Reviewerly/exHarmony huggingface dataset:
A deterministic gradient-based approach to avoid saddle points

Abstract Loss functions with a large number of saddle points are one of the major obstacles for training modern machine learning (ML) models efficiently. First-order methods such as gradient descent (GD) are usually the methods of choice for training ML models. However, these methods converge to saddle points for certain choices of initial guesses. In this paper, we propose a modification of the recently proposed Laplacian smoothing gradient descent (LSGD) [Osher et al., arXiv:1806.06317 ], called modified LSGD (mLSGD), and demonstrate its potential to avoid saddle points without sacrificing the convergence rate. Our analysis is based on the attraction region, formed by all starting points for which the considered numerical scheme converges to a saddle point. We investigate the attraction region’s dimension both analytically and numerically. For a canonical class of quadratic functions, we show that the dimension of the attraction region for mLSGD is $\lfloor (n-1)/2\rfloor$ , and hence it is significantly smaller than that of GD whose dimension is $n-1$ .
Internet technology letters special section on mobility support in slice‐based network control for heterogeneous environment 2021

Internet Technology LettersVolume 5, Issue 6 e396 EDITORIAL Internet technology letters special section on mobility support in slice-based network control for heterogeneous environment 2021 Daniel Corujo, Corresponding Author Daniel Corujo dcorujo@av.it.pt orcid.org/0000-0002-7484-1027 Universidade de Aveiro and Instituto de Telecomunicações, Aveiro, PortugalSearch for more papers by this authorAugusto Neto, Augusto Neto orcid.org/0000-0002-9936-3770 Informatic and Applied Mathematics Department of the Rio Grande do Norte Federal University, Natal, BrazilSearch for more papers by this authorSeil Jeon, Seil Jeon orcid.org/0000-0002-6924-5159 Huawei Technologies, Stockholm Research Center, Stockholm, SwedenSearch for more papers by this authorMarília Curado, Marília Curado orcid.org/0000-0001-6760-4675 University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, Pólo II - Pinhal de Marrocos, 3030-290 Coimbra, PortugalSearch for more papers by this author Daniel Corujo, Corresponding Author Daniel Corujo dcorujo@av.it.pt orcid.org/0000-0002-7484-1027 Universidade de Aveiro and Instituto de Telecomunicações, Aveiro, PortugalSearch for more papers by this authorAugusto Neto, Augusto Neto orcid.org/0000-0002-9936-3770 Informatic and Applied Mathematics Department of the Rio Grande do Norte Federal University, Natal, BrazilSearch for more papers by this authorSeil Jeon, Seil Jeon orcid.org/0000-0002-6924-5159 Huawei Technologies, Stockholm Research Center, Stockholm, SwedenSearch for more papers by this authorMarília Curado, Marília Curado orcid.org/0000-0001-6760-4675 University of Coimbra, Centre for Informatics and Systems of the University of Coimbra, Department of Informatics Engineering, Pólo II - Pinhal de Marrocos, 3030-290 Coimbra, PortugalSearch for more papers by this author First published: 09 November 2022 https://doi.org/10.1002/itl2.396Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume5, Issue6November/December 2022e396 RelatedInformation
Errorless Robust JPEG Steganography using Outputs of JPEG Coders

Robust steganography is a technique of hiding secret messages in images so that the message can be recovered after additional image processing. One of the most popular processing operations is JPEG recompression. Unfortunately, most of today's steganographic methods addressing this issue only provide a probabilistic guarantee of recovering the secret and are consequently not errorless. That is unacceptable since even a single unexpected change can make the whole message unreadable if it is encrypted. We propose to create a robust set of DCT coefficients by inspecting their behavior during recompression, which requires access to the targeted JPEG compressor. This is done by dividing the DCT coefficients into 64 non-overlapping lattices because one embedding change can potentially affect many other coefficients from the same DCT block during recompression. The robustness is then combined with standard steganographic costs creating a lattice embedding scheme robust against JPEG recompression. Through experiments, we show that the size of the robust set and the scheme's security depends on the ordering of lattices during embedding. We verify the validity of the proposed method with three typical JPEG compressors and the {\it Slack} instant messaging application. We benchmark its security for various embedding payloads, three different ways of ordering the lattices, and a range of Quality Factors. Finally, this method is errorless by construction, meaning the embedded message will always be readable.
The Influence of Innovative Forms and Methods of Learning on the Quality of Professional Training of Higher Education Students

The article investigates the influence of innovative teaching methods on the formation and development of professional competencies of higher education students.&#x0D; The paper shows that the success of the process for assimilation of professional knowledge, skills and abilities by students depends on the professional activity of the teacher. The results of the survey aimed at identifying problems which affect the formation of the professional readiness of scientific and pedagogical workers to implement modern forms and methods of education, including a block of questions regarding the implementation of distance education, were highlighted.&#x0D; The paper proves that higher education institutions of Ukraine actively participated in the development and implementation of distance education and continue to work on the establishment and implementation of methods of teaching distance courses that help any person to get an education, improve their qualifications or carry out retraining with the receipt of relevant certification.&#x0D; The ways to improve the quality of professional training of higher education students via innovative methods and forms of education in combination with traditional ones are identified.
GANStrument: Adversarial Instrument Sound Synthesis with Pitch-invariant Instance Conditioning

We propose GANStrument, a generative adversarial model for instrument sound synthesis. Given a one-shot sound as input, it is able to generate pitched instrument sounds that reflect the timbre of the input within an interactive time. By exploiting instance conditioning, GANStrument achieves better fidelity and diversity of synthesized sounds and generalization ability to various inputs. In addition, we introduce an adversarial training scheme for a pitch-invariant feature extractor that significantly improves the pitch accuracy and timbre consistency. Experimental results show that GANStrument outperforms strong baselines that do not use instance conditioning in terms of generation quality and input editability. Qualitative examples are available online.
Research on the "Foreign Language+" Curriculum System in Universities with Industrial Features

Under the background of the construction of the new liberal arts, the traditional curriculum system for foreign language subjects cannot meet the market demand. The development space of foreign language majors is increasingly compressed, and the quality of graduates is generally declining. The situation of foreign language majors in universities with Industrial Features is even more difficult due to the weakness of their disciplines, the limited teaching staff and the lack of language learning environment. In this paper, we use literature research and questionnaires to explore the development of "foreign language +" courses in universities with Industrial Features with industrial characteristics, by adjusting course hours, diversifying course settings and offering cross-disciplinary courses. This article provides some ideas and suggestions for the development of foreign language courses and curriculum reform in universities with Industrial Features.
Exploring Tertiary Learners’ Perceptions, Activities and Experiences of Using Digital Mind Map via Mobile Application

A promising digital visual aid that encourages learners to think critically and creatively is digital mind mapping.This digital tool takes a conceptual approach to teaching and learning, assisting students in visualizing a subject and comprehending how various ideas are interconnected in both theoretical and practical contexts.However, many students are not exposed and are not proficient in using digital mind maps.Students still need a lot of guidance in the use of this technique.Furthermore, mobile technologies are also a relatively flexible gadget trend that is widely used by students.These two mediums when combined can assist students in learning process.Thus, this paper explored three major aspects (i) learners' perceptions (ii)learners' activities and (iii) learners' experiences of using digital mind map via mobile application.The study used a quantitative method.The questionnaire was distributed to 23 tertiary learners from a selected public university in Malaysia.The data was analysed using the SPSS version 26.The results were presented in percentages.Findings of the study showed that the tertiary learners had positive perceptions om the use of digital mind map via mobile application, used a lot of beneficial activities through the technique, and experienced an exciting and useful technique in using digital mind map via mobile application.Therefore, the results of the study revealed that the use of digital mind map via mobile application apparently encourages the tertiary learners in supporting the learning process of writing.More research is needed to determine the effectiveness of the technique in teaching and learning among the tertiary learners.
AI-Assisted Dynamic Modelling for Data Management in a Distributed System

There are many interdependent computers available in distributed networks. In such schemes, overall ownership costs comprise facilities, such as computers, controls, etc.; buying hardware; and running expenses such as wages, electrical charges, etc. Strom use is a large part of operating expenses. AI-assisted dynamic modelling for data management (AI-DM) framework is proposed. The high percentage of power use is connected explicitly to inadequate planning of energy. This research suggests creating a multi-objective method to plan the preparation of multi-criteria software solutions for distributed systems using the fuzzy TOPSIS tool as a comprehensive guide to multi-criteria management. The execution results demonstrate that this strategy could then sacrifice requirements by weight.
Dynamic game coverage control algorithms for multiple mobile agents through virtual repulsive force

To improve the coverage efficiency of mobile agents, the related information of the agents is generally required partially or completely during the coverage control process, which may lead to a dramatic control cost and energy consumption increase. How to balance the improvement in coverage rate and the reduction of control cost is an important issue in the coverage control area of mobile agents. This paper addresses the dynamic cooperative game coverage control algorithm design problem of a multi-agent system under an incomplete information condition. First, by separating the moving multi-agent system into several subgroups, where each agent can only obtain the position information of the neighbor agents, the coverage control problem of the moving multi-agent system is transformed into a dynamic cooperative game coverage problem of moving multi-groups under incomplete information conditions. Then, the cooperative game rules of the subgroups are presented, and a virtual repulsive force-based dynamic coverage game decision strategy of the agent system is developed to compute the new candidate positions of the agents. Third, the moving multi-agent system is considered a rigid virtual structure, and the coverage control problem of the system is turned into a new one with the virtual structure as a reference frame. Thus, the displacement path planning design of the coverage control for a multi-agent system is simplified. Simulation results reveal that the dynamic cooperative game coverage algorithm based on the virtual repulsive force can effectively realize the coverage control requirement of the moving agent system under the incomplete information condition and can remarkably reduce the cost of coverage control. In addition, compared with several existing coverage algorithms, using the dynamic cooperative game coverage algorithm proposed in this paper requires fewer moving times of agents while obtaining a higher coverage rate.
Physical Benchmarking for AI-Generated Cosmic Web

The potential of deep learning based image-to-image translations has recently drawn a lot of attention; one intriguing possibility is that of generating cosmological predictions with a drastic reduction in computational cost. Such an effort requires optimization of neural networks with loss functions beyond low-order statistics like pixel-wise mean square error, and validation of results beyond simple visual comparisons and summary statistics. In order to study learning-based cosmological mappings, we choose a tractable analytical prescription - the Zel'dovich approximation - modeled using U-Net, a convolutional image translation framework. A comprehensive list of metrics is proposed, including higher-order correlation functions, conservation laws, topological indicators, dynamical robustness, and statistical independence of density fields. We find that the U-Net approach does well with some metrics but has difficulties with others. In addition to validating AI approaches using rigorous physical benchmarks, this study motivates advancements in domain-specific optimization schemes for scientific machine learning.
The height of record-biased trees

Given a permutation $\sigma$, its corresponding binary search tree is obtained by recursively inserting the values $\sigma(1),\ldots,\sigma(n)$ into a binary tree so that the label of each node is larger than the labels of its left subtree and smaller than the labels of its right subtree. In 1986, Devroye proved that the height of such trees when $\sigma$ is a random uniform permutation is of order $(c^*+o_\mathbb{P}(1))\log n$ as $n$ tends to infinity, where $c^*$ is the only solution to $c\log(2e/c)=1$ with $c\geq2$. In this paper, we study the height of binary search trees drawn from the record-biased model of permutations, introduced by Auger, Bouvel, Nicaud, and Pivoteau in 2016. The record-biased distribution is the probability measure on the set of permutations whose weight is proportional to $\theta^{\mathrm{record}(\sigma)}$, where $\mathrm{record}(\sigma)=|\{i\in[n]:\forall j<i,\sigma(i)>\sigma(j)\}|$. We show that the height of a binary search tree built from a record-biased permutation of size $n$ with parameter $\theta$ is of order $(1+o_\mathbb{P}(1))\max\{c^*\log n,\,\theta\log(1+n/\theta)\}$, hence giving a full characterization of the first order asymptotic behaviour of the height of such trees.
Multi-Agent Modelling Notation (MAMN): A Multi-layered Graphical Modelling Notation for Agent-Based Simulations

Cause-effect graphs have been applied in non agent-based simulations, where they are used to model chained causal relations between input parameters and system behaviour measured by appropriate indicators. This can be useful for the analysis and interpretation of simulations. However, multi-agent simulations shift the paradigm of chained causal relations to multiple levels of detail and abstraction. Thus, conventional cause-effect graphs need to be extended to capture the hierarchical structure of causal relations in multi-agent models. In this paper, we present a graphical modelling method that we call Multi-Agent Modelling Notation (MAMN), with which global aspects of the simulation as well as detailed interior mechanisms of agent behaviour can be described. We give proof of concept by showing how the logic that connects individual agent behaviour to global outcomes in a previously published simulation model can be expressed in a concise diagrammatic form. This provides understanding into what drives the model behaviour without having to study source code. We go on to discuss benefits and limitations as well as new opportunities that arise from this type of model analysis.
Emoji Education: How Students Can Help Increase Health Awareness by Making Emojis

Emojis can improve health communication, especially when incorporating emojis into traditionally word-only texts. Beyond improving communication, emojis also offer greater access to health care, especially for vulnerable and marginalized populations with limited health literacy. A recent study found that 94% of patients with limited health literacy preferred health reports with emojis. Moreover, health officials are considering adding emojis to cardiopulmonary resuscitation guidelines and public health guidelines for handwashing. As the world evolves with new technology and new methods of communication, we must also evolve the language and method we use to communicate health information to patients. In this viewpoint, we aim to discuss the methods health care professionals can use to develop novel communication methods using emojis and the benefits of their incorporation into health care communication.
SURG-37. NEURO-ONCOLOGICAL AUGMENTED REALITY: A MORE INTUITIVE APPROACH TO RESECTION PLANNING

Abstract BACKGROUND When preparing for the resection of an intracranial lesion, its borders and optimal approach are often determined using neuronavigation with a tracked pointer. This can sometimes prove challenging, especially for deep-seated lesions. Augmented reality (AR) can simplify and improve this step by directly displaying the lesion on the patient's skin. METHODS A proprietary inside-out infrared tracking solution was developed, allowing for heads-up displaying AR scenes on the Microsoft HoloLens II without the need for an external tracking camera or computer. We included twenty patients with an intracerebral lesion planned for resection. After semi-automatic hologram-to-patient registration, different participants marked the lesion outlines on the patient’s skin, consecutively aided by the Brainlab neuronavigation system and the HoloLens. Each registration on both systems provided a registration transform that was compared for accuracy and consistency. Participant performance was quantified in terms of duration and accuracy for both patient registration and lesion delineation, and compared to expert performance. RESULTS When using AR both registration and delineation were significantly faster than with conventional neuronavigation (p = 0.02 and p &amp;lt; 0.001, respectively, and p &amp;lt; 0.001 for the total duration), taking 79.23 ± 17.48 and 39.58 ± 39.10 seconds while neuronavigation required 96.61 ± 24.54 and 90.80 ± 44.09 seconds. AR had a registration offset of 3.3mm and 3.4°, and was more consistent compared to neuronavigation. AR facilitated more accurate and detailed lesion delineation, while neuronavigation often overestimated lesion size. CONCLUSION Augmented reality provides a faster and more accurate alternative for resection planning. Lesion delineation was more intuitive while retaining high accuracy. Future research should focus on further intraoperative implementations.
Securing healthcare information system through fuzzy based decision-making methodology

The purpose of the healthcare Information System (HIS) is to replace the conventional method of data gathering and organization in hospitals into a modern method of systematic data collection, maintenance and dissemination. There has been an unprecedented rise in the malware and cyber-attacks on HIS recently. Cyber-attacks have become a major crisis for the healthcare industry. To address this scenario, the present paper conducts a study on the security factors integral to the healthcare information system and conducts the performance analysis of these factors. For this intent, the study has employed the Fuzzy Analytic Hierarchy Process (F.AHP) integrated with Technique Order Preference by Similarity to Ideal Solution (TOPSIS) integrated framework for evaluating the performance of each factor. Thereafter, the factors that play a vital role in healthcare data security breaches have been prioritized as per their security weights. Furthermore, the validity of the results obtained by the stated methodology has been established by conducting the sensitivity analysis and comparison of results with the other methods by using the same data set. Based on results thus obtained, the access control and software security have been identified as the most promising security factors.
Boil-Turbine System Identification Based on Robust Interval Type-2 Fuzzy C-Regression Model

The boil-turbine system is a multivariable and strong coupling system with the characteristics of nonlinearity, time-varying parameters, and large delay. The accurate model can effectively improve the performance of turbine–boiler coordinated control system. In this paper, the boil-turbine model is established by interval type-2 (IT2) T-S fuzzy model. The premise parameters of IT2 T-S fuzzy model are identified by robust IT2 fuzzy c-regression model (RIT2-FCRM) clustering algorithm. The RIT2-FCRM is based on interval type-2 fuzzy sets (IT2FS) and applies a robust objective function, this clustering algorithm can reduce the impacts of outliers and noise points. The effectiveness and practicability of RIT2-FCRM are demonstrated by the identification results of the boiler–turbine system.
Exploring hybrid learning readiness and acceptance model using the extended TAM 3 and TPB approach: An empirical analysis

Several universities are experimenting with hybrid-based learning systems to enter a new era after the COVID-19 pandemic. This study explores the model of student readiness and acceptance of the hybrid learning system. For this reason, this study was designed to use Hierarchical Component Models to build a hybrid learning readiness construct and combine it with two other major theories, namely extended TAM 3 and TPB. Data were collected from several logistics business students who had participated in hybrid learning. The findings in this study will prove how the readiness model we built can increase student acceptance of using the hybrid learning system.