Reviewerly/exHarmony huggingface dataset:
Safety Assessment of Chinese Large Language Models

With the rapid popularity of large language models such as ChatGPT and GPT-4, a growing amount of attention is paid to their safety concerns. These models may generate insulting and discriminatory content, reflect incorrect social values, and may be used for malicious purposes such as fraud and dissemination of misleading information. Evaluating and enhancing their safety is particularly essential for the wide application of large language models (LLMs). To further promote the safe deployment of LLMs, we develop a Chinese LLM safety assessment benchmark. Our benchmark explores the comprehensive safety performance of LLMs from two perspectives: 8 kinds of typical safety scenarios and 6 types of more challenging instruction attacks. Our benchmark is based on a straightforward process in which it provides the test prompts and evaluates the safety of the generated responses from the evaluated model. In evaluation, we utilize the LLM's strong evaluation ability and develop it as a safety evaluator by prompting. On top of this benchmark, we conduct safety assessments and analyze 15 LLMs including the OpenAI GPT series and other well-known Chinese LLMs, where we observe some interesting findings. For example, we find that instruction attacks are more likely to expose safety issues of all LLMs. Moreover, to promote the development and deployment of safe, responsible, and ethical AI, we publicly release SafetyPrompts including 100k augmented prompts and responses by LLMs.
Fixed Point Logics on Hemimetric Spaces

The µ-calculus can be interpreted over metric spaces and is known to enjoy, among other celebrated properties, variants of the McKinsey-Tarski completeness theorem and of Dawar and Otto’s modal characterization theorem. In its topological form, this theorem states that every topological fixed point may be defined in terms of the tangled derivative, a polyadic generalization of Cantor’s perfect core. However, these results fail when spaces not satisfying basic separation axioms are considered, in which case the base modal logic is not the well-known K4, but the weaker wK4.In this paper we show how these shortcomings may be overcome. First, we consider semantics over the wider class of hemimetric spaces, and obtain metric completeness results for wK4 and related logics. In this setting, the Dawar-Otto theorem still fails, but we argue that this is due to the tangled derivative not being suitably defined for general application in arbitrary topological spaces. We thus introduce the hybrid tangle, which coincides with the tangled derivative over metric spaces but is better behaved in general. We show that only the hybrid tangle suffices to define simulability of finite structures, a key ‘test case’ for an expressively complete fragment of the µ-calculus.
How To Bind A TPM’s Attestation Keys With Its Endorsement Key

Abstract A trusted platform module is identified by its endorsement key, while it uses an attestation key to provide attestation services, for example, signing a set of platform configuration registers, providing a timestamp or certifying another of its keys. This paper addresses the problem of how a certificate authority binds the endorsement and attestation keys together. This is necessary for the authority to be able to reliably certify the attestation key. This key binding also enables the authority to revoke the attestation key should the endorsement key be compromised. We study all of the existing solutions and show that they either do not solve the problem or cannot be implemented with a real trusted platform module (or both). We propose a new solution which addresses this problem. We develop a security model for our solution and provide a rigorous security proof under this model. We have also implemented the solution using a real trusted platform module, and our implementation results show that this solution is feasible and efficient.
Robust Gan Training with Selective Conditional Matching

Conditional generative adversarial networks (cGANs) have demonstrated remarkable success due to their class-wise controllability and superior quality for complex generation tasks. Typical cGANs solve the joint distribution matching problem by decomposing two easier sub-problems: marginal matching and conditional matching. From our toy experiments, we found that it is the best to apply only conditional matching to certain samples due to the content-aware optimization of the discriminator. This paper proposes a simple but effective training methodology, selective focusing learning, which enforces the discriminator and generator to learn easy samples of each class rapidly while maintaining diversity. Our key idea is to selectively apply conditional and joint matching for the data in each mini-batch. We conducted experiments on recent cGAN variants in ImageNet (64x64 and 128x128), CIFAR-10, and CIFAR-100 datasets, and improved the performance significantly (up to 35.18% in terms of FID) without sacrificing diversity.
Cloud Security Governance Guidelines

Cloud computing is a widely adopted technology thatoffers many benefits, including cost-effectiveness,scalability, and flexibility. However, the use of cloudcomputing also poses significant challenges related todata security and privacy. Cloud security governance isa critical component of managing these challenges.This research paper aims to provide an in-depthanalysis of cloud security governance, its importance,challenges, and best practices for implementation.Study findings indicate that cloud security governanceis critical in protecting organizational assets andreputation, especially in regulated industries. The studyresults also highlight the importance of proactive riskmanagement, employee training, and continuousmonitoring as essential elements of cloud securitygovernance.This research paper offers practical insights andrecommendations for organizations seeking to improvetheir cloud security governance practices. This articleemphasizes the importance of effective cloud securitygovernance. It provides a valuable framework fordeveloping tailored security policies and proceduresthat align with the unique requirements of the cloudenvironment
Internal and External Factors Affecting Reading Performance in English and Filipino

Reading is very important to a pupil.The love of reading may only develop when the child has reading motivation and good reading habits.Family support and the home environment, too are great help in the child's reading development.Hence, this research study aimed to determine the level of the reading factors in reading in terms of reading motivation and reading habit, family support, and home environment among Grade V pupils to identify the level of the respondents' reading performance as to PHIL-IRI result in the First Grading Period, the significant difference between internal factors affecting reading performance and the relationship of the external factors affecting reading performance among Grade V pupils.It was conducted among the Grade 5 respondents ( n= 321) of the five schools in South District.This study used a research-made questionnaire which was tested with a Cronbach result of 0.785.The study used the statistical treatment on the frequency, percentage, mean and standard deviation, and T-test.Findings show that the overall Level of Reading on Internal Factors was high level, and the External Factors resulted in a Very high level; while the PHIL-IRI reading performance is on the Instructional level.Both the internal and external reading factors affect pupils reading performance, thus rejecting the null hypothesis.It is recommended, the reading must be further enhanced both at home and in school for mastery and familiarization with reading materials to help the child develop the love of reading in English and Filipino.
INFORMATION POTENTIAL OF OFFICIAL WEBSITES OF THE MUSEUMS OF CHERKASY REGION AS A SOURCE FOR STUDYING HISTORY OF THE NATIVE REGION AT HISTORY LESSONS

The article analyzes the peculiarities of organization of museum-pedagogical activities in institutions of general secondary education in conditions of mixed education. Raising a sense of patriotism and active citizenship in the younger generation is now recognized as a general national problem. In modern conditions in our country the requirements for education and training of the younger generation are growing. Thus, one of the most important pedagogical tasks is to educate children in love for Ukraine, respectful attitude towards the family, respect for national traditions and customs, the State and native language, and national values of Ukrainian people. Museum pedagogy considers the museum as a place where feelings are nurtured. The museum does not “illustrate” history, does not teach history. It forms a personʼs personal emotional attitude to one or the other historical facts. The main purpose of the museumʼs existence is to serve people; it provides visitors with a symbolic access to the space of culture. The author reveals the meaning of the terms “museum pedagogy” and “mixed learning”, outlines the possibilities of the teacherʼs use of museum tours for teaching and educating students, determines the potential of Internet resources of museums of Cherkasy region in the context of digitalization of school education and introduction of virtual educational technologies. Especially valuable for the work of a history teacher are the virtual tours presented on the official Internet resources of museums and on other tourist-related sites, which provide an opportunity to work with the museum environment both during lessons and in extracurricular activities.The author emphasizes the fact that the representation of the museum on the Internet allows free access to the objects of historical and cultural heritage for a mass audience. The number of visits to relevant museum Internet resources is increasing significantly. Representation of museums on the Internet is the most effective communication channel for informing about news and events in the institution and allows to interest the younger generation (“raised” on the Internet), to study the history of their native land.&#x0D; Keywords: museum pedagogy; site; virtual tour; Internet network; virtual space; communication; reserve; museums.
Three-dimensional path planning of UAV in complex urban environment

Aiming at the three-dimensional path planning problem of UAV in complex urban environment, the improved grid method is used to simulate the flight environment, and the safety of path planning is improved by building a safe flight area and introducing a navigation safety cost function. In order to solve the problems of A* (A_Star) algorithm in path planning, such as large number of nodes, large amount of computation and low planning efficiency, we can reduce the redundant checking process in the path search process by expanding the line of sight strategy, improve the algorithm search efficiency and smooth the planned lines. Analyze the characteristics of each stage of path planning, adaptively adjust the weight factor, design the flight cost function, shorten the length of path planning, and improve the speed of path planning. As a result of the experiment, the improved A* algorithm clearly decreased over the time of the path planning, the number of nodes and the total cost of the flight, and it was clarified that the planned route was smoother and more feasible than the traditional algorithm. The performance of the improved algorithm has been fully verified under the complexity of different cities, which provides a reference for the research of UAV path planning in urban environment.
The Applications of Interface Design and User Experience in Virtual Reality

With the rapid development of science and technology, the application of Virtual Reality (VR) technology is becoming more and more widespread. With its immersion, interactivity and expandability, VR technology has become a promising technology with broad application prospects. Therefore, this paper aims to investigate the factors that influence user experience in the design of user interface in VR environment, and to summarize the key points of VR user interface design in different application areas. The article will take interface design and user experience as the starting point to compare different user interface modes and their impact on user experience in VR environment; meanwhile, the design points of VR user interface in education field and game field and the impact factors on user experience in different scenarios are compared and summarized respectively. The final part of the article summarizes the user interface in VR environment in education and game field, and provides an outlook on the future improvement and enhancement of user experience in VR scenario.
A Survey of Crowd Counting Algorithm Based on Domain Adaptation

Crowd counting, the task of estimating the number of individuals in a crowded scene, has gained increasing attention in computer vision research. However, crowd counting remains a challenging problem due to the complex and diverse nature of crowd scenes. In recent years, domain adaptation has emerged as a promising approach to improve crowd counting performance by adapting a pre-trained model to a target domain with different characteristics. This paper provides a survey of domain adaptation-based crowd counting algorithms, including their methods, datasets, and evaluation metrics. Overall, domain adaptation shows great potential in improving the accuracy and robustness of crowd counting algorithms, and further research in this direction is expected to lead to more effective and practical crowd counting solutions.
Prevalence of malaria infection amongst students of a southwest Nigerian federal university

One of the dreadful parasitic infection that ravages the lives of the very young and old in Sub-Saharan Africa is Malaria. It is a serious public health problem. Although interventions to curtail and curb it prevalence at various tiers of government local, state and federal were enforced, however, such strategy is not well disposed of in the citadel of learning –university amongst the students This form the basis of the objective of the study and why it is conducted. Method: We examined the prevalence of malaria infection among students of the Federal university of Technology, Akure. Nigeria. Blood samples were collected from 300 patients between April 2019 to September 2019. Aged between 15 -30 years that visited the Medical centre with complaints and symptoms ranging from headache, body pains, undulating high temperature, nausea and vomiting abdominal cramps etc. Antimalarial drugs were not administered until outcome of laboratory result is available within a short while. Result: A total number of three hundred (300) subjects were screened for malaria infection 183 (61%) were male while 117 (39%) were female. The number of individuals with malaria infection were 242 (80.6%) of the 300 subjects screened for malaria. Conclusion: The prevalence rate of students infected with malaria parasitaemia is 80.6% of the student populace screened in the university under the study which indicated a high rate of prevalence of malaria. lt is therefore exigent to execute strategic interventions through health education in form of seminars/ workshop for the students and ways of prevention and elimination of the vector – anopheles mosquito in the environment.
Implementation and Design of Home Economics Education Class utilization of Metaverse Platform in University

본 연구의 목적은 메타버스 플랫폼 활용 가정과 수업을 설계하고 적용하여 예비 가정과교사들의 디지털 리터러시를 향상시키는데 있다. 이를 위해 예비 가정과교사를 위한 ‘가정교재연구 및 지도법’ 수업 중 6차시를 메타버스 플랫폼을 활용한 수업으로 설계하여 적용하여 효과성을 분석하였다. 먼저 분석단계에서는 메타버스 플랫폼과 연계한 수업 가능성을 탐색하고, 대학에서 적용가능한 메타버스 플랫폼 활용수업 사례를 분석하였다. 설계와 개발 단계에서는 다양한 메타버스 플랫폼에서 가정교재연구 및 지도법 수업의 TBL, 토의수업, 문제해결수업을 운영하였다. 평가 단계에서는 수업만족도에 대한 설문조사 결과를 실시하여 사전 조사와 비교분석하였다. 연구 결과, 대부분의 학습자가 메타버스 플랫폼 활용 수업에 대해 수업 만족도가 높았고, 학습자-교수자 간 상호작용과 실제 수업사례의 실재감 부분에서 수업의 효과성이 나타났다. 이와 같은 결과를 토대로 다양한 메타버스 플랫폼을 활용한 가정과 수업이 개발되고 학교현장에서 적용되어 수업의 실재성을 높일 수 있는 기회로 확산되길 기대한다.The purpose of this study is to improve the digital literacy of pre-service home economics education teachers by designing and applying ‘teaching materials and methods of home economics education’ class using the Metaverse platform in virtual classes during the Covid-19 pandemic. For this purpose, six lessons of the ‘Teaching Materials and Methods of Home Economics Education’ classes were designed and applied as a class using the Metaverse platform, and the effectiveness was analyzed. In this study, three types of classes(TBL, discussion, and PBL) were developed and evaluated. The results of the study showed that most of the learners were satisfied with the classes utilizing the Metaverse platform, and the effectiveness of the classes was shown in terms of learner-instructor interaction and the realism of actual classroom cases. Based on these results, it is expected that various home economics education classes utilizing metaverse platforms will be developed and applied to school sites to increase the realism of lessons.
What behavioral beliefs could robot-served hotels focus on to attract potential consumers?

Service robots could provide benefits for hotels in terms of productivity and even service quality. However, hotel managers in Spain (and Europe) have not implemented them as yet or are doing so only tentatively. This could be due to the fact that current literature is fragmented (i.e., dominated by hybrid models) and inconclusive and does not provide consistent guidelines for practitioners. This research narrows this gap by showing that a parsimonious application of the Theory of Planned Behavior is useful to predict attitude and buying intention toward robot-served hotels. Through an empirical analysis of 600 consumers in Spain, our findings indicate that hotel managers could focus on intrinsic motivations (enjoyment and challenge). They should also communicate the advantages of hybrid human–robot teams, in which the robots supplement humans instead of substituting them. The anthropomorphism of robots should not be emphasized as it seems to be perceived as a threat. Although utilitarian benefits matter, they seem to have a subordinate salience.
Robust segmented entangling gates with pulse gradient and power optimization using a hypersurface-tangent method

To implement a scalable and fault-tolerant programmable quantum computing architecture, the realization of high-fidelity, robust, and efficient quantum entangling gates in a multiqubit system is an essential requirement. In this paper, we consider the optimization of the segmented amplitude-modulated entangling gates realized by applying spin-dependent forces to a chain of ions trapped in a hybrid quadratic and quartic potential. We propose a geometrical hypersurface-tangent method to optimize the laser power and the pulse gradient, carefully considering the experimental feasibility in realizing the effective Rabi frequency and its change between adjacent pulse segments. In addition, our method allows us to optimize the solution for the case of a few segments by constructing an approximated null space through trading a negligible amount of gate fidelity. Finally, we show that the present scheme can provide a unified framework to improve the robustness to an arbitrary order against random static drifts of the motional frequencies, the gate duration errors, the laser detuning drifts, and their simultaneous drifts.
Business-Oriented Security Analysis of 6G for eHealth: An Impact Assessment Approach

Following the COVID-19 outbreak, the health sector is undergoing a deep transformation that is increasingly pushing it towards the exploitation of technology, thus fostering the growth of digital health (eHealth). Cellular networks play a pivotal role in promoting the digitalization of healthcare, and researchers are banking on beyond fifth-generation (B5G) and sixth-generation (6G) technologies to reach the turning point, given that, according to forecasts, 5G will not be able to meet future expectations. Security is an aspect that definitely should not be overlooked for the success of eHealth to occur. This work aims to address the security issue from a poorly explored viewpoint, namely that of economics. In this paper, we first describe the main eHealth services, highlighting the key stakeholders involved. Then, we discuss how next-generation technologies could support these services to identify possible business relationships and, therefore, to realize an innovative business-oriented security analysis. A qualitative assessment of the impact of specific security breaches in diverse business conditions is provided. Moreover, we examine a case study in order to show the effects of security attacks in a definite scenario and discuss their impact on business dynamics.
<scp>DatAFLow</scp> : Toward a Data-flow-guided Fuzzer

This Replicating Computational Report (RCR) describes (a) our datAFLow fuzzer and (b) how to replicate the results in “ datAFLow : Toward a Data-Flow-Guided Fuzzer.” Our primary artifact is the datAFLow fuzzer. Unlike traditional coverage-guided greybox fuzzers—which use control-flow coverage to drive program exploration— datAFLow uses data-flow coverage to drive exploration. This is achieved through a set of LLVM-based analyses and transformations. In addition to datAFLow , we also provide a set of tools, scripts, and patches for (a) statically analyzing data flows in a target program, (b) compiling a target program with the datAFLow instrumentation, (c) evaluating datAFLow on the Magma benchmark suite, and (d) evaluating datAFLow on the DDFuzz dataset. datAFLow is available at https://github.com/HexHive/datAFLow.
tieval: An Evaluation Framework for Temporal Information Extraction Systems

Temporal information extraction (TIE) has attracted a great deal of interest over the last two decades. Such endeavors have led to the development of a significant number of datasets. Despite its benefits, having access to a large volume of corpora makes it difficult to benchmark TIE systems. On the one hand, different datasets have different annotation schemes, which hinders the comparison between competitors across different corpora. On the other hand, the fact that each corpus is disseminated in a different format requires a considerable engineering effort for a researcher/practitioner to develop parsers for all of them. These constraints force researchers to select a limited amount of datasets to evaluate their systems which consequently limits the comparability of the systems. Yet another obstacle to the comparability of TIE systems is the evaluation metric employed. While most research works adopt traditional metrics such as precision, recall, and F1, a few others prefer temporal awareness -- a metric tailored to be more comprehensive on the evaluation of temporal systems. Although the reason for the absence of temporal awareness in the evaluation of most systems is not clear, one of the factors that certainly weighs on this decision is the need to implement the temporal closure algorithm, which is neither straightforward to implement nor easily available. All in all, these problems have limited the fair comparison between approaches and consequently, the development of TIE systems. To mitigate these problems, we have developed tieval, a Python library that provides a concise interface for importing different corpora and is equipped with domain-specific operations that facilitate system evaluation. In this paper, we present the first public release of tieval and highlight its most relevant features. The library is available as open source, under MIT License, at PyPI and GitHub.