Reviewerly/exHarmony huggingface dataset:
Evaluation of DeepGaze-Generated Saliency Maps for Affective Scenes

DeepGaze (Kümmerer et al., 2017) is an AI platform that is trained on and designed to generate saliency maps for natural images that are emotionally neutral. To what extent it can be used to generate saliency maps for natural images varying in emotional content remains not known. We addressed the question (1) by comparing the DeepGaze-generated saliency maps with eye-tracking data from human observers viewing affective scenes from the International Affective Picture System (IAPS) (Fan et al., 2018) and (2) by analyzing the impact of occluding the DeepGaze-generated saliency map on emotion recognition by a recently proposed VisualCortex-Amygdala (VCA) deep learning system for valence analysis. We found that (1) the saliency maps generated by DeepGaze matched the eye-tracking data better than that generated by other methods including the Grad-CAM (Selvaraju et al., 2017) and (2) occluding the saliency map generated by DeepGaze led to significantly more deteriorated valence recognition by the VCA system compared to occluding random patches of voxels. These results suggest that DeepGaze, despite being trained on emotionally neutral images, can generate saliency maps that convey the emotional significance of the images.
Review on Alexa as a Hospital Receptionist

A hospital receptionist is the first point of contact between a hospital or medical facility and patients. These receptionists play an vital role in a medical facility because they perform customer service and administrative-related duties like scheduling appointments, answering patients' questions, answering phone calls and placing calls to confirm patients' appointments. A questionnaire was designed for the expectant patients, to design the Alexa. The inputs were captured to verify the feasibility, relevance, and technology acceptance for the use case. Chatbot designs are slowly changing from voice-to-voice communication like an alexa which was tested on Echo dot, a smart speaker device supported by Amazon Voice Service (AVS). Designing a chatbot on top of a custom Alexa skill allows developers to use multiple Amazon Web Services. The design has used AWS for hosting voice server and Azure for hosting Back-end which is created in c#. After that we connect Echo device with our created system. The concept of connecting smart devices, makes the chatbot solution accessible at any time and from anywhere.
Learning Expected Emphatic Traces for Deep RL

Off-policy sampling and experience replay are key for improving sample efficiency and scaling model-free temporal difference learning methods. When combined with function approximation, such as neural networks, this combination is known as the deadly triad and is potentially unstable. Recently, it has been shown that stability and good performance at scale can be achieved by combining emphatic weightings and multi-step updates. This approach, however, is generally limited to sampling complete trajectories in order, to compute the required emphatic weighting. In this paper we investigate how to combine emphatic weightings with non-sequential, off-line data sampled from a replay buffer. We develop a multi-step emphatic weighting that can be combined with replay, and a time-reversed $n$-step TD learning algorithm to learn the required emphatic weighting. We show that these state weightings reduce variance compared with prior approaches, while providing convergence guarantees. We tested the approach at scale on Atari 2600 video games, and observed that the new X-ETD($n$) agent improved over baseline agents, highlighting both the scalability and broad applicability of our approach.
AdaLoss: A computationally-efficient and provably convergent adaptive gradient method

We propose a computationally-friendly adaptive learning rate schedule, "AdaLoss", which directly uses the information of the loss function to adjust the stepsize in gradient descent methods. We prove that this schedule enjoys linear convergence in linear regression. Moreover, we provide a linear convergence guarantee over the non-convex regime, in the context of two-layer over-parameterized neural networks. If the width of the first-hidden layer in the two-layer networks is sufficiently large (polynomially), then AdaLoss converges robustly \emph{to the global minimum} in polynomial time. We numerically verify the theoretical results and extend the scope of the numerical experiments by considering applications in LSTM models for text clarification and policy gradients for control problems.
OVIS: Open-Vocabulary Visual Instance Search via Visual-Semantic Aligned Representation Learning

We introduce the task of open-vocabulary visual instance search (OVIS). Given an arbitrary textual search query, Open-vocabulary Visual Instance Search (OVIS) aims to return a ranked list of visual instances, i.e., image patches, that satisfies the search intent from an image database. The term "open vocabulary" means that there are neither restrictions to the visual instance to be searched nor restrictions to the word that can be used to compose the textual search query. We propose to address such a search challenge via visual-semantic aligned representation learning (ViSA). ViSA leverages massive image-caption pairs as weak image-level (not instance-level) supervision to learn a rich cross-modal semantic space where the representations of visual instances (not images) and those of textual queries are aligned, thus allowing us to measure the similarities between any visual instance and an arbitrary textual query. To evaluate the performance of ViSA, we build two datasets named OVIS40 and OVIS1600 and also introduce a pipeline for error analysis. Through extensive experiments on the two datasets, we demonstrate ViSA's ability to search for visual instances in images not available during training given a wide range of textual queries including those composed of uncommon words. Experimental results show that ViSA achieves an mAP@50 of 21.9% on OVIS40 under the most challenging setting and achieves an mAP@6 of 14.9% on OVIS1600 dataset.
An Analysis of Hate Speech on Students Interaction and The Impact on Student Motivation

The aims of this research are to investigate the types of hate speech on students interaction such as incitement to hatred, expression of insulting and ridicule or slander of person. Then, to investigate the impact of hate speech on students motivation such as it can make the students less of self-confidence, overthinking, become anti-social and isolate them self from their friends and the worst impact is the student become lazy to go to school and feel depressed. This research uses descriptive qualitative method. The technique of data collecting are take the video, interview and questionnaire. There are three videos which are uses as source of data about types of hate speech, those videos show on the students interaction. Interview with two students and an English lecturer which are uses as source of data about the impact of hate speech on students motivation that consist of 16 questions. Questionnaire which are uses as source of data about the impact of hate speech on students motivation that consist of 10 questions. In collecting the data, the researcher transcribe the videos into written data accurately, and classify the data based on data from utterances of the students then put them into appropriate categories. In order the data can be easy to be identify and to be analyze. After all of the data are collected, the researcherl analysis the data and draw the conclusion. The result of this research can be seen as follows there are the impact of hate speech on students motivation, it can make the students less of self-confidence, overthinking, become anti-social and isolate them self from their friends and the worst impact is the student become lazy to go to school and feel depressed.
Transgender reporting in the British press: editorial standards and discursive harms in the post-Leveson era

This article looks at transgender media representations from the aspect of press regulation which is so far under-researched. Placing the analysis within the fragmented post-Leveson UK press landscape, it examines the two UK press watchdogs’ provisions relating to transgender reporting. The study evaluates IPSO’s and IMPRESS’ editorial standards through the lens of queer legal theory, offering a fresh perspective on the key role of these bodies in establishing (trans)gender ‘outsiders’ and ‘insiders’ in the ongoing trans rights debate of which the press forms a key part. It is argued that, although both regulators have taken steps to tackle trans-discriminatory reporting, IMPRESS’ approach seems to strike a more constructive balance between freedom of expression and trans people’s rights than IPSO. The paper concludes by making recommendations for both press regulators to address the complexities of trans issues and tackle the discursive harm of transgender media ‘othering’ more effectively.
Forecasting Monthly Housing Sales to Foreigners with Type 1 Fuzzy Regression Functions Approach Based on Ridge Regression

Artificial neural networks, fuzzy inference systems, and hybrid methods where these methods are used together have been frequently used in forecasting problems. Although fuzzy inference systems produce very effective results in forecasting problems, the fact that many classical fuzzy inference systems depend on the rule base makes it difficult to implement these methods. The type 1 fuzzy regression functions approach, which is not dependent on the rule base and has a simpler structure than many fuzzy inference systems, is frequently used in forecasting problems. Although the Type 1 fuzzy regression functions approach has superior forecasting performance, it is known that the method has a multicollinearity problem in the application process of this method. The type 1 fuzzy regression functions approach based on ridge regression both eliminates the multicollinearity problem of the Type 1 fuzzy regression functions approach and produce better forecasting results than the Type 1 fuzzy regression functions approach. In this study, the forecasting of monthly house sales to foreigners is carried out for the first time with the Type 1 fuzzy regression functions approach based on ridge regression, and the results of the analysis are compared with many methods suggested in the literature. As a result of the analysis, it is concluded that the forecasting results obtained with the Type 1 fuzzy regression functions approach based on ridge regression produce better results than some other methods in the literature.
Tools and Computational Machinery for Movement

This paper is a discussion of computational tools and circuits that deal with the internal and external worlds of the human body. The information processing avenues in the central nervous system (CNS) are an important part of the development.&#x0D; &#x0D; All sensory channels and the vision system are involved. It clarifies the role of the sensory system in internal coordinate systems and for all activities of the CNS. It includes the inherent redundancy aspects of the motor system as well. The visual system is involved in sports such as soccer and basketball and for being aware of and paying attention to both the internal world and the external reality surrounding the athlete.
Distribution pattern and spatial analysis of factors for tuberculosis (TB) cases in Bandar Lampung City in 2022

Background: Indonesia will be free of TB (Tuberculosis) in 2050, and elimination will begin in 2030. TB cases are still high in Bandar Lampung City, so efforts are needed to solve the problem. Mapping of TB cases using a Geographic Information Spatial (GIS) approach was performed in this study to evaluate the spreading patterns of TB patients so that policies can be taken to deal with TB cases in an epidemiological manner. Methods: The research was conducted in 31 public health centers in Bandar Lampung City. The number of TB patients in this study was 879 people. Making maps for visualizing the spread of TB patients using Archgis software, data were analyzed with Geoda and Moran's Index to see the spatial relationship between variables. Results: The spatial analysis using Geoda found a spatial relationship between TB patients and population density (p=0.00079) and the distance between the TB patient's house and the health center (p=0.00000). However, there was a significant relationship between the underprivileged group (p=0.21682) and topography (p= 0.29139). The Z score for the 4 variables is quite large and &gt;Z0.95, so the distribution pattern of TB patients is stated to be clustered (cluster). Conclusion: Based on the TB patients mapping and the spatial analysis, it is known that the distribution pattern of TB patients in Bandar Lampung City forms a clusters pattern, and there is an autocorrelation relationship between population density, underprivileged groups, height and distance from the TB patient's house to the health center.
Automatic Realization of Light Processing Functions for Programmable Photonics

We propose an automatic technique to implement light processing on a square-mesh programmable photonic circuit. Our method does not require human design knowledge, and can be applied to realize configurations for different light processing functions (e.g., splitting and filtering) at time scales of minutes.
Penerapan Rantai Markov Dalam Peramalan Cuaca (Studi Kasus: Cuaca Harian di Kota Padang)

Information about the weather is needed. Weather is one of the considerations of the community in carrying out various activities. The purpose of this study is to provide information related to weather forecasts by applying Markov chain theory. The Markov chain is a random process in which all information about the future is contained in the present state. The study uses daily weather data that occurs on June 1, 2022 to June 30, 2022 to predict the weather for the next 7 days. The data used is secondary data taken from the website of the Meteorology, Climatology, and Geophysics Agency (BMKG) of Padang City. Based on the results of calculations using Markov chains, a transition matrix is obtained that is used to predict the weather for the next day.
Policy Implementation in Preventing Plagiarism in Students in the Digital Age

The act of plagiarism or copying other people's work via the internet is a phenomenon that has been around for a while among students; in making scientific work assignments, not a few students plagiarism or copy-paste from the internet so that the task is immediately resolved. The purpose of this research was to find out how the State Islamic University Sunan Gunung Djati Bandung's efforts to prevent and deal with plagiarism in the midst of the digitalization era. Therefore, another objective of this research is to determine whether the State Islamic University of Sunan Gunung Djati Bandung students are capable and understand digital literacy. So far, the efforts made by the State Islamic University Sunan Gunung Djati have been quite good in preventing plagiarism by making policies on the percentage of plagiarism and also providing sanctions for students who commit plagiarism. However, some students still feel they need help understanding how to avoid plagiarism. In addition, some students have understood digital literacy. However, its application still needs to be improved, such as being often influenced by fake news or hoaxes and students' lack of interest in studying the truth of information on the internet for reference to scientific papers because it is considered to take a long time.
Analysis of the Influence of Pupils&amp;apos; Reading Quantity and Reading Type on Their Exercises

Objective: Analysis of the influence for number/types of books reading after school for primary school students on their grades of writing, which would provide solid evidence on supporting the recommendation the types of the books for primary school students after class.Methods: The dataset of students from classes A and B of a primary school in Yunnan were collected in September 2022, including the formal reading scores in this semester, the reading lists of 88 students from classed and B were collected and analyzed here.Results: The grads for writing of the students from class B was higher than that of students from class A, however, no significant difference was detected (P>0.05), and the reading volume of students from class B was higher than that of students from class A, and the significantly difference was detected between two class (P<0.05).The results of regression analysis suggested that reading type was the most important factor affecting the grade level of writing for primary school students, especially the number of reading books belonging to literary might have important impact on their witting.Conclusion: The number of reading book belong to literature, which might affect the writing grade of primary school students, thus, primary students should cultivate good reading interest and reading habits, especially the literary books, which would help to improve the writing grade level of primary school students.
Research on the Construction of STEAM Curriculum Mode Based on Project Based Learning

Project based learning is a kind of project oriented learning method，which is used to learn and explore in real situations.STEAM education is a new educational model with the characteristics of interdisciplinary, interdisciplinary, situational, integrated, scientific rationality and humanistic quality.The current development of both of them has encountered some practical obstacles, but both of them have a positive significance for the development of education reform, and they have something in common in their educational concepts and training objectives.In many educational practices, there are also many cases of project-based teaching combined with STEAM education elements.Therefore, on the basis of in-depth understanding of project-based learning and STEAM education, this paper clarifies the characteristics and significance of the research on the construction of STEAM curriculum model based on project-based learning.Based on the broad curriculum level, this paper conceives and discusses the STEAM curriculum model based on project-based learning from the establishment of curriculum objectives, the selection of curriculum themes, the construction of curriculum structure and the development of curriculum evaluation, It is expected to provide a theoretical and practical reference for the research and development of project-based learning and STEAM education.
Improved Support Vector Machine Personal Credit Rating Model

Credit consumption has become the choice of more and more people.While the expansion of credit consumption brings convenience, the consequent problem of discredit brings incalculable loss to trust institutions, such as intentional arrears, malicious overdraft consumption, etc. to the trust in the operation of the huge losses caused.On the one hand, our country is unable to establish perfect personal credit record, customer credit information is difficult to share, access to relevant data is limited, personal credit system is not perfect, therefore, it is necessary to establish a perfect and automatic personal credit evaluation system, identify the personal credit risk scientifically, and realize the maximization of bank credit income.In the bank risk management, the main problem is how to measure and avoid the bank's financial risk, and personal credit assessment is the most difficult and important part.In this paper, we use the XGBOOST algorithm to sort the importance of features, and select the number of features and the specific features according to the relationship between the model accuracy and the number of features, then 80% of the data was taken into the traditional Support vector machine model as a training set and tested with the remaining data with low accuracy, so that, in terms of individual credit risk assessment, this paper introduces the quadric surface into the traditional Support vector machine and builds the kernel-free quadric surface Support vector machine model, which improves the accuracy
IMPLEMENTASI MEDIA SMART POP UP BOOK UNTUK MENINGKATKAN LITERASI BACA-TULIS PADA ANAK

Every school must participate in literacy activities, which are required. Through the efforts of the national literacy movement, the government has made this announcement. Literacy activities can be implemented more effectively with the help of interactive learning media. At the moment, children tend to prefer modern media or games like smartphones and tablets. In fact, children's development can be negatively impacted by these various media if they are not closely monitored. As a result, research was conducted on the use of smart pop-up book media in education to familiarize young children with literacy. The reason for this study was to decide the execution of brilliant spring up book media in learning education in youth. Children between the ages of 5 and 6 participated in this study at TK Pertiwi Wonorejo 02 Kec. Talun of the Blitar Empire. A descriptive qualitative research design is used in this study. Based on aspects of children's language literacy development, this study found that smart pop-up book media can help students improve their reading and writing literacy. As a result, it can be concluded that children can improve their reading and writing literacy skills by utilizing smart pop-up book media in early childhood education.
Virtual reality technology in physician education: focus on emergency medical care

Virtual reality technology has been developing rapidly over the past two decades and is becoming available in various areas of healthcare — in surgery, neurology, rehabilitation, and education. The need for virtual reality technology is also manifested in the development of algorithms for emergency medical care by primary care physicians. Currently, 6 interactive case problems have been developed for the most common emergency conditions, requiring, among other things, resuscitation. The concept of teaching using virtual reality technology has become the basis for the development of an additional professional advanced training program for general practitioners "Development of an algorithm for providing emergency medical care for sudden acute diseases and conditions". A unique feature of the program is the ability to practice the emergency medical care algorithm using virtual reality technology, as well as practice skills using a simulation manikin and an automatic external defibrillator.
The Sequential Schematic Scene-building Theory in Dan Brown’s The Da Vinci Code: A Cognitive Semantic Study

Everything in the universe is movable or being moved, starting from galaxies and planets to the smallest object, such as the atom. But how can we conceptualize the motion of such entities and what are the basic elements of sequential scene? To do that, a theory of the sequential schematic scene-building has developed to treat this issue. This theory deals with the basic dynamic, on-line, or real-time perceptual processes by which we build a scene. The study focuses on the schematic, not conceptual, elements of sequential scenes which deal with the highly abstracted, primitive system. Such system is considered as the skeleton or building blocks of any sequential scene. To make the theory more applicable, the study selects a scene from Dan Brown’s The Da Vinci Code to be analyzed in terms of the theory developed. The study arrived at a conclusion that the moveable scene can include a group of sequential schematic structures, such as the mover, motion, causality, geometrical structures, and containment. All these elements work together sequentially in the sense that they are inherently consolidated.