Reviewerly/exHarmony huggingface dataset:
Techniques for secure distributed systems

Abstract In recent networked world, more of the times computers work not isolation. They work with each other in order to satisfy communication purpose, processing, transfer of data, saving, etc., the systems can be described as distributed when it contain several systems work together in harmonic way with each other that are geographically lies over far distance. The security of distributed systems is very important issues and it may be describe as the most difficult part in the design for a system. In this paper the basic principles of distributed system is presented, then the security vulnerabilities are shown and the recent technique that used for solving the security problems are discussed and also analysis for their performance is done where the advantages and disadvantages with robustness for each technique are shown. So as conclusion for the results that are gotten by researchers, the selection of security technique depends on what really need to be protected, type of distributed systems and available resources. Although there are several efficient techniques, but the most powerful one is using of biometric and encryption for authentication and security purposes.
ATC: An Automatic Text Comparison Tool Based on Diff Algorithm

Text comparison is to look up the differences and commonness between texts, so it is widely used in editing, duplicate checking, keywords extraction and so on. To improve the efficiency of batch text comparison, we have designed an automatic text comparison tool (ATC) based on Diff algorithm. According to the pipeline design mode, ATC combines multiple processes such as multiple data sources access, file filtering, de-duplication, extraction, comparison, and display, while using multithreading technology to accelerate the text comparison process. The experimental results show that ATC can be applied to multilingual text comparison, and the introduction of multithreading technology has also greatly improved the comparison efficiency.
Towards an Integrated Solution for Intelligent Visual Data Discovery

Visual data exploration enables users to identify trends and patterns, generate and verify hypotheses, and detect outliers and anomalies. However, the growing scale and complexity of data exploration present a barrier to discovering useful, actionable insights from data. Often, users may not know which visualizations would lead to desirable insights, resulting in wasted efforts in manual searching. Users can also be overwhelmed or lose track of where to look across a large potential space of attributes and filter combinations, leading to missed insights or even potentially erroneous conclusions. My thesis research involves designing systems that democratize data science by providing automated guidance to analysts in visual data exploration. My current work includes accelerating manual data exploration tasks and supporting user exploration in analytical workflows. Finally, I will describe future work in developing a high-level language for addressing analytical inquiries.
Class Based Multi Stage Encryption for Efficient Data Security in Cloud Environment Using Profile Data

The security issues in the cloud have been well studied. The data security has much importance in point of data owner. There are number of approaches presented earlier towards performance in data security in cloud. To overcome the issues, a class based multi stage encryption algorithm is presented in this paper. The method classifies the data into number of classes and different encryption scheme is used for different classes in different levels. Similarly, the user has been authenticated for their access and they have been classified into different categories. According to the user profile, the method restricts the access of user and based on the same, the method defines security measures. A system defined encryption methodology is used for encrypting the data. Moreover, the user has been returned with other encryption methods which can be decrypted by the user using their own key provided by the system. The proposed algorithm improves the performance of security and improves the data security.
English Machine Translation Model Based on Modern Intelligent Recognition Technology

The statistical machine translation method based on the maximum entropy is adopted. The best combination mode of different English language features is obtained after obtaining related parameters by means of direct maximum entropy model training, so as to resolve the problem of part of structural ambiguity in the massive English language, and improve the accuracy of English machine translation. The experimental results show that the designed English machine translation model has high translation accuracy and stability.
The Design Of Wheelchair Systems With Raspberry Pi 3-Based Joystick Analog And Voice Control

Abstract In this study, an electric wheelchair that combines two controls: joystick analog and voice control is designed. IC MCP3008 is used to navigate wheelchairs by using Josytick, where joystick analog data will be converted into digital data. The movements resulted from the joystick analog on the xAxis axis (horizontally) are the right turn and left turn, and on the yAxis axis (vertically) are forward and backward. The movements on the yAxis and xAxis axes set by the user affects the speed of the wheelchair. Meanwhile, the AMR-Voice application on Android is used to navigate wheelchairs by using sound. There are five commands in this voice control: “Forward”, “backward”, “left”, “right”, “stop”. The order will be sent to Raspberry Pi 3 via the HC-06 module to then be recognized for the command. If the voice commands are received accordingly, Raspberry Pi 3 will provide an activation signal to the motor driver to move the wheelchair in the direction corresponding to the command given by the user. Voice control testing on wheelchairs is tested in quiet rooms and noisy rooms. The results of the wheelchair control testing with sound indicate that the accuracy and speed of the wheelchair response rely heavily on Internet connection and room conditions. The average response when the condition of the room is quiet is 0.16 s and when the condition of the room is noisy is 5.18 s. Wheelchairs with joystick control and the voice made can be used for the disabled, whether for those who can move their fingers or not, at a low cost so that they can be an alternative in developing countries.
Assessing Indonesian Military Camouflage using Camouflage Similarity Index (CSI) Algorithm

Military camouflages is one of the research areas in human factors & ergonomics and purchasing a new military camouflage design has been a critical issue in the Indonesian military. The purpose of this study was to assess the existing Indonesian military camouflage effectiveness using Camouflage Similarity Index (CSI) algorithm. CSI algorithm shows a value between 0 to 1 and the lowest value 0 is achieved if the selected camouflage perfectly blends with the selected background. A total of 8 Indonesian military camouflage was evaluated under 5 different locations (20x50 pixels) from one selected woodland background. Each location had different L*, a*, and b* values. ANOVA test showed that there was a significant effect of camouflage on CSI. Post-hoc Tukey test was utilized to derive the difference between each camouflage. This study represents a first attempt to assess the effectiveness of Indonesian military camouflages and the results of this study could be very beneficial for military organizations, academicians, and camouflage manufacturers particularly related to purchasing decisions.
Interacting Across Contexts: Augmented Reality Applications for Developing the Understanding of the Anthropocene

Augmented reality (AR) provides new ways that humans can engage with the world. The affordance of AR to mediate human–environment relationships addresses some major challenges people face in understanding the idea of the Anthropocene, which refers to the current geological stage of our planet, where human impact is the dominant force. This is important because being aware of how human activities change the planet is constructive to building the human–environment relationship that is sustainable for the future. As a result, with the growing popularity of mobile AR applications, pioneering designs in the last decade attempt to integrate AR with the Anthropocene. In this chapter, we present a systematic review of these AR applications guided by qualitative content analysis methods. Results indicate that AR creates multiple learning opportunities across contexts for understanding the Anthropocene based on particular forms of interaction. Implied in these interactions are two major approaches (exploration and creation) that the designers adopted to engage users with the theme context of the Anthropocene. The findings of the review can inform the future design of AR applications that mediate more meaningful interactions with the Anthropocene.
New Image Encryption Scheme Using Chaotic Maps

Data on the Internet is always vulnerable to different types of attacks due to the public nature of the Internet, which is the only source of communication all over the world. To protect sensitive information, many encryption techniques like Gingerbreadman chaotic map and S8 permutation-based image encryption scheme are proposed. However, due to security issues in these techniques, 3D Logistic map based confusion and diffusion processes are employed which solve those security problems.3D Logistic map was used to eliminate the strong correlation between the plain text image pixels. A random matrix is created in the diffusion stage via a 3D Logistic map and XORed with the scrambled image. The final ciphertext image is extracted using existing Gingerbread-man chaotic map based S-Box. The proposed scheme is analyzed experimentally and statistically using key space analysis, information entropy analysis, and differential analysis. Results are also validated via the Number of Pixel Rate Change (NPRC) to ensure the security and robustness of the proposed scheme.
HDR image reproduction based on visual achromatic response

High-dynamic range image reproduction using tone-mapping algorithms are used for image processing to reduce the dynamic range of a real scene to be displayed on low-dynamic range devices. General tone-mapping methods are associated with the determination of local parameters for tone compression and the halo artifact connected to detail enhancements. This paper proposes a lightness-preserved tone-mapping method and a halo-artifact reduction method based on the property of visual achromatic responses. For the reproduction of the visual perception of the real scene on displays, the sensitivity parameter of the sigmoidal transfer curves is optimized for the lightness-preserved tone mapping, and anti-halo image decomposition method is applied for the halo-artifact reduction. In results, it is confirmed that the proposed method improves the performance of the tone-mapping method effectively.
Designs and Comparisons of Facial Direction Detection Technology with YOLO Based Deep Learning Networks

By utilizing the deep learning model to develop the pedestrian facial direction classifier, in this paper, the proposed You only look once (YOLO)-based deep-learning technology is applied to analyze the images captured by camera to identify the facial directions of pedestrians. To enhance the training effect of mirror categories, the selected images are horizontally flipped to expand the datasets. To avoid misclassification of facial directions, the softmax scheme of the original YOLOv2 model is replaced with the logistic classifier used in YOLOv3, and the improved model is called YOLOv2_ logistic. By the same parameters on the webcam captured dataset, the experimental results show that the YOLOv2_logistic has the best performances on recall, precision, and mean Average Precision (mAP), which are 85%, 81%, 86.28%, respectively. The YOLOv3 tiny has the second performances, and its recall, precision, and mAP is 81%, 80%, 78.83%, respectively. In the frame per second (fps) test, the YOLOv3 tiny has the second best performance, and it reaches 30 fps on the Xavier platform. Although the facial direction detection performance of the YOLOv3 tiny model is slightly lower than that of the YOLOv2_logistic model, the performance of fps by the YOLOv3 tiny model is more than that by the YOLOv2_logistic model.
Non-Digital Competencies for a Digital World: Why Higher Education Needs Humanities and STEM Disciplines

Forecasts on the future of the workplace abound. Predictions vary from a “smart,” network-based, and still human-centered organization of work to scenarios in which artificial intelligence and algorithms take over repetitive as well as complex jobs by 2030. Either way, questions arise regarding the set of skills that will be necessary for successful participation in the workplace and what role higher education will play in shaping and providing these skills. Currently, demand for graduates from the STEM (Science, Technology, Engineering, Mathematics) disciplines is high in politics and industry. In addition, the workforce also needs people who are able to harness technological developments for the economy as well as for society. Think tanks have described the skills necessary to establish this connection between technological progress and societal needs. They show that skills from the humanities and the social sciences are as necessary as technological capabilities because future members of the workplace—and, even more importantly, responsible members of society—need to contextualize technological developments. Thus, the challenge will be to combine digitalization in higher education with critical thinking, creativity, problem solving, communication, and social and ethical reflection.
An interactive sensory system to record and monitor human motion in physical rehabilitation

This paper briefly presents the application of an interactive sensory system to sense, record, restore, and monitor the movement of objects such as the human body. The setup, consisting of a data streamer and a software development kit (SDK), has nine degrees of freedom (DoFs): three orientation (roll, pitch, and yaw angles), three linear accelerations, and three magnetic field components. The SKD is a graphical user interface (GUI) that records, restore, and analyzes the signal received from the data streamer and presents advanced statistical analysis such as predicting the behavior of the measured data in the future. An application claimed is to provide patients with an accurate measurement that simplifies the tracking of performance and effectiveness of physical exercises and treatments. To show the proof of concept, we conducted an experimental study on the human's hand at the iRobohabilitation Laboratory, and quantified the signals measured by the sensory system in real-time.
E-learning in 21st Century Era

This study aims to reveal E-learning implementation readiness in junior high schools. This study was a quantitative study employing questionnaire as the main instrument. This study utilized six ELR (E-learning Readiness) factors, namely (1) students' readiness, (2) teachers' readiness, (3) infrastructure, (4) management support, (5) school culture, and (6) face-to-face learning tendency. These six factors were transformed into 34 statements in the questionnaire. The respondents were 59 teachers who were the members of Teacher Communication Forum or Forum Komunikasi Guru (FKG) in Indonesia. The result indicated that junior high schools in Indonesia in general were ready to use E-learning but required an improvement with an overall ELR score of 3.78. Five of the six factors proposed indicated schools' readiness. The five factors were teachers' readiness with ELR score of 3.97, students' readiness with ELR score of 3.92, infrastructure with ELR score of 3.82, management support with ELR score of 3.82, and school culture with ELR score of 3.76. The sixth factor was face-to-face learning tendency which had an ELR score of 3.39 or smaller than 3.4. Therefore, it was categorized as not ready and required improvement to be able to implement E-learning.
Identifying and Addressing Design and Policy Challenges in Online Content Moderation

My doctoral research identifies and addresses the design and policy challenges of content moderation on the levels of smaller communities and larger platforms, using a combination of interviews and surveys. My prior work studies voice-based communities on Discord, and shows that voice as a new technology brings unique challenges to community moderators and highlights the fundamental evidentiary need in content moderation. My dissertation expands on this work by (1) quantifying severity of violations as a way to address social media platforms' challenge of prioritization, and (2) empirically evaluating existing moderation approaches and design recommendations by soliciting moderator and user perceptions of them. Combining these perspectives, my dissertation will provide guidelines for improving content moderation in online communities.
Multiple Mobile Robot Path Planning in 3D Environment Using Tangent Tree Algorithm

Abstract Due to the effective applications of multi-agent systems, there is an importance to develop efficient methods to manage these systems. One of the most important methods is path planning. This paper proposes a new algorithm for the path planning of multiple mobile robots in 3D environment named Tangent Tree Algorithm. It based on the assumption that the robots have spherical shapes and can move in a 3D space like drones, other moving robots considered as obstacles for the robot. The robot path performed using two modes: In the first mode, the robot moves in a straight line to the tangent point of assumption sphere. In the second mode, it moves around the assumption sphere. The assumption sphere locates at the calculated collision 3D point with the other robots. A number of possible paths constricted using these modes. A Tangent tree algorithm for multi-robot formed and the minimum path is determined based on minimizing this tree. Simulation results indicate that the new algorithm is superior to other algorithms in terms of both the path cost and computation required. Furthermore, this algorithm does not change the velocity of the robots; it only depends on the orientation.
Saying "Yes, and..." to learning: The educational process as improvisation

The paper analyzes the various aspects of the possibilities for the implementation of improvisation activities in the process of adult education. The author presents some of the theoretical assumptions that suggest the importance of improvisation for learning at all ages, along with its essential traits that construct and define it. Furthermore, the paper indicates the profound permeation of the capacity for improvisation and human development. It is through this connection that the andragogical interest for the techniques of improvisation stems from. As part of such analysis, improvisation was perceived as a methodology of learning and a manner of enriching the educational process by a collective activity of creative development. The approach that is used in this paper to interpret improvisation in relation to adult education and learning perceives improvisation as a fundamental human capacity, a manner and type of an inherent capacity for play, which is a precondition and driver of human development. By favoring the model of developmental learning, improvisation presents a possible path and direction of inserting the developmental element in the process of adult education, which in contemporary times demonstrates diminishing spontaneity and creativity. In that sense, this paper should be perceived as an inclination to initiate an improvised collective process involving everyone ready to inspire others with their desire and readiness for play.
Using 3D animation combined with augmented reality for promotion media: Case study of STMIK Bina Patria

Abstract STMIK Bina Patria as the first computer academy in Magelang, prepares students to have competitive advantages and improving added value in the field of Science and Technology. Since the establishment of STMIK Bina Patria in 1999, this institution has experienced significant progress, seen from the increasing number of students and improvement of the infrastructure to support teaching and learning activities. Brochures and billboards are used for promoting the campus. But the impact is far from its expectation. Seeing these conditions, improvement is needed to intensify media promotion functions at STMIK Bina Patria. Therefore, the researcher constructs Augmented Reality 3D animation of STMIK Bina Patria. Augmented reality (AR) is constructed using Multimedia Development Life Cycle (MDLC) research method consisting of Concept, Design, Material Collecting, Assembly, Testing and Distribution. Constructing begins by taking pictures, followed by designing STMIK Bina Patria building using Blender software. Unity and Vuforia Library software are used to design the AR application. The results of this study are Augmented Reality introduction media Application of S TIMIK Bina Patria Magelang which can be run on an Android. By using this media, it is expected that people are more interested in studying at STMIK Bina Patria.
What you see is what you get

Analyzing delivered QoE for Adaptive Bitrate (ABR) streaming over cellular networks is critical for a host of entities including content providers and mobile network providers. However, existing approaches mostly rely on network traffic analysis. In addition to potential accuracy issues, they are challenged by the increasing use of end-to-end network traffic encryption. In this paper, we explore a very different approach to QoE measurement --- utilizing the screen recording capability widely available on commodity devices to record the video displayed on the mobile device screen, and analyzing the recorded video to measure the delivered QoE. We design a novel system VideoEye to conduct such screen-recording-based QoE analysis. We identify the various technical challenges involved, including distortions introduced by the screen recording process that can make such analysis difficult. We develop techniques to accurately measure video QoE from the screen recordings even in the presence of recording distortions. Our evaluations demonstrate that VideoEye accurately detects important QoE indicators including the track played at different points in time, and stall statistics. The maximal error in detected stall duration is 0.5 s. The accuracy of detecting the displayed tracks is higher than 97%.
A Procurement Data Standard Tool for State Universities and Colleges

Abstract The study presents the development of a procurement data standard tool to promote transparency for compliance monitoring on the procurement process in all government agencies. Extreme programming was utilized as a methodology during the development of the system. Procurement Data Standard was validated and evaluated using the USE Questionnaire to check the usability of the data standard tool that focuses on three factors namely: usefulness, ease of use and satisfaction and get its equivalent based on the respective percentage, for usefulness is 4.12 (30%); ease of use is 4.25 (40%) and satisfaction is 3.96 (30%). Based on the result the overall weighted mean got a total of 4.11 and was interpreted as Very Satisfactory, it clearly indicates that the developed standard tool is easy to use and useful. This study will aid government agencies to promote transparency and accountability in Procurement Activities of the Government.