Reviewerly/exHarmony huggingface dataset:
Pengujian Blackbox Menggunakan Teknik Equivalence Partitions pada Aplikasi Petgram Mobile

Software testing aims to evaluate whether an application is functioning correctly or some errors must be fixed so that the quality of the application is said to be good. Some of the testing methods include Blackbox testing and Whitebox testing, which are often used by testers to evaluate the application according to stakeholder needs or not. This article will examine the Blackbox testing method for evaluating the Petgram mobile application. Evaluations are carried out on the Petgram mobile application on the functional register, login, and make posts. One of the Blackbox method techniques is Equivalence Partitions, a test based on input on each form in the Petgram mobile application, where there are expected results and actual results and successful or failed conclusions. The study results show that there are still some functional failures, especially in the functional register and making posts. The hope is that with the results of this test, the developer can improve it so that the Petgram mobile application becomes of good quality.
PERSONAL ASSISTANT FOR BLIND PEOPLE

Visual impairment is one of the major problems that people face. They need human assistance to do many activities in daily life. This paper describes the designation of the smart assistance device to help blind people by using multiple sensors.  The device mainly provides basic services including object detection, falling detection, water detection, heart-beat rate detection, temperature detection and emergency button to send alert messages which makes day to day activities easier for them. The microcontroller will retrieve data and it passes vibrations to the user through sensors which will notify about detected things. It is an efficient device and it would be great assistance to blind person.
A generalized framework for analytic regularization of uniform cubic B-spline displacement fields

Image registration is an inherently ill-posed problem that lacks the constraints needed for a unique mapping between voxels of the two images being registered. As such, one must regularize the registration to achieve physically meaningful transforms. The regularization penalty is usually a function of derivatives of the displacement-vector field, and can be calculated either analytically or numerically. The numerical approach, however, is computationally expensive depending on the image size, and therefore a computationally efficient analytical framework has been developed. Using cubic B-splines as the registration transform, we develop a generalized mathematical framework that supports five distinct regularizers: diffusion, curvature, linear elastic, third-order, and total displacement. We validate our approach by comparing each with its numerical counterpart in terms of accuracy. We also provide benchmarking results showing that the analytic solutions run significantly faster -- up to two orders of magnitude -- than finite differencing based numerical implementations.
Personalized recommendation algorithm based on online comment sentiment analysis

Abstract Artificial intelligence is one of the many branches of computer science. With the continuous development of information technology and computer networks, artificial intelligence technology has also received tremendous support and rapid development. In the computer field, recommendation systems can be said to be the most extensive and successful application of artificial intelligence technology. This paper focuses on the problems of cold start and low recommendation accuracy caused by sparse rating data in traditional recommendation systems, proposes a personalized recommendation algorithm based on online comment sentiment analysis. The algorithm uses feature-level sentiment analysis to mine user preference information implicit in comments, and finally implements recommendations based on user ratings and preference information. Experiments show that the algorithm proposed in this paper can effectively make up for the shortcomings of traditional collaborative filtering recommendation algorithms, and is of great help in improving user cold start and the quality of recommendation results.
LibGuides: Picture Books are NOT Just for Little People: Home

This guide will give to research to support unit picture books in all grade. It will also give you list of books that would provide good background and high interest for students based on topic.
Optimizing Student Photography Skills Through Development of Project Based E-Learning in Photography Courses

Even at this time photography is becoming a trend, apparently it does not have a major impact on college students' mastery of theoretical concepts in photography courses.The reality that happens is that the understanding of the basic concepts of photography is not very good, so it has implications for his skills.Based on the data obtained in the field, student learning outcomes are not satisfactory.Based on this phenomenon, development research is carried out to produce e-learning products based on project-based learning model to improve student photography learning outcomes.The development process carried out refers to the stages of the ADDIE development model which involves media experts, learning design experts, learning content experts as media validators and semester II students as research subjects.This study aims to 1) describe design the project based learning (PjBL) based e-learning; 2) Describe responses of experts and students to quality of project based learning (PjBL) Based e-learning wich had been developed; 3) To determine the effectiveness of the product (project based learning (PjBL) Based e-learning) in improving student photography learning outcomes.
A Method for Detecting Interaction between 3D Hands and Unknown Objects in RGB Video

Abstract We propose a model that can extract 3D position of hand and object in per-frame of RGB videos through a single feed-forward neural network and a zero-shot learning classifier, and understand unknown hand-object interactions in the entire video through an interactive temporal module. The process is trained end-to-end, without depth images or annotated coordinates as input, which has good application prospects in real life.
A novel scatterer model for the security of key generation based on DISC model

Abstract Physical layer security is a method of extracting encryption keys according to the randomness of reciprocal propagation channels between legitimate users, and the security under normal circumstances is ensured according to the decorrelation between these channels and those tapped by eavesdropper. However, evidences show that in some scenarios, such as the environment of quasi-static or insufficient scattering, the tapped channel still has a strong correlation with the legitimate channel, leading to bits leakage and security imperilment of key generation. The effect of introducing scatterers has been experimentally proved, however, these studies are based on fixed positions or special models and there is yet a lack of research on the influences brought by various scatterer distributions. In this paper, we introduce scatterers into single-bounced DISC model and control their distributions through a probability density function with two degrees of freedom, aiming to deeply investigate the impacts of scatterer distribution on channel decorrelation as well as key security. Simulation results prove that spiral correlation between tapped channel and legitimate channel can be effectively reduced by increasing scatterers and arranging them around the legitimate receiver, which make contributions to reduce key leakage and improve security.
GEPSA, a tool for monitoring social challenges in digital press

This papers presents a platform for monitoring press narratives with respect to several social challenges, including gender equality, migrations and minority languages. As narratives are encoded in natural language, we have to use natural processing techniques to automate their analysis. Thus, crawled news are processed by means of several NLP modules, including named entity recognition, keyword extraction,document classification for social challenge detection, and sentiment analysis. A Flask powered interface provides data visualization for a user-based analysis of the data. This paper presents the architecture of the system and describes in detail its different components. Evaluation is provided for the modules related to extraction and classification of information regarding social challenges.
LibGuides: Library Information: Materials & Services

Information related to NPU Library services and resources. Provides policies, and fees for loaning of books & magazines, and duplications services.
Fast signature preserving LWIR detail uncovering and image enhancement with dedicated color tables

There are powerful image enhancement methods using, e.g., contrast stretching or retinex to compute enhanced LWIR or MWIR grayvalue images. But some methods have considerable computation times. Additionally, some applications demand object signatures to remain structurally unchanged for further evaluations. Furthermore, since humans can distinguish only far less than 100 grayvalues, but numerous different colors, grayvalue visual- ization of thermal images is considerably suboptimal anyway. So, there are several reasons to use pre-defined, fast color tables. But this pseudo-coloring method is often limited in practice, especially when structures with small thermal differences need to be examined. As a solution, this paper explores different possibilities to reach a maximum benefit for detail uncovering by generating high dynamics in color, saturation, and/or brightness. The challenge is to balance detail uncovering with local as well as global image understandability and to find a long discrete 1D path in 3D color space without visible ambiguities. On the one hand, neighboring colors on this path need to have distances in color space big enough for good detail uncovering. On the other hand, non-neighbor parts of the path need to have even bigger color distances to distinguish high temperature differences. Different color tables are generated and compared. The given results show the reached benefit.
Max Your Vista-Integrated Mobile Field App Investment

Discover how to get the most out of your investment in Vista-connected field service management Collecting data via mobile devices in the field ...
Inovasi Media Pembelajaran Berbasis Markeless Augmented Reality Untuk Meningkatkan Minat Belajar Siswa

The COVID-19 (Coronavirus Disease) pandemic affects policy changes and reforms to be implemented in various sectors, one of which is the education sector. On March 17th 2020, the minister of education and culture of the Republic of Indonesia issued a circular, regarding online learning. Alternatives that can be used in learning during the pandemic are to use digital technology and several supporting learning media such as zoom, google classroom, WhatsApp, and other applications. Throughout online learning, there are many complaints from students who are not happy with learning online. Therefore, there is a need for learning media that can help teachers to make students more interested and independent in learning during the COVID-19 pandemic and the new normal era, namely the Meaning of Learning Markerless Augmented Reality-Based Learning Media. The purpose of this research is to create alternative learning media that can be used in creating an interesting, fun, and interactive learning atmosphere during the pandemic and new normal era. By using Markerless Augmented Reality technology as a learning medium, students can learn the material more easily and pleasantly by making observations, so as to increase their interest and understanding of a lesson. The method we use is using descriptive analysis and primary data search to identify the problems stated above. The idea implementation is designed by making a prototype as well as finding primary data with a questionnaire. Primary data is used to reinforce ideas so that ideas can answer problems. This idea uses qualitative and exploratory analysis so that the planned idea can be implemented properly. And of course, this learning media can help the learning process online.Keywords: Augmented Reality, Arti Learning, New Normal
Trends In Critical Reading Skills Research In The Journal Of Indonesian Language and Literature Education In PPJB-SIP

The 21st century requires that every individual has a critical ability to receive, process, and understand diverse information.This study aimed at answering the questions (1) what are the research profiles of critical reading skills from year to year? and ( 2) what are the profiles of the research subjects used to determine critical reading skills?The research method in this study was content analysis.The sources of the data in this study were 113 journals written in the PPJB-SIP website and database.This study's data were the results of the content analysis of research articles on critical reading skills.The instrument used in this study was a content analysis guideline.The results showed a number of critical reading skill studies conducted from 2011-2020 with the highest results in 2015-2017.Besides, the research subjects were dominated by undergraduate students.This research would give valuable information about critical reading skills profiles and become a basis to activate critical reading skills amid the digital information era.
What’s data got to do with it?

Continued advancements in adversarial attacks have crippled neural network performance. These small pixel perturbations can go undetected and cause networks to misclassify with high confidence. The motivation for this paper was to investigate how various sensor modalities and network models respond to adversarial attacks. It is important to realize that the large diversity in neural network architectures makes it difficult for any analytical conclusions to be made that generalize across any given neural network. For this reason, we share the statistical analyses performed which could be applied to any network under review. General observations gained from this analysis are also shared which indicated that network classification accuracy is not just a function of the network model but the data as well.
Development of Breast Cancer Diagnosis System Based on Fuzzy Logic and Probabilistic Neural Network

Breast cancer is one of the most common kinds of cancers that infect females in the whole world. It has happened when the cells in breast tissues start to grow in an uncontrollable way. Because it leads to death, early detection and diagnosis is a very important task to save the patient's life. Due to the restriction of human observers, computer plays a significant role in detecting early cancer signs. The proposed system uses a multi-resolution analysis and a top-hat operation for detecting the suspicious regions in a mammogram image. The discrete wavelet transform feature analysis is utilized for extracting features from the region of interest. Fuzzy Logic (FL) and Probabilistic Neural Network (PNN) are utilized for classifying the tumor into normal or abnormal. The differences between the proposed system and other researches are the use of adaptive threshold value depending on each image, by using Discrete Wavelet Transform (DWT) in both segmentation and feature extraction phases, which decrease complexity and time. Additionally, the detection of more than one tumor in the breast mammogram image and the utilization of FL and PNN work on increasing the system efficiency that led to raising the accuracy rate of the system and reducing the time. The obtained results of accuracy, sensitivity, and specificity were equal to 99 %, 98 %, and 47 %, respectively, and these results showed that the proposed system is more accurate than the other previous related works.
Multilingual Slavic Named Entity Recognition

Named entity recognition, in particular for morphological rich languages, is challenging task due to the richness of inflected forms and ambiguity. This challenge is being addressed by SlavNER Shared Task. In this paper we describe system submitted to this task. Our system uses pre-trained multilingual BERT Language Model and is fine-tuned for six Slavic languages of this task on texts distributed by organizers. In our experiments this multilingual NER model achieved 96 F1 score on in-domain data and an F1 score of 83 on out of domain data. Entity coreference module achieved F1 score of 47.6 as evaluated by bsnlp2021 organizers.
Subject Research, Course Guides, Documentation: Hyperlinked Stories with Twine: Adding Links

This guide introduces Twine as a lightweight and open-source tool to craft your own hyperlinked stories and games.
Sistem Informasi Manajemen Rumah Sakit Dalam Meningkatkan Efisiensi : Mini Literature Review

Healthcare services are the main topic because of the high complexity challenges in the health sector. The purpose of this study is to determine the implementation of Hospital Information System (HIS) in increasing the efficency of healthcare services. The method used in this article is literature searches related to Hospital Information System. The writing arrangement based on the mind map that is structured to answer scientific questions according to the purpose of this article. The results showed that Hospital Information System can minimize the complexity of healthcare services by increasing organizational efficiency through innovation in developing information system based on business process management, service automation, reducing costs, improving hospital performance, which aims to develop human resources, organizational development, and technological quality improvement to achieve efficency in healthcare services.
Pengaruh Nilai Mata Kuliah Micro Teaching Dan Praktik Magang 3 Terhadap Minat Menjadi Guru Pada Mahasiswa Program Studi Pendidikan Akuntansi Fkip UMS Angkatan 2016

The purpose of this research is to find out: 1) To find out the influence of the value of micro teaching courses on the interest of becoming a teacher in accounting students of the FKIP UMS 2016 Study Program. Accounting Education Faculty of Mathematics and Natural Sciences UMS 2016. 3) To find out the influence of the value of micro teaching courses and internship practice 3 together on the interest of becoming a teacher in students of the Faculty of Education Education Study Program FKIP UMS 2016. The research method used is quantitative methods with the entire population FKIP UMS Accounting Education class of 2016. Samples were taken as many as 169 students with proportional random sampling. The results of the regression analysis obtained the regression line equation: Y = 27.795 + 0.678X1 + 0.949X2. The equation shows that the interest in becoming a teacher is influenced by the value of micro teaching courses and the practice of apprenticeship 3. 1) The value of micro teaching courses on interest in becoming a teacher is acceptable. This is based on multiple linear regression analysis (t test) it is known that tcount> t table, 7,414> 1,960 and significance value t table, ie 10.254> 1.960 and significance value Ftable, which is 156.683> 3,000 and a significance value <0.05, which is 0.000. 4) The coefficient of determination (R2) of 0.654 indicates that the magnitude of the effect of the value of micro teaching courses and the value of apprenticeship practice 3 on interest in becoming a teacher is 65.4%, while the rest is influenced by other variables
CCS Library: Interlibrary Loan (ILL): Overview

This guide covers how interlibrary loan (ILL) works at CCS Library and includes the forms needed to request materials from external partners
EXPERT SYSTEM FOR TROUBLESHOOTING LAPTOP MOTHERBOARD DAMAGE USING FORWARD CHAINING METHOD AT BUDI DARMA UNIVERSITY COMPUTER LAB

The development of laptop hardware technology in the 21st century is increasingly rapid to support information technology that is increasingly easily accessed. Laptops have an important role in helping human activities, especially in teaching and learning activities. Not infrequently a laptop or better known as a laptop as most students and lecturers and even students who sit in secondary education have started to use it. In national tertiary education, the entire campus requires both public and private universities to have laptop laboratories. Along with these developments in the case of laptop usage is getting bigger.
Watermarking public‐key cryptographic functionalities and implementations: The case of encryption and signatures

A watermarking scheme for a public-key cryptographic functionality enables the embedding of a mark in the instance of the secret-key algorithm such that the functionality of the original scheme is maintained, while it is infeasible for an adversary to remove the mark (unremovability) or mark a fresh object without the marking key (unforgeability). A number of works have appeared in the literature proposing different definitional frameworks and schemes secure under a wide range of assumptions. In the previous work [1, 2], the authors proposed a meaningful relaxation of the watermarking model and gave constructions that allow direct watermarking of popular cryptographic schemes (e.g. ElGamal Encryption). A definitional framework for watermarking public-key cryptographic functionalities and implementations which covers both deterministic (e.g. decryption) and probabilistic (e.g. signing) secret-key algorithms is provided. The authors’ work unifies the previous results of [1, 2] where deterministic and probabilistic circuits to be watermarked as separate cases are considered. The constructions of [1, 2] were previously presented as extended abstracts missing rigorous security proofs. The authors prove those constructions secure under their new, unified framework. In the authors’ schemes secret detection of the watermark is provided, and security under minimal hardness assumptions assuming only the existence of one-way functions, is proved.
LibGuides: Education: Database Help

This Library Guide will help students find the resources they need for their education research.
Sistem Informasi Cuti Pada Badan Pengelolaan Keuangan Aset Daerah di Sumsel Berbasis Web

The leave application system at BPKAD South Sumatra currently still uses manual leave, so there is a desperate need for an application to make it easier for employees to apply for leave and manage leave, from filing, printing letters, to arranging the remaining leave. The purpose of this Final Project is to make an Employee Leave Application which is equipped with a brief employee data, position and simple assessment. In this research the writer uses the Waterfall method. This Employee Leave application uses the PHP programming language, it is based on the ability of PHP which supports all types of databases including MySQL, besides that PHP also produces dynamic and flexible web page content. He made an Information System so that the information system created could help record employee leave accurately and make the company more effective and efficient in seeing the remaining leave he has.
Cost-Sensitive Topical Data Acquisition from the Web

The cost of acquiring training data instances for induction of data mining models is one of the main concerns in real-world problems. The web is a comprehensive source for many types of data which can be used for data mining tasks. But the distributed and dynamic nature of web dictates the use of solutions which can handle these characteristics. In this paper, we introduce an automatic method for topical data acquisition from the web. We propose a new type of topical crawlers that use a hybrid link context extraction method for topical crawling to acquire on-topic web pages with minimum bandwidth usage and with the lowest cost. The new link context extraction method which is called Block Text Window (BTW), combines a text window method with a block-based method and overcomes challenges of each of these methods using the advantages of the other one. Experimental results show the predominance of BTW in comparison with state of the art automatic topical web data acquisition methods based on standard metrics.