Reviewerly/exHarmony huggingface dataset:
Multiple Residual Quantization of Pruning

Model compression technology investigates the compression of deep neural networks by quantizing the full-precision weights of the network into low-bit ones, to achieve network acceleration. However, most of the existing quantization operations are calculated by simple thresholding operations, which will lead to serious precision loss. In this paper, we propose a new quantization framework combined with pruning, called Multiple Residual Quantization of Pruning (MRQP), to achieve higher precision quantization neural network (QNN). MRQP recursively performs quantization of the full-precision weights by combining the low-bit weights stem and residual parts many times, to minimize the error between the quantized weights and the full-precision weights, and to ensure higher precision quantization. At the same time, MRQP prunes some weights that have less impact on loss function to further reduce model size.
Heidegger’s Critique of the Natural Science Method

One of the main statements of the work is that in the analysis of development prospects it is necessary to rely on the very roots, the origins of the develop­ment of our civilization, and it is on their philosophical foundations that set the vector of the development of civilization for the future, for many centuries to come. This was pointed out by V.S. Stepin, who, speaking about the philo­sophical foundations of modern science, distinguished the ontological and cate­gorical grids of concepts that are always used when thinking about the future. In many of his works, M. Heidegger spoke about the same, and even more defi­nitely. It is necessary to critically analyze the mathematical method of modern natural science, possible risks and dangers in applying this method to the hu­man world. The paper is devoted to the analysis of the natural science method in the works of Heidegger. This method is associated with the philosophy of Descartes. As Heidegger shows, from the Cartesian concept of the evidence of the “thinking self”, the evidence of mathematical rules follows. These rules are associated with the key concept of measurability, or computability of the physi­cal world. Heidegger connects this computability with the concept of objec­tification. In principle, a person is not objectified, but modern science tries to consider him within the framework of its quantitative method. Heidegger states that such an approach will inevitably lead to the appearance of a human machine. In conclusion, the paper raises the question of the role of quantitative methods in physics and philosophy.
Debris flow risk assessment based on machine learning theory

Taking the debris flow in Chongli County of Hebei Province as the research object, based on the field investigation, this paper analyzed the formation conditions, material source characteristics, trigger mechanism, development stage, and susceptibility of debris flow in the Chongli district. According to the characteristics of debris flow gullies in the study area, the risk and vulnerability evaluation indexes were selected. On this basis, forty-nine debris flow gullies were trained by machine learning, and a debris flow early warning model was constructed. The model was based on six main control factors and trained by a support vector machine to obtain a linear regression equation, which can quickly output its risk level according to the current state of debris flow gullies.
Capacity, load, and effort in translation, interpreting and bilingualism

The ability to communicate through language, which is often said to set humans apart from other animals, is governed by complex cognitive processes enabled by a similarly complex cognitive architecture. The estimated storage capacity of the human brain has recently been revised upwards and put in the range of several million gigabytes. The construct of capacity is usually related to that of working memory and generally understood as the maximum number of resources the system can deploy in order to temporarily retain and process information at a given time. The notion of load finds its origins in educational psychology, more specifically in the construct of Cognitive Load Theory. While comprehension processes are traditionally viewed from the bottom up, production processes are often considered from the top down. Shadowing, in other words the overt verbatim repetition of an auditory message usually heard over headphones, is among the simplest tasks combining language comprehension and production processes in real time.
GIS-Based Emergency Hospital Location Suitability Analysis (Case Study: Surabaya City)

Abstract Indonesia is a country that has been exposed to the COVID-19 virus pandemic, and has positive cases of COVID-19, which are increasing every month. The COVID-19 Handling Task Force confirmed this in 2022. The large number of patients exposed to COVID-19 made the hospital unable to accommodate all patients requiring inpatient treatment, one of the cities that constructed an emergency hospital is the City of Surabaya, which has four emergency hospitals. Surabaya is one of the cities with the most people exposed to the COVID-19 virus. According to the East Java Provincial Government, until 2022, the City of Surabaya was confirmed to have 67,088 cases of COVID-19. According to the mayor of Surabaya, COVID-19 virus patients in the city of Surabaya can be handled well and continue to decline due to the construction of an emergency hospital. The purpose of this paper is to analyze the distribution of the suitability of the location of the emergency hospital to maximize the role of the emergency hospital in the city of Surabaya. The method used is the GIS method, a method that refers to the requirements for the construction of an emergency hospital regulated in the Decree of the Minister of Health of the Republic of Indonesia Number HK.01.07/MENKES/230/2021 concerning Guidelines for the Operation of Field Hospitals/Emergency Hospitals During the Corona Virus Disease Pandemic Period. 2019 (COVID-19). The results showed that four emergency hospitals in the city of Surabaya were by the requirements for the construction of an emergency hospital, namely an emergency hospital located in an area that was in accordance with its designation by the City Spatial Planning and Detailed Map (RDTRK) of the city of Surabaya. From four hospitals emergency, there is no other built area within a radius of 20 meters. From four emergency hospitals, there is no other built area within a radius of 20 meters. It can also be seen that out of the four emergency hospitals, there are public utility networks and drainage canals.
A Framework for Object Detection with Distance Metrics in Vehicular Ad hoc Networks

The detection and tracking of objects in autonomous vehicles is essential for operation safety. There are several approaches for computing the distance between static objects. Conventional machine learning methods are using distance metrics to calculate the distance between the objects like Manhattan distance, hamming distance and Euclidean distance based on p-norm measure. But coming to the field of moving objects the focal length is the point of concern. In this paper, the object detection and also tracking of the object is worked out from the moving camera. The detection is performed based on You Only Look Once (YOLO) algorithms and the distance is calculated by finding the focal length between the object and camera. The methods tailored gave accurate results in assessing the spatial distance between the camera and the moving object.
Locating Optimal Study Areas Using Augmented Reality And Low Cost IoT Devices

Study areas on campuses whether outdoors or indoors provide a space for students to focus on their studies. For these areas to be conducive to study, environmental factors such as temperature, sound and lighting must be considered. Additionally, outdoor spaces have additional factors such as rainfall which could affect the availability of suitable surfaces and seating. This work proposes a system which would allow users interested in utilizing a study space to use Augmented Reality (AR) to identify a suitable area. Using AR, users can use a mobile phone to see an overlay of sensed elements in that space. These elements are sensed by deploying IoT devices which includes Repurposed Cell Phones (RCP) and Arduino technology.
Emergent Archaeological Realities and Reusable Datasets

Archaeological realities often emerge without prior notice, literally popping out of the trench or survey tract in front of seasoned practitioners. Recording these observations is possible using a paper margin or the diary, yet, how do we accommodate the unexpected in our digital systems? While most data capture systems are flexible, is tweaking in the middle of a campaign a good decision considering the long-term? The authors discuss their experience with changing data structures half-way through the fieldwork and the impact these changes had on future data quality and data reuse. Additions and other tinkering with data structures often produce sparse and inconsistent datasets. Tacked-on, partially-filled or NA-dominated columns, however, hinder reuse and often end up discarded from datasets. The question arises of how one should accommodate archaeological data that emerges in the field and, while aberrant, forms part of a fascinating human past that merits documentation? The ethical drive to record everything clashes with the digital future of such loose ends on the “write once, read never” heap. Archaeologists need to navigate these digital challenges if archaeology as a discipline is to rise to big-data
Postcolonial and Indigenous Perspectives in Digital Archaeology

This chapter examines digital archaeology in the Canadian context through postcolonial and Indigenous perspectives. The chapter demonstrates that diversity practices can serve as both gateways and gatekeeping for Indigenous and racialized scholars in Canadian archaeology. Through the case of archaeology in New Brunswick, it is shown how barriers prevent First Nations peoples from ownership of their heritage and how Indigenous data governance principles can re-center First Nations narratives, and open opportunities for Indigenous and racialized students to gain research experience and advanced training in digital method and practice.
Narrating Transitions and Transformations in Cultural Heritage Digital Workflows Using a JSON-Encoded Dataset of Roman Amphitheaters

Sebastian Heath narrates the process of making both data visualizations and maps from a dataset of Roman amphitheaters. It emphasizes transition and transformation as important concepts in digital workflows. The data used as illustration is encoded using Javascript Object Notation (JSON) and its GeoJSON variant. This enables processing using the Python programming language and the steps by which maps and tables are produced are described. It is also shown that GeoJSON data can be imported into the QGIS open-source Geographic Information System. The ease with which the various steps are accomplished are a practical demonstration of the benefits of open standards.
Metadata for the Masses

This chapter seeks to demystify metadata for archaeologists who are responsible for producing and managing digital documentation, but who are not themselves trained in library and information science. It provides a general overview of the role and importance of metadata in contextualizing digital documents and ensuring possibilities for future reuse. Following this overview, common metadata standards such as the Dublin Core are introduced, along with some simple, relatively easy strategies to incorporate metadata into data structures for digital archaeological documentation. After a discussion of Linked Data principles and approaches, the chapter concludes with a brief explanation of ontologies, semantic representations of data, and serialization. Archaeologists producing or using digital data are encouraged to familiarize themselves with these concepts to enhance the discipline’s capacity to produce discoverable, well-described, and reusable digital records.
A Parser Based Apparel Transformation to Aid in Cloth Virtual Try-On

Presenting a tailored state-of-art Deep Learning model pipeline for providing the seamless experience of different fashion designing and editing tasks. Some of the end-user features offered to the world of virtual fashion are: Pose Transfer, various features for top garments, trying out coats/jackets over upper-body garments i.e., layering of outfits at different levels, content removal, introducing stickers to garments on the body, opacity control for layered cloth. These are some of the features which we believe are going to bring a revolutionary step toward the world of virtual fashion try-on. The model separately segments and encodes different garments to provide us the flexibility to try clothes in different orders which provides us different visual experience.
PESQUISA COM GRAFOS

This article is intended as a report on interdisciplinary research in Curatorship, Visual Arts and Literature, within the field of Digital Humanities, using relational graphs from mathematics and other Data Visualization tools. This research extends itself through the author's studies, carried out during her master's, doctoral and post-doctoral studies, between 2015 and 2022. The research is described as a single process, as it is a single continuous reflection.
Implementation of a convolutional neural network using Tensorflow machine learning platform

The generalized algorithm of a typical convolutional neural network realization by means of TensorFlow machine learning library is considered. The peculiarities of the coding implementation of the convolutional neural network in the image recognition problem are analyzed with the example of the MNIST datаset.
Manipulation of a Rigid Object in 3-D Space by a Pair of UAVs using Sliding Modes

We consider the problem of cooperative manipulation of a rigid body by a pair of Unmanned Aerial Vehicles (UAVs) in 3-Dimensional (3-D) space. The maneuvers of the UAVs are designed using sliding mode control so that they can track a platform, also moving in 3-D space, within a finite-time interval and without requiring the knowledge of the platform's acceleration components. The maneuvering strategies, based on kinematics-based engagement dynamics in 3-D space, are also applicable to approach a stationary platform at a desired azimuth and elevation angle. The strategies are also coupled with controllers to orient the azimuth and elevation angles of the rigid body itself. The results are applicable to delivery or retrieval of a payload from moving or stationary platforms.
Onboard path planning for unmanned aircraft automated taxi using a virtual line-graph

Automated taxi is a key enabler for fully automated unmanned aircraft operation and is especially relevant with unmanned aircraft of size and weight which cannot be moved to the take-off position manually. But literature addressing automated taxi trajectory planning and demonstrations of unmanned taxi operations is still rare. Within this paper a path planning approach for automated unmanned aircraft taxi is described and demonstrated. A Dubins car model is used for motion planning. The path planning is conducted with a roadmap method, using a virtual line graph and a local straight-curve-straight planning problem. Using the presented method, taxi trajectories can be planned in a computationally efficient manner as evaluated in an exemplary scenario. For demonstration at a research airport the automated taxi path planning is integrated in a 450kg maximum take-off mass unmanned gyrocopter system.
Weaving a new web

The online world is controlled by a handful of powerful companies. Is it time we put a stop to that by building a new version of the internet? Chris Stokel-Walker logs on to web3
Building a Digital Twin for Local Heating Housing Services

The paper presents a digital twin of a local heating station with a heat consumption loop of a building. It contains a model of the object of control in a PLC which is utilized to stabilize the temperature inside the building. The work discusses the development of the application for process control based on the model loaded into a PLC. The distinguishing feature of the approach is based on code generation from a mathematical model of the control object created in MATLAB Simulink. An additional goal for the control system of the heating station deals with environmental conditions, namely, outdoor temperature. The model of a water-jet unit is built, simulated data are presented, and discussed, the control system is investigated, and the analysis of the data is carried out. The model is checked based on data for the city of St. Petersburg, Russia as an example. Implementation of the approach leads to overcoming risks and disadvantages of reactive organization of heating housing services, the main of which are downtime of the heating supply process and life quality reduction for energy end-users.
Caching Data in a Web Audio Service Using Progressive Web Apps Technologies

The article presents a new approach to developing web audio services. The approach is based on the use of Progressive Web Apps (PWA) technologies and data caching. Data caching using special caching strategies allows for efficient use of network resources and makes the web application capable of working offline. PWA also provides the ability for a web application to be installed on a smartphone directly from the browser. The use of this approach allows you to reduce the cost of developing audio services for various operating systems. As part of our work, we have developed a client application for the audio service. The article presents the structure of the application and the technologies that we used. The results of the research are recommendations for configuring resource caching and a description of a set of tools for developing a client application of a web audio service that can work in online and offline modes.
Analysis and detection of optical path error of large aperture plane mirror

When the Ritchey-Common method is used for high-precision surface shape detection of large-aperture plane mirrors, a reflective spherical mirror needs to be used to build the detection optical path. When building the detection optical path, the plane mirror and the spherical mirror has a large diameter and a long detection optical path, so there are various artificial adjustment errors. In order to solve the problems of high-precision surface shape detection of large-diameter plane mirrors, two common adjustment errors of eccentricity and tilt during optical path detection are analyzed. By using optical software to build a large-diameter plane mirror detection optical path model, set different eccentricity and tilt errors to obtain the system wave aberration, solve the system wave aberration data to obtain the plane mirror shape to be measured, and compare it with the preset standard surface shape. The simulation of a 2m plane mirror shows that the difference between the two Ritchey angles is in the range of 11&deg;~30&deg;. When the eccentricity error is controlled within 5% of the aperture and the tilt error is controlled within 1&deg;, the surface shape recovery results are different from the standard surface RMS by the order of 10<sup>-3</sup>&lambda;. Based on the above error simulation analysis, the actual &Phi;2m plane mirror shape detection is guided, and the results show that the RMS of the plane mirror reaches 0.0238&lambda;, and the PV is 0.1629&lambda; (&lambda;=0.6328um). The purpose of this paper is to reveal the influence of the optical path adjustment error on the shape of the 2m plane mirror, so as to control the error of the plane mirror shape detection of the actual large-aperture mirror.
Scrutinizing UML Teaching and Learning Modeling Tools

The purpose of this paper was to identify, synthesize, and analyze the modeling tools, especially those that support UML modeling and interactive learning methods for Software Engineering and Information Systems Design courses. The goals were to guide both professors and students to choose the proper modeling tools to support software engineering courses objectives. The research identified many successful modeling tools that can help students use what is suitable for learning UML modeling and contribute to engaging students in modeling. Moreover, this research used the meta-ethnography method for synthesizing qualitative results in the area of software engineering, especially modeling. Group of modelling tools have been chosen for this paper based on their usages popularity and successfulness in producing high quality design models. &nbsp;The contribution of this paper is highlighting and defining the strengths, weakness, and limitations of each studied tool. &nbsp
Development of an Additive Manufactured Fitting Sensorized with Optical Fibres for Load Recognition

In this work an additive manufactured fitting sensorized with optical fibres was developed with the objective to recognize the applied loads in terms of load magnitude and orientation. The component was designed with grooves to host the optical fibre sensors. A technological study to assess the strain transfer between the component and the fibre was carried out by comparing two strategies. Such evaluation was based on 3 point bending tests on specimens and numerical studies. Results showed that embedding the optical fibre into a composite patch bonded to the component guarantee good strain transfer. The component was then modeled with Finite Elements and influence functions, which relate the load orientation to the strain read by the sensors, were created. Load identification is obtained minimizing the difference between the strain read by the sensors and the influence functions. A correction procedure for the influence functions was set up using a Genetic Algorithm, which allows taking into account for the discrepancies between numerical model and real component. Virtual experiments with Finite Elements models were performed to assess the correction procedure introducing discrepancies like variation in material properties, contacts and noise. Despite such variability loads were correctly identified, moreover, a high sensitivity to the sensor position and contact clearance was observed. Correction procedure was further assessed experimentally by loading the component with different orientation. Overall results are satisfactory, the algorithm is able to identify the applied loads with sufficient accuracy and only some problems were encountered during a test on a specific configuration.
Efficient Semi-supervised Multi-organ Segmentation Using Uncertainty Rectified Pyramid Consistency

To meet the problems that great dependence on fully annotated data and spatio-temporal inefficiency of remaining automatic multi-organ segmentation methods, an efficient semi-supervised framework with uncertainty rectified pyramid consistency regularization is introduced. Specifically, inspired by the fact that the predictions of the same input should be similar under different disturbance, this work uses an extending backbone to produce different-scale predictions for unlabeled images and encourage them to be consistent. In order to avoid lost of fine detail or model collapse when directly encouraging the multi-scale predictions to be consistent, a rectified scale-level uncertainty-aware module is introduced to enable the framework to gradually learn from reliable prediction regions. To deal with the domain gaps among multi-center datasets, a number of prepocessing methods are utilized, such as resampling the multi-center CT volumes to the same spacing and adjusting the window level and width. Quantitative evaluation on the FLARE2022 20 validation cases given the labels, this method achieves the average dice similarity coefficient (DSC) of 0.793 and average normalized surface distance (NSD) of 0.852.