Reviewerly/exHarmony huggingface dataset:
An Annotation System to Annotate Healthcare Information from Tweets

This paper presents a unique idea to utilize social media data for the betterment of healthcare service, provided by the doctors and related industries. The researchers have observed that every day, on average, around 5 million tweets are tweeted on Twitter and around 2 billion tweets per year related to health care. This huge data source can be used and analyzed to obtain better knowledge about recent trends and discoveries in a particular field. Hence, we are motivated to develop a structured corpus from scratch, identify concepts and categories using the machine learning approach on the extracted unstructured and semi-structured corpora. In order to build the system, we have employed two well-known classifiers, namely multinomial Naive Bayes and support vector machine on the top of our prepared experimental dataset. The training and test datasets are part of the experimental dataset and have been used to build the module and validate them, respectively. The proposed module is able to assign healthcare concepts and their categories for tweets. Finally, the validation offers F-measure 0.67 and 0.57 for concept identification as well as categorization system individually. This annotation system may help to design various applications such as summarization and recommendation system in health care for assisting medical practitioners.
Evaluation of Ad-hoc Secure Device Pairing Method with Accelerometer and Camera Using Marker

Currently, devices with wireless technologies often communicate each other ad hoc. For example, a presenter wirelessly distributes ad-hoc meeting materials from a PC to mobile device in a meeting room. However, there is a problem of spoofing by an impersonator outside the room. Hence, devices must conduct secure pairing, which is exchange of key necessary for encrypting communication contents, before the communication. As a pairing method between devices, there are pairing methods using RSS from access point as features. However, RSS changes significantly due to environmental factors. On the other hand, there are the pairing methods which compare acceleration data from devices with displacement data of devices from camera of a server. However, these methods have problems that it is necessary to use infrared camera and difficult to recognize inclination of devices. Thus, these methods cannot perform accurate device pairing. Therefore, in this paper, we propose a method that perform pairing using devices' accelerometers and markers displayed on devices, and a camera of authentication server. This method performs pairing by calculating similarity between velocity data from acceleration data from devices and displacement data of the marker from camera after comparing marker sequence displayed on the device. This method has advantage that can detect devices' inclination by recognizing markers' inclination. We performed three types of experiments to confirm the similarity of displacement data and acceleration data, whether an impersonator outside camera range can perform pairing, and possibility of several devices pairing together. As a result, we founded that the larger the device's display is, the higher the similarity, the proposed method can distinguish legitimate user from impersonator outside camera range by average similarity, and three devices succeeded pairing at rate of 71.8%.
Self-adjusting Learning Strategies of Preservice Teachers’ Cross-disciplinary Teaching Professionalization: Adjusting 107 Curriculum Reform and Industry 4.0

This study aims to design a self-adjusting learning strategy for the pre-service teachers' cross-disciplinary teaching professionalism in order to adjust to the 107 Curriculum Reform and Industry 4.0.Experimental teaching in a self-adjusting learning strategy training program is given herein.The teaching is aimed at exploring the impact of the course on pre-service teachers' cross-disciplinary teaching professionalism.The sample for the study included 64 pre-service teachers in an unequal pre-and post-test control group.Research tools included the cross-disciplinary teaching professional behavior scale.The conclusions were: 1.After the teaching, the pre-service teachers of the experimental group showed significant improvement in the areas of "curriculum development and design", "pro-teacher communication" and "professional leadership" in the cross-disciplinary teaching specialization.2. Of the pre-service teachers in the experimental group, 87.2% had a positive attitude to self-adjustment curriculum teaching.
Mining Frequent Patterns in Firewall Logs Using Apriori Algorithm with WEKA

With the enormous growth of security incidents in computer networks, the network security defense has gained significant attention from the information industry and network community. Firewalls are the first lines of defense for protecting computer networks and important information. They function as routers to connect different network segments together. Furthermore, they considered as the most important elements in the networks used by organizations to enforce their security policy. The security policies of enterprises and companies are implemented as firewall rules. These firewall rules are sensitive and any misconfiguration of them will cause anomalies. The subject of mining of frequent patterns in itemsets of the dataset is considered as one of the most important aspects in data mining technology. Apriori algorithm is the simplest and most powerful association rule mining (ARM) algorithms which can be efficiently used for mining frequent itemsets in the dataset. In this study, we proposed Apriori algorithm on WEKA to extract frequent itemset in the firewall logs to determine the best association rules that ensure the general orientations in the dataset.
Theory for non-theoreticians

tutorial Share on Theory for non-theoreticians: introductory tutorial Author: Benjamin Doerr École Polytechnique, Palaiseau, France École Polytechnique, Palaiseau, FranceView Profile Authors Info & Claims GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference CompanionJuly 2019 Pages 523–549https://doi.org/10.1145/3319619.3323373Published:13 July 2019Publication History 0citation75DownloadsMetricsTotal Citations0Total Downloads75Last 12 Months5Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Development of Model for Load Impacts to the Database

The article describes some of the results of database performance studies, identifies features of the influence of some factors on their functioning. The wording of the problem is fulfilled and the ways of their solution are indicated. Also, a model of the element as the main component of the load impacts is proposed. The input and output parameters of the element for load impacts are shown, and their characteristics are provided. An example of load impacts using the software tool for testing open MySQL database connections is given.
“We Are Actively Reaching Out to Different Organizations and Folks to Come in”: Collective Design of the Vancouver Tool Library Project

This paper reports on a case study that describes the collective design process of the Vancouver Tool Library, a non-profit community service cooperative that provides tools to its members in the city of Vancouver. By using the theory of infrastructuring in relation to the theoretical framework publics (Le Dantec 2016), we describe the project through its confronted issues and the emerged work of infrastructuring in the project. We also reflect on the infrastructuring work and analyze the characteristics of the collective design in the Vancouver Tool Library project. On the one hand, this research highlights the aspects of the design process in which interaction designers can play a significant role and further support the collective design in a community-based project. On the other hand, applying the notion of infrastructuring to the collective design of community-based project provides an opportunity to extend the understanding of design toward a more dynamic and open-ended process where conflicts, standards, and adaptions are interwoven within an infrastructuring process.
Breaking News Recognition Using OCR

Identifying and recognition of breaking news in most of the TV channels in different backgrounds with varying positions from a static image plays a significant role in journalism and multimedia image processing. Now a days it’s very challenging to isolate only breaking news from headlines due to overlapping of many categories of news, keeping all this in mind, a novel methodology is proposed in this paper for detecting specific text as a breaking news from a given multimedia image. Basic digital image processing techniques are used to detect text from the images. The methods like MSER (Maximally Stable Extremal Regions) and SWT (Stroke Width Transform) are used for text detection. The proposed work focuses on extraction of text in breaking news images also discusses the different methods to overcome existing challenges in text detection along with different types of breaking news datasets collected from various news channels are used to identify text from images and comparative study of different text detection methods. The comparative study proves that MSER and SWT is a better technique to detect text in images. Finally using OCR (Optical Character Recognition) technique to extract the breaking news text from the detected regions will help in easy indexing and analysis for journalism and common people. Extensive experiments are carried out to demonstrate the effectiveness of the proposed approach.
How much has technology dehumanized us in school

The world of education is changing and the changes affect all its aspects. The development of education is directed toward learning processes that aim at acquiring basic knowledge, the capability to solving problems and preparing one for the challenges of the future by developing skills and lifelong learning. In this context, the information and communication technology has made great progress. Today, after we started using computers in teaching and learning, we ask ourselves how much we gained and how much we may have lost in the process. This paper researches and analyzes the attitudes of the teachers to the use of ICT in teaching and the use of computers in learning. In our efforts to direct education towards the labour market and look at certain professions from that aspect, we grow distant from Humboldt's concept of education and lose the humanistic aspect. How do we maintain education as a development of independence, competence, innovativeness, capability to maintain and renew skill by shaping better and more humane mutual social relationships. Today, considering the needs and demands of the modern world, the orientation of education toward ICT seems necessary and inevitable. The question is where does one set the limit. This paper addresses the importance of ICT in teaching and education. Special attention is given to the issue from the aspect of national minority schools where the use of ICT means a more open and cheaper access to study materials from the country of origin, while from the aspect of teaching we shall address the issue of ICT competition for teachers. The aim of this paper is to present the usage of ICT in teaching and learning as well as the attitudes of teachers and students.
Identity Credibility Evaluation Method Based on User Behavior Analysis in Cloud Environment

The openness, dynamics, randomness and other characteristics of cloud computing make the malicious attack in the cloud environment more destructive and influential than the traditional environment. Existing identity authentication technology can verify the legality of user identity in the cloud environment. But, it cannot prevent the malicious user who is stealing a legitimate identity to carry out an attack or legal user's illegal behavior. That is, the user identity is legal but we cannot guarantee that the user must be trusted. Therefore, in order to achieve a quantitative assessment of the user's identity credibility and identify the user type, this paper proposes an identity credibility evaluation method based on user behavior analysis. It is designed to analyze user behavior to determine its identity credibility. This method uses fuzzy analytic hierarchy process to weaken the subjectivity of credible evaluation, and uses multi-partite graph model to construct an intuitive credible judgment basis. At the same time, the identity credibility evaluation strategy is introduced to quantitatively analyze the credibility of user identity. Experiments show that this method can effectively evaluate the credibility of user identity, meet the needs of cloud service providers for user classification management, and achieve moderate security.
An Improved Multidimensional Query Language for Oil and Gas Development Data Warehouse

Abstract Multidimensional data analysis is the most central technique for processing data in data warehouse and On-Line Analysis Processing (OLAP). In order to solve the problem of multi-dimensional analysis expression and query processing in oil and gas development data warehouse, this paper proposes an improved multi-dimensional query language application method to realize effective interaction between query terminal and OLAP server. This formal language has the following advantages, such as simplicity, flexibility and easy to use. It also meets the needs of multi-dimensional query for oil and gas data analysis, and has various display modes. The results can be displayed in two-dimensional space. And it provides an extended function beyond the standard MDX, simple grammar format, concise and clear semantic expression, and is conducive to query processing conversion.
Cops and Robber on Some Families of Oriented Graphs

Cops and robber game on a directed graph $$\overrightarrow{D}$$ initiates by Player 1 placing k cops and then Player 2 placing one robber on the vertices of $$\overrightarrow{D}$$ . After that, starting with Player 1, alternately the players may move each of their tokens to the adjacent vertices. Player 1 wins if, after a finite number of moves, a cop and the robber end up on the same vertex and Player 2 wins otherwise. However, depending on the type of moves the players make, there are three different models, namely, the normal cop model: both cops and robber move along the direction of the arcs; the strong cop model: cops can move along or against the direction of the arcs while the robber moves along them; and the weak cop model: the robber can move along or against the direction of the arcs while the cops move along them. A graph is cop-win if Player 1 playing with a single cop has a winning strategy. In this article, we study the three models on some families of oriented graphs and characterize the cop-win directed graphs for the third model.
3D Regional Shape Analysis of Left Ventricle Using MR Images: Abnormal Myocadium Detection and Classification

Accurate detection of abnormal myocardium regions is essential for differential diagnosis of cardiovascular disease. However, to achieve this goal by image analysis will significantly increase the burden on radiologists who is already overwhelmed. To ease the time and energy-demanding process and enhance the reproducibility, we proposed a novel framework for automatic abnormal shape detection on left ventricular (LV) using MR images. Our proposed approach utilizes the features obtained by large deformation diffeomorphic metric mapping (LDDMM). To take advantage of 3D structural information, we introduce multilinear principal component analysis (MPCA) in the framework to reduce feature dimensions. Then we combine MPCA with linear discriminant analysis (LDA) to perform differential diagnosis. The performance of proposed framework is evaluated on patients' images. In the classification of three common cardiovascular diseases, our proposed method outperformed traditional classifiers (Global point signature, Random Forest and XGBoost) with an accuracy of 94%. To further automatically detect the dysfunctional heart regions, we did a comparison on 3D morphology between the diseased subjects and healthy controls and performed an automatic visualization of the abnormal myocadiac regions. In conclusion, our proposed framework reserves the spatial information of the features generated through LDDMM registration and enables the 3D visualization of abnormal regions of LV. With the advance of our method, differential diagnosis is successfully performed on patients with different cardiovascular diseases.
Infer Creative Analogous Relationships from Wikidata

Making analogies is an important rhetorical device. Analogies can not only help explain new concepts, but also make the expressions more interesting and creative. In our previous work, we explored an automated approach for making analogies using data from knowledge graphs where concepts are connected by their relationships. The algorithm computes how analogous two relationships are to each other based on the structural similarity of their adjacent concepts and relationships. The analogous relationships are then used to construct analogies between two concepts. In this work, we study how people’s impressions of the analogies are affected by how the analogies are presented. We hypothesized that the analogy between a pair of relationships will be perceived as stronger when it is presented in a group of analogous relationship pairs for supporting making an analogy between two concepts than when it is presented alone. This hypothesis is confirmed by our empirical study. In addition, we found that people’s impressions of how creative the analogy between a pair of relationships is not affected by how they are presented.
Flipping the Second Year Pre-Service Chemistry Teacher Classroom

This chapter is a recount of the author's experiences in flipping his second year Chemistry classroom during the #Fallism movement at a University of Technology in South Africa. The main aim of this chapter is to narrate how the author used online-platforms, such as Blackboard, social media (WhatsApp), and YouTube, to not only complete his curriculum during this period but also how he used these Web 2.0 applications to support his students in completing their tasks. In this chapter “support” refers to how the author used various online tools (Blackboard, WhatsApp, YouTube) to communicate, design, and develop his lessons, and present them with their associated assessment tasks. A direct consequence of this flipped classroom model was self-directed and deeper learning in Chemistry.
Intermediated Reality: A Framework for Communication Through Tele-Puppetry

We introduce Intermediated Reality (IR), a framework for intermediated communication enabling collaboration through remote possession of entities (e.g. toys) that come to life in mobile Mediated Reality (MR). As part of a two-way conversation demonstration, each person communicates through a toy figurine that is remotely located in front of the other participant. Each person's face is tracked through the front camera of their mobile devices and the tracking pose information is transmitted to the remote participant's device along with the synchronized captured voice audio, allowing a turn-based interactive avatar chat session, which we have called ToyMeet. By altering the camera video feed with a reconstructed appearance of the object in a deformed pose, we perform the illusion of movement in real-world objects to realize collaborative tele-present augmented reality (AR). In this turn based interaction, each participant first sees their own captured puppetry message locally with their device's front facing camera. Next, they receive a view of their counterpart's captured response locally (in AR) with seamless visual deformation of their local 3D toy seen through their device's rear facing camera. We detail optimization of the animation transmission and switching between devices with minimized latency for coherent smooth chat interaction. An evaluation of rendering performance and system latency is included. As an additional demonstration of our framework, we generate facial animation frames for 3D printed stop motion in collaborative mixed reality. This allows a reduction in printing costs since the in-between frames of key poses can be generated digitally with shared remote review.
Evaluation of the Impact of Mobile VR Interaction Methods on Performance, Preference, and Enjoyment

Virtual Reality (VR) has expanded from the training and high-end entertainment world into the homes of everyday users through mobile head mounted displays (HMDs). Currently, several different interaction methods for mobile VR HMDs exist, including remotes, external controllers, motion controllers, touch, and free form hand tracking. The goal of this study was to evaluate the impact that these interaction methods have on specifically mobile VR HMD user experience, including performance, user preference, and enjoyment. It was hypothesized that interaction methods would vary significantly in enjoyment, preference, and performance as many factors such as ease of use and familiarity can influence these factors. To evaluate the interaction methods, participants performed trials of a matching task utilizing menus in a VR environment in which the participants selected the features of an object (e.g., shape, color, pattern) from a menu to the right of the object. The Leap Motion had usability issues that impacted it’s performance and enjoyment scores resulting in it being the poorest performer of the group. Overall the gamepad was most preferred and performed the best due to its ease of use and familiarity, but the touchpad and leap motion offered immersive aspects. These results highlight the importance of ease of use in interaction methods and the impact it has on overall user experience. This paper will discuss these results and implications for design of interaction methods and associated VR HMD controllers.
Design &amp; Development of Well Site Drilling Information System used in South Azadagan

Abstract Based on our experience and successe in the development of drilling information management software as well as our understanding of the South Azadagan well site situation in Iran, the South Azadagan Well Site Drilling Information Management System has been designed. Through the establishment of database of DIMS, the integrated well site drilling information management and application system is developed. In the process of collaborative information management under network environment, a convenient and unified data manage and analysis platform for well site drillers in different Rigs has been provided. This paper describes the design and development of South Azadagan Well Site Drilling Information Management System in detail.