Reviewerly/exHarmony huggingface dataset:
Virtual Laboratory-Based Game Application: The Quality and Its Effects Towards Students’ Motivation and Self-Regulated Learning

Considering that students have a lot of experiences using mobile applications in their daily life, teacher should engage mobile application as learning media, thus the student are more motivated to learn independently. As a consequence, the teachers should implement existing mobile learning in the learning process and it is even better if they can develop it themselves. Besides, developing mobile learning is being heavy burden for a teacher as they still lack of skills to design and to develop mobile learning. Therefore, we aimed to explore the quality of Amazing Science application as mobile learning incorporated with a virtual laboratory based game application and to investigate its effect on students’ motivation and self-regulated learning. This research involved 5 sciences teachers and 50 students from five secondary schools in Yogyakarta, Indonesia. The research data were collected through online questionnaires consisting of three instruments, namely; viz product quality questionnaire for product validation, motivation questionnaires and self-regulated questionnaires for product implementation. Product validation data are quality data in the form of categories, so they are converted to data score using the Likert scale. Meanwhile, implementation data consisting of motivation and self-regulated learning data were analyzed with a sample paired t-test to discover the effect of product implementation towards motivation and self-regulated learning. The result revealed that Amazing Science application has a good quality according to the reviewers and students through a preliminary test and limited trial. Moreover, there are significant differences in both students’ motivation and self-regulated learning before and after the implementation of Amazing Science. However, there is no significant correlation between students’ motivation and self-regulated learning. From the findings, it can suggest that Amazing Science should be implemented by combining with the cooperative learning model, so others' skills can be improved. Besides, it can rebuild on another learning material or subject
Mastering the power of creative thinking

Creative thinking is one of the human skills through which we visualise new perspectives, adopt new ways to solve problems, and design innovative solutions. Creative thinking facilitates new pathways for progress and prosperity of humankind. In this chapter, I will discuss my experiences in promoting creative thinking and nurturing creative thinking skills of young people. We partner with government agencies and educational institutions to deliver technology and creative thinking skill programmes in countries around the world. In recent years, scores of young people are using digital technologies including artificial intelligence for developing creative solutions for solving day-to-day problems faced by communities. Creative thinking skills can be learnt by anyone. Based on my experience and research evidence, I will discuss practical ways to master the power of creative thinking.
Upaya Pengendalian Banjir Kawasan Sub-Das Celeng Pra Pembangunan Embung Imogiri

Flood on March 17 in the Celeng River, Wukirsari Village, D.I. Yogyakarta became the biggest flood that ever happened on the Bog River. Floods are caused by heavy flow of water from the hills in the Imogiri and Dlingo areas. The Celeng River overflowed and submerged four hamlets in Wukirsari Village, Imogiri District. This study aims to determine flood control efforts in the Celeng sub-watershed area. The research location is in the Kali Celeng sub-watershed, Wukirsari, Imogiri, D.I. Yogyakarta with the control point located in the lower reaches of the Celeng River right at the confluence of the Celeng River and the Oyo River. The hydrological analysis was calculated using the Gamma 1 unit hydrograph method with a return period of 10 years. The maximum flood discharges for each of the Celeng sub-watersheds are 75.73 m3/s, 38.22 m3/s, 37.20 m3/s, 18.54 m3/s, and 21.57 m3/s, and 26.29 m3/s, while the 10-year return flood discharges for the Oyo watershed is 959.60 m3/s. The hydraulic analysis was carried out by modeling the 13.35 km long Celeng River channel with HEC-RAS 4.1 software. The flow simulation is carried out steadily. The simulation results show that during the simulation of the existing state there are several points of the section of the Celeng River that overflow. The overflowing sections are then normalized with certain groove dimensions that are adjusted to the location of the flood point. The results of the flow simulation after normalization show that most of the Celeng River channel can accommodate the flood discharge that occurred. The sections that still overflow after normalization are then given embankments with an average height of 0.75 m.
Comparison of Brownian jump and Brownian bridge resetting in search for Gaussian target on the line and in space

For $d\ge1$ and $r>0$, let $X^{(d;r)}(\cdot)$ be a $d$-dimensional Brownian motion with diffusion coefficient $D$, equipped with an exponential clock with rate $r$. When the clock rings, the process jumps to the origin and begins anew. For a parameter $T>0$, let $X^{\text{bb},d;T}(\cdot)$ be the process that performs a $d$-dimensional Brownian bridge with diffusion coefficient $D$ and bridge interval $T$, and then at time $T$ starts anew from the origin, and let $X^{d;T}$ be the process that performs a $d$-dimensional Brownian motion with diffusion coefficient $D$ up until time $T$, at which time it jumps to the origin and begins anew. Denote expectations by $E_0^{d;r},E_0^{\text{bb},d;T}$ and $E_0^{d;T}$. These Markov processes with resetting search for a random target $a\in\mathbb{R}^d$ with centered Gaussian distribution of variance $\sigma^2$, denoted by $\mu_{\sigma^2}^{\text{Gauss},d}$. Fix $\epsilon_0>0$. Let $\tau_a$ be the hitting time of $a$, for $d=1$, and the hitting time of the $\epsilon_0$-ball around $a$, for $d\ge2$. The expected time to locate the target for each of the processes is $\int_{\mathbb{R}^d}\big(E_0^*\tau_a\big)\mu_{\sigma^2}^{\text{Gauss},d}(da)$, where $E_0^*$ stands for $E_0^{d;r}, E_0^{\text{bb},d;T}$ or $E_0^{d;T}$. For $d=1$ and $d=3$, we calculate the infimum of each of the above expressions over $r>0$ or $T>0$ as appropriate, in order to compare the relative efficiencies of the three search processes. In terms of the parameters $D$ and $\sigma$, in the 1-dimensional case these infima scale as $\frac{\sigma^2}D$, which is a natural scaling, but in the 3-dimensional case, they scale anomalously as $\frac{\sigma^3}D$. We also show that in the 2-dimensional case, the infimum over $r>0$ for the first of the three search processes scales as $\frac{\sigma^2}D$ as in the 1-dimensional case.
Python as a Scientific Calculator

Python is one of the most popular programming languages, widely used for data analysis and modelling, and is fast becoming the leading choice for scientists and engineers. Unlike other textbooks introducing Python, typically organised by language syntax, this book uses many examples from across Biology, Chemistry, Physics, Earth science, and Engineering to teach and motivate students in science and engineering. The text is organised by the tasks and workflows students undertake day-to-day, helping them see the connections between programming tools and their disciplines. The pace of study is carefully developed for complete beginners, and a spiral pedagogy is used so concepts are introduced across multiple chapters, allowing readers to engage with topics more than once. “Try This!” exercises and online Jupyter notebooks encourage students to test their new knowledge, and further develop their programming skills. Online solutions are available for instructors, alongside discipline-specific homework problems across the sciences and engineering.
Using Augmented Reality Toward Improving Social Skills: Scoping Review (Preprint)

<sec> <title>BACKGROUND</title> Augmented reality (AR) has emerged as a promising technology in educational settings owing to its engaging nature. However, apart from applications aimed at the autism spectrum disorder population, the potential of AR in social-emotional learning has received less attention. </sec> <sec> <title>OBJECTIVE</title> This scoping review aims to map the range of AR applications that improve social skills and map the characteristics of such applications. </sec> <sec> <title>METHODS</title> In total, 2 independent researchers screened 2748 records derived from 3 databases in December 2021—PubMed, IEEE Xplore, and ACM Guide to Computing Literature. In addition, the reference lists of all the included records and existing reviews were screened. Records that had developed a prototype with the main outcome of improving social skills were included in the scoping review. Included records were narratively described for their content regarding AR and social skills, their target populations, and their outcomes. Evaluation studies were assessed for methodological quality. </sec> <sec> <title>RESULTS</title> A total of 17 records met the inclusion criteria for this study. Overall, 10 records describe applications for children with autism, primarily teaching about reading emotions in facial expressions; 7 records describe applications for a general population, targeting both children and adults, with a diverse range of outcome goals. The methodological quality of evaluation studies was found to be weak. </sec> <sec> <title>CONCLUSIONS</title> Most applications are designed to be used alone, although AR is well suited to facilitating real-world interactions during a digital experience, including interactions with other people. Therefore, future AR applications could endorse social skills in a general population in more complex group settings. </sec> <sec> <title>CLINICALTRIAL</title> <p /> </sec>
Room-temperature strong coupling of a single-photon emitter and a bound-state-in-the-continuum cavity (Conference Presentation)

Cavity quantum electrodynamics describes coupled systems comprising of optically active emitters with atom-like transitions, such as single-photon emitters (SPEs), and optical cavities that underlies various fundamental quantum properties. In the strong coupling regime, SPEs and cavity photons coherently exchange energy leading to two new hybrid states that significantly modify the optical responses of the originally uncoupled or weakly coupled states. As a result, various intriguing effects could be realized such as Rabi oscillations, nonlinearities, photon blockade when the system is in strong coupling conditions. To achieve strong coupling between SPEs and photonic cavities, SPE transition energies have to coincide with cavity resonances (spectral overlapping), SPEs are precisely positioned at the electric field antinodes (spatial overlapping) and SPE emission decay is slower than coupling strength (narrow linewidth). Such stringent conditions impose serious challenges for experimental realization of SPE-cavity strong coupling particularly at room temperature due to the lack of stable single-photon sources with high color purity at high temperatures and controllability on positioning SPE in cavity. Strong coupling has been reported for single semiconducting quantum-dots and photonic crystal cavities at cryogenic temperature1,2 and for single molecules and plasmonics cavities at room temperature.3 Here, we introduce a new approach using point-defects purposely created in a two-dimensional few-layer-thick hexagonal boron nitride (hBN) film as single-photon emitters and a robust photonic cavity with arbitrarily high quality-factor based on bound-state-in-the-continuum (BIC) concept.4 We observe, at room temperature and in ambient conditions, strong coupling between SPEs and BIC photons characterized by a Rabi splitting of ∼7 meV. The coupling strength can be tuned by varying detuning energy that is strongly supported by theoretical calculation. Our findings unveil new opportunities for exploiting the BIC cavity to realize the long-sought strong coupling with SPEs, ultimately for the development of quantum-based devices operating at ambient conditions. 1Reithmaier, J. P. et al. Nature 432, 197-200 (2004) 2Yoshie, T. et al. Nature 432, 200-203 (2004) 3Chikkaraddy, R. et al. Nature 535, 127-130 (2016) 4Do, T. T. H. et al., manuscript in preparation (2022)
Quantitative phase imaging using diffractive optical networks (Conference Presentation)

Quantitative phase imaging (QPI) has emerged as a powerful, label-free tool for revealing specimens' optical path length information. We demonstrate diffractive QPI networks that all-optically synthesize the quantitative phase image of an object by converting the optical path length variations at the input into spatial intensity distributions at the output plane. These diffractive QPI networks are spatially-engineered using deep learning to form all-optical coherent processors, and can enable power-efficient, high frame-rate and compact quantitative phase imaging systems that will be useful for various applications, including, e.g., on-chip microscopy and sensing.
Literature Classification Research on Fusion of Pretraining Model and Bidirectional Gated Recurrent Unit

At present, manual literature classification methods are inefficient and rely on expert knowledge, while traditional machine learning literature classification methods need to construct complex feature engineering, and usually use static word embedding methods such as TF-IDF or Word2Vec to represent document text, ignoring context information and the degree of influence of each part of the literature text on the classification results. In response to the above problems, the ERNIE-BiGRU-Attention model is proposed. The model first preprocesses the document index data and then fuses the processed titles, abstracts and keywords into the ERNIE pretraining model to generate corresponding. Then, the model uses the bidirectional gated recurrent unit to extract features and learn semantics. Finally, the attention mechanism is introduced to assign different weights according to the influence of each part of the text on the classification results to complete the classification task. The experiment compares the macro precision rate, macro recall rate, and macro F1 value under different models using the feature input of titles, abstracts, and fusion of titles, abstracts, and keywords respectively. The results show that the proposed model improves the accuracy of literature classification and provides literature classification research with a new idea.
Improving Named Entity Recognition in Tor Darknet with Local Distance Neighbor Feature

Name entity recognition in noisy user-generated texts is a difficult task usually enhanced by incorporating an external resource of information, such as gazetteers. However, gazetteers are task-specific, and they are expensive to build and maintain. This paper adopts and improves the approach of Aguilar et al. by presenting a novel feature, called Local Distance Neighbor, which substitutes gazetteers. We tested the new approach on the W-NUT-2017 dataset, obtaining state-of-the-art results for the Group, Person and Product categories of Named Entities. Next, we added 851 manually labeled samples to the W-NUT-2017 dataset to account for named entities in the Tor Darknet related to weapons and drug selling. Finally, our proposal achieved an entity and surface F1 scores of 52.96% and 50.57% on this extended dataset, demonstrating its usefulness for Law Enforcement Agencies to detect named entities in the Tor hidden services.
Sign Determination to Measure Non-Monotonous Displacements in Temporal Speckle Pattern Interferometry Without a Temporal Carrier

In this paper, we present a generalized method to automatically detect the correct sign of non-monotonous displacements in temporal speckle pattern interferometry without the introduction of a temporal carrier in the optical setup. This approach can be used with any phase retrieval technique.In this proposed method, when the phase change is evaluated, the sign ambiguity is resolved due to a function that determines the correct sign of the displacement between two consecutive speckle interferograms. The errors introduced by the proposed function are determined using computer-simulated speckle interferograms, and its performance is analyzed using three phase recovery techniques and different phase distributions and average speckle sizes. A relation between the sliding window used to compute the correct sign and the speckle sizes is also presented.Finally, the presentation is illustrated with an experimental application of the proposed method to detect the correct sign of the out-of-plane displacement field of a metal plate.
Compensation of off-axial aberrations using polarization-masked azimuthal Walsh filters

In the presence of astigmatism, the three-dimensional distribution of rays in the image region passes through two orthogonal lines, the vertical sagittal foci and the horizontal tangential foci. With increasing astigmatic behaviour of the imaging system, the sagittal and tangential foci will be farther removed from each other and the separation between these two planesserves as the measure of astigmatism. Midway between these planes, i.e., corresponding to the defocus term, 𝑊20 = − 𝑊22⁄2 , where 𝑊22 is the co-efficient of astigmatism, the intensity spread is found to be minimum and the transverse plane passing through this point is referred to as the plane of minimum aberration variance. For a diffraction-limited imaging system, the IPSF on this plane is the Airy pattern. In our study, each sector of the azimuthal Walsh aperture is masked by suitably oriented linear polarizers. The polarization phase introduced is a function of the state of polarization (SOP) of the input beam, the transmission axis of orientation of the masking polarizer and the orientation of the analyzer. A feasible method to assess the degree of astigmatic compensation is to compute the IPSF at the plane of minimum astigmatic variance and compare the intensity distribution with that of airy pattern. IPSFs for different values of 𝑊22 are computed with the presence of compensating polarization masked azimuthal Walsh filters at 0° and 90° with input beam parameters a=b=1 , 𝛿 = 90° and analyser kept at a particular angle. The results are compared with IPSFs computed for an unmasked lens and airy pattern.
The Use of Digital Technology for Enhancing Proof in Forensic Document Examination

Visual perception is the most important tool for Forensic Document Examination (FDE). However, the limits of human visual perception, along with multiple optical illusions intrinsic to human vision, mean that objectively measuring digital software tools are needed to supplement expert human evaluation of documents. Specifically, standardized scanning and processing of documents are essential, using easily available commercial software. It is crucial that scanned questioned documents can then be studied without time limitations and without fear of damaging the original documents. Moreover, FDE dedicated artificial intelligence (AI) software applications and image processing software are also very useful for signature and/or handwriting authentication, as the software results are independent of the user. Thus, the use of digital technology enhances proof in FDE cases in courts. Knowledge of specific human visual limitations – the major ones listed here – is a prerequisite, so that the examiner knows in which situations human eyesight is less reliable than digital software calculations. A case study is provided, demonstrating the utility of this approach. Future perspectives of the application of digital technology in FDE, along with correlation to kinesiology and electromyography, are also discussed.
Multi-modal Graph Attention Network for Video Recommendation

In view of the problems of cold start and data interaction in recommendation systems, and most current recommendation algorithms ignore the diversity of data types, the combination of multimodal data and knowledge graph is bound to improve the pertinence of video recommendation. In this paper, we propose Multi-modal Knowledge Graph Attention Network (MMKGV) model, and all the entity nodes of the knowledge graph are innovatively introduced into multimodal information. The high-order recursive node information dissemination and information aggregation are carried out on the multimodal knowledge graph through the graph attention network. In the model, the triplet function of the knowledge graph is used to construct the triplet inference relationship, and the vector representation generated by the final aggregation is used for recommendation. Through extensive experiments on two public datasets TikTok and Kwai, the results show that the MMKGV can effectively improve the effect of video recommendation compared with other comparison algorithms.
PERANCANGAN APLIKASI PENJUALAN CCTV PADA PT INTERNUSA TECHNOLOGY DI JAKARTA SELATAN BERBASIS ANDROID

Watching the rapid development of science and technology, companies that run a sales business are required to be more effective in working and marketing their products. PT Internusa Technology or also known as INUS, is a company engaged in the sale of analog and digital CCTV. PT Internusa Technology has problems in data collection transactions. In addition, there are other problems, there are still very few promotional media to introduce various kinds of products that are to be sold and also prospective buyers sometimes have difficulty in knowing the prices and types of products to be sold by PT Internusa Technology. The purpose of research and making this journal is to make the sales system at PT Internusa Technology computerized, make it easier for PT Internusa Technology to market its products, and also make it easier for prospective buyers to find out the types and prices of products to be sold by PT Internusa Technology. The research method used is Research and Development (R&amp;D). The result is making of applications design that support all the problems discussed previously. This application can make it easier for users to make CCTV sales transactions, the company can market their own products to be sold online with a larger target market, and making it easier for buyers and sellers to transact or just look for information about the store.