Reviewerly/exHarmony huggingface dataset:
Sentimen Analisis Masyarakat Indonesia di Twitter Terkait Metaverse dengan Algoritma Support Vector Machine

Metaverse is part of the increasingly rapid development of technology in the world, bringing the virtual world into the real world is very possible. Starting from a novel, metaverse has now begun the process of being implemented, especially with the COVID-19 pandemic being one of the strong foundations for speeding up the implementation of this technology. Since the emergence of the metaverse echoed by Facebook, which has changed its name to meta, has made the world's public attention increasingly highlight this technology, some have welcomed it and some have concerns about the development of this technology. Research to explore the sentiments of the Indonesian people towards metaverse technology uses the CRISP-DM method with the Support Vector Machine algorithm and the test is carried out by comparing it with another algorithm, namely the tree algorithm, the programming language used is the R language with the Rstudio application. This study obtained the results of Indonesian public opinion on metaverse technology which showed 66% to be neutral, 17% negative and 16% positive, while the results of testing with the SVM algorithm showed SVM performance results of 87% with the kernel used was Linear, and these results are far better than using the tree algorithm which only has a performance of 71%.
Analyzing the Feasibility and Generalizability of Fingerprinting Internet of Things Devices

Abstract In recent years, we have seen rapid growth in the use and adoption of Internet of Things (IoT) devices. However, some loT devices are sensitive in nature, and simply knowing what devices a user owns can have security and privacy implications. Researchers have, therefore, looked at fingerprinting loT devices and their activities from encrypted network traffic. In this paper, we analyze the feasibility of fingerprinting IoT devices and evaluate the robustness of such fingerprinting approach across multiple independent datasets — collected under different settings. We show that not only is it possible to effectively fingerprint 188 loT devices (with over 97% accuracy), but also to do so even with multiple instances of the same make-and-model device. We also analyze the extent to which temporal, spatial and data-collection-methodology differences impact fingerprinting accuracy. Our analysis sheds light on features that are more robust against varying conditions. Lastly, we comprehensively analyze the performance of our approach under an open-world setting and propose ways in which an adversary can enhance their odds of inferring additional information about unseen devices (e.g., similar devices manufactured by the same company).
The Intelligent Process Lifecycle of Active Cyber Defenders

“There are a thousand hacking at the branches of evil to one who is striking at the root.” Henry David Thoreau Successful information security requires careful application of tools to goals. The tools must be well used and well configured and require skillful interpretation of results. If problems occur in daily digital forensic workflows, then they must be documented in a systematic manner that aids process improvement. This article is the third in a series of three articles, where the connection between all the articles is displayed in the “Intelligent Process Lifecycle of Active Cyber Defenders” poster [ 1 ]. The poster showcases the main cyber defence disciplines and how, if false-positive events are classified in a systematic manner for each service, this information can afterwards be used to identify improvement areas. It focuses on false positives, error states, and common operation problems that occur when identifying and assessing vulnerabilities, as well as problems that happen when the security operations centre (SOC) tries to add a log source for continuous monitoring. For all these problems it also includes suggestions on how to solve or document them if they cannot be solved. We also demonstrate how to map these practical SOC outcome failures into clear risk management categories. That mapping can be used to optimize workflows, improve strategic cyber risk management, as well as deliver valuable metrics.
Kite

Converged multi-level secure (MLS) systems, such as Qubes OS or SecureView, heavily rely on virtualization and service virtual machines (VMs). Traditionally, driver domains - isolated VMs that run device drivers - and daemon VMs use full-blown general-purpose OSs. It seems that specialized lightweight OSs, known as unikernels, would be a better fit for those. Surprisingly, to this day, driver domains can only be built from Linux. We discuss how unikernels can be beneficial in this context - they improve security and isolation, reduce memory overheads, and simplify software configuration and deployment. We specifically propose to use unikernels that borrow device drivers from existing general-purpose OSs.
Comparative analysis of PHP frameworks on the example of Laravel and Symfony

This study aims to determine which of the analyzed PHP-based design patterns – Laravel or Symfony – is a better and more universal solution for a developer. For this purpose, a comparative analysis was carried out based on the available documentation, as well as a comparison of the static and dynamic metrics obtained in the research environment of both tested patterns. As a result of a series of experiments and studies, it was established that both design patterns are an optimal and efficient solution, but their best application depends on the developer's individual needs and project requirements.
Latest advances in the development of the open-source player dash.js

The trend to consume high-quality videos over the internet lead to a high demand for sophisticated and robust video player implementations. dash.js is a prominent option for implementing production grade DASH-based applications and products, and is also widely used for academic research purposes. In this paper, we introduce the latest additions and improvements to dash.js. We focus on various features and use cases such as player performance and robustness, low latency streaming, metric reporting and digital rights management. The features and improvements introduced in this paper provide great benefits not only for media streaming clients, but also for the server-side components involved in the media stream process.
THE ROLE OF EMPOWERING LEADERSHIP IN ENHANCING THE ADAPTIVE PERFORMANCE OF EMPLOYEES

The main objective of this research is to explore the effect relationship of two main variables: (empowering leadership and adaptive performance of employees), by surveying the opinions of a number of employees at Al-Iraqia University – Baghdad Governorate. The researcher used the simple random sample method and distributed the questionnaire to a sample of employees amounting to their number is (148) in the various departments and sections of the faculties. After sorting and checking the questionnaires, the number of valid questionnaires for statistical analysis reached (141) out of the number of (143) retrieved questionnaires. Statistical analysis of the collected data was carried out using the program (SPSS v.22). The research reached to accept the main hypothesis, and concluded that the principals at Al-Iraqia University in the study sample are interested and have a great orientation towards empowering leadership, which in turn enhances the adaptive performance of employees. The results of the current research are, to the best of the researcher's knowledge, a first attempt in the context of reducing or bridging the knowledge gap between the variables of empowering leadership and adaptive performance.
SoK: Plausibly Deniable Storage

Abstract Data privacy is critical in instilling trust and empowering the societal pacts of modern technology-driven democracies. Unfortunately it is under continuous attack by overreaching or outright oppressive governments, including some of the world’s oldest democracies. Increasingly-intrusive anti-encryption laws severely limit the ability of standard encryption to protect privacy. New defense mechanisms are needed. Plausible deniability (PD) is a powerful property, enabling users to hide the existence of sensitive information in a system under direct inspection by adversaries. Popular encrypted storage systems such as TrueCrypt and other research efforts have attempted to also provide plausible deniability. Unfortunately, these efforts have often operated under less well-defined assumptions and adversarial models. Careful analyses often uncover not only high overheads but also outright security compromise. Further, our understanding of adversaries, the underlying storage technologies, as well as the available plausible deniable solutions have evolved dramatically in the past two decades. The main goal of this work is to systematize this knowledge. It aims to: (1) identify key PD properties, requirements and approaches; (2) present a direly-needed unified framework for evaluating security and performance; (3) explore the challenges arising from the critical interplay between PD and modern system layered stacks; (4) propose a new “trace-oriented” PD paradigm, able to decouple security guarantees from the underlying systems and thus ensure a higher level of flexibility and security independent of the technology stack. This work is meant also as a trusted guide for system and security practitioners around the major challenges in understanding, designing and implementing plausible deniability into new or existing systems.
Blockchain: The Gateway to New Technology and its Applications for Academic Libraries

The block chain is a distributed database that stores and shares records of all transactions or digital events that have taken place. Each transaction is double-checked by the majority of the system's members. It holds every single transaction's record. The block chain is a novel technology that is being used to validate and store transaction records for online crypto currencies such as Bit coin. Transactions cannot be retracted, copied, or faked because the system is redundant and distributed. The block chain has potential applications in domains other than online money, such as public libraries. This column will briefly outline what a block chain is and how it is used, as well as potential future uses that librarians and Academic Library practitioners would be interested in, as well as some of the system's flaws. Information workers may be able to utilize and benefit from this technology in a variety of ways.
Understanding code snippets in code reviews

Code review is a mature practice for software quality assurance in software development with which reviewers check the code that has been committed by developers, and verify the quality of code. During the code review discussions, reviewers and developers might use code snippets to provide necessary information (e.g., suggestions or explanations). However, little is known about the intentions and impacts of code snippets in code reviews. To this end, we conducted a preliminary study to investigate the nature of code snippets and their purposes in code reviews. We manually collected and checked 10,790 review comments from the Nova and Neutron projects of the OpenStack community, and finally obtained 626 review comments that contain code snippets for further analysis. The results show that: (1) code snippets are not prevalently used in code reviews, and most of the code snippets are provided by reviewers. (2) We identified two high-level purposes of code snippets provided by reviewers (i.e., Suggestion and Citation) with six detailed purposes, among which, Improving Code Implementation is the most common purpose. (3) For the code snippets in code reviews with the aim of suggestion, around 68.1% was accepted by developers. The results highlight promising research directions on using code snippets in code reviews.
Research On Path Planning of Mobile Robot Based On Improved RRT* Algorithm

Rapidly-Exploring Random Tree (RRT) has been widely used in robot navigation as a fast and efficient path planning method. Rapidly-Exploring Random Tree Star (RRT*) is one of the extensions of RRT, which outperforms the RRT algorithm because it can approximate the optimal path as the number of iterations increases. However, as the number of sampling points increases, the time to obtain the optimal path is too long, the algorithm converges significantly slower, and it is difficult to pass narrow obstacles in a short time. In this paper, we propose an improved RRT* algorithm, which first samples nodes in the dynamic target region to narrow the sampling range; expands tree nodes by target biasing strategy to reduce the randomness of tree growth; and generates more sampled nodes near the narrow obstacle nodes to make them have a higher probability of passing through the narrow channel. Simulation results show that our algorithm can find feasible paths quickly. Compared with the original RRT* algorithm, the algorithm performs better in terms of time and path cost.
FastText Word Embedding and Random Forest Classifier for User Feedback Sentiment Classification in Bahasa Indonesia

User feedback nowadays become a platform for software developer to identify and understand user requirements, preferences, and user’s complaints. It is important for the developer to identify the problem that exist in user feedback. According to software growth, user amount also growth. Read and classify one by one manually are wasting time and energy. As the solution for the problem, sentiment analysis system using Random Forest Classifier which use word embedding as the feature extraction is made to help to classify which feedback is positive, neutral, or negative. Random Forest Algorithm is chosen because it gives the best performance, even its need the larger resources. Furthermore, with word embedding, the words which has semantic or syntactic similarities will be detected. Word embedding does not need stemming and stop word removal, so the context of the sentences keep remains. This research is made to implement word embedding to classify sentiment of user feedbacks using Random Forest Classifier. 70.27% accuracy, 80% precision, 54 recall and 54% F1 score is reached when BYU dataset (200 dimension) as embedding dataset with the train and test ratio 80:20.
Specifics of Happiness Felt Over by Students with Different Life-Purpose Orientations

Introduction. The integral concept of happiness relies on understanding the influence on its feeling specifics, the external conditions of life. Moreover, it depends on the individual psychological properties and states of the personality and its semantic and value orientations. Despite a great deal of works devoted to this phenomenon, there are practically no publications in the scientific literature on the relationship between the degree of happiness experienced by students and their meaning-of-life orientations, which determined the purpose of our study – to study the features of the relationship between meaning-of-life orientations and the level of happiness of students. Materials and Methods. The results of an empirical study among students of the Mordovia State University in various fields of training are presented. The sample size is 110 people. The study was conducted using several test methods: “Oxford Happiness Questionnaire” by M. Argyll, “Existence Scale” by A. Langle and K. Orgler (translated by S. V. Krivtsova), “Life-Sense Orientations (LSS)” by J. Crumbaugh and L. Makholik (adapted by D. A. Leontiev). Spearman’s rs rank correlation test, factor, cluster analysis and Mann-Whitney U test were used for mathematical processing. Results. In the course of the study, the features of life orientations, existential values of students and their level of happiness were studied. The results show that the level of happiness, meaningfulness and fulfillment of life among students does not depend on the profile of their education (natural science or humanities). Statistically significant correlations between the level of happiness and the degree of fulfillment of life, self-transcendence, freedom, personality, existentialism, self-distancing, as well as the meaningfulness of students' life, were revealed. As a result of factor analysis, three groups of factors were identified that link the indicators of meaningfulness, existentialism and fulfillment of life with the level of happiness of the subjects: “Meaningfulness of Life”, “Productivity of Life” and “Level of Happiness”. Discussion and Conclusion. The conclusions made by the authors contribute to the development of ideas about the dominant life orientations of students and their influence on the experience of happiness. The materials of the article can be used in teaching and psychological counseling of students to increase the degree of awareness of the meanings, goals and process of life, which can contribute to an increase in their level of happiness.
Two-particle superposition effects in two-slit interference

Entanglement can modify the interference patterns of multi-particle systems. We analyse, using the path integral formalism, a novel example of multi-particle interference and some unexplored aspects of this phenomenon by considering the two-slit arrangement with two distinguishable particles in a superposition state. The two components of entanglement, multiplicity of multi-particle terms and their coherence, can be studied separately by comparing the patterns of product, mixed and superposition states. This suggests a scheme to detect multi-particle superposition in some favourable cases. Moreover, the dependence of the effect on the entanglement degree, measured by the Schmidt number, is not a monotone.
Petrography and Heavy Mineral Studies of Lokoja Formation along Mount Patti North Central Nigeria: Implication for provenance Studies

The Southern Bida basin consists of the Lokoja, Patti, and Agbaja formations. This study focuses on the Lokoja formation and samples gotten were used for petrography and heavy mineral analysis. Results of all analytical techniques employed in the study are presented here. A critical assessment of each set of results and their integration aided the proper interpretation and useful discussion. This study focuses on the Southern Bida Basin, specifically the Lokoja Formation because the exposures of Patti are poorly exposed. Outcrop samples were obtained from the exposed sections of the study area in Kabawa and Robinson street respectively. Different features were observed, such as the thickness of the exposure, the nature of the lithology, color, and sedimentary structures. The dominant lithologies in the area include sandstone and ironstone. The sandy facies are generally arkosic characterized by poorly sorted very fine to conglomeratic sandstone sequence. Laboratory investigations of samples included petrography and heavy mineral analysis. Sandstone samples were collected from the study area. Each sample was divided into two parts: the first part for petrographic studies and the second part for heavy mineral analysis.
Performance Simulation of a Traffic Sign Recognition based Neural Network on Cadence’s Tensilica Vision P6 DSP using Xtensa Xplorer IDE

Advanced Driver Assistance System (ADAS) technology is currently in an embryonic stage. Many multinational tech companies and startups are developing a truly autonomous vehicle that will guarantee the safety and security of the passengers and other vehicles, pedestrians on roads, and roadside structures such as traffic signal poles, traffic signposts, and other structures. However, these autonomous vehicles have not been implemented on a large scale for regular use on roads currently. These autonomous vehicles perform many different object detection/recognition tasks. Examples include traffic sign recognition, lane detection, pedestrian detection. Usually, the person driving the vehicle performs these detection/recognition tasks. The main goal of such autonomous systems should be to perform these tasks in real-time. Deep learning performs these object recognition tasks with very high accuracy. The neural network is implemented on the hardware device, which does all the computation work. Different vendors have many different hardware choices that suit the client's needs. Usually, these neural networks are implemented on a CPU, DSP, GPU, FPGA, and other custom-made AI-specific hardware. The underlying processor forms a vital part of an ADAS. The CNN needs to process the incoming frames from a camera for real-time object detection/recognition tasks. Real-time processing is necessary to take appropriate actions/decisions depending on the logic embedded. Hence knowing the performance of the neural network (in terms of frames processed per second) on the underlying hardware is a significant factor in deciding the various hardware options available from different vendors, which CNN model to implement, whether the CNN model is suitable to implement on the underlying hardware depending upon the system specifications and requirement. In this paper, we trained a CNN using the transfer learning approach to recognize german traffic signs using Nvidia DIGITS web-based software and analyzed the performance of this trained CNN (in terms of frames per second) by simulating the trained CNN on Cadence's Xtensa Xplorer software by selecting Cadence's Tensilica Vision P6 DSP as an underlying processor for inference.
Recognition of Handwritten Flowcharts using Convolutional Neural Networks

Currently, artificial vision is used in an endless number of tasks from domestic tasks to industrial and educational ones since with it those tasks can be streamlined because of having an automated process. This project explores the problem of handwritten information recovery, specifically the flowcharts used in the programming and designing of algorithms,approaching a solution with artificial vision, and proposes a pipeline able to recognize the elements of a handwritten flowchart using convolutional neural networks in order to generate code source in the C programming language equivalent to the recognized diagram, in addition the digitalized version of the flow diagram, thus automating the various tasks, having as a final result a file with .c extension with the source code, the compilation output and an image in .png format with the digitization of the diagram.
Bright Field Droplet Image Recognition Based on Fast Hough Circle Detection Algorithm

Digital polymerase chain reaction (PCR) bright-field droplet image recognition not only requires manual marking of the diameter and length, which is time-consuming and laborious, but also the existing circle detection algorithm has the problems of slow recognition speed and poor diameter measurement accuracy. In response to these problems, this paper proposes a fast Hough circle droplet detection algorithm. The algorithm mainly includes three steps: firstly, use the gradient information of the edge points and the geometric properties of the circle to determine the candidate circle; secondly, if the distance from the edge point in the set range to the center of the candidate circle is approximately equal to the radius, then the circle is determined as a true circle; finally, the circle with the largest radius among the neighboring true circles is taken as the final detection result. It is verified by comparative experiments that the algorithm can significantly improve the efficiency of droplet recognition and the accuracy of diameter measurement.