Reviewerly/exHarmony huggingface dataset:
statsExpressions: R Package for Tidy Dataframes and Expressions with Statistical Details

The `statsExpressions` package is designed to facilitate producing dataframes with rich statistical details for the most common types of statistical approaches and tests: parametric,nonparametric, robust, and Bayesian t-test, one-way ANOVA, correlation analyses, contingency table analyses, and meta-analyses. The functions are pipe-friendly and provide a consistent syntax to work with tidy data. These dataframes additionally contain expressions with statistical details, and can be used in graphing packages to display these details.
The Molecular Basis of Neural Memory. Part 7 Neural Intelligence (NI) versus Artificial Intelligence (AI)

A memorium to my late wife and fan, the artist Georgette Batlle , for kindly receiving my discourses on the chemical basis of thought.Thanks to friends, Lilly Rivlin (New York, NY) and the late Bill Needle www.videleaf.com(Eastchester, NY) for their early encouragement and financial support in the period 1980-1984.I appreciate ongoing discussions with Karine Ahouva Leopold (Paris), about feelings and emotions.-By GM The references presented in previous Parts of this series, are also appropriate here.In the interest of space, many works have not been cited again, though they all contribute to the knowledge base of neurobiology and cognitive sciences.Those cited below were chosen to establish particular points of fact.We stand on their shoulders, to glimpse vistas of neural memory and intelligence. Conflict of Interest:GM is a founder of MX Biotech Ltd., with the commercial goal to develop new classes of "memory materials" and devices.CG is emeritus professor of Chemistry at Hebrew University (Jerusalem), active in developing and patenting peptide-based tools for surgery and pharmacology.Notwithstanding, the ideas
A Future Solution for Block chain Based Distributed Electronic Health Record Data with Confidentiality and Security using Blake2b

A blockchain is a shared, public register, storing business transactions and outlining assets, and of which immutable in nature. Globally Electronic Health Record (EHR) market is swiftly rising. Due to this swift growth of the EHR market worth is predictable to be $50 billion in 2025. Blockchain will revolutionize in the medical field, to store medical historical records in a tamper proof, secure, and more reliable in the effective diagnosis and treatment in the real-time medical data. Health care data it can be twisted copied and modified faster than ever before and if the data is the critical thing behind more efficient care block chain may be the medium to get us there, currently the medical organizations are being ruined because of poor data integration. Our project consists of Drug description, Data Security, Huge Data, cloud. Once the data is entered the data goes to the block and links to the chain. We are using blake2b, because blake2b is much faster and has less rounds compared with the blake. Blake2b is about 30 percent faster than the blake. The data is finally transferred to the Json file to compact and easy to transfer in nature. We similarly converse the privileges of blockchain, along with the tests tackled and future viewpoints. Execution measurements in blockchain systems, for example, latency, throughput, Round Trip Time (RTT), has been advanced for achieving upgraded results. Contrasted with customary EHR frameworks, which use customer server design, the proposed framework utilizes blockchain for improving proficiency and security.
MICROFACIES ANALYSIS AND BASIN DEVELOPMENT OF THE CENOMANIAN - EARLY TURONIAN SEQUENCE IN THE RAFAI, NOOR AND HALFAYA OIL FIELDS, SOUTHEASTERN IRAQ

&nbsp;&nbsp;&nbsp; The stratigraphic sequence of Cenomanian-Early Turonian is composed of Ahmadi, Rumaila, and Mishrif formations in the Rifai, Noor and Halfaya Oil Fields within the Mesopotamian Zone of Iraq, which is bounded at top and bottom by unconformity surfaces. The microfacies analysis of the study wells assisted the recognition of five main environments (open marine, basinal, shallow open marine, Rudist biostrome, and lagoon); these microfacies were indicative of a normal lateral change facies from shallow water facies to deeper water and open marine sediments. &nbsp; &nbsp;&nbsp; &nbsp;Ahmadi Formation (Early Cenomanian) is characterized by open marine sediments during the transgressive conditions, and would become deep basinal environment upward to deposition the Rumaila Formation. Rumaila Formation (Middle Cenomanian) was deposited in the deeper part of the intrashelf basin; it comprises basinal sediments mainly, and includes an abundant of open marine fauna supportive of Middle Cenomanian age. Rumaila Formation is represented as time equivalent basin to the Mishrif Formation, where they were deposited during highest and system tract (HST). The Cenomanian- Early Turonian sequence can be subdivided into three cycles displaying coarsening upward cycles :Mishrif A, Mishrif B, and Mishrif C; which comprises a highest and system tract dominated by rudistid packstone to grainstone or rudistid biostrome facies separated by transgressive units (CR I and CR II).
Research on Road Traffic Fatal Accidents using Data Mining Techniques

Road safety plays a major role in our day-to-day life and also transportation system, due to its priority, it has become the major concern for everyone. In order to increase the road safety, traffic rules are included in education, clear and careful predictive analysis and study is done on factors effecting fatal accidents. We apply predictive analysis, statistical analysis and some algorithms related to data mining which includes FARS such as Apriori algorithm, associative rule techniques are used. These methods help in encountering the road fatal accidents that cause due to mentioned factors. These factors may include climatic and surface conditions and also drunken drivers or may be condition of vehicles also. Clusters are formed using simple k-means clustering algorithms. Finally road safety driving rules are made based on the factors effecting, clusters formed and predictive analysis and prior information.
Chaotic Creations

Chaotic Creations is a Windows application aimed toward Dungeon Masters of the fifth edition of Dungeons and Dragons. It includes a dice roller visual, a database of random-selection tables, as well as tools for generating non-player characters, encounters, and terrains. The application is built using Windows Presentation Foundation (WPF) with C# being used for the back end and XAML used for the front end. SQLite was used for database creation and management. The motivation for this project is to help Dungeon Masters be able to improvise during gameplay more effectively.
Conditional Mixture Model and Its Application for Regression Model

Expectation maximization (EM) algorithm is a powerful mathematical tool for estimating statistical parameter when data sample contains hidden part and observed part. EM is applied to learn finite mixture model in which the whole distribution of observed variable is finite sum of partial distributions. Coverage ratio of every partial distribution is specified by the probability of hidden variable. An application of mixture model is soft clustering in which cluster is modeled by hidden variable whereas each data point can be assigned to more than one cluster and degree of such assignment is represented by the probability of hidden variable. However, such probability in traditional mixture model is simplified as a parameter, which can cause loss of valuable information. Therefore, in this research I propose a so-called conditional mixture model (CMM) in which the probability of hidden variable is modeled as a full probabilistic density function (PDF) that owns individual parameter. CMM aims to improve power of mixture model. I also propose an application of CMM which is called adaptive regressive model (ARM). Traditional regression model is effective when data sample is scattered equally. If data points are grouped into clusters, regression model tries to learn a unified regression function which goes through all data points. Obviously, such unified function is not effective to evaluate response variable based on grouped data points. The concept &amp;ldquo;adaptive&amp;rdquo; of ARM means that ARM solves the ineffectiveness problem by selecting the best cluster of data points firstly and then evaluating response variable within such best cluster. In order words, ARM reduces estimation space of regression model so as to gain high accuracy in calculation.
What's Next? An Exploration of the Next Phase in Access to Electronic Information

What online features would users like to have in the next phase of access to electronic information? What other content, besides journals, do users want to access online? This workshop discussed features such as profiling, threading, and advanced search capabilities that will enhance online access for users. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-342-9678. E-mail address: getinfo@haworth.com]
The Curved Space-Time Paradox

The fundamental principle in General Relativity is to combine the inertia of mass and the relationship with the gravity force acting on this mass. In this article a new concept in General Relativity will be introduced. The concept of the “Paradox in a Curved Space-Time Continuum”. The “Paradox in a Curved Space-Time Continuum” has been based on the fundamental question: Does light follow a curved path within a gravitational field because a gravitational field causes a “Curved Space Time Continuum” or does a curved path of a beam of light generate a Gravitational Field. Differently formulated: Is Gravity a second order effect of a curved Electromagnetic field?To answer this question a new theory will be introduced. The “Quantum Light Theory” which is a specialization of “Quantum Field Theory”.Quantum Light Theory (QLT) is the new development in Quantum Field Theory (QFT). In Quantum Field Theory, the fundamental interaction fields are replacing the concept of elementary particles in Classical Quantum Mechanics. In Quantum Light Theory the fundamental interaction fields are being replaced by One Single Field. The Electromagnetic Field, generally well known as Light. In which gravity is the second order effect of the fundamental Electromagnetic Field. To realize this theoretical concept, the fundamental theory has to go back in time 300 years, the time of Isaac Newton to follow a different path in development. Nowadays experiments question more and more the fundamental concepts in Quantum Field Theory and Classical Quantum Mechanics. The publication “Operational Resource Theory of Imaginarity“ in “Physical Review Letters” in 2021 (Ref. [2]) presenting the first experimental evidence for the measurability of “Quantum Mechanical Imaginarity” directly leads to the fundamental question in this experiment: How is it possible to measure the imaginary part of “Quantum Physical Probability Waves”? This publication provides an unambiguously answer to this fundamental question in Physics, based on the fundamental “Gravitational Electromagnetic Interaction” force densities. The “Quantum Light Theory” presents a new “Gravitational-Electromagnetic Equation” describing Electromagnetic Field Configurations which are simultaneously the Mathematical Solutions for the Quantum Mechanical “Schrodinger Wave Equation” and more exactly the Mathematical Solutions for the “Relativistic Quantum Mechanical Dirac Equation”. The Mathematical Solutions for the “Gravitational-Electromagnetic Equation” carry Mass, Electric Charge and Magnetic Spin at discrete values.
Factors Influencing Research Productivity of Private Higher Education Institutions Lecturers in Kopertis Region XII Maluku and North Maluku

A researcher is said to be productive after publishing their findings. The analysis of the Science and Technology Index portal, called SINTA, shows the productivity of researches of private higher education institutions lecturers in Kopertis Region XII Maluku and North Maluku is still very low. The ranking of private higher education institutions in Kopertis Region XII compared with other universities in Indonesia further strengthens the opinion. This research aimed to determine the factors influencing the research productivity of private higher education institutions lecturers in Kopertis Region XII. The method used was an online survey on 155 samples of lecturers in Maluku and North Maluku. The data obtained were analyzed statistically descriptive. The results showed that research productivity is influenced by individual and institutional factors. Individually, the biggest driving factor is the perception of the function and benefits of research for human life, while the smallest one is the desires to be famous and financial benefits. The biggest inhibiting factor is the limited cost of research and publication, while the smallest is the motivation to research and publish. Institutionally, library facilities are deemed inadequate, thus contributing less to the increase of research productivity.
George A. Beauchamp

His book titled Curriculum Theory, which discusses curriculum theory that adheres to the resultsof research. The entire contents of this book are divided into three parts. The first part discussescurriculum theory which is a sub-theory of education: curriculum theory as an educationalproblem, theory formation, theory in education, curriculum theory. The next section outlines ananalysis of theoretical issues, problems, and alternative solutions to problems in curriculumdevelopment. The last section presents curriculum theory as a result of the writer's owndevelopment/thinking, mainly focused on the curriculum as a field of study of curriculum theory.
Professionalization Processes in the Context of Modernization of the Social Structure of Russian Society

The object of abcomprehensive interdisciplinary research (Sociology, Economics, History, Psychology, Pedagogy, Management, Law, etc.) is about study the problems of social adaptation and functioning of various professional groups in the process of modernizing the social structure of Russian society and impact of social processes on their viability. The relevance of the research is due to the rapidly changing and increasingly complex processes of forming the professional structure of Russian society under the influence of external factors (instability of the world socio-political systems, the crisis of the world economy, the prospects for resolving contradictions between global and national ways of development of States, Informatization and digitalization of social communications, the increase in conflicts of interests between subjects of the labor process) and internal factors (features of the modern national labor market, disproportionality of the distribution of productive forces on the territory of Russia, demographic problems; changes in the motivational vector of the choice of professional trajectory of young people, ineffective reform of the system of secondary and higher education). The work carried out in 2019 is devoted to the study of changes in status positions and the implementation of cultural, political and educational capital by representatives of the engineering, pedagogical, medical community, environmentalists and online specialists in the context of changes in the social structure of abmodernizing society. The most significant areas of activity were: assessment of the quality and prospective role of engineering education as abtechnological basis for the effectiveness of modernization processes in the economy; considering proforientation events as part of government policy in abperspective of staffing modernization processes; analysis of the role of Informatization of computerization and digitalization as the realities of the developing information society, shaping new relations of production and specifics of communication in society at all stages of formation or extinction of occupational groups. The results of the research deserve the attention of specialists who study the social structure of society, can be useful for preparing abcourse of lectures on the sociology of professions and professional groups, as well as for managers at various levels involved in education, labor relations and information technology.
Malayalam Error Sentence Detection using Deep Learning with RNN-LSTM

Malayalam is a difficult Indian language and not easy for foreigners. Even as a mother tongue, you should spend more time learning as a child. In Malayalam, the use of the wrong word in a sentence may change the whole meaning and purpose. Many errors occur during the writing process. It is very difficult to find errors in the Malayalam language, and no one can remove those errors without their linguistic knowledge In this paper, we have proposed the structure of repetitive neural networks using long short-term memory (RNN-LSSTM) to detect Malayalam sentence errors.
QuickStart UIkit

UIkit is a lightweight web design framework with modular components that help you rapidly design robust user interfaces. It comes with a slew of ready-to-use elements like cards, buttons, and navigation helpers among other power-packed utilities to build clean and fully functional web pages. Responsive by default, it removes the guesswork out of developing mobile-friendly layouts in a minimalistic way. The set of tools that is ingrained in this front-end framework is quite simple to use, customize, and extend. It enables you to create consistent feature-rich sites, without the bloat or clutter associated with popular heavyweight frameworks like Bootstrap and Foundation.
Deep Learning Based Data Fusion for Sensor Fault Diagnosis and Tolerance in Autonomous Vehicles

Abstract Environmental perception is one of the key technologies to realize autonomous vehicles. Autonomous vehicles are often equipped with multiple sensors to form a multi-source environmental perception system. Those sensors are very sensitive to light or background conditions, which will introduce a variety of global and local fault signals that bring great safety risks to autonomous driving system during long-term running. In this paper, a real-time data fusion network with fault diagnosis and fault tolerance mechanism is designed. By introducing prior features to realize the lightweight of the backbone network, the features of the input data can be extracted in real time accurately. Through the temporal and spatial correlation between sensor data, the sensor redundancy is utilized to diagnose the local and global condence of sensor data in real time, eliminate the fault data, and ensure the accuracy and reliability of data fusion. Experiments show that the network achieves the state-of-the-art results in speed and accuracy, and can accurately detect the location of the target when some sensors are out of focus or out of order.
Bayesian Networks: Learning

This chapter gives an introduction to learning Bayesian networks including both, parameter and structure learning. Parameter learning includes how to handle uncertainty in the parameters and missing data; it also includes the basic discretization techniques. After describing the techniques for learning tree and polytree BNs, the two main types of methods for structure learning are described: score and search, and independence tests. We then describe how to combine expert knowledge and data. The chapter concludes with two application examples, one in the area of pollution modeling and other for agricultural planning.
DESIGN AND DEVELOPMENT OF TALKING BRAILLE CALCULATOR.

This research focused on the design and development of a Talking Braille Calculator.More specifically, the following were the objectives of the study: specify the technology requirements needed for the development of a Talking Braille Calculator; test the Talking Braille Calculator in terms of its responsiveness, synchronization and accuracy and evaluate the Talking Braille Calculator in terms of effectiveness.The Talking Braille Calculator was developed to help the visuallyimpaired students to study and SPED teachers to teach the four Mathematical operations with the implementation of Braille Writing system.It was set to provide an advanced tool for the visually-impaired students and teachers of Santa Cruz Central Elementary School (SCES), Sta.Cruz, Laguna.The design of the Talking Braille Calculator used the idea of the conventional calculators with the implementation of Nemeth codes programmed in order to mount the answer through the braille pins attached to the device using a servo motor.The keys, buttons and braille pins can talk when pressed using the pre-recorded voice installed into the voice module.The research resulted to use C Programming Language to program the PIC microcontroller that controls the whole device including the voice module and the servo motor.It can process a whole operation in 13.05 sec.which consist of four digits, and one operator pressed with the result matching the pre-recorded voice and the display.The device obtained 4.903 weighted mean average interpreted as Highly Acceptable evaluated by the visually-impaired students.Copy Right, IJAR,
European national news

Issues regarding the authenticity and integrity of electronic evidence have plagued judges worldwide. From a statistical viewpoint, the main cause of the judicial puzzle in dealing with electronic evidence lies in its special physical properties and judges' lack of necessary expertise. With its technical development and widespread application, blockchain technology is showing significant power and is gradually supplanting judges and expert witnesses, who have played a central role in the identification of electronic evidence's authenticity and integrity. In two recent cases, Chinese courts have confirmed for the first time that electronic data stored on or generated by blockchain met the requirements of authenticity and integrity and proposed a specific procedural test to identify blockchain evidence. Although blockchain technology may revolutionise the rules of evidence, it contains inherent risks. Its application in electronic evidence may also indicate the fusion between decentralised technology and the traditional, centralised juridical mechanisms.
Cognitive Inductive Prejudice For Corporal Edifice In Hominids And Contraption

A strong and insightful interpretation of scientific knowledge and practice must take into consideration how human cognitive skills and constraints enable as well restrict the scientific enterprise's activities and products. While existing deep learning systems are outstanding in functions such as object classification, language processing, and gameplay but few can create or transform a complex system like a Frame Pyramid. Assume that what these systems lack is a "Cognitive Inductive Prejudice": an ability to justify inter-object relationships and make decisions about an organized description of the incident. In order to assess this premise, this paper concentrated on a work involving stapling together stacks of frames to balance a castle and quantify how well hominids are doing. Then for analyzing contraption capability, our work introduce the Significant Stimulus Learning Tool that utilizes object-and interactioncentered scene and policy representations, these apply to the task. Our results shows that these structural portrayals enable the tool to perform both hominids and contraption for more naive methods, indicating that cognitive inductive effect is a significant element in solving structured reasoning issues and building more intelligent also flexible for machines.