Reviewerly/exHarmony huggingface dataset:
CRITICAL ANALYSIS OF DIGITAL VIDEO AUTHENTICATION BASED ON VARIOUS TECHNIQUES

It is becoming very important to assure the trustworthiness of video information. In crime investigation the video sequences are playing vital role because it gives clear and particular information about the crime scene. There is vast type of video editing tools are available it can be used to efficiently and effectively alter the content of digital data. Therefore, it is increasingly significant to protect video information from manipulation and alterations. There are various researches and literature is available about video authentication and proposing different algorithms and methods. Unfortunately, existing solutions like digital signature and watermarking techniques that address video tampering problems fail to identify the device that produces the images or footage while techniques that can identify the camera is incapable of locating the tampered content of its captured video. All the other methods and algorithms available show the result mostly in digital video content authentications. So, it is required to classify the intelligent techniques or methods and algorithms for future development in this subject and fellow researcher should get clear and precise information for their further study and findings in digital video authentication field.
Pengetahuan Dasar Guru Bahasa Inggris SMP di Indonesia Dalam Menilai Kemampuan Writing Siswa

The professionalism of junior high school teachers is characterized by their ability to prepare and evaluate students' learning. Therefore, the basic knowledge of junior high school English teachers in assessing writing is essential because it dramatically influences their assessment of student writing learning outcomes. This quantitatively descriptive study invited 87 junior high school teachers in the district and 38 junior high school teachers in the municipality to fill out questionnaires about basic knowledge of assessing writing. As a result, only 16.09% of district teachers and 26.32% of municipal teachers scored above 60. Although these teachers have all been certified and report serious professional activities regularly, they still have severe problems carrying out the preparation, implementation, and assessment of writing. All parties, especially schools, education ministry, and teacher's education institutions, need to anticipate by preparing in-service teachers and pre-service teachers to evaluate students' learning outcomes well, mainly writing assessment.
The use of podcast in disseminating agricultural technology innovation: A SWOT analysis

Downloadable audio files called podcasts have become popular within many areas of communication. Agricultural technology and innovation disseminators may wish to deliver their work to a larger audience but may not know how. The present study aims to explore the use of podcast series as a media for disseminating agricultural technology innovation and demonstrate the sustainability, and acceptance level of this dissemination platform. The agricultural technology innovation produced by Indonesian Agency for Agricultural Research and Development (IAARD), Ministry of Agriculture were used as an input in creating a weekly series of agricultural and technology review podcasts. Based on the analysis of the SWOT approach, the right strategy in developing podcasts in the future is a weakness and opportunity strategy, where podcasts are a new thing that has several weaknesses as well as opportunities to be developed.
RANCANG BANGUN SISTEM PERSEDIAAN KAPAS BERBASIS WEB DI PT. ARGO MANUNGGAL TRIASTA

—  Design a web-based cotton Inventory System at PT. Argo manunggal Triasta PT. Argo Manunggal Triasta is an industrial company engaged in the field of Textile. This company is one of the many companies in Indonesia that has obstacles in the delivery of information, especially information data about reports in and out of goods, reports of final stock of goods and all problems related to inventory. This makes the data management process slow, as does the provision of information when needed so that it hinders the process of selling / releasing goods. By designing a better system, it is expected to be able to assist and facilitate the ongoing system processes in managing data, including processing, compiling, and storing data which ultimately produces accurate data that can be used for company needs. The results of the analysis are described using the UML (Unified Modeling Language) modeling language. Implementation in the form of the final results achieved is the formation of a web-based information system that can facilitate users in managing data. —  Design a web-based cotton Inventory System at PT. Argo manunggal Triasta PT. Argo Manunggal Triasta is an industrial company engaged in the field of Textile. This company is one of the many companies in Indonesia that has obstacles in the delivery of information, especially information data about reports in and out of goods, reports of final stock of goods and all problems related to inventory. This makes the data management process slow, as does the provision of information when needed so that it hinders the process of selling / releasing goods. By designing a better system, it is expected to be able to assist and facilitate the ongoing system processes in managing data, including processing, compiling, and storing data which ultimately produces accurate data that can be used for company needs. The results of the analysis are described using the UML (Unified Modeling Language) modeling language. Implementation in the form of the final results achieved is the formation of a web-based information system that can facilitate users in managing data.
LibGuides: ISU Libraries Production Lab: Computer

This guide lists the technology, both hardware and software, available in the Production Lab.
Improving Web user Experience by Adapting RWD

Responsive Web Design (RWD) is a design which focuses on responsively fitting in whatever device the website is accessed from. It involves writing code for all possible screen sizes and bundling them together. Hence when the website is accessed, the whole bundle alongside the code for all screen sizes are downloaded to the user’s device and acts responsively when the browser window is resized, or the mobile device is rotated to portrait or landscape orientation. RWD can provide a far better user experience than the other designs because it primarily focuses on the user experience. Despite the bundle size being large, this method has proved to be robust in providing a better user experience and has evolved with evolution of web technologies. Latest CSS Media Queries make it possible to even target devices with limited accuracy. CSS Media Queries form the fundamentals of RWD because it is the most used way of targeting devices with various screen sizes.
Does Computer-Aided Instruction Improve Children’s Cognitive and Noncognitive Skills?

This paper examines the causal effects of computer-aided instruction (CAI) on children’s cognitive and noncognitive skills. We ran a clustered randomized controlled trial at five elementary schools with more than 1,600 students near Phnom Penh, Cambodia. After 3 months of intervention, we find that the average treatment effects on cognitive skills are positive and statistically significant, while hours of study were unchanged both at home and in the classroom. This indicates that CAI is successful in improving students’ learning productivity per hour. Furthermore, we find that CAI raises students’ subjective expectation to attend college in the future.
Efficient Cauchy distribution based quantum state preparation by using the comparison algorithm

The quantum Monte Carlo algorithm can provide significant speedup compared to its classical counterpart. So far, most reported works have utilized Grover’s state preparation algorithm. However, this algorithm relies on costly controlled Y rotations to apply the correct amplitudes onto the superposition states. Recently, a comparison-based state preparation method was proposed to reduce computational complexity by avoiding rotation operations. One critical aspect of this method is the generation of the comparison threshold associated with the amplitude of the quantum superposition states. The direct computation of the comparison threshold is often very costly. An alternative is to estimate the threshold with a Taylor approximation. However, Taylor approximations do not work well with heavy-tailed distribution functions such as the Cauchy distribution, which is widely used in applications such as financial modeling. Therefore, a new state preparation method needs to be developed. In this study, an efficient comparison-based state preparation method is proposed for the heavy-tailed Cauchy distribution. Instead of a single Taylor approximation for the entire function domain, this study uses quantum piecewise arithmetic to increase accuracy and reduce computational cost. The proposed piecewise function is in the simplest form to estimate the comparison threshold associated with the amplitudes. Numerical analysis shows that the number of required subdomains increases linearly as the maximum tolerated approximation error decreases exponentially. 197 subdomains are required to keep the error below 18192 of the maximum amplitude. Quantum parallelism ensures that the computational complexity of estimating the amplitudes is independent from the number of subdomains.
Pengaruh Media Tematik Berbasis Flip Booklet Terhadap Hasil Belajar Siswa Kelas II di MI Falakhiyah Glagah Lamongan

This research is motivated by the fact that there are problems in thematic learning, one of which can be seen from the class II thematic learning textbooks used at MI Falakhiyah Glagah Lamongan, namely the lack of media use which is limited to image media and text books, resulting in less varied learning and impact. on student learning outcomes that are less than optimal. In thematic learning, a media is needed to facilitate the delivery of material to students. One of the media that can be used is flip booklet media. The purpose of this study specifically was to examine the effect of Flip booklet-based Thematic learning media on the learning outcomes of class II A students at MI Falakhiyah Glagah Lamongan. The research method used is a quantitative experimental method with an experimental design of one group pre-test post-test design. The results showed that the use of thematic learning media based on Flip Booklet had an effect on the learning outcomes of class II A students MI Falakhiyah Glagah Lamongan with the average value of this pre-test an increase of 16.9. With the key words that the thematic media based on Flip Booklet affects the learning outcomes of class II students at MI Falakhiyah Glagah Lamongan and increases their learning outcomes.
Learner Profiling in Intelligent Tutoring Systems: A New Perspective

Student profiling lays the foundations of the personalization that happens in adaptive educational applications and Intelligent Tutoring Systems (ITS). A student’s level of knowledge on a topic is estimated from their performance on certain activities related to the topic. For this, researchers have devised many model extensions throughout the years that incorporate specific cognitive features into student profiling. In this paper, a new framework for student profiling has been proposed. The proposed framework takes into account features that include question quality and errors in the formulation of practice items.
Information Technology Knowledge Management taxonomy to enhance government electronic services in existence of COVID 19 outbreak

Information technology and the need for timely and effective communication during the Covid-19 have made most governments adopt technological approaches to provide their services. E-government services have been adopted by most governments especially in developed countries to quickly and effectively share information. This study discusses the reasons why governments in the Gulf region should develop a new model for information technology knowledge management practices. To achieve this, the author identified possible benefits of adopting information technology knowledge management practices and why most governments in the Gulf find it hard to adopt them. Knowledge management allows for learning, transfer as well as sharing of information between government organizations and citizens and with the development of technology, the effectiveness of electronic services can easily be achieved. Also, effective adoption of information technology can improve knowledge management with the help of techniques that enhance capture, storage, retrieval as well as sharing of information. The author used systematic literature review to select 28 journals and articles published post 2019. IEEE, Google Scholar and Science Direct were used to select potential studies from which 722 journals and articles were selected. Through screening and eligibility assessment, 21 articles were retained while the back and forward search had 7 more articles which were also included in the study. Using information gathered from these articles and journals a new conceptual model was developed to help improve information technology knowledge management for governments in the Gulf region to effectively deliver e-services during Covid-19. This model was developed based on the process of KM, Theory of Planned Behavior and Unified Theory of Acceptance and Use of Technology. Based on the developed model. From UTAUT model, performance expectancy, effort expectancy as well as social influence had a great impact.
Evaluation of Various DR Techniques in Massive Patient Datasets using HDFS

The objective of comparing various dimensionality techniques is to reduce feature sets in order to group attributes effectively with less computational processing time and utilization of memory. The various reduction algorithms can decrease the dimensionality of dataset consisting of a huge number of interrelated variables, while retaining the dissimilarity present in the dataset as much as possible. In this paper we use, Standard Deviation, Variance, Principal Component Analysis, Linear Discriminant Analysis, Factor Analysis, Positive Region, Information Entropy and Independent Component Analysis reduction algorithms using Hadoop Distributed File System for massive patient datasets to achieve lossless data reduction and to acquire required knowledge. The experimental results demonstrate that the ICA technique can efficiently operate on massive datasets eliminates irrelevant data without loss of accuracy, reduces storage space for the data and also the computation time compared to other techniques.
Self-Training for Compositional Neural NLG in Task-Oriented Dialogue

Neural approaches to natural language generation in task-oriented dialogue have typically required large amounts of annotated training data to achieve satisfactory performance, especially when generating from compositional inputs. To address this issue, we show that self-training enhanced with constrained decoding yields large gains in data efficiency on a conversational weather dataset that employs compositional meaning representations. In particular, our experiments indicate that self-training with constrained decoding can enable sequence-to-sequence models to achieve satisfactory quality using vanilla decoding with five to ten times less data than with ordinary supervised baseline; moreover, by leveraging pretrained models, data efficiency can be increased further to fifty times. We confirm the main automatic results with human evaluations and show that they extend to an enhanced, compositional version of the E2E dataset. The end result is an approach that makes it possible to achieve acceptable performance on compositional NLG tasks using hundreds rather than tens of thousands of training samples.
Real Time Face Matching With Document Image Using Transfer Learning

In our project, we use an automated system to verify or check our identity and other details by showing our ID documents containing face images such as passports, driving licence and other documents to human operators. Then the user must show their person’s face image and will detect the 21 facial landmarks by using SDM algorithm. Once it has done, we will verify the real time face with document image by matching them using CNN algorithm. Previously, they have used a pair of sibling network to learn domain specific parameters from heterogeneous face pairs. But the cross validation is done only by CNN based general face matcher. The dataset used to train the system also require more space for storage and in case of any errors, manual checking process is the only solution. To get the better solution, we put forward a technique called Dynamic Weight Imprinting (DWI) to renovate the differentiator weights which permit quick merging and more extraditable portrayal. And a pair of sibling network with partly shared parameters are trained to learn a unified face portrayal with domain specific parameters.
Long-term deviation detection in human behavior

World population ageing causes an important increase of people needing specific health care and monitoring. Dedicated institutions exist, but most of the elderly prefer to keep their autonomy for economic and personal reasons. To ensure a good quality of life and health to this population, Health at Home (HaH) solutions are explored. Many works focus on monitoring smart home inhabitant behavior to detect changes which might be due to health problems. These approaches are efficient to detect accident or short-term diseases such as a cold or influenza but tend to detect too tardily diseases which provoke slow declines in behavior. This is a problem as the elderly are likely to suffer from such troubles and early detection allows for better diagnosis and may help to prevent or reduce future worsening. In this paper, a novel approach for the detection of long-term behavior changes is introduced. It focuses on activity duration as this indicator is influenced by most diseases and give clear information about the inhabitant health status. This paper proposes data forecasting to detect future anomalies to assess existence of evolution in the current behavior. Information is sent to medical staff to refine their prognostic and adapt their treatment or call for a medical appointment. A case study based on a real smart home simulating a worst-case scenario attests for the efficiency of the approach and its resilience.
TNAS: Neural Network Architecture Search Sampling Module Based on Variational Autoencoder

Neural Architecture Search (NAS) searches the architecture of neural network automatically in a large search space. The search space typically contains billions of network architectures, which makes it computationally expensive to search for the best-performing architecture. One-shot and gradient-based NAS methods have achieved good results in various computer vision tasks. Even though they achieved success, the current sampling methods are either fixed or manual, all of which are ineffective. In this paper, we propose a learning sampling module for neural architecture search (NAS) named TNAS, based on variational auto-encoder (VAE). This module can be easily embedded into the existing weight sharing NAS framework such as one-shot approach and gradient-based approach, and significantly improve the performance of search results. In NasNet-like search space, TNAS produced a series of competitive results on CIFAR-10 and ImageNet. In addition, combined with the one-shot method, our method obtains the latest results of ImageNet classification model under 400M FLOPs frequency hopping with a probability of 77.4% in a ShuffleNet-like search space. Finally, we performed an in-depth analysis of TNAS on the NAS-BENCH-201 dataset to verify the effectiveness of our proposed approach.
Temporal analysis on pull request patterns: an approach with sliding window

In open-source software projects, it is common for external collaborators to send contributions through pull requests, with bug fixes, new features and/or any type of modification in software artifacts. These contributions are evaluated by the core team that decides on their acceptance. This pull requests evaluation process has been the object of study by researchers who seek to understand which factors influence this stage. Some works used association rules to show patterns that indicate the influencing factors in various scenarios, namely: acceptance, lifetime, and assignment of reviewers. However, in general, these results do not consider the time perspective inherent in the collaborative process and software evolution. The temporal analysis of patterns on pull requests, through association rules, is configured as an open research topic. This analysis is important, above all, for development teams, so that they can identify the moment when certain patterns have occurred with greater intensity, allowing a contextual and qualitative assessment of the projects at a given moment. In addition, a more detailed assessment can allow development teams to react appropriately to the patterns found, enhancing practices that lead to positive patterns and/or avoiding mistaken actions to mitigate undesired patterns. The goal of this work is to propose an approach of temporal analysis of association rules on pull requests that allows a more detailed interpretation of the extracted patterns. The results found show patterns that: i) gain/lose strength over time, regardless of the partitioning used; ii) do not exist for some periods of time; and iii) show a tendency to stability.
RANCANG BANGUN SISTEM INFORMASI SEKOLAH DAN PENDAFTARAN ONLINE SISWA BARU DENGAN METODE USER CENTERED DESIGN (STUDI KASUS SMA MUHAMMADIYAH 1 PEKANBARU)

Muhammadiyah senior high school, which is one of the private schools in Pekanbaru and has become a Building Education Center in Riau Province and Sumatra Regional, makes this school an Islamic-based private school to be reckoned with. In February 2020, interviews were conducted with several school parties, it was found that Muhammadiyah senior high school was still having difficulties in terms of promoting schools and registering new prospective students which were still being done manually. So that information brochures are at risk of being lost easily, registration forms are at risk of being damaged, and take a long time to register. To overcome the above problems, a school website system and registration were developed using the User Centered Design (UCD) method. The User Centered Design method is a design that places the user at the center of the system development process. This research was conducted using the User Experience Questionnaire (UEQ) tools. Research results were obtained from 72 respondents who showed the website had a high UEQ scale value. The website built using the UCD method has succeeded in obtaining a good user experience questionnaire (UEQ). Based on the test, the value of attractiveness is 1,480, perspicuity is 1,535, efficiency is 1,497, dependability is 1,379, stimulation is 1,401, and novelty is 1,105. So that from these values it can be seen that the Muhammadiyah senior high school website is in accordance with the needs of the user.