Reviewerly/exHarmony huggingface dataset:
Miracle of Deep Learning Using IoT

Human recognition is still difficult due to the fact we do not yet have a data set sufficiently extensive to oversee the model preparing. This chapter addresses this difficulty from three perspectives to make human recognition adaptable to genuine information and applications. We consider a semi-directed profound learning structure that utilizes boisterous marked, as opposed to very much commented on information, and a huge scale dressing dataset with loud explanations, from which we can learn great portrayals for garments that assists in perceiving a human. A profound learning calculation and a space guided dropout procedure are taken in a solitary model from various human identification datasets with area predispositions. Ongoing advances of profound learning have created urging results tantamount to and even better than obtained by human specialists. Nonetheless, the extensive sum information input has been an overwhelming undertaking for profound figuring out how to be broadly connected in the Internet-of-Things (IoT) with continuous handling. The objective of this chapter is to investigate brilliant and quick information handling plan for more computationally proficient profound figuring out how to help versatile and continuous applications, which will have the capacity to build the range and vital productivity in IoT. This chapter will indicate how singular value decomposition (SVD)-QR calculation is required for preprocessing of profound learning for vast scale information input. Because of the quick increase of detecting information and brisk reaction prerequisite in the IoT conveyance organization; the rapid transmission has risen as a vital issue. Allocating reasonable directs in the remote IoT conveyance organization is an essential certification of rapid transmission. In any case, the high elements of movement stack make the regularly settled channel task calculation inadequate. As of late, the software defined networking based IoT (SDN-IoT) is suggested to be used to enhance the transmission quality. Other than this, the keen method of profound learning is broadly looked into in high computational SDN.
Reversible data hiding method by extending reduced difference expansion

To keep hiding secret data in multimedia files, such as video, audio, and image considers essential for information security. Image, for instance, as the media aids data insertion securely. The use of insertion technique must ensure a reliable process on retaining data quality and capacity. However, a trade-off between the resulted image quality and the embedded payload capacity after the embedding process often occurs. Therefore, this research aims at extending the existing method of integrating confidential messages using the Reduced Difference Expansion (RDE), transform into a medical image by changing the base point, block size, and recalculating of difference. The results display that the proposed method enhances the quality of the stego image and capacity of the hidden message.
Designation of modern management in education

Management, as a phenomenon of a developed society, is analyzed and perfected in conditions of growing globalization, in a world filled with challenges to find answers. Economic development depends on the functioning of management and managers in all sectors of human activity, as well as the overall social and economic development of a country. Today, special attention is given to the coordination of the theory and practice of the management of the countries in transition. The scientific approach to management in the field of education involves functional coherence and interconnection of human and material resources in order to achieve the tasks of individuals and the system of Change, which requires modern access to management in education, requires greater managerial activities in all spheres of life, so that the education system could make it more efficient and effective. Education in Serbia has to go through the changes that have already taken place in the developed countries, because we live in a society of knowledge and economy of knowledge. Education represents the "central nervous system" of every society - the pedagogic, educational, cultural chain that constantly vibrates. In this chain, a significant link, in addition to educators, teachers, professors and others, should be an educated and skilled manager. It is widely known that managers are required to possess the capacity for innovation and management in the planning, organization, coordination and control of the performance of educational institutions.
Pengembangan Media Pembelajaran Berbasis Web Desain Wix Materi Bangun Ruang Matematika SD Kelas V

Education has a major influence on the formation of character and human personality, so that the quality of human resources is determined by the level of education pursued by students. Elementary School Mathematics Lesson V in the perception of most students is still considered difficult because it is abstract with calculation formulas and must use logic to analyze it. The purpose of the study was to develop Wix web-based learning media design material for elementary class V Mathematics space. Research design was development research carried out based on 6 stages of the process namely concept, design, material collection, manufacture, testing and publication. The subject of the study consisted of media experts, material experts and sample classes consisting of 29 fifth grade students at SD 1 Babakan Elementary School in Parungkuda District. Data collection techniques were carried out through the media expert test questionnaire and material expert test and user response questionnaire conducted by students. The results of the development of instructional media are based on the assessment of media experts and material experts, namely the need for improvement for the scope of the material presented is more complete and more interactive to facilitate material search. The criteria for the assessment of product trial instruments carried out by students get an average score of facilitation aspects of 2.753, the attractiveness aspect is 2.697 and the benefit aspects of the product are 2.583 so that based on the assessment indicators the product is in good criteria.
Current Procedural Terminology Coding in an Academic Breast Pathology Service

Many physicians share the perception that the work required to evaluate breast pathology specimens is undervalued by Current Procedural Terminology (CPT) codes. To examine this issue, we compared slide volumes from an equal number of breast and nonbreast specimens assigned 88305, 88307, or 88309 CPT codes during four 2.5-week periods over 1 year. For each specimen, a number of initial hematoxylin and eosin–stained sections (H&amp;Es), preordered additional H&amp;E sections (levels), H&amp;E sections ordered after initial slide review (recuts), and specimen type were recorded. Slides associated with ancillary stains were not considered. In total, 911 breast and 911 nonbreast specimens, each assigned 88305 (n=580), 88307 (n=320), and 88309 (n=11) CPT codes, were compared. Breast 88305 specimens were mainly core biopsies and margins and generated 2.3 and 6.4 times the H&amp;Es and recuts, respectively, than did nonbreast specimens ( P &lt;0.01). Breast 88307 specimens were mainly lymph nodes and lumpectomies and generated 1.8 times the total slides than did nonbreast specimens ( P &lt;0.01). Eleven modified radical mastectomies (88309) generated 2.1 times the total slides than nonbreast 88309 specimens ( P &lt;0.01). In total (n=911 in each cohort), breast specimens generated 1.9, 4.0, and 1.7 times the H&amp;Es, recuts, and total slides ( P &lt;0.01) than did nonbreast specimens. At our academic institution, the slide volume for breast specimens is nearly twice that of similarly coded nonbreast specimens. These results have significant implications for workload management and assessing pathologist productivity, particularly in subspecialty practices.
Implementasi Game Based Learning pada Pembelajaran Bahasa Inggris

Games are media that can be used in the learning process to stimulate students in teaching and learning activities in the classroom. The game used is a game that has been adapted to the needs of learning in the classroom called game based learning or educational games. English subjects are difficult to learn by elementary students at SDN Bujur Barat II, so the use of learning media is needed to attract students' interest in learning the subject. In this study, an educational game was made based on the SD English curriculum consisting of writing, reading, listening, and speaking, which was built using the Ionic programming language and the PHP Framework.
Adaptive signal fusion based on relative fluctuations of variable signals

To solve the problem of the total mean square error of the traditional random weighting algorithm being much larger when the target signal is variable than when the signal is constant, an improved adaptive random weighting algorithm is proposed. To bring the estimated value closer to the true value, the algorithm adjusts the proportional relationship between the current acquisition signal and the historical acquisition signal adaptively by using the relative fluctuation value of the collected signal. Because the relative fluctuation value can be adjusted autonomously according to the signal variation, it can be combined with the traditional random weighting algorithm very successfully. Numerical simulations demonstrate the effectiveness of the proposed fusion method.
Experience and Problems of Increasing the Efficiency of Scientific Activity of National Libraries

The purpose of the article is to substantiate the further development and increase of the efficiency of scientific research and scientific-methodical activity as the main type of activity of the National Libraries (NL). There is presented the analysis of the legal basis of the research function of NL — legislation in the field of librarianship, science and scientific and technological policy. The author considers the reflection of this function in the Statutes of NL of different times and stages of development. The article reveals the modern forms of institutionalization of scientific activity and scientometric approach to assessing the efficiency of scientific institutions. The author records the necessity of comparative analysis of the legal substantiation of the forms of organization and content of scientific activity of the National libraries of different countries. The author analyses domestic and foreign sources on this problem, as well as determines the scope of missing information for more profound and comprehensive assessment of the current state of research activities of NL. To this end, the author examines the official websites of the libraries and reveals the following results. Most of NL are engaged in scientific research. Based on the analysis, the article substantiates the conclusion about the presence of general trends in their content, corresponding to the modern requirements of socio-economic and cultural development. The author presents the conclusion on the need to develop scientific activity of the National Library of Russia in accordance with the “Concept of Development of the National Library of Russia for 2018—2025”. The article analyses the normative and regulatory documents of domestic and foreign NL, as well as the experience of domestic and foreign researchers over the past 20 years, which proves the important place and role of scientific research in the activities of the modern NL. The conducted analysis will contribute to improving the efficiency of scientific activities of NL, strengthening of their role as a scientific and methodological centre for the Central libraries of the Russian Federation, as well as the role of regional libraries in the formation of the research space and the environment of professional scientific communications.
Debunking the Myth That Upfront Requirements Are Infeasible for Scientific Computing Software

Many in the Scientific Computing Software community believe that upfront requirements are impossible, or at least infeasible. This paper shows requirements are feasible with the following: i) an appropriate perspective ('faking' the final documentation as if requirements were correct and complete from the start, and gathering requirements as if for a family of programs); ii) the aid of the right principles (abstraction, separation of concerns, anticipation of change, and generality); iii) employing SCS specific templates (for Software Requirements and Module Interface Specification); iv) using a design process that enables change (information hiding); and, v) the aid of modern tools (version control, issue tracking, checking, generation and automation tools). Not only are upfront requirements feasible, they provide significant benefits, including facilitating communication, early identification of errors, better design decisions and enabling replicability. The topics listed above are explained, justified and illustrated via an example of software developed by a small team of software and mechanical engineers for modelling the solidification of a metal alloy.
A Fragile Watermark Scheme for Image Recovery Based on Singular Value Decomposition, Edge Detection and Median Filter

Many fragile watermark methods have been proposed for image recovery and their performance has been greatly improved. However, jagged edges and confusion still exist in the restored areas and these problems need to be solved to achieve a better visual effect. In this paper, a method for improving recovery quality is proposed that adopts singular value decomposition (SVD) and edge detection for tamper detection and then uses a median filter for image recovery. Variable watermark information can be generated that corresponds to block classifications. With mapping and neighborhood adjustment, the area that has been tampered can be correctly detected. Subsequently, we adopt a filtering operation for the restored image obtained after the inverse watermark embedding process. During the filtering operation, a median filter is used to smooth and remove noise, followed by minimum, maximum and threshold operations to balance the image intensity. Finally, the corresponding pixels of the restored image are replaced with the filtered results. The experimental results of six different tampering attacks conducted on eight test images show that tamper detection method with the edge detection can identify the tampered region correctly but has a higher false alarm rate than other methods. In addition, compared with the other three similar methods previously, using a median filter during image recovery not only improves the visual effect of the restored image but also enhances its quality objectively under most tampering attack conditions.
Financial shielding that Bitcoin grants to capitals in the world

Market forces are not the only influence on currency exchange rates. They can change due to monetary and fiscal policies among other international repercussions. Bitcoin, for its independence from all the central banks worldwide, has a natural shield that will change the direction in the economic policy of the industrialized countries. The research aim is to analyze the influence that indicators and financial assets can have on Bitcoin. The study tries to confirm the reasons why it has begun to be the solution in economies with unstable currencies.The behavior of the different agents appears as the core of the study. It is creating a backward 5-year work horizon. The data are continuous values, and they are the numerical variables for Pearson correlation analysis. The time series in fixed periods are the basis for the study of projections. Besides, the Relative Strength Index or Relative Strength Index called Welles Wilder is useful in the research. Bitcoin does not get influenced by the Dow Jones, gold price, and Gross Domestic Product (GDP). The independence in the creation of this cryptocurrency could in the long term end up turning it into a currency of world use. As a result, the understanding and management of this cryptocurrency could generate new ways of building the future monetary system. The new direction of the economy will be registered in the blockchain and not in a central bank.
Interaction Promotes the Adaptation of Referential Conventions to the Communicative Context

Coordination between speakers in dialogue requires balancing repetition and change, the old and the new. Interlocutors tend to reuse established forms, relying on communicative precedents. Yet linguistic interaction also necessitates adaptation to changing contexts or dynamic tasks, which might favor abandoning existing precedents in favor of better communicative alternatives. We explored this tension using a maze game task in which individual participants and interacting pairs had to describe figures and their positions in one of two possible maze types: a regular maze, in which the grid-like structure of the maze is highlighted, and an irregular maze, in which specific parts of the maze are salient. Participants repeated this task several times. Both individuals and interacting pairs were affected by the different maze layouts, initially using more idiosyncratic description schemes for irregular mazes and more systematic schemes for regular mazes. Interacting pairs, but not individuals, abandoned their unsystematic initial descriptions in favor of a more systematic approach, which was better adapted for repeated interaction. Our results show communicative conventions are initially shaped by context, but interaction opens up the possibility for change if better alternatives are available.
Association rules with apriori algorithm and hash-based algorithm

Abstract The purpose of this research is to determine the pattern of hijacking cases in Samarinda by using association rules and comparing apriori and hash-based. The data used for this research are secondary data from POLRESTA Samarinda which is processed using association rules algorithm with apriori and hash-based with minimum support of 10% and minimum confidence of 70%. The result of this research, in apriori, the pattern is often formed as many as 4 5-itemset combination while the hash-based obtained pattern that often formed by 3 3-itemset combination. In 2-itemset that is if the victim is female and young, then have a possibility of 46.67% chance of experiencing minor injuries with confidence of 90.9%, in 3-itemset if the victim is in location 1 and young, then have a possibility 53.33% chance of experiencing minor injuries with confidence of 88.89%, in 4-itemset if the victim in location 2, female and young then have a possibility 40% chance of experiencing minor injuries with confidence of 100%, in 5-itemset if the victim in location two, quite, female and young then have a possibility 26.67% chance of experiencing minor injuries with confidence of 100%.
A Generate-Validate Approach to Answering Questions about Qualitative Relationships

Qualitative relationships describe how increasing or decreasing one property (e.g. altitude) affects another (e.g. temperature). They are an important aspect of natural language question answering and are crucial for building chatbots or voice agents where one may enquire about qualitative relationships. Recently a dataset about question answering involving qualitative relationships has been proposed, and a few approaches to answer such questions have been explored, in the heart of which lies a semantic parser that converts the natural language input to a suitable logical form. A problem with existing semantic parsers is that they try to directly convert the input sentences to a logical form. Since the output language varies with each application, it forces the semantic parser to learn almost everything from scratch. In this paper, we show that instead of using a semantic parser to produce the logical form, if we apply the generate-validate framework i.e. generate a natural language description of the logical form and validate if the natural language description is followed from the input text, we get a better scope for transfer learning and our method outperforms the state-of-the-art by a large margin of 7.93%.
Software clusterings with vector semantics and the call graph

In this paper, we propose a novel method to determine a software's modules without knowledge of its architectural structure, and empirically validate the method's performance. We cluster files by combining document embeddings, generated with the Doc2Vec algorithm, and the call graph, provided by Static Graph Analyzers to an augmented graph. We use the Louvain Algorithm to determine its community structure and propose a module-level clustering. Our method performs better in terms of stability, authoritativeness, and extremity over other state-of-the-art clustering methods proposed in the literature and is able to decently recover the ground truth clustering of the Linux Kernel. Finally, we conclude that semantic information from vector semantics as well as the call graph can produce accurate results for software clusterings of large systems.
FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension

Conversational machine comprehension requires deep understanding of the dialogue flow, and the prior work proposed FlowQA to implicitly model the context representations in reasoning for better understanding. This paper proposes to explicitly model the information gain through dialogue reasoning in order to allow the model to focus on more informative cues. The proposed model achieves state-of-the-art performance in a conversational QA dataset QuAC and sequential instruction understanding dataset SCONE, which shows the effectiveness of the proposed mechanism and demonstrates its capability of generalization to different QA models and tasks.
Information dynamics with confidence: Using reservoir computing to construct confidence intervals for information-dynamic measures

Information dynamics provides a broad set of measures for characterizing how a dynamical system stores, processes, and transmits information. While estimators for these measures are commonly used in applications, the statistical properties of these estimators for finite time series are not well understood. In particular, the precision of a given estimate is generally unknown. We develop confidence intervals for generic information-dynamic parameters using a bootstrap procedure. The bootstrap procedure uses an echo state network, a particular instance of a reservoir computer, as a simulator to generate bootstrap samples from a given time series. We perform a Monte Carlo analysis to investigate the performance of the bootstrap confidence intervals in terms of their coverage and expected lengths with two model systems and compare their performance to a simulator based on the random analog predictor. We find that our bootstrap procedure generates confidence intervals with nominal, or near nominal, coverage of the information-dynamic measures, with smaller expected length than the random analog predictor-based confidence intervals. Finally, we demonstrate the applicability of the confidence intervals for characterizing the information dynamics of a time series of sunspot counts.