Reviewerly/exHarmony huggingface dataset:
Design And Build Information System For Land Certificaton Of Land Office In Sidoarjo Regency

The purpose of this study is to build an information system for Land Certification in the Land Office of Sidoarjo Regency. This information system is a form of development in facilitating prospective applicants for making land easier and faster. To support the performance of the Sidoarjo Regency Land Office staff and make it easier for users to make land certificates. In this study, the method used was SDLC according to Ian Sommerville (2011). The cycle of stages contains requirement definition, system and software design, implementation and unit testing, integration and system testing, operation and maintenance so that the implementation can be maximized. The results of this study have built a Land Certification-based information system which greatly facilitates the performance of the Sidoarjo Regency Land Office staff. The conclusion from the research and discussion is that the Land Certification information system is running well and smoothly. With the existence of a land information system, it is hoped that it can help the work of BPN office officers, so that the efficiency and effectiveness of service performance can be improved as well as accelerating officer services for land-making transactions in Sidoarjo Regency.
User Behavioral Intention to Use Online Distance Learning (ODL): The Role of Self-Efficacy and Domain Knowledge

&lt;p class="0abstract"&gt;&lt;span lang="EN-US"&gt;The rise of novel coronavirus 2019 has shifted the roles of education industry. Face-to-face have become a distant memory; students and educators are now heavily relying on the digital communication. Application such as Google Meet, Webex, Webinar, Stream Yard, Zoom, and many more have become the new norm among educators and students. However, the sudden dependency on the digital technologies raises a question on the user intention to use this new digital technology. Therefore, the objective of this study is to determine the role of self-efficacy and domain knowledge towards user behavioral intention to use online distance learning. An instrument was developed by adopting to previous instruments and was analyze using Statistical Package for Social Science and SmartPLS for inferential analysis. Findings shows that the exogenous variables are capable to explained between 47.8% to 68.1% of the endogenous variables.&lt;/span&gt;&lt;/p&gt;
The Students' Reading Habit of English Education Study Program at STKIP PGRI Lubuklinggau

This research aimed to identified English reading habits of the sixth semester students of English Education Study Program at STKIP PGRI Lubuklinggau. This research employed in descriptive qualitative research design. The participants were from class B at the sixth semester students of English Education Study Program. The subject was 16 students. The data collected by using questionnaire adapted from a survey of EFL students in Indonesia from Iftanti (2012) and study from Samaranayake (2016) as the instrument to identify about English reading habits at the sixth semester students of English Education Study Program at STKIP PGRI Lubuklinggau. Based on the result of data analysis, the researcher found out the data: 1) 3 motivation English reading habits such as: improved reading skill, to know the knowledge and to improve their vocabularies. 2) Students’ belief, reading English can improve English ability in their activity and 3) Students’ purpose in reading English is for their study. In conlusion, the sixth semester students of English Education Study Program Class B at STKIP PGRI Lubuklinggau have good English reading habits. Students good habits are: they are eager to read English, they spend most of their time reading English texts,and they have strong interest to read English regularly.&#x0D; &#x0D; Key word: Higher Education Students’, Reading, Reading Habit&#x0D;
Spatial Characterization and Geological Modeling of Heterogeneous Resource Quality in a Multilayer Coal Deposit : 多層石炭鉱床における資源品質の不均質性の空間的な特徴抽出と地質的モデリング; タソウ セキタン コウショウ ニ オケル シゲン ヒンシツ ノ フ キンシツセイ ノ クウカンテキ ナ トクチョウ チュウシュツ ト チシツテキ モデリング

This dissertation focuses on the spatial characterization and geological modeling of the heterogeneity of coal qualities in a multilayer coal deposit. The geostatistical methods and CT-image analysis were used for this purpose. The coal is considered to be essential in this study because coal is one of the most abundant energy resources in the world and its importance as an energy source is increasing as petroleum and gas resources decline. The reasons why coal is important to everyday life due to its abundant, safe, clean, and cost effective.
WildWood: a new Random Forest algorithm

We introduce WildWood (WW), a new ensemble algorithm for supervised learning of Random Forest (RF) type. While standard RF algorithms use bootstrap out-of-bag samples to compute out-of-bag scores, WW uses these samples to produce improved predictions given by an aggregation of the predictions of all possible subtrees of each fully grown tree in the forest. This is achieved by aggregation with exponential weights computed over out-of-bag samples, that are computed exactly and very efficiently thanks to an algorithm called context tree weighting. This improvement, combined with a histogram strategy to accelerate split finding, makes WW fast and competitive compared with other well-established ensemble methods, such as standard RF and extreme gradient boosting algorithms.
A Study on the Construction of the Building DB for School Particulate Matter Management Technology Development Using QR Code

The purpose of this study is to review and categorize building information for the development of school particulate matter management technology. Therefore, we divided the database into 7 categories (school type, area, external environment, internal environment, school building status, building certification status) and subdivisions from 1,000 schools and organized data for a total of 38 detailed types. We presented a method of outputting data according to the 7 categories. In addition, after the construction of the school building DB, we intended to simplify and use this big data by generating a QR code. As for the QR code output method, it was possible to visually show the school building data by providing methods, such as, outputting in Korean, outputting in English, specifying a URL path, and outputting as an image. Comparing the use of Excel and Python in the previous study with the use of QR code, it was found that Excel could easily build a DB and Python could easily output desired data even if data accumulated once coding was done through DB. It was found that the QR code became complicated if the data was generated as it is, but the advantage was that it could be printed simply by using a URL, and it was necessary to produce a separate platform. Future research projects require the establishment and study of platforms which can utilize both Excel, Python, and QR codes.
Investigation of Job Satisfaction Dimensions of Health Care Knowledge Workers: Factor Analysis-Multivariate Approach

The investigation of the job satisfaction dimensions is crucial before further analysis such as testing the research hypotheses.The widely used approach includes Exploratory Factor Analysis with principal components analysis, unweighted least squares, generalized least squares, maximum likelihood, principal axis factoring, alpha factoring, and image factoring.The study focuses on investigation of the underlying dimensions of the job satisfaction of the knowledge workers in healthcare using multiple methods.The target sample of the research is the health care personnel including nurses, administrators, and doctors as the knowledge workers.Toward this end, a theory-based classical approaches are utilized.Healthcare employee's job satisfaction is an important in the successful performance of institutions.A rich literature of academic studies has showed that personnel's satisfaction is critical for the successful performance of organizations.The dimensions healthcare workers' satisfaction as the knowledge workers were extracted by employing: (i) Exploratory Factor Analysis method, (ii) Confirmatory Factor Analysis.The sample of this study were collected via a survey from health care personnel as knowledge workers.There are 249 observations collected from healthcare workers.A set of 34 items are utilized to investigate the job satisfaction of the healthcare knowledge workers.The results of the factor analysis indicated that six underlying crucial factors are extracted: attitude of management, organizational support, job security, reward and pay, working conditions, attitude of colleagues.
Understanding the Effects of Visualizing Missing Values on Visual Data Exploration

When performing data analysis, people often confront data sets containing missing values. We conducted an empirical study to understand the effects of visualizing those missing values on participants' decision-making processes while performing a visual data exploration task. More specifically, our study participants purchased a hypothetical portfolio of stocks based on a dataset where some stocks had missing values for attributes such as PE ratio, beta, and EPS. The experiment used scatterplots to communicate the stock data. For one group of participants, stocks with missing values simply were not shown, while the second group saw such stocks depicted with estimated values as points with error bars. We measured participants' cognitive load involved in decision-making with data with missing values. Our results indicate that their decision-making workflow was different across two conditions.
Distinguishing Lightweight Block Ciphers in Encrypted Images

Modern day lightweight block ciphers provide powerful encryption methods for securing IoT communication data. Tiny digital devices exchange private data which the individual users might not be willing to get disclosed. On the other hand, the adversaries try their level best to capture this private data. The first step towards this is to identify the encryption scheme. This work is an effort to construct a distinguisher to identify the cipher used in encrypting the traffic data. We try to establish a deep learning based method to identify the encryption scheme used from a set of three lightweight block ciphers viz. LBlock, PRESENT and SPECK. We make use of images from MNIST and fashion MNIST data sets for establishing the cryptographic distinguisher. Our results show that the overall classification accuracy depends firstly on the type of key used in encryption and secondly on how frequently the pixel values change in original input image.
Automatic Generation of Board Game Manuals

In this paper we present a process for automatically generating manuals for board games within the Ludii general game system. This process requires many different sub-tasks to be addressed, such as English translation of Ludii game descriptions, move visualisation, highlighting winning moves, strategy explanation, among others. These aspects are then combined to create a full manual for any given game. This manual is intended to provide a more intuitive explanation of a game’s rules and mechanics, particularly for players who are less familiar with the Ludii game description language and grammar.
On Pursuit of Designing Multi-modal Transformer for Video Grounding

Video grounding aims to localize the temporal segment corresponding to a sentence query from an untrimmed video. Almost all existing video grounding methods fall into two frameworks: 1) Top-down model: It predefines a set of segment candidates and then conducts segment classification and regression. 2) Bottom-up model: It directly predicts frame-wise probabilities of the referential segment boundaries. However, all these methods are not end-to-end, i.e., they always rely on some time-consuming post-processing steps to refine predictions. To this end, we reformulate video grounding as a set prediction task and propose a novel end-to-end multi-modal Transformer model, dubbed as GTR. Specifically, GTR has two encoders for video and language encoding, and a cross-modal decoder for grounding prediction. To facilitate the end-to-end training, we use a Cubic Embedding layer to transform the raw videos into a set of visual tokens. To better fuse these two modalities in the decoder, we design a new Multi-head Cross-Modal Attention. The whole GTR is optimized via a Many-to-One matching loss. Furthermore, we conduct comprehensive studies to investigate different model design choices. Extensive results on three benchmarks have validated the superiority of GTR. All three typical GTR variants achieve record-breaking performance on all datasets and metrics, with several times faster inference speed.
Witnessing Subsystems for Probabilistic Systems with Low Tree Width

A standard way of justifying that a certain probabilistic property holds in a system is to provide a witnessing subsystem (also called critical subsystem) for the property. Computing minimal witnessing subsystems is NP-hard already for acyclic Markov chains, but can be done in polynomial time for Markov chains whose underlying graph is a tree. This paper considers the problem for probabilistic systems that are similar to trees or paths. It introduces the parameters directed tree-partition width (dtpw) and directed path-partition width (dppw) and shows that computing minimal witnesses remains NP-hard for Markov chains with bounded dppw (and hence also for Markov chains with bounded dtpw). By observing that graphs of bounded dtpw have bounded width with respect to all known tree similarity measures for directed graphs, the hardness result carries over to these other tree similarity measures. Technically, the reduction proceeds via the conceptually simpler matrix-pair chain problem, which is introduced and shown to be NP-complete for nonnegative matrices of fixed dimension. Furthermore, an algorithm which aims to utilise a given directed tree partition of the system to compute a minimal witnessing subsystem is described. It enumerates partial subsystems for the blocks of the partition along the tree order, and keeps only necessary ones. A preliminary experimental analysis shows that it outperforms other approaches on certain benchmarks which have directed tree partitions of small width.
The Agile Game

It would be inappropriate to write a book about leading product development teams without saying something about the process of software development. Some individuals go as far as to suggest that software is eating the world. Software continues to play an increasingly vital role in business success in almost every sector imaginable. Many product and service companies rely on software solutions as part of their business strategy. Many businesses have undergone (or are undergoing) a “digital transformation,” which means they are automating many of their processes using software. Web pages, desktop applications, and mobile apps have replaced activities performed with pen and paper. An audit recovery company with 40 people who manually review hundreds of receipts in the hopes of identifying rebates their clients did not take advantage of decided to develop an automated software-based process that scanned the receipts and used algorithms to identify missed rebates. Suddenly, a process that took weeks now took minutes. Walk into a restaurant, bank, or school, and you will observe software playing an integral part in how employees do their jobs. Everywhere we look, software is part (or even at the heart) of business operations.
SMARRT: Self-Repairing Motion-Reactive Anytime RRT for Dynamic Environments

This paper addresses the fast replanning problem in dynamic environments with moving obstacles. Since for randomly moving obstacles the future states are unpredictable, the proposed method, called SMARRT, reacts to obstacle motions and revises the path in real-time based on the current interfering obstacle state (i.e., position and velocity). SMARRT is fast and efficient and performs collision checking only on the partial path segment close to the robot within a feasibility checking horizon. If the path is infeasible, then tree parts associated with the path inside the horizon are pruned while maintaining the maximal tree structure of already-explored regions. Then, a multi-resolution utility map is created to capture the environmental information used to compute the replanning utility for each cell on the multi-scale tiling. A hierarchical searching method is applied on the map to find the sampling cell efficiently. Finally, uniform samples are drawn within the sampling cell for fast replanning. The SMARRT method is validated via simulation runs, and the results are evaluated in comparison to four existing methods. The SMARRT method yields significant improvements in travel time, replanning time, and success rate compared against the existing methods.
MENULIS TEKS PROSEDUR MENGGUNAKAN MODEL PEMBELAJARAN NEUROLINGUISTIC PROGRAMMING (NLP) DI SMK

This study aims to describe the implementation of learning, teacher and student responses, and to find out the difficulties experienced by class X SMK students in completing tasks in learning to write procedural texts using the NLP model. The research method used was descriptive quantitative with a sample of 38 students of SMK class X TO. The results obtained are as follows: (1) the implementation of learning is carried out in two meetings with the results of observations showing a very good category (2) the teacher's response to the implementation of learning is at a very good level, as well as student responses. (3) students' difficulties in implementing learning, namely when answering questions related to aspects of knowledge and skills in diction or word choice.
Music in Virtual Reality

Virtual reality (VR) is a platform that is only just beginning to find its footing in the consumer industry. With a highly diverse line of products available, composers are challenged with different technological specifications for each VR project. This chapter discusses how VR, as a medium, is unique, covering important concepts and technological differences like degrees of freedom (DOF), positional tracking systems, binaural audio, ambisonics, and more. It then goes on to explore some different methods for designing scores for VR.
Blockchain, Smart Contracts and Financial Audit Implications

Blockchain technology and cryptoassets may have seized the attention of the financial services space, but as the technology ecosystem continues to mature there are additional considerations coming to the forefront. Smart contracts represent an important piece of the blockchain conversation and play a critical role in how blockchains interact with other technology platforms. Accounting and auditing professionals will need to understand both how smart contracts function, and also how these applications will impact accounting and auditing processes. The present paper, written keeping both the academic and practitioner audience in mind, seeks to examine how smart contracts interact with blockchain technology, analyze how these applications can change audit processes, and propose potential future roles for the profession.
Analisa Pemilihan Kursus Daring Pada Karyawan PT. Gramedia Asri Media dengan Metode Analytical Hierarchy Process

PT. Gramedia Asri Media established the Gramedia Digital Technical Department which implements remote work so that it is possible for employees working in various places to stay connected and collaborate. However, with the limited space and time for employees and the difficulty of meeting at one time to get various trainings, then MOOC is expected to be the answer to the need for workers to get proper training and in accordance with the technical capabilities required by the company. MOOC (Massive Open Online Courses) is an example of technological development of the learning process that offers flexibility in time and place. Currently, there are many alternative MOOC providers with various criteria, so it is necessary to choose the one that is most suitable for its users. One method of making decisions based on many criteria is AHP (Analytical Hierarchy Process). This study uses 5 criteria, namely Teacher Credibility, Certificate, Price, Course Topics and Course Time and 4 alternatives, namely Coursera, EdX, Udemy and Codecademy, where the course topic is obtained as the priority with a priority weight of 0.2289 then followed by Course time with a priority weight of 0.2238 Price with priority weight 0.2133, Credibility of teachers with priority weight 0.1833, Certificate with priority weight 0.1508. While the alternative with the priority is Udemy with a priority weight of 0.4379 followed by Coursera with a priority weight of 0.2234, Codecademy with a priority weight of 0.1989 and lastly Edx with a priority weight of 0.1723.
STD-Trees: Spatio-temporal Deformable Trees for Multirotors Kinodynamic Planning

In constrained solution spaces with a huge number of homotopy classes, standalone sampling-based kinodynamic planners suffer low efficiency in convergence. Local optimization is integrated to alleviate this problem. In this paper, we propose to thrive the trajectory tree growing by optimizing the tree in the forms of deformation units, and each unit contains one tree node and all the edges connecting it. The deforming proceeds both spatially and temporally by optimizing the node state and edge time durations efficiently. Deforming the unit only changes the tree locally yet improves the overall quality of a corresponding subtree. Further, to consider the computation burden and optimizing level, patterns to deform different tree parts in combination of different deformation units are studied and compared, all showing much faster convergence. The proposed deformation can be easily integrated into different RRT-based kinodynamic planning methods, and numerical experiments show that integrating the spatio-temporal deformation greatly accelerates the convergence and outperforms the spatial-only deformation.
Fixed Wing Deflection Measurement using Sensor Fusion

The system presented in this paper integrates measurements from Deflection-Detection-Vision-System (DDVS) and strain gauge sensors to calculate the dynamic performance of the unmanned aerial vehicle (UAV) fixed-wing. The fusion results are more accurate and reliable than the measurement from the single sensor alone, and this is used to design an advanced control system. Unscented Kalmar Filter (UKF) is the choice of fusion method because it gives better performance in dealing with nonlinear systems and deals with white and color Gaussian noise. The presented novel measurement and control system gives accurate shape and deflection of the fixed-wing, which will be used to calculate the aerodynamic performance. The DDVS was verified in extensive experiments with the system installed in the wind tunnel. The objective of experiments conducted was to determine the wing's deflection in flight parameters' function. The results of the camera and strain gauges integration resulted in accurate measurements in comparison with results obtained from one sensor only.