Reviewerly/exHarmony huggingface dataset:
A SURVEY RESEARCH ON THE USE OF PROJECT MANAGEMENT APPROACHES IN AGILE SOFTWARE DEVELOPMENT

Project management is unavoidable in today's world as there is a need for continuous improvement across different types of projects. However, project management is not a trivial task, given the multitude of factors that need to be taken into account. Therefore, it is essential that projects effectively apply techniques, methods, software, methodologies, that is, approaches to achieve their goals. Thus, this work aims to identify which are the project management approaches used in agile software development, as well as their main strengths and weaknesses. To achieve the objective of this research, a survey was conducted with 30 software project managers. From this survey, it was possible to identify the main approaches used by these professionals, and these approaches were grouped into eight categories: Software, Methodologies, Methods, Techniques, Tools, Frameworks, Practices and Models. Finally, it was possible to identify 12 strengths of the approaches, as well as seven weaknesses. O gerenciamento de projetos é inevitável no mundo de hoje, pois há uma necessidade de se obter melhorias contínuas por meio de diferentes tipos de projetos. No entanto, o gerenciamento de projetos não é uma tarefa trivial, tendo em vista a multiplicidade de fatores que precisam ser levados em consideração. Diante disso, é essencial que os projetos apliquem de forma eficaz técnicas, métodos, softwares, metodologias, ou seja, abordagens para alcançarem seus objetivos. Assim, este trabalho tem como objetivo identificar quais são as abordagens de gerenciamentos de projetos usadas no desenvolvimento ágil de software, assim como seus principais pontos fortes fracos. Para atingir o objetivo desta pesquisa, foi conduzido um survey com 30 gerentes de projetos de software. A partir deste survey foi possível identificar as principais abordagens utilizadas por esses profissionais, sendo que essas abordagens foram agrupadas em oito categorias: Softwares, Metodologias, Métodos, Técnicas, Ferramentas, Frameworks, Práticas e Modelos. Por fim, foi possível identificar 12 pontos fortes das abordagens, assim como sete pontos fracos.
Cyber security training in Finnish basic and general upper secondary education

Cyber security in Finland is part of other areas of comprehensive security, as digital solutions multiply in society and technologies advance. Cyber security is one of the primary national security and national defense concerns. Cyber security has quickly evolved from a technical discipline to a strategic concept. Cyber security capacity building can be measured based on the existence and number of research and developments, education and training programs, and certified professionals and public sector agencies.&#x0D; Cybersecurity awareness and the related civic skills play an increasingly important role as our societies become more digitalized. Improving citizens' cyber skills through education is an important goal that would strengthen Finland as a country of higher education and expertise and lay the foundation for the society of the future.&#x0D; Pursuant to the Finland’s Cyber Security Strategy (2019) “National cyber security competence will be ensured by identifying requirements and strengthening education and research.” Finland’s Cyber Security Development Programme (2021) necessitates that in basic education ensures young people have sufficient skills to operate in a digital operating environment and that they understand cyber security threats and know how to protect themselves from them. So, cybersecurity is an important subject for everyone, not just industry or public organizations. It’s also vital for our children to understand how to stay safe online, and the need to be aware of any dangers that might come their way. Cybersecurity awareness training is important because it teaches pupils how they can protect themselves from cyber-attacks (MTC, 2021).&#x0D; The study of cybersecurity education in Finland was made in autumn 2021 and spring 2022 for the National Cyber Security Director. According to the study, measures are needed so that cyber security becomes an important aspect when planning education and teaching. There are different models to choose from to make training more effective. This paper presents the results of the research focusing basic and general upper secondary education.
Online Distribution Method of Application Key Based on AKMA

With the development of information technology, security issues such as 5G + Industrial Internet and Internet of Things have attracted more and more attention. This article first introduces that the Third Generation Partnership Project (3GPP) has defined a series of 5G network security technology systems, such as primary authentication, secondary authentication, GBA, AKMA etc. Secondly, this paper analyzes the security problems such as initial key leakage existing in popular security technologies in the current 5G + Industrial Internet, Internet of Things and other scenarios. Finally, in view of the security problems existing in 5G+Industrial Internet, an online password distribution method based on AKMA is designed. The method realizes the generation and online distribution of the application key, and at the same time realizes the functions of regular update and safe storage of the application key, and solves the above-mentioned security problems.
INTEGRACAO ENTRE IOT E BLOCKCHAIN: DESAFIOS E OPORTUNIDADES

Internet of Things and Blockchain are technologies which lately have been quite explored in researches both in academia and industry. The former is gaining space in applications related to smart environments, whilst the later evolves as an infrastructure to support the development of distributed applications. As far as the convergence between these two emerging areas is concerned, researches propose the use of blockchain to build more reliable and robust IoT systems. This paper presents both technologies, as well as the main advantages and challenges on the integration between them. Furthermore, some proposed architectures are discussed, in order to demonstrate the impact of using blockchain in current IoT systems.
ANALYSIS OF PBB COMPATIBILITY WITH THE EXPECTED RESULTS OF THE MPS.BR REQUIREMENTS DEVELOPMENT PROCESS

The software industry in the nation showed a high growth rate. For this reason, software development companies have adopted agile methodologies, aiming at speed in their processes. However, the nation's software market demands a quality model from the software industry, so it is necessary that the quality model and agile methodologies talk to each other in order to maintain the quality and speed of software production. This article aims to present a mapping between the MPS.BR software quality model through the expected results of the requirements development process of the MPS.BR Implementation Guide with the steps of building requirements of the agile methodology Product Backlog Build PBB. This research deals exclusively with requirements engineering as it is the main pillar in the construction of a project. In order to obtain the data from this research, a bibliographic study of the mentioned methodologies was carried out, the analysis of similar characteristics between them and an end to the validation of the study by an expert to consolidate the mapping. The results were satisfactory and will be detailed throughout this article. A indústria de software no país presentou uma alta taxa de crescimento. Por esta razão as empresas de desenvolvimento de software têm feita a adoção de metodologias ágeis, visando rapidez em seus processos. Entretanto o mercado de software do país exige um modelo de qualidade da indústria de software, logo mostra-se necessário que o modelo de qualidade e as metodologias ágeis conversem entre si para que se mantenha a qualidade e a rapidez na produção de um software. Este artigo tem como objetivo apresentar um mapeamento entre o modelo de qualidade de software MPS.BR por meio dos resultados esperados do processo de desenvolvimento de requisitos do Guia de Implementação do MPS.BR com as etapas de construção de requisitos da metodologia ágil Product Backlog Build PBB. Esta pesquisa trata exclusivamente da engenharia de requisitos por ser o pilar principal na construção de um projeto. Para obtenção dos dados desta pesquisa, foi feito um estudo bibliográfico das metodologias citadas, a análise de características semelhanças entre elas e pôr fim à validação do estudo por parte de um especialista para consolidar o mapeamento. Os resultados se mostraram satisfatórios e serão detalhados no decorrer deste artigo.
Digital Marketing Security: Risks and Mitigation Strategies

The field of digital marketing has seen rapid growth in recent years, but with this growth comes new security challenges. This review paper examines the current state of digital marketing and the various security risks associated with it. Firstly, it explores the concept of digital marketing and its various components, including search engine optimization (SEO), social media marketing (SMM), and email marketing. Secondly, it delves into the security challenges faced by digital marketers, including data breaches, hacking, and phishing attacks. Additionally, the paper discusses the importance of implementing strong security measures to protect sensitive customer data. This includes the use of encryption, secure socket layer (SSL) certificates, and firewalls. The review also touches on the role of government and other regulatory bodies in ensuring the security of digital marketing practices. The paper concludes by emphasizing the need for continued education and awareness on the topic of digital marketing security. Marketers must stay up-to-date with the latest threats and implement best practices to secure their campaigns and protect their customers ’ information.
Three proofs of an observation on irreducible polynomials over GF(2)

We present three proofs of an observation of Ahmadi on the number of irreducible polynomials over GF(2) with certain traces and cotraces, the most interesting of which uses an explicit natural bijection. We also present two proofs of a related observation.
A distributed newton method for processing signals defined on the large-scale networks

In the graph signal processing (GSP) framework, distributed algorithms are highly desirable in processing signals defined on large-scale networks. However, in most existing distributed algorithms, all nodes homogeneously perform the local computation, which calls for heavy computational and communication costs. Moreover, in many real-world networks, such as those with straggling nodes, the homogeneous manner may result in serious delay or even failure. To this end, we propose active network decomposition algorithms to select non-straggling nodes (normal nodes) that perform the main computation and communication across the network. To accommodate the decomposition in different kinds of networks, two different approaches are developed, one is centralized decomposition that leverages the adjacency of the network and the other is distributed decomposition that employs the indicator message transmission between neighboring nodes, which constitutes the main contribution of this paper. By incorporating the active decomposition scheme, a distributed Newton method is employed to solve the least squares problem in GSP, where the Hessian inverse is approximately evaluated by patching a series of inverses of local Hessian matrices each of which is governed by one normal node. The proposed algorithm inherits the fast convergence of the second-order algorithms while maintains low computational and communication cost. Numerical examples demonstrate the effectiveness of the proposed algorithm.
Kwon Oh-seol’s Acceptance of National Revolutionary Move- ment Discourse and Tactics of National Liberation Movement

Kwon Oh-seol, who participated in the national liberation movement led by the communist group in Colonial Joseon in the 1920s, participated in the enlightenment movement before accepting socialism. Previous studies have identified his activities as influenced by the national independence movement in the 1910s, but did not to elaborate on his acceptance of socialism and the development of the national liberation movement centered on the popular movement. this paper tried to clarify the relationship between his activities and the national liberation movement by specifically reviewing his growth background and acceptance of socialism, and the theory of national revolutionary movement. Kwon Oh-seol was able to forming an enlightened consciousness of life improvement and a revolutionary class consciousness and possible to participate in the national liberation movement based on the national revolutionary movement. he planned The 6·10 National Movement in 1926 and tried to embrace the Old faction of Cheondogyo and the student class while attempting to raise the public’s consciousness of national liberation. Kwon Oh-seol’s national liberation movement were formed based on the consciousness of life improvement and Comintern’s theory of the National Revolutionary Movement.
Intelligent Transportation Reminder System Using Mobile Terminal and IoT

The intelligent transportation reminder system is analyzed and designed based on Android technology to solve users’ complex and untimely arrival of public transportation problems. Finally, the intelligent transportation accurate reminder system is realized. Through the user’s analysis of public transport demand, the system provides bus route query, transfer query, station query, regular reminder, and other functions. Based on GPS positioning, laser sensors are installed at the front and rear doors of the bus to record the number of people on the bus in real time, and upload the data to the server. When the user travels, the mobile terminal cannot only query the location information of the bus in real time, but also view the crowd on the bus, which is convenient for the user to choose the appropriate bus travel. At the same time, it can push the user's bus information regularly at the specified time, accurately remind the user to take the bus, so that the user can reasonably arrange the bus time.
DCVQE: A Hierarchical Transformer for Video Quality Assessment

The explosion of user-generated videos stimulates a great demand for no-reference video quality assessment (NR-VQA). Inspired by our observation on the actions of human annotation, we put forward a Divide and Conquer Video Quality Estimator (DCVQE) for NR-VQA. Starting from extracting the frame-level quality embeddings (QE), our proposal splits the whole sequence into a number of clips and applies Transformers to learn the clip-level QE and update the frame-level QE simultaneously; another Transformer is introduced to combine the clip-level QE to generate the video-level QE. We call this hierarchical combination of Transformers the Divide and Conquer Transformer (DCTr) layer. An accurate video quality feature extraction can be achieved by repeating the process of this DCTr layer several times. Taking the order relationship among the annotated data into account, we also propose a novel correlation loss term for model training. Experiments on various datasets confirm the effectiveness and robustness of our DCVQE model.
Kelayakan Buku Suplemen Membaca Permulaan Berbasis Kearifan Lokal pada Kelas II Sekolah Dasar

Before actually moving on to the reading comprehension level, students must be proficient in their pre-reading skills. Hence, the researcher intended to create a supplementary book based on local wisdom for second graders to help their pre-reading skills proficiency. This research used a Research and Development (R&amp;D) method with the adaption of the ADDIE model. 2 teachers, 31 students, and 6 expert review were chosen as the sample. Then, the data collection was conducted through interviews and questionnaires techniques. The result showed a “very good” response from students with a 90,5% percentage on the experiment and a “very good” response from teachers with a 96,66% percentage. These findings were supported and categorized as “very good” by the validation of linguistic experts with 92,5% percentage, 98,75% percentage for content experts, and 93,75% for design experts. In conclusion, this supplementary book is decent for pre-reading skill proficiency.
Attacking Compressed Vision Transformers

Vision Transformers are increasingly embedded in industrial systems due to their superior performance, but their memory and power requirements make deploying them to edge devices a challenging task. Hence, model compression techniques are now widely used to deploy models on edge devices as they decrease the resource requirements and make model inference very fast and efficient. But their reliability and robustness from a security perspective are major issues in safety-critical applications. Adversarial attacks are like optical illusions for ML algorithms and they can severely impact the accuracy and reliability of models. In this work, we investigate the performance of adversarial attacks across the Vision Transformer model compressed using 3 SOTA compression techniques. We also analyze the effect different compression techniques like Quantization, Pruning, and Weight Multiplexing have on the transferability of adversarial attacks.
Lightweight Alpha Matting Network Using Distillation-Based Channel Pruning

Recently, alpha matting has received a lot of attention because of its usefulness in mobile applications such as selfies. Therefore, there has been a demand for a lightweight alpha matting model due to the limited computational resources of commercial portable devices. To this end, we suggest a distillation-based channel pruning method for the alpha matting networks. In the pruning step, we remove channels of a student network having fewer impacts on mimicking the knowledge of a teacher network. Then, the pruned lightweight student network is trained by the same distillation loss. A lightweight alpha matting model from the proposed method outperforms existing lightweight methods. To show superiority of our algorithm, we provide various quantitative and qualitative experiments with in-depth analyses. Furthermore, we demonstrate the versatility of the proposed distillation-based channel pruning method by applying it to semantic segmentation.
Learning Using Privileged Information for Zero-Shot Action Recognition

Zero-Shot Action Recognition (ZSAR) aims to recognize video actions that have never been seen during training. Most existing methods assume a shared semantic space between seen and unseen actions and intend to directly learn a mapping from a visual space to the semantic space. This approach has been challenged by the semantic gap between the visual space and semantic space. This paper presents a novel method that uses object semantics as privileged information to narrow the semantic gap and, hence, effectively, assist the learning. In particular, a simple hallucination network is proposed to implicitly extract object semantics during testing without explicitly extracting objects and a cross-attention module is developed to augment visual feature with the object semantics. Experiments on the Olympic Sports, HMDB51 and UCF101 datasets have shown that the proposed method outperforms the state-of-the-art methods by a large margin.
GB-CosFace: Rethinking Softmax-Based Face Recognition from the Perspective of Open Set Classification

State-of-the-art face recognition methods typically take the multi-classification pipeline and adopt the softmax-based loss for optimization. Although these methods have achieved great success, the softmax-based loss has its limitation from the perspective of open set classification: the multi-classification objective in the training phase does not strictly match the objective of open set classification testing. In this paper, we derive a new loss named global boundary CosFace (GB-CosFace). Our GB-CosFace introduces an adaptive global boundary to determine whether two face samples belong to the same identity so that the optimization objective is aligned with the testing process from the perspective of open set classification. Meanwhile, since the loss formulation is derived from the softmax-based loss, our GB-CosFace retains the excellent properties of the softmax-based loss, and CosFace is proved to be a special case of the proposed loss. We analyze and explain the proposed GB-CosFace geometrically. Comprehensive experiments on multiple face recognition benchmarks indicate that the proposed GB-CosFace outperforms current state-of-the-art face recognition losses in mainstream face recognition tasks. Compared to CosFace, our GB-CosFace improves 5.30%, 0.70%, and 0.36% at TAR@FAR=1e-6, 1e-5, 1e-4 on IJB-C benchmark.
Decanus to Legatus: Synthetic Training for 2D-3D Human Pose Lifting

3D human pose estimation is a challenging task because of the difficulty to acquire ground-truth data outside of controlled environments. A number of further issues have been hindering progress in building a universal and robust model for this task, including domain gaps between different datasets, unseen actions between train and test datasets, various hardware settings and high cost of annotation, etc. In this paper, we propose an algorithm to generate infinite 3D synthetic human poses (Legatus) from a 3D pose distribution based on 10 initial handcrafted 3D poses (Decanus) during the training of a 2D to 3D human pose lifter neural network. Our results show that we can achieve 3D pose estimation performance comparable to methods using real data from specialized datasets but in a zero-shot setup, showing the generalization potential of our framework.
‘Labelling the Gaps’: A Weakly Supervised Automatic Eye Gaze Estimation

Over the past few years, there has been an increasing interest to interpret gaze direction in an unconstrained environment with limited supervision. Owing to data curation and annotation issues, replicating gaze estimation method to other platforms, such as unconstrained outdoor or AR/VR, might lead to significant drop in performance due to insufficient availability of accurately annotated data for model training. In this paper, we explore an interesting yet challenging problem of gaze estimation method with a limited amount of labelled data. The proposed method utilize domain knowledge from the labelled subset with visual features; including identity-specific appearance, gaze trajectory consistency and motion features. Given a gaze trajectory, the method utilizes label information of only the start and the end frames of a gaze sequence. An extension of the proposed method further reduces the requirement of labelled frames to only the start frame with a minor drop in the generated label’s quality. We evaluate the proposed method on four benchmark datasets (CAVE, TabletGaze, MPII and Gaze360) as well as web-crawled YouTube videos. Our proposed method reduces the annotation effort to as low as 2.67%, with minimal impact on performance; indicating the potential of our model enabling gaze estimation ‘in-the-wild’ setup $$^{1}$$ (https://github.com/i-am-shreya/Labelling-the-Gaps).