Reviewerly/exHarmony huggingface dataset:
Efficient New Conjugate Gradient Methods for Removing Impulse Noise Images

In most applications, denoising image is fundamental to subsequent image processing operations. In this research, we derivation a new formula of conjugate gradient methods based on the quadratic model. The fact that the search direction created at each iteration of the proposed approach is descending and independent of the line search makes it interesting. The use of Wolfeconditions also determines the global convergence of the suggested approach. To prove the viability of the suggested approach, comparison tests on impulse noise reduction are given.
"I'm sorry to hear that": Finding New Biases in Language Models with a Holistic Descriptor Dataset

As language models grow in popularity, it becomes increasingly important to clearly measure all possible markers of demographic identity in order to avoid perpetuating existing societal harms. Many datasets for measuring bias currently exist, but they are restricted in their coverage of demographic axes and are commonly used with preset bias tests that presuppose which types of biases models can exhibit. In this work, we present a new, more inclusive bias measurement dataset, HolisticBias, which includes nearly 600 descriptor terms across 13 different demographic axes. HolisticBias was assembled in a participatory process including experts and community members with lived experience of these terms. These descriptors combine with a set of bias measurement templates to produce over 450,000 unique sentence prompts, which we use to explore, identify, and reduce novel forms of bias in several generative models. We demonstrate that HolisticBias is effective at measuring previously undetectable biases in token likelihoods from language models, as well as in an offensiveness classifier. We will invite additions and amendments to the dataset, which we hope will serve as a basis for more easy-to-use and standardized methods for evaluating bias in NLP models.
Enhanced heralded single-photon source with a photon-number-resolving parallel superconducting nanowire single-photon detector

Heralded single-photon sources (HSPS) intrinsically suffer from multiphoton emission, leading to a trade-off between the source's quality and the heralding rate. A solution to this problem is to use photon-number-resolving (PNR) detectors to filter out the heralding events where more than one photon pair is created. Here, we demonstrate the use of a high-efficiency PNR superconducting nanowire single-photon detector (SNSPD) as a heralding detector for a HSPS. By filtering out higher-order heralding detections, we can reduce the $g^{(2)}(0)$ of the heralded single photon by $(26.6 \pm 0.2)\,\%$, or alternatively, for a fixed pump power, increasing the heralding rate by a factor of $1.363 \pm 0.004$ for a fixed $g^{(2)}(0)$. Additionally, we use the detector to directly measure the photon-number distribution of a thermal mode and calculate the unheralded $g^{(2)}(0)$. We show the possibility to perform $g^{(2)}(0)$ measurements with only one PNR detector, with the results in agreement with those obtained by more common-place techniques which use multiple threshold detectors. Our work shows that efficient PNR SNSPDs can significantly improve the performance of HSPSs and can precisely characterize them, making these detectors a useful tool for a wide range of optical quantum information protocols.
Fast Single Photon Detectors and real-time Key Distillation: Enabling High Secret Key Rate QKD Systems

Quantum Key Distribution has made continuous progress over the last 20 years and is now commercially available. However, the secret key rates (SKR) are still limited to a few Mbps. Here, we present a custom multipixel superconducting nanowire single-photon detectors and fast acquisition and real-time key distillation electronics, removing two roadblocks and allowing an increase of the SKR of more than an order of magnitude. In combination with a simple 2.5 GHz clocked time-bin quantum key distribution system, we can generate secret keys at a rate of 64 Mbps over a distance of 10.0 km and at a rate of 3.0 Mbps over a distance of 102.4 km with real-time key distillation.
The Effect of Using Podcasts and Vodcasts on Developing Ninth Graders’ Speaking Skills of the English Language

The study aimed to determine the effect of applying Podcasts and Vodcasts on developing speaking skills for Ninth-graders in King Abdullah II Schools for Excellence. The study used the quasi-experimental approach by dividing the study sample into three groups, which include the group of Podcasts (23) students, the group of Vodcasts (27) students, and the control group (25) students. An oral test scale for students' speaking skills was prepared, and its validity and reliability were verified by applying it to a pilot sample of (25) individuals from outside the main study sample. The results indicated that the use of Podcasts leads to statistically significant differences in the level of the Ninth-grade students' acquisition of speaking skills in the English language compared to their peers in the control group, which was taught in the conventional method. In the same context, the results indicated that using Vodcasts leads to statistically significant differences in the level of Ninth-grade students’ acquisition of speaking skills in the English language compared to their peers in the control group, which was taught in the conventional method. In addition, the results concluded that Vodcasts have a more significant positive effect on developing students' speaking skills when compared to Podcasts. Finally, several recommendations were suggested as the necessity of activating the use of podcasts and vodcasts in teaching speaking skills, as well as the need to re-review current English language curricula to include classroom activities consistent with the requirements of applying podcasts and vodcasts in teaching the English language.
Domain Adaptation-Based Deep Learning Models for Forecasting and Diagnosis of Glaucoma Disease

&lt;p&gt;Domain adaptation methods are designed to extract shared domain-invariant features by projecting data on a common subspace in order to align their domain distributions. However, these methods do not usually consider domain-specific features, and therefore their distributions may not be well aligned. To address this problem, we introduce a novel model that learns domain-invariant and domain-specific representations to extract both their general and specific features. We also propose progressive weighting to accurately transfer the source domain knowledge and to mitigate negative knowledge transfer from the source to the target domain and to employ low-rank coding for aligning the source and target distributions. We evaluated the model based on several real-world datasets and showed that our method significantly improved the accuracy for forecasting and diagnosis of glaucoma disease from fundus photographs.&lt;/p&gt;
Fraud Triangle Theory on Accounting Students Online Academic Cheating

Academic cheating is a phenomenon found in the academic area. Cheating, copying answers, plagiarism are some forms of academic cheating. Online learning that has been carried out during the pandemic is also not free from the phenomenon of cheating. This study aims to see the effect of the Fraud triangle theory dimension on online academic cheating behavior in accounting students.&#x0D; The data of this study were obtained from questionnaire data distributed to accounting students at UIN Raden Mas Said Surakarta. The respondents of this study amounted to 203 people. The analysis technique is carried out using multiple linear analysis&#x0D; The results of this study indicate that there are two dimensions of the fraud triangle that can increase online academic cheating behavior in students, namely opportunity and pressure. This research is expected to help the education system in universities to understand how severe the problem of online cheating is among students, but they can also help universities in identifying the underlying motives behind cheating behavior.
Open Translation Models, Tools and Services

Abstract The ambition of the Open Translation Models, Tools and Services (OPUSMT) project is to develop state-of-the art neural machine translation (NMT) models that can freely be distributed and applied in research as well as professional applications. The goal is to pre-train translation models on a large scale on openly available parallel data and to create a catalogue of such resources for streamlined integration and deployment. For the latter we also implement and improve web services and computer-assisted translation (CAT) tools that can be used in on-line interfaces and professional workflows. Furthermore, we want to enable the re-use of models to avoid repeating costly training procedures from scratch and with this contribute to a reduction of the carbon footprint in MT research and development. The ELG pilot project focused on European minority languages and improved translation quality in low resource settings and the integration of MT services in the ELG infrastructure.
Broad effects of shallow understanding: Explaining an unrelated phenomenon exposes the illusion of explanatory depth

People often overestimate their understanding of how things work. For instance, people believe they can explain even ordinary phenomena such as the operation of zippers and speedometers in greater depth than they really can. This is called the illusion of explanatory depth. Fortunately, a person can expose the illusion by attempting to generate a causal explanation for how the phenomenon operates (e.g., how a zipper works). Researchers have assumed for two decades that explanation exposes the illusion because explanation makes salient the gaps in a person’s knowledge of that phenomenon. However, recent evidence suggests that people might be able to expose the illusion by instead explaining a different phenomenon. If true, this would challenge our fundamental understanding of how the illusion works. Across three preregistered studies we tested whether the process of explaining one phenomenon (e.g., how a zipper works) would lead someone to report knowing less about a completely different phenomenon (e.g., how snow forms). In each study we found that explaining led people to report knowing less about various phenomena, regardless of what was explained. For example, people reported knowing less about how snow forms after attempting to explain how a zipper works. We discuss alternative accounts of the illusion of explanatory depth that might better fit our results. We also consider the utility of explanation as an indirect, non-confrontational debiasing method in which a person generalizes a feeling of ignorance about one phenomenon to their knowledge base more generally.
The Application of Remote Sensing Techniques and Spectral Analyzes to Assess the Content of Heavy Metals in Soil – A Case Study of Barania Góra Reserve, Poland

The understanding of the spatial and temporal dynamics of farmland processes is essential to ensure the proper crop monitoring and early decision making needed to support efficient resource management in agriculture. By creating appropriate crop management strategies, one can increase harvest efficiency while reducing costs, waste, chemical spraying, and inhibiting the impact of biotic and abiotic factors on crop stress. Only reliable spatial information makes it possible to comprehend the influence of various factors on the environment. The main objective of the research presented in the paper was to assess the possibility of using maps of vegetation and soil indices, such as NDVI, SAVI, IRECI, CIred-edge, PSRI and HMSSI, calculated on the basis of images from the Sentinel-2 satellite, to qualitatively determine the increased amount of heavy metals in the soil in the areas of small agricultural plots around the Barania Góra nature reserve in Poland.The conducted pilot project shows that the spectral indices: NDVI, SAVI, IRECI, CIred-edge, PSRI, and HMSSI, calculated on the basis of images from Sentinel-2, have the potential to assess the content of nickel zinc, chromium and cobalt in the soil on agricultural plots. However, the confirmation of the obtained results requires continuation of the research.
E-Book with Problem Based Learning to Improve Student Critical Thinking in Science Learning at Elementary School

With the development of technology, especially in the world of education, teachers must have learning media that attracts students' attention, one of which is E-Books. This study aims to determine whether Problem Based Learning-Based E-Books Can Improve Students' Critical Thinking Ability in Primary School Science Learning. This research was conducted on elementary school students in the district of Jagakarsa, South Jakarta. This research method uses the RnD method. In this research. To get the results, the researchers used a pre-test and also a post-test to get the results. The results show that this E-Book is able to improve critical thinking skills in science learning as digital media innovation, narration, video and also practice questions.
Pengaruh Platform Wordwall Berbasis Website dalam Meningkatkan Minat Belajar Peserta Didik pada Mata Pelajaran PAI

This study aims to determine the effect of a website-based wordwall platform on students' interest in learning. The type of this research is quantitative with a pre-experimental method of design one shoot case study. The subjects of this study were students of class X TJKT SMK Negeri 2 Padang. The data collection instrument used was a questionnaire with additional supporting data such as observations, interviews and documentation. The results showed that 1) from the results of hypothesis testing using the t test, it was stated that t table &gt; t arithmetic, namely 5.666 &gt; 2.03951, with a significance value of 0.000 which means &lt;0.05 this means that H1 is accepted and H0 is rejected. 2) based on the results of the f test, the results of f table &gt; f count are 32.106 &gt; 4.16, which means that the wordwall platform variable (x) has an influence on increasing the learning interest variable (y). 3) from the simple linear regression test the equation Y = 17,830 - 1,225X
Digital Inclusion Strategies of a Learning Community in Times of Covid-19

Schools are formal educational spaces susceptible to promoting both inclusion and socio-educational exclusion strategies. In this contribution, part of a broader project, we intend to recognize and understand the socio-pedagogical strategies consistent with the principles of the culture of peace that are promoted in a school constituted as a Learning Community, in a context of cultural diversity and social vulnerability. For this we follow a qualitative methodology, of a phenomenological-ethnographic nature, with a case study approach. The interest groups of the school community actively participated as informants through interviews, questionnaires and focus groups which, together with participant observation, were the data collection techniques used. The results show an estimable knowledge about inclusive education, equality and culture of peace by students and teachers. It highlights their involvement in promoting cooperative spaces for a dialogue approach to conflicts stands out, as well as its efforts to maintain a high level of participation in activities despite pandemic restrictions, analyzing the impact of the digital divide in classrooms and adopting measures in this regard.
TEACHERS’ DIGITAL COMPETENCE: BIBLIOMETRIC ANALYSIS OF THE PUBLICATIONS OF THE WEB OF SCIENCE SCIENTOMETRIC DATABASE

With the Online Emergency Remote Teaching (OERT) practices emerged during the outbreak of the pandemic, teachers’ digital competence (TDC) has gained growing attention in educational ICT research realm. In view of this context, the present review study aimed at illuminating the current state of TDCs literature by identifying the volume, growth trajectory, geographical distribution of TDC research. It also aimed at mapping highly influential TDC scholars, documents, and journals. Retrieved from the educational research category in the Clarivate Analytics Web of Science (WoS) core collection database, the metadata of 406 articles were analyzed by employing bibliometric performance and science mapping techniques in VOSwiever 1.6. The timeframe for the study was the last two decades (from 2002 to 2021). Findings illustrated that there has been a growing increase in the number of studies focusing on TDCs. This increase is more evident in the Covid-19 pandemic period, particularly in the last two years. More specifically, more than half of all studies were published in the years 2020 and 2021. Findings also illustrated that there is a dominance of Spanish scholars and organizations in TDC research since 2 out of every 3 studies were carried out by researchers affiliated to Spanish Universities. Additionally, co-citation analysis purported the intellectual structure of TDC knowledge base by identifying the most influential authors and documents. Finally, co-occurrence analysis revealed the concept analysis topical foci of TDC research. These topics are concentrated on “teachers’ digital competence”, “higher education studies”, teacher training programs”, and “ICT in education”. As a result, based on the findings of the study some recommendations were proposed that will contribute into the ICT research community by reflecting the intellectual structure of existing TDC research, thus highlighting the future research direction.
Efficiency and Precision Trade-offs in UAV Tracking with Filter Pruning and Dynamic Channel Weighting

Due to the limitations of computing resources, battery capacity, and maximum load of unmanned aerial vehicle (UAV), efficiency is a critical issue in UAV tracking. Deep learning (DL)-based trackers are known for their high precision but hardly achieve real-time tracking on a single CPU. The traditional framework of discriminative correlation filters (DCF) is famous for its high efficiency but its precision is barely satisfactory. Despite the inferior precision, DCF-based trackers rather than DL-based ones are widely adopted in UAV tracking to trade precision for efficiency. This paper aims to trade off efficiency and precision for UAV tracking using model compression techniques (i.e., filter pruning), which has not been well explored before. To combat the possible precision drop caused by pruning, we propose a dynamic channel weighting strategy to improve the rank-based pruning method which uses the average rank of each filter response as the pruning criterion. The dynamic channel weighting seeks to adjust the contribution to the loss of each channel through optimization. As a result, we achieved better precisions when compressing the original model SiamFC++ with a global pruning ratio instead of tedious layer-wise ones. Extensive experiments on four UAV benchmarks, i.e., UAV123@10fps, DTB70, UAVDT, and Vistrone2018, show that the proposed tracker demonstrates a remarkable balance between precision and efficiency.
Program Pengabdian Masyarakat: Workshop Penulisan Artikel Ilmiah

Writing scientific papers is still considered a difficult task for some lecturers, even though according to Law Number 14 of 2005 it is one of the obligations of a lecturer. For this reason, the Media and Cultural Literacy Expertise Group conducts scientific article writing workshops to help lecturers express their ideas and research results systematically according to the rules that apply in the publication of scientific papers. This activity was carried out online and offline by involving approximately 30 lecturers of the Al Islam Polytechnic Bandung. This workshop was conducted using various methods: lectures, discussions, and consultations (coaching clinic). The materials include the introduction of scientific papers, techniques for writing scientific articles, strategies to avoid plagiarism and the practice of using digital reference management programs. Evaluation of this activity was carried out using pretest-posttest and filling out a questionnaire. The results of the evaluation showed that most (96.1%) participants considered the material presented according to their needs and all participants (100%) found it very useful and motivated to write scientific articles.&#x0D; &#x0D; Keywords: scientific articles, writing techniques, hybrid workshop
Generalized Space-Time Autoregressive Modeling of the Vertical Distribution of Copper and Gold Grades with a Porphyry-Deposit Case Study

We examined the first-order application of the generalized space-time autoregressive GSTAR (1;1) model. The autoregressive model was used and was performed simultaneously in multiple drill-hole locations. The GSTAR model was applied to data with absolute time parameter units, such as hours, days, months, or years. Here a new perspective on modeling space-time data is raised. We used the relative time parameter index as a discretization of the same drilling depth of mineralization through a porphyritic deposit. Random variables were the copper and gold grades derived from the hydrothermal fluid that passed through the rock fractures in a porphyry copper deposit in Indonesia. This research aims to model the vertical distribution of copper and gold grades through backcasting the GSTAR (1;1) model. Such results could help geologists to predict copper and gold grades in deeper zones in an ore deposit. Two spatial weight matrices were used in the GSTAR (1;1) model, and these were based on a Euclidean distance and kernel function. Both weight matrices were constructed from different perspectives. The Euclidean distance approach gave a fixed weight matrix. Meanwhile, the kernel function approach gave the possibility to be random since it is based on real observations. It is obtained that the estimated (in-sample) and predicted (out-sample) kernel weight approach was accurate. Copper and gold grades data could recommend the GSTAR (1;1) model with a spatial kernel weight for modeling the vertical continuity case.
Koyak Ke?: Humorous Social Media Post On Israel-Palestine Conflict

Previous research has discussed on the usefulness of humour during online interaction.The positive emotion that humour evoke tend to also be related to online sharing behaviour and engagement.However, for more 'serious' and pressing issue, like the case of Israel-Palestine conflict, the use of humour as a response is rather puzzling.Thus, in this study, the researchers aim to uncover 1) What are the 'humorous' target or focal point highlighted using the #IsraelKoyak?2) What are the functions of these 'humorous" posts?All posts and comments with the localized hashtag #IsraelKoyak and indication of amusement on three social media platforms namely Instagram, Twitter, and Facebook were included in this study.The research period was from May to August 2021.To answer the research questions, posts that were considered humorous -which received emojis and comments that depict amusement by netizens were selected and analysed using QSR International's NVivo 12 software.This inductive approach study categorized the findings into five functions of humour, namely, to demean, to instigate, to mobilize, to create awareness and to entertain.The target and focal points as well as the symbolic association were also highlighted in this study and discussed from the lens of benign-violation theory.It is hope that this research would provide a better understanding of using humour on social media and the categories created can be used as referent point by future scholars and relevant stakeholders