Reviewerly/exHarmony huggingface dataset:
Assessment of Spatial Intervention of Public Spaces by Locative Augmented Reality Games Players

Augmented Reality (AR) games appear to have had a massive growth in the era of the Fourth Industrial Revolution (IR 4.0). Locative AR games require the usage of big spaces for gamers to move around. Nevertheless, there is a question of whether public spaces are suitable for the spatial intervention of locative AR games players. Spatial intervention may become an issue among the public regarding accessibility, permeability, openness, centrality, and sense of security. This paper assesses the public perceptions of the spatial intervention of public spaces by locative AR games players. Researchers conducted this research by using both qualitative and quantitative approaches. The primary data was obtained based on observation and survey questionnaires, whilst the secondary data was collected using desk research. The findings of this research could help city authorities to consider formulating new design criteria of public spaces that are safe for both AR games’ players and the public.
Smart House Control Using Hand Gestures Recognition LabVIEW Applications

Smart homes have a positive impact on people with physical disabilities by improving their quality of life. Thus, depending on the health and physical condition of the person, a certain type of architecture can be chosen. This paper presents a system designed to command a smart house low-cost prototype being based on two modalities of hand gestures recognition. The first approach is referring to the usage of an envelope signal taken from an electromyography (EMG) sensor. The gestures sequence of tightening and releasing an elastic object in the hand was coded in such a way that through the digital output signals, different appliances in a smart home can be controlled. The second application uses hand gestures images and with the help of a recognition algorithm the same smart home prototype can be commanded. A particle classifier was used in order to recognize nine hand gestures. The beneficiary of this system could be mainly a person with motor disabilities that can manage in a simple and relatively inexpensive way any household devices such as lights, doors, fans, TV sets, heaters and others. The applications are implemented in LabVIEW environment from National Instruments (NI) and they offer a friendly interface and also a simple and robust way to communicate with the relays module that controls the intelligent house.
ANALISIS K-MEANS CLUSTER PADA KABUPATEN/KOTA DI PROVINSI BANTEN BERDASARKAN INDIKATOR INDEKS PEMBANGUNAN MANUSIA

The Human Development Index (HDI) is one of the parameters of success in the development of the quality of human life, besides that at the regional level, the HDI is an indicator of the primary performance measurement and allocation of Regional Incentive Funds in promoting the welfare of the people in the area. In 2020 the Banten Province Human Development Index 72.45 only rose 0.01% compared to 2019, lower than the growth in 2019, which reached 0.68% and is still stuck in the high category (70≤HDI≤80), this indicates the progress of human development in Banten experienced a slowdown, In addition, when compared to the growth of the HDI-forming indicators in 2019, all components that make up the HDI experienced a slowdown in growth except for RLS which experienced growth acceleration of 0.33% from 1.39% in 2019 to 1.72% in 2020. So it is necessary to do a deeper analysis to determine the characteristics of the indicators that make up the HDI in the City as a contributor to the HDI value of the Banten Province so that efforts can be made to increase human development as evidence of improving the welfare of the people in the Banten Province. The K-Means Cluster method is used to group cities in Banten Province based on similar characteristics in terms of the HDI compiler indicators, including Life Expectancy at Birth, Expected Years of Schooling, and Average Length of School in, and Expenditure per Capita. Based on the results of the analysis obtained three clusters consisting of cities with similar characteristics in each cluster. Cluster 1 is a City with a low HDI indicator consisting of Pandeglang, Lebak, Serang. Cluster 2 is a City with a medium HDI indicator consisting of Tangerang, Cilegon, Serang City. Cluster 3 has a high HDI indicator consisting of Tangerang City and South Tangerang City. After obtaining City information based on the characteristics of each cluster, then the Banten Provincial government can provide direction and policies to each City in Clusters 1 and 2 to be able to develop activity programs with more attention to the HDI compiler indicators so that the Human Development Index in the City can increase
PENGARUH LAYANAN ADMINISTRASI TERHADAP KEPUASAN SISWA MTs. UNGGULAN MUKHTAR SYAFA�AT BLOKAGUNG TEGALSARI BANYUWANGI TAHUN PEMBELAJARAN 2019/2020

Abstract&#x0D; The purpose of this study was to determine the quality of administrative services at MTs Unggulan Mukhtar Syafaat Benefits Blokagung Tegalsari Banyuwangi. Second, what is the level of satisfaction of the students at MTs Unggulan Mukhtar Syafaat Benefits Blokagung Tegalsari Banyuwangi. Third, is there an effect of service on the satisfaction of students at MTs Unggulan Mukhtar Syafaat Blokagung Tegalsari Banyuwangi.&#x0D; The method in this study uses quantitative data collection used in this study is a questionnaire, observation, and documentation. While the data validity test uses the Product moment formula, to find data reliability using the Cronbach Alpha formula. Then to test the hypothesis using the T-test and F test, while for the normality test using the Kolmogorov-Smirnov formula. In data analysis using Simple Linear Regression analysis.&#x0D; The results of this study indicate that: (1) the quality of administrative services at MTs Featured Mukhtar Syafaat Blokagung Tegalsari Banyuwangi for the 2019/2020 academic year is quite good, because the results of the T-test are 26.038&gt; 1,290 t table., Which means that Ha is accepted; (2) the level of satisfaction MTs Featured students Mukhtar Syafaat Blokagung Tegalsari Banyuwangi Academic Year 2019/2020 is quite good, because the results of the T count is&gt; 1920 ta table, which means Ha is accepted; (3) is there an effect of service on the satisfaction of students of MTs Featured Mukhtar Syafaat Blokagung Tegalsari Banyuwangi Year The 2019/2020 lesson was 87.4% while the remaining 12.6% was influenced by other variables that were not studied, which means that the effect of administrative services on student satisfaction at MTs Unggulan Mukhtar Syafaat Blokagung Tegalsari Banyuwangi is very good.
Chapter 10. Explainable Neuro-Symbolic Hierarchical Reinforcement Learning

Human-robot interactive decision-making is increasingly becoming ubiquitous, and explainability is an influential factor in determining the reliance on autonomy. However, it is not reasonable to trust systems beyond our comprehension, and typical machine learning and data-driven decision-making are black-box paradigms that impede explainability. Therefore, it is critical to establish computational efficient decision-making mechanisms enhanced by explainability-aware strategies. To this end, we propose the Trustworthy Decision-Making (TDM), which is an explainable neuro-symbolic approach by integrating symbolic planning into hierarchical reinforcement learning. The framework of TDM enables the subtask-level explainability from the causal relational and understandable subtasks. Besides, TDM also demonstrates the advantage of the integration between symbolic planning and reinforcement learning, reaping the benefits of both worlds. Experimental results validate the effectiveness of proposed method while improving the explainability in the process of decision-making.
Hybrid scatter and ant search feature subset selection: applications in classification problems

This paper presents an approach to metaheuristic-based feature subset selection. Feature selection is an NP-problem. This means that finding the optimal feature set is an intractable problem. Approximate algorithms are very convenient since the exhaustive search is prohibitive due to the extremely high computational cost. Metaheuristics are a key approach in the field of data mining and especially in data pre-processing. Scatter search has been applied in context of feature selection although ant search is more widespread in the data preparation area. This contribution hybridises both search strategies to get a prediction model which is able to predict faster and more accurately with further unseen data. First the scatter search takes place and the reached solution is improved by means of an ant search. The test-bed comprises a good number of high-dimensional data sets. Results are very substantial since the second metaheuristic improves greatly the performance of the classifiers and reduces the models&#x2019; complexity in terms of input feature space.
Development of lexical speech skills of high school students based on educational computer games

The purpose of the study is to substantiate the didactic potential of educational computer games in the development of lexical speech skills in high school students. We analyze the basic skills that are formed in the study of vocabulary. The basic lexical skills and their division into productive and receptive skills are considered. The analysis of the basic principles under which the process of learning foreign words takes place is carried out. The main advantages associated with learning vocabulary using computer games are considered. These include: encouraging creativity, the ability to create teamwork, easy adaptation for all ages and all language levels. The reasons for the growing popularity of games are analyzed in the context of training. These reasons include: in-terest that students have in class through games; beneficial effect on the educational process; the emergence of a need to create such a learning environment; the emergence of skills of independent work. Scientific novelty consists in the generalization of the experience of teaching vocabulary based on computer games. We also analyze the main advantages associated with teaching foreign language vocabulary to high school students using computer games and consider the reasons for the growth in popularity of games in the context of foreign languages teaching. As a result, a conclusion is made about the positive influence of computer games in foreign language teaching and improving the lexical skills of high school students.
Quantum Randomness Expansion with Uncharacterized Homodyne Detection Secure against Quantum Side-Information

We propose a quantum randomness expansion protocol based on untrusted homodyne detection. We certify the randomness of the output against quantum side-information without assuming that the devices behave identically and independently in each round.
A Human-machine Cooperation Protocol for Machine Translation Output Edit Annotation

We report on a study exploring automatic edit annotation in a post-editing corpus with a new method for computing edit types. We examine edit type association with quality scores assigned to the machine translation output and the post-edited texts. Finally, we account for shortcomings in our method and point out edit types worth leveraging.
Efecto de las interacciones de estudiantes de ciencias con laboratorios virtuales de realidad aumentada para el desarrollo de visualización espacial

The main scope of this article is to highlight the potential of student interactions in Science teaching, from educational resources in augmented reality, and its effect on the development of spatial visualization skills. Therefore, it presents a contextualization about Science teaching, the use of real laboratories, as well as its limitations, presenting as an alternative the use of educational resources in augmented reality with the support of mobile devices. The solution was tested in activities that complement the Science teaching and learning process with basic education students in Brazil. It aimed to investigate whether students' interactions with educational resources in augmented reality can contribute to the development of spatial visualization skills. The methodological procedures were organized in a quasi-experimental approach, through activities foreseen in a test protocol carried out with 208 participants divided into two groups: Control (n=96 subjects) and Experimental (n=112 subjects). In general terms, the results of this research point to contributions arising from the interactions of students with educational resources in augmented reality, both for the development of spatial visualization skills, as well as for the observation of the phenomenon and understanding of the abstract concepts associated with it, formulation and testing of hypotheses, as well as conclusions from the situations experienced.
Mission Book Game: Enhancing Fifth-Grade Students’ Learning Motivation on Thematic Learning

The lack of use of learning media in the learning process causes students to find it difficult to understand the material. This study aims to produce learning media that can increase students' motivation and activeness in the learning process. Media development in this study is guided by the ADDIE model procedure which consists of several stages, namely analysis (analyze), design (design), development (development), implementation, and evaluation (evaluate). The subject in this development research is the mission book game media to increase the learning motivation of fifth-grade students while the object in this research is the validity and effectiveness of the mission book game media developed. This development research method is a qualitative and quantitative analysis method. The data collection used is a questionnaire method with data collection instruments in the form of a rating scale by giving an assessment instrument to 4 experts, namely, 2 material experts, 2 media experts, 2 practitioner responses, and 12 students. The data were analyzed by testing the validity and reliability test of the mission book game media based on data from experts, practitioners, and students' responses. The data obtained is calculated using the mean formula to determine the average validity of the media. The average validity score of the mission book media game in terms of material experts is 4.8 with very valid criteria, in terms of media experts it is 4.4 with very valid criteria, in terms of practitioner responses it is 4.7 with very valid criteria and in terms of student response of 4.9 with very valid criteria. The motivational data analysis technique used is descriptive quantitative statistical data analysis techniques in the form of prerequisite tests and t-tests. The results of the hypothesis test showed a significance value of 0.033 which means 0.033 &lt;0.05, so it can be concluded that there is an effect of the.
Blockchain

Blockchain is a digital ledger of economic transactions that is constantly updated by an unlimited number of users and it is considered impossible to corrupt. It is a list of continuous records in blocks. Blocks hold sets of transactions and they connected to the previous blocks. A block is also time stamped (Carlozo ). Blocks are chained with each other through hash identifiers. The complete blockchain is copied in a number of places in the network and this makes blockchain a distributed database (Bozic et al. ).
Quantizing Neural Networks for Low-Power Computer Vision

Over the last years, Neural Networks (NNs) have been widely adapted in Computer Vision (CV) applications. While for many tasks they outperform traditional CV algorithms they often come at a high compute cost. Even mobile friendly architectures such as MobileNet still require hundreds of million floating point operations. To further reduce the energy efficiency and latency of NNs, quantization can be used to replace the original floating-point operations with low bit fixed-point operations. In this chapter we introduce NN quantization for low-power computer vision. Afterward we highlight recent advances in post-training quantization, a class of algorithms that can be applied to pretrained NNs and do not require any expert knowledge. In the last part we will focus on quantization-aware training, a technique that trains NNs with simulated quantization operations. Take-aways Introduces neural network quantization Serves as a practical guide to quantization simulation with HW considerations Introduces state-of-the-art post-training quantization (PTQ) techniques that are easy to use. Introduces state-of-the-art quantization-aware training (QAT) approaches that result in best performance. Defines standard PTQ and QAT pipeline and evaluates them on several computer vision models and tasks.
Construction of Deep Representations

This chapter deals with the construction of deep representations. With the advancement in technology and more and more accumulation of data, domains like artificial intelligence, bioinformatics, businesses, etc. are in need of data representation learning as a critical step for the facilitation of tasks such as image classification, object recognition, speech recognition, data retrieval, and recommendations over data. One of the most important and present-day challenges is learning the underlying structure of data and uncovering precious information from data for huge applications. The field of deep representation learning over the past 100 years includes the proposal of principal component analysis by K. Pearson in 1901, followed by linear discriminant analysis in 1936, perceptron in 1958, back propagation in 1986, and initiation of representation learning by G. Hinton in 2006 with the advent of neural networks.
MedTextSeg: A Deep Dual Sequential Model for Section Segmentation in Medical Reports

Segmenting clinical texts into sections that uncover the underlying content structure is an important NLP task as it can facilitate robust information extraction in the medical domain. Recently, supervised neural models have been proposed for this task, however, they fail to capture the multi-granural sequential dependency characteristic within the texts effectively. In this light, we introduce the MedTextSeg model, which learns the sentence representation by modeling both the local and global contexts from the surrounding sentences. Through both quantitative and qualitative evaluations, we show that the proposed sequential encoding of sentences improves the overall section label prediction performance on several real-world datasets compared to state-of-the-art methods.
Odia Handwritten Numeral Recognition: A Hybrid Modelling Approach

The task of recognizing characters and numbers from handwritten images has a wide variety of applications in today's world In this paper, a deep hybrid learning approach using transfer learning to classify numbers from handwritten images of regional language Odia numbers was implemented. The performance across various optimizers on VGG16, and even among various traditional machine learning classifiers, were compared. Each of the networks was trained for 50 epochs, with ReduceLR on plateau as a callback mechanism to make the model learn the parameters better. Augmentation techniques such as image shearing and rescaling to further generalize the model.
Towards Learning Geometric Shape Parts

In this article, we explore the effectiveness of using neural networks to generate skeleton-based representations of shapes. Deep-learning approaches have proven very efficient to extract meaningful information from images. Our goal is to learn a mapping from a binary image of a 2D shape to a parametric Bézier curve representation of the medial axis of the shape using a convolutional neural network. We determine the most salient curves in the Blum medial axis and then train a CNN to produce one, two, and five curve medial representations. Using a Bézier curve representation of the medial axis reduces the number of parameters, since we express medial curves and their radii as degree-five Bézier curves, and learn only the associated control points rather than the full point set of the medial axis.
Unit Optimalization Using the QM App for Windows on Perumahan Bukit Aradiar Permai Balikpapan

&lt;p&gt;&lt;em&gt;Abstract&lt;/em&gt;&lt;/p&gt;&lt;p&gt;Housing demand continues to increase along with the increase in economic activity and the number of residents in the city of Balikpapan according to the 2017 Central Statistics Agency as many as 636,012 people to 645,727 people. The increase in housing demand is driven by the community's perspective that home ownership must be met while housing availability is limited. Based on the Balikpapan City Government in the 2012 Regional Spatial Plan, the plan to develop a spatial pattern of cultivation areas is more directed towards the north and east parts of the city so that population growth and development are not concentrated in the city center. This is a challenge for housing providers to meet the needs of long-lived communities and migrant communities by building housing located in the East of Balikpapan City as a place to live. The increase in land prices is so high in Balikpapan due to the movement of the capital from Jakarta to East Kalimantan, making housing prices also higher. The limited land owned by the housing developer must be utilized as well as possible for the construction of housing units, construction of facilities, and the existence of green space in the housing according to government regulations related to Balikpapan City RTRW. Land owned by housing developers that vary in shape is extremely limited with the type of house being built also varies and the price of the unit offered is different for each unit. For this reason, the developer must be able to optimize the production of the type of house that will be built based on government regulations and the National Spatial Plan, optimizing the land to get the optimum profit. This optimization uses the assistive application of QM for Windows and obtained 98 units for type 40/120 and type 45/120 for 102 units with optimum profit yielding Rp 104,292,098,201 for the BEP method.&lt;/p&gt;&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords:&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; &lt;/em&gt;&lt;em&gt;Optimization&lt;/em&gt;&lt;em&gt;;&lt;/em&gt;&lt;em&gt; QM For Windows&lt;/em&gt;&lt;em&gt;;&lt;/em&gt;&lt;em&gt; Unit.&lt;/em&gt;&lt;/p&gt;
Lectures in distant format: certain methodological techniques

This article is the result of research carried out during the pandemic, which was intended to determine the interrelation between certain methodological techniques and engagement of students in the distant learning process. The following techniques were used for improving the effectiveness of educational process: well-defined structure of the lecture, presentation as the system of questions and topics for discussion, grasping new material in the form of discussion, test cases on the material learned, weekly results and systematization of knowledge, implementation of video materials in homework. The authors held lectures in accordance with all listed points, observing the response and motivation of students. The surveys conducted at the beginning and at the end of the lecture course indicate a sharp increase in cognitive activity, overall satisfaction of students, and interest in further study of the discipline. The students also gave a five point scale rating to each of the offered methodological techniques; in spite of the hypothesis advanced by the authors, the students highlighted presentation as the system of questions and discussion during a distant lecture. The research demonstrates that such methodological techniques effectively increase students' engagement in the learning process, as well as stimulate cognitive activity. The described aspects of conducting lectures can be applied not only in distant format, but in offline learning as well.