Reviewerly/exHarmony huggingface dataset:
Pedagogical Bases of Teaching Students the Methodology of Conducting Research Work (on the Example of the Subject Zoology)

The training of modern teachers in higher education through the adaptation of future biologists to scientific and practical activities, self-improvement, integration of education and science, their involvement in cognitive and research activities is a modern requirement. This article presents the results of scientific and pedagogical research, reflecting the organization of research activities of biological students and the stages of research, the role of COOPERATIVE LEARNING in the development of research skills. In the process of researching on the topic, empirical, statistical methods, scientific and laboratory methods and the pedagogical experience of the object of study, a self-assessment map were used. As a result of the research, the research work allowed students to develop their thinking, make them scientific research, and present new thoughts. Using the method of COOPERATIVE LEARNING, students analyzed, processed, summarized, systematized scientific information, and solved a specific problem. Thus, students' research, personal, and cognitive abilities were developed. As a result of research, the importance of teaching and research activities of biological students during laboratory workshops was revealed. In the discipline of vertebrate zoology on the topic «Internal structure of bony fish and amphibians, students were presented with a laboratory and developed research skills. The results of scientific research can be used as methodological guidelines when students master research work of the vertebrate zoology.
A High Secured Steganalysis Using QVDHC Model

Data compression plays a vital role in data security as it saves memory, transfer speed is high, easy to handle and secure. Mainly the compression techniques are categorized into two types. They are lossless, lossy data compression. The data format will be an audio, image, text or video. The main objective is to save memory of using these techniques is to save memory and to preserve data confidentiality, integrity. In this paper, a hybrid approach was proposed which combines Quotient Value Difference (QVD) with Huffman coding. These two methods are more efficient, simple to implement and provides better security to the data. The secret message is encoded using Huffman coding, while the cover image is compressed using QVD. Then the encoded data is embedded into cover image and transferred over the network to receiver. At the receiver end, the data is decompressed to obtain original message. The proposed method shows high level performance when compared to other existing methods with better quality and minimum error.
Block-Chain-Based Vaccine Volunteer Records Secure Storage and Service Structure

Accurate and complete vaccine volunteer’s data are one valuable asset for clinical research institutions. Privacy protection and the safe storage of vaccine volunteer’s data are vital concerns during clinical trial services. The advent of block-chain technology fetches an innovative idea to solve this problem. As a hash chain with the features of decentralization, authentication, and resistibility, blockchain-based technology can be used to safely store vaccine volunteer clinical trial data. In this paper, we proposed a safe storage method to control volunteer personal /clinical trial data based on blockchain with storing on cloud. Also, a service structure for sharing data of volunteer’s vaccine clinical trials is defined. Further, volunteer blockchain features are defined and examined. The projected storage and distribution method is independent of any third person and no single person has the complete influence to disturb the processing..
The results of the study conducted in 2022 at the necropolis medieval settlement Syganak

A mausoleum is a monument, a funeral building that included a chamber where the remains of the dead were placed. The Turkic peoples have built mausoleums over the graves of their dead ancestors for centuries. Mausoleums were considered the afterlife home of the dead. The erected structures make it possible to determine the social status of people buried in the mausoleum or to which class they belonged. After all, it is known that huge mausoleums were built for famous people, consisting of several rooms, with internal and external walls covered with decorative ceramics. The mausoleums had one or more burials. The graves studied and the materials found in them allow us to determine the status, outlook, way of life, traditions, religious beliefs and burial rites of the inhabitants. For this reason, in this article, we set the task of analyzing the studies conducted in 2022 at mausoleums No. 6 and No. 7 and introducing the data obtained during archaeological excavations into scientific circulation. Conducted scientific research within the framework of this topic made it possible to determine the features of mausoleums No. 6 and No. 7, construction technology and construction time. As a result of a comparative analysis with the mausoleums of this type from adjacent regions, the similarities and differences between the mausoleums of Syganak were determined. In addition, in the article we considered it appropriate to present the history of the emergence and development of mausoleums. In the article, when studying the little-studied history of the formation of mausoleums located in the middle reaches of the Syr Darya River, it is known that mausoleums arose on the basis of the ancient funeral tradition of nomadic peoples living in Central Asia.
Survey of United States Related Domains: Secure Network Protocol Analysis

Over time, the HTTP Protocol has undergone significant evolution. HTTP was the internet's foundation for data communication. When network security threats became prevalent, HTTPS became a widely accepted technology for assisting in a domain defense. HTTPS supported two security protocols: secure socket layer (SSL) and transport layer security (TLS). Additionally, the HTTP Strict Transport Security (HSTS) protocol was included to strengthen the HTTPS protocol. Numerous cyber-attacks occurred in the United States, and many of these attacks could have been avoided simply by implementing domains with the most up-to-date HTTP security mechanisms. This study seeks to accomplish two objectives: 1. Determine the degree to which US-related domains are configured optimally for HTTP security protocol setup; 2. Create a generic scoring system for a domain's network security based on the following factors: SSL version, TLS version, and presence of HSTS to easily determine where a domain stands. We found through our analysis and scoring system incorporation that US-related domains showed a positive trend for secure network protocol setup, but there is still room for improvement. In order to safeguard unwanted cyber-attacks, current HTTPS domains need to be extensively investigated to identify if they possess lower version protocol support. Due to the infrequent occurrence of HSTS in the evaluated domains, the computer science community necessitates further HSTS education.
Certification and identification of possible threats to information security of software and firmware

A number of methods, methods and tools are proposed for certification of software and firmware in information systems in order to select approaches and tools for working in non-standard situations in a constantly changing regulatory and methodological framework and possible threats to their information security. The type of certification under consideration is limited to methods and techniques for analyzing vulnerabilities and undeclared capabilities. This type of certification is intended for software research. Not all possible aspects related to this type of certification have been considered, however, the novelty and advantages of the approaches are based on some original approaches in cases where it is not clear how to present sets of input data for testing. Approaches to certification tests are presented using tools of our own design, which allows you to identify the main parameters necessary for assembling software and its research, and to parse software written in various programming languages. Based on the program of testing and verification of the object of assessment in accordance with the requirements of information security under a certain level of control, methods for conducting certification studies are proposed, the advantages of approaches using the available and proposed tools are shown. To save on the purchase of tools, some well-known, free and freely distributed tools, as well as effective and inexpensive software products, are proposed for use in tests.
Effect of Sociability and Curiosity of Senior Developers in Building Agile Scrum Team Competency

This paper aims to investigate the mechanisms that contribute to propagation of competence in an Agile Scrum team. This study seeks to challenge the traditional view of bounded rationality (BR). An Agile Scrum team (Team) is expected to build problem solving competence quickly as the expected ramp up time continues to shrink. But the team has a mixture of expertise, competence and sociability levels that affect out-of-the-box performance. The objective is to expand BR into the social realm and see how teams can self-organize and reconfigure to allow effective problem solving. Studies have shown that agent-based computational simulation is an appropriate technique to explore this point from a theoretical perspective. (Fioretti, 2013) (Secchi, 2015). The first step is to define the problem, discuss how senior team members exhibit high curiosity and apply sociability and cognitive resources to develop overall team competence. This dynamic is modeled and simulated in NetLogoR and the results are analyzed. Finally, some key findings are presented and discussed.
A Comprehensive Survey of Phishing Attacks and Defences: Human Factors, Training and the Role of Emotions

Phishing is a sort of cybercrime as well as a security risk that enables ('phishers') to trick, manipulate, and deceive users into divulging and revealing confidential and sensitive information. Typically, attackers aim to influence and manipulate victims' psyche and emotions. The growing threat of phishing has made it desirable to investigate, and significant research has been undertaken on this matter. This paper explores the human and emotional factors that have been reported in previous studies to be significant in phishing victimization. In addition, we compare what security organizations and researchers have highlighted and emphasised in terms of phishing types and categories as well as training in tackling the problem, in a literature review which takes into account all major credible and published sources.
Causes of Conflicts between Stakeholders and Educational Management

The purpose of the article is to find out the causes of conflicts occurs in the colleges between the stakeholders and educational management by the help of different kinds of literature reviews. The study of article is based on the review of literature and the secondary data has been used. The causes of conflicts occur due to different kinds environment in the organization. That environment may be internal and external. The causes occur due to the misunderstanding, selfishness, dominating behaviour, insufficient resources, traditional planning ways, etc.
User-concerned actionable hot topic mining: enhancing interpretability via semantic–syntactic association matrix factorization

Purpose Mining user-concerned actionable and interpretable hot topics will help management departments fully grasp the latest events and make timely decisions. Existing topic models primarily integrate word embedding and matrix decomposition, which only generates keyword-based hot topics with weak interpretability, making it difficult to meet the specific needs of users. Mining phrase-based hot topics with syntactic dependency structure have been proven to model structure information effectively. A key challenge lies in the effective integration of the above information into the hot topic mining process. Design/methodology/approach This paper proposes the nonnegative matrix factorization (NMF)-based hot topic mining method, semantics syntax-assisted hot topic model (SSAHM), which combines semantic association and syntactic dependency structure. First, a semantic–syntactic component association matrix is constructed. Then, the matrix is used as a constraint condition to be incorporated into the block coordinate descent (BCD)-based matrix decomposition process. Finally, a hot topic information-driven phrase extraction algorithm is applied to describe hot topics. Findings The efficacy of the developed model is demonstrated on two real-world datasets, and the effects of dependency structure information on different topics are compared. The qualitative examples further explain the application of the method in real scenarios. Originality/value Most prior research focuses on keyword-based hot topics. Thus, the literature is advanced by mining phrase-based hot topics with syntactic dependency structure, which can effectively analyze the semantics. The development of syntactic dependency structure considering the combination of word order and part-of-speech (POS) is a step forward as word order, and POS are only separately utilized in the prior literature. Ignoring this synergy may miss important information, such as grammatical structure coherence and logical relations between syntactic components.
Towards an Efficient, Privacy-aware Federated Learning Scheme

Abstract With the rapid evolution of Internet-of-Things (IoT) devices and the emergence of Autonomous Vehicles (AVs), machine learning processes pose a growing privacy issue. Federated learning (FL) and current cryptography can mitigate this problem; however, these solutions might not be efficient enough during the decades-long lifespans of such gadgets. In this paper, a generalization of FL schemes, incorporating sharing a part of raw data, is presented with a proof-of-concept experiment. Besides anonymization, the exchanged data portion can also directly support real-time decision-making. In contrast with cryptographical approaches, the proposed FL scheme can guarantee a certain level of privacy during the whole lifetime of IoT devices or AVs.
SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise

Despite the large progress in supervised learning with neural networks, there are significant challenges in obtaining high-quality, large-scale and accurately labelled datasets. In such a context, how to learn in the presence of noisy labels has received more and more attention. As a relatively complex problem, in order to achieve good results, current approaches often integrate components from several fields, such as supervised learning, semi-supervised learning, transfer learning and resulting in complicated methods. Furthermore, they often make multiple assumptions about the type of noise of the data. This affects the model robustness and limits its performance under different noise conditions. In this paper, we consider a novel problem setting, Learning with Unknown Label Noise}(LULN), that is, learning when both the degree and the type of noise are unknown. Under this setting, unlike previous methods that often introduce multiple assumptions and lead to complex solutions, we propose a simple, efficient and robust framework named Sample Selection and Relabelling(SSR), that with a minimal number of hyperparameters achieves SOTA results in various conditions. At the heart of our method is a sample selection and relabelling mechanism based on a non-parametric KNN classifier~(NPK) $g_q$ and a parametric model classifier~(PMC) $g_p$, respectively, to select the clean samples and gradually relabel the noisy samples. Without bells and whistles, such as model co-training, self-supervised pre-training and semi-supervised learning, and with robustness concerning the settings of its few hyper-parameters, our method significantly surpasses previous methods on both CIFAR10/CIFAR100 with synthetic noise and real-world noisy datasets such as WebVision, Clothing1M and ANIMAL-10N. Code is available at https://github.com/MrChenFeng/SSR_BMVC2022.
A Theory of Dynamic Benchmarks

Dynamic benchmarks interweave model fitting and data collection in an attempt to mitigate the limitations of static benchmarks. In contrast to an extensive theoretical and empirical study of the static setting, the dynamic counterpart lags behind due to limited empirical studies and no apparent theoretical foundation to date. Responding to this deficit, we initiate a theoretical study of dynamic benchmarking. We examine two realizations, one capturing current practice and the other modeling more complex settings. In the first model, where data collection and model fitting alternate sequentially, we prove that model performance improves initially but can stall after only three rounds. Label noise arising from, for instance, annotator disagreement leads to even stronger negative results. Our second model generalizes the first to the case where data collection and model fitting have a hierarchical dependency structure. We show that this design guarantees strictly more progress than the first, albeit at a significant increase in complexity. We support our theoretical analysis by simulating dynamic benchmarks on two popular datasets. These results illuminate the benefits and practical limitations of dynamic benchmarking, providing both a theoretical foundation and a causal explanation for observed bottlenecks in empirical work.
InfoOT: Information Maximizing Optimal Transport

Optimal transport aligns samples across distributions by minimizing the transportation cost between them, e.g., the geometric distances. Yet, it ignores coherence structure in the data such as clusters, does not handle outliers well, and cannot integrate new data points. To address these drawbacks, we propose InfoOT, an information-theoretic extension of optimal transport that maximizes the mutual information between domains while minimizing geometric distances. The resulting objective can still be formulated as a (generalized) optimal transport problem, and can be efficiently solved by projected gradient descent. This formulation yields a new projection method that is robust to outliers and generalizes to unseen samples. Empirically, InfoOT improves the quality of alignments across benchmarks in domain adaptation, cross-domain retrieval, and single-cell alignment.
Bad Citrus: Reducing Adversarial Costs with Model Distances

Recent work by Jia et al., showed the possibility of effectively computing pairwise model distances in weight space, using a model explanation technique known as LIME. This method requires query-only access to the two models under examination. We argue this insight can be leveraged by an adversary to reduce the net cost (number of queries) of launching an evasion campaign against a deployed model. We show that there is a strong negative correlation between the success rate of adversarial transfer and the distance between the victim model and the surrogate used to generate the evasive samples. Thus, we propose and evaluate a method to reduce adversarial costs by finding the closest surrogate model for adversarial transfer.
Beyond the shortest path: the path length index as a distribution

The traditional complex network approach considers only the shortest paths from one node to another, not taking into account several other possible paths. This limitation is significant, for example, in urban mobility studies. In this short report, as the first steps, we present an exhaustive approach to address that problem and show we can go beyond the shortest path, but we do not need to go so far: we present an interactive procedure and an early stop possibility. After presenting some fundamental concepts in graph theory, we presented an analytical solution for the problem of counting the number of possible paths between two nodes in complete graphs, and a depth-limited approach to get all possible paths between each pair of nodes in a general graph (an NP-hard problem). We do not collapse the distribution of path lengths between a pair of nodes into a scalar number, we look at the distribution itself - taking all paths up to a pre-defined path length (considering a truncated distribution), and show the impact of that approach on the most straightforward distance-based graph index: the walk/path length.
Universal Quantum Speedup for Branch-and-Bound, Branch-and-Cut, and Tree-Search Algorithms

Mixed Integer Programs (MIPs) model many optimization problems of interest in Computer Science, Operations Research, and Financial Engineering. Solving MIPs is NP-Hard in general, but several solvers have found success in obtaining near-optimal solutions for problems of intermediate size. Branch-and-Cut algorithms, which combine Branch-and-Bound logic with cutting-plane routines, are at the core of modern MIP solvers. Montanaro proposed a quantum algorithm with a near-quadratic speedup compared to classical Branch-and-Bound algorithms in the worst case, when every optimal solution is desired. In practice, however, a near-optimal solution is satisfactory, and by leveraging tree-search heuristics to search only a portion of the solution tree, classical algorithms can perform much better than the worst-case guarantee. In this paper, we propose a quantum algorithm, Incremental-Quantum-Branch-and-Bound, with universal near-quadratic speedup over classical Branch-and-Bound algorithms for every input, i.e., if classical Branch-and-Bound has complexity $Q$ on an instance that leads to solution depth $d$, Incremental-Quantum-Branch-and-Bound offers the same guarantees with a complexity of $\tilde{O}(\sqrt{Q}d)$. Our results are valid for a wide variety of search heuristics, including depth-based, cost-based, and $A^{\ast}$ heuristics. Universal speedups are also obtained for Branch-and-Cut as well as heuristic tree search. Our algorithms are directly comparable to commercial MIP solvers, and guarantee near quadratic speedup whenever $Q \gg d$. We use numerical simulation to verify that $Q \gg d$ for typical instances of the Sherrington-Kirkpatrick model, Maximum Independent Set, and Portfolio Optimization; as well as to extrapolate the dependence of $Q$ on input size parameters. This allows us to project the typical performance of our quantum algorithms for these important problems.
Primeness of alternating virtual links

The usual notion of primeness for virtual links does not correspond to the notion of primeness typically found in the literature on links in thickened surfaces. We compare these and related notions (split, stabilized, irreducible). Our main result, generalizing a classical result of Menasco, is that an alternating virtual diagram $V$ represents a prime virtual link unless $V$ is "obviously" nonprime. (Adams et al proved a related result.) We also introduce "lassos" for virtual link diagrams and describe how to use lassos to determine by inspection whether or not an alternating virtual diagram is weakly prime, pairwise prime, or nonsplit. This is a companion paper to $\textit{The virtual flyping theorem}$.