Reviewerly/exHarmony huggingface dataset:
KGAMD: an API-misuse detector driven by fine-grained API-constraint knowledge graph

Application Programming Interfaces (APIs) typically come with usage constraints. The violations of these constraints (i.e. API misuses) can cause significant problems in software development. Existing methods mine frequent API usage patterns from codebase to detect API misuses. They make a naive assumption that API usage that deviates from the most-frequent API usage is a misuse. However, there is a big knowledge gap between API usage patterns and API usage constraints in terms of comprehensiveness, explainability and best practices. Inspired by this, we propose a novel approach named KGAMD (API-Misuse Detector Driven by Fine-Grained API-Constraint Knowledge Graph) that detects API misuses directly against the API constraint knowledge, rather than API usage pat-terns. We first construct a novel API-constraint knowledge graph from API reference documentation with open information extraction methods. This knowledge graph explicitly models two types of API-constraint relations (call-order and condition-checking) and enriches return and throw relations with return conditions and exception triggers. Then, we develop the KGAMD tool that utilizes the knowledge graph to detect API misuses. There are three types of frequent API misuses we can detect - missing calls, missing condition checking and missing exception handling, while existing detectors mostly focus on only missing calls. Our quantitative evaluation and user study demonstrate that our KGAMD is promising in helping developers avoid and debug API misuses
Special Issue on PHM for Human Health and Performance II

This special issue was conceived during the 11th Annual Conference of Prognostic and Health Management Society’s Panel session on the September 25th at Scottsdale, AZ, USA. We would like to thank the panel members and their colleagues in their participation in this special issue focusing on engineered technologies for older adults. This work was partially funded by the NSF ERC seed grant from an interdisciplinary group of researchers from Iowa State University, Arizona State University, Georgia Tech, Florida State University, Chapman University and the University of California Irvine who are engaged in developing a large-scale grant proposal that will be focused on integrated technologies to promote resilient aging and reducing healthcare costs.The manuscripts exemplify our research focus and illustrates contributions in the fields of wearable smart sensors, sensor-data-fusion, machine learning and data mining, prediction and diagnosis, and electronic health records and databases - all in the context of prognostics and health management for human health and performance.We would like to thank the PHM Society for providing an opportunity to publish in their premier journal, and importantly, we are grateful for help of the Editor-in-Chief – Marcos Orchard, Ph.D. for his countless hours to edit and make it best possible of this special issue. Finally, we would like to express sincere appreciation to all the reviewers who have contributed their time and thoughtful feedback to making this special issue publication a success.
On the Feasibility of Fast Fourier Transform Separability Property for Distributed Image Processing

Given the high algorithmic complexity of applied-to-images Fast Fourier Transforms (FFT), computational-resource-usage efficiency has been a challenge in several engineering fields. Accelerator devices such as Graphics Processing Units are very attractive solutions that greatly improve processing times. However, when the number of images to be processed is large, having a limited amount of memory is a serious problem. This can be faced by using more accelerators or using higher-capability accelerators, which implies higher costs. The separability property is a resource in hardware approaches that is frequently used to divide the two-dimensional FFT work into several one-dimensional FFTs, which can be simultaneously processed by several computing units. Then, a feasible alternative to address this problem is distributed computing through an Apache Spark cluster. However, determining the separability-property feasibility in distributed systems, when migrating from hardware implementations, is not evident. For this reason, in this paper a comparative study is presented between distributed versions of two-dimensional FFTs using the separability property to determine the suitable way to process large image sets using both Spark RRDs and DataFrame APIs.
Cryptography – An Overview

With the day-by-day advancement of the Internet throughout the world, online marketing sites and applications are growing rapidly. More and more social networking sites are emerging almost every day connecting people from various parts of the world. These situations demand the organizers behind those networks to generate and store a huge amount of data regularly. Nonetheless to say, the more the data, the more is the risk of losing it. Hackers, phishers, or breachers are there at every nook and corner of the World Wide Web to steal and abuse the data of users. To protect the data from breaches, it is a necessity to secure the network. The general method of network protection is known as "Cryptography". Users are generally given a unique User ID and authentication code known as Password under which their data are stored individually. In this paper, we will discuss the overall idea of cryptography along with its methods and techniques.
Hand Gesture Recognition System as Virtual Mouse for HCI

Abstract: The technique of interaction between human and computer is evolving since the invention of computer technology. The mouse is one of the invention in HCI (human computer interaction) technology. Though wireless are Bluetooth mouse technology is invented still, that technology is not completely device free. A Bluetooth mouse has the requirement of battery power it requires extra power supply. Presence of extra devices in a mouse increases the difficulty level of more hardware components. The proposed mouse system is outside this limitation. This paper proposes a virtual mouse system using colored hand glove based on HCI using computer vision and hand gestures. Gestures captured with a webcam on processed with color segmentation, detection technique and feature extraction. The user will be allowed to control some of the computer cursor functions with a colored glove on the hand. Primarily, a user can perform with their fingers, scrolling up or down using their hands in different gestures. This system captures frames using a webcam or built-in cam it is based on the camera quality. So the usage of colored glove mouse system eliminates device dependency in order to use a mouse. Keywords: HCI(human computer interaction), colored hand glove , gestures
Network Security Based on Component for Information Network

It is a difficult building to ensure the security of data arrange, so it is important to consider out a new security control design and model in the viewpoint of foundational control. As indicated by the attributes and security requests of data net, another security control viewpoint and its engineering dependent on parts is proposed, the security control framework is made-up, and insights regarding the structure of control system, its different kinds, and capacities and spread methods of security control parts are presented, at that point the highlights of the control framework are outlined at last.
Characterizing Reverse Engineering Practices on Decayed Software Applications

Architecture reverse engineering is an approach to reproduce architectural contents once an application has deviated from its planned architecture.Unassisted understandings of an application by an individual, interviewing a person knowing the subject system, and computer-aided tools are few approaches that can produce architectural contents from a decayed software application.The former two approaches are helpful when an individual in the organization can understand the software application.Worst comes when computer-aided tools remain the only way to produce architectural contents from an application's source code.This research aims to identify architectural contents that industrial practitioners reproduce through reverse engineering, finding out the users of identified architectural contents and how the existing tools help in meeting industrial practitioners' needs.A qualitative study was performed to achieve the research objectives by choosing a homogenous sampling approach from the organizations where software applications were under gradual development for many years.Semi-structured interviews were conducted, and a coding approach was used to find out themes from transcribed data.We identified different architectural contents that practitioners produce from source code.Our findings show that practitioners use reverse engineering tools to produce architectural content from an application's source code.However, there are some architectural contents that practitioners need to reverse engineer, but no available tool produces those contents.The reverse engineering tools produce a wide range of architectural contents from source code but, contents visualization as required by practitioners is a challenge that needs to be addressed.
Facial Emotion Recognition and Detection in Python Using Deep Learning

Human facial emotion recognition (FER) has attracted the eye of the research network for its promising applications.Mapping one of a kind facial expressions to the respective emotional states are the primary task in FER.The classical FER consists of two most important steps: feature extraction and emotion recognition.presently, the Deep Neural Networks, particularly the Convolutional Neural network (CNN), is extensively used in FER with the aid of distinctive feature of its inherent feature extraction mechanism from pictures.numerous works were reported on CNN with only some layers to clear up FER issues.but, wellknown shallow CNNs with straightforward getting to know schemes have restricted characteristic extraction capability to seize emotion data from high-resolution pictures.A notable disadvantage of the most current techniques is that they consider only the frontal pictures (i.e., ignore profile perspectives for convenience), despite the fact that the profile perspectives taken from different angles are essential for a practical FER system.For growing a highly correct FER system, this study proposes a completely Deep CNN (DCNN) modeling thru transfer learning (TL) technique wherein a pre-skilled DCNN model is followed through changing its dense top layer(s) well suited with FER, and the model is great-tuned with facial emotion data.a novel pipeline strategy is brought, wherein the training of the dense layer(s) is accompanied via tuning each of the pre-skilled DCNN blocks successively that has brought about gradual improvement of the accuracy of FER to a better level.
Efektivitas Model Pembelajaran Information Gap Activity Normalism (IG-AN) terhadap Keterampilan Berbicara Peserta Didik Kelas X SMA

Abstract: Information Gap model is a learning model that can be used to be applied to speaking skills. The Information Gap model can train learners to dare to speak independently and communicatively in teams through various forms of activity and stimulus variety. The study is useful for knowing the effect of the Information Gap model to the Chinese speaking skills for grade Tenth 2 Malang Senior High School and their response to Information Gap learning model. This research is an quantitative research with quasi experiment design pretest posttest control group design. The free variable in this study is the Information Gap model whereas bound variables to this study are Chinese speaking skills. The data acquisition in the study was a score on the results of experimental and control group' pretest and posttest results. The instrument validity test is performed by a sticky validity test and reliability test. The results of validity and reliability tests show that the instrument is valid and reliable. Data analysis is done by hypothesis tests that have previously been performed normality tests and homogeneity tests. The results of the study showed that the Information Gap learning model was effectively applied in speaking skills to the material of everyday activities and transportation tools in the grade tenth 2 Malang Senior High School class.&#x0D; Keywords: information gap activity normalism learning model, speaking skill&#x0D; Abstrak: Model Information Gap adalah model pembelajaran yang dapat digunakan untuk diterapkan pada keterampilan berbicara. Model Information Gap dapat melatih peserta didik untuk berani berbicara secara mandiri dan komunikatif dalam tim melalui berbagai bentuk kegiatan dan ragam stimulus. Penelitian ini bertujuan untuk mengetahui efektivitas model Information Gap Activity Normalism terhadap keterampilan berbicara bahasa Mandarin peserta didik kelas X SMAN 2 Malang dan respons peserta didik terhadap model pembelajaran Information Gap tersebut. Penelitian ini adalah penelitian kuantitatif dengan desain penelitian quasi experiment pretest posttest control group design. Variabel bebas dalam penelitian ini adalah model Information Gap Activity Normalism sedangkan variabel terikat pada penelitian ini adalah keterampilan berbicara bahasa Mandarin. Perolehan data dalam penelitian ini berupa skor hasil tes berbicara peserta didik kelompok eksperimen dan kontrol dari hasil pretest dan posttest. Uji validitas instrumen dilakukan dengan uji validitas angket dan uji reliabilitas. Hasil uji validitas dan reliabilitas menunjukkan bahwa instrumen valid dan dinyatakan reliable. Analisis data dilakukan dengan uji hipotesis yang sebelumnya telah dilakukan uji normalitas dan uji homogenitas. Hasil penelitian menunjukkan bahwa model pembelajaran Information Gap efektif diterapkan dalam keterampilan berbicara pada materi kegiatan sehari-hari dan alat transportasi di kelas X SMAN 2 Malang.&#x0D; Kata kunci: Information Gap Activity Normalism, keterampilan berbicara
The Expansionary or Contractionary Effects of Devaluation: Empirical Evidence from Pakistan

The current research is the long-term and short run impact of real exchange rate variations on growth for Pakistani annual data from 1973 to 2011.Pesaran and Shin (1999) and Pesaran et al. (2001) introduced the Autoregressive Distributed Lag (ARDL) approach to Co-integration which is employed for empirical analysis.The findings revealed a negative relationship between growth and real effective exchange rate, which is statistically significant at 1%, implying that 1% devaluation in the real effective exchange rate induces a 0.16 percent drop in real GDP, implying that devaluation is contractionary for Pakistan in the long run.The real effective exchange rate has a negative impact on economic growth in the short run, but this is statistically insignificant, suggesting that devaluation is neutral for Pakistan.Other factors such as money supply, government spending, and worker remittances have a positive impact on economic growth, while crude oil prices have a negative impact in the long run.These variables have almost identical impacts on economic growth in the short term.
Improved Learning Outcomes Of Social Sciences Lessons Through Google Meet Assisted Powerpoint Media

&lt;p&gt;&lt;em&gt;This research is a classroom action research (CAR) which aims to improve student learning outcomes in social studies subject matter through the use of the Google Meet application with the help of PowerPoint learning media. The sample in this study amounted to 12 students. The research method used is Classroom Action Research (CAR) in two cycles consisting of two meetings in each cycle. The stages of each cycle are planning, implementation, observation and reflection. In the first cycle, the students who completed the post test were 66.67%, and in the second cycle 91.67%. From this analysis, it can be seen from the increase in student learning outcomes in cycle I to cycle II. It can be concluded that the use of the google meet application with the help of powerpoint learning media can improve student learning outcomes, especially in Social Studies class VI SDN Randugunting 7 Tegal City.&lt;/em&gt;&lt;/p&gt;
Antecedents of University Performance: Does Strategy Matter?

In a bid to contribute to the increasing body of extant interdisciplinary research within the antecedents of university performance and strategic management domains, this study investigates the role of generic strategies in the perceived performance of universities. Using a case study of eight Nigerian universities and survey responses from 380 academics and administrative staff from these universities, the study tested four succinct hypotheses using the covariance structural equation modeling (CB-SEM) technique. Findings revealed that while there was a limited link between differentiation strategy and performance, there was a substantially strong link between focus strategy and performance according to the findings. Similarly, findings revealed that respondents from public-private universities perceived their institutions as having the strongest generic strategy-performance connection, followed by respondents from the public sector. The cost leadership-performance path demonstrated no significant effect.
Triangular Silicon Carbide Nanophotonic Devices for Quantum Simulators

We explore applications of silicon carbide photonics in quantum simulation. We design a low-loss triangular photonic crystal molecule with embedded color centers, and explore the formation of hybridized light-matter states in this system.
Study and Survey on Image Compression Techniques

In the Modern World, image is the important source for new technologies. The image compression is one of the important techniques which play a vital role in many applications. This paper presents the study of various image compression techniques which are used in the different Image Processing Applications. The advancement in the computer vision increases the demand of high data transmission speed also there is a need of large storage space. So, the image compression field is a necessary one for such applications where high volume of data is required to store and transmit. This paper focuses on the area of image compression, advantages of image compression, types of image compression and its different types of techniques. In addition to that, one of the new lossless image compression techniques ABO is explained. In this paper, it gives the overview of the ABO Framework and the ABO mechanism.
PENGARUH PENGGUNAN MODEL PEMBELAJARAN CORE (CONNECTING, ORGANIZING, REFLECTING, EXTENDING) BERBANTU MULTIMEDIA INTERAKTIF TERHADAP HASIL BELAJAR EKONOMI

This research was conducted with an effort to determine the effect of the use of CORE learning methods (Connecting, Organizing, Reflecting, Extending) assisted by interactive multimedia on student learning outcomes. CORE is learning that emphasizes students to be more active in finding information. So that with the presence of interactive multimedia can help students to find wider information.This research is the result of quantitative quasi-experimental research, with a design that is Non- equivalent Control Group Design. The selected sample is XI IPS 2 class with 27 students as the control class and XI IPS 1 as the experimental class with 31 students by using Purposive Sampling. Data collection methods by interview, documentation, observation and tests. Meanwhile, to determine whether there is an effect of the CORE method on social skills using the t-test formula. Based on the results of the study, through the calculation of the t-test formula the use of two similarity test levels with an average level of 5%. To test the hypothesis using the Simple Linear Registration formula Ỳ = a + bX is Ỳ = 39.44497 + 0.6424x followed by the tcount formula t = b / sb = 4.33. Ttab = 1,699 5% signification level to 4.33&gt; 1,699, the hypothesis is accepted. So it can be concluded that there is a significant influence on the use of CORE Learning Methods (Connecting, Organizing, Reflecting, Extending) assisted by Interactive Multimedia on the learning outcomes of XI IPS MAN 1 Lampung Timur Economic Year 2019/2020 ".Keywords: CORE, Interactive Multimedia, Learning Outcomes
EqGNN: Equalized Node Opportunity in Graphs

Graph neural networks (GNNs), has been widely used for supervised learning tasks in graphs reaching state-of-the-art results. However, little work was dedicated to creating unbiased GNNs, i.e., where the classification is uncorrelated with sensitive attributes, such as race or gender. Some ignore the sensitive attributes or optimize for the criteria of statistical parity for fairness. However, it has been shown that neither approaches ensure fairness, but rather cripple the utility of the prediction task. In this work, we present a GNN framework that allows optimizing representations for the notion of Equalized Odds fairness criteria. The architecture is composed of three components: (1) a GNN classifier predicting the utility class, (2) a sampler learning the distribution of the sensitive attributes of the nodes given their labels. It generates samples fed into a (3) discriminator that discriminates between true and sampled sensitive attributes using a novel ``permutation loss'' function. Using these components, we train a model to neglect information regarding the sensitive attribute only with respect to its label. To the best of our knowledge, we are the first to optimize GNNs for the equalized odds criteria. We evaluate our classifier over several graph datasets and sensitive attributes and show our algorithm reaches state-of-the-art results.
Pengaruh Media Pembelajaran Zoom Meeting Terhadap Hasil Belajar IPS pada Masa Covid -19 Di SMP Shidqia Islamic School Bekasi

At this time, the world is facing the phenomenon of the Covid-19 pandemic. In order to minimize the spread of the Covid-19 virus, the government has taken a policy of Social Distancing, including policies in the field of education through the implementation of learning from home, physical distancing, study from home. the application of the zoom meeting method in the study from home process can provide effective learning such as related feedback, combining collaborative independent learning activities, and personalizing learning based on the needs of students using question and answer by communicating directly with educators. By still following the rules of Social Distancing. The purpose of this research is to find out whether there is an influence in the application of the zoom meeting method in the study from home process on the social studies learning outcomes for class VIII in SMP Shidqia Islamic School, this research method uses the experiment with the form of Pretest and Posttest assessment. The results of this study can be concluded that there is a Positive effect of using zoom meeting media on Social Sudies learning outcomes for class VIII in SMP Shidqia Islamic School, the percentage of the influence of the independent variable (Zoom Meeting) on the dependent variable (IPS Learning Outcomes) called the coefficient of determination / R square (R2) is 0.264, which implies that the influence of Zoom Meeting online learning media on social studies learning outcomes is 26.4 %.