Reviewerly/exHarmony huggingface dataset:
TEAMX or Manned and Unmanned Cooperation

Since several years the UAVs (Unmanned Aerial Vehicle) win more and more market. For specific short missions, UAVs perform surveillance or infrastructure checking. However, due to the UAV limitation in terms of endurance and autonomy, for many missions the cooperation between manned and unmanned aircraft is needed. The UAV will play the role of deported arms and eyes of the helicopter. With such innovation, the helicopter performs what the UAV cannot do and on the operation theatre the UAV performs what the helicopter cannot do anymore. In order to ensure the multipurpose platform functionality of the helicopter, the cooperation system will be considered as an optional and will demand only simple and quick plug and play actions. The main constraints are to relatively locate the UAV and Helicopter with a centimetric accuracy and in addition to ensure safety in flight (collision avoidance) with functionality such as geo and helicopter fencing. With an efficient MUM-T architecture system, we will be capable to perform missions with an increased level of safety, to increase the availability of the H/C, to enlarge the H/C mission perimeter, to reduce the pilot workload and to avoid human operation in the so called 3D (Dull, Dirty, Dangerous) zones.
Cognitive Diagnosis Models

Cognitive diagnosis models originated in the field of educational measurement as a psychometric tool to provide finer-grained information more suitable for formative assessment. Typically, but not necessarily, these models classify examinees as masters or nonmasters on a set of binary attributes. This chapter aims to provide a general overview of the original models and the extensions, and methodological developments, that have been made in the last decade. The main topics covered in this chapter include model estimation, Q-matrix specification, model fit evaluation, and procedures for gathering validity and reliability evidences. The chapter ends with a discussion of future trends in the field.
Statistical Decision Theory

Statistical decision theory provides a general account of perceptual decision-making in a wide variety of tasks that range from simple target detection to complete identification. The fundamental assumptions are that all sensory representations are inherently noisy and that every behavior, no matter how trivial, requires a decision. Statistical decision theory is referred to as signal detection theory (SDT) when the stimuli vary on only one sensory dimension, and general recognition theory (GRT) when the stimuli vary on two or more sensory dimensions. SDT and GRT are both reviewed. The SDT review focuses on applications to the two-stimulus identification task and multiple-look experiments, and on response-time extensions of the model (e.g., the drift-diffusion model). The GRT review focuses on applications to identification and categorization experiments, and in the former case, especially on experiments in which the stimuli are constructed by factorially combining several levels of two stimulus dimensions. The basic GRT properties of perceptual separability, decisional separability, perceptual independence, and holism are described. In the case of identification experiments, the summary statistics method for testing perceptual interactions is described, and so is the model-fitting approach. Response time and neuroscience extensions of GRT are reviewed.
Retraction: CNN based framework for identifying the Indian currency denomination for physically challenged people (IOP Conf. Ser.: Mater. Sci. Eng. 992 012016)

This article has been retracted by IOP Publishing following an allegation that this article may contain tortured phrases [1]. IOP Publishing has investigated and agrees the article contains a number of nonsensical phrases that feature throughout the paper, masking overlap with previously published work [2-4], to the extent that the article makes very little sense. This casts serious doubt over the legitimacy of the article. IOP Publishing wishes to credit PubPeer commenters [5] for bringing the issue to our attention. The authors agree/disagree to this retraction. [1] P. Selvi Rajendran and Dr. T. P. Anithaashri 2020 IOP Conf. Ser.: Mater. Sci. Eng. 992 012016 [2] https://ieeexplore.ieee.org/document/7426896 [3] https://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/3079 [4] https://www.researchgate.net/publication/329487411_Currency_Recognition_System_for_Blind_people_using_ORB_Algorithm [5] https://pubpeer.com/publications/E9B4C348D8BC1D3D6F10FAF94258F1 Retraction published: 19 April 2023
ARIAS: An AR-based interactive advertising system v2

ARIAS is an AR-based advertising system, it can be manipulated by gestures interactively.
Medical Chatbot in Machine Learning

Abstract: This article suggests a medical chatbot that uses machine learning methods to provide personalised healthcare assistance. The chatbot is intended to interact with patients, collect information about their symptoms, medical history, and other pertinent details, and give treatment guidance and recommendations. Natural language processing (NLP) algorithms are used in the suggested chatbot to comprehend patients' requests and provide pertinent answers. It also analyses medical documents and other data using machine learning algorithms to provide personalised health suggestions. To provide efficient and cost-effective medical treatment, the chatbot can be combined with current healthcare systems. This article also examines the possible advantages of using robots in the medical field, such as increased patient involvement, lower healthcare costs, and easier access to medical guidance. The findings of this study show that a chatbot for medical uses is feasible and successful, highlighting the potential for future research in this area
Cloudbook Website

Abstract: CloudBook is a notes-taking platform that allows users to create and organize notes in separate files with headings, subheadings, and content. The platform automatically updates the changes made when users save and sign out. While phone notepads are commonly used to write down grocery lists, to-do lists, or notes from presentations, these notes often get lost or become disorganized. Additionally, transferring them to a computer can be challenging. To address this issue, CloudBook was created to provide an organized and accessible format for note-taking. The platform includes features such as checklists, emoticons, and the ability to save external links for further reading. Users can access their notes from any device by logging into their accounts.
Chatbot in Artificial Intelligence

Abstract: This paper discloses a virtual conversational method and system to relieve the psychological stress of adolescents. It also aims at providing some positive information through continuous dialogue answers in order to guide adolescents to think and face difficulties with a positive and optimistic attitude and the agenda of reliving the psychological pressure of the adolescents can be achieved. Conventional face-to-face stress detection and relief methods do not work when confronted with those adolescents who are reluctant to express their negative emotions to the people in real life. In this paper, we would like to present an adolescent- oriented intelligent conversational chatting system called “HappySoul”, which acts as a virtual friend who can assist to encourage, understand, comfort, and guide stressful adolescents to pour out their bad and negative feelings, thereby releasing the stress. Chatbots, or conversational interfaces, present a new way for adolescents to interact with computer systems. This chatbot will allow a user to simply ask questions in the same way that they would address a human. The technology at the core of the proposed chatbot is natural language processing (“NLP”), RNN and client server architecture with the help of Android GUI.
MMANet: Margin-aware Distillation and Modality-aware Regularization for Incomplete Multimodal Learning

Multimodal learning has shown great potentials in numerous scenes and attracts increasing interest recently. However, it often encounters the problem of missing modality data and thus suffers severe performance degradation in practice. To this end, we propose a general framework called MMANet to assist incomplete multimodal learning. It consists of three components: the deployment network used for inference, the teacher network transferring comprehensive multimodal information to the deployment network, and the regularization network guiding the deployment network to balance weak modality combinations. Specifically, we propose a novel margin-aware distillation (MAD) to assist the information transfer by weighing the sample contribution with the classification uncertainty. This encourages the deployment network to focus on the samples near decision boundaries and acquire the refined inter-class margin. Besides, we design a modality-aware regularization (MAR) algorithm to mine the weak modality combinations and guide the regularization network to calculate prediction loss for them. This forces the deployment network to improve its representation ability for the weak modality combinations adaptively. Finally, extensive experiments on multimodal classification and segmentation tasks demonstrate that our MMANet outperforms the state-of-the-art significantly. Code is available at: https://github.com/shicaiwei123/MMANet
Analysis of Interpolating Regression Models and the Double Descent Phenomenon

A regression model with more parameters than data points in the training data is overparametrized and has the capability to interpolate the training data. Based on the classical bias-variance tradeoff expressions, it is commonly assumed that models which interpolate noisy training data are poor to generalize. In some cases, this is not true. The best models obtained are overparametrized and the testing error exhibits the double descent behavior as the model order increases. In this contribution, we provide some analysis to explain the double descent phenomenon, first reported in the machine learning literature. We focus on interpolating models derived from the minimum norm solution to the classical least-squares problem and also briefly discuss model fitting using ridge regression. We derive a result based on the behavior of the smallest singular value of the regression matrix that explains the peak location and the double descent shape of the testing error as a function of model order.
Penerapan Model pembelajaran Project Based Learning (PjBL) untuk Meningkatkan Hasil Belajar Bahasa Indonesia Siswa Kelas I Materi Ungkapan Terimakasih, Maaf dan Tolong di SDN Banjarsugihan V/617 Surabaya

This study aims to determine the increase in activity and learning outcomes of Indonesian language students in grade I at SDN Banjarsugihan V/617, Surabaya, use Project Based Learning (PjBL) learning. This researhed is a classroom action research carried out for two cycles conducted an class I SDN Banjarsugihan V/617 many as 26 students.Cycle I shows the completeness of student learning activities reaching 74.78% and student learning outcomes of 58%. In cycle II, student learning activities increased to 85.89%, while students learning outcomes achieved 88%. Based on the results of the research above, it can be concluding that the use of Project Based Learning (PjBL) learning can increase activities and learning outcomes of Indonesian language material for expressions of thanks, sorry and help class I students at SDN Banjarsugihan V./617 Surabaya semester I 2022-2023 school years. Keywords: Project Based Learning (PjBL), learning outcomes, Learning Activities
Succupedia: Augmented reality-driven horticultural book and its potential on becoming a metaverse object

During the pandemic, the new culture of working from home ignited new interests and hobbies to help entertain people from the monotony of lockdown.Horticultural activity has seen a surge in popularity over the past year.Unsurprisingly, horticultural activity has indeed helped people to stay physically and mentally well.The wave of new horticulturalists has led to a growth in sales of house plants, especially succulents.Unfortunately, many plants died due to a struggle in finding proper care.Therefore, it is necessary to provide education and guidance on succulent plant cultivation through the Succupedia book.Succupedia is an augmented reality-driven (AR) book that aims to provide knowledge about succulents for beginners.In parallel, the pandemic has left the creative industry devastated to seek new sources of income, as many projects and events are cancelled, and the discovery of Non-Fungible Token (NFT) is becoming popular.Conceptually, this article extends how AR objects inspired by horticultural activity could potentially become an NFT object inside of the Metaverse as meta-species.
RESEARCH ON APPLICATION OF COMPUTER GRAPHICS SOFTWARE

Computer graphics software has become an integral part of the digital age, transforming the way we create and interact with visual media. The software allows users to create stunning visual content that can be used in a variety of industries. One such industry is the film industry, where computer graphics software is extensively used to create realistic visual effects and animations that are immersive and visually appealing to audiences. The gaming industry is another industry where computer graphics software plays a crucial role. Game developers use computer graphics software to create 3D models, animations, and environments for video games. The development of game engines such as Unity and Unreal Engine has led to the creation of visually stunning games that have revolutionized the gaming industry. Advertising and marketing are other industries that have significantly benefitted from computer graphics software. Digital advertisements, product designs, and marketing campaigns can be created with ease, making them more visually appealing and engaging to potential customers. The software allows advertisers to create unique and compelling content that stands out from their competitors. The architecture and engineering industries also rely heavily on computer graphics software to create 3D models of buildings and structures. The software allows designers to create accurate and realistic designs that can be used for presentations and proposals. It has become an essential tool in the architecture and engineering industries, enabling designers to visualize their ideas and present them to clients with more clarity. Advancements in computer graphics software have made it easier for users to create stunning visual content. The development of new tools and techniques has improved the user experience and enhanced the quality of graphics. For instance, machine learning algorithms have been integrated into the software, enabling users to create more realistic images and animations. The future of computer graphics software is bright, with new technologies and innovations constantly being developed. The development of augmented and virtual reality has revolutionized the way we experience visual content, and software developers are working on tools and techniques to create even more immersive experiences for users. With the continuous development of technology, we can only expect to see even more exciting developments in the world of computer graphics software.
A world with Cloud Computing

Cloud computing is a type of computing that utilizes a network on the internet rather than a local server or a personal computer to store, manage, and process data,. It is a model of service delivery that allows businesses to access technology-enabled services over the internet. Cloud computing provides a range of benefits to users, including scalability, cost savings, increased collaboration and productivity, and improved disaster recovery and business continuity. Moreover, cloud computing offers businesses the opportunity to access enterprise-level applications and services without the need to invest in costly hardware and software. This abstract outlines the basics of cloud computing, its benefits, and the potential for businesses to leverage it for their own success. Cloud computing is a model of delivering on- demand computing resources, including servers, storage, and applications, over the internet. In this model, users can access these resources from anywhere and at any time without needing to manage or own the underlying infrastructure. Cloud computing offers several benefits, including scalability, cost efficiency, and flexibility. It enables businesses to easily scale their operations up or down based on changing demands, pay only for the resources they use, and access a range of services without needing to invest in their own hardware and software. Cloud computing has become increasingly popular in recent years, with public cloud providers like Amazon Web Services, Microsoft Azure, and Google Cloud Platform dominating the market. As more businesses move their operations to the cloud, the need for skilled cloud computing professionals is also increasing. KEYWORDS Cloud computing, services, businesses,storage ,data,storage,
Using Facebook Stories to Improve Vocabulary Learning among Year 4 Pupils in Rural School

Vocabulary is the fundamental aspect of learning a language.Language learners must acquire vast vocabulary knowledge to master the four basic skills of a language which are; listening, speaking, reading and writing.Nonetheless, lack of vocabulary repertoire is a prevalent issue among young learners in ESL Malaysian primary classrooms.This study aimed to improve the vocabulary learning among primary school pupils in a rural setting.This action research had been conducted on eight Year 4 pupils using Facebook Stories as the digital intervention in facilitating the pupils to learn about vocabulary.The data collection methods used by the researcher were pre and post-test, observations and semi-structured interview.Observation was carried out to analyse the pupils' behaviours in classroom.Field notes, interview transcript and pupils' pre-and post-test results were the primary sources to gain knowledge and insight on the effectiveness of using Facebook Stories.The findings of this study shown that pupils' vocabulary learning and the researcher's vocabulary teaching technique was improved with the help of Facebook Stories.
Investigation of the Properties of First Nearest Neighbors’ Graphs

In this study we present a benchmark of statistical distributions of the first nearest neighbors in random graphs. We consider distribution of such graphs by the number of disconnected fragments, fragments by the number of involved nodes, and nodes by their degrees. The statements about the asymptotic properties of these distributions for graphs of large dimension are proved. The problem under investigation is to estimate the probability of realization of a certain structure of the first nearest neighbors graph depending on the distribution function of distances between the elements of the studied set. It is shown that, up to isomorphism, the graph of the first nearest neighbors does not depend on the distance distribution. This fact makes it possible to conduct numerical experiments on the construction of basic statistics based on a uniform distribution of distances and obtain tabulated data as a result of numerical modeling. We also discuss the approximation of the distribution of graph vertices by degrees, which allows us to estimate the proportion of randomness for a particular structure resulting from clustering elements of a certain set by the nearest neighbor method. The asymptotic analysis of the fragment distribution is discussed.
Visualization of Knowledge in the Educational Process

The purpose of the study is to examine the theoretical and practical aspects of knowledge visualization in the educational process, to compare different models of knowledge representation, give an example of building an ontology to represent the subject area of knowledge visualization in the learning process, as well as an example of using Kohonen Maps to visualize student performance. In the study, modeling methods were used to learn ontological and cluster models, methods of visualization and data systematization. It is concluded that the visualization of knowledge is a complex, multicomponent concept that has a number of features in the context of the didactic principles of the educational process, the theory of the cognitive model of personality, the features of the perceptual properties of thinking, philosophical perception, the epistemological theory of knowledge and the theory of reflection of reality in the human mind.
Mechanical Properties of Composites Combination of Areca Fronds with Epoxy Resin

Technological advances in material aspects are always increasing, and one of the applications of natural fibers as a matrix in composite materials has begun to be widely used. Composite materials have mechanical properties that are sturdy, corrosion resistant, and concise, and can be used as a substitute for metal materials. Areca palm fronds are part of the areca palm tree which are widely used as storage media because they are durable and weather resistant. The aim of this study was to determine the tensile strength of areca nut composites without alkali treatment combined with epoxy. Tensile test based on ASTM D3039 test standard. The test results showed a maximum tensile strength of 4839886.67 N/m2 or 4.84 MPa, and a modulus of elasticity of 114148270.5 N/m2 or 114.15 MPa. According to the JIS A 5905 standard, it meets the specified requirements, namely elastic strength of 32 MPa and tensile strength of 0.4 MPa.
THE SYSTEM OF VALUES OF THE MODERN SECONDARY VOCATIONAL EDUCATION STUDENTS

The article dwells on the results of monitoring the system of values of secondary vocational education students. The conducted research made it possible to deduce the formation of the system of values in students, their readiness to study at institutions of the secondary vocational level and to get a profession. It was found that together with the increase of importance of such value as happy marriage, the significance of values of love, active and financially secure life, comfort and freedom grow substantially as the students get older. This implies infantilism and inactivity of the most part of the interviewed students. The article suggests the paths for correcting the students’ system of values, taking into account the specifics of the obtained profession.
Quack Attack: De Facto Rate Regulation in Telecommunications

Rate regulation can take many forms. Rates may be regulated through overt price controls, such as price ceilings or price floors; through less-overt rules governing the pace of price changes; or through quality mandates or restrictions. Some rate regulations can provide short-run benefits to certain groups of consumers or producers, but often result in shortages or surpluses that diminish overall welfare. In the long run, rate regulation often distorts investment incentives, leading to a misallocation of investment (e.g., to under- or over-investment).Because the costs of overt rate regulations are so well-known, price controls are often buried under layers of bureaucracy or wrapped in with other policies and programs, such that policymakers can plausibly claim that their proposals do not directly regulate rates. While not explicit price controls, these programs amount to de facto rate regulation. It’s a regulatory version of the Duck Test.This issue brief gives an overview, with a particular focus on the telecommunications sector, of the consequences of different types of overt rate regulation—price ceilings and prices floors—as well as how quality regulations can amount to rate regulation. Price controls, such as price ceilings and price floors, are government interventions in the market that aim to regulate the prices of goods and services. While they may have some short-term benefits, they can also lead to long-term consequences that are not always positive. We examine, in particular, four telecommunications programs in which de facto rate regulation is a key component.