Reviewerly/exHarmony huggingface dataset:
Cross Time-Frequency Transformer for Temporal Action Localization

Most modern approaches in temporal action localization (TAL) mainly focus on time domain information, while neglecting the advantages of information from other domains. How to effectively utilize information from different domains and their interactions in a reasonable manner has been an attractive yet challenging issue in TAL. In this paper, we propose a novel cross time-frequency Transformer model (TFFormer) for TAL. A dual-branch network architecture is designed to capture the time and frequency features at multiple scales, using the multi-scale transformer in the time branch and the DB1 Discrete Wavelet Transform (DWT) in the frequency branch. To fuse these features from different domains, we propose a cross time-frequency attention mechanism that includes a time pathway and a frequency pathway, enhancing the interaction between the temporal and frequency features. Furthermore, a gated control mechanism is designed to aggregate features from different scales, characterizing the respective contributions of features at different scales. We also design a new regression loss function for locating the time boundaries. Extensive experiments were carried out on four challenging benchmark datasets, including two third-person datasets and two first-person datasets. The proposed method achieves impressive results on these datasets. Specifically, TFFormer achieves an average mAP of 23.2% on Ego4D and 25.6% on EPIC-Kitchens 100, which outperform previous state-of-the-arts by a large margin. It also obtains competitive results on ActivityNet v1.3 and THUMOS14, with an average mAP of 36.2% and 67.8%. We also conducted extensive ablation studies to validate the effectiveness of each component in the proposed method.
Reclaiming the Horizon: Novel Visualization Designs for Time-Series Data with Large Value Ranges

We introduce two novel visualization designs to support practitioners in performing identification and discrimination tasks on large value ranges (i.e., several orders of magnitude) in time-series data: (1) The order of magnitude horizon graph, which extends the classic horizon graph; and (2) the order of magnitude line chart, which adapts the log-line chart. These new visualization designs visualize large value ranges by explicitly splitting the mantissa <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</i> and exponent <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">e</i> of a value <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">v = m 10<sup>e</sup></i> We evaluate our novel designs against the most relevant state-of-the-art visualizations in an empirical user study. It focuses on four main tasks commonly employed in the analysis of time-series and large value ranges visualization: identification, discrimination, estimation, and trend detection. For each task we analyze error, confidence, and response time. The new order of magnitude horizon graph performs better or equal to all other designs in identification, discrimination, and estimation tasks. Only for trend detection tasks, the more traditional horizon graphs reported better performance. Our results are domain-independent, only requiring time-series data with large value ranges.
Data Formulator: AI-powered Concept-driven Visualization Authoring

With most modern visualization tools, authors need to transform their data into tidy formats to create visualizations they want. Because this requires experience with programming or separate data processing tools, data transformation remains a barrier in visualization authoring. To address this challenge, we present a new visualization paradigm, concept binding, that separates high-level visualization intents and low-level data transformation steps, leveraging an AI agent. We realize this paradigm in Data Formulator, an interactive visualization authoring tool. With Data Formulator, authors first define data concepts they plan to visualize using natural languages or examples, and then bind them to visual channels. Data Formulator then dispatches its AI-agent to automatically transform the input data to surface these concepts and generate desired visualizations. When presenting the results (transformed table and output visualizations) from the AI agent, Data Formulator provides feedback to help authors inspect and understand them. A user study with 10 participants shows that participants could learn and use Data Formulator to create visualizations that involve challenging data transformations, and presents interesting future research directions.
The effects of mobile-assisted concept mapping on EFL learners’ writing fluency and motivation

Writing and its role in English as a foreign language (EFL) context has been one of the primary areas of focus for many years. The present study examined the effects of mobile-based concept mapping on EFL learners’ writing fluency and motivation. To fulfill the objective, 70 upper-intermediate level Persian EFL learners were assigned into one experimental and one control conditions, each including 35 participants. The experimental condition’s participants received instruction through mobile-based concept mapping while the students of the control condition did not receive any instruction and were just required to discuss the topics and write about them traditionally. The findings of the study revealed that mobile-mediated concept mapping was effective for EFL students’ writing fluency. Moreover, the results indicated that mobile-based concept mapping was beneficial for learners’ writing motivation.
Waste Operational Budget Before And After The Pandemic At The Kramatwatu Sub-District Office

&#x0D; &#x0D; &#x0D; &#x0D; Purpose - The formulation of the problem in this study is whether the operational budget for waste before the pandemic is bigger than after the pandemic and vice versa at the kramatwatu sub-district office. The purpose of this study was to find out whether the operational budget for waste before the pandemic was bigger than after the pandemic and vice versa at the kramatwatu sub-district office.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; Design/methodology/approach - This research uses a writing method using a descriptive method according to sugiono, a method used to make broader conclusions. Using the descriptive method focusses on the problems that exist should be actual problems. Data collection is done by interview process, direct observation, and documentation.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; Finding - The results of this study indicate that after the covid19 outbreak, the revenue from the waste operational budget has increased at the kramatwatu sub-district office.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; Originality -&#x0D; &#x0D; &#x0D; &#x0D;
PERANCANGAN USER INTERFACE PADA WEBSITE STREAMING ANIME MENGGUNAKAN APLIKASI FIGMA

Videos and Japanese cartoons called anime are getting more and more fans. With the development of computer technology, internet, to be able to watch movies and videos, it is enough to look at streaming websites. To create an attractive anime streaming website that provides various kinds of anime videos and films, a user interface design is needed so that website development is easier and can provide user convenience. Good user interface design must be user oriented. This study discusses the design of the user interface on anime streaming websites using the Figma application. The research method used is the prototype method, namely the stage of making the user interface design through a wireframe and then proceed with making a prototype. The finished user interface design will be used as a reference for creating an anime streaming website which will be used as the final product as the output of this research. Based on the test results using the Present facility in the Figma application and trials using a browser on a notebook device, the user interface design of the anime streaming website can run smoothly and the display of all web pages and menu buttons works well.&#x0D; &#x0D; Keywords: Figma, prototype, user interface, website, wireframe
RANCANG BANGUN SISTEM INFORMASI PENDATAAN DAN MONITORING TUMBUH KEMBANG ANAK SEBAGAI UPAYA PENCEGAHAN STUNTING DESA KOTAPARI

Stunting is one of the problems being faced by Kotapari Village. The absence of an information system about stunting that is easily accessible to the public is one of the aspects that has slowed down the resolution of the stunting problem. To accelerate the resolution of the stunting problem, it is considered necessary to have an information system that can help the community easily and quickly. Methods of data collection is done by interviews and observation. In this study the system development method used is waterfall with the supporting software used are PHP and MySQL. Seeing the reality above, it is deemed necessary to build a website-based information system that is useful to facilitate Kotapari Village and the Community in working to resolve the stunting problem in Serdang Bedagai Regency. Apart from being able to provide stunting information to the community, this application also has a child health check menu related to child growth and a discussion menu that can be used by the community to communicate with Kotapari Village.
ANALISIS KUALITAS WEB ZENIUS MENGGUNAKAN SYSTEM USABILITY SCALE (SUS)

During the Covid-19 pandemic, many students found it difficult to carry out their studies, so many companies provided online learning services to make it easier for students to learn. One of them is PT Zenius Education which provides online learning services, PT Zenius Education is a technology-based education company from Indonesia. Zenius provides education access services in Indonesian language video formats which are presented online through the website (zenius.com) and mobile phone applications. On the Zenius web there are many features and tutors that can make learning easier. The usability of the website according to Nielsen, namely learnbility, efficiency, memorability, errors, and satisfactions, the usability contained on the Zenius website is able to attract users because it is easy to use the Zenius website. This journal will discuss the analysis of the quality and usability of the Zenius website based on the views of various people who have used the Zenius website, so that it can make it easier for companies to improve the website so that Zenius website users are satisfied.
MENGGUNAKAN TEKNOLOGI BLOCKCHAIN UNTUK MEMASTIKAN KEAMANAN

The use of Blockchain in the Internet of Things networks is an innovative approach that can make communication between devices of such a network distributed, autonomous and secure. The blockchain in this context is a set of cryptographically connected blocks. Transactions in the network act as the main carriers of information about the state of the nodes, as well as the output information of the nodes themselves for the autonomous functioning of the network. A node is a "smart" device, a sensor, or a microcontroller that connects a group of sensors. Blockchain will be used to provide secure data transmission and processing of devices in the Internet of Things network. This article discusses the main opportunities and challenges in the application of technology in distributed networks.
RANCANG BANGUN WEBSITE PENCUCIAN DAN PERAWATAN SEPATU MENGGUNAKAN PHP DAN FRAMEWORK CODEIGNITER

This research aims to design and build a website which contains information about the business of cleaning and caring shoes. This research is motivated by the function of shoes which are currently a primary human need as a foot protection device and also have become part of a lifestyle. Shoes hygiene is important, and dirty shoes are not only unsightly, but also harmful to health. The condition of clean shoes will certainly make them comfortable to wear at all times. Today, there are many businesses that provide shoe cleaning and care services. Many of these businesses still use manual transactions and customers have to come to the place of business themselves to get their shoes cleaned and cared. With the advancement of internet technology, shoes cleaning and care businesses should created a transactions that can be carried out online and customers doesn’t need to come directly to the place of business because the shoes will be taken by the shoe cleaning and caring business to the customer's home. One of the uses of the internet for this shoe clean and care business is to use a website. This research will discuss the design of a shoe cleaning and care website and the website was created using PHP and the codeigniter framework
A study on the legal risk assessment of virtual currency transactions based on statistical analysis

Abstract This paper first analyzes the definition and characteristic attributes of virtual currency transactions, secondly constructs the legal risk indicator evaluation system, then pre-processes the evaluation data and assigns the indicators, and then constructs the legal risk evaluation model using TOPSIS-grey correlation. Finally, the quantitative data analysis was carried out by analyzing the indicator weights and evaluating indicators. The results show that the overall score of the trading platform is 73.86, with the evaluation scores of the first-level indicators being 24.56, 11.35, 16.23, 15.42, and 6.30, respectively. This study fully illustrates that the use of TOPSIS-grey correlation analysis can provide data support and a decision-making basis for legal risk assessment and prevention and new directions for reforming and developing the legal risks of virtual currency trading.
Analysis of personal career development planning of teachers in higher education institutions based on system GMM model

Abstract This paper analyzes the personal career planning of teachers in higher education institutions, the influencing mechanisms, and the influencing factors. A systematic GMM model was constructed by combining differential GMM estimation and horizontal GMM estimation, and the systematic GMM estimation commonly used in dynamic panels was improved and applied using more effective instrumental variables and continuously updated objective functions. The results of the GMM analysis obtained through the selection of the influencing factors showed that the proportion of senior teachers’ willingness to personal career development and planning decreased by -0.04 and 0.02, respectively, and the proportion of negative development to total development willingness increased by +0.02 and +0.01, respectively, and the proportion of positive development to total development willingness increased by +0.03 and +0.01, respectively, and all of them were significant at the 1% level.
Evaluation and Analysis of the Effectiveness of University Innovation and Entrepreneurship Courses Based on Data Analysis Technology

Abstract An innovation and entrepreneurship education model centered around Timmons’ entrepreneurial process is suggested in this study after an initial analysis of applied bachelor universities, innovation and entrepreneurship education, and innovation and entrepreneurship courses. Second, a neural network with BP and an artificial neural network is used to build an assessment system for the efficiency of school innovation and entrepreneurship courses. Finally, examples were used to quantitatively study data on the approval of innovation and entrepreneurship classes and students’ graduation selections. The findings reveal that satisfaction with the innovation and entrepreneurship course may be successfully assessed using data analysis techniques because there is just a variance of 0.037 between the input assessment, with the lowest average score of 4.938 and the multidimensional experience assessment, with the highest average score of 4.975.
Atmospheric dristribution of traffic heavy metals at temu-interchange, Epe Lagos, Nigeria

The Atmospheric distribution of traffic heavy metals is a dynamic process that involves the emission of various pollutants released from vehicular traffic. It has affected both human and plants around Temu-interchange hence, the need to characterized the emissions. The objective of the study was determined concentration of Particulate Matter (PM) and Enrichment Factor (EF) depending on the traffic emission. The research was conducted using deposition method. The study area and the control experiment were conducted simultaneously for a period of thirty (30) days between December 2022-January 2023 (Dry Season). Samples were prepared and deposition fluxes (DF) were determined. The particulates were taken to the Central Research Laboratory, Tanke in Ilorin for characterization using X-ray Fluorescence (XRF) spectrometer. EF was also determined. Thirteen elements Fe, Ag, Cd, Zn, Sn, Ti, In, Co, Mn, Pd, Rh and Ru were characterized from the samples collected at the study area while Twenty-one Si, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ge, As, Zr, Sr, Pb, W, Po and Ac elements were characterized from the samples collected at the control unit of the experiment. The EF of the detected elements both in the study area and in the control, experiment was determined. Five elements in the study area were moderately enriched, while elements such as S, Cl and Zn were highly enriched in the control unit. An indication of anthropogenic activities particularly traffic emission influence within the area hence, a clean-up of the study area is highly recommended.
Metaphors of Intensities and Indices: Using Digital Technologies and Non-Human Actors in Performing Art

This research investigates the role of non-human actors in the context of digital performing arts.It employs an interdisciplinary approach, integrating philosophical, historical, and artistic perspectives to explore the unique potential of non-human actors.Starting with an in-depth analysis of the philosophical concepts laid out by Deleuze, Bergson, and Tyler, the study establishes a theoretical framework.It then investigates the historical and contemporary artistic movements that have begun to challenge the anthropocentric paradigm in performing arts.The practical application of these theoretical and historical perspectives is illustrated through an examination of three case studies: Leňochod má celkom vážny dôvod sa vykakať [Sloth Has a Pretty Good Reason to Poop], Foam, and Heterotopia [Heterotopy].These projects leverage extended reality technologies to offer spectators an immersive glimpse into the lives and experiences of non-human entities.They employ philosophical concepts such as intensity and indices to test their potential for establishing communication between human and non-human entities.The research concludes by emphasizing the transformative potential of incorporating non-human actors in digital performing arts, suggesting that such a practice can redefine traditional theatre boundaries, challenge human-centric worldviews, and foster empathetic connections across species.
Mobility-Aware Multi-Task Migration and Offloading Scheme for Internet of Vehicles

In Internet of vehicles, vehicular edge computing (VEC) as a new paradigm can effectively accomplish various tasks. Due to limited computing resources of the roadside units (RSUs), computing ability of vehicles can be a powerful supplement to computing resources. Then the task to be processed in data center can be offloaded to the vehicles by the RSUs. Due to mobility of the vehicles, the tasks will be migrated among the RSUs. How to effectively offload multiple tasks to the vehicles for processing is a challenging problem. A mobility aware multi-task migration and offloading scheme for Internet of vehicles is presented and analyzed. Considering the coupling between migration and offloading, the joint migration and offloading optimization problem is formulated. The problem is a NP-hard problem and it is very hard to be solved by the conventional methods. To tackle the difficult problem, the idea of alternating optimization and divide and conquer is introduced. The problem can be decoupled into two sub-problems: computing resource allocation problem and vehicle node selection problem. If the vehicle node selection is given, the problem can be solved based on Lagrange function. And if the allocation of computing resource is given, the problem turns into a 0–1 integer programming problem, and the linear relaxation of branch bound algorithm is introduced to solve it. Then the optimization value is obtained through continuous iteration. Simulation results show that the proposed algorithm can effectively improve system performance.
Numerical influence of ReLU'(0) on backpropagation

In theory, the choice of ReLU(0) in [0, 1] for a neural network has a negligible influence both on backpropagation and training. Yet, in the real world, 32 bits default precision combined with the size of deep learning problems makes it a hyperparameter of training methods. We investigate the importance of the value of ReLU'(0) for several precision levels (16, 32, 64 bits), on various networks (fully connected, VGG, ResNet) and datasets (MNIST, CIFAR10, SVHN, ImageNet). We observe considerable variations of backpropagation outputs which occur around half of the time in 32 bits precision. The effect disappears with double precision, while it is systematic at 16 bits. For vanilla SGD training, the choice ReLU'(0) = 0 seems to be the most efficient. For our experiments on ImageNet the gain in test accuracy over ReLU'(0) = 1 was more than 10 points (two runs). We also evidence that reconditioning approaches as batch-norm or ADAM tend to buffer the influence of ReLU'(0)'s value. Overall, the message we convey is that algorithmic differentiation of nonsmooth problems potentially hides parameters that could be tuned advantageously.
Dimensions of Disagreement: Unpacking Divergence and Misalignment in Cognitive Science and Artificial Intelligence

The increasing prevalence of artificial agents creates a correspondingly increasing need to manage disagreements between humans and artificial agents, as well as between artificial agents themselves. Considering this larger space of possible agents exposes an opportunity for furthering our understanding of the nature of disagreement: past studies in psychology have often cast disagreement as two agents forming diverging evaluations of the same object, but disagreement can also arise from differences in how agents represent that object. AI research on human-machine alignment and recent work in computational cognitive science have focused on this latter kind of disagreement, and have developed tools that can be used to quantify the extent of representational overlap between agents. Understanding how divergence and misalignment interact to produce disagreement, and how resolution strategies depend on this interaction, is key to promoting effective collaboration between diverse types of agents.