Reviewerly/exHarmony huggingface dataset:
Machine Learning Methods Based on Convex Hulls Analysis in Medical Diagnostics Tasks

The methods of machine learning using the apparatus of computational geometry are investigated. The use of convex hulls of sets in a multidimensional feature space allows implementing algorithms for visualization of class intersection area, reduction of feature space dimension and classification algorithms. A method of measurement of convex hull proximity to test point, if the test point is within the convex hull, is proposed. It is based on assessment of directional penetration depth of convex hull vertices projected onto the direction vector from this point to class centroid. Nearest convex hull algorithm, based on the proposed simplified method of assessment of proximity to convex hull, is described. Results of classification for breast cancer diagnosis task solution are presented. The results showed sufficient efficiency of the proposed methods..
An Image Processing Based Approach for Monitoring Changes in Webpages

As the website content is changing dynamically and many users rely on change detection and notification-based systems. Prominent ones are crawling-based change detection and notification systems. But this system has drawback, such as requirement of huge computational resources, which make them a poor choice for less frequently changing websites. In this paper, we propose, an alternative approach which is based on Image Processing and Image Comparison. The proposed system includes functionalities for fetching webpage from the Internet and allowing the users to select zone in webpages to monitor. Using Image Comparison Algorithm, two different versions of webpage captured at different time, are compared and the modified portion of the webpage is highlighted. This approach is validated with the help of prototype implementation.
Application of Cognitive Changes Markers for Diagnostics’ Purposes and in Neurofeedback Therapy

Thanks to the automation of diagnostic processes based on the EEG signal and the creation of classifications of various attention disorders based on the analysis of the EEG signals (as diagnostic markers) - it may be possible to refer patients to appropriate specialists and provide them with appropriate neurofeedback-based treatment. The marker method proposed by the authors of the hereof paper is based on analysis of the EEG, which signal can be widely use in screening diagnostics. The proposed solution in this work may be used for neurofeedback or Brain Computer Interfaces (BCI). In this paper the authors presented implementation of markers for the purpose of analysis of some memory disorders and short-time attention disorder. The study is still in progress. Presented results have initial-study character.
A Novel Method to Improve Hit Rate for Big Data Quick Reading

In big data mining analysis, the data records in the dataset are randomly retrieved. The distributed storage modes, such as BigTable, HBase, provide the cache policy for file blocks in retrieval operations. Since these records are scattered in different file blocks, the block cache does not have a high hit rate. To deal with the above problem, we propose an LRU-based double queue K-frequency cache method (DLK). The method presents a double queue storage structure, applying different storage and eviction rules for the data with varying access frequency (i.e., high/low access frequency). While the method divides the memory into data area and list area and adopts different data structure to reduce the time of data retrieval and data processing. The experimental results show that proposed method can reduce retrieval time by 30% with the cache mechanism. Compared with existing methods DLK can improve the hit rate by 60.1% and reduce the retrieval time by 43.5%. While applying in smaller cache capacity, our method outperforms other algorithms.
Cross-Project Code Clone Consistency Prediction

There are large numbers of code clones in software, which are introduced by developers to speed software development. Due to the similarity of code clones, consistent change usually happens to code clones, which can lead to extra maintenance cost and/or consistent-defect. To address this problem, researchers have proposed approaches to predict the requirement of consistent change. Although their works have good predictive effectiveness within one project, there is not enough data to make such prediction at the beginning phase of development. Therefore, in this paper, we first try to make use of the data from cross-projects and propose an approach to predict cross-project clone consistency-requirement. We construct the experiments on four open-source projects, and the results show that the cross-project prediction can be employed for clone consistency prediction. What's more, we suggest that the scale of data have not a significant impact on the effectiveness prediction.
o-LPMLN: A Combination of LPMLN and LPOD

Nowadays, our lives are surrounded by various information, where large pieces of information are uncertain even inconsistent. And in user-oriented applications, users’ preferences should also be taken into account. Therefore, for knowledge-based systems, it is significant to find a knowledge representation and reasoning tool that is able to handle uncertainty, inconsistencies, and preferences. In this paper, we present a logic formalism o-LPMLN that is created by introducing ordered disjunctions in LPMLN. LPMLN provides a powerful framework to handle uncertainty and inconsistencies by combining the ideas of Answer Set Programming (ASP) and Markov Logic Networks (MLN); and logic programming with ordered disjunctions (LPOD) is a simple yet effective way to handle preferences in ASP. By combining LPMLN and LPOD, o-LPMLN is able to handle uncertainty, inconsistencies, and preferences in a unified framework. After defining the language o-LPMLN, we present two modular translations from o-LPMLN to LPMLN and LPOD respectively, which leads to some solving algorithms of the language. Due to the close relationship between o-LPMLN and LPOD, the translations also present an approach to implementing LPOD via using LPMLN solvers. Throughout the paper, we use a prototype application to show the knowledge representation and reasoning with o-LPMLN, which can be regarded as a start point of further work.
LibGuides: Information Technology Help: Microsoft Office

Resources to help Central Penn College students navigate the technology required in their courses.
Effect of Smart Device Ability on the Smart Device-Based Testing National Board Examination for Optometry Students

Purpose : This study is an empirical research study aimed at verifying the effect of smart device utilization capability on smart device-based national test recognition. Methods : The survey was conducted among 60 optometry students, who will be take a National Board examination. The survey contained 15 items scored using a 5-points Likert scale. Results : Apart from the information and documentation capabilities among smart device utilization, the recording, communication, management and multimedia capabilities showed a significant positive correlation with the recognition of smart device-based test. In addition, smart device utilization capability is explained to be about 46% in positive recognition of Smart Device-based national testing, and multimediaization capability among the smart device utilization was significant influence on the recognition of smart devices-based on the national test. Conclusion : This study secured the feasibility of developing multimedia questions and introducing smart device-based national test, relied on smart device-based national tests with multimedia items for who preparing national test by supplementing the problems of smart device-based national test systems. Also, this may affect the change of positive perception.
Repeated Values on Collections Harvested using the Open Archive Initiative Protocol for Metadata Harvesting

Libraries use repeated values to always denote each entity or group of entities in a specific way. When resources have metadata elements with the exact same value, their correlation is made obvious, making the retrieval of all matching metadata records easier. The library uses guidelines on which metadata elements should only use controlled terms, and how these values will be selected. In this paper, we study the use of the repeated values in many collections and also their effectiveness when all the collections are used together. We discovered values that are repeated often and values that are unusual, misused or just rare. Many metadata elements may use controlled terms as values, although they are traditionally used mostly in some of them. We see the differences on the use of the Dublin Core elements. The lack of coordination among collections results to many variations for each value. The study reveals the current usage of repeated values in active collections and helps adopting better guidelines, designing better tools and improving the effectiveness of the collections.
Real-world applications and implementation of Keystroke biometric system

keystroke dynamics authenticates the system user by analyzing his typing rhythm. Given that each of us has his own typing rhythm and that the method is based on the keyboard makes it available in all computer machines, these two reasons (uniqueness and reduced cost) have made the method very solicit by administrators of security. In addition, the researchers used the method in different fields that are listed later in the paper.
Alcune osservazioni sulle strutture genitivo-locative, strumentali e comitative in russo e le proprietà di inclusione (sottoinsieme/soprainsieme)

In this paper I will argue that the behaviour of Russian oblique cases can be dealt with in terms of ‘zonal inclusion’ properties, whereby the Instrumental encodes inclusion ( part-of , contained-in relation ) of the inflected noun into the denotation of its sister projection; Genitive, Dative and Prepositive lexicalize the opposite relation (container, possessor, etc.). I will also maintain that prepositions are just modifiers of the inflectional head, thus unifying a preposition selecting for multiple cases like s (with apparently idiosyncratic meanings: ‘with’, ‘from’, ‘of-the-same-size-of’) under a single lexical entry.
Utility Evaluation Measures for Categorical Data by Classification Performance

In statistical disclosure control, global recoding is a typical masking method for categorical variable. When merging categories in global recoding, the decision of the minimum frequency ratio is essential from the point of view of both the reduction of the disclosure risk and the utility of masked data. Previous utility measures such as comparison of record value itself or contingency tables between original data and masked data can not evaluate masked data by global recoding. We propose a new information loss measure that can evaluate masked data by global recoding based on the model performance. Using the proposed information measure, we examined three hypotheses concerning global recoding, (a) when minimum frequency ratio increases, information loss increases, (b) when the number of input variable in model increases, information loss increases, (c) models yielding high performances in the original data suffer from large information loss by global recoding, by numerical experiments of the data of 2010 Population Census of Japan. For the performance measure by recall the hypotheses were supported, for that by accuracy, the hypotheses were supported, except for models that predicts a dominant category. Also, values of information loss for specific number of input variables and minimum frequency ratio are reported in our study. In the worst case, the mean of information loss of accuracy was 0.041, where the number of input variables was 4 and minimum frequency ratio was set at 0.05. These results provide useful insight for protected data publishers in deciding minimum frequency ratio, and for users conducting statistical analyses.
QoE Evaluation of Adaptive Video Streaming Algorithms in Multi-user Networks

Adaptive bitrate control (ABR) is an important technique for video streaming. This technique selects the video quality adaptively according to various network conditions, to ensure the quality of experience (QoE) for users. In the previous works, the ABR methods are mainly tested in single user environment. In this paper, an emulation testbed is constructed for QoE performance evaluation in multi-user networks. The state-of-the-art ABR methods are incorporated into the proposed environment. Emulation experiments are carried out to evaluate the performance of the methods. Preliminary results show that in FESTIVE, which has the least QoE variation in the six-user experiments, the user QoE of the worst case is only 27.5% of that of best case, demonstrating that the state-of-the-art ABR methods are not effective enough to optimize the QoE for all users under multi-user condition. Future design of the ABR method should take factors such as the fairness and resource allocation into consideration.
Coordinated Development of Coal and Water Resources Based on Big Data Analysis

Human beings have entered the stage of big data in the information age. How to use big data to serve all walks of life is a very worthy of discussion. This article thought that the mine well under - ground real-time monitoring data and mining production, living and ecological water demands as the research object, from the large data set up, management, analysis, and maintain the four aspects, combining the reality of mine work, using the large system decomposition-coordination principle and fuzzy hierarchy comprehensive evaluation method, the multi-objective dynamic programming model for nonlinear iterative simulation optimization, determine coal water - coordinate the development of new pattern and the underground water source water coal mining technology, mine Wells under - ground multi-objective efficient mixing technology, realizing the accurate, intelligent mine water utilization. Research method, this paper USES “Knowledgediscovery from GIS” and “Simonett rubik’s cube” concept, cyber GIS method is applied to build the mine Wells under - ground real-time monitoring to the big data is discussed, at the same time points out the characteristics of the coal mining situation of real-time, and possible problems are derived, which provide reference for other mines to establish large data.
Chinese-Foreign Cooperative Education Management System Based on Cloud Platform

In recent years, cloud computing technology has been widely used in the field of education in the country, especially in the field of higher vocational education. The education cloud platform based on the World University City has taken initial shape. And some teaching reforms based on cloud space are also in full swing. On the basis of introducing the concept of cloud computing and education cloud platform, and we give the application status of the current cloud platform. Some measures for applying the cloud education platform for teaching and management reform are proposed. Taking learning management as an example, the in-depth study of the Chinese-foreign cooperative education management system can achieve the purpose of improving teaching effectiveness and improving the quality of personnel training.
Keep Your Dimensions on a Leash

Automatic Cognate Detection helps NLP tasks of Machine Translation, Information Retrieval, and Phylogenetics. Cognate words are defined as word pairs across languages which exhibit partial or full lexical similarity and mean the same (e.g., hund-hound in German-English). In this paper, we use a Siamese Feed-forward neural network with word-embeddings to detect such word pairs. Our experiments with various embedding dimensions show larger embedding dimensions can only be used for large corpora sizes for this task. On a dataset built using linked Indian Wordnets, our approach beats the baseline approach with a significant margin (up to 71%) with the best F-score of 0.85% on the Hindi-Gujarati language pair.
OntoScene, A Logic-Based Scene Interpreter: Implementation and Application in the Rock Art Domain

Abstract We present OntoScene, a framework aimed at understanding the semantics of visual scenes starting from the semantics of their elements and the spatial relations holding between them. OntoScene exploits ontologies for representing knowledge and Prolog for specifying the interpretation rules that domain experts may adopt, and for implementing the SceneInterpreter engine. Ontologies allow the designer to formalize the domain in a reusable way and make the system modular and interoperable with existing multiagent systems, while Prolog provides a solid basis to define complex rules of interpretation in a way that can be affordable even for people with no background in Computational Logics. The domain selected for experimenting OntoScene is that of prehistoric rock art, which provides us with a fascinating and challenging testbed.
Body Architectures Real time data visualization and responsive immersive environments

This project sets up a design framework that promotes augmenting the human body's interactions exploring methods for merging and blending the users of physical and virtual environments, through the design of wearable devices that are embedded with sensors and actuators.This allows for haptic and visual feedback through the use of data that reflects changes in the surrounding physical environment, and visualized in the immersive Virtual Reality (VR) environment.We consider the Body Architectures project to serve as mechanisms for augmenting the body in relation to the virtual architecture.These wearable devices serve to bring a hyper-awareness to our senses, as closed-loop cybernetic systems that utilize `digitized' biometric and environmental data through the use of 3D scanning technologies and cloud point models, virtual reality visualization, sensing technologies, and actuation.The design of Body Architectures relies on hybrid design, transdisciplinary collaborations, to explore new possibilities for wearable body architectures that evolve human-machine-environment interactions, and create hyper awareness of the temporal, atmospheric qualities that make up our experience of space, as `sensorial envelopes' (Lally 2014).
College Students Interactive E-Poster Project Work

The article deals with the description of e-book maintaining that has interactive e-posters. The aim of such posters is to learn the presented tables of multiplying and dividing at primary school lessons for the second-year learners. The author describes the project work of students, the process of interactive e-poster detailed creation. The results of students` work are investigated at every step of e-resource creation. The workshop is of great importance for the future students` pedagogical activities. The author describes the created e-book and proves the importance of maintaining such educational facilities at primary school. Such facilities have highly estimated level, complexity and interactivity that become the most important aids for both students and school teachers at primary school at the lessons learning such topic as “Multiplying and Dividing Tables”. The scripts in the programming Action Script are developed by the author of the article. It caused the creation of this e-guide by means of Adobe Flash. Own technology for the design of interactive e-posters and methods of its usage were presented using the Adobe Flash system. The future teacher can create interactive electronic posters not only at Maths but also teaching other subjects.
Classification of GSM-R Network Operation Quality Evaluation Indicators Based on WDFCE Algorithm

Abstract This paper proposed a fuzzy clustering ensemble algorithm based on membership weighting and distance decision (WDFCE) and defined a method for determining the boundary threshold of indicators’ grade intervals. Base clusters and corresponding membership matrices were obtained by multiple fuzzy C-means (FCM) algorithm. Considering the reliability of each base cluster, the decision weighting method was introduced to weight the membership matrix and construct the cumulative distance matrix. The Density Peaks (DP) algorithm was used for clustering ensemble to obtain the final result. By defining the boundary zone, the boundary zone class density and the threshold possibility, the clustering result was combined to determine the grade interval of the indicators. In order to judge the advantages and disadvantages of the improved algorithm, the S_Dbw index with the best evaluation effect was selected from the various cluster validity evaluation indicators studied by domestic and foreign scholars. The results of the indicator S_Dbw for evaluating cluster validity indicated that the improved method we proposed is superior to the general clustering ensemble algorithm and it solved the problem of determining the boundary threshold of the indicator grade interval in the GSM-R evaluation system.
Segmentation of the Left Ventricle on EchoCG Images Using MultiResUnet

We compared the segmentation quality obtained with the following network architectures: Unet, Wide Unet, Unet++ and MultiResUnet. The MultiResUnet architecture has shown improved quality in other medical image segmentation tasks. It is applied to the problem of left ventricular segmentation for the first time. This architecture showed segmentation accuracy on augmented data equal to 92.78% by Dice metric. This is 1.3% more than the result of Unet++ and 2.5% more than the result of Unet. Also, this architecture showed a smaller variance of segmentation accuracy on cross validation: 1.2% vs. 1.4%.
Architecture for Video mapping Development: The Method and the Application in NMSPCAM

New media, such as projections using the video mapping technique, are increasingly used in public spectacles, attracting many viewers. However, those video mapping spectacles are highly focused on the special effects and visual appeal, rarely focusing in the art of a visual narrative, with the aim of communicating and diffusing historical knowledge. Interested in the unexplored potential of using this technique, the project established and proposed an Architecture for Video mapping Development (AVmD). It is divided in three parts, comprised of multiple stages and phases, tested during the development of an audiovisual production for a video mapping projection that took place in May 2019, as part of a project. The current article reveals the innovation introduced in the process of the proposed architecture, along with technical details for contents development, concerning storytelling and cultural heritage communication, in the real context of a video mapping project.
Research on Path Planning of Mobile Robot Based on Ant Colony Algorithm

With the continuous progress and development of robot technology, mobile robot application is also more and more widely used. The path planning is a prerequisite for the development of intelligent robot, it is a mobile robot capable of autonomous movement, the basis for the completion of complex motion. Therefore, the ant colony algorithm is proposed and applied to the mobile robot path planning problem. Path planning ant colony algorithm uses the grid method to establish the environment model, the use of ant colony algorithm to achieve path planning and obstacle avoidance of mobile robots, seeking the optimal path. Experimental results show that the above method has some validity and feasibility in the mobile robot path planning, and finally get the optimal path, complete path planning.