Reviewerly/exHarmony huggingface dataset:
Mundane Food Photography

This article investigates mundane photo taking practices with personal mobile devices in the co-presence of others, as well as “divergent” self-initiated smartphone use, thereby exploring the impact of everyday technologies on social interaction. Utilizing multimodal conversation analysis, we examined sequences in which young adults take pictures of food and drinks in restaurants and cafés. Although everyday interactions are abundant in opportunities for accomplishing food photography as a side activity, our data show that taking pictures is also often prioritized over other activities. Through a detailed sequential analysis of video recordings and dynamic screen captures of mobile devices, we illustrate how photographers orient to the momentary opportunities for and relevance of photo taking, that is, how they systematically organize their photographing with respect to the ongoing social encounter and the (projected) changes in the material environment. We investigate how the participants multimodally negotiate the “mainness” and “sideness” (Mondada, 2014) of situated food photography and describe some particular features of participants’ conduct in moments of mundane multiactivity.
Similarity and Dimensional Analysis

This chapter briefly introduces the application of similarity theory and dimensional analysis in fluid mechanics. The concept of flow similarity is discussed at first to give the readers a brief idea what similarity means. Then some important dimensionless number is listed and discussed, which includes Reynolds number, Mach number, Strouhal number, Froude number, Euler number and Weber number. Next, the governing equations are transformed to a dimensionless form to shows how the dimensionless numbers act in the equations. In the end, some flow examples are provided to show the role of the dimensionless numbers.
The Grammar of Groups and Phrases in Korean

This chapter describes the grammar of groups and phrases in Korean – covering nominal groups, verbal groups, adverbial groups and co-verbal phrases. The function structure of each unit is introduced and their meaning potential is formalised in system networks. The realisation of systems by function structures and their realisation in turn by words and morphemes or by embedded groups or clauses is outlined. Korean morphology is brought into the picture to clarify the realisation of choices for meaning at group/phrase rank.
Comparing and Contrasting Gold and Bitcoin Standards

Chapter 6. As a future monetary standard, should fiat standards collapse, gold would exhibit greater purchasing-power stability than Bitcoin. Gold and Bitcoin supply and demand diagrams from earlier chapters, brought side-by-side, illustrate that Bitcoin’s purchasing power is more volatile in the short run and especially in the long run. Legal obstacles facing gold and Bitcoin as media of exchange are similar. Bitcoin’s main advantage is its greater resistant to government censorship, but the difference is smaller than sometimes claimed. A determined government can drive Bitcoin underground to the point where it is unlikely to serve as a common currency. The policy conclusion is not a blueprint for top-down choice among monetary standards, but a plea to let potential monies compete openly and freely on a legally level playing field.
A Study on the Interrelationship Among Import Volume, Export Volume and the Effects of Korean Wave: Focusing on BTS

Purpose – This study is an empirical study on the relationship among export volume and import volume, with BTS internet search trends indexed. Design/Methodology/Approach – In this study, we used 111 monthly data sets on BTS internet search trends, the export volume, and the import volume from April 30, 2013 to Jun 30, 2022. We try to analyze the mutual influence and causality among BTS internet search trends, the export volume, and the import volume. We seek to analyze the extent of any cross-influence. We employ a variance decomposition function based on a VAR model, as well as impulse response after a cointegration test and unit root test. Findings – The important results of this study are summarized as follows. First, there is at least one cointegration among the first differential data of BTS internet search trends, export volume, and import volume. Secondly, import volume does have Granger causality with BTS internet search trends. The export and import volume show Granger causality. BTS internet search trends and the export volume have Granger causality with BTS internet search trends and export volume. Research Implications – This study differs in that it uses BTS internet search trends and the Korean wave. It has limitations in that the study period is short and the study sample is limited.
Analysis of the multi-dimensional transformation of the perspective of new media image artworks using the image stabilization system

New media image art, an essential branch of new media art, is characterized by the primary form of expression being an image and adopting various new means of production and communication. As an emerging art form, new media art has extensive connections to various fields due to the complexity of media and diversity of expression. New media image art has been shaped by the diverse expressions enabled by the development of various production technologies, among which is the Image Stabilization System (ISS). The ISS is a series of technical systems based on a camera stabilization device, thus integrated control of camera motion attitude to complete the camera motion shooting. Recently, the ISS has gained popularity in the film and television industry and is widely used in various video production processes. This article takes the multi-dimensional transformation of the perspective of new media image artworks, using the ISS, as the research subjects. The author briefly introduces some ISSs used in new media image art, analyzes the multi-dimensional transformation of shooting perspectives (the changes in the degree of freedom, immersion and interactivity) by the application of ISS through production examples, and explores the prospect of their application in new media image art.
An Analysis of Korea-UK FTA Improvement Negotiations and the New Trade Environment

Purpose – The aim of this analysis is to provide implications for trade practice by analyzing FTA progress in the digital economy and trade field with IPEF through FTA improvement negotiations between Korea and the UK, and an analysis of the new trade environment. Design/Methodology/Approach – The annual export/import growth rate (year-on-year) before and after the Korea-UK FTA was concluded and forecasts for 2022 and 2023 were reviewed. This data from 2000 to 2021 are based on the Economic Statistical System of the Bank of Korea. It recorded 33.20% in 2021, the second highest growth rate since the 2000s, after recording 36.95% in 2004. It was estimated through the model of ARIMA (1, 1, 0) in the case of 2022 and 2023. After the Korea-UK FTA was concluded, it was found that the trade volume of Korea-UK combined exports and imports increased. Findings – In the future, it is expected that joint cooperation and R&amp;D investment in high-tech and hightech industries will be more actively developed through improvement negotiations in the fields of SCM, digital economy, and trade. Research Implications – The US is currently emphasizing US production of optical fibers, semiconductors, and electric vehicles as well as key parts in relation to the global supply chain. Therefore, the Korea-UK FTA improvement negotiation and framework require joint cooperation and R&amp;D investment in the reorganization of the US global supply chain in cutting-edge industries, including US semiconductors, science law, and inflation reduction laws.
Sequential Path Planning Considering Collision Avoidance in Multi-robots

Multi-robot path planning involves establishing collision-free paths for multiple robots such that each robot reaches its goal without colliding with other robots. The possibility of collision between robots is high in dynamic environments where robots with different speeds move simultaneously. For a group of robots moving at different speeds, a path-planning method was proposed for minimizing the time cost while avoiding collisions between obstacles and robots. In the proposed method, the path is sequentially planned according to the predefined priorities between robots so that each robot can plan the path in a distributed manner. The performance of the proposed algorithm was compared with existing algorithms, namely hierarchical cooperative A* and conflict-based search, and its performance in various real-world scenarios was verified using a three-dimensional robot simulator.
A Blockchain Based Access Control System for Internet of Things (IoT) Networks

The rapid development and widespread application of IoT network systems, network security, in particular access control and data privacy, have become critical. Blockchain technology provides features such as decentralization, high reliability, and tampering prevention, which are advantages in solving the challenges of access control: audit ability, resource consumption, scalability, central authority, and trust. In this paper, we propose an ABAC access control system that can be applied to IoT networks. The proposed system utilizes Ethereum
N-bit Finite Fields Multiplier Design and Implementation Using 1-Bit Left Shift Operations by N-1 Times

In this paper, we propose a finite fields GF(2n) multiplier algorithm by repeating the 2 multiplication algorithm n-1 times with a combination circuit composed only of AND and XOR gates. The proposed algorithm can be configured with fewer gates than the existing finite fields multiplication algorithm, and is expected to be easy to implement in hardware because it is very regular. Finally, the time to perform finite fields multiplication is also expected to be faster than other multiplication algorithms due to the smaller number of gates.
Least Square Generative Adversarial Network Applying PCA to Latent Space

Image generation is an important area of artificial intelligence that involves creating new images from existing dataset. It involves learning the distribution of target images from randomly generated vectors. Like other deep learning models, the image generation model requires a vast refined data set to produce high-quality results. When there is little data, there is a problem that the diversity and quality of generated images are compromised. In this paper, we propose a new generative model that applies PCA to the generator of the least square error adversarial generative network that, in turn, generates high-quality images even with a small data set. Unlike the existing models that generate target data from randomly generated noise, in the proposed method the direction of the image to be generated is guided by extracting the features of the target data through PCA. The results section shows the superior performance of the proposed model against a different number of images in dataset.
Airlight Estimation of a Single Hazy Image Using Patch-wise Bright Pixels (PBP)

Image haze removal is essential for preprocessing in computer vision applications, as outdoor images taken in adverse weather conditions such as fog or snow have poor visibility. This problem has been extensively studied in the literature. Unlike transmission estimation, which has been widely studied, relatively few studies have been conducted on airlight estimation. In this paper, novel airlight estimation algorithm using Patch-wise Bright Pixels and superpixel based airlight area candidate score is proposed. The performance of the proposed method is evaluated by using ground truth data sets. Experimental results show that the proposed method outperforms the state-of-the-art airlight estimation method both visually and numerically.
Development of Marker-based Interaction Synchronization and Mixed Reality Content for Collaboration

As non-face-to-face services spread in the post-COVID-19, expanded reality technologies such as mixed reality are attracting attention in various fields. In mixed reality, each user forms a unique coordinate system with the device location at the time the application is executed as the origin. The positions of virtual objects thus cannot be shared or synchronized by using absolute coordinates. In particular, for a co-located collaboration, virtual objects augmented on each user’s device should exist exactly at the same spot in the real world, which means the objects rendered on each user’s display should be aligned in the same position and rotation in the real world as well as synchronized. For this, we propose a method for creating a standard coordinate system for a collaborative workspace and synchronizing interactions. All users create a standard coordinate system at the location of a marker, and then register virtual objects and avatars as its sub-objects. Afterwards interactions in the collaborative space are synchronized among users by exchange of local position relative to the standard coordinate system. We developed the mixed reality application in which multiple users collaborate for 3D-drone assembly, and verified our proposal by showing that it synchronizes interactions in real-time successfully.
Similar Font Recommendation Technique Based on Hangul Stroke Element Using CNN-based Image Embedding Model

Font design has emerged to become more competitive in the "Content Smog". In this Study, we propose a technique that identifies fonts and automatically recommends the similar, using the extracted "Stroke element" from previous studies. First, we implement an image embedding model that extracts features of an image in vector form through CNN(Convolution Neural Network). we analyze the similarity between fonts through ‘multidimensional cosine similarity calculations’ on the basis of each extracted font’s feature vector through the model. From the final analysis, the fonts of a particular character could be identified and similar fonts are automatically recommended. Since Font Recommendation is subjective, we establish the ‘Ground-Truth’ through survey. Comparing with the ground-truth, a high result close to 1(0.938). Plus, compared with character-based recommendations to verify whether the stroke element-based technique is a significant method, the results were lower(0.893). Therefore, it was verified that the technique implemented through this paper is a system that automatically recommends fonts of similar shapes that meet the subjective criteria.
Automatic Text Classification Model Based on Machine Learning

The artificial neural network is composed of RBF algorithm, multi-layer parallel model and other parts.Its working principle is to classify the input image through layer by layer training, and then develop and determine the attributes of each neuron with similar features.This paper studies them based on Bayesian classifier, a common method in machine learning.First of all, before text recognition, we need to select the sample library and data type, and design the parameters according to the requirements to form an efficient automatic text classification.Then, according to the functional modules required by the specific model, select the appropriate language and compile and generate program code to realize the whole process, and carry out simulation tests on the functions of the model.The test results show that this test has prepared different quantities of simple words, short sentences, long articles, professional terms and colloquial expressions for classification tests.The classification accuracy of this model is as high as 90%, the error rate is low, and the classification time is fast, This shows that the model meets the needs of users.
Research on the Key Problems of Credit Bank System Construction in Vocational Education

The construction of credit bank system in vocational education is a systematic and complex work, which requires us to solve three key problems: defining the operating mechanism, improving the organizational structure, and building a supporting platform. Only by solving the three problems and removing the barriers at the ideological, organizational and technical levels can we ensure the efficient implementation of the credit bank system in vocational education.
Vision enhancement via virtual diffraction and coherent detection (VEViD): a physics-inspired low-light enhancement algorithm

The task of low-light image enhancement, in which the quality of images captured in low illumination conditions is enhanced, has high importance within industrial, security and scientific applications. In this paper we discuss Vision Enhancement via Virtual diffraction and coherent Detection (VEViD), a novel physics-inspired algorithm in which we map the physics of diffractive optics and phase detection to that of digital image processing. By applying virtual diffraction, we create a nontrivial spatial phase profile that encodes an enhanced version of the incoming image, a version in which the image’s previously unseen low-light details are made accessible to human and computer perception.
Nanodevices and nanomachines powered by photonic heat engines

We exploit photonic heat engines, which involve optical cooling and heating of matter, for the development of a new class of optical nanodevices and nanomachines. Working principles and applications of these devices and machines will be discussed.
Scaling laws for deep neural networks

Recent work in deep learning has underscored the importance of measuring and understanding trends in model performance as a function of basic variables, such as the size of the training dataset, the number of model parameters, and the amount of compute. These trends often, though not always, are governed by power-law scaling. I will survey some of the existing empirical evidence for these so-called “scaling laws” and then discuss regimes where we have a theoretical understanding underlying these trends, based on joint work with collaborators. I will close by discussing connections to optical implementations of deep neural networks.
How a Bitcoin Standard Works

Chapter 5. Bitcoin emerged in 2009 from a community of libertarian cryptographers who sought an alternative payment system free from fiat inflation and from government payment surveillance and censorship. Today it provides an alternative payment rail that circumvents central banks. Bitcoin serves as a medium of exchange in some transactions, but not yet as a commonly accepted medium of exchange. The Bitcoin source code keeps the number of Bitcoin in circulation growing, at an ever-slowing rate, along a programmed quantity path. Basic monetary theory shows that this supply mechanism has pros and cons: It avoids money supply shocks, but it rules out any supply response to variations in demand, making the purchasing power of Bitcoin more volatile than that of gold or (relatively well-managed) fiat, which limits the attractiveness of holding Bitcoin as a medium of exchange. The costs of the Bitcoin industry are borne by its users, not by third parties, to the same extent as those of any energy-using private industry. The non-zero chance of its serving as a future global money means that Bitcoin has a fundamental value. It does not inherently rest on an unsustainable chain-letter or “bigger fool” process.
ANAFORA I UPOTREBA ČLANA U ITALIJANSKOM JEZIKU

Anaphora represents a complex linguistic phenomenon that enables the interconnection of textual information. It consists of an antecedent and anaphoric expression. The antecedent introduces an extratextual referent that is grammatically accompanied by indefinite article. In some cases the use of definite article is correct but such choices are usually based on pragmatic factors. The anaphoric expression is always introduced by the definite article, because the defi- nite article is the signal that the textual cohesion has taken place through the relation between the elements of the anaphora. The main goal of this paper is to investigate the types of bonding between the anteced- ent and the anaphoric expression. Depending on the prevalent type of bond we singled out four types of anaphora in our corpora based on six Italian novels: direct, indirect, associative anaphora and anaphoric encapsulator. Our research shows that the first two types are characterized by coreference, while the other two are not. This implies that the direct anaphora is based on lexical bonding, whereas the indirect is based on semantic bonding of various lexical substitutes such as equivalent expressions, hyponyms, hyperonyms, synonyms or diminutives. The associative anaphora requires strong logical and associative bond between the antecedent and the anaphoric expres- sion in order for cohesion to happen. The anaphoric encapsulator presents a single word that can summarize a whole segment of the previous text. We have concluded that all four types of anaphora successfully create textual cohesion and the reader is equipped to connect the antecedent to the anaphoric expression, regardless of whether there is a referential identity within the anaphora. The goal of this article is to point out the importance of pragmatic factors that enable this kind of referential recognition. They include the encyclopedia knowledge, the common knowledge, the knowing of the context and the co-text, the discourse universe and the cooperative principle that depends on the reader’s willingness to accept the referential connections within anaphoric elements.
MnemoSys: A Conditional Probability Estimation Protocol for Blockchain Audited Reputation Management

Reputation systems have been one method of solving the unique challenges that face distributed networks of independent operators. Fundamentally, historical performance must be considered in a way that attempts to predict future behav-ior, optimize present functionality, and provide some measure of immutable recording. In this paper, a three-part system, MnemoSys, is proposed to solve this diverse set of problems. First, historical performance is dynamically weighted and scored using geometrically expanding time windows. Second, a quorum is abstracted as a restricted Boltzmann machine to produce a conditional probability estimate of log-normal likelihood of good-faith behavior. Third, all rewards and punishments are recorded on an immutable, decentralized ledger. Our experimentation shows that when applied iteratively to an entire network, consistently under-performing nodes are removed, network stability is maintained even with high percentages of simulated error, and global network parameters are optimized in the long-term.
Multimodal intention understanding method based on NHMM

This paper proposes a multimodal intention understanding method based on NHMM. Due to the declining expression ability of the elderly, single-mode input during human-computer interaction may reduce the accuracy of robot intention understanding and cannot meet the requirements of helping the elderly. Therefore, in the aspect of intention understanding, this paper uses multi-modal input of voice, gesture and posture to obtain the user’s multi-dimensional information as much as possible. Each modal information is processed to obtain three intention sets, and then fused to obtain the fused intention set, By combining the improvement of the core formula of hidden Markov model (HMM) with Bayes, the intention with the highest probability in the fusion intention set is calculated as the result of intention understanding. The results show that the accuracy of this method is 97.7% in the state of user natural interaction, and compared with the other four intention understanding methods, this method is more effective for intention extraction under fuzzy input.