Reviewerly/exHarmony huggingface dataset:
Sentence Pattern and Usage of Adjective Predicative Construction for ‘Sinsokankei’

This article is written for studying sentence pattern and usage in adjective predicative sentence that express ‘Sinsokankei’. The adjetive that denote ‘Sinsokankei’ are analyzed in two categories, orginal-adjective and transferred-adjective. The main results of the analysis can be summarized as follows.<BR> ① Typical examples are ‘Shitasii’ of orginal-adjecitve and ‘Ii, Warui, Nai’ of transferred-adjective. The adjectives of these two types represent a wide difference in sentence pattern and usage.<BR> ② The main sentence patterns of original-adjective are ｢N2ha․ga＋N1to＋A｣ and ｢N1ha․ga＋A. On the other hand, the main sentence patterns of transferred-adjective are ｢N3ha(ga)＋N2to+N1ga＋A｣ and ｢N2ha(ga)＋N1ga＋A｣.<BR> ③ Transferred-adjective required additional noun pharases because the semantic attribute of the word are weak compare to original-adjective. This is why there are more noun phrases in the sentence pattern. And, while ‘Ii and Warui’ of transferred-adjective mean general judgement of ‘Sinsokankei’, ‘Nai’ means absence of ‘Sinsokankei’.<BR> ④ The most basic sentenc pattern is ｢N2ha․ga＋N1to＋A｣ in original-adjective and ｢N3ha(ga)＋N2to+N1ga＋A｣ in tranferred-adjective. Both patterns are used for the objective of judging ‘Sinsokankei’.<BR> ⑤ There is a lot of abbreviations and reordering of two noun phrases in ｢N2ha․ga＋N1to＋A｣ and ｢N3ha(ga)＋N2to+N1ga＋A｣.
Monitoring: Predictions of the Effectiveness of Educational Processes in Higher Educational Institutions

In the period of globalization new requirements of the level of teachers’ preparation for their pedagogical career have significantly increased. Consequently, it demands higher educational institutions the necessity to draw special attention to enhance the efficiency of educational processes in preparing future teachers. In this article, the mechanism of implementation monitoring processes on improvement of the system of preparation teachers for pedagogical career in the high educational institutions has revealed. In this monitoring the distributional parameters of the corresponding processes according to the direction has taken into consideration and provided prognoses of them on the basis of interrelation and impact between indicators. On this purpose, the algorithmic model of interrelations between indicators of argumentative, procedural and productive directions of a process has developed. This model gives the chance to obtain the predicted information on educational process based on certain evidence, to define necessary organizational and pedagogical measures by comparison with the expected results, corrections, specifications and modernizations of teaching and learning processes.
The Seismic Wave Equation

This third edition provides a concise yet approachable introduction to seismic theory, designed as a first course for graduate students or advanced undergraduate students. It clearly explains the fundamental concepts, emphasizing intuitive understanding over lengthy derivations, and outlines the different types of seismic waves and how they can be used to resolve Earth structure and understand earthquakes. New material and updates have been added throughout, including ambient noise methods, shear-wave splitting, back-projection, migration and velocity analysis in reflection seismology, earthquake rupture directivity, and fault weakening mechanisms. A wealth of both reworked and new examples, review questions and computer-based exercises in MATLAB®/Python give students the opportunity to apply the techniques they have learned to compute results of interest and to illustrate Earth's seismic properties. More advanced sections, which are not needed to understand the other material, are flagged so that instructors or students pressed for time can skip them.
Developing a student attendance app using QR codes: educational and practical considerations

Recording student attendance in educational institutions is a tedious, manual process that is both time-consuming and error prone. We have developed an app to capture student attendance. During each class session, the students will point their device at a unique QR Code displayed on the teacher's projector. Each student's attendance will be recorded immediately on the learning-management system. The app has been developed for both Apple and Android platforms to enable attendance capture in all classroom settings; a module added to a home-grown learning-management system enables display of the appropriate QR Code for each class session. We conclude that it is possible to develop an app that records student attendance using QR codes and institutional information systems. Implemented efficiently, student attendance can be recorded accurately and effectively, saving class time. Overall user satisfaction with the system was high, demonstrating that information technology can positively drive and support change in medical education.
Troubleshooting: capnography

Abstract This section provides examples of capnograph traces, and lists causes and interventions for a range of abnormal capnography results.
Multilayer ensemble of ELMs for image steganalysis with multiple feature sets

A multilayer ensemble of extreme learning machines (ELMs) for multi-class image steganalysis is proposed in this paper. The proposed ensemble consists of three levels and uses multiple feature sets extracted from images. The first two layers form sub-ensembles, one sub-ensemble for each of the feature sets. Each feature set is partitioned and used with multiple ELMs at level-1. These feature sets along with the output of the ELMs at level-1 are used by different ELMs at level-2 to classify images into multiple classes. To combine these results from sub-ensembles a stacking technique is used. Results of level-2 ELMs are used as input for the last level ELM. The fast learning process of ELM aids the speedy execution of the proposed method. Performance of the proposed method is compared with existing steganalysis methods based on individual feature sets and on 2-level ensemble. The experimental study demonstrates that the proposed method classifies images into multiple classes with higher accuracy and this has been confirmed using t-test with 99% confidence.
An Implementation of Map Reduce on the Hadoop for Analyzing Big Data

The Speedy development of Internet has led to huge quantities of digital data available online and vast capacity of digital data is increasing and successfully stored. In demand to the process, analyzed, and linked huge volume of stored data to achieve correct Information, some computation is required. Even efficient processing and implementation is needed for scientific data performance analysis. We will compare with already existing MapReduce Technique with Hadoop to afford high performance and efficiency for large volume of dataset. Hadoop distributed architecture with MapReduce programming is analysis here.
Networking Letters

high-impact results in a timely manner.The IEEE Networking Letters is intended as a spinoff from IEEE Communications Letters and IEEE Wireless Communications Letters.Submitted papers are restricted to a maximum of four pages and the review cycle is intended to last at most six weeks after the submission date.It will publish high-quality, original research results derived from theoretical or experimental exploration of the area of communication/computer networking, covering all network layers except the physical layer, including architecture and design, protocols, control mechanisms, operations and management of access, core and edge networks.Although the Letters will not cover original work focusing on the physical layer, the letters will cover cross-layer design techniques including physical transmissions.IEEE Networking Letters topics include, but are not limited to, the following: Network protocols: Design, specification and verification, implementation, operation and performance evaluation of protocols in all network layers (data link, network, transport, and application).
Bitcoin Practice

In this chapter we will learn how to automate Bitcoin’s daemon with systemd, a software suite that provides service management facilities. It will help us create Raspberry Nodes that are more resilient to failures. We will also learn to communicate with Bitcoin nodes by utilizing packages and libraries written in Python and JavaScript. Although Bitcoin offers an easy-to-use graphical wallet, the real power lies in services that run behind it. The knowledge about its interfaces and commands should be part of every proper crypto-toolbelt. We will also learn to build our own Bitcoin Explorer by using an inexpensive, database-independent tool called btc-rpc-explorer. Following one of the golden rules in blockchains “Don’t trust. Verify.”, we should always strive to utilize the information that our own nodes provide. There is no need to rely on 3rd-party services, no matter how convenient they might be, because validating Full Nodes, like those we’re building here, offers everything we need to be independent actors in decentralized networks.
Does Shortening the Release Cycle Affect Refactoring Activities: A Case Study of the JDT Core, Platform SWT, and UI projects

The International Conference on Software Maintenance and Evolution is the premier international forum for researchers and practitioners from academia, industry, and government to present, discuss, and debate the most recent ideas, experiences, and challenges in software maintenance and evolution.
Session details: Theme: Distributed systems: WT - Web technologies track

The Web is relentlessly evolving. Once a single interconnection of static, physically distributed content passively accessed by human users through personal computers, during the explosion of Web-based social networks the Web evolved into an environment allowing users worldwide to interact and collaborate to create user-generated content within many virtual communities. In this line, Web 2.0 is the umbrella term used to encompass several developments which followed, namely social networking sites and social media sites (e.g., Facebook), blogs, wikis, folksonomies (e.g. Flickr), video sharing sites (e.g., YouTube), Web applications ("apps"), collaborative platforms, and mashup applications. Many technologies such as HTML 5, CSS3, AJAX and client-side scripting helped to bring these ideas into practice.
Session details: Theme: Information systems: DS - Data streams track

The rapid growth in data science and technology, in particular in the complexity and volume of Big Data, has introduced new challenges for the research community. Several of these are related to the nature of data generation, since most of the data sources produce data continuously. Examples include sensor and wireless networks, radio frequency identification, customer click streams, telephone records, multimedia and scientific data, and sets of retail chain transactions, among others. These sources are called data streams, ordered sequences of instances that can typically be read only once or a small number of times due to its their high speed of flow and continuous nature. Data streams are characterized by being open-ended, and generated by non-stationary distributions. Thus, they are increasingly important in the research community, as new algorithms are needed to efficiently process this streaming data, to enable rapid and real-time updated understanding of the data. The goal of this track is to convene researchers who work with data streams, defining models, processing continuous queries, developing sampling, filtering and stream mining methods, machine learning, and visualization techniques and related issues.
A Method to Comprehend Feature Dependencies Based on Semi-Static Structures

The International Conference on Software Maintenance and Evolution is the premier international forum for researchers and practitioners from academia, industry, and government to present, discuss, and debate the most recent ideas, experiences, and challenges in software maintenance and evolution.
Math Medley

Song parodies are a fun way to engage others with mathematical topics. The challenge, of course, is finding a song and lyrics that fit just right. While teaching together in Honolulu, we stumbled across a popular song that turned out to be a math parody in disguise! You will notice that we have not changed the words, just how the words were displayed. You might want to try singing this yourself or sing along with the YouTube version: https://youtu.be/d1mqNdZ0obA . What do you notice? What do you wonder?
Converting from Service Level Agreement to Probabilistic Temporal Logic Specification

The need for conversion method exists due to the limitation of manual conversion at design time whenever the interested party must perform some assessments using an existing model checker tool. Manual conversion of the related requirements into the respective specification language is time-consuming especially when the person has limited knowledge and need to do the task repetitively with a different set of Service Level Agreement (SLA) configurations. This paper aims to address the need to automatically capture non-functional requirements specified in the SLA, namely, Service Level Objectives (SLO) and converting them into a specific probabilistic temporal logic specification. We tackle this problem by proposing a conversion method that utilizes a rule-based and template-based approach. The conversion method automatically extracts the required information in SLA based on certain rules and uses the extracted information to replace the elements in the prepared template. We focus on WS-Agreement language for SLA and probabilistic alternating-time temporal logic with rewards specification (rPATL) for the properties specification used in PRISM-games model checker tool. We then implement an initial proof-of concept of a conversion method to illustrate the applicability of translating between targeted specifications.
Locating Optimal Coordinates of Police Deployment and Outpost in Santa Maria Bulacan using Centroid 360: An Enhanced Centroid Initialization for K means Algorithm

The number of police in the Philippines is way below than the declared number of police per population based on the Philippines Republic Act No. 6975, Chapter 3, Section 27 which states that one (1) policeman per five hundred (500) persons. Santa Maria Bulacan only have fifty-two (52) police personnel, and one (1) police outpost which is located in the town of Poblacion which is in the far south east of the whole municipality. This produces different speed when responding to incident reports. The police force’s response time vary based from the location of the incident. This research determined the optimum location to where police will be deployed as a mobile unit to be able to respond faster to more areas than staying in the outpost. Another thing that will be determined by this research is the optimum coordinates of a perfect scenario where each town in the municipality of Santa Maria Bulacan would have their own police outpost. The coordinates will be calculated based on the populations’ location by plotting all the houses and structures located in Santa Maria Bulacan based on Google Map Images, and the Optimum locations will be determined in the form of the converged centroids after applying enhanced K means clustering algorithm.
Development of Optimizing Technique for Temperature Control Based on Bayesian Optimization

Generally, a peltier device is controlled by PID control method. The performance of the temperature control depends on its PID parameters, and the optimum parameters have been explored through many try and errors. Those process have required huge effort of the engineers. So, we have used Bayesian Optimization method which is based on Bayesian statistics to optimize the parameters for PID control automatically. We adopted Bayesian Optimization method which was based on Bayesian statistics to optimize the parameters for the temperature settings automatically. We had constructed the temperature control unit to realize the rapid and the precise temperature control. Those process have required only 20 trials to improve the fast response and stability of the temperature control.
Superimposed Rule-Based Classification Algorithm (SRBCA) for One-Class Multivariate Conditional Anomaly Detection

Traditional anomaly detection causes a problem of detecting too numerous false positives in many problem domains.In this work, a Superimpose Rule-Based Classification algorithm (SRBCA) is proposed for conditional anomaly detection.The algorithm is an enhancement of the traditional OneR algorithm.The traditional OneR can generate a set of rules from its attributes with multiple classes, compute the error rate and apply the rule to the attribute with the smallest error.However, OneR has a disadvantage for one-class datasets which contains values belonging to the normal class.The enhanced algorithm, SRBCA, does not embody very complex rules similar to its predecessor.Furthermore, SRBCA includes the generation and application of rules from the one-class dataset in an n-dimensional space using classification.Holdout method was used to evaluate the performance of the classifiers' accuracy which involved training multiple subsets' behavioral and indicator attributes, superimposing rules and testing by using balanced and unbalanced class data to detect and label conditional anomaly data points.This paper shows the comparison between SRBCA, One-Class Support Vector Machine (OCSVM) and other anomaly detection classification algorithms for conditional anomaly detection.It proves that the new method can handle one-class multivariate for conditional anomaly detection with better accuracy.
Cluster Matching for Discrete Data with Multiple Domains with out Alignment of Information

We advocates a Topic methods for unsupervised cluster matching; this is the project of locating matching amongst clusters in first rate domains without correspondence statistics. As an instance, the proposed version famous correspondences among record clusters in English and German without alignment statistics, along with dictionaries and parallel sentences/files. The proposed version assumes that files in all languages have a not unusual latent challenge rely shape, and there are in all likelihood endless numbers of subject matter proportion percent vectors in a latent subject rely region that is shared by means of way of all languages. Each record is generated the use of one of the subject matter percentage percent vectors and language-particular phrase distributions. Via inferring a subject percent vector used for each document, we are able to allocate documents in wonderful languages into commonplace clusters, wherein each cluster is associated with a subject percent vector. Documents assigned into the same cluster are considered to be matched. We extend an green inference method for the proposed version based totally on collapsed Gibbs sampling. The effectiveness of the proposed model is confirmed with real datasets together with multilingual corpora of Wikipedia and product reviews.
Report for Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System

The study conducted by Wen et al. (2019) proposes a multi-Level Deep Cascade Trees Model (IdcTree) for conversion rate prediction in the recommendation system.The report introduces the background of recommendation systems used in the e-commerce industry and the proposed IdcTree for conversion rate prediction.The history and the challenges associated with DNN in previous work are carried out in the previous work of this study.The report also summarized in detail the main techniques and results of this study conducted by Wen et al. (2019) which establishes a basis for future research to investigate incorporating more features and other improvements that can improve efficiency in deep learning.
An integrative approach for tracking of mobile robot with vision sensor

Current work addresses an experimental approach which incorporates feature-based object detection, KLT algorithm-based tracking method and Kalman filter-based de-noising technique in a real-time environment. In the detection phase, the mobile robot is detected using Viola-Jones algorithm which extracts detectable features. Then the position of the mobile robot is computed with homography constraints and a region of interest window is set up to accommodate the mobile robot. In the tracking phase, the region of interest window is dealt with using KLT algorithm. The proposed method is of practical importance when the mobile robot is tracked while moving on a predetermined (specified) path as the size of the image of the mobile robot is small relative to the captured image of the environment. Thus the analysis of captured image of environment becomes unnecessary for tracking and thereby the approach reduces computational load. The proposed approach accurately detects and tracks the mobile robot with error percentage ranging from 0.5% to 10% in different parts of the specified path.
ON LINEARIZED COVERINGS OF A CUBIC HOMOGENEOUS EQUATION OVER A FINITE FIELD. LOWER BOUNDS

We obtain lower bounds for the complexity of linearized coverings for some sets of special solutions of the equation $$ x_{1}x_{2}x_{3} \mathclose{+} x_{2}x_{3}x_{4} \mathclose{+} \cdots \mathclose{+} x_{3n}x_{1}x_{2} \mathclose{+} x_{1}x_{3}x_{5} \mathclose{+} x_{4}x_{6}x_{8} \mathclose{+} \cdots \mathclose{+} x_{3n-2}x_{3n}x_{2} \mathclose{=} b $$ over an arbitrary finite field.
c-lightning

In this chapter we will learn how to set up a Lightning Node based on c-lightning, one of the three implementations of the BOLT specification. Using our previously configured Full Node, we will join the Lightning Network by opening and funding new channels to other nodes. We will also learn how to pay invoices and create own payment requests.
Book Reviews

Eva Paus of Department of Economics, Mount Holyoke College reviews “Trapped in the Middle? Developmental Challenges for Middle-Income Countries” by José Antonio Alonso and José Antonio Ocampo. The Econlit abstract of this book begins: “Fifteen papers investigate the existence of middle-income traps in middle-income countries (MICs), analyzing how these pitfalls manifest, their causes, and the economic policy measures required to escape from them.”
Applications of Fuzzy dot i* algebra in Computer Vision

Right now shows another route sort of identifying an edges and corners in the computer vision calculation. The Edge location is a key purpose of numerous calculations, both in picture preparing and video handling. It is significant that the calculation is proficient quick to bring out through the whole program. The custom system is to utilize the edge recognition it's not giving the better outcome dependent on the presumptions. In these conventional procedures here and there is vulnerability of the edge, and the man can't recognize whether it is the edge or not. So as to turn the fuzzy dot i* algebra based edge and corner (named as FDIA) all things considered and tackle the above issues. Fuzzy innovation has been a recent rising innovation utilized in numerous fields, particularly in the image handling, and computer vision is one significant piece of the fuzzy innovation. In light of this innovation, the edges and corners recognize by vigilant corner identification, calculation likewise to portray devices from picture preparing and the speed with the assistance of MATLAB programming.