Reviewerly/exHarmony huggingface dataset:
Comparative Analysis of Results of Modern Classification Algorithms Usage for Determining the Type of Physical Activity Based on Integrated Sensors Data

The article considers the usage of various classification algorithms to process data from integrated sensors of a modern smartphone to obtain user's physical activity. To compare classification algorithms, we use modeling based on a dataset from an experiment that has 561 significant characteristics for each type of activity with a total number of records equal to 10299. The analysis of data from integrated sensors is performed by several classification algorithms: decision trees, Random Forest algorithm, logistic regression, support vector machine with a linear function and a kernel function. In addition to pure (without modification) ones, algorithms with preliminary optimization of hyperparameters using random search and cross-validation are used. The evaluation metrics are: Accuracy, Precision, Recall, F-measure, Mean Absolute Error and Root Mean Square Error. The estimated metrics and confusion matrices obtained using specially written python scripts using the sklearn library are provided for each algorithm. Analysis of the presented results shows that the best classification results both with preliminary optimization of hyperparameters and cross-validation, and without preliminary tuning, are provided by the use of linear support vector machine algorithm.
Exploring Interactions in YouTube to Support the Identification of Crime Suspects

The identification of crime suspects on social networks (e.g. pedophilia, terrorism, etc.) has been one of the most relevant topics in social network analysis. The vast majority of methods are based on the extraction of textual content, senders and receivers from the network, but do not take into account the interactions that occur inside the textual content. The present work raises the hypothesis that these interactions, if taken into consideration, can lead to better results when it comes to identifying crime suspects. To validate this hypothesis, an algorithm named TROY was developed to define and represent the interactions that occur in Youtube. Then, it is proposed as the first stage of the INSPECTION method, which analyzes the textual content exchanged on a social network, in order to identify crime suspects. This method is based on the use of a controlled vocabulary with terms categorized according to a certain domain (for example, pedophilia, cyberbullying, terrorism, etc.). Experiments on the pedophilia domain were carried out applying the INSPECTION method to Youtube. The first stage of the method may use any algorithm that is able to extract social interactions. In this case, we used TROY and another algorithm called CRAWLER, which does not take into account the previously mentioned interactions. The results showed that the TROY algorithm obtained better results than the CRAWLER algorithm, validating the hypothesis raised.
Modular Image Synthesizer for Annotated Test Sets on Incremental Parameter Fields

There are many ways to improve the quality of indoor localization. A big lever here is the quality and quantity of training data. For the evaluation of algorithms, fully annotated and repeatable accurate training data is essential. In order to reduce the personnel effort for manual annotations, it is advisable to generate these training data automatically. This offers the additional advantage of changing existing scenes in small steps. This enables a finely granular evaluation of algorithms trained with it. For this purpose we developed a Modular Synthesizer for Annotated Test Sets (MSATS). With MSATS we generate large data sets of completely annotated image data based on publicly available 3D CAD models. The scenes rendered automatically in small-step increments using multidimensional, modular parameter fields. The object annotations are determined from the projected virtual 2D viewer plane using a raycast method and coupled to the 3D data. The composed scenes are presented in orbitals. The resulting sets of images allow us to evaluate object detectors in detail and compare their output with the MSATS output.
Autocoder Guide Multi-category Topic Clustering for Keywords Matching

In the task of multi-category keyword extraction, how to make effective use of text topic information is a very challenging research problem. In order to solve the problems such as weak cluster center information representation and noise influence of non-topic word feature in unlabeled topic clustering, we proposed a keyword extraction model of multi-category topic clustering based on autocoder. The modeling was carried out respectively from the aspects of node representation and topic cluster division to effectively alleviate the influence of high-dimensional noise features on the establishment of cluster centers. In the evaluation, the Gini impurity was used as an index to measure the fitting degree between the clustering effect of the method and the artificial clustering, and the cluster center was used to measure the topic similarity of the words in the clustering results. The results on the THUCNews and short text datasets show that the model can obtain information beneficial for keyword extraction tasks, and achieve better performances on various evaluation indexes.
Realizing Ontology-based Reusable Interfaces for Data Access via Virtual Knowledge Graphs

In this paper, we present a comprehensive framework, which we call VKG-UI, for realizing ontology-based reusable user interfaces (UIs) for data access via virtual knowledge graphs (VKGs). The VKG approach uses an ontology to model the domain of interest and to hide the heterogeneity of the underlying data sources. Reusable UIs can be built by relying on queries that are issued to the VKG system and that use the high level vocabulary from the ontology layer. This use of VKGs allows for decoupling the data from the UIs, and brings great reusability in designing the latter. To illustrate our approach, we introduce significant use cases with various types of UIs, including programming, graphic, natural language, and voice interfaces.
Higher Vocational Digital Loose Leaf Textbook Design System Based on Task Driven and PS Development

To meet the special needs of higher vocational software development loose leaf teaching materials, this paper fully investigates the actual requirement of teachers and students for digital teaching environment and digital teaching materials, and develops a loose leaf teaching material design system based on task driven and PS development. The scheme uses B/S architecture, and it is combined with MFC class library, MSSQL, task driven theory, summed up the overall structure and workflow of the textbook design system. This paper also focuses on the determination of the development and operation environment, the design of the program architecture and the implementation technology of each functional module. Taking the graphic design case of a course textbook as an example, the system function test and performance test are performed. The experimental results show that the digital loose leaf textbook system under e-learning platform enables designers to directly participate in the process of graphic creation and knowledge integration, and supports the needs of new education mode.
Enhancing Primary ESL Learners’ Simple Sentence Construction Using the PPT PiWoCa Technique in the Form of Bubble Map—A Literature Review

Society of today signifies how English, as a global language, has attained a universal pedestal compared to others.Thus, it is highly demanding and challenging for one to be a proficient and effective language user.In Malaysia, teachers of English as a Second Language (ESL) tend to face umpteenth challenges in developing primary ESL learners' language abilities, especially in the scope of writing.Some of the problems include deprivation of vocabulary, lack of motivation, lack of reading and the influence of multimedia language.Consequently, ESL teachers have to opt for different strategies and approaches to tackle primary ESL learners' writing skills, particularly in simple sentence construction.Therefore, this study presents a literature review on the use of PowerPoint Picture-Word Card (PPT PiWoCa) technique in the form of bubble map to enhance primary ESL learners' simple sentence construction.In this study, social constructivist theory and the visual-spatial element in Gardner's Multiple Intelligences theory reveal that the PPT PiWoCa technique allows primary ESL learners to brainstorm ideas and construct knowledge in authentic contexts.Similarly, the use of visual representations such as PPT, pictures, word cards and bubble map is able to capture primary ESL learners' attention in the recognition of words, grammatical functions and sentence structure based on a guided sample of simple sentence construction.With the presence of visual aids, primary ESL learners are able to model the sample given in order to produce meaningful simple sentences.
Estimation of von mises-fisher distribution algorithm, with application to support vector classification

The most common method in the Evolutionary Algorithm community to handle constraints is to use penalties. The simplest being the death penalty, which rejects solutions that violate constraints. However, its inefficiency in search spaces possessing small feasible regions spurred research into adaptive penalties and other competitive methods. A major criticism of these approaches is that they require the user to fine-tune parameters or design problem-dependent operators. We propose to do away with penalty functions for problems over the Euclidean space when the constraint is an equality concerning the Euclidean distance. This paper describes an evolutionary algorithm on the unit hypersphere based on representing the population with the von Mises-Fisher probability distribution from the field of Directional statistics. We demonstrate its utility by solving the support vector classification problem for a few datasets.
RETRACTED ARTICLE: Design of Heterogeneous Data Transmission System for Industrial Enterprises Based on Fuzzy Algorithm

The traditional heterogeneous data transmission system of industrial enterprises has poor performance. In order to solve this problem, the design of heterogeneous data transmission system of industrial enterprises based on fuzzy algorithm is proposed. The hardware of the system is composed of STM32F107RCt6 microprocessor, FLASH memory, AS32-TTL-100 wireless module and DP83848x chip, which realizes the hardware design of two node functions. The system software introduces the fuzzy algorithm to realize the data transmission function, including data source management module, data extraction module, data writing module, log management module and user management module. The design of heterogeneous data transmission system of industrial enterprise based on fuzzy algorithm is completed by combining software and hardware. Finally, enter the experimental part to test the performance of the proposed system and the traditional system. The experimental results show that the performance of the proposed system is better, further play the role of information data in production; improve system efficiency and anti-fault ability.
The experimental test of the best abasorbents for controlling poly aromatic hydrocarbon on sea water around graving dock and hhip loading terminal

Abstract Bentonite and zeolite adsorbents have the ability to adsorb PAH content around the shipyard and ship loading and unloading areas. The factors that potentially affect the level are: a. The types of bentonite and zeolite adsorbents, b. Sampling time is 0, 2, 4, 6 and 8 hours. Adsorption of poly aromatic hydrocarbon by zeolite adsorbent as much as 150 gram done at certain place with volume of 3 liters of sea water taken from ship loading and unloading terminal area and at time variable 0, 7, 14, 28 and 42 days. Measurement of PAH on day 0 by way of direct examination of sea water concentration and PAH type. Determination of the best adsorbent, seen from the ability of the absorption of PAH both in the high concentration and the number of PAH types adsorbed, the results showed that zeolite adsorbents have better adsorption capacity because it has sufficient surface area and does not clot when exposed to water. The concentration of sea water PAH at ship loading and unloading terminal is very high, that is 65,45ppb, especially for PAH type of naphthalene and 2-Bromonaphthalene ie 28,3255 and 27, 2821ppb respectively. The ability of zeolite adsorbent and maximum adsorption of PAH at 28 days adsorption, ie 19, 75ppb is dominated by Benzo(a)pyrene type PAH with concentration of 19,2771ppb. Based on Linear Regression test to total PAh, it can be concluded that the value of R Square 0,190511343 which shows that the absorption time by zeolite absorbent and absorption power of poly aromatic hydrocarbons compound of the whole types has no significant effect. Therefore, polynomial testing is done through the equation y = -8,959x^3+62,858x^2-125,49x+72,379 yield value R^2= 1 which means absorption of 100% polyaromatic hydrocarbons compound in time.
Impact Umurenge Sacco to Financial Inclusion in Rwanda

This study examines the impact of Umurenge SACCOs to financial inclusion in Rwanda. Secondary data which are time series were analyses with objectives to find out whether U-SACCO have impact to financial inclusion with baseline to 3 dimensions of Quality, accessibility and usage are dimensions of financial inclusion. This study used descriptive analysis and both excel and STATA used in computing data. The finding of this study demonstrated the positive impact of U-SACCOs to financial inclusion. However, government should put more attention on quality of financial service in SACCOs by automating of all SACCOs.
Application of determining the price of batik using Fuzzy Tsukamoto

Abstract Competition in the world of business is something that is definite and occur in all kinds of b business. One of the ways that businesses keep running is to satisfy the customer. Batik business sales in Indonesia continues to grow, this is because one of the non-verbal culture heritage objects is Batik. But not all business people have good luck, this is because they are unable to satisfy customers. Things that make customers upset one of the types of batik is not in accordance with the price. Fuzzy Tsukamoto is one method that there is fuzzy for the determination of the decision. No exception to the price of batik. This study uses Tsukamoto fuzzy to determine the price of batik. The results of the implementation of the Tsukamoto fuzzy method in determining the price of batik in accordance with the price of fabric, the manufacturing process, batik motifs and colours. This system can also help determine the price of batik in accordance with the quality of batik.
ARDNA: A Mobile App Based on Augmented Reality for Supporting Knowledge Exploration in Learning Scenarios

Nowadays, Augmented Reality is broadly integrated across multiple environments, but the smart learning area is still polarized on visualizing articulated 3D models. Our proposal consists of a new approach to collect and organize notes, that takes full advantage of the AR platform providing an useful learning tool for students. Augmented Reality Data Navigation App (ARDNA) manages to display on screen notes, images and 3D graphs floating alongside traditional study material to support students during their learning acquisition process. The app has been implemented through the use of Unity and Vuforia Augmented Reality SDK. A minimum viable product has been handed to a small group of students and their experiences have been monitored and evaluated; the results obtained support the founding statement of the app with measurable improvement for smarter studying.
Research on Service-Oriented Integration of Hospital Application System

An integration platform solution of existing hospital information system based on Service-Oriented Architecture (SOA) is proposed. The whole system is designed and combined with the loosely coupled subsystem through Web Service, and finally integrated into an organic whole organization with multiple functions. The problem of information heterogeneity, geographic distribution and isolation among management systems of various hospital departments is solved, which is helpful for organizing complex data interaction interface, greatly improving the efficiency of data exchange and forming a standardized interface platform of hospitals that is easy to be controlled and managed.
How Emotional Intelligence and Consciousness (Mindfulness) in Education Can Provide a New Character and Orientation to the Nation

Our nation and state today are going through a difficult period in their life and survival, because the moral principles and values, the principles of democracy, in particular the human principles of mutual respect, respect and empathy for each other, have been damaged. The causes are certainly deeper, and researching, one concludes that the great nursery of democracy is education lags behind in terms of adhering to the principles of education and functional efficiency. The change of orientation of our education towards the inner world of man, the upliftment of the spiritual struggle, and cultivating from the inside out with the skills of emotional intelligence and consciousness will help citizens to reorient themselves and realize that they are part of a nation but at the same time citizens of a global community with broader perceptions, goals, and obligations. The revision of education programs and the introduction in education of emotional intelligence and consciousness will lay the foundations for the creation of a new generation of sensitized and conscious citizens.
A graphical approach for multiclass classification and for correcting the labeling errors in mislabeled training data

Multiclass data classification, where the goal is to segment data into classes, is an important task in machine learning. However, the task is challenging due to reasons including the scarcity of labeled training data; in fact, most machine learning algorithms require a large amount of labeled examples to perform well. Moreover, the accuracy of a classifier can be dependent on the accuracy of the training labels which can be corrupted. In this paper, we present an efficient and unconditionally stable semi-supervised graph-based method for multiclass data classification which requires considerably less labeled training data to accurately classify a data set compared to current techniques, due to properties such as the embedding of data into a similarity graph. In particular, it performs very well and more accurately than current approaches in the common scenario of few labeled training elements. Morever, we show that the algorithm performs with good accuracy even with a large number of mislabeled examples and is also able to incorporate class size information. The proposed method uses a modified auction dynamics technique. Extensive experiments on benchmark datasets are performed and the results are compared to other methods.
Bio-Rad Lab'ys, Inc. v. Int'l Trade Comm'n

Biotechnology Law ReportVol. 40, No. 5 Original ArticlesBio-Rad Lab'ys, Inc. v. Int'l Trade Comm'nUnited States Court of Appeals of the Federal Circuit, 2021996 F.3d 1302Edited for Biotechnology Law Report by Christopher M. HolmanEdited for Biotechnology Law Report by Christopher M. HolmanChristopher M. Holman is a Professor of Law at the University of Missouri–Kansas City School of Law; a Senior Scholar at the Center for the Protection of Intellectual Property at the Antonin Scalia Law School, George Mason University; and the Executive Editor of Biotechnology Law Report.*The synopsis is original content and the decision itself has been condensed for ease of readability.Search for more papers by this authorPublished Online:12 Oct 2021https://doi.org/10.1089/blr.2021.29237.cmhAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleFiguresReferencesRelatedDetails Volume 40Issue 5Oct 2021 InformationCopyright 2021, Mary Ann Liebert, Inc., publishersTo cite this article:Edited for Biotechnology Law Report by Christopher M. Holman.Bio-Rad Lab'ys, Inc. v. Int'l Trade Comm'n.Biotechnology Law Report.Oct 2021.339-351.http://doi.org/10.1089/blr.2021.29237.cmhPublished in Volume: 40 Issue 5: October 12, 2021Online Ahead of Print:July 6, 2021PDF download
The Snowden Phone: A Comparative Survey of Secure Instant Messaging Mobile Applications

In recent years, it has come to attention that governments have been doing mass surveillance of personal communications without the consent of the citizens. As a consequence of these revelations, developers have begun releasing new protocols for end-to-end encrypted conversations, extending and making popular the old Off-the-Record protocol. New implementations of such end-to-end encrypted messaging protocols have appeared, and several popular chat applications have been updated to use such protocols. In this survey, we compare six existing applications for end-to-end encrypted instant messaging, namely, Signal, WhatsApp, Wire, Viber, Riot, and Telegram, most of them implementing one of the recent and popular protocols called Signal. We conduct five types of experiments on each of the six applications using the same hardware setup. During these experiments, we test 21 security and usability properties specially relevant for applications (not protocols). The results of our experiments demonstrate that the applications vary in terms of the usability and security properties they provide, and none of them are perfect. In consequence, we make 12 recommendations for improvement of either security, privacy, or usability, suitable for one or more of the tested applications.
Automatic Image Processing of Locator Sensors. Main Problems of Processing Radar, Sonar and Optoelectronic Images

The article analyzes the typical conditions for the functioning of locator systems for various purposes. The general problems of processing location images are considered: radar, sonar, optoelectronic. The problems of analyzing radar images of a surveillance radar at various stages of processing are considered particularly. The characteristic features of such images are described. Examples of various interference-target situations are given. The problems of analysis of sonar images of highly automated sonar systems are commented in detail. A classification of the characteristic features for the sidescan sonar and near field sonar is given. A set of methods for overcoming the problems of a priori uncertainty and non-stationarity of the signal-interference environment is commented. The problems of the analysis of optoelectronic images are described. They are systematized and classified by the features of images for different conditions of observation of marine optoelectronic systems. Comments on processing when various objects of brightness are detected in the image are given.