Reviewerly/exHarmony huggingface dataset:
Using Flutter to Develop a Hybrid Application of Augmented Reality

With the idea of real being combined with virtual, augmented reality (AR) is a cutting-edge technology that has allured lots of attention from the industry and is seen as an ideal way to envision context-related information. A key component of the umbrella term mixed reality (MR), we can see AR as helping the current generation deal with the issues of time and space. Along with the increasing usage of multimedia content in everyday life, virtual reality labs are being set up at an unprecedented scale. The idea of computer-generated graphics is presented to the user as a very appealing way of interacting with the surroundings. Moreover, overlaying it with the content and rendering it with real-world images is seen as the next step in computer multimedia. This is the main concept behind AR. Due to the promise shown in this field, many resources are being directed by prominent companies towards AR, to improve productivity and amplify intelligence. Though not a recent field, as research has been done on it in the last few decades, AR has yet to reach the masses in an intelligent way, i.e., the user has yet to use it to its full potential. Self-paced learning is one of the few ways in which AR can be implemented. This paper presents the use of 3-D models for intraoperative visualization, through a newly developed mobile application based on flutter framework. It renders the 3-D models in a real-time scenario, which were either rendered in real time, or downloaded from the cloud. Moreover, the spatial relations between the objects were accentuated. Future scope of AR with several hosts has also been explored, i.e., multiuser AR. In addition, this paper discusses specific constraints and superiorities of various techniques used for the generation of AR. Further, the paper also explores the use of hybrid frameworks in AR-specific applications and provides an overview of all the existing techniques employed about AR.
Issues in Requirements Specification in Malaysia’s Public Sector: An Evidence from a Semi-Structured Survey and a Static Analysis

Requirement specifications (RS) are essential and fundamental artefacts in system development.RS is the primary reference in software development and is commonly written in natural language.Bad requirement quality, such as requirement smells, may lead to project delay, cost overrun, and failure.Focusing on requirement quality in the Malaysian government, this paper investigates the methods for preparing Malay RS and personnel competencies to identify the root cause of this issue.We conducted semi-structured interviews that involved 17 respondents from eight critical Malaysian public sector agencies.This study found that ambiguity, incompleteness, and inconsistency are the top three requirement smells that cause project delays and failures.Furthermore, based on our static analysis, we collected the initial Malay RS documents from various Malaysian public sector agencies; we found that 30% of the RS were ambiguous.Our analysis also found that respondents with more than 10 years of experience could manually identify the smells in RS.Most respondents chose the Public Sector Application Systems Engineering (KRISA) handbook as a guideline for preparing Malay RS documents.Respondents acknowledged a correlation between the quality of RS and project delays and failures.
Distributed System Access Control for Fuzzy Mathematics and Probability Theory

AC is to control and manage the access rights of legitimate users who enter the system on the basis of user identity authentication, so that the user's access rights are limited within the allowable range.It is an important part of information security technology.Implementing AC to users through technical means plays an important role in information security.The main purpose of this paper is to use fuzzy mathematics (FMs) and probability theory (PT) to study the access control (AC) of distributed systems (DS).This paper adds trust elements on the basis of the AC model, sets roles for each trust level, and sets a series of permissions for each role.The user determines the trust level to which he belongs by being judged by other users, and then obtains the corresponding authority through the role corresponding to the trust level.Experiments show that by evaluating the trust degree and the reputation value of user behavior, the ability of user trust degree and service and access behavior is greatly improved.Compared with the existing trust evaluation algorithm, it has a good correlation.At the same time, it satisfies the rule of "slow increase and sudden decrease" of the target change trust degree, which can effectively resist malicious users' phishing attacks, bleaching attacks, collusion attacks and other security attacks, and has higher security.
The Effects of Motivation, Career Decision-Making Self-Efficacy, and Self-Regulation on Learning Engagement of Junior College Students

This study examined three influential factors of junior college students' learning engagement: (a) intrinsic and extrinsic motivation, (b) career decision-making self-efficacy (CDMSE), and (c) self-regulation. Participants included 206 students enrolled in the secretarial administration program in a junior college in South Korea. The primary research findings are as follows. First, intrinsic and extrinsic motivation positively influenced CDMSE. Intrinsic motivation influenced learning engagement through CDMSE and self-regulation; extrinsic motivation did not. Second, CDMSE influenced self-regulation and indirectly influenced learning engagement through self-regulation. Third, self-regulation had the largest effect on learning engagement. The findings highlight the need to examine and enhance students' self-regulation skills and help improve the learning engagement of junior college students. This study confirmed the significance of motivation, CDMSE, and self-regulation for junior college students' learning engagement.
Fighting Against Piracy:An Approach to Detect Pirated Video Websites Enhanced by Third-party Services

Along with the development of video streaming, the increasing number of pirated video websites has caused unprecedented damage to copyright holders and potential security risks to their users. Though many efforts have been made to take down pirated video websites, they are still emerging by utilizing evading approaches like Fast-Flux domains and Cybercrime-as-a-Service(CaaS) tools. In this paper, to detect pirated video websites, we propose a Third-party Enhanced Pirated Video Website Classification Network (TEP-Net), which integrates both semantic features and relationship information between websites and their third-party services. More specifically, we apply CNN-BiLSTM-Attention to explore both character-level and domain-level textual embedding and utilize relationship information by constructing statistical features in classification. The experiment shows that TEP-Net achieves a significant performance compared with existing methods. Furthermore, we perform an in-depth analysis of the CaaS behind pirated video websites. Our research can help the security community fight against video piracy more precisely and effectively.
Empowerment Village Community Through the Rawang Village Information System (SiDeRa)

The purpose of this research is the development of a village information system with community empowerment to manage data in Rawang Village. The problem in this research is that the data management has not been recorded properly. Service activity data is archived in paper-based form and requires a large storage space so that there are difficulties in finding the data and information needed, which causes public services to be not optimal. In addition, another problem faced is that the existing profile application is still manually adding data. The solution to this problem is to build a web-based information system because of the web application in terms of almost unlimited data access, flexibility, and portability so that data management is optimal, village profile data is automatically added, and improving public services. All activity data will be stored in the system and village communities can get information quickly. The method used in this research is Agile Scrum and User Acceptance Test (UAT) to test user satisfaction with the system. UAT uses a questionnaire with 50 respondents from Pariaman village and the sampling method used is a random sample. The statistical method used is regression analysis with the independent variable (variable X) and the dependent variable (variable Y). The UAT results found that the village information system variable (X) has an effect on the variable to improve the quality-of-service quality in Rawang village (Y) by 75.6% which means that the information system built helps village communities in improving services public, more optimal data management, easier access for village communities to information, and provide statistics or data reports automatically.
Research on machine reading comprehension based on pre-trained model

In order to improve the machine reading ability of the model, this article starts from the high-level semantic information of the text and the concepts of the distillation model. Among the high-level semantic information of the text, part-of-speech information and named entity information are selected as additional information that the model can obtain. Combined with part-of-speech tagging technology and named entity recognition technology, a BERT-HSI model based on a pre-training model and fusion of high-level semantic information is proposed. Later, on the basis of BERT-HSI, the paper started from the perspective of model optimisation, with the concepts in the distillation model as the core, and proposed a capability learning method. Finally, the research method about machine reading comprehension based on the pre-training model is presented, which not only integrates high-level semantic information but also includes the capacity learning process.
A DirectX-Based DICOM Viewer for Multi-user Surgical Planning in Augmented Reality

Preoperative medical imaging is an essential part of surgical planning. The data from medical imaging devices, such as CT and MRI scanners, consist of stacks of 2D images in DICOM format. Conversely, advances in 3D data visualization provide further information by assembling cross-sections into 3D volumetric datasets. As Microsoft unveiled the HoloLens 2 (HL2), which is considered one of the best Mixed Reality (XR) headsets in the market, it promised to enhance visualization in 3D by providing an immersive experience to users. This paper introduces a prototype holographic XR DICOM Viewer for the 3D visualization of DICOM image sets on HL2 for surgical planning. We first developed a standalone graphical C++ engine using the native DirectX11 API and HLSL shaders. Based on that, the prototype further applies the OpenXR API for potential deployment on a wide range of devices from vendors across the XR spectrum. With native access to the device, our prototype unravels the limitation of hardware capabilities on HL2 for 3D volume rendering and interaction. Moreover, smartphones can act as input devices to provide another user interaction method by connecting to our server. In this paper, we present a holographic DICOM viewer for the HoloLens 2 and contribute (i) a prototype that renders the DICOM image stacks in real-time on HL2, (ii) three types of user interactions in XR, and (iii) a preliminary qualitative evaluation of our prototype.
Chaotic association feature extraction of big data clustering based on Internet of Things

This article addresses the stabilization of chaotic characteristics in abnormal data by proposing the chaotic correlation feature extraction of big data clustering based on the Internet of things. The chaotic features in big data usually show complex folding and distortion without obvious rules and order and non-synchronization. In this paper, the extracted correlation dimension is used as the chaotic feature of big data clustering. The one-dimensional time series can be extended in multi-dimensional space is analyzed based on phase space reconstruction, so as to extract the chaotic correlation dimension features. After the relevant experimental analysis, this paper mainly compares the energy consumption and processing time of the two respective algorithms. In the simulation parameter design, the time interval of big data packet generation is 0.1s, and the data is generated from the simulation time of 300s. The results obtained show that when dealing with the same amount of data, the energy consumption of this algorithm is significantly lower than that of the traditional algorithm. When dealing with the same amount of data, the time required by this algorithm is significantly lower than that of the traditional algorithm. This is because this algorithm is easy to implement and has good clustering efficiency for data, so the clustering time is short. With the gradual increase of the amount of data, the correlation dimension of this algorithm tends to be stable. While the correlation dimension of the traditional algorithm fluctuates greatly, it is revealed that the proposed approach has high data clustering efficiency and verifies the effectiveness of this algorithm.
The role of digital technologies in improving the quality of higher education

The main directions of the development of the educational process based on the use of digital technologies in the higher education system and the analysis of their possibilities are revealed in the article. Also, the author expressed his opinion on the introduction of digital technologies and modern methods to the educational process.
Auditing an insightful method for determining the sequence of intersecting strokes: Scanning electron microscope

Over the years, many studies have been published on complex and challenging problem of sequence of strokes examination in order to find a suitable technique in the field of questioned documents. There are various destructive and non-destructive techniques for the examination of various sequence problems. Scanning electron microscopy (SEM) or scanning electron microscopy with energy dispersive x-ray (SEM-EDX) could be one of the advanced and complementary technique useful in chronological investigation of sequence of strokes. This paper deals with the brief introduction to the scanning electron microscope along with research studies conducted on determining sequence of intersecting strokes utilizing SEM.
From Screenwriting to Space-Writing

In the past ten years, audiovisual creators have been working on the development of narrative experiences for extended reality (XR) technologies, especially virtual reality (VR). The evolution of this practice has led to the creation of a technical language and processes. The transfer of knowledge from cinematography and videography has been the basis for the creative practice of “immersive narratives,” very often carrying with it jargon and practices that do not fit entirely with XR’s spatial nature. In this essay, I ref lect on whether we are still writing for a screen or writing for space from a practitioner’s perspective. Such a change of perspective starts with the recognition of the perceptual sphere and how to compose scenes in it. In this regard, a review of storyboarding for VR, followed by my own experience in creating an interactive VR movie, allowed me to ref lect on the concept of framing, camera positions, and authorial intentions. Finally, I argue that we can move from screenwriting to space-writing in relation to the technologies and immersive power of XR.
A Novel Hybrid Tracking Algorithm for Client–Server Connection Using a Machine Learning Technique

Machine intensive and cyclical earth-moving activities could benefit from genuine surveillance heavy machinery. It could provide accurate information for development purposes in the future. Reasonably clear sightlines and recognized machined, ground, earth-moving work locations are among the greatest choices for vision-based solutions. The server-customer interaction tracker (SCIT) seems to be a system that recognizes and monitors the unclean loading cycle by combining many cutting-edge image processing algorithms using spatiotemporal data and depth of understanding. For the SCIT technology, a proposed hybrid detection method is designed to monitor vehicles in optically cluttered entrance ramps. Video capturing underneath various settings is used to assess the built system. The SCIT device including its newly designed monitoring algorithm performed admirably, as evidenced by the incredible precision of the computer and ground truth statistical correlation.
Predictive Angular Potential Field-based Obstacle Avoidance for Dynamic UAV Flights

In recent years, unmanned aerial vehicles (UAVs) are used for numerous inspection and video capture tasks. Manually controlling UAVs in the vicinity of obstacles is challenging, however, and poses a high risk of collisions. Even for autonomous flight, global navigation planning might be too slow to react to newly perceived obstacles. Disturbances such as wind might lead to deviations from the planned trajectories. In this work, we present a fast predictive obstacle avoidance method that does not depend on higher-level localization or mapping and maintains the dynamic flight capabilities of UAVs. It directly operates on LiDAR range images in real time and adjusts the current flight direction by computing angular potential fields within the range image. The velocity magnitude is subsequently determined based on a trajectory prediction and time-to-contact estimation. Our method is evaluated using Hardware-in-the-Loop simulations. It keeps the UAV at a safe distance to obstacles, while allowing higher flight velocities than previous reactive obstacle avoidance methods that directly operate on sensor data.
GraphVid: It only Takes a Few Nodes to Understand a Video

We propose a concise representation of videos that encode perceptually meaningful features into graphs. With this representation, we aim to leverage the large amount of redundancies in videos and save computations. First, we construct superpixel-based graph representations of videos by considering superpixels as graph nodes and create spatial and temporal connections between adjacent superpixels. Then, we leverage Graph Convolutional Networks to process this representation and predict the desired output. As a result, we are able to train models with much fewer parameters, which translates into short training periods and a reduction in computation resource requirements. A comprehensive experimental study on the publicly available datasets Kinetics-400 and Charades shows that the proposed method is highly cost-effective and uses limited commodity hardware during training and inference. It reduces the computational requirements 10-fold while achieving results that are comparable to state-of-the-art methods. We believe that the proposed approach is a promising direction that could open the door to solving video understanding more efficiently and enable more resource limited users to thrive in this research field.
A Quick Overview of Cloud-Based Services

In the realm of Services Computing, Cloud Computing has developed into a scalable platform for the consumption and delivery of such services.Service-oriented architecture (SOA) and virtualizations of hardware and software are the technological underpinnings of cloud computing.To determine the contours of a new age, we look to the evolution of technologies like cloud computing, which combines parallel and distributed processing, grid computing, and virtualization.Businesses are beginning to use cloud computing as a new method of data storage and management.In this study, we examine the architecture of the cloud and draw parallels between cloud and grid computing.In addition, we discuss the features and potential uses of various widely used cloud computing systems.The purpose of this study is to highlight some of the problems and difficulties associated with cloud computing.We found many obstacles from an adoption of cloud computing perspective and emphasised the cloud interoperability problem that needs considerable additional study and development.However, customers face significant resistance to adopting cloud computing systems due to concerns about security and privacy.In this research, we look at the worries of various cloud computing system vendors about security and privacy.The purpose of cloud computing is to enable resource sharing amongst cloud service users, cloud partners, and cloud suppliers.Infrastructure cloud (e.g., hardware, IT infrastructure management), software cloud (e.g., SaaS focusing on middleware as a service, or traditional CRM as a service), application cloud (e.g., Application as a Service, UML modelling tools as a service, social network as a service), and business cloud (e.g., Software as a Service, UML modelling tools as a service, social network as a service) are all the result of resource sharing at different (e.g., business process as a service).
A Comprehensive Study on Eucalyptus, Open Stack and Cloud Stack

Cloud computing remains the discussing topic in the field of deploying applications, data storage, improvising operational efficiency, cost savings, and high performance. Incremented storage capacity and automation suppleness, flexibility, and scalability are the key factors in cloud computing. Choosing an appropriate cloud platform can be very difficult and every platform can have advantages and disadvantages. So, in our research, we are comparing the attributes of open stack and cloud stack. This platform comparison intends to compare the efficiency and usage of the cloud platforms. Then, the eucalyptus, cloud stack, and open stack come under the cloud platform to perform efficiently with high scalability. These platforms can go hybrid with AWS to develop applications. The comparison between this cloud platforms is to summarize the scalability and services. Eucalyptus, open stack, and cloud stack are all reopen-source cloud computing software platforms and this paper heavily focuses on their pros and cons in terms of efficiency, storage, and usage parameters. Conservation of user data should be more cost-efficient in the cloud and these tools comparison would highly assist the users to have an eagle view over the major cloud computing platforms.
Manajemen Perpustakaan Sekolah (Studi pada Perpustakaan Ceria SMA N 1 Rejang Lebong)

School library management is basically a process of optimizing human, material, and budgetary contributions to achieve library goals. The purpose of this study is to describe the management of the Ceria library at SMA N 1 Rejang Lebong, the specific purpose of which is to find out how the implementation of the management function in the cheerful library at SMA N 1 Rejang Lebong starts from planning, organizing, implementing (actuating), controlling which is applied in the cheerful library of SMA N 1 Rejang Lebong. This research method the author uses a descriptive research method with a qualitative approach to find out how the implementation of library management in the cheerful library of SMA N 1 Rejang Lebong. The subject of this research is the head of the library, librarians, teachers, students and schools. The results of this study are the implementation of management functions in the cheerful library of SMA N 1 Rejang Lebong has been implemented well.