Reviewerly/exHarmony huggingface dataset:
Equivalent Causal Models

The aim of this paper is to offer the first systematic exploration and definition of equivalent causal models in the context where both models are not made up of the same variables. The idea is that two models are equivalent when they agree on all essential causal information that can be expressed using their common variables. I do so by focussing on the two main features of causal models, namely their structural relations and their functional relations. In particular, I define several relations of causal ancestry and several relations of causal sufficiency, and require that the most general of these relations are preserved across equivalent models.
Threat Intelligence Analytical Software

KTP № 11598 was a public-private research partnership between Lancaster University and Mitigate Cyber that ran from August 2019–March 2021, part-funded by Innovate UK. The goal of the partnership was to design and implement a novel IT threat intelligence analysis and quantitative risk calculation tool that would integrate into Mitigate Cyber’s existing SaaSS platform.
Periodization of training of specialists in the system of Secondary and Higher vocational education in the Volga region (from 1917 up to the early 1960 years)

Examined is the problem of modernization of vocational training system, that experience does not exclude reference to the historical past, since interesting experience in solving various problems and tasks can be used at present. The analysis of archival sources allows to trace exactly, how the process of formation of vocational training system at its initial stages took place and to get an understanding of what factors influenced it. This article presents the periodization of specialists’ training in the system of secondary and higher professional education from 1917 up to 1961 years. The first period 1917–1945 presents development of a net of secondary and higher training system institutions under new socio-economic conditions and establishment of new types of institutions. The second period from 1945 up to beginning of the 1960 years shows development of a centralized personnel training system, its improvement based on principles of statehood, centralization, consistency and efficiency. The choice of the territorial framework is due to the fact, that the Volga region is a central region of Russia, particularities of the development of vocational training system in which are typical for other regions of our country. The choice of chronological period is explained by the fact, that in the period from 1917 up to 1961 years the traditional specialists’ training system started to form in our country and was finally completed.
Realistic Rain & Fog & Thunder Sounds V4.0.1

Realistic Rain & Fog & Thunder Sounds V4.0.1 Released Compatible With ETS 1.34.x & 1.35.x Features & News In Rain & Fog & ...
Actual Legal Aspects of the Referencing and Indexing of Scientific Publications in Bulgaria

This paper examines the indexation of scientific publications in the context of the requirements of the digital society. The process is examined in terms of the interconnection development of the academic staff and the necessity of dissemination of scientific works through publication in referenced and indexed editions. The emphasis is on legal publications, which are examined in comparison to other scientific publications. On the basis of this analysis the author makes conclusions, generalisations and practical recommendations.
Improved Single Target Tracking Learning Detection Algorithm

In order to improve the robustness and speed of single target tracking, this paper proposes an improved tracking learning method. The purpose is to improve the tracking module in the traditional tracking learning detection (TLD) algorithm. By introduced oriented fast and rotated brief (ORB) feature points and keep the original uniform distribution point to improve the robustness and speed up execution of tracking. The experiment shows that the improved TLD algorithm has strong robustness in different environments, and the feat can quickly and accurately track the single object. The proposed algorithm can overcome the tracking failures caused by objects with partial occlusion, fast motion and leave the tracking field of vision, and has better robustness. It is experimentally verified that it has the veracity and the execution speed, compared with the traditional TLD algorithm.
Applying Strategic Reasoning for Accountability Ascription in Multiagent Teams.

For developing human-centred trustworthy autonomous systems and ensuring their safe and effective integration with the society, it is crucial to enrich autonomous agents with the capacity to represent and reason about their accountability. This is, on one hand, about their accountability as collaborative teams and, on the other hand, their individual degree of accountability in a team. In this context, accountability is understood as being responsible for failing to deliver a task that a team was allocated and able to fulfil. To that end, the semantic (strategic reasoning) machinery of the Alternating-time Temporal Logic (ATL) is a natural modelling approach as it captures the temporal, strategic, and coalitional dynamics of the notion of accountability. This allows focusing on the main problem on: “Who is accountable for an unfulfilled task in multiagent teams: when, why, and to what extent?” We apply ATL-based semantics to define accountability in multiagent teams and develop a fair and computationally feasible procedure for ascribing a degree of accountability to involved agents in accountable teams. Our main results are on decidability, fairness properties, and computational complexity of the presented accountability ascription methods in multiagent teams.
Causal feature learning for utility-maximizing agents

Discovering high-level causal relations from low-level data is an important and challenging problem that comes up frequently in the natural and social sciences. In a series of papers, Chalupka et al. (2015, 2016a, 2016b, 2017) develop a procedure for causal feature learning (CFL) in an effort to automate this task. We argue that CFL does not recommend coarsening in cases where pragmatic considerations rule in favor of it, and recommends coarsening in cases where pragmatic considerations rule against it. We propose a new technique, pragmatic causal feature learning (PCFL), which extends the original CFL algorithm in useful and intuitive ways. We show that PCFL has the same attractive measure-theoretic properties as the original CFL algorithm. We compare the performance of both methods through theoretical analysis and experiments.
Leadership Qualities of Students - As an Integral Part of A Developed Personality, in Their Organizational Activities

The article deals with the importance of leadership qualities in the formation and formation of a fully developed competitive personality
PageRank–Based Extractive Text Summarization

At present text summarization is one of the important aspects of data science. As the bulk of data is available on the Internet, also the number of web pages is available for the same. Most of the time we find that with irrelevant data sometimes fraudulent data is also available. Fraudulent data may be identifiable when going through whole documents of that web page, but the effort results in a waste of time and money. To overcome these problems, text summarization is a robust solution. PageRank is one of the efficient algorithms for text summarization. By considering the vector matrix, we can verify which page is important. For the same, we used a mathematical model for calculating iteration and find the best score of pages.
Research Guides: Education: Educational Leadership

Guide to research in education, including early childhood, elementary, secondary, and higher education.
A New Algorithm for Equivalence of Cyclic Codes and Its Applications

Cyclic codes are among the most important families of codes in coding theory for both theoretical and practical reasons. Despite their prominence and intensive research on cyclic codes for over a half century, there are still open problems related to cyclic codes. In this work, we use recent results on the equivalence of cyclic codes to create a more efficient algorithm to partition cyclic codes by equivalence based on cyclotomic cosets. This algorithm is then implemented to carry out computer searches for both cyclic codes and quasi-cyclic (QC) codes with good parameters. We also generalize these results to repeated-root cases. We have found several new linear codes that are cyclic or QC as an application of the new approach, as well as more desirable constructions for linear codes with best known parameters. With the additional new codes obtained through standard constructions, we have found a total of 14 new linear codes.
Effectiveness of Organizational Culture on Teacher Performance at Secondary School Level in Khyber Pakhtunkhwa Pakistan

School culture plays an important role in the success of a school. The purpose of the study was to find out the effectiveness of school culture on teachers performance at secondary schools of Khyber Pakhtunkhwa, Pakistan. It was quantitative study. The research design of the study was co-relational and survey type. Population of the study comprised of 197 secondary schools of District Malakand, Khyber Pakhtunkhwa. Population of the study includes all the 197 secondary schools principals (public =78, private =119) and the 10th grade students enrolled in these schools for the academic year 2015-16, of District Malakand. To reduce the sampling error a representative sample were selected. Stratified random sampling technique was used to select 60% of secondary schools to get their principal perception. The homogenous purposive sampling technique was used to select four students from each selected school. Therefore sample for this quantitative study was 118 principals (public=47, private = 71) and 482students (public =188, private =284) of class ten. SPSS (Version, 21) was used to analyze data using mean, standard deviation, Pearson correlation, multiple regression and t-test statistics.
Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering.

We introduce multi-goal multi agent path finding (MG-MAPF) which generalizes the standard discrete multi-agent path finding (MAPF) problem. While the task in MAPF is to navigate agents in an undirected graph from their starting vertices to one individual goal vertex per agent, MG-MAPF assigns each agent multiple goal vertices and the task is to visit each of them at least once. Solving MG-MAPF not only requires finding collision free paths for individual agents but also determining the order of visiting agent's goal vertices so that common objectives like the sum-of-costs are optimized.
Real Santorini 1:1 V3.1

High definition 4k images To install, create a new profile by selecting “Sant_Pir_Kor.mbd”. Drive on the real, challenging roads of the ...
Improving abstraction through Python programming in undergraduate computer science and math classes

Stenger et al. [8] developed an instructional model that can be applied in any STEM classroom to use computer programming to explore the essential characteristics of a math or science concept and t...
Research of Checking the Pulse and Temperature of Higher Education Based on the BP Neural Network Prediction Model

This paper discusses the path to achieve high-quality development of higher education, which is conducive to improving the overall quality of higher education and the level of sustain able development. First of all, according to the collected data and the current higher education system of various countries, a perfect evaluation index system of higher education development health level is established. Then the AHP-NBM-fuzzy comprehensive evaluation (ANFCE) model is established. The BP neural network prediction model based on genetic algorithm optimization is established. The process of China's transition from the current state to the proposed state is simulated, and the corresponding schedule is given in Table 8. The result shows that China can reach the ideal health level by 2048, with a score of 4.1043. Then, the stability of the model is analyzed, and the results show that the model has a certain stability.
Anomaly Detection of Budgetary Allocations Using Machine-Learning-Based Techniques

In Nigeria, a crucial responsibility of the executive arms of the government is to submit annual budgetary allocations to the national assembly for approval. Due to the diversity and complexity of the budget, the national assembly is mandated to carry out its constitutional duty of scrutinizing the budget to discover irregularity or anomaly, make recommendations, or substantial modification upon what it received. This is very challenging, particularly in Nigeria where there are many different ethnicities and regional, to ensure inclusiveness, the national assembly must carry out its constitutional duty diligently and carefully without fear or favor that often has unintended consequences. This might not be very easy to accomplish within a short period. Thus, this research aims at detecting an anomaly in the budget that will ease the legislative duty thereby facilitating the process of appropriation. The concept of Clustering for Machine learning technique was used for the detection of an anomaly, where the detected ones are noted and indicated for critical examination.
National University Online Radio Using Shoutcast in Radio Laboratory Work Unit: National University Online Radio Using Shoutcast in Radio Laboratory Work Unit

Today's technological developments, where work can take advantage of existing technologies. Radio is a sound-shaped source of information and nowadays radio has evolved so that it can be accessed through the Internet with streaming media. Streaming radio is not a new technology, but this streaming app is widely implemented by many people. There is a lack of physical radio media among the limited range of broadcasts in an area, limited reach due to weak transmitter frequencies in the area. From the limited range it gives birth to an idea to be able to listen to your favorite radio broadcast anytime and anywhere by utilizing the development of Internet technology as a technique in data compression. In addition, the development of Radio Streaming Media in Indonesia has experienced an increase in which Radio Streaming users from time to time are increasing including application on campus-both public and private campuses. Based on the background that has been outlined, the author will build a Streaming Radio system on the campus of the National University with the Shoutcast method. The results are done by some testers that 93% of online radios can provide up-to-date information, media chats and media requests for listeners and online radios can be accessed well by various users using Internet media via desktop or mobile phone.
LBCC LibGuides: School of Career Technical Education: LAW

This guide highlights the course- and discipline-specific guides for the offerings in the School of Career Technical Educations. In each guide you will find the methods for finding books and other resources curated by the LBCC Librarians.
Environment Shift Games: Are Multiple Agents the Solution, and not the Problem, to Non-Stationarity?

Machine learning and artificial intelligence models that interact with and in an environment will unavoidably have impact on this environment and change it. This is often a problem as many methods do not anticipate such a change in the environment and thus may start acting sub-optimally. Although efforts are made to deal with this problem, we believe that a lot of potential is unused. Driven by the recent success of predictive machine learning, we believe that in many scenarios one can predict when and how a change in the environment will occur. In this paper we introduce a blueprint that intimately connects this idea to the multiagent setting, showing that the multiagent community has a pivotal role to play in addressing the challenging problem of changing environments.
Student Needs for Developing E-Book for Teaching Speaking Skills for Young Learners

In the Curriculum 2013, English is excluded from the Elementary School Subjects, especially for the State Elementary Schools. The English teachers found difficulty in providing a textbook that covers the student needs. Fortunately, in this pandemic covid-19, it is easier in the teaching and learning process by using electronic books or E-Book. This study aimed to find out the student needs to be able to develop an E-Book for teaching speaking skills for the fourth grade of elementary school students. This research’s respondents were four English elementary school teachers in Palangka Raya and 30 students of the fourth grade of Elementary School at SDN 11 Langkai. This research was done to do the first step of the design of Research and Development (R&D) based on ADDIE (need analysis, design, development, implementation, and evaluation) as proposed by Branch (2009) elaborated with local content in Palangka Raya. The instrument applied was a guided interview. The data obtained were analyzed and described qualitatively. The finding showed that there were positive responses from the result of the interview. Then, the findings become basic for the researcher to develop E-Book for teaching English speaking skills.
Vision-Based Motion Planning of Cable-Driven Parallel Robots in the Presence of Moving Obstacle Using Sampling-Based Method

Abstract In the past decades, cable-driven parallel robots (CDPRs) have been proven the extraordinary performance for various applications. However, the multiple cables lead the robot easy to interfere with environments. Especially the large workspace of CDPR may introduce unknown moving obstacles. In this study, a sampling-based path planning method is presented for a CDPR to find the collision-free path in the presence of the moving obstacle. The suggested method is based on rapidly exploring random tree (RRT) algorithm which gives CDPRs advantages to handle complex constraints such as cable collision and dynamic feasible workspace (DFW). Moreover, we conduct the forward simulation to check the feasibility in a closed-loop system. The moving parts of both CDPRs and the moving obstacle are assumed as convex bodies, so that Gilbert-Johnson-Keerthi (GJK) algorithm is adopted to detect collision in real-time. Finally, the related simulation is carried out to illustrate the algorithm. The experiment is also presented using the drone as a moving obstacle and YOLO vision algorithm to detect the drone. The experiment results demonstrate the reliability of the suggested method.
QUANTUM CODES OBTAINED THROUGH -CONSTACYCLIC CODES OVER

The structural properties and construction of quantum codes over  using Constacyclic codes over the finite commutative non-chain ring  = where  are the focus of htis paperand  is field having  elements with characteristic p where p is an prime such that . A Gray map is defined between  and . Decomposing constacyclic codes into cyclic and negacyclic codes over  yields the parameters of quantum codes over . Some examples of quantum codes of arbitrary length are also obtained as an application.
Supporting Users in Review and Analysis of Academic Literature

Today, information search and retrieval tools are ubiquitous and powerful. However, there is comparably little investment in helping users with analysis of materials found via search. This paper introduces a software tool designed to help individuals and teams improve their ability to examine and to use the results of search. The existing tool focuses on literature review and analysis and emphasizes support for users who are building an initial mental model of a domain new to them. The paper describe rationales and goals for helping users perform literature searches, current implementation and features, preliminary user feedback, and future work.
Digitization of Library: Beginning of New Era for Indian Libraries.

This paper discusses the new activities, purpose, function, and different stages used in digitizing documents and the formation of digital libraries. Due to the globalization of information and territorial boundaries are becoming meaningless. The Majority of libraries are getting converted into digital libraries with the availability of different digital library management software which helps to fulfill their users' basic objectives of providing relevant information. This paper ends by discussing the major role of librarians towards library digitization and maximizing effectiveness and how this beginning of a new era changes the whole concept of traditional libraries.
LibGuides: Staff Recommended Reading Lists: Winter 2020-2021

This guides contains staff recommended reading lists posted on the Library's social media accounts.
An Efficient Cervical Whole Slide Image Analysis Framework Based on Multi-scale Semantic and Spatial Features using Deep Learning.

Digital gigapixel whole slide image (WSI) is widely used in clinicaldiagnosis, and automated WSI analysis is key for computer-aided diagnosis.Currently, analyzing the integrated descriptor of probabilities or feature mapsfrom massive local patches encoded by ResNet classifier is the main manner forWSI-level prediction. Feature representations of the sparse and tiny lesioncells in cervical slides, however, are still challengeable for theunder-promoted upstream encoders, while the unused spatial representations ofcervical cells are the available features to supply the semantics analysis. Aswell as patches sampling with overlap and repetitive processing incur theinefficiency and the unpredictable side effect. This study designs a novelinline connection network (InCNet) by enriching the multi-scale connectivity tobuild the lightweight model named You Only Look Cytopathology Once (YOLCO) withthe additional supervision of spatial information. The proposed model allowsthe input size enlarged to megapixel that can stitch the WSI without anyoverlap by the average repeats decreased from $10^3\sim10^4$ to $10^1\sim10^2$for collecting features and predictions at two scales. Based on Transformer forclassifying the integrated multi-scale multi-task features, the experimentalresults appear $0.872$ AUC score better and $2.51\times$ faster than the bestconventional method in WSI classification on multicohort datasets of 2,019slides from four scanning devices.