Reviewerly/exHarmony huggingface dataset:
An Ontology-Driven Structured Processing Method for History of Present Illness of Discharge Summary

The history of present illness in the discharge summary is one of the important components of these medical data resources. It records the health status of inpatients and the treatment process, which contains a wealth of medical knowledge. However, the present illness history in discharge summary is often recorded in narrative medical text, which is an unstructured text format. It is difficult to directly apply machine learning or deep learning models for data mining and analysis, which hinders the reuse of medical data. In this paper, the history of present illness data in the discharge summary provided by a 3A grade hospital in Shanghai is researched, and an ontology-driven method of structuring the present illness history in the discharge summary is proposed. Specifically, this method first builds a professional medical dictionary to improve the accuracy of word segmentation, and to ensure the quality of the ontology and the effect of text structuring. Then, based on dictionary matching, a method of constructing the ontology of the history of present illness in the discharge summary is proposed. Finally, based on regular expressions and heuristic rules, an ontology-driven method of structuring the history of present illness in the discharge summary is proposed. Through comparative experiments, the validity and accuracy of this method are verified.
NATURAL LANGUAGE PROCESSING AND ITS EFFECTS ON SOCIETY AS A WHOLE: A SURVEY

Over the past 25 years, computational linguistics has grown to become both an interesting area of scientific research and upcoming technology that is increasingly being put into consumer products (for example, applications such as Apple’s Siri, Microsoft Cortana or Skype). There are main four key factors that are the driving force behind these developments: (i) an immense increase in computing power, (ii) the availability of huge amounts of linguistic data, (iii) the development of highly effective machine learning (ML) methods, and (iv)a more enriched understanding of the structure of human language and its application in social contexts.[2] Natural language processing (NLP) is the branch of Artificial Intelligence (AI) that deals with communication: How can a computer be programmed to understand, process, and generate language just like a human being? With the increasing use of the Web and other text application areas, there has been an increasing demand in both text mining and natural language processing (NLP). The main goal of Natural Language Processing (NLP) is to implement within computers the skill set required to understand a normal human language or natural language. It is related to the field of HCI ie. Human-Computer Interaction. One of the motivations of NLP is for the society whose access to web information is blocked simply by their inability to use the keyboard and OS. Natural language comes under the purview of AI with the goal of understanding and recreating meaningful expressions in human language. AI is the ability of a machine to imitate intelligent human behavior. This paper presents a survey on Natural language processing (NLP) and its effects on society as a whole. Here I talk about sentiment analysis which has a long-term effect on society. I also talk about social media mining which results in a huge amount of structured social information which is extremely important in the predictive analytics industry also. Then I discuss the future scope of NLP in the society.
Anomaly Detection using Machine Learning: A Rule Based Classification and Ordered Regression Tree with Real Time Datasets

What we use the protection of system data and user credentials is still very dispensable presently in factual applications frequently used by common people. Also losing their assets and confidence level due to lack of knowledge about usage of applications and failure to grab the abnormal behavior. How system data and user credentials are helpful to creating clone by others causes of showing anomalous behavior and don’t know to protect from the anomalies and how it is avoid. In this paper we are presenting short-lived discussion on anomaly detection and its nature of impact showing on original true datasets related to daily land transactions, medical and social networking. This paper shows the significant usage of machine learning approach applied in anomaly detection to know the fact anomalies in various datasets took from different sources. Here we are using an updated CART called Rule based Classification and Ordered Regression Tree (RBT-ORT). This method is new one with combination of Decision Tree; Rules of Random Tree giving a new adorned rule sets in classification and regression to ensure the improvement in results compare to other techniques. Our work carried out on three datasets, two are taken from UCI repository for machine learning and other one is real and original dataset Land sale data pertaining to land transactions noted in the year 2016-18. Finally the results of anomaly detection using Classification and Ordered Regression Tree compare with other machine learning methods such as ID3, C4.5, C-RT, PLSDA, CHAID, C4.5 Rule, I (Improved) - C4.5, K-Nearest neighbor and Neural Networks.
Entanglement

Entanglement is an essential feature of quantum mechanics. If two systems are entangled, there are not individual quantum states describing each system, only a global state describing both. Systems that are entangled can exhibit strong correlations, and it is possible to make use of those correlations in quantum communication protocols. In this chapter we will describe how entangled states can be used to violate Bell inequalities, and thereby show that the world is not described by local hidden-variable theories. We will then show how entanglement can be detected and measured and then describe two communication protocols, teleportation and dense coding, in which it is essential.
Congratulations to the Global Learning XPRIZE Grand Prize Winners

Two Teams Recognized for Developing Effective, Scalable Learning Software for Children Around the World
Multi-dimensional constraints analysis in Viet Nam

The multi-dimensional analysis identifies constraints to Viet Nam’s development along the Sustainable Development Goals. To improve people’s quality of life and opportunities, access to upper-secondary education and more sophisticated skills has to improve, together with coverage of social protection and health system. Boosting productivity requires enhancing the macroeconomic policy framework, tackling inefficiencies in the state sector, handling large pockets of low-productivity firms, and promoting integration between domestic and foreign firms. Global and domestic challenges call for fiscal policies and financial reforms to mobilise private resources. Building capacity of the public administration and building predictability around the legislative process should create a more conducive business environment, ensure effective implementation and re-establish trust in institutions. Finally, a more efficient use of natural resources and horizontal management of impact from natural hazards are required to bring Viet Nam back on a sustainable growth path.
PEMETAAN TATA KELOLA TI DAN ANALISA FAKTOR PENGHAMBATNYA : STUDI KASUS PT BANK DNM, TBK

Fulfillment of the provision of accurate information and timely in the use, management, effectiveness and responsibility in the banking sector is a must.As a high industry regulation, then needed a good Governance to all sectors including in the field of information technology (it), particularly in the implementation of the principles of Good Corporate Governance.Research using the framework IT Governance as a method of analysis, namely: structure, process, the mechanisms of the relationship; Weill &amp; Ross; ITGI; and AS8015.Then the mapping of the results obtained will be formulated problems facing Banks DNM in it governance.The formulation of the problem is then mapped into a Fishbone Analysis solution is given and try using COBIT 4.1 Best Practice.From the results of this research are expected to Bank DNM can enhance the fulfillment of their needs in terms of information provision to support the implementation of the tasks and functions in the banking sector.
New Rules

As the preceding chapters demonstrate, existing norms, suitably interpreted, are able to deal with many of the challenges presented by AI. But not all. This chapter begins with a survey of guides, frameworks, and principles put forward by states, industry, and intergovernmental organizations. These diverse efforts have led to a broad consensus on half a dozen norms that might govern AI. Far less energy has gone into determining how these might be implemented – or if they are even necessary. Rather than contribute to norm proliferation, the chapter focuses on why regulation is necessary, when regulatory changes should be made, and how it would work in practice. Two specific areas for law reform address the weaponization and the victimization of AI. Regulations aimed at general AI are particularly difficult in that they confront many ‘unknown unknowns’, but uncontrollable or uncontainable AI could pose a threat far more serious than lethal autonomous weapon systems. Additionally, however, there will be a need to prohibit some conduct in which increasingly lifelike machines are the victims – comparable, perhaps, to animal cruelty laws.
Mastermind

This chapter describes Mastermind in the sense of a game-theoretic model. Mastermind is a nonrandom two-person zero-sum game without perfect information, but with perfect recall. The encoder has a single decision to make, at the start of the game, associated with a single one-element information set. The game of 32 Mastermind, with its nine codes 11,12,13,21,22,23,31,32,33, permits 3! = 6 exchanges of colors and an additional 2! = 2 exchanges of position. For calculating the minimax strategies for 32 Mastermind, one can use the techniques that used in the le Her and baccarat, where the amount of effort will be of about the same order of magnitude. How information about the minimax value of 64 Mastermind could be obtained at a significantly reduced cost over that of a complete minimax analysis was shown in 1986 by Merrill Flood. According to a 1995 newsgroup memo from Michael Wiener, the minimax value of 64 Mastermind is in fact 5600/1290 = 4.341.
Cloud Architecture

Cloud Computing is currently an essential part of network infrastructure. The U.S. National Institute for Standards and Technology has proposed defining cloud computing as a model “for enabling convenient, on-demand network access to a shared pool of configurable computing resources.” The cloud structure facilitates the user to access the real-time metadata in a quick and more efficient manner. Data uploads into a centralized data center and is distributed through the network in milliseconds.
Generating Quality Items Recommendation by Fusing Content based and Collaborative filtering

Recommendation system has become an inevitable part of our life. It has already spread its prominence in various fields like movies, music, news, article recommendations etc. Due to the influence of social media, data is streaming from all over the Internet. Collect the relevant information from chunks of data available has become much difficult. Recommender systems guides in filtering data to get the relevant information. Commonly used recommendation approaches are content based filtering and collaborative filtering. Each approach has its own limitations. The hybrid approach combines the advantages of both the approaches. In this paper, we have tried to enhance the quality of the items recommendation system by fusing both content based and collaborative filtering uniquely. The experimental results are compared with that of other traditional approach using precision and recall evaluation measure. The comparison results show that our approach has 10% better precision for top-10 recommendations than other established recommendation technique.
Aspect-Oriented Programming with Spring

AOP is the acronym for aspect-oriented programming, which refers to a type of programming that aims to increase modularity by allowing the separation of cross-cutting concerns. A cross-cutting concern is a functionality that is tangled with business code, which usually cannot be separated from the business logic. Auditing, security, and transaction management are good examples of cross-cutting concerns. They are mingled with the business code and heavily coupled with functionalities that might be affected if they fail. They are good candidates for separation using aspects, because there is no design pattern that allows writing code in such a way that it is separated from the business logic. This means that additional behavior is added to existing behavior when the application is compiled.
Disputation

Those who have coined a word that others use, or think they have, are seldom shy about making that claim. Competing assertions are therefore common. Terms with multiple claims of coinage include <italic>gonzo, software,</italic> and <italic>fashionista.</italic> Since such terms typically were circulating on the street long before someone claimed authorship, their actual etymology is vague. A coinage that has never appeared in print, or can only be found in obscure publications, is particularly susceptible to assertions of authorship by more than one person. That’s why someone’s claim to have invented a word is an unreliable source of etymology. It’s common to read that X word was coined by Y person, when in fact that word was either invented by someone else, or was already being used orally at the time it appeared in print. This is one of many reasons that determining original word authorship is so problematic.
A flexible family of hypertabastic models

Survival analysis is a major tool in cancer research, with a wide application in modeling a variety of cancer survival time data.The family of hypertabastic models includes the hypertabastic proportional hazards model and the hypertabastic accelerated failure model.The hypertabastic survival model has been applied to analysis of various types of cancer data including breast cancer, multiple myeloma, and glioma and to the analysis of non-cancer data.In the area of medical genomics, Tabatabai et al analyzed breast cancer data using clinical and multiple gene expression variables using the hypertabastic proportional hazards model and compared the results with Cox regression.Compared with Cox regression, the increase in accuracy was complemented by the capacity to analyze the time course of disease progression using the explicitly described hazard and survival functions.Recently the hypertabastic accelerated failure models have also been used to analyze mylar-polyurethane insulation data.This gives a new dimension in the application of hypertabastic survival models in biomedical settings.In his paper, we discuss the family of flexible hypertabastic models with applications in cancer.
Design Mind or Laws of Nature: Space, Vital and Social Reality

The article is devoted to the consideration of two interrelated topics: the opposition of two foundations of social action, one of which is called the ‘design mind’ by the author, and the other is known as ‘nature’, and the path of evolution, in which three types of realities arose sequentially - cosmic, vital (biological) and social. The discourse of the design mind is formed in ancient culture in the works of Plato, and the concept of nature in the works of Aristotle. The first is characterized by the predominance of ideas and patterns, as well as a belief in the possibility of their implementation. The second is characterized by considering the prevailing reality (nature) and mediating social action by knowledge of the processes of nature. The new European understanding of nature is a hybrid; it combines the Aristotelian and Platonic approaches. Nature is both actions in nature and design creation. The second difference is that the new European nature was understood as “written in the language of mathematics” and passed through experimentation. However, since the 19th century, the natural-scientific understanding of nature has been criticized and differentiated: a demarcation is made between the first and second nature, different types of realities, nature and technology. Within the framework of this process, in the course of explaining the origin of life, man and society, a diagram of the evolution of three types of realities is outlined: first, there is only cosmic reality, understood as the first nature, then comes vital reality, and then social (second nature). An assumption is introduced that the next type of reality in evolution appears as a new formation, on the one hand, as a result of development and complication, and on the other, as a number of random processes. The conditions of interaction of processes belonging to different types of reality are discussed; in this regard, the concepts of “renegade areas” and “maternal reality” are introduced. On the basis of the outlined distinctions and relationships, an explanation of the pandemic and the modern transition process from modernity to post-culture is proposed.
After the License Is Signed: Collaboration to Resolve License Breaches

SUMMARY. The purpose of the session was to explore key issues about electronic resource license breaches from the perspective of a library, publisher, and information provider. The presenters discussed how each of their organizations manage license breaches. Libraries, publishers, and information providers need to work together to continue to develop effective methods of addressing and preventing license breaches while also being sensitive to privacy issues and the need to support library users’ research needs. [Article copies available for a fee from The Haworth Document Delivery Service: 1-800-HAWORTH. E-mail address: &lt;docdelivery@haworthpress.com&gt; Website: &lt;https://www.HaworthPress.com&gt;]
Quantifying Cyberthreat for Patients, Providers, and Institutions

Cybercrime has become a ubiquitous part of modern life, almost to the point of becoming background noise. Statistically, almost every American adult has been the victim of cybercrime or is associated with someone who has. Beyond identity theft and the corresponding financial circumstances, we have seen massive cyberattacks target and disable huge portions of health systems. The largest systems have been differentially prepared but many of the small systems have not recovered. In this chapter the prevalence of cybercrime against health care is quantified in hopes that health systems and digital health innovators will understand and address the risks and potential harms that patients face when interacting with them.
Anti aging controllable true random number generator for secured AES-based crypto system

A tetrahedral oscillator-based true random number generator for secret key generation in cryptosystem has been proposed. The circuit is made to behave correctly for a long time. By applying pass transistors, the aging effects due to hot carrier injection (HCI) and negative bias temperature instability (NBTI) are reduced. This fact is helpful to achieve the goal and its performances have also been improved. Pass transistor makes the transistors to operate only at enabling times. Thus, bit flipping in normal designs are reduced. Due to the complexity in the tetrahedral oscillator hacking will be very tough. The secret key generated from TRNG circuit is adopted in advanced encryption standard (AES) cryptosystem to maintain an off-chip database. Moreover, controlling circuits for TRNG have been introduced because in any of the cryptosystem man-in-middle attack is possible. To avoid this controlling circuits are used to identify the authenticity of customers. Simulation results explain that our aging resistant design can be used for generating more reliable keys. Although the operating conditions changes, the DC operating point of the system does not change more. The randomness is also shown through NIST tests.
Preface

This proceeding consisted of peer-review papers from the First International Seminar on Civil and Environmental Engineering (ISCEE) 2020, which was organized by the Department of Civil and Environmental Engineering, in collaboration with the Center of Disaster Studies of IPB University, Department of Civil and Environmental Engineering, Ehime University, Department of Civil Engineering Halu Oleo University, and Department of Civil Engineering Padang State University on November 2 nd – 4 th , 2020. This conference expressed our concern for establishing and developing aspects related to the effective, innovative, and environmentally-friendly disaster mitigation system to develop a robust infrastructure resilient, with the topics of disaster mitigation and adaptation; risk management; vulnerability assessment; environmental management; environmental engineering and technology; innovative construction materials; robust structure construction; information technology for disaster management; spatial modelling and analysis; agriculture infrastructure and technology; water resources engineering. This conference had gathered the plenary sessions presented by 1 (one) honorable keynote speaker and 5 (five) distinguished invited speakers during the conference from Japan, Thailand, Iran and Indonesia on interesting topics such as Innovation in Disaster Mitigation of Indonesia and Its Challenge delivered by Head of Indonesian Board for Natural Disaster Affairs, Letjend Doni Monardo; Soil Improvement Technique for Liquefaction Prevention delivered by Prof. Hideaki Yasuhara from Ehime University, Japan; Environmental Recovery in Fukushima delivered by Prof. Masaru Mizoguchi from The University of Tokyo, Japan; Earthquake Risk Reduction in Asia delivered by Prof. Pennung Warnitchai from Asian Institute of Technology, Thailand; Zero Runoff System delivered by Prof. Budi Indra Setiawan from IPB University, Indonesia and Drainage Infrastructures for the Prevention of Flooding in Megacities delivered by Vice President ICID (International Commission on Irrigation and Drainage), Dr. Kamran Emami (Iran) ISCEE 2020 had organized successfully with 65 presenters and more than 300 participants from around the world. A total of 101 research articles were submitted and 52 papers had been accepted by the peer review process to be processed to IOP Conferences Series: Earth and Environmental Science (EES) for publication. We would like to express our sincere gratitude to scientific committees, reviewers, and all participants. The acknowledgment is mainly addressed to keynotes and invited speakers, presenters, and moderators for this conference.
Local Binary Patterns Histograms (LBPH) Based Face Recognition

The human face has been broadly used in computer vision field for individual recognition. The face recognition is one of the secure ways to protect the data over the internet. In this paper we use (LBPH) Local Binary Patterns Histogram based Face Recognition. We use Yale face database for experiment and it contains 165 grey images in the GIF format of 15 person and 11 image per person and in this experiment we use only normal image in 180*180 at grey scale images and in this research article in the verification phase the difference between two histograms are calculated by Chi-square distance, Manhattan distance. The proposed technique has achieved TSR=98.8% in Chi-square and TSR=98.5% in Manhattan distance parameter. Person Identification using their physical structure or behavioral characteristic is known as the biometric.