Reviewerly/exHarmony huggingface dataset:
Follow the Title Then Read the Article: Click-Guide Network for Dwell Time Prediction

In article recommendation, the amount of time user spends on viewing articles, dwell time, is an important metric to measure the post-click engagement of user on content and has been widely used as a proxy to user satisfaction, complementing the click feedback. Recently, the sequential pattern of impression-click-read has become one of the most popular type of article recommendation service in real world, where users are presented with a list of titles at first, then get interested in one and click in for reading. Predicting dwell time in such service is conditioned on the click, since the user reads the article only after he clicks the corresponding title. We argue that conventional models for dwell time prediction, which mainly focus on the relevance between the content and the general preference of user, are not well-designed for such service. There is a natural assumption in recommendation system that the click indicates user's getting attracted by the item. Therefore, in the pattern of impression-click-read, the user might get interested and curious on some other concepts different from his general preference while reading, due to the attraction of the title. Conventional models tend to ignore the gap between such temporary interest and the general preference of user in the reading behavior, which fails to use the pattern of impression-click-read and the assumption of the click very well. In this work, we propose a framework, Click-guide Network (CGN) for dwell time prediction, which makes good use of the sequential pattern and the assumption to model the ”guidance” of the click on user preference. CGN is a joint learner for dwell time and click through rate (CTR). We introduce the CTR task as an auxiliary task to help us better learn the preference of user and the representation of title. Besides, we propose the Guider to capture the user's temporary interest raised by the title. We collect the data from WeChat, a widely-used mobile app in China, for experiments. The results demonstrate the advantages of CGN over several competitive baselines on dwell time prediction, while our case studies show how the Guider effectively capture the temporary interest of user.
A Technique for Estimating Updated Frequent Itemsets in ESC-Growth Algorithm

In discovering association rules from a dynamic database, iteration through the frequent itemsets requires significant resources and computational time for construction of sub-trees, sub-tree traversal and generation of conditional pattern bases, and it is quite possible that no updated frequent itemsets may have been found at all, resulting in a waste of resources and computational time. We describe a technique for estimating the support count for the itemsets for the next iteration of discovery of the frequent itemsets by our ESC-Growth Algorithm. This technique reduces the need to construct a new sub-tree and next discovery step. If no frequent itemsets in the updated database have been found in the next iteration, ESC-Growth will not construct a new sub-tree and will stop discovering new frequent itemsets in that iteration, reducing the waste of resources and computational time. We measured execution time and sub-tree counts for FP-Growth, FUFP-tree, FPISC-Growth and ESCGrowth on the same synthetic dataset; we found that, at 5% minimum support threshold, ESC-Growth used only 40.3, 96.5, and 99.6% of the execution time required by FP-Growth, FUFPtree and FPISC-Growth, respectively.
A New Approach of Intuitionistic Fuzzy Membership Matrix in Medical Diagnosis with Application

Concepts of fuzzy set theory and intuitionistic fuzzy set theory have become interesting and important areas of research in the field of medicine in recent times. Particularly, the application of intuitionistic fuzzy sets has been very impressive in the discrimination analysis for diagnosis of sickness and symptoms of many diseases. Intuitionistic fuzzy sets and intuitionistic fuzzy membership functions are extensively applied for improving knowledge-based structure in medicine for various instances of medical diagnosis. Using the idea of fuzzy matrix, many mathematicians (e.g. Sanchez 1976, 1979) formulated the diagnostic models characterizing the medical knowledge between symptoms and diseases. Similarly, some important models using intuitionistic fuzzy sets were developed (Samuel and Balamurugan 2012). In the present work we construct and establish a modified model for medical diagnosis to deal with some complicated features of medical issues using intuitionistic fuzzy membership matrix. This work develops a new approach of performing medical diagnosis with the help of intuitionistic fuzzy membership function. Further, we provide study-based examples of medical diagnosis to demonstrate the validity of proposed model.
Reward-based evolutionary swarm UAVs on search and rescue mission

Search and rescue missions (SARs) are challenging in a harsh environment especially on a sea surface. Currently, swarm robotics incorporating group of autonomous aerial vehicle (UAVs) can cover greater search area than one autonomous vehicle more efficiently if correctly programmed. An ongoing study applying a rewards-based system to an evolutionary swarm (ES) to enhance its searching capability in a harsh environment is reported in this paper. However, the evolutionary method utilising fitness function to tackle tasks in such environments often gives a deceptive result, because the predefined objective function is fixed. The fitness function for the evolutionary mechanism should not be fixed for a useful result to be obtained. In this study a rewards-based system is used to investigate a method to overcome these deceptive results. Results and comparison between fitness-based and rewards-based ES on SAR mission are discussed in this paper and preliminary results reported on.
A status assessment model for dynamic system based on cloud evidence reasoning

In order to ensure the safe and efficient operation of dynamic system in engineering practice, solve the common problems such as nonlinearity, timeliness and uncertainty in realtime status tracking during system operation. This paper studies a status assessment model for dynamic system based on cloud evidence reasoning. Based on the traditional evidence reasoning model, cloud model is introduced to enhance the description ability of expert knowledge in the model. Considering the operating environment of dynamic system in engineering practice, the uncertainty information in operating process is described and quantified by defining static reliability and dynamic reliability. Finally, the effectiveness and correctness of the method are verified by the High-Speed train running gear system.
Research and Software Implementation of Document Service System Based on Cloud Platform

Abstract With the explosive growth of various types of documents, these resources have been collated and utilized to become a concern of the industry. This paper builds a cloud computing platform based on OpenStack, and implements a document service system based on the built cloud computing platform. The administrator can perform state monitoring and management operations on the implemented document service system, and the system user can delete, search and classify the document. This research has greatly improved the use of documents and the level of scientific research.
COMPLEXING IMAGES IN A TWO-CHANNEL OPTICAL-ELECTRONIC SYSTEM AS A METHOD OF REDUCING THE PROBABILITY OF DISAPPOINTING AN AUTOMATIC SURVEILLANCE OF LOW CONTRAST OBJECTS

The paper discusses the work of the correlation algorithm for automatically tracking objects of interest in a two-channel optical-electronic system in a complex background-target environment and the presence of intentional interference. Conditions in which the contrast of the desired object in both channels is negligible but not equal to zero are considered difficult in the paper. Intentional interference refers to masking interference of natural and artificial origin, which helps to reduce the contrast of the object in both channels. By two-channel means an optical-electronic system, which includes channels of the visible and infrared ranges. It is believed that the multi-spectral images of both channels are reduced to a single time and scale, which allows them to be integrated using various methods. The purpose of this paper is to prove that the likelihood of disruption of automatic tracking is reduced when complexing the source images of the visible and infrared ranges, when the contrast of the desired object in both channels is negligible. For research the mathematical apparatus of the theory of random functions and simulation with subsequent statistical data processing are used. It is shown that the probability of disruption, characterized by the ratio of the correlation coefficients of two fragments of images, one of which contains the desired object, and the second not, depends on both the correlation coefficients and the values of their mean square deviations. The simulation shows that the breakdown of tracking occurs both when the mean square deviations of these correlation coefficients are equal, and at their different values, moreover, an increase in their difference increases the probability of a breakdown. The article shows that the likelihood of a breakdown in a two-channel optoelectronic system will decrease when using two channels, compared to working only in the visible or infrared channel. The obtained results substantiate the promise of using image complexing in multichannel systems of automatic tracking of objects in a complex background-target environment and the presence of deliberate interference.
Traceability Framework for Requirement Artefacts

In a bid to improve requirement traceability techniques, a framework is presented which aims to clarify the link between artefacts, stakeholders who deal with the software, SDLC models, and their stages by providing definitions and classifications. Through finding the missing links using a semantic traceability approach, risk within software project is minimised and the process better understood. Identifying the links will also improve traceability and in doing so support the software development lifecycle. The links found between the artefacts, stakeholders, and SDLC will be stored in an ontology so that they can be put to use in a framework. This paper will discuss why a conceptual framework is a suitable choice for the clarification of the links found. It also discusses the design of this framework, including its features and process. A description of why, to whom, and how this framework will be of benefit is provided. The potential contribution of the framework and its usefulness are also explained, whereby interviews on a target company are carried out and highlight where the tool developed could be improved, as well as the great advantages it provides. This study thus provides an important asset applicable to all sectors of software development.
The big short

School Science and MathematicsVolume 119, Issue 8 p. 429-431 EDITORIAL The big short Jonathan Norris Thomas, Corresponding Author Jonathan Norris Thomas jonathan.thomas1@uky.edu Mathematics Education, Department of STEM Education, University of Kentucky & The Kentucky Center for Mathematics Correspondence Jonathan Norris Thomas Mathematics Education, Department of STEM Education, University of Kentucky & The Kentucky Center for Mathematics Email: jonathan.thomas1@uky.eduSearch for more papers by this author Jonathan Norris Thomas, Corresponding Author Jonathan Norris Thomas jonathan.thomas1@uky.edu Mathematics Education, Department of STEM Education, University of Kentucky & The Kentucky Center for Mathematics Correspondence Jonathan Norris Thomas Mathematics Education, Department of STEM Education, University of Kentucky & The Kentucky Center for Mathematics Email: jonathan.thomas1@uky.eduSearch for more papers by this author First published: 21 December 2019 https://doi.org/10.1111/ssm.12377Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume119, Issue8December 2019Pages 429-431 RelatedInformation
Hardware and User Perspective Assessment on Application of Smart Door Access

Abstract Nowadays, applications of technology in various aspects of human life have been widely adopted. This increasing application relies on the degree of technology involvement, which supports an interconnected communication among resources available in the location. Smart room is a room equipped with technology where electronic devices contained in it can connect and communicate with each other so that it becomes a system that can be controlled thoroughly. One part of the smart room is the door. The door can be accessed using a variety of technologies. some of them are RFID tag technology, PIN code, Fingerprint technology, and Infrared sensor technology. This study discusses the satisfaction of smart room users about the time, distance and technology used. System 1 uses RFID tag technology, and Infrared sensor, and on system 2 uses RFID tag technology, PIN code, Fingerprint technology, and Infrared sensor technology. The time used is 10 seconds on system 1 and 3-6 seconds on system 2 is considered sufficient. The distance of around 3.5 -4.2 is also considered quite good and is also considered to be close. The use of RFID tag technology, PIN code, Fingerprint technology for incoming access and Infrared sensor technology for outgoing access is considered appropriate. Respondent satisfaction in system 1 was around 79% and in system 2 around 74%. System 1 is the most desirable technology, then system 2, then the door with conventional locking.
Approximated Scale Space for Efficient and Accurate SIFT Key-Point Detection

The SIFT (scale invariant feature transform) key-point serves as an indispensable role in many computer vision applications. This paper presents an approximation of the SIFT scale space for key-point detection with high efficiency while preserving the accuracy. We build the scale space by repeated averaging filters to approximate the Gaussian filters used in SIFT algorithm. The accuracy of the proposed method is guaranteed by that an image undergoes repeated smoothing with an averaging filter is approximately equivalent to the smoothing with a specified Gaussian filter, which can be proved by the center limit theorem. The efficiency is improved by using integral image to fast compute the averaging filtering. In addition, we also present a method to filter out unstable key-points on the edges. Experimental results demonstrate the proposed method can generate high repeatable key-points quite close to the SIFT with only about one tenth of computational complexity of SIFT, and concurrently the proposed method does outperform many other methods.
Open access to US federally funded research still lagging

US agencies have not fully implemented a plan to give the public free access to federally funded research, according to a report from the Government Accountability Office (GAO), the research branch of Congress. In 2013, the Office of Science and Technology Policy (OSTP) directed all agencies that annually fund over $100 million in research to develop a plan to make the resulting publications and data freely available to the public. All 19 agencies the GAO questioned for the report have identified repositories where researchers can put that information. But the GAO found that 11 have no way to ensure that scientists are actually placing information into those repositories. In addition, 4 haven’t required that all researchers create a data management plan for how to preserve and share their data, and 7 are lagging in making information easily accessible by the public, such as by creating a single point of access
On the estimation of correlation in a binary sequence model

We consider a binary sequence generated by thresholding a hidden continuous sequence. The hidden variables are assumed to have a compound symmetry covariance structure with a single parameter characterizing the common correlation. We study the parameter estimation problem under such one-parameter models. We demonstrate that maximizing the likelihood function does not yield consistent estimates for the correlation. We then formally prove the nonestimability of the parameter by deriving a non-vanishing minimax lower bound. This counter-intuitive phenomenon provides an interesting insight that one-bit information of each latent variable is not sufficient to consistently recover their common correlation. On the other hand, we further show that trinary data generated from the hidden variables can consistently estimate the correlation with parametric convergence rate. Thus we reveal a phase transition phenomenon regarding the discretization of latent continuous variables while preserving the estimability of the correlation. Numerical experiments are performed to validate the conclusions.
A Globally Sound Analytic Calculus for Henkin Quantifiers

This paper presents a methodology to construct globally sound but possibly locally unsound analytic calculi for partial theories of Henkin quantifiers. It is demonstrated that locally sound analytic calculi do not exist for any reasonable fragment of the full theory of Henkin quantifiers. This is due to the combination of strong and weak quantifier inferences in one quantifier rule.
General tendencies and priorities in the staff potential development in public libraries of Khabarovsk region and Republic of Belarus: the international cooperation experience

Sociological research “Human resources of public libraries: modern requirements for professional activity and opportunities for its implementation” was carried out by the Far Eastern State Scientific Library. It was made on the base public libraries in Khabarovsk region within the framework of the partnership and cooperation agreement with the National Library of Belarus. A comparative analysis of the results of the survey of employees in both libraries allowed to identify the characteristic features of personnel problems of public libraries of the Khabarovsk region, to assess the existing the library system of training, to show the level of professional selfassessment of employees, their willingness to accept new knowledge, to determine the professional competence that the managers and ordinary employees of libraries that would like to improve. Despite the geographical remoteness of the Khabarovsk region and Belarus, the peculiarities of social and historical development of the territories, the differences in the structure and density of municipal libraries network, the number of staff, the analysis of the results of the survey of library specialists showed the presence of common personnel problems in the library industry, regardless of the region and its social and economic well-being: the aging of the main staff in libraries, the shortage of specialized human resources and a significant number of specialists in related fields in library industry.
Data Mining Using Clustering Methods to Identify The Type of Lung Disease (Case Study: Siti Hajar Hospital)

Abstract In the process of grouping types of lung disease, doctors and staff Siti Hajar hospital experience the various obstacles encountered, including difficulties in grouping the data types of lung disease. This deployment planning analysis will help the hospital in analyzing data classification type of lung disease. This method of making use of data collection by taking data at the hospital.
Gauging variational inference

Computing of partition function is the most important statistical inference task arising in applications of graphical models (GM). Since it is computationally intractable, approximate methods have been used in practice, where mean-field (MF) and belief propagation (BP) are arguably the most popular and successful approaches of a variational type. In this paper, we propose two new variational schemes, coined Gauged-MF (G-MF) and Gauged-BP (G-BP), improving MF and BP, respectively. Both provide lower bounds for the partition function by utilizing the so-called gauge transformation which modifies factors of GM while keeping the partition function invariant. Moreover, we prove that both G-MF and G-BP are exact for GMs with a single loop of a special structure, even though the bare MF and BP perform badly in this case. Our extensive experiments indeed confirm that the proposed algorithms outperform and generalize MF and BP.
AN APPROACH TO RESEARCH IN HIGHER EDUCATION INSTITUTIONS THROUGH OPEN EDUCATIONAL RESOURCES

1 Universidad Autónoma Metropolitana, Unidad Lerma (MEXICO)2 Universidad Autónoma Metropolitana (MEXICO)3 Universidad Autónoma de Ciudad Juárez (MEXICO)
The framework accommodation of systems recommendation via social media

Abstract Tourists can plan trips using social media and other information sources found on the internet. However, to get information takes more time and efficient less. Recommendation systems have been developed to solve this problem. This research proposes the two-way relationship framework for the accommodation of systems recommendation using the hybrid method. To implementing the two-way relationship framework, this research is divided into two main architectural frameworks, the text processing architecture and the component system recommendation architecture. Focus this research for the framework component recommendations, where the decision-making process within the framework of two-way relationships using the hybrid method. The two-way relationship framework is probably to provide impression for the accommodation of system recommendation that can be developed and implemented in future research.
Application of Computer-Aided Diagnosis Algorithm in CT Images of Urinary Calculi

Abstract In recent years, computer-aided diagnosis has developed from pure theory to clinical trials, which has proved its feasibility and applicability in the diagnosis of breast cancer and pulmonary nodules. Therefore, combined with the actual medical background, computer-aided diagnosis is used in the analysis of urinary calculi components in patients, and the composition and structure of calcium oxalate calculi and anhydrous uric acid calculi are accurately analyzed, which has important guiding significance for the clinical treatment and prevention of urinary calculi.
The End of Strategic Leadership: Be Extelligent or Extinct

One of the main forms of building worldwide is gated communities. Because of the Internet of Things, there will be zones where citizens lease all services for a fixed fee. The citizens entitle service providers to enrich, digitize, and personalize these data sets. In this system, citizens engage with their personal controllers - a dedicated smartphone doubling as a passport - through dedicated platforms in a single set of federated and potentially decentralized Clouds. Citizens accept the semi-autonomous decision in their health, home, mobility, and smart city domain, but in politics, the narrative is fully drenched in emotional and socio-cultural, sometimes even religious arguments. Citizens are keeping RMB 140 trillion in the bank, saving as they are unsure where to invest. People who have money to invest enter into meaningful relationships with fellow citizens, who need money to make new infrastructure, services, and applications.