Reviewerly/exHarmony huggingface dataset:
Effective Density-Based Concept Drift Detection for Evolving Data Streams

Concept drift is a common phenomenon appearing in evolving data streams of a wide range of applications including credit card fraud protection, weather forecast, network monitoring, etc. For online data streams it is difficult to determine a proper size of the sliding window for detection of concept drift, making the existing dataset-distance based algorithms not effective in application. In this paper, we propose a novel framework of Density-based Concept Drift Detection (DCDD) for detecting concept drifts in data streams using density-based clustering on a variable-size sliding window through dynamically adjusting the size of the sliding window. Our DCDD uses XGBoost (eXtreme Gradient Boosting) to predict the amount of data in the same concept and adjusts the size of the sliding window dynamically based on the collected information about concept drifting. To detect concept drift between two datasets, DCDD calculates the distance between the datasets using a new detection formula that considers the attribute of time as the weight for old data and calculates the distance between the data in the current sliding window and all data in the current concept rather than between two adjacent windows as used in the exiting work DCDA [2]. This yields an observable improvement on the detection accuracy and a significant improvement on the detection efficiency. Experimental results have shown that our framework detects the concept drift more accurately and efficiently than the existing work.
Recognition-Independent Handwritten Text Alignment Using Lightweight Recurrent Neural Network

Legibility refers to the ease with which handwritten content can be read and understood accurately. However, existing approaches to handwriting beautification either rely on the result of handwriting recognition and accumulate errors from the recognition system or do not address the alignment problem and are difficult to generalize to other languages. This paper presents a novel approach to improve handwriting legibility by straightening the written content. It utilizes a recurrent neural network that operates without the need for recognition, supports connected writing, and accommodates various writing styles. The results obtained with this method demonstrate significant improvements in handwriting alignment. Moreover, a single neural network model can effectively cater to multiple languages within the same writing system.
Developing a Realistic VR Interface to Recreate a Full-body Immersive Fire Scene Experience

This paper describes a research project on the development of a VR fire training system. We aimed to create a multi-sensory experience that simulates a real-world fire scene. To achieve this, we developed a motion simulator to provide physical stimulation, haptic firefighting nozzles to provide a realistic sense of tool use, and a firefighting suit that can transmit the hot/cold sensations of VR content to the entire body. We evaluated firefighter and public satisfaction with the VR firefighting experience, and outlined future research challenges to improve usability in the field.
An Examination of Text Shaking Correction Methods for AR Walking

One problem with walking in AR is less readability of displayed text. Head shaking causes the displayed text to shake. The screen coordinate system(SCS) or world coordinate system(WCS) is used for displaying text with different effective distances. We propose methods to correct text shaking by combining SCS and WCS.
Room to Room Mapping: Seamlessly Connecting Different Rooms

In this study, we propose a projection mapping technique designed to connect rooms in disparate locations virtually, creating a continuous, immersive space.
Landmark Guided 4D Facial Expression Generation

In this paper, we proposed a generative model that learns to synthesize the 4D facial expression with the neutral landmark. Existing works mainly focus on the generation of sequences guided by expression labels, speech, etc, while they are not robust to the change of different identities. Our LM-4DGAN utilizes neutral landmarks to guide the facial expression generation while adding an identity discriminator and a landmark autoencoder to the basic WGAN for achieving better identity robustness. Furthermore, we add a cross-attention mechanism to the existing displacement decoder which is suitable for the given identity.
Rule-of-Thirds or Centered? A study in preference in photo composition

The Rule of Thirds is a well known heuristic in photo composition. The professional photography community both uses it and derides it. We report on an experiment to test the validity of the Rule of Thirds in the simplest case: composition of a single object. Our results show that our participants overwhelmingly preferred a centered object in the image to one positioned according to the Rule of Thirds. We speculate why this is so and point to other research that addresses how we can take advantage of this “salient centeredness”.
asmVR: VR-Based ASMR Experience with Multimodal Triggers for Mental Well-Being

Individuals are besieged by anxiety and stress throughout the world. Solutions to improve mental well-being can vary, and Autonomous Sensory Meridian Response (ASMR) is one potential method that has proven to be able to reduce stress. To that end, we introduce asmVR, a novel approach to enhancing ASMR experiences using multi-modal triggers. Combining online and offline modes, asmVR enhances ASMR tingling, offering immersive VR environments and remote ASMRist embodiments. Initial user testing shows tingles enhance and stress relief potential, along with new possibilities for VR in psychological therapy.
NinjaHeads: Gaze-Oriented Parallel View System for Asynchronous Tasks

Virtual parallel experience enables a person in Virtual Reality (VR) to receive multiple and concurrent perspectives. It also enables the person to synchronously participate in activities or solve multiple tasks at once. This research focuses on utilizing parallel views for asynchronous tasks by providing the user with intuitively extended view perspectives driven by gaze. In this demonstration, we present NinjaHeads, a parallel view system that generates four additional perspectives "parallel views", based on the user’s gaze point. We introduce a technique where a user can manipulate parallel views and their behaviors through eye, head, and hand movements. This allows the user to concurrently examine an object or a point of interest from different perspectives, as if the user has more than a pair of eyes.
Kristine Is Not Well

Memes vs. algorithm in metaverse inspired by real rebellion stories. Kristine is Not Well is a 20-minute animated VR social media simulation that highlights the resistance of online activists against algorithmic surveillance and censorship.
MiniGI: Guerilla Mappings in Miniature

We present Secret Mapping, an interactive tabletop installation coupled with a handheld Augmented Reality (AR) visualisation. The installation showcases five selected locations which are the human-scale twins of actual, real-word exhibits all located throughout former Yugoslavia. AR visualisation illuminates these miniature 3D replicas and encompasses them with an extended version of the archived visuals created by the artists, specifically to each spot. The installation invites visitors to join the artists on their trip and reenact their journey with an collaborative tabletop interface, while offering the possibility for backwards or forward exploration.
Transcale: Embodiment Transition Toward Multi-Verse Exploration

Transcale is a VR experience where the users can change the body scale smoothly while walking. By continuously modifying their perceived body scale, this interaction method provides the users to explore the virtual world from various points of view from a dwarf to a giant.
Exploring Storytelling Approach with Service Design to Create Empathetic Experiences for Adolescents Living with HIV: A Case Study

In India, a significant number of children live with HIV. Due to a lack of awareness and social stigma, they do not make timely and responsible life decisions around intimacy and HIV status disclosure. In this paper, we share our experience of collaborating with Prayas Health Group (PHG), a prominent Non-Government Organization in Maharashtra (India) that is dedicated to enriching the lives of HIV patients. We used Service Design methods to create a solution that disseminates essential information and enables Adolescents Living with HIV (ALHIV) to make informed life decisions. The solution is an interactive story media where adolescents make decisions around in-design encounters that parallel with possible real-life encounters. As a result, they learn more about the subject and its implications, leading to improved real-life decision-making. This paper demonstrates the orchestration of human and technology touchpoints through multiple dynamic and choice-based scenarios.
Mapping Facts to Concrete Game Elements for Generation Purposes: A Conceptual Approach

Designing serious games or serious game activities requires mapping the educational elements and the game elements. This mapping is mainly addressed from a high-level game design perspective. Moreover, low-level mapping methods are generally domain-specific. Our aim is to address this problem, at an algorithmic level, in the context of activity generation (i.e., automatic creation of activities) for declarative knowledge training. This paper presents a generic modelling approach of questioned facts and gameplays, and an algorithm for the automatic and domain-independent generation of various gameplays for training purposes. The approach has been applied to multiplication tables training.
Browser-Based Game Design for Cognitive Effort Aware Quality of Experience Evaluation

Cognitive effort plays a crucial part in our multimedia consumption experience as it affects attention. However, traditional research in quality of experience (QoE) relies on the subjective ratings of a multimedia consumption experience under a lab-based environment without distractions. To make the collected QoE ratings closer to realistic usage scenarios we designed a browser-based game as an adapted QoE subjective test that can incorporate and quantify cognitive effort using a dual-task paradigm. Our pilot study results show that our proposed browser-based game is a viable protocol that can control for, and reflect, the cognitive effort via selected self-reported measures given an appropriate load range. Future work will further standardise and simplify the game protocol for robustness, repeatability and test duration.
Analysis of regularized least squares ranking with centered reproducing kernel

The existing results of the regularized least squares ranking (RLSR) algorithm are mainly related to the reproducing kernels. In this paper, we go beyond this limitation by investigating the convergence rates of ranking with centered reproducing kernel (CRK). We develop a new error analysis framework by means of CRK and integral operator. The result shows that the convergence rate of RLSR is still optimal as those in the traditional analysis framework.
Emirati economic cohesion could gradually increase

Significance On November 7-8, senior Emirati officials gathered in Abu Dhabi for an annual meeting focusing on diversifying the economy, chiefly away from reliance on Abu Dhabi's oil, an imperative made more challenging by accelerating global decarbonisation trends. Impacts Supply chain and workforce localisation will guide economic development plans. Dubai and Abu Dhabi will retain separate stock markets but collaborate to improve the depth and liquidity of bourses. A new federal drugs regulator will support investment in pharmaceuticals, a key target sector.
Blockchain and Flutter-Based Quiz Mobile DApp Toward Decentralized Continuous Assessment

Education being an indispensable to our lives, efforts are continuously being made to strengthen it. Assessment lies at the core of any given educational program or module, irrespective of modes (online, offline, blended) and format (short time, part time, or full time). Among the various types of assessment, continuous assessment has been widely adopted. Quizzes are one of the important and common ways to conduct continuous assessment. However, due to the existing processes and involved centralized technologies, there are numerous challenges such as non-transparent and insecure conduction of assessment, non-verifiability of assessment process and computation of final grades from these assessments, and trusted sharing of assessment (or learning) logs along with final grades. Blockchain and smart contracts have emerged as potential technologies which can be leveraged to overcome these challenges. Thus, this paper proposes a blockchain-based architecture for conduction of online quiz. In particular, the paper aims to design and develop secure, transparent, and verifiable, Blockchain and Flutter-based Quiz Mobile-Decentralized Application (BFQM-DApp). To the best of our knowledge, this is first work which attempts to develop a blockchain and flutter-based mobile DApp for online quiz.
MetaFund: Blockchain Based Crowdfunding Platform

An innovative and common way to raise funds for tasks is to crowdfund or crowdsource. People can use the acquired fundings to create projects that contribute to the betterment of the society. Current crowdfunding platforms charge a significant fee for every event or project that is listed. The fee charged is sometimes a fixed amount or a percentage of the total donation required. Centralized crowdfunding platforms do not bother to protect intellectual property either. It is possible that the start-up idea of a smaller group could get stolen by a bigger company. This creates pressure on smaller groups to meet deadlines and spend the donation money to patent their projects. Our platform will be a one-stop solution for all funding requirements such as start-ups, medical needs, charities, and so on. It will be secure, transparent, and easy-to-use.
A Blockchain Model to Uplift Solvency by Creating Credit Proof

A credit score represents an individual’s financial ability and stability which is calculated upon various factors like financial behavior of transacting, re-paying loan on time, spending in a healthy manner, etc. Approval for loans, credit score is strictly restricted for a set of people who have a strong economic support and perfect access to every transaction. But in a region with a major population that doesn’t even have access to digital transactions, this is a way to make them financially stable. By collecting various information about their financial history and setting up an application that can track financial behavior and store every transaction possible in blockchain, we can solve this problem. Blockchain-based ledger application is used to calculate credit score for non-registered people who cannot access credit score until now. This is more secure to store every transaction made by the user and analyze the behavior to generate a credit score. So that they can show it as proof for taking credit for their personal development and uses. Anyone who has an ability to take credit must not be wasted, because when there is a healthy flow of money, the healthier would be the country’s economy.
Protecting the Privacy of IoMT-Based Health Records Using Blockchain Technology

Internet of medical things (IoMT) has become one of the revolutionary technology nowadays due to wide spread use of IoT in healthcare applications. IoMT improves the human–machine interaction enhancing the instantaneous monitoring of patient’s health and also involves patients in making decisions. So, the current medical devices have to be transformed into IoMT-based medical devices to collect patient information instantaneously. The patient’s health-related information can be observed from remote location without any need to go to hospital, and this data can be processed and is sent to mediators for further use. So, we are in need of technology that secures the confidentiality of the health information of patients. Blockchain is one such technology that helps in securing privacy of patient’s health-related data. Blockchain technique uses a sequence of blocks comprising the block ID, previous block ID, and the transactions. The preceding block ID can be used to maintain a link between subsequent blocks. These links continue until the first block is reached. This ID contains hash in blocks, and this hash is appended to subsequent blocks in chain. Any modifications to the patient information in a block will change the subsequent blocks in the chain also. So, changes to the data made by a hacker will become impossible. It uses public key cryptography for performing transactions between nodes. So, use of such type of cryptographic hash technique and chain formation for the blocks guarantees the security and privacy of the patient’s health information or records.
Sentimental Analysis for Social Media Topic Analysis Using Multi-tweet Sequential Summarization

The rising of online media has delivered gigantic interest among Internet customers today. Data from these long reach relational correspondence regions can be used for different purposes, like assumption, promoting or assessment examination. Twitter is a comprehensively used online media site page for posting comments through short circumstances with. The enormous quantities of tweets got every year could be presented to notion examination. Nevertheless, managing an especially huge proportion of unorganized data is a dull work to take up. The analytics tools and models currently available on the market are not satisfactory for managing huge amounts of data. Therefore, we have used Hadoop for intelligent evaluation and bounding of huge data. In this proposed work, we have performed an evaluation of user feedback in a Hadoop environment.
The Effect of Fly Swatter Game Toward Students’ Vocabulary Mastery

Vocabulary mastery is a crucial foundation for elementary students studying any language, including English. The typical problems that cause students to lack vocabulary are that they easily become bored when the teacher explains things, that they believe acquiring language only entails understanding its meaning, and that they exclusively acquire vocabulary from their textbooks. On the other hand, many studies show that using games can improve vocabulary mastery, but most studies on this teaching method are not conducted with elementary students, especially considering that previously, English was not a compulsory subject in the elementary school curriculum as far as the Indonesian EFL context is concerned. To fill this gap, this study examines whether the use of this method has an impact on the vocabulary mastery of elementary students. The study was an-experiment study involving 26 students from a state elementary school in Tabanan Regency, Bali. Using descriptive and inferential (paired t-test) statistics, this study concluded that the use of the fly swatter game had a significant effect on the students' vocabulary mastery which was indicated by a significant increase in student scores after being given the teaching treatment using the fly swatter game. Regarding this result, it is suggested that elementary school teachers consider using the fly swatter game when teaching vocabulary to their students.
Artificial Intelligence Tools in Higher Education Students Usage Analysis – Case Study: Sampoerna University

The potential application of AI in education has become an area captivating the younger generation. Among higher education students, AI tools support academic activities by providing students with personalized learning experiences that digitize each student's needs and abilities. This research aims to determine the adoption of AI tools in academic areas, specifically at Sampoerna University. This research contributes to the socialization of the use of AI tools to support academics in a good and correct way. This research used a combination of quantitative and qualitative surveys as primary data. Results show that using AI tools has become common among Sampoerna University students and has gained importance in supporting their academic needs. 50% of respondents used the AI tools in less than six months, and the most used AI tool was for grammar checking. Tablet device was the least used by the students to use the AI tools, with only 6.09%.
The Hyperledger fabric as a Blockchain framework preserves the security of electronic health records

The Hyperledger Fabric (HF) framework is widely studied for securing electronic health records (EHRs) in the healthcare sector. Despite the various cross-domain blockchain technology (BCT) applications, little is known about the role of the HF framework in healthcare. The purpose of the systematic literature review (SLR) is to review the existing literature on the HF framework and its applications in healthcare. This SLR includes literature published between January 2015 and March 2023 in the ACM digital library, IEEE Xplore, SCOPUS, Springer, PubMed, and Google Scholar databases. Following the inclusion and exclusion criteria, a total of 57 articles emerged as eligible for this SLR. The HF framework was found to be useful in securing health records coming from the Internet of Medical Things (IoMT) and many other devices. The main causes behind using the HF framework were identified as privacy and security, integrity, traceability, and availability of health records. Additionally, storage issues with transactional data over the blockchain are reduced by the use of the HF framework. This SLR also highlights potential future research trends to ensure the high-level security of health records.
A New Method for Orthographic Video Map Construction Based on Video and GIS

For the problem that the non-ground plane and dynamic object areas in surveillance videos have large deformation after geographic mapping, a new method for orthographic video map construction (OVMC) based on video and GIS is proposed. Firstly, the segmented video background (SegBG), dynamic object sub-image (SubObjPic) and its coordinates are extracted. Secondly, the homography matrix (H) is solved. An area (R) is set in 2D map. based on H−1, the orthophoto map of video background (OrviBG) is constructed. Finally, each SubObjPic are converted to geographic space and overlaid on OrviBG, then the ortho video map is generated. The results show that:(1) The accuracy of semantic segmentation model for removing non-ground plane is 96.70%; (2) Compared with the traditional method, the amount of orthographic video is reduced by 22.9%; (3) The deformation of non-ground and dynamic object areas is eliminated. This method can promote the deep integration of surveillance video and GIS.