Reviewerly/exHarmony huggingface dataset:
Organization of teacher education (comparative analysis)

The urgency of the problem of training pedagogical staff capable of demonstrating readiness to perform any task in the course of their work is enhanced by globalization trends and accession to the European educational space. The purpose of the article is to research the organization of teacher education at the present stage of development of educational systems, which involves a comparative analysis of the experience of foreign countries in this aspect. The methods of the research were: analysis, systematization, generalization of scientific sources, comparison of experience in the organization of teacher education. It has been found that the development of teacher education in each country has its own characteristics, but there are also general trends. Among them are the content of teacher training and the organization of their practical training, which is accompanied by the search for new approaches, the freedom of higher education institutions to determine the duration and content of practice, and the differentiation of pedagogical practice. The professional development of teaching staff is carried out through short-term paid courses, participation in seminars, conferences, online courses on teaching programming. New models of pedagogical education are being created that aim to prepare teachers capable of independent learning and development of personal evidence-based practice; to teach effectively in heterogeneous classes with pupilsfrom different social and cultural backgrounds in a wide range of abilities and needs in early childhood education institutions and at the university. A comprehensive analysis of European pedagogical methods and innovative technologies for training future teachers is seen as promising for national education.
Machine Learning Techniques of Weather Forecasting – A Review

Weather is a particular state of the atmosphere that describes the degrees to which it is hot or cold, wet or dry, calm or stormy, clear or cloudy. On earth, most weather phenomena occurs in the lowest layer of the planet’s atmosphere i.e the troposphere. Weather forecasting tools are used in the field of science and technology to forecast atmospheric conditions for a certain place and period. It is a very challenging task for the researchers of this field in this modern era. In this review paper we have tried to estimate the accuracy level of different machine learning method of weather forecasting.
Penerapan Pengkodean Data Base-64 dan Kode QR Citra Foto Wajah untuk Autentikasi Tanda Tangan Dokumen Digital dengan Library Javascript

The application of technology has an impact on replacing conventional methods with modern ones, one of which is providing document authentication. Signatures can be used as a solution in authenticating documents because they are considered capable of being used as mathematical proof that the document is not modified illegally. The difference that lies between the signature on digital documents and conventional documents is in terms of security. Signatures on conventional documents are prone to forgery. This is due to the absence of evidence to ensure that the document has been signed by the party concerned. Thus, the use of signatures on digital documents is more secure than on conventional documents. The security that is carried out to ensure its authenticity is by utilizing a QR code which contains an id, photo of the signatory which is encoded first using base-64 coding, and a link which is used to verify the authenticity of the document. The verification process carried out to ensure its authenticity is by scanning the QR code embedded in the document. The library developed using Javascript and Waterfall is used as a development method, and the testing method used is black-box testing.
Pengembangan Sistem Informasi Monitoring Prospek Marketing Menggunakan Framework Laravel (Studi Kasus: PT Asuransi Bintang Tbk Cabang Lampung)

Insurance companies exist as a means to protect individuals or businesses from unexpected financial risks, such as losses resulting from accidents, natural disasters, fires, or theft. Monitoring the marketing prospect reporting is one of the challenges faced by every insurance company. In light of this issue, this research proposes the development of a marketing prospect monitoring information system. The development of this information system uses Laravel Framework and employs a prototype method, encompassing stages of requirement gathering, design, implementation, evaluation, and system distribution. The results show that this information system has a positive contribution to the company and addresses previous issues, although there are some improvements that need to be considered in the future.
Obstacles in Teaching Reading to Asperger Syndrome Students in The Primary School

Abstract Teaching reading to Asperger’s Syndrome students especially in primary level is difficult. Students with Asperger syndrome often struggle to comprehend other people's perspectives, experiences, or even the possibility that other people may hold experiences, emotions, or opinions that diverge from their own.This study aims to outline the challenges associated with teaching English reading to individuals with Asperger syndrome. This study used a descriptive qualitative methodology. The primary school pupils with Asperger syndrome are the focus of this study.To determine the barriers Asperger syndrome students have when learning to read in English, the researcher employed a qualitative descriptive approach. Based on the results, the author came to the conclusion that teaching English reading to primary kids with Asperger syndrome presents a variety of challenges that call for a customized strategy. The biggest challenge was keeping their eyes open for long stretches of time, which affected their focus and participation in class. The author also noted that these children could have trouble digesting and comprehending complicated directions, so it's critical to provide structured instructions that are broken down into smaller, more doable steps. To keep students' interest and attention, teachers must give clear directions, divide work into manageable chunks, and come up with creative ways to do things.
SQA-SAM: Segmentation Quality Assessment for Medical Images Utilizing the Segment Anything Model

Segmentation quality assessment (SQA) plays a critical role in the deployment of a medical image based AI system. Users need to be informed/alerted whenever an AI system generates unreliable/incorrect predictions. With the introduction of the Segment Anything Model (SAM), a general foundation segmentation model, new research opportunities emerged in how one can utilize SAM for medical image segmentation. In this paper, we propose a novel SQA method, called SQA-SAM, which exploits SAM to enhance the accuracy of quality assessment for medical image segmentation. When a medical image segmentation model (MedSeg) produces predictions for a test image, we generate visual prompts based on the predictions, and SAM is utilized to generate segmentation maps corresponding to the visual prompts. How well MedSeg's segmentation aligns with SAM's segmentation indicates how well MedSeg's segmentation aligns with the general perception of objectness and image region partition. We develop a score measure for such alignment. In experiments, we find that the generated scores exhibit moderate to strong positive correlation (in Pearson correlation and Spearman correlation) with Dice coefficient scores reflecting the true segmentation quality.
The Role of Cyber security in a Digitalizing Economy: A Development Perspective

A transforming economy undergoes several transformations including digitalization. The 21st-century economy must be driven on the wheels of digital technologies that cannot be wished away. This requires protecting vital information in the digital space with an increasing number of actual cyber-attacks and cyber frauds. The economy remains the base of any society and determines its level of development, any form of compromise in this institution spells doom for its various organizations or arms. There is a need to protect vital information which is key to development in any sector. Therefore, the paper interrogates the importance of securing cyberspace, especially in developing economies. Some prevalent cybersecurity threats include; malware that attacks information systems, information theft, and fraud in cyberspace. It becomes imperative that companies, organizations, individuals, and governments envisage security threats to their vital information and that of their clients and customers; and be proactive in adopting security measures and policies that will ensure the integrity of their information systems and reduce the cost of systems’ compromise.
Word classes in corpus linguistics

Abstract Word classes play a central role in corpus linguistics under the name of parts of speech (POS). Many popular corpora are provided with POS tags. This chapter gives examples of popular tagsets and discusses the methods of automatic tagging. It also considers bottom-up approaches to POS induction, which are particularly important for the ‘poverty of stimulus’ debate in language acquisition research. The choice of optimal POS tagging involves many difficult decisions, which are related to the level of granularity, redundancy at different levels of corpus annotation, cross-linguistic applicability, language-specific descriptive adequacy, and dealing with fuzzy boundaries between POS. The chapter also discusses the problem of flexible word classes and demonstrates how corpus data with POS tags and syntactic dependencies can be used to quantify the level of flexibility in a language.
Relational Models for the Lambek Calculus with Intersection and Constants

We consider relational semantics (R-models) for the Lambek calculus extended with intersection and explicit constants for zero and unit. For its variant without constants and a restriction which disallows empty antecedents, Andreka and Mikulas (1994) prove strong completeness. We show that it fails without this restriction, but, on the other hand, prove weak completeness for non-standard interpretation of constants. For the standard interpretation, even weak completeness fails. The weak completeness result extends to an infinitary setting, for so-called iterative divisions (Kleene star under division). We also prove strong completeness results for product-free fragments.
Integral Fractional Ornstein-Uhlenbeck Process Model for Animal Movement

Modeling the trajectories of animals is challenging due to the complexity of their behaviors, the influence of unpredictable environmental factors, individual variability, and the lack of detailed data on their movements. Additionally, factors such as migration, hunting, reproduction, and social interactions add additional layers of complexity when attempting to accurately forecast their movements. In the literature, various models exits that aim to study animal telemetry, by modeling the velocity of the telemetry, the telemetry itself or both processes jointly through a Markovian process. In this work, we propose to model the velocity of each coordinate axis for animal telemetry data as a fractional Ornstein-Uhlenbeck (fOU) process. Then, the integral fOU process models position data in animal telemetry. Compared to traditional methods, the proposed model is flexible in modeling long-range memory. The Hurst parameter $H \in (0,1)$ is a crucial parameter in integral fOU process, as it determines the degree of dependence or long-range memory. The integral fOU process is nonstationary process. In addition, a higher Hurst parameter ($H > 0.5$) indicates a stronger memory, leading to trajectories with transient trends, while a lower Hurst parameter ($H < 0.5$) implies a weaker memory, resulting in trajectories with recurring trends. When H = 0.5, the process reduces to a standard integral Ornstein-Uhlenbeck process. We develop a fast simulation algorithm of telemetry trajectories using an approach via finite-dimensional distributions. We also develop a maximum likelihood method for parameter estimation and its performance is examined by simulation studies. Finally, we present a telemetry application of Fin Whales that disperse over the Gulf of Mexico.
Lecturers’ Perceptions of Using Information, Communication and Technology (ICT) in Fkip Unilak

Nowadays, ICT has huge potential to facilitate learning now, where online learning is as central media in education. Class activities directly is prohibited by government because spreading pandemic covid 19 in the world. This study aims at finding lecturers’ perceptions in using ICT as teaching and learning. This study used qualitative method. The data collection was done through a survey questionnaires consisting of open ended questions. The result of this research showed that the implementation ICT as learning media is effective. ICT helps teachers to be creative, it helps an easy in preparing the material for teaching. It can be concluded that ICT is very important to support teaching and learning process.
Osprey: Pixel Understanding with Visual Instruction Tuning

Multimodal large language models (MLLMs) have recently achieved impressive general-purpose vision-language capabilities through visual instruction tuning. However, current MLLMs primarily focus on image-level or box-level understanding, falling short in achieving fine-grained vision-language alignment at pixel level. Besides, the lack of mask-based instruction data limits their advancements. In this paper, we propose Osprey, a mask-text instruction tuning approach, to extend MLLMs by incorporating fine-grained mask regions into language instruction, aiming at achieving pixel-wise visual understanding. To achieve this goal, we first meticulously curate a mask-based region-text dataset with 724K samples, and then design a vision-language model by injecting pixel-level representation into LLM. Specifically, Osprey adopts a convolutional CLIP backbone as the vision encoder and employs a mask-aware visual extractor to extract precise visual mask features from high resolution input. Experimental results demonstrate Osprey's superiority in various region understanding tasks, showcasing its new capability for pixel-level instruction tuning. In particular, Osprey can be integrated with Segment Anything Model (SAM) seamlessly to obtain multi-granularity semantics. The source code, dataset and demo can be found at https://github.com/CircleRadon/Osprey.
Webinars and War Rooms: Technopolitics of Data in the Digitalizing State

This chapter focuses on ‘Covid war rooms’ created through a repurposing of the control and command centres of Indian smart cities in the context of the coronavirus pandemic by the Indian Smart City Mission. We study this process in the making in webinars that took place in the early days of the pandemic. Webinars and war rooms are analysed as sites of data- and technopolitics in the making where the pandemic works as test bed, accelerator, and legitimation for the full use of the smart city’s surveillant affordances. We argue that these are sites where ‘smartness as epistemology’ can be observed at work. However, we conclude, Indian urban data politics, both highly centralized in its organization and much more fragmented across scales and actors when observed in action, blurs the idea of a frictionless roll-out of this way of seeing and organizing the digitalized city.
Assessing the Cross-linguistic Utility of Abstract Meaning Representation

Abstract Semantic representations capture the meaning of a text. Abstract Meaning Representation (AMR), a type of semantic representation, focuses on predicate-argument structure and abstracts away from surface form. Though AMR was developed initially for English, it has now been adapted to a multitude of languages in the form of non-English annotation schemas, cross-lingual text-to-AMR parsing, and AMR-to-(non-English) text generation. We advance prior work on cross-lingual AMR by thoroughly investigating the amount, types, and causes of differences which appear in AMRs of different languages. Further, we compare how AMR captures meaning in cross-lingual pairs versus strings, and show that AMR graphs are able to draw out fine-grained differences between parallel sentences. We explore three primary research questions: (1) What are the types and causes of differences in parallel AMRs? (2) How can we measure the amount of difference between AMR pairs in different languages? (3) Given that AMR structure is affected by language and exhibits cross-lingual differences, how do cross-lingual AMR pairs compare to string-based representations of cross-lingual sentence pairs? We find that the source language itself does have a measurable impact on AMR structure, and that translation divergences and annotator choices also lead to differences in cross-lingual AMR pairs. We explore the implications of this finding throughout our study, concluding that, while AMR is useful to capture meaning across languages, evaluations need to take into account source language influences if they are to paint an accurate picture of system output, and meaning generally.
Cooperation of Autonomous Mobile Robots with Different Maneuverability in Transportation

This study proposes a cooperative transportation system, which uses multiple autonomous mobile robots with different maneuverability cooperating together to transport a rigid object. The system uses a leader-follower formation control strategy, by using the non-holonomic leading the way while the holonomic AMRs follow. The object is assumed as a constraint between the robots, and the cooperation is tested using a designed destination point, in which each follower robot receives commands from the leader sent through the laptop. To walk straight, all robots receive the same command, but for rotating, leader robot must evaluate the command for the follower robots by the designed method. The Robot Operating System (ROS) is used for the development of the robots and for standard communication. The proposed method is validated through simulation tasks using autonomous mobile robots with different wheel types. The results of the experiments have resulted and supported that holonomic and non-holonomic robots being able to cooperate with each other’s in transportation.
OIX: Unveiling the DNA for a universal digital ID

Governments and businesses worldwide are seeking to create biometrically-secured digital IDs that enable everyone to safely communicate and trade online. But to create a truly universal digital identity, these individual efforts need to be integrated, says Nick Mothershaw of the non-profit Open Identity Exchange (OIX).
Detection of Burst Header Packet Flooding Attacks via Optimization based Deep Learning Framework in Optical Burst Switching Network

Optical Burst Switching (OBS) technique has the greatest potential for securing future Internet connections. In real-time applications, OBS adoption is motivated by the lack of Quality of Service (QoS) in OBS networks. The accuracy of existing methods for detecting the misbehaving nodes that cause Burst Heading Packet (BHP) flooding attacks is typically poor. To overcome these issues, a novel Elephant Herd Algorithm-based Deep Learning (EHA-DL) network has been proposed for detecting BHP flooding attacks. The proposed approach is divided into three phases: pre-processing, feature selection, and classification. The Elephant Herd Algorithm (EHA) is used to select the most crucial features after pre-processing the raw data to increase the effectiveness of the model. To decrease overfitting and increase detection accuracy, a MobileNet is used to construct the model for the classification phase using the select features of BHPs. The performance of the experimental outcomes was assessed using evaluation metrics like accuracy, specificity, recall, and f-measure. The EHA-DL approach method yielded a 99.27% accuracy rate, which was comparatively high when compared to other approaches. In optical burst switching networks, the method effectively and highly efficiently detects flooding assaults and maintains network stability.
DESIGN OF VACUUM MACHINE FOR SEPARATING METAL SCRAP WASTE WITH OIL CUTTING USING AUTODESK INVENTOR

Metal scrap waste mixed with oil cutting can reduce the quality of the oil cutting itself, so it cannot be used directly. Meanwhile, the waste that is mixed with oil cannot be processed directly such as recycling / remelting. Cutting oil as a cooling material for the cutting process, so from here the recycle of cutting oil is needed, so a tool/machine is needed to separate the waste from the oil cutting.&#x0D; The research method used is design research which consists of planning machine elements and making machine designs. In the planning of machine elements, more emphasis is placed on the impler blade of the vacuum separator while the drawing uses Autodesk Inventor. &#x0D; From the results of the design and design of the "vacuum separator" it is obtained that; the dimensions of the impeller are 20 mm in diameter, the impeller neck is 28 mm in diameter, the impeller eye and the inlet side are the same diameter 92 mm, the inlet side of the impeller has an angle of 16 °, the width of the bow is 18.85 mm, while the distance between the blades (𝑡1) is 48.17 mm, the diameter of the outgoing side of the results of the calculation is 230 mm, the angle of the outgoing side of the impeller is 25 ° and the wide side of the impeller is 7.5 mm, at the distance between the blades of the incoming side (𝑡2) 120.42 mm. So that from the design of the machine element, the number of impellers is obtained 6 blades, with the results analyzed with a safety factor of 15 Ul.
Cyber Security - A Case Study of Comodo Security Solutions

Background/Purpose: Humans are currently heavily reliant on digital infrastructure and can easily access practically all services. All of these technological advancements have an impact on people, both positively and badly. As risks change in nature, it becomes much more difficult to overcome them. In the digital age, security is crucial. Many firms have serious cybersecurity concerns. We should practice excellent cyber hygiene, double-check our sources, and keep up with official changes if we want to maintain cybersecurity. Xcitium (previously Comodo Security), a cybersecurity-focused organization, runs many tests to improve detection rates. This business specializes in online and computer security. Objective: Design/Methodology/Approach: This paper discusses the technological improvement of Comodo Security products Findings/Results: This company undergoes much research to improve threat detection and thereby it finds its role in the cybersecurity world. They work in the principle that every single digital transaction must have a layer of trust and security. Originality/Value: Journals, annual reports, academic articles, websites, and the internet were some of the secondary sources used in this study to acquire data. Paper Type: Company Analysis Keywords: cyber security, malware, cyber hygiene, comodo solutions