Reviewerly/exHarmony huggingface dataset:
A Hough Transform for Detecting Facial Symmetry Axis

We propose a method for detecting a facial symmetry axis from a frontal face image.&nbsp;The proposed method adopts a voting procedure like Hough transform that transforms a set of edge points into perpendicular bisectors of two different edge points selected from the set.&nbsp;The initial guess of a symmetry axis is adjusted accurately by the following fine tuning procedure.&nbsp;Experimental results show that the proposed method correctly detects facial symmetry axes from real face images visually and quantitatively.
ELECTRONIC-VOTING (E-VOTING) POLICY IN CONSISTENT GENERAL ELECTIONS TOWARDS A DEMOCRACY SYSTEM IN INDONESIA

Indonesia as a democratic country has entered the era of the millennium in the implementation of general elections simultaneously, it is necessary to utilize computer technology using the Electronic-Voting (E-Voting) method. Several regions in Indonesia have used the E-Voting method as a means of democracy which is applied at the hamlet and village head election levels. Village Head election policy with E-Voting as a new means of democracy through a touch of the monitor screen and E-Verification through voters' E-KTP. For example: Pemalang Regency (Ujunggede Village), Jembrana Regency in Bali (Mendoyo Dangin Tukad Village). Elections through e-voting must be designed as best as possible to realize the principles of direct elections, namely direct, general, free, secret (overflow) and honest and fair (fair) in direct elections. Electronic voting systems (e-voting) must be taken seriously and ensure transparency, certainty, security, accountability, and accuracy. In addition to technology readiness, of course, it must be supported by the readiness of the community in implementing this e-voting system in the future. The government's unpreparedness and lack of socialization of e-voting can also be a factor triggering failure in implementing this system.
Production Method of Light Field Image Simulation Based on 3ds Max 3D Reconstruction

At present, there are various ways to implement a light field imaging system, among which light field array camera as a new system of the light field imaging system is widely concerned and researched, however, the light field image produced based on this method does not provide the demand of scene baseline changeable, which greatly limits the application scene of light field image. To this end, this paper proposes a light field image simulation production method based on 3ds Max 3D reconstruction, which mainly includes five key steps, including 3D scene modeling, scene unit configuration, lighting parameter adjustment, array camera construction, and rendering imaging. The method proposed in this paper solves the shortcomings of the traditional light field image production process that cannot target array camera baseline changes and has advantageous features such as stable camera parameters, idealized rendering imaging, variable imaging baseline, and simultaneous presentation of a depth map. Compared with the traditional method, the method produces images with balanced quality and high automation, which can effectively improve the production efficiency of light field images in specific scenes and meet the requirements of relevant light field image processing tasks.
Sector-Based Parametric Sound Field Reproduction in the Circular Harmonic Domain Using Covariance Based Rendering

Parametric spatial audio rendering approaches are able to reproduce a recorded sound scene with high perceptual quality. Most approaches, however, assume a sound field model of a single plane wave plus a diffuse field component, an assumption which is often violated. Therefore, a sector-based reproduction method operating on higher-order spherical harmonic domain signals has been proposed. This paper provides an adaptation of this method to the circular harmonic domain. Furthermore, objective and subjective evaluations are performed, to identify particular strengths and weaknesses of the proposed method.
Query Recompilation

In order to minimize the overhead from compiling execution plans, the plans are stored in a memory space called the plan cache. When prepared statements, whether as stored procedures or the other mechanisms for creating parameterized queries, are used, the process takes advantage of the plans being in cache. However, a number of things can cause plans to be removed from cache. Sometimes, this is a good thing. Either data has changed, statistics have been updated, or something has happened so a different execution plan may enhance performance. Sometimes, this is a bad thing, and you get a lot of recompiles, placing excessive load on the processor and interfering with the general good behavior of queries on the system. This chapter covers the following topics:
Meningkatkan Kemampuan Speaking Siswa Kelas XII TAV SMKN 2 Kota Bima Dengan Model Pembelajaran Kooperatif Tipe Jigsaw

This research is aimed to know (1) the increasing of speaking achievement of class XII TAV SMKN 2 Kota Bima by using cooperative learning type jigsaw (2) to know the students’ responses towards the using of cooperative learning type jigsaw in learning speaking. The data collecting; observation, students’ responses of the questionnaire and the result of the scores from sycle 1 and sycle 2. The technique of analyzing data is descriptive analysis; to analyze the response of the questionnaire and students’ score from sycle 1 (one) and sycle 2(two). The result of the research is showed that the using of cooperative learning type jigsaw can increase the speaking ability of students class XII TAV SMKN 2 Kota Bima in academic year 2020/2021. The result of the sycle 2 (two); students’ score is 75,32. It means that as stated by Nana Sujana (2009: 62), if the score is 75 means success. The result of the questionnaire; number 1(one) is 92 % yes; question number 2(two) 12% is yes for negative statement; question number 3 (Three) 80% is yes; question number 4 (four) 88% is yes; and question number 5 (five) that 96% students answered yes. The hypothesis which is stated that the using cooperative learning type jigsaw can increase students ability in speaking of students class XII TAV SMKN 2 Kota Bima is accepted.
Design and Realization of Real-time Face Beauty System based on Android

With the popularity of mobile terminals and the speed-up of network, short videos are favored by all platforms, fans and capital. People often record and share their lives through short videos. For most users, it is vitally important to show their best self to the audience. Therefore, short video software needs to provide users with a variety of real-time beauty effects, such as face thinning, whitening, mapping and filters, to meet users’ demand for beauty. This paper mainly focuses on the design of a real-time facial beauty system based on Android. The system uses key point detection technology based on deep learning to realize detection of key facial feature point, adopts OpenGL ES to realize image deformation algorithm, and adjusts the face shape according to the detected key points, so as to achieve the effects of thin face and big eyes. The system mainly includes three functional modules: camera module, detection module of key facial feature point and beauty filter module. To meet individual needs, every function parameter in the system is adjustable.
An analysis of apology in an Indonesian ELT textbook and the teacher's strategy to teach the apology

&#x0D; The apology is one of the speech acts that language functions cover. Considering that students must have pragmatic competence to use language appropriately in context, this research looked at apologies in an Indonesian senior high school ELT textbook, as well as the strategies used by teachers to teach apology. This study employed a qualitative approach which involves a textbook analysis and a semi-structured interview of the teacherâ€™s teaching strategies to collect the data. The collected data then were classified, transferred into tables, and analyzed using Limberg (2015)â€™s principles of teaching pragmatics. The findings of this study show that the textbook entitled Bahasa Inggris Kelas XII covers some parts of Limbergâ€™s principles of teaching pragmatics of apology. There is one principle that is not covered, namely, the principle of drawing a comparison. However, the findings of this study expose that the teacherâ€™s teaching strategies cover all Limbergâ€™s principles of teaching pragmatics of apology. Therefore, English teachers and institutions are expected to take into account the materials used to teach apology to students to raise studentsâ€™ pragmatic competence.
A Cascade of Checkers for Run-time Certification of Local Robustness

Neural networks are known to be susceptible to adversarial examples. Different techniques have been proposed in the literature to address the problem, ranging from adversarial training with robustness guarantees to post-training and run-time certification of local robustness using either inexpensive but incomplete verification or sound, complete, but expensive constraint solving. We advocate for the use of a run-time cascade of over-approximate, under-approximate, and exact local robustness checkers. The exact check in the cascade ensures that no unnecessary alarms are raised, an important requirement for autonomous systems where resorting to fail-safe mechanisms is highly undesirable. Though exact checks are expensive, via two case studies, we demonstrate that the exact check in a cascade is rarely invoked in practice. Code and data are available at https://github.com/ravimangal/cascade-robustness-impl .
A Science-Enabled Virtual Reality Demonstration to Increase Social Acceptance of Prescribed Burns

Increasing social acceptance of prescribed burns is an important element of ramping up these controlled burns to the scale required to effectively mitigate destructive wildfires through reduction of excessive fire fuel loads. As part of a Design Challenge, students created concept designs for physical or virtual installations that would increase public understanding and acceptance of prescribed burns as an important tool for ending devastating megafires. The proposals defined how the public would interact with the installation and the learning goals for participants. This poster provides an overview of the virtual reality (VR) pipeline created to develop working prototypes of the immersive experiences and VR games that were proposed by the finalists in the design challenge.
Análise de Arquiteturas de Redes Neurais Para Segmentação Semântica de Dados Sísmicos

With the advancement of technology, the characterization of oil reservoirs has become more accurate and with that its complexity has increased, mainly with the acquisition of 3D seismic data.In this article, two deep neural network architectures applied to semantic segmentation of seismic images are presented.Only 100 images are used for training the network.With the proposal to use clustering and CLAHE filter in the U-Net architecture, it was possible to increase its performance and reach 99.37% of accuracy, thus surpassing the state-of-the-art obtained by the Danet-FCN3 architecture, which had reached an accuracy of 98.13%.
Modeling and correction of piezoelectric string instrument pickups

Under-string piezoelectric pickups are often used to amplify and record stringed instruments such as guitars and violins. The mounting configuration of pickups differ with the most common placements being under the saddle, bridge, or directly under the strings, where the pickup functions as the saddle. Each of these placements, as well as the design of the piezoelectric pickup imparts a particular characteristic on the sound of the instrument. We investigate the equalization imparted by the pickup and present methods to correct for the frequency domain differences to produce a neutral sound. Additionally, piezoelectric sensors can exhibit nonlinear behavior such as hysteresis. Measurements are made with an attempt to model and correct for any nonlinear behavior observed.
Broadcasts

Android broadcasts are messages following the publish-subscribe pattern. They are sent across the Android OS, with the internals hidden by the Android OS, so both publishers and subscribers only see a lean asynchronous interface for sending and receiving messages. Broadcasts can be published by the Android OS itself, by standard apps, and by any other app installed on the system. Likewise, any app can be configured or programmed to receive broadcast messages it is interested in. As with activities, broadcasts can be explicitly or implicitly routed – whichever is used is the responsibility of the broadcast sender.
Introducing Always Encrypted with Enclaves

In SQL Server 2019 the potential to use enclaves was added to Always Encrypted. An enclave is a secure partition of memory, in this case on the SQL Server machine, that appears as a black box to anything outside of the enclave. There is no way to view the data or code inside the enclave from outside of it, which makes it a trusted and secure environment in which to perform cryptographic operations. Code that runs in the enclave must also be signed and cannot be modified. In this chapter we take an overview of how it works and what it offers us.
An experimental study of graph theory-based image segmentation techniques to improve graph cut algorithm

The Graph cut algorithm of Graph theory has been successfully applied to various image segmentation problems. One of the most efficient algorithms is Normalized cut which is successfully implemented by many researchers for extraction of salient object from a natural scene. We have conducted a number of experiments on Normalized cut algorithm using Gaussian Filter, Median Filter, Lp1 norm based Gaussian filter and Lp1 norm based Median filter to enhance the efficiency of the Normalized Graph Cut Algorithms on individual color channels of an image and conducted different experiments to prove the efficiency of the new experimental models on the selected images from Corel and Berkley image segmentation data set. We have compared the results of the models with Otsu (Otsu thresholding algorithm) and C-means (C-means clustering algorithm), and to quantify the results we have used three validity indices.
Interpretable Machine Learning Fusion and Data Analytics Models for Anomaly Detection

Explainable artificial intelligence received great research attention in the past few years during the widespread of Black-Box techniques in sensitive fields such as medical care, self-driving cars, etc. Artificial intelligence needs explainable methods to discover model biases. Explainable artificial intelligence will lead to obtaining fairness and Transparency in the model. Making artificial intelligence models explainable and interpretable is challenging when implementing black-box models. Because of the inherent limitations of collecting data in its raw form, data fusion has become a popular method for dealing with such data and acquiring more trustworthy, helpful, and precise insights. Compared to other, more traditional-based data fusion methods, machine learning's capacity to automatically learn from experience with nonexplicit programming significantly improves fusion's computational and predictive power. This paper comprehensively studies the most explainable artificial intelligent methods based on anomaly detection. We proposed the required criteria of the transparency model to measure the data fusion analytics techniques. Also, define the different used evaluation metrics in explainable artificial intelligence. We provide some applications for explainable artificial intelligence. We provide a case study of anomaly detection with the fusion of machine learning. Finally, we discuss the key challenges and future directions in explainable artificial intelligence.
MaxEnt Dreamer: Maximum Entropy Reinforcement Learning with World Model

Model-based reinforcement learning algorithms can alleviate the low sample efficiency problem compared with modelfree methods for control tasks. However, the learned policy's performance often lags behind the best model-free algorithms since its weak exploration ability. Existing model-based reinforcement learning algorithms learn policy by interacting with the learned world model and then use the learned policy to guide a new round of world model learning. Due to weak policy exploration ability, the learned world model has a large bias. As a result, it fails to learn the globally optimal policy on such a world model. This paper improves the learned world model by maximizing both the reward and the corresponding policy entropy in the framework of maximum entropy reinforcement learning. The effectiveness of applying the maximum entropy approach to model-based reinforcement learning is supported by the better performance of our algorithm on several complex mujoco and deepmind control suite tasks.
Artificial intelligence systems

Today, artificial intelligence is becoming more and more popular in almost every aspect of our daily lives. Artificial intelligence is usually concerned withthe creation of computer systems with the capabilities of the human mind: understanding, learning, discussing, solving problems, translating, and so on. During the study of artificial intelligence, human-intelligent programming, technologies and tools for designing intelligent systems, databases, knowledge bases, database management systems, speech interfaces, computer linguistics, computer graphics, computer networks and web programming , information security in computer systems
Application of Big Data Processing Technology in Power Marketing System

Based on multi data fusion, this paper introduces a retrieval model for audio frequency data, which is combined with big data and applied to information retrieval. Firstly, the model is pre trained, and then the network parameters are fine-tuned through the network training method. By adjusting the network parameters, the recognition ability of the model is improved. In view of the assumption that whether external factors can interfere with external dependent variables on dependent variables, the multi group structure model is used for analysis. This method is a general method that can quickly find the target data under massive data. In the experiment, the features are used as the key words of the inverted table index to establish the table, and all the file information in the reference database will be stored in the corresponding entries in the inverted table according to its underlying features. When the feature of each query file finds data in the table, it only needs to use its eigenvalue to calculate the complexity once, and the information of the reference data with this feature can be searched.
INTERFERENSI PADA RUBRIK AKTUAL MAJALAH KARTINI EDISI OKTOBER–DESEMBER 2009

AbstractThis study provides a description of the types of interference and factors inthe Actual rubric of Kartini Magazine October–December 2009 edition, aswell as their implementation in learning Indonesian at school. This researchis useful theoretically and practically. The theory used in this study is asociolinguistic study. This research method is descriptive qualitative. Basedon the data analysis, this study resulted in a conclusion (1) the type ofinterference obtained the amount (102) of data; (2) the factors that cause theinterference of regional languages and foreign languages are the bilingualismof the speech participants, the low loyalty of the recipient language users, theneed for synonyms, and the prestige of the source language and style oflanguage; (3) the implementation of research results on lesson plans can beapplied in junior high schools in identifying and analyzing news texts, classVII (odd) using the 2013 curriculum teaching.Keywords: interference, Kartini Magazine, Implementation.
More with Less: ZeroQA and Relevant Subset Selection for AI2 Reasoning Challenge

Natural language processing has had a significant growth in recent years, two key factors being the increase of processing capabilities leading to very large models and the availability of larger standardized datasets. However, not every specific task has a fair amount of available data and using more data does not always lead to better results. Therefore, we also need to focus on obtaining good results even when small datasets are provided. For this reason, we propose a model for question answering, called ZeroQA, which ranked first place when submitted in two popular leaderboards for answering multiple-choice science questions: ARC Easy and ARC Challenge. Our ZeroQA model uses no transformers fine-tuned on the ARC training dataset, and relies mainly on transfer learning using a mixture of experts. We also propose methods of selecting relevant subsets from the ARC datasets for training and we use them to analyze how our model performs with less, but well chosen training datasets.
Robot Path Planning in Narrow Environments Using Improved Roadmap Sampling

Path planning is a fundamental problem in mobile robots that optimize the path to determine how the robot reaches its goal. In particular sampling-based methods are popular in robotics. However, the sampling-based method is unsuitable for dynamic and narrow environments, unlike the adaptive method due to its prior planning before moving. Moreover, applying the sampling-based method in real-time and dynamic environments becomes more difficult due to its high computational cost. In this paper, we propose an efficient sampling method for roadmap planners to decrease its computational cost and increase the success rate of path planning. The proposed method applies the artificial potential method and map-decomposition method to roadmap planners such as PRM to achieve the goal.
Relationship Between Symmetry and Physical Properties

The physical properties of crystals are defined by the relationships between measurable quantities. These quantities may or may not depend on the direction in which they are measured. In certain cases, the value of a certain property is constant for all directions of the crystal; therefore, isotropic and anisotropic crystals will be differentiated. It will be shown that the properties can be represented by tensors, scalars being those of range 0. Depending on the symmetry of the crystal and the tensor range of the properties, they can be represented geometrically, which is especially useful for optical properties. The Curie–Neuman principle, which shows the relationship between the point symmetry of a crystal before the external influence and the symmetry of its physical properties, is explained. Finally, scalar properties, specific heat, and density are explained. In Chaps. 11 to 15 , the optical properties of crystals and minerals are described, as a result of the interaction of light with them. The phenomena and properties that are observed with transmission and reflection polarization microscopes, instruments of routine use in the identification of minerals and rocks, are explained.
Efektivitas Penggunaan Bahan Ajar Digital Berbasis Android dalam Pembelajaran IPA pada Siswa Berkebutuhan Khusus

This study aims to determine the effectiveness of using Android-based digital teaching materials in science learning for students with special needs. This research is a qualitative research which conducted on respondents, namely students with special needs at the Special Secondary School level. Data collection was carried out using test instruments. Data collection was carried out by giving tests to students and questionnaires to teachers. The collected data were analyzed descriptively quantitatively. The analysis is carried out by providing an interpretation of the data obtained so that it becomes clearer and more meaningful. The results showed that Android-based digital teaching materials were causing an increase in students learning outcomes in this subject by 83.3 percent. The study showed that android-based digital teaching materials effectively used in science learning for students with special needs. Further research is needed using more varied media and a wider scale of research.&#x0D; Keywords: Teaching materials, android, students with special needs.