-Computer Dialogue Technology

Abstract There is a growing interest in developing human-computer dialogue systems which is an important branch in the field of artificial intelligence (AI). However, the evaluation of large-scale Chinese human-computer dialogues is still a challenging task. To attract more attention to dialogue evaluation work, we held the fourth Evaluation of Chinese Human-Computer Dialogue Technology (ECDT). It consists of few-shot learning in spoken language understanding (SLU) (Task 1) and knowledge-driven multi-turn dialogue competition (Task 2), the data sets of which are provided by Harbin Institute of Technology and Tsinghua University. In this paper, we will introduce the evaluation tasks and data sets in detail. Meanwhile, we will also analyze the evaluation results and the existing problems in the evaluation.
Using Web Crawler Technology to Realize the Cross- cultural Communication of "Foreign online Celebrities" Videos on the Internet Platform : —Take the example of "I am Jerry Kowal"

With the continuous iteration of online video platforms supported by big data, artificial intelligence, and internet technology, the phenomenon of "Foreign Online Celebrities" is increasingly becoming an important subject in the creation, production and dissemination of online video content. Behind this is an inevitable choice for the connection of existing network media. And more blessings of new media technology and algorithm tools. With the help of data mining methods of computational communication and the analysis theory of digital humanities, this paper analyzes how " Foreign Online Celebrities " use media platforms to connect Chinese and foreign cultures and their audiences. Using computer crawler technology to obtain the "I am Jerry Kowal " account data on the Bilibili platform as the research content, and using "the DEEPL Model" and "the Hidden Markov Model" to visualize the video keywords. The paper explores the main factors of the blogger’s use of internet technology to spread video narratives across cultures, and investigate the technical and non-technical characteristics of its content dissemination In-depth analysis, pointed out that the cross-cultural communication network video narrative strategy from the perspective of the "other" has an enlightening effect on the "going out" of local video uploaders and the innovative exploration of digital communication.
Semantic based Cross-Language Clone Related Bug Detection

Code clones are widespread in software since programmers always reuse code to reduce programming effort. As programming languages are continuing to evolve and morph, code clones also widely exist across different languages for platform compatibility and adoption. Although code clones can improve development efficiency, they are prone to introducing bugs. Existing code clone detection technologies, however, mainly focused on single programming language or syntactical features of code. The syntax of different programming language are diverse because of syntax sugar, and many cloning pairs are semantic related instead of syntactic similar, such as Type 4 clones. To bridge the gap between syntax and semantic, and detect clone-related bugs more accurately, we explore an IR (Intermediate Representation) based method to represent code semantic representation information of multiple language code. We utilize graph neural network to learn code semantic representation. Through the semantic representation, we can detect more cross-language clone related bugs across multiple language.
Research on the Application and Development of Digital Supply Chain Using Internet of Things and Big Data Technology

With the emergence of popular terms such as the Internet of Things and big data, the traditional supply chain has also undergone earth-shaking changes. Visualization, chain network, etc. are all characteristics of digital supply chain. Many companies have benefited from the digital supply chain, but the current digital supply chain also has many problems and challenges. This article also timely proposes several ways to build a digital supply chain.
Adaptive Contrast Enhancement using Fuzzy Logic

Contrast enhancement in digital image processing is application-specific and the measure of the quality of the image is subjective. Hence, the interpretation of an image with good contrast differs from one individual to another. Various contrast enhancement methods have been developed such as contrast stretching, histogram equalization, homomorphic filtering, etc. This paper presents an adaptive contrast enhancement technique using fuzzy logic. Fuzzy logic has been observed to be very effective at managing data that is ambiguous and vague in nature. As contrast can also be considered a vague term, fuzzy logic can be effectively used to amplify the contrast of an image. We have established an adaptive fuzzy inferencing system which determines the pixel value of the output based on the contrast measure of the input image. The contrast measure selected is the standard deviation of the image. The experimental results have been compared with existing methods of contrast enhancement and have been assessed both visually and quantitatively.
Computational Linguistic Analysis of Submitted SEC Information (CLASSI)

Text analysis is growing in research and practice of finance, management, and operations. Word associations offer deep insight at scale into dynamics, strategy, and tactics of industries, and thus automated text processing is of great interest. We report development of a new platform using a Latent Dirichlet Allocation (LDA) topic modeling process to analyze 10-K reports that publicly traded companies submit to the Securities and Exchange Commission (SEC). We describe evaluations of the system’s intrinsic performance and an important external measure, the ability to sort documents into Standard Industrial Classifications (SICs), a widely used measure of industry categories. We discuss potential applications in operations, finance, and management.
Colorization method of high resolution anime sketch with Pix2PixHD

Image colorization is an important field of computer vision. With the increasing resolution of colorized images, people’s requirements for the quality of the coloring effect of pictures have been increasingly improved, and the effects of traditional image colorization methods can not longer resolve with high-resolution colorization problem. This paper proposed a colorization method for high-resolution anime sketch based on conditional generation confrontation network. By using a network model with multi-scale generator and multi-scale discriminator, the mapping relationship between the anime sketch and the corresponding image was learned and optimized in the process of generator and discriminator training. Finally, the trained network model was used to color the anime sketch. Experiment results show that compared with other anime sketch colorization methods, the proposed in this paper can color high resolution anime sketch while maintaining considerable visual effects.
Perceptual intelligence

Perceptual intelligence refers to the ability to interact with the environment through various sensory organs, such as vision, hearing, touch, etc.