Reviewerly/exHarmony huggingface dataset:
Deep Kalman Filters Can Filter

Deep Kalman filters (DKFs) are a class of neural network models that generate Gaussian probability measures from sequential data. Though DKFs are inspired by the Kalman filter, they lack concrete theoretical ties to the stochastic filtering problem, thus limiting their applicability to areas where traditional model-based filters have been used, e.g. model calibration for bond and option prices in mathematical finance. We address this issue in the mathematical foundations of deep learning by exhibiting a class of continuous-time DKFs which can approximately implement the conditional law of a broad class of non-Markovian and conditionally Gaussian signal processes given noisy continuous-times measurements. Our approximation results hold uniformly over sufficiently regular compact subsets of paths, where the approximation error is quantified by the worst-case 2-Wasserstein distance computed uniformly over the given compact set of paths.
Cyber crime investigation and digital forensics

Usage of internet has become a daily routine for majority of people for day-to-day transactions. The number of internet users has grown tremendously and so does cybercrimes. Cybercrime is a growing issue, still not fully understood by researchers or policing/law enforcement communities. This research paper analyzes the cybercrimes, talks about its prevention and control, and shows us the problems of cybercrime investigation for obtaining evidence. The readers will get to know the techniques and methods of cybercrime scene protection, site investigation and online tracking in the investigation of cybercrime cases. the paper will review the growth of cybercrimes in India and measures taken by the government of India to combat the cybercrimes. Investigating a crime scene is not an easy job. It requires years of study to learn how to deal with hard cases, and most importantly, get those cases resolved. This applies not only to real-world crime scenes, but also to those in the digital world. Technology has become pivotal a part of life, Criminals use new technology developments to commit crimes, and investigators must adapt to these changes. Many people have, and will become, victims of cybercrime, making it even more important for investigators to understand current methods used in cyber investigations.
Using Personas to Leverage Students’ Understanding of Human Performance Technology to Support Their Instructional Design Practice

Scholars recommend that Human Performance Technology be incorporated within instructional design coursework. HPT embraces a systems-thinking approach that relies heavily on analysis methods. However, many of our students struggle with this mindset. In this chapter we will describe how we used UX techniques (personas and journey maps) to understand a variety of students’ journeys and struggles during an HPT class and identify areas that can be adapted and customized to meet students’ varied needs. Recommendations for how this can be used in course design activities will be offered.
A Low-Cost, User-Friendly Technology for Making Samples and Artifacts Accessible to Online Audiences

AbstractHands-on learning is critical for learning about Earth sciences, but proper samples are often not readily available in all educational settings. While some early adopters offered roadmaps for how technology could help increase access to geological objects and landscapes via digital platforms (CitationDePaor 2016), the COVID-19 pandemic brought the need to deploy such tools from the realm of interesting to essential (CitationAndrews et al. 2020).Keywords: Middle SchoolHigh SchoolInformal EducationInquiryTechnology AcknowledgmentsWe acknowledge use of the Polar Rock Repository collection, funded under NSF grant #1643713. We also would like to recognize Ryan Hollister, whose workshop inspired our team to consider 3D sample collection, and Kira Harris who developed a workflow for our center.While virtual samples are not accessible to all audiences—for instance individuals without an internet connection or audiences who are blind or visually impaired—the Polar Rock Repository loans educational boxes with physical samples to educational institutions at no cost via our website (Rock Boxes for Education).Additional informationNotes on contributorsDaniel HamiltonDaniel Hamilton is a Science Outreach and Coding Intern and at The Ohio State University Byrd Polar and Climate Research Center in Columbus, Ohio.Jason CervenecJason Cervenec is the Education and Outreach Director, at The Ohio State University Byrd Polar and Climate Research Center in Columbus, Ohio.Erica MaleticErica Maletic is a Postdoctoral Scholar at The Ohio State University Polar Rock Repository in Columbus, Ohio.Jeremy PattersonJeremy Patterson is a Senior Graphics Researcher at The Ohio State University Advanced Computing Center for the Arts and Design in Columbus, Ohio.
How plastic is our plastic culture?

Our deep attachment to plastics exists within a complex set of relationships between manufacturers, consumers, markets, and environmental forces. In this paper, I question the reasons behind these relationships and seek to discover why we have become so attached to plastics, and why it is so hard to break this attachment. The effects of plastics extend far beyond the issue of litter, but relate to our construction of identity and our sense of social justice. In this paper, I will argue that plastic is reflective of who we are, and also reflective of the global inequalities we have created and is thus an important social justice issue. I will employ the theory of political ecology to analyze the consumption of single-use plastics within industrialized countries and to untangle these complex relationships. This theory will highlight the influence of finance and power and help to unravel the role of industry and institutions in the seemingly agential decisions we make as consumers. I will then discuss why the plastics problem is so pressing, and why we need to change our culture of single-use plastics. The issue of single-use plastics has widespread global effects, and thus solving the plastics problem is a matter of social justice. I will then apply a political ecological framework to argue that single-use plastics are an integral part of consumer culture, and lie at the core of our identity as a society. Finally, I will turn to the question of how and if our plastic culture is capable of changing.
Effect of financial stability on new business establishments in Africa: does ease of doing business matter?

Purpose Given the relevance of entrepreneurship in nation-building, studies geared towards the promotion of new businesses are crucial. This study aims to contribute to the finance and entrepreneurship literature by providing empirical evidence on the role ease of doing business plays in promoting new business establishments amidst financial stability. Design/methodology/approach The study used the fixed and random effect estimation techniques as well as the impulse response function to analyse annual panel data covering 53 African countries. Findings The results indicate that regulatory quality and access to electricity promote new business establishments. Also, to experience the direct effect of financial stability on new business establishments or entrepreneurship in Africa, the role of the ease of doing business cannot be isolated. The policy implication is that the creation of an enabling business environment is crucial for new business establishments. Research limitations/implications The sample only includes countries in Africa. Future or further studies may want to expand the sample size and also consider a comparative analysis where this analysis will be done plus another region so that the differences in findings can be known. Originality/value To the best of the authors’ knowledge, this is the first study to investigate the role of ease of doing business on new business establishments in the presence of financial stability in Africa.
Unleashing the power of Bat optimized CNN-BiLSTM model for advanced network anomaly detection: Enhancing security and performance in IoT environments

The growth of IoT (Internet of Things) devices has revolutionized several industries and brought about novel security threats. Recognizing network anomalies that may point to malicious activity or system flaws is a major issue. Traditional anomalous identification methods frequently need to catch up when dealing with the special traits of IoT environments, including resource limitations and changing network behavior. This paper introduces an innovative approach, the Bat-optimized CNN-BiLSTM model, to enhance the security and efficiency of IoT environments. This model combines the strengths of Convolutional Neural Networks (CNNs) for spatial analysis and Bidirectional Long Short-Term Memory (BiLSTM) networks for capturing temporal patterns, thus effectively representing time and space trends in IoT data. To optimize its performance further, researchers have leveraged the Bat algorithm, inspired by natural behaviors, to fine-tune the model. This program effectively searches for the best network anomaly detection parameters by imitating the echo activity of bats. Researchers want to increase detection accuracy by lowering false positives and false negatives using the Bat algorithm to enhance the CNN-BiLSTM model. The experimental findings show that the Bat-optimised CNN-BiLSTM model beats the state-of-the-art anomaly detection methods with 99.43% accuracy and efficiency.
Review on Reversible Logic Gates

Abstract: Reversible logic gates have emerged as a pivotal area of research in the field of digital circuit design, offering the promise of ultra-low power consumption. This survey paper comprehensively explores the foundations and practical applications of reversible logic gates. Beginning with an introduction to the fundamental principles of reversibility, it delves into the design of reversible gates, covering CNOT, Feynman, Toffoli, Peres, Fredkin gates, and beyond. The paper offers a systematic review of state-of-the-art research in the field, discussing various optimization techniques and quantum-inspired reversible circuits. It also investigates real-world applications, ranging from low-power VLSI design to quantum computing. By summarizing the key findings, challenges, and potential future directions in reversible logic gate design, this survey paper provides a valuable resource for researchers, engineers, and enthusiasts seeking a comprehensive understanding of this transformative technology
ANI-DB (An Enhanced Anime Database Website)

Abstract: The demand for extensive and user-friendly platforms to organize and access information about anime series, episodes, and associated content has increased due to the industry's rapid growth. This research paper presents the design and development of an Anime Database Website using a combination of Figma, HTML, CSS, JavaScript, and PHP. The primary objective of this project is to create a comprehensive and user-friendly platform for anime enthusiasts to explore, search, and access information about various anime series, characters, and episodes. The website incorporates essential features such as a responsive layout, interactive user interface, advanced search functionality, and a secure database management system. The paper outlines the design process, implementation details, and key features of the developed Anime Database Website, highlighting the useof Figma for prototyping, HTML and CSS for frontend development, JavaScript for client-side interactivity, and PHP for server-side functionality
Metaverse Forensics

The metaverse is poised to offer an immersive virtual environment for people to meet, socialize, collaborate, play, and conduct business transactions. Although the metaverse has not yet reached its full maturity, it has already been misused to launch illegal activities that can jeopardize the safety and well-being of individuals, and cause harm to organizations. Despite its increased importance, “metaverse forensics” remains an unexplored research topic. This chapter starts by reviewing the state-of-the-art research related to metaverse cybersecurity threats and underlying ethical, privacy, and legal issues. It then presents the results of a forensic investigation analysis performed on the VRChat and AltspaceVR metaverse platforms. The authors present new insights into metaverse forensics in terms of accessing digital containers and retrieving useful information for forensic investigators. Additionally, they highlight the primary obstacles encountered in metaverse digital forensic investigations and put forth recommendations for future research directions.
A lattice-based designated-server public-key authenticated encryption with keyword search

Public-key Encryption with Keyword Search (PEKS) provides an efficient way to search on encrypted cloud data. However, it cannot resist against off-line Inside Keyword Guessing Attacks (IKGA). To alleviate this issue, Huang and Li proposed the Public-key Authenticated Encryption with Keyword Search (PAEKS), which the keyword is also authenticated. However, they do not provide post-quantum security promises. In this paper, we propose the first lattice-based designated-server PAEKS (dPAEKS). We formally define dPAEKS and its security models, and propose a lattice-based construction. It is quantum-resistant under the assumption of learning with errors and the sender authenticated the keyword so it can resist IKGA. Furthermore, we strengthen the security requirement, so that only the designated tester can search the ciphertext. Finally, we compare our scheme with some related schemes to demonstrate its efficiency.
Implementasi Augmented Reality Sebagai Media Edukasi Tanaman Hias Berbasis Marked Based

Ornamental plants are plants that we often encounter in the community and in public places, such as in the yard, in the park or in the school yard. Ornamental plants are usually very popular with people, especially housewives, because ornamental plants have their own characteristics and benefits, such as the snake plant (Sansevieria) which has benefits for the environment, namely it can absorb air pollution. In society, especially housewives, it is difficult to care for ornamental plants, so that the plants they cultivate often wilt or die. Therefore, media to increase education about ornamental plants must be improved to help people who want to cultivate ornamental plants. This research uses Marked Based Augmented Reality as a learning medium for the public in introducing and caring for ornamental plants. Augmented Reality is an example of technology that can visualize an object from the virtual world to the real world with a 3D object shape in real time. In this research, the Software Development Life Cycle or Waterfall (SDLC) method was used as the research method. The Software Development Life Cycle method or Waterfall model (SDLC) has five stages, namely data collection, software analysis, software design, implementation and software testing. Based on the results of black box testing, all functions in this application have run well on every Android smartphone used. Testing with the System Usability Scale (SUS) Re-spondents also got a score of 84%, so the application was declared acceptable.
The Impact of Collaborative Strategic Reading (CSR) on the Students’ Reading Comprehension

The researcher found some problems of students in reading comprehension. The classroom was also quite crowded, boisterously, and students bored. The aims of this research are to know whether there is any significant effect of using Collaborative Strategic Reading (CSR) on the student reading comprehension. To explained the impact of using Collaborative Strategic Reading (CSR), the researcher used pre-experimental research and quantitative approach with one group pretest and posttest. This research was conducted at SMAN 6 Kediri. The subject of this research is first grade students and the sample consist of 36 students. The result of this research showed that t-score is higher than t-table in the level significant of 0,000. The mean score of pretest is 57,77 and the mean of posttest is 87,77. The result of this research shows that there is any significant effect of using Collaborative Strategic Reading (CSR), it is proven by the different score between pretest and posttest. This strategy helps the students to solve their problem in reading comprehension. The students are able to understand the text easily and enjoy learning.
A survey of consumer health question answering systems

Abstract Consumers are increasingly using the web to find answers to their health‐related queries. Unfortunately, they often struggle with formulating the questions, further compounded by the burden of having to traverse long documents returned by the search engine to look for reliable answers. To ease these burdens for users, automated consumer health question answering systems try to simulate a human professional by refining the queries and giving the most pertinent answers. This article surveys state‐of‐the‐art approaches, resources, and evaluation methods used for automatic consumer health question answering. We summarize the main achievements in the research community and industry, discuss their strengths and limitations, and finally come up with recommendations to further improve these systems in terms of quality, engagement, and human‐likeness.
Probability and confidence: How to improve communication of uncertainty about uncertainty in intelligence analysis

Abstract Intelligence agencies communicate uncertainty to decision‐makers through verbal probability phrases that correspond to numerical ranges (i.e., probability lexicons) and ordinal levels of confidence. However, decision‐makers may misinterpret the relationship between these concepts and form inappropriate interpretations of intelligence analysts' uncertainty. In two experiments, four ways of conveying second‐order probability to decision‐makers were compared: (a) probability and confidence phrases written in the text of a report, (b) the addition of a probability lexicon, (c) the addition of a probability lexicon that varied numerical ranges according to the level of confidence (i.e., revised lexicon), and (d) a probability phrase written in text followed by a numerical range that varied according to the level of confidence. The revised lexicon was expected to improve interpretations of second‐order probability. The 275 participants in Experiment 1 and 796 participants in Experiment 2 provided numerical estimates corresponding to analytic judgments provided in descriptions about three overseas military operations and also indicated their support for approving or delaying the operations. The results demonstrated that providing the numerical range in the text of the report or providing a probability lexicon, improved interpretations of probability phrases above the verbal phrase‐only condition, but not interpretations of confidence. Participants were unable to correctly interpret confidence with respect to the precision of their estimate intervals and their decisions about the operations. However, in Experiments 2 and 3 the effects on these variables of providing decision‐makers with information about the source of the analyst's uncertainty were examined. In Experiment 3 ( n = 510), providing this information improved correspondence between confidence level and approval of the operation. Recommendations are provided regarding additional methods of improving decision‐makers' interpretation of second‐order probability conveyed in intelligence reporting.
Development of Teaching and Learning Process Plans Based on the Use of the Metaverse ZEP Platform in Practical Arts (Technology &amp; Home Economics) Focusing on the “Family Life” Unit

The purpose of this study is to design and develop a Metaverse ZEP platform-based teaching and learning process plan by selecting learning topics that are commonly dealt with among the core concepts of the “family” area of practical (technical and home) subjects. To this end, a teaching and learning process plan was developed through planning, Metaverse platform design, expert review, and revision stages. The Metaverse ZEP “Open Class Day” platform, a virtual learning space, was created and developed to further utilize EduTech programs, such as Padlet, Mentimeter, Jamboard, Miricanvas, and Spatial. The teaching and learning process plan developed in this study consists of a total of seven sessions, including approaching EduTech, Changing Families, Exploring Our Family, and Counseling Centers 1, 2, and 3. Among them, Geumji Counseling Center 1, 2, and 3 was designed as a class in which parents and children participate together in open classes using the ZEP platform. This platform can be used as part of parent classes as well as to encourage online participation in the open classes held periodically at each individual school. In terms of the content validity ratio (CVR) of the developed teaching and learning process verified through five experts, 12 out of 15 questions had a CVR of 1, while the remaining three questions had a CVR of 0.6. The three questions with lower validity were revised and supplemented.
Semi‐supervised domain adaptation via subspace exploration

Abstract Recent methods of learning latent representations in Domain Adaptation (DA) often entangle the learning of features and exploration of latent space into a unified process. However, these methods can cause a false alignment problem and do not generalise well to the alignment of distributions with large discrepancy. In this study, the authors propose to explore a robust subspace for Semi‐Supervised Domain Adaptation (SSDA) explicitly. To be concrete, for disentangling the intricate relationship between feature learning and subspace exploration, the authors iterate and optimise them in two steps: in the first step, the authors aim to learn well‐clustered latent representations by aggregating the target feature around the estimated class‐wise prototypes; in the second step, the authors adaptively explore a subspace of an autoencoder for robust SSDA. Specially, a novel denoising strategy via class‐agnostic disturbance to improve the discriminative ability of subspace is adopted. Extensive experiments on publicly available datasets verify the promising and competitive performance of our approach against state‐of‐the‐art methods.
A Dynamically Programmable Quantum Photonic Microprocessor for Graph Computation

Abstract Quantum computing has grown extensively, especially in system design and development, and the current research focus has gradually evolved from validating quantum advantage to practical applications. In particular, nondeterministic‐polynomial‐time (NP)‐complete problems are central in numerous important application areas. Still, in practice, it is difficult to solved efficiently with conventional computers, limited by the exponential jump in hardness. Here, a quantum photonic microprocessor based on Gaussian boson sampling (GBS) that offers dynamic programmability to solve various graph‐related NP‐complete problems is demonstrated. The system with optical, electrical, and thermal packaging implements a GBS with 16 modes of single‐mode squeezed vacuum states, a universal programmable 16‐mode interferometer, and a single photon readout on all outputs with high accuracy, generality, and controllability. The developed system is applied to demonstrate applications in solving NP‐complete problems, manifesting the ability of photonic quantum computing to realize practical applications for conventionally intractable computations. The GBS‐based quantum photonic microprocessor is applied to solve task assignment, Boolean satisfiability, graph clique, max cut, and vertex cover. These demonstrations suggest an excellent benchmarking platform, paving the way toward large‐scale combinatorial optimization.