Reviewerly/exHarmony huggingface dataset:
Studying the Influence of Translational and Rotational Motion on the Perception of Rotation Gains in Virtual Environments

Rotation gains in Virtual Reality (VR) enable the exploration of wider Virtual Environments (VEs) compared to the workspace users have in VR setups. The perception of these gains has been consequently explored through multiple experimental conditions in order to improve redirected navigation techniques. While most of the studies consider rotations, in which participants can rotate at the pace they desire but without translational motion, we have no information about the potential impact of the translational and rotational motions on the perception of rotation gains. In this paper, we estimated the influence of these motions and compared the perceptual thresholds of rotations gains through a user study (n = 14), in which participants had to perform virtual rotation tasks at a constant rotation speed. Participants had to determine whether their virtual rotation speed was faster or slower than their real one. We varied the translational optical flow (static or forward motion), the rotational speed (20, 30, or 40 deg/s), and the rotational gain (from 0.5 to 1.5). The main results are that the rotation gains are less perceivable at lower rotation speeds and that translational motion makes detection more difficult at lower rotation speeds. Furthermore, the paper provides insights into the user’s gaze and body motions behaviour when exposed to rotation gains. These results contribute to the understanding of the perception of rotation gains in VEs and they are discussed to improve the implementation of rotation gains in redirection techniques.
SABMIS: sparse approximation based blind multi-image steganography scheme

We hide grayscale secret images into a grayscale cover image, which is considered to be a challenging steganography problem. Our goal is to develop a steganography scheme with enhanced embedding capacity while preserving the visual quality of the stego-image as well as the extracted secret image, and ensuring that the stego-image is resistant to steganographic attacks. The novel embedding rule of our scheme helps to hide secret image sparse coefficients into the oversampled cover image sparse coefficients in a staggered manner. The stego-image is constructed by using the Alternating Direction Method of Multipliers (ADMM) to solve the Least Absolute Shrinkage and Selection Operator (LASSO) formulation of the underlying minimization problem. Finally, the secret images are extracted from the constructed stego-image using the reverse of our embedding rule. Using these components together, to achieve the above mentioned competing goals, forms our most novel contribution. We term our scheme SABMIS (Sparse Approximation Blind Multi-Image Steganography). We perform extensive experiments on several standard images. By choosing the size of the length and the width of the secret images to be half of the length and the width of cover image, respectively, we obtain embedding capacities of 2 bpp (bits per pixel), 4 bpp, 6 bpp, and 8 bpp while embedding one, two, three, and four secret images, respectively. Our focus is on hiding multiple secret images. For the case of hiding two and three secret images, our embedding capacities are higher than all the embedding capacities obtained in the literature until now (3 times and 6 times than the existing best, respectively). For the case of hiding four secret images, although our capacity is slightly lower than one work (about 2/3rd), we do better on the other two goals (quality of stego-image & extracted secret image as well as resistance to steganographic attacks). For our experiments, there is very little deterioration in the quality of the stego-images as compared to their corresponding cover images. Like all other competing works, this is supported visually as well as over 30 dB of Peak Signal-to-Noise Ratio (PSNR) values. The good quality of the stego-images is further validated by multiple numerical measures. None of the existing works perform this exhaustive validation. When using SABMIS, the quality of the extracted secret images is almost same as that of the corresponding original secret images. This aspect is also not demonstrated in all competing literature. SABMIS further improves the security of the inherently steganographic attack resistant transform based schemes. Thus, it is one of the most secure schemes among the existing ones. Additionally, we demonstrate that SABMIS executes in few minutes, and show its application on the real-life problems of securely transmitting medical images over the internet.
Symbols Detection and Classification using Graph Neural Networks

In this paper, we propose a method to both extract and classify symbols in floorplan images. This method relies on the very recent developments of Graph Neural Networks (GNN). In the proposed approach, floorplan images are first converted into Region Adjacency Graphs (RAGs). In order to achieve both classification and extraction, two different GNNs are used. The first one aims at classifying each node of the graph while the second targets the extraction of clusters corresponding to symbols. In both cases, the model is able to take into account edge features. Each model is firstly evaluated independently before combining both tasks simultaneously, increasing the quickness of the results.
Processing extreme-scale graphs on China's supercomputers

research-article Open Access Share on Processing extreme-scale graphs on China's supercomputers Authors: Yiming Zhang National University of Defense Technology in Changsha, China National University of Defense Technology in Changsha, ChinaView Profile , Kai Lu National University of Defense Technology in Changsha, China National University of Defense Technology in Changsha, ChinaView Profile , Wenguang Chen Tsinghua University in Beijing, China Tsinghua University in Beijing, ChinaView Profile Authors Info & Claims Communications of the ACMVolume 64Issue 11November 2021 pp 60–63https://doi.org/10.1145/3481614Published:25 October 2021Publication History 1citation2,263DownloadsMetricsTotal Citations1Total Downloads2,263Last 12 Months326Last 6 weeks22 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteView all FormatsPDF
Numerical Association Rule Mining from a Defined Schema Using the VMO Algorithm

Association rule mining has been studied from various perspectives, all of which have made valuable contributions to data science. However, there are promising research lines, such as the inclusion of continuous variables and the combination of numerical and categorical attributes for a supervised classification variety. This research presents a new alternative for solving the numerical association rule-mining problem from an optimization perspective by using the VMO (Variable Mesh Optimization) meta-heuristic. This work includes the ability for classification when categorical data are available from a defined rule schema. Our technique implements an optimization process for the intervals of continuous variables, unlike others that discretize these types of variables. Some experiments were carried out with a real dataset to evaluate the quality of the rules obtained; in addition to this, this technique was compared with four population-based algorithms. The results show that this implementation is competitive in classification cases and has more satisfactory results for completely numerical data.
DEVELOPING VALUE FRAMEWORK OF STUDENT INFORMATION CULTURE IN THE ORGANIZATION OF SECONDARY VOCATIONAL EDUCATION

The article focuses on the problem of developing value framework of student information culture in the organization of secondary vocational education. For the first time, the author reveals pedagogical conditions for the efficiency of this process: the stages of experimental work aimed at developing the value framework of student information culture in the organization of secondary vocational education are considered. The analysis performed before and after the experimental study shows positive dynamics within the value framework development of information culture. It is concluded that the presented results of an empirical study indicate the efficiency of experimental work on the value framework of student information culture in the organization of secondary vocational education.
Lexicon Based Sentiment Analysis in Indonesia Languages : A Systematic Literature Review

This systematic literature review aims to determine the trend of lexicon based sentiment analysis research in Indonesian Language in the last two years. The focus of the study is on the understanding of preprocessing used in lexicon-based sentiment analysis studies in the last two years, the lexicon used in these studies, and classification accuracy. The main question in this SLR : what techniques of lexicon based sentiment analysis will provide the highest accuracy. The most widely used preprocessing methods in previous research are tokenization, case conversion, stemming, remove punctuation, remove stop word, remove or replace emoji and emoticons, and normalization or slangword conversion. The sentiment labeling process in previous studies calculated based on the comparison of the number of negative sentiment keywords with positive sentiment keywords in one sentence. The maximum accuracy from previous study is 90%. The most widely used lexicon is NRC and Inset which is a lexicon dictionary in Indonesian. Knowledge of this can be used to propose a better model for lexicon based sentiment analysis in Indonesian Languages.
Methodology of preparing future computer science teachers to create electronic educational resources

Modern society stands in need of a next-generation teacher, in the light of which this study acquires particular relevance. The paper investigates the urgent issue of modern pedagogy – the study of the scientific foundations of the methodology for preparing future computer sciences teachers for the development of electronic educational resources. In the study, the following general scientific methods were used: logical-historical method, pedagogical observation, analysis, synthesis, systematisation and generalisation, methods of pedagogical experiment, methods of mathematical statistics. The authors propose criteria and indicators of the readiness of future informatics teachers to develop electronic educational resources, as well as levels to identify the readiness of future informatics teachers to create electronic educational resources. In the paper, the authors share the results of an experiment to determine the suitability of their proposed methodology, describe the ways of forming the skills of future teachers to develop EER.&#x0D; &#x0D; Keywords: learning process, informatisation of education, structure, aptitude of future teachers, criteria, indicators.
Phishing Detection Methods: A Review

The web has turned into a principal part of our conventional social and financial activities. The web isn't significant for singular clients just yet additionally for associations, since associations that offer web-based exchanging can accomplish an upper hand by serving overall customers. Webworks arriving at clients all around the globe with no commercial center limitations and with successful utilization of internet business. Consequently, Internet customers may be defenceless against different kinds of web risks, that may cause financial damages, information forgery, brand reputation mischief, the sacrifice of private information, and loss of customers' confidence in online business and electronic banking. Thusly, the reasonableness of the Internet for business exchanges becomes dubious. Phishing is seen as a design of web peril which is classified as the forte of mimicking a website of a legitimate undertaking proposing to gain a client's private accreditations, for instance, usernames, passwords, and federal retirement aide numbers. In this paper, we present an overview of cutting-edge research on such attacks. Besides, we expect to perceive the cutting-edge advancements in phishing, furthermore, give a far-reaching overview and comparison of these kinds of literatures to understand the hole that is as yet prevailing around anti-phishing. This overview will be for the most types of online phishing detection techniques for the last 4 years.
APLIKASI RESTFULL PADA SISTEM INFORMASI GEOGRAFIS PARIWISATA KOTA BANDAR LAMPUNG

Android, Geographic Information Systems, RESTful, Web One of the mapping technologies widely used today is Geographic Information Systems. Geographic Information Systems (GEOGRAPHIC INFORMATION SYSTEMS) is a mapping technology in the form of computer-based information systems, designed to work using data that has spatial information or spatial reference. Mapping technology is widely used to facilitate human work. In this research, Geographic Information System technology was used to support one of the business processes at the Bandar Lampung City Tourism Office. This system was built to assist related agencies in recording tourist sites. The system consists of a web-based system and Android-based applications that are connected using RESTful Web Service. The system is implemented using the PHP programming language with the help of CodeIgniter for web-based systems, and the Java programming language for Android-based applications. The method of developing the system used is the waterfall model method according to Rossa U.S. and Saladin (2014). Application design is based on Unified Modeling Language (UML), flowchart diagrams, and interface design. While the application used in the creation of the Android base system is Android Studio. The testing method used is the system's functional Black-Box. The results of black-box testing data show that the system runs as it should, the system is easy to understand by users, and can meet the functional needs of the system needed by the Bandar Lampung City Tourism Office
Compact Reconfigurable Architecture for Sosemanuk Stream Cipher

Sosemanuk is word oriented synchronous stream cipher capable to produce 32 bit ciphertext. It uses variable key from 128 bit to 256 bit and publically known Initialization Vector (IV) of 128 bit. Sosemanuk is one of the finalists in Profile 1 of the eSTREAM Portfolio. This cipher targets to avoid structural properties of SNOW2.0 to improve its efficiency by reducing the internal state size. It also uses reduced round Serpent24 block cipher to provide secure and efficient key loading process. This paper presents compact architecture for Sosemanuk stream cipher. The proposed architecture uses compact S-box architecture and compact modulo adders designed using CLA. The proposed compact S-box minimizes resources utilized without affecting performance. Proposed modulo adder architecture minimizes resources used as compared to conventional CLA implementation. The algorithm was designed by using VHDL language with CAD tool Xilinx ISE design suite 13.2 and implemented on Xilinx Virtex XC5VFX100E FPGA device. The proposed architecture achieved throughput of 4.281 Gbps at clock frequency of 133.788 MHz
Innovative mixed reality approach to rock mass mapping in underground mining

Traditional methods of mapping in mines use a geological compass for orientation measurements, a tape measure for length measurements and pen/paper for sketching and taking notes.This has been improved in recent years with a change from compass to smart phones/tablets and the use of tablets for sketching photographic images.A significant improvement is the use of remote sensing e.g.LiDAR and photogrammetry to collect data with subsequent office-based data processing.However, the collected 3D data is usually displayed on 2D monitors which is a very different experience in comparison to fieldwork.The perception of 3D geometry and scale are lost, which may result in biased and limited interpretations.The Microsoft HoloLens is an augmented reality headset comprising a computer with a transparent screen and a 3D scanner.This device allows the creation of a 3D map of the real-world almost in real-time.Using this map, it becomes possible to place virtual objects within the real-world and to know the location of the HoloLens user.As the screen is transparent HoloLens users can see the real-world along with virtual objects, such as previous mapping and drilling completed anywhere within the underground mining operation.Advantage of state-of-the-art new VR/MR technology was taken and a Microsoft HoloLens application which can be used to annotate/draw directly on a rock face was developed and the necessary spatial data in the field for use during mapping is made available.After field work has been undertaken, the collected data can be easily exported to other software without further post-processing.Holographic mapping procedures for virtual rock outcrops constructed from remote sensing data, e.g.ground and UAV based LiDAR and photogrammetry was also developed.This allows office-based mapping of virtual outcrops.The developed software will improve direct outcrop mapping and office-based mapping using remote sensing data.
NetXplain: Real-time explainability of graph neural networks applied to networking

Recent advancements in Deep Learning (DL) have revolutionized the way we can efficiently tackle complex optimization problems. However, existing DL-based solutions are often considered as black boxes with high inner complexity. As a result, there is still certain skepticism among the networking industry about their practical viability to operate data networks. In this context, explainability techniques have recently emerged to unveil why DL models make each decision. This paper focuses on the explainability of Graph Neural Networks (GNNs) applied to networking. GNNs are a novel DL family with unique properties to generalize over graphs. As a result, they have shown unprecedented performance to solve complex network optimization problems. This paper presents NetXplain, a novel real-time explainability solution that uses a GNN to interpret the output produced by another GNN. In the evaluation, we apply the proposed explainability method to RouteNet, a GNN model that predicts end-to-end QoS metrics in networks. We show that NetXplain operates more than 3 orders of magnitude faster than state-of-the-art explainability solutions when applied to networks up to 24 nodes, which makes it compatible with real-time applications; while demonstrating strong capabilities to generalize to network scenarios not seen during training.
PENGEMBANGAN APLIKASI DAILY ACTIVITYDI BPS PROVINSI KALIMANTAN UTARA

Daily Activity is an application developed by BPS-Statistics of Sulawesi Tenggara Province. The application is then also applied in BPS-Statistics of Kalimantan Utara Province. In Daily Activity, employees report their daily activities, including the outputs. The list of activities is then manually summarized every month to form an Employee Performance Achievement Report (CKP). Because the process is still manual, the preparation of CKP reports has become less effective and efficient. Thus, the author tries to develop Daily Activity by adding the Employee Performance Achievement menu. The development uses the Software Development Life Cycle (SDLC) method with the waterfall approach. With this menu, now the list of activities can be summarized automatically by activity categories. The application has been tested with black-box testing to determine its functionality. The test results show that the application meets user needs in forming CKP reports. Keywords: CKP, Employee Performance Achievement Report, PHP, SDLC, web-based.
The impact of the covid-19 crisis on higher education

Abstract The current pandemic crisis is unique in its kind, becoming a global cataclysm with a multilateral impact and an extended spread over time. Affecting all aspects of human activity, this crisis has inevitably affected the higher education system, and its consequences are manifesting both locally and internationally. The purpose of this paper was to establish the influence of crisis on the economic situation of higher education institutions. After studying of different institutions reports, analytical presentations of authors from different countries, as well as the author's communication with colleagues from different educational institutions during online academic meetings, it became possible to compile a complex picture of economic consequences of the COVID-19 crisis on higher education system. The research results showed an extremely uneven spread of the economic effects of the pandemic crisis. Thus, the least COVID-19 crisis has affected universities in industrially developed countries and the disastrous impact will manifested in developing countries. In addition, a dependence of evolution of economic situation of educational institutions of a complex of important factors was detected. It is about of change in living standard of the population, the capacity of the local authorities to manage the consequences of the pandemic, the changes in higher education policies, presiding students to do higher education, managerial ability to manage the economic and financial status of higher education institutions and others. Likewise, certain ways of solving economic problems have been outlined.
Spatio-Temporal Path Planning for Lunar Polar Exploration with Robustness against Schedule Delay

This paper presents a method to obtain a robust optimal path in an environment with time-varying safety features, such as in the lunar polar region. In designing the path for planetary exploration rovers, we must consider various safety conditions, such as terrain hazards, illumination, and communication visibility to the Earth. Some of the safety features are time-varying, and the optimal path should be searched for both the spatial direction and the temporal direction. In addition, there is no guarantee that all of the sequences will be successfully executed on time due to misoperation, failures, or trouble. Therefore, a path that is robust against the delay must be planned so as to guarantee safety even when behind schedule. The authors propose an algorithm called “Robust Spatio-Temporal Path Planner for the Planetary Rover (Robust-STP3R)” to obtain a path that is robust against schedule delay in a time-varying environment. This method defines a cost function that consists of the distance as well as the region type cost. To add robustness against schedule delays, the authors consider a weighted summation of the time-varying region type cost with regard to the temporal direction. The effectiveness of the proposed method is demonstrated through use in a simulated lunar polar exploration exercise.
Agile Transformation at Scale: A Tertiary Study

Abstract Due to the fast-paced nature of the software industry and the success of small agile projects, researchers and practitioners are interested in scaling agile processes to larger projects. Agile software development (ASD) has been growing in popularity for over two decades. With the success of small-scale agile transformation, organizations started to focus on scaling agile. There is a scarcity of literature in this field making it harder to find plausible evidence to identify the science behind large scale agile transformation. The objective of this paper is to present a better understanding of the current state of research in the field of scaled agile transformation and explore research gaps. This tertiary study identifies seven relevant peer reviewed studies and reports research findings and future research avenues.