Reviewerly/exHarmony huggingface dataset:
Decentralised Renewable Electricity Certificates Using Smart Meters and Blockchain

Recently, the use of renewable energy has been promoted to decarbonise the world. Renewable energy certificates are issued to prove the authenticity of source of renewable energy. However, it is not easy to deal with this system because of security and privacy issues caused in the process amongst stakeholders. We analyse plausible security and privacy issues caused in related ICT systems and then propose a renewable electricity certificate to be issued in a decentralised manner using smart meters and a blockchain.
Security of Input for Authentication in Extended Reality Environments

In this concept paper, we evaluate the security impact of accelerometer data for authentication in extended reality (XR) environments. Currently, there is a lack of authentication mechanisms in VR/XR environments. Most authentication is carried out through PINs and passwords which detracts from the immersive experience and inconveniences the user. Motion-based gesture techniques have recently shown potential in authentication users in VR environments. However, the state-of-the-art works have not considered the issue of VR being a visible activity which would yield gestures used to authenticate vulnerable to mimicry. We demonstrate how subtle changes to a user interface (UI) can increase the complexity and cost of eavesdropping on users in VR environments and propose directions for future research. We call on the industry to acknowledge and design around the unique security challenges of authentication in VR.
The Occurrence Environment and Semantic Function of the Particle ‘poko’: A Construction Grammar Approach

Korean Semantics, 80. This study presents an in-depth analysis of the Korean particle ‘poko’, examining its occurrence environment and semantic function within the framework of Construction Grammar. The particle ‘poko’, as evidenced by corpus examination, is predominantly used in spoken discourse, particularly within scenarios that require the quotation of speaking situations. Its primary semantic function is to indicate the original addressee of the quoted speech. Its versatility, however, extends to a range of diverse constructions, including naming, evaluative, causative, and the ‘napoko ∼rako?’ construction. We conduct a detailed examination of each construction, further investigating the derivational relationships among these constructions. In addition to the synchronic analysis, the study also discusses the grammaticalization of ‘poko’, thereby adding a diachronic dimension to our understanding of its usage.
A study of phonetic realization of backchannels based on the functions

Korean Semantics, 80. Previous studies have shown the functions performed by backchannels and identified their locations from a sentence perspective. In this study, we argued that the form, prosodic location, and prosodic realization patterns of backchannels exhibit more complex variations based on their functions, through an analysis of colloquial corpus. The form, prosodic location and timing, and duration of backchannels were measured and the differences between functions were tested using a corpus of 40 two-person conversation data. As a result, the form of backchannels mainly used varied depending on their functions. In addition, backchannels were most frequently used with the speech overlaps and the duration of backchannels was a significant factor in identifying functions. The realization of backchannel functions is complexly revealed through not only the forms used but also prosodic locations and cues. This study demonstrates the importance of researching backchannel using spoken Korean data.
4 Personalization and user modeling for interaction processes

Personalization in computer-based systems aims at supporting users individually, by tailoring various system characteristics and components according to their respective needs and prerequisites. Traditionally, the emphasis hereby has most often been on either the content provided by the system, the way it is presented to the users or the way how users navigate through the system. However, additionally, the interaction process itself can be in the focus of a personalization approach. By personalized interaction processes, we subsume activities related to either efforts to personalize input on the user’s side (e. g., through an individually tailored choice of input devices or their configuration), or a system’s personalized output to a user (e. g., output modalities tailored to a user’s abilities or preferences). In this chapter, we provide a concise overview of literature on personalized interaction processes and underlying user modeling activities and domains that have been in the focus of related research, and discuss the evolvement of this field throughout the past decades.
SISTEM INFORMASI E-REKRUTMEN BERBASIS WEB PADA PT PHAROS INDONESIA

Human resources are individuals who work productively for an organization such as an institution or company in an effort to achieve organizational goals that act as a driver and have value as assets for the organization so that their capabilities need to be improved and developed. Considering that human resources have a very large contribution to the company in achieving its goals and are an important capital asset for the company, therefore, a web-based e-recruitment information system in the process of recruiting and selecting prospective workers is needed by PT Pharos Indonesia to obtain qualified and competent human resources. &#x0D; The development of this e-recruitment information system uses the Waterfall System Development Life Cycle (SDLC) methodology. The database used by this application uses the MySQL database. The programming languages used are Golang and Javascript with the ReactJS Framework. Web-based e-recruitment information system can improve the recruitment process at PT Pharos Indonesia. Processing prospective employee data becomes easier, faster, and more accurate because prospective employee data is processed by computerization
Virtual Trial Room Simulation for Online Ordering and Alteration of Clothes According to Buyers’ Ergonomics

Online ordering has always been a popular option among youth. It has seen an immense advancement in the midst of pandemic and even after it. Ordering clothes online can be convenient but also a hassle in many instances. It happens especially when the clothes do not fit the buyers. Fitting depends upon the body measurements including the height of the buyer. According to the National Institute of Nutrition (NIN), the average height of Indian women is 5.3 ft., while that of men is 5.8 ft. Clothes are usually manufactured taking into account the average heighted people. While the needs of the petite population are disregarded, presently, the shorter population has to spend extra time and money after receiving online orders to get their clothes altered according to height. This paper proposes how a solution in the VR system can be created such that the shorter population can shop according to their heights. Virtual reality could have a great impact when it comes to online shopping. The study revolves around creating a conceptual model using virtual reality which can be incorporated into any existing shopping website. It will be a trial model of a VR space where people can try clothes from the website and give requests for alteration according to their height. The user can enter the virtual trial room using a VR headset. Then, they need to create their avatars which can be done using haptic suits or image processing for data points. The haptic suit will take body dimensions of the user to create their avatar. It will also allow the users to feel the quality of clothes. The user can use controllers to try on clothes and adjust lengths according to their heights on their avatars. The adjustments will be sent to the online platform for alteration during ordering.
Interactive News Platform for User Perspective Through Design Concept for Interesting Visual Understanding

Globalization and awareness have impacted the masses in a certain way, that information exchange has become an integral part of the societal system in modern days. One very convenient mode of information exchange is in the form of general news. In the wake of social media and technology, the stage for delivering news has drastically broadened and has become diverse. Children being one of the crucial pillars of society should stay aware of their surrounding developments and issues, yet in the present scenario, a gap can be witnessed that children find it challenging to connect toward the current presentation of news in comparison with elders, as children find a lack of entertainment and fun element in the current news presentation system. This paper aims toward the execution of general news for children into news content containing visual motion graphics for an effective and better understanding of the subject matter. The design concept would essentially contain the graphical representation of news materials to generate interest, curiosity, and cognitive retention of the information. Visual motion graphics being a very attractive and exciting element of new media could be effective in the exchange of information with children while adding a fun element to it. The advantages and challenges of the implementation of the design concept are tallied through a survey conducted among children and their guardians in Kokrajhar, Assam, India. The study explores the potential progressive breadth of the design concept to produce an efficient information transfer for kids using visual motion graphics.
Hybrid Methods to Analyze a Skin Tumor Image and Classification

Processing medical images involve the creation of problem-specific strategies for improving raw medical imaging data for targeted visualization objectives and additional research. There are numerous medical issues, some place emphasis on broadly applicable theories, and some concentrate on certain uses. We mainly concentrate on segmenting images and doing multi-spectral analysis. After the image is preprocessed and the tumor area is isolated, a hybrid between two methods, sub-block discrete cosine transform and second-level discrete wavelet transform, is used to transform the image into a frequency domain to analyze the tumor area and calculate the features; features are computed in two ways; the first way is Michelson contrast (calculated after the image is preprocessed), and the second way is first-order statistics that calculated after the sub-block DCT and two-level DWT performed, the output saved as a feature vector after that passes the vector to backpropagation NN. For training and classification, dataset ISIC 2018 was used in the experimental analysis (we use only four cases). ANN was used for classification, and the results show that it is accurate to roughly 88.98% for DWT, and 85.44% for sub-band DCT, the ANN training performance (MSE) after 1000 epochs for first-order statistics of (DWT + DCT + Contrast) is 2.69 * 10–4.
Is Internet Language a Destroyer to Communication?

Internet language is known as the new form of language that has been used on social media by the Internet users. Since the Internet language has been widely used through social media, there is some influence on the users’ behaviour. As a result, the use of the Internet language is feared to undermine the authenticity of the original language. Language is a significantly important communication tool for everyone, and hence, there are many studies on human communication. As the emergence of the Internet is growing fast, language has been affected and caused by the inventions of Internet language which is also known as Internet slang. It is also now widely used by people in their daily communication. However, there are several problems caused by Internet language. For example, people who seldom use the Internet could not understand the Internet language which might cause communication problems, the loss of language authenticity, and generation gap. As the study of Internet language is not broad, a few problems still remain unknown such as the communication habits of Internet language users, the level of understanding of the original language, and how elders are out of touch with contemporary society due to the Internet language. Quantitative research method which is an online survey is used to study the generation Z who were born from 1997 to 2012 and baby boomers who were born from 1955 to 1964. The reason why this research targets these selected samples is to investigate the generation gap between gen Z and baby boomers that the Internet language brings to them. The research is intended to investigate how the Internet language affects human communication habits. This research has found out that the Internet language has actually affected human communication habits, because the Internet language has become a part and parcel of their communication style.
Machine Learning Algorithms for Geriatric Fall Detection with Multiple Datasets

Privacy of data is a significant concern, especially in the healthcare domain; it is paramount to abide by the existing privacy regulations. However, we require large datasets for training the ML/DL models. Fusion of similar or related data from multiple datasets taken from various sources worldwide will therefore be beneficial while retaining the anonymity of the test subjects. The impact of using multiple and different datasets for testing and training is yet to be studied. In contrast, individual datasets have been split randomly for testing and training in multiple research works; using separate datasets and studying the accuracies of ML algorithms is yet to be done. In this paper, we use multiple datasets for testing and different datasets for training, and we have studied the impact of using different datasets. We found that there was a massive drop in accuracy when varied datasets were used for testing and training, especially when the data collection methodology and demographics were different; in real-life scenarios, especially in relation to geriatric fall detection systems, the training data would be collected from much younger volunteers due to the risk factor involved when asking the elderly to fall. So the dataset and the demographics for training will be completely different from the end users. Hence this analysis of using multiple datasets gains immense importance.
Optimize One Max Problem by PSO and CSA

The optimal solution in mathematical concepts, computer science, and finance is to find the best solution out of all possible solutions. The type of optimization problem is determined by whether the variables are continuous or discrete.This study presents a One Max solution that shifts from the notion of optimization to the notion of the optimal strategy. Based on the time dimension difference, the CSA and PSO algorithms have been proposed as more effective in optimization, since the PSO algorithm is the oldest in the optimization field and CSA is modern. Nevertheless, despite being newly configured, the CSA algorithm has proven its effectiveness. Both algorithms must use values that are generated at random. Each cycle has a predetermined range of values for 100, 500, and 1000 cycles, and the values are calculated using the Sigmoid function. They go through 30 cycles with a number of function evaluations of 100,000. The Sigmoid function, which raises values above 0.5–1, is used to display the results for each range of 30 values. The results showed that the CSA algorithm outperformed PSO by 20% in terms of improvement values for each cycle (100, 500, and 1000). The CSA algorithm was selected as the preferred method for improving the One Max problem because of its efficiency and speed. Moreover, it has less dispersion than the PSO algorithm.
Accountable Policy-Based Sanitizable Signature for Medical Data Sharing

With the Internet and cloud computing development, signed electronic medical data can be stored on the cloud server for flexible data sharing. However, the signed medical data contains much private information, and directly sharing the entire medical data may lead to privacy leakage. The sanitizable signatures can solve this problem well. However, in the existing sanitizable signature schemes, few schemes achieve access control to sanitizer while achieving invisibility and unlinkability. In addition, the existing schemes only consider a signer and a single sanitizer situation. If the sanitizer is not online or unwilling to perform the sanitization operation, the data cannot be sanitized in time. The existing methods to achieve the accountability of sanitizer cannot be directly expanded to the situation of multiple sanitizers because the existing methods are less flexible, and the signer is required to regenerate the signature to assign sanitization rights to a new sanitizer. We propose an accountable policy-based invisible and unlinkable sanitizable signature scheme to solve the above problems. This scheme contains a signer and multiple sanitizers and can achieve signer and multiple sanitizer accountability. Specifically, the medical data provider can specify the access policy when signing the data. Only those who meet the access policy can sanitize the signed data and generate valid signatures. When there is a dispute, not only can the medical data provider generate a proof tag, but all medical data sanitizers can also generate proof tags to identify the actual generator of the data-signature pair. In addition, this paper proposes an electronic medical data-sharing scheme based on the above-mentioned sanitizable signature. Finally, the security analysis and performance analysis show that the scheme of this paper is feasible.
Research on target recognition of UAV remote sensing image based on improved mask R-CNN model

To solve the problems of low visible edge, low average gradient, low value signal-to-noise ratio, low overlap, high loss rate of image feature details and poor recognition quality existing in traditional methods, a target recognition method of UAV remote sensing image based on improved mask R-CNN model is proposed. Firstly, multi-scale Retinex and dark channel are used to process fog in UAV remote sensing images. Secondly, the mask R-CNN model is improved through pyramid balance strategy and bypass connection. Finally, the demobilised image is input into the improved model to realise remote sensing image target recognition. The experimental results show that the highest values of visible edge and average gradient of the method reach 0.988 and 992, the highest value of PSNR reaches 67.47, the highest value of overlap reaches 98.7%, and the loss rate of detail is below 1.2%, the recognition quality is high.
The Problem of Images’ Classification: Neural Networks

The article discusses the employment of an artificial neural network for the problem of image classification. Based on the compiled dataset, a convolutional neural network model was implemented and trained. An application for images classification was created. The practical value of the developed application allows an efficient use of a smartphone camera’s storage facilities. The article presents a detailed methodology of the application’s development.
PERANCANGAN APLIKASI TATA KELOLA KEUANGAN SALON YINHOA BERBASIS WEB

Prior to the creation of this web-based financial management application, Salon Yinhoa ​​carried out all financial processes using the traditional method with on-the-spot transaction processes and recording was done manually using an excel file. As customers increase, recording transactions is considered to be quite time-consuming and a solution is needed to simplify financial management. Therefore, it is necessary to design a web-based financial management application for Salon Yinhao as a database for financial management using the SDLC-waterfall method. The final result is that the web-based application is used to facilitate financial management at Salon Yinhoa.
An investigation of media reports of digital surveillance within the first year of the COVID-19 pandemic

Introduction The COVID-19 pandemic prompted a surge in digital public health surveillance worldwide, with limited opportunities to consider the effectiveness or impact of digital surveillance. The news media shape public understanding of topics of importance, contributing to our perception of priority issues. This study investigated news media reports published during the first year of the pandemic to understand how the use and consequences of digital surveillance technologies were reported on. Methods A media content analysis of 34 high- to low-income countries was completed. The terms “COVID-19,” “surveillance,” “technologies,” and “public health” were used to retrieve and inductively code media reports. Results Of the 1,001 reports, most were web-based or newspaper sources on the development and deployment of technologies directed at contact tracing, enforcing quarantine, predicting disease spread, and allocating resources. Technology types included mobile apps, wearable devices, “smart” thermometers, GPS/Bluetooth, facial recognition, and security cameras. Repurposed data from social media, travel cards/passports, and consumer purchases also provided surveillance insight. Media reports focused on factors impacting surveillance success (public participation and data validity) and the emerging consequences of digital surveillance on human rights, function creep, data security, and trust. Discussion Diverse digital technologies were developed and used for public health surveillance during the first year of the COVID-19 pandemic. The use of these technologies and witnessed or anticipated consequences were reported by a variety of media sources worldwide. The news media are an important public health information resource, as media outlets contribute to directing public understanding and shaping priority public health surveillance issues. Our findings raise important questions around how journalists decide which aspects of public health crises to report on and how these issues are discussed.
Image charges from boundary value problems

The examples usually solved by means of the method of images are revisited solving directly the Laplace equation. We also give a simple derivation of the axially symmetric solutions of the Laplace equation in spherical coordinates and of the translationally symmetric solutions of the Laplace equation in cylindrical coordinates.
PENERAPAN ARTIFICIAL NEURAL NETWORK UNTUK MENDUGA PROGRAM STUDI DI UNIVERSITAS UDAYANA BERDASARKAN NILAI RAPOR

This research aims to develop an artificial neural network-based estimation system to predict the suitable study program at Udayana University for high school students in Denpasar City based on their report cards. The research is divided into four stages: system overview, user interface design, implementation of the artificial neural network in the system, and system testing. System testing results on report card data for science and social science classes demonstrate that the developed model has good accuracy with an error rate below 7%.