Reviewerly/exHarmony huggingface dataset:
An Examination on Applying Machine Learning in Game Industry

Machine learning is one of the biggest trends in the current computer industry. However, the implementation of machine learning in commercial games is rare and limited to a certain minor feature in the game. That being said, there are a few implementations of machine learning in game industry that actually works. In this paper, we present our observation result regarding the implementation of machine learning in computer games. The observation focus on the architecture and methods used in the system, and the performance and advantage of using machine learning as part of the system. We go through several commercially available games that implement machine learning and analyze the architecture and performance of the system. Additionally, we also observe a few research related to machine learning that uses game as its environment by collecting several publications related to this area.
Pornography Cybercrime in the Qatari Cybercrime Law

This study deals with pornography cybercrime as organized by the Qatari legislator in the combating cybercrime law No. ( 14) of 2014, Where the law refers to pornographic crimes related to persons who have not reached the age of eighteen years of age under article (7) thereof, the researcher concluded that the Qatari legislator did not indicate what electronic pornography crime is and its concept accurately, in addition, it does not address pornographic crimes related to the promotion of prostitution, as well as the technical legal aspect of this type of crime.This study concluded with a series of conclusions and recommendations that were a natural secretion of the research process in this subject and the related concerns, taking into account the issue of the use of computers and various means in rationing those crimes.
Image stitching by points grouping and mesh optimization

Image stitching is a cost-effective way to expand the field-of-view of imaging system. The traditional homography-based image stitching uses a global homography transformation matrix for image transformation, which is stable, but only works well for flat scenes, relative far scenes or the scenes which are captured by the camera with rotation only. The AsProjective-As-Possible and Content-Preserving-Warping methods, which are realized by mesh optimization, improve the stitching result to a certain degree, but there is obvious ghost in the near scenes or images which have relatively large parallax. In this paper, an image stitching method which utilizes depth information and mesh optimization is proposed. The feature points are detected and then clustered, and the depth information are used to assign weights to each mesh to compute homography for each mesh respectively. Experiments show proposed method has better results than other methods.
PENGEMBANGAN MEDIA SMART WINDOW AND WALL PICTURES DALAM PEMAHAMAN BERITA HOAX DI SD SE-KECAMATAN MALINAU KOTA

Abstract: The development of smart window and wall pictures media in this study was made so that students understood the hoax news. The development of research is done in order to overcome the problems faced by students who have not been able to distinguish the right news and false news (Hoax) . The research was conducted with Research and Development . The media is validated by linguists and media experts, and is tried out to small groups to find out news about hoaxes, so researchers can draw conclusions that the development of smart window and wall pictures can be used as a medium for understanding hoax news in the Malinau City sub-district.
USING GEOMORPHOLOGY, LIDAR AND GEOLOGIC MAPPING TO DEVELOP CONSISTENT PROTOCOLS FOR DEFINING FOCUS AREAS INCLUDED IN THE PLACER MINERAL SYSTEM ON THE ATLANTIC COASTAL PLAIN AND ADJACENT ENVIRONS OF THE SOUTHEASTERN USA (EAST REGION)

To transcend state boundaries and simplify the USGS catalog of Mineral Systems, Focus Areas, and Focus Area Identifiers for the EAST region of the U.S., we provide here a genetically-based, source-to-sink, depositional systems approach to classifying heavy mineral placer deposits associated with the southeast Atlantic Coastal Plain Province (ACP). Heavy minerals include ilmenite (FeTiO3), rutile (TiO2), zircon (ZrSiO4), and monazite (CePO4), which contain economically valuable critical commodities such as titanium, zirconium, and rare earth elements. Focus Area compartments are defined here using geomorphology (LiDAR) and detailed geologic mapping that includes correlation of alloformations between states and identification of common settings for regolith- and facies-controlled heavy mineral deposits. The ACP includes a set of regionally extensive, relict Pliocene and Pleistocene paleoshorelines and marine terraces that step down in elevation and age to sea level; these are dissected by incised valleys that include sets of fluvial, estuarine and marine terrace deposits that are connected downstream to a marine terrace and associated paleoshoreline or the Holocene shoreline. Upstream, incised valleys of the Coastal Plain may transition into Piedmont alluvial systems. Each source to sink depositional systems tract includes source rocks and regolith, Piedmont source streams, a set of terraces in the connecting incised valleys, and a paleoshoreline/marine terrace complex. Placers may also occur as older in-place or reworked sedimentary facies (e.g. Cretaceous) that lack discernable geomorphic signatures. In the Fall Zone, regolith placers (weathered in-situ bedrock) may overlap with paleoshoreline generated placers. The solution proposed here is to subdivide the Placer Mineral System for heavy minerals using geomorphology and detailed geologic mapping to identify the following compartments in the source to sink system: 1) paleoshorelines, 2) incised valley, 3) upstream alluvial (Piedmont), 4) regolith, 5) formation controlled (e.g. Cretaceous), and 6) the Holocene depositional system. Optimally, LiDAR should be used to map environmental geologic map units that will define depositional systems and their upstream and downstream landform elements.
Trajectory Planning for Point-to-Point Motion Using High-order Polynomials

In this paper, a trajectory planning problem based on high-order polynomials is formulated for a point-to-point motion. The problem aims to find suitable polynomial trajectories that connect an initial to a final configuration while satisfying other specified constraints. The constraints are considered as zero velocity at the endpoint as well as a limitation on acceleration for the whole motion time. However, this problem is very difficult to trace more particularly when the number of coefficients (decision-making variables) is large. As a new approach, a high-order polynomial equation containing only two-term is proposed to generate suitable trajectories between two configurations. The advantage of the proposed polynomial is that it can be traced analytically in order to get solutions for the two independent coefficients in a closed-form. The motion simulations show that the resulting high-degree trajectories with two-term polynomial satisfy the mentioned constraints as well as they are continuous and smooth. Additionally, comparing outputs of Genetic Algorithm with the closed-form solutions for the problem show that closed-form expressions generate coefficients that are near optimal.
A Corpus-based Study of Noun Phrase Complexity in Applied Linguistics Research Article Abstracts in Two Contexts of Publication

Unlike conversation, academic writing is characterized by the frequent use of noun phrases which make it difficult for less proficient readers to process a text. Using a subset of Biber, Gray, and Poonpon’s (2011) hypothesized developmental stages of writing, we analyzed noun phrase modifiers in applied linguistics research article (RA) abstracts between expert non-native English Persian writers and international writers. To that end, a 38,762-word corpus was constructed, consisting of 109 international academic research articles (RAs) and 100 Persian English-medium RAs randomly chosen from international peer-reviewed journals and Persian English-medium peer-reviewed journals. Using an automatic extraction computer program (PyCharm, version 3.4.), we tagged texts, identified noun phrase modifiers, and compared the normalized frequency of the modifiers between two writer groups. Independent-samples t-tests and chi-square tests of independence were run to analyze the data. The findings revealed that international writers differed significantly from Persian writers in the use of total noun phrase modifiers, relative clauses, and post-modifying prepositional phrases. Results from the analysis of lexical bundles indicated that Persian writers used lexical bundles to modify noun phrases more frequently than international writers. The findings of this study offer insights into the way expert international and non-native academic writers in applied linguistics make use of phrasal features for complexifying RA abstracts.
Improving the accuracy of 3D surface reconstruction by controlling height compensation

The southwell model algorithm based on the least squares method is suitable for a variety of wavefront reconstruction and three-dimensional shape detection through slope fitting. Due to the assumption that the height is linearly related to the gradient in the southwell model, the detailed information of the surface shape needs to be gradually improved by the iterative algorithm. In this paper, we add an attenuation factor in the form of a power function controlled by exponential and iterative times to increase the height compensation amount in the early iteration and control the excessive noise data to participate in the iteration, which leads to the deviation of the fitted surface shape from the actual surface shape. Through simulation comparison experiments, the new algorithm has faster iteration rate and higher accuracy than traditional iterative algorithms.
The Rhetorical Problems Experienced by Indonesian Lecturers in Social Sciences and Humanities in Writing Research Articles for International Journals.

The publication rate of Indonesian academics in reputable international journals is far below those of neighbouring countries. This is because Indonesian academics are not familiar with the appropriate rhetorical style of English research articles although they can write academic texts in English reasonably well. This study investigated the rhetorical problems experienced by Indonesian lecturers in social sciences and humanities when writing research articles for international journals. In this study, all sections (abstract, introduction, methods, results and discussion) of research article drafts written by Indonesian academics were analysed based on their rhetorical styles following the models suggested by Swales (1990, 2004), Swales and Feak (2009), Lim (2006), and Peacock (2011). The results show that Indonesian authors have significant rhetorical problems in writing the introduction, results and discussion sections but few problems with writing abstracts and the methods section. The majority of these academics fail to write a convincingly argumentative introduction and discussion because they either do not use relevant references at all or they use them in improper ways. The study concludes that Indonesian authors must learn the ideal rhetorical styles of research article introductions and discussions, especially the use of references, in order to be accepted in international journals.
Modelling the Impact of Demographic Variables on Employee Motivation Levels in Automobile Industry

Motivation of employees is one of the most critical components for an organization to be effective and efficient. Employee motivation is presented in the form of commitment, job satisfaction, high energy levels, willingness to take challenging assignments, and innovation while they are working for their organizations. It becomes very important for organizations to devise strategies and ways through which they can motivate and retain their employees. The present study is aimed to predict the motivation level of employees in automobile industry on the basis of their demographic variables using machine learning algorithms. The motivation level is measured by structured questionnaire with 70 items on the scale. The sample was collected from employees in automobile sector in Delhi/NCR region with a sample size of 340 employees. Analysis of the sampled data revealed that the machine learning algorithm is able to depict the motivation levels of employees on the basis of age, gender, and designation.
Pengembangan Media Pembelajaran Aplikasi “Akuntansi UKM” Berbasis Android sebagai Penyusunan Laporan Keuangan untuk Meningkatkan Hasil Belajar Siswa Kelas XI Akuntansi di SMK Muhammadiyah Delanggu

This study aims to develop accounting learning media using the Android-based UKM application in the preparation of Financial Statements. In addition, this research is also used to create an effective learning process and can improve student learning outcomes. This research is a research development using Quasi Experiment method. This research was conducted at Muhammadiyah Delanggu Vocational School with the test subjects is XI Accounting class students as the experimental class and the control class. The data analysis technique used in this study was the T-test. The results showed that: 1) Based on research from material experts and media experts stated that accounting learning media using the Android-based UKM application is feasible to be used for learning as a learning medium in the preparation of Financial Statements. 2) The average of pre-test and post-test scores in the control class only had a difference of 18.63 from the pre-test score of 39.55 to 58.18 in the post-test scores so that it showed no significant improvement. 3) In the experimental class the pre-test score was 45.55 and the post-test score increased by 91.82 so it shows that after the use of accounting learning media using the Android-based UKM application there was an increase in student learning outcomes.
Bitcoin-Blockchain Phenomenon: An Investigation on News Titles Influence

The research purposed would explain, not the bitcoin-blockchain (BTC-BC) phenomenon per se, considering a good level of knowledge on the themes, but focusing the attention on two implicit connotations that these “disruptive technologies” involve. The investigation conducted by the authors considers a sentiment analysis on news titles influence during the period 2015-2018 supported by a field analysis. That approach based on framing activity would intersect different study areas from innovation, economics, psychology, behavioral analysis, marketing and decision-making. Innovations should be studied under different aspects considering their probable wide range impacts on several fields. The exploratory approach to investigate something new would be interesting and useful to open windows of discussion and interpretation. The research focuses the two main factors of marketing strategies: scarcity and persuasion. The aim would be to validate these concepts in BTC-BC phenomenon as a kind of implicit marketing strategy.
Improving the Recognition Rate of Phonetic Arabic Letters Via Artificial Intelligent

It is very important to enhance the recognition accuracy of the Arabic spoken letters. The accuracy of recognition system is affected by the feature extraction and the used classifier. An effective and robust method is proposed to evaluate speech feature to improve the performance the recognition accuracy. This work introduces applying the mel frequency cepstral coefficient (MFCC) to extract the speech features. Hidden Markov model and neural network are used as classifier tools. The objective of the proposed system is to enhance the performance by introducing three systems which are proposed to recognize the spoken Arabic letters. The first is based on neural networks. The second is based on hidden Markov model. While third system is based on combination between neural networks and hidden Markov models. The accuracy of neural network is found to be 42% with MFCC for 84 spoken letters. The hidden Markov models are statistical based approach. Its performance is found to be 98.5%. But for combination system based on neural network and hidden Markov models, the accuracy of 99.25% is obtained.
Traffic Predictive Analysis Through Data Stream Mining

With a huge increase in computational power, Traffic Predictive Analysis has seen various improvements in the recent years. Additionally, this field is experimenting an increase in available data, which allows to produce more precise forecasting and classification models. However, this means that the available data has also seen a huge increase in terms of storage size. Data Stream Mining provides a brand new approach to data processing, allowing to create adaptive, incremental models that do not need huge amounts of storage size, as the data is processed as it is received. In this communication, we will explore the state of the art and the first research efforts that can be found in this direction.
Exploring the adoption of blockchain technology in the oil and gas industry supply chain : a unified theory of acceptance and use of technology model approach

The aim of the study is to explore blockchain adoption in the oil and gas supply chain using UTAUT model. Qualitative strategy was used to explore the reaction of the adoption of blockchain technology. Semi-structured interview was conducted across different categories. Specifically, the interviews were structured around the key pillars of performance expectancy, effort expectancy, social influence facilitating conditions and their influence on behaviour intention and use of behaviour all within the context of blockchain adoption in oil and gas supply chain.The findings indicate some acceptance of blockchain technology as users reported that it enhances efficiency in the supply chain.
LibGuides: Access Matters: Home

Information is inherently valuable. Access to it, or lack of access, has the potential to affect the quality of one’s life. In this lesson, students will learn how access to information shapes people’s lives.
HUBUNGAN MOTIVASI BERPRESTASI DENGAN PRESTASI BELAJAR MAHASISWA AKADEMI REFRAKSI OPTISI (ARO) YLPTK-PADANG

There are many factors affecting learning achievement include: external factors namely social environment and non social environment, factors of the consisting of physiological factors and psychological factors, and learning approach factors. One of important factors in an individual which pshycological factors affecting learning achievement is motivation to learn. With high motivation, then will get a high learning achievement too. This is research aims to know about the relationship between motivation to achievement with learning achievement. Design of this research is analytic, with use approach descriptive correlational.. Subject of this research is ARO student year 2018. Total sample of this research is 82 people and use total sample. Prossesing the statistical data for the relationship between motivation to learn with learning achievement use Spearman test. The result of this research show a significant relationship between motivation to achievement with learning achievement (r=0,243 p=0,213). In conclusion there was a relationship between motivation to achievement with learning achievement ARO student YPLTK Padang.
PENTINGNYA PENGGUNAAN BAHASA INDONESIA DI PERGURUAN TINGGI

The Indonesian Ministry of National Education Director General decided to include Indonesian as one of the subjects that must be taught in all tertiary institutions and departments. The aim is to hone language skills and develop students' personalities. It has become an obligation for us as Indonesian Citizens (WNI) to master and apply Indonesian language in everyday life properly and correctly, so that Indonesian language can be maintained its authenticity. The purpose of this study is to find out: 1) understanding of language; 2) Indonesian Language courses for students; 3) The importance of Indonesian in universities; 4) The purpose and benefits of the Indonesian Language course. The conclusions that can be drawn are: Indonesian is important to be studied in higher education, because Indonesian is a unifying language, because in universities every student comes from various regions in Indonesia. Then, Indonesian as a guide for the preparation and use of good and correct grammar in scientific communication (thesis, thesis, dissertation, etc.), besides studying Indonesian for students at the university as well as studying Indonesian subjects in high school, however discussion at the university is more specific and in-depth, and most students still want to learn Indonesian because in order for them to speak the language properly and correctly, Indonesian is also important to be preserved by native speakers. Suggestions that can be given are: that the Indonesian language needs to be learned, because in this way we also indirectly have preserved our language. Who else will preserve this Indonesian language if we are not Indonesian citizens themselves. that the Indonesian language needs to be learned, because in this way we also indirectly have preserved our language. Who else will preserve this Indonesian language if we are not Indonesian citizens themselves.
Comparative study on double-step phase-shifting algorithm for nonlinear phase error compensation

The phase-shifting method is widely used in fringe projection profilometry (FPP),The digital light projector (DLP) and charge coupled device (CCD) are generally nonlinear devices.The captured fringes do not have a good sinusoidal property,which leads to errors in the retrieved phase map.The methods to calibrate the nonlinear response of a FPP and compensate for the associated error can be classified into active methods(correction before pattern projection) and passive methods(correction after pattern projection).The basic idea of the active method to precisely obtain the input output relation function of the projector. The passive method compensates the error in phase domain by the post-processing algorithms. Huang et. al. presented the double three-step phase shifting algorithm to reduce the nonlinear phase error by projecting two groups of three-step phase-shifting fringe with an initial phase offset of 60 degree.Subsequently,some scholars improved this method. Zheng et.al. presented a method that combined the two wrapped phases to obtain the combination of the wrapped phase,it is simpler than Huang’s method because only one time phase unwrapping procedure is needed. Lei et. al. combined double-step phase-shifting method and multifrequency temporal phase unwrapping algorithm, proposed a multi-frequency inverse-phase method to realize the 3D shape measurement of the complicated objects. Mao proposed a similar approach.The main difference between Lei and Mao is that the operation order of double-step phase-shifting algorithm for error compensation is different. In Mao’s method,error compensation is performed in the wrapped phase map while it is done with the unwrapped phase map in Lei’s method.This paper compares double-step phase-shifting algorithm, its variational algorithm (Zheng's method, Lei’ s method, Mao's method) and phase shift algorithm with twice the number of steps for nonlinear error compensation, our study finds that these algorithms have similar effect in reducing nonlinear phase error. Phase shift algorithm with twice the number of steps is simpler and more direct than double-step phase-shifting algorithm.In variational algorithm, Zheng’s method reduces the number of phase unwrapping by half compared with traditional double-step phase shifting algorithm,Mao’s method is essentially the same as Lei’s method,it was by introducing multi-frequency temporal phase unwrapping algorithm that Lei and Mao's method can measure the complex object. Experimental results are presented to demonstrate the rationality of this analysis.