Reviewerly/exHarmony huggingface dataset:
ICU Mortality Prediction Based on Key Risk Factors Identification

Predicting ICU mortality and finding key risk factors make sense for both doctors and patients. Although there has been a number of research pertaining to ICU mortality prediction systems and algorithms, plenty of room still exists for improvement in practical prediction results and identification of important risk factors. In this study, we use C5 decision tree model to predict mortality of ICU patients and identify key risk factors. Totally 4367 records of ICU patients from a local grade-A tertiary hospital were selected for motality prediction, including 244 dead records with demographic information and physiological parameters. In order to solve the problem of inconsistent data sampling frequency, we extracted 96 statistical indicators based on the original records, such as the kurtosis value of red blood cells (HXB_kurt), the skewness coefficient of red blood cells (HXB_skew). Totally 41 indicators as the final input of the prediction model were extracted through feature extraction method. The experimental results show that C5 decision tree model outperform C&RT, CHDID, KNN, Logistic, SVM and Random Forest in five different performance indicators. Moreover, worst-case status and state of changes in respiratory, body temperature, care level, diastolic blood pressure and age were found to be the key risk factors.
Practical Differential Privacy for Location Data Aggregation using a Hadamard Matrix

Location data are very valuable personal information. These private data are frequently sent to servers to query relevant information to the users. Often aggregated location statistics are made publicly available for public resource planning, behavioral studies, or commercial usages. This raises privacy issues. Working under the differential privacy paradigm, Chen, Li, Qin, Kasiviswanathan, and Jin [ICDE'16] proposed a count estimation protocol called PCEP which ensures ϵ-local differential privacy and provides good frequency approximation based on the private succinct histogram protocol by Bassily and Smith [STOC'15]. We observe that, while providing an excellent theoretical guarantee, one of the key steps which essentially reduces location dimension, based on the Johnson-Lindenstrauss Lemma is not very helpful in practice as the actual dimension is even larger than the original dimension. We replace this step with the usage of Hadamard matrix. This results in more communication-efficient protocol (because the Hadamard matrix can be computed efficiently by the users) with theoretically improved approximation guarantee.
The Different Tools and Technique to Handle Challenges in Big Data

The big data are data in large size and which cannot be maintained in terms of bytes. Know a day's big data is so popular that almost every business is depends on data. The data can arise in various forms such as structured, unstructured and semi structured. The different sources of big data generations are through social media such as face book, Google forums, and search engines. These data will be used by different enterprises to make their decision making. Hence big data analysis is a big challenge because data is time variant. This paper presents different techniques used to process big data and various challenges faced by analysts while making decision making. This paper also gives description of various frameworks available to process a big data. The scope of this paper is to find best possible technique to process big data.
The Sharing Charging System Cloud Based on Bomb Back-end Cloud

as the increasing demand for mobile devices in modern society, the cruising power of these portable sets is woefully inadequate. In this paper, the study of charging system and sharing system on cloud based on Bomb Back-end Cloud is aimed at power using questions on resident trip, pollution reducing questions on high limit and offering sharing as entertainment to strengthen awareness of environmental protection and energy saving.
Object-based Normalized-Cuts for High-Resolution Polsar Image Segmentation

As more and more high-resolution PolSAR images being available, effective methods need to be studied for the processing of high-resolution PolSAR images. Since the complexity and speckle noise in high-resolution PolSAR image, traditional pixel-based image segmentation methods can result in heavy salt-and-pepper noise and the segments won't be in accord with the edge in PolSAR images. Object-based image analysis (OBIA) methods have been proven to be effective for high-resolution images. In this paper, a novel object-based image segmentation method for high-resolution PolSAR image is proposed, combining the superpixel algorithm and Normalized-Cuts segmentation (NCuts). The proposed method first generates original objects using simple local iterative clustering (SLIC) which is a new superpixel algorithm; and then Ncuts segmentation is implemented on the original objects to obtain refined object segments and reduce the computational complexity. In addition, both spatial information and polarimetric information will be introduced in the proposed method. Experiments using EMISAR image show that the proposed method can better preserve the edges and homogeneous regions on the image.
A Secure and Size Efficient Approach to Enhance the Performance of Text Steganographic Algorithm

Steganography is a fundamental and foremost approach that is used to ensure confidentiality of secret data. It is an art, which ensures invisible communication by concealing secret information in cover media through scientific techniques. The text steganography has a great challenge of security, robustness and size of stego text. In current studies, an improved, lightweight, secure, robust and size efficient technique is proposed for text steganography that also enhances the performance of existing approaches. To achieve the objectives, algorithm applies a conditional bit-complement function on binary value of confidential information. Moreover, start and end bits are also inserted during embedding secret information in cover text and confirms the integrity and confidentiality of secret data. Experimental results revealed that projected approach is more robust and secure without any stego key overhead. Furthermore, it has successfully achieved a size efficient stego text. Therefore, the secret information exhibits harder to track
Using chatbots to compare drug prices extracted in real-time from the web

In this paper we present a chatbot for the medicines information consultation. The system presented aims to act as a single access point for the natural and simplified information retrieval of medicines, its prices and risks, democratizing the access to knowledge and promoting the conscious consumption of medicines. The chatbot has two modes of operation: Quick Response and Interactive modes. The first answers questions asked in natural language, while the second has three interactive tasks, namely Navigation, Query and Price Comparison. In this work, we focus on the presentation of the system architecture and the Price Comparison task. This task presents the best prices for medicines and their best possible substitutes extracted in real-time from web with the help of information obtained from a linked data mashup. The work is still under development, however in this paper we present the results of preliminary assessments and possible directions for future work.
The Use of Information and Communication Technologies in the Training of Specialists in the Rear Profile of Institutions of the Penitentiary System

The article is devoted to the problems of implementation of practical training of specialists for the rear services of institutions of IP in the learning process. The article reveals the role of practice-oriented methods of training in the formation of the competence of specialists of logistics services. Particular importance is attached to the use of simulation programs with a practical orientation in the training of cadets of rear specialties. As a practical implementation of the task, the author proposes the creation of simulators of various technological processes using the Flash package as an example of creating a simulator of the KPU-250 boiler.
Analysis of Problems and Solutions in Integrated Management of Operating Room Supply Room

OBJECTIVE To explore the problems and measures of the integrated management of the operating room supply room in the treatment of surgical instruments. METHODS A total of 20 nursing staff working in the operating room of our hospital were selected as the research objects. All the patients were divided into observation group and control group by random number method. The control group was treated with routine management intervention. The observation group was managed by integration. The quality of sterilizing and sterilizing operation instruments, the satisfaction of the staff in the operating room and the supply room and the interval time of operation were compared between the two groups. RESULTS After the integrated management of the operating room and the supply room, the sterilizing and sterilizing quality of the surgical instrument package, the operation room and the supply were carried out. The satisfaction degree of the staff was significantly higher than that before the integrated management, and the interval time of operation was shorter than that before the integrated management. CONCLUSION The integrated management of operating room and supply room can effectively improve the quality of surgical instrument package, maximize the utilization of all resources, and improve the working efficiency of operating room, which is worth popularizing.
Efficient Retrieval of Knowledge Graph Fact Evidences

We report preliminary results on the problem of efficient retrieval of evidences for knowledge graph (KG) facts from large document collections. KGs are rich repositories of human knowledge and real-world events. To verify and validate facts about entities, it is often required to spot their evidences in large news archives or on the Web. To do so, KG facts can be translated to their natural language equivalent by using surface forms. Naïvely, attempting to search for all combinations of the aliases in large document collections is a time-consuming solution. We show that by using a combination of inverted indexes over n-grams and skip-grams we can return evidences in the form of sentences for KG facts within seconds.
Researchon Application of Network System to Nursing Management

With continuous advancement of society and rapidly development of science and technology, the Internet has become popular in all walks of life in society, especially in the medical system. Under the new situation, a traditional medical system has been unable to adapt to the current working methods and modern medical management system. In order to improve efficiency and quality of nursing management, in-hospital information network management can be implementedthrough establishment of nursing management network information system. As a result, the application of nursing management information system improves nursing management ability and work efficiency, saves cost of nursing management, and improves patients' satisfaction.
Hiding Sensitive Association Rules Using Modified Genetic Algorithm: Subtitle as needed (paper subtitle)

Association Rule Hiding is the Data Mining method which is used for extracting hidden information from huge dataset. In our paper, Two approaches are introduced. In first approach FP Growth Algorithm is being presented that generate association rules efficiently and it reduces time of forming frequent item sets every time. In second approach we have tried to hide sensitive association rules by Genetic Algorithm. Generally from large databases frequent items are extracted by applying different algorithms. In this paper, we compare all the algorithms for extracting frequent items which are Association Rule Mining, Apriori Algorithm and FP growth Algorithm. We also compare Fuzzy Logic Algorithms and Genetic Algorithm for hiding sensitive association rules.
Method for Sentiment Text Analysis based on Statistical and Semantic Properties of Words

In the paper the authors study text sentiment analysis. The research reviewed the existing methods for sentiment analysis. This analysis showed that the most frequently used for this purpose methods of machine learning (such as support vector machines) and classification by linguistic rules. For this reason, the authors decided to combine machine learning based on the statistical properties of the words and linguistic rules. The paper considers a method of sentiment analysis, based on a probabilistic model of the occurrence of words in documents. It proposes to extend this model through consideration of the semantics of words. For the method study, the authors used three collections provided by the organizers ROMIP: reviews of movies, reviews of books from site imhonet.ru, reviews of cameras from Yandeks. Market. The method was further tested on a collection of blog posts provided ROMIP. The research showed that the generalized method based on statistical and semantic properties of the words occurrence in a document provides a fairly accurate assessment of sentiment text analysis.
Shopping Website Search System Based on Solr

In this paper, based on the project of automobile service electronic mall website, an efficient search system was constructed based on the open source search engine Solr. The test results showed that the average search time of Solr was 49.6 ms and that of database query was 159.4 ms. The average number of correct entries in the first 40 results was 33.8 in Solr and 13.4 in database query. Compared with the database search function, the search time of this system was shorter and the search result accuracy was higher.
Automata-Based Behavioural Contracts with Action Correlation

The rigorous design of Service-Oriented Computing (SOC) applications has been identified as one of the primary research challenges for the next 10 years. Many foundational theories for SOC have been defined, but they often rely on mechanisms different from real-world SOC technologies, hindering actual service modelling and verification. In this paper, we propose a novel automata-based formalism of service contracts equipped with a mechanism, inspired by current web service technologies, exploiting correlation data to drive service interactions and with formal foundations enabling reasoning about service correctness.
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In [6], Munemasa presented results concerning when a trinomial divides a trinomial in F2[x] and in [7], Panario, Sosnovski, Stevens and Wang presented a similar result for F3[x] along with a result for when a trinomial divides a binomial in the same polynomial ring. In this paper, by using a different technique from the one used in those papers, we generalize and extend these results to Fq[x] for any prime power q. We also provide results and conjectures resulting from a computer search for small q.
A Distributed Ledger Based Cyber-Physical Architecture to Enforce Social Contracts: Paper Cup Recycling

In this paper, we describe a distributed ledger re-cycling system to encourage responsible disposal of paper cups. A complete working prototype is described. Real measurements are presented to illustrate the potential suitability of the IOTA based distributed ledger for this application.
On some noncryptographic works of Goldwasser and Micali

research-article Share on On some noncryptographic works of Goldwasser and Micali Author: Oded Goldreich View Profile Authors Info & Claims Providing Sound Foundations for Cryptography: On the Work of Shafi Goldwasser and Silvio MicaliOctober 2019 Pages 527–542https://doi.org/10.1145/3335741.3335761Published:04 October 2019Publication History 0citation43DownloadsMetricsTotal Citations0Total Downloads43Last 12 Months1Last 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
I Know Where to Find What You Want: Semantic Data Map from Silos

Data-driven analysis is critically important for creating new insights and values; however, data silos prevent a full utilization of existing data. To overcome this issue, we propose Semantic Data MAP (SD-MAP). SD-MAP utilizes a virtual graph and conceptual groups to bypass a physical integration of databases while allowing users to access data using intuitive queries. In order to show our system’s effectiveness, we introduce a plausible scenario with a data structure from real world. A demonstration video of SD-MAP is available at: https://youtu.be/i7U_8763Ogk .
Fast Detection of Hidden Dangers in Transmission Line Corridors Based on Region Partitioning and Feature Extraction

Abstract Hidden dangers like large-scale construction machinery are the main causes of line trips. In this paper, we propose a fast detection algorithm for hidden dangers in transmission line corridors based on region partitioning and feature extraction. Since the scenes in the sky are simple and stable compared with the scenes on the ground, we detect hidden dangers in the sky and those on the ground separately. For hidden dangers in the sky, we firstly designed an algorithm to calculate the mask image for sky area. After dividing the sky area, we extracted features including colors and shapes of the difference areas in order to eliminate the interference factors. The targets left are the hidden dangers we truly cared about. For hidden dangers on the ground, firstly we design a pre-processing algorithm to eliminate the influence of uneven illumination on subsequent matching. Secondly, we propose a multi-scale gray-weighted average method to fuse multiple channels of multiple color spaces, by which we can effectively suppress noise caused by camera shake and maximize the area that cannot be matched. Thirdly, we use the Haar feature density map to filter the photo to remove discrete pixel points caused by small disturbances. Finally, we extract multiple features and fuse those features on decision level to obtain the final matching result. When deployed on intelligent monitoring devices and tested with massive scene photos, our algorithm has achieved the expected running efficiency and detection accuracy.
ABOUT SELF-STUDY OF PHYSICAL CULTURE DURING THE EXAMINATIONS AS A CRITERION OF STUDENTS’ READINESS TO PROFESSIONAL ACTIVITIES

Purpose of the study: The relevance of the research is conditioned by the contradiction between the social and state need to form the positive attitude to healthy lifestyle (including extracurricular time) in student youth and the underestimation of the potential of students' self-study activities aimed at increasing of physical activity and development of readiness for physical culture in specified group of youth. The article is aimed at the study of the student’s readiness for independent physical education during the examinations as a manifestation of independence in general, as well as at the study of the significance of independent physical education of students during the examinations in the process of future specialist formation. Methodology: The leading approach to the study of this problem was the theory of the activity approach in the development of personality and independent activities of students which allowed to substantiate the place of readiness of university students for independent physical training during the examinations in the process of future specialist training. Results: Of all the types of special readiness, the readiness of university students for independent physical training during examinations is of particular importance, the specificity of which is that this type of readiness contains features of types of readiness for professional activity, as well as readiness to act in problem situations, in which connection the readiness for independent physical training during the examinations is an indicator of the future specialist's readiness to problem professional situation. Applications of this study: The results of the study allow specialists who study the quality of university graduates to use the assessment of the development of student’s readiness for independent physical training during the examinations as an indicator of the future specialist’s readiness to act in a problem situation. Novelty/Originality of this study: The authors note that this problem cannot be solved by simply increasing the hours envisaged by the curriculum for independent work in the framework of the subject “Physical Education”, i.e. increase in quantity. A qualitative change in the approach to independent work of students, an appropriate system of actions in her organization and planning are necessary to achieve the desired effect.
Secure and Efficient Control Data Isolation with Register-Based Data Cloaking

Attackers often exploit memory corruption vulnerabilities to overwrite control data and further gain control over victim applications. Despite progress in advanced defensive techniques, such attacks still remain a major security threat. In this article, we present Niffler, a new technique that provides lightweight and practical defense against such attacks. Niffler eliminates the threat of memory corruption over control data by cloaking all control data in registers along its execution and only spilling them into a dedicated read-only area in memory upon a shortage of registers. As an attacker cannot directly overwrite any register or read-only memory pages, no direct memory corruption on control data is feasible. Niffler is made efficient by compactly encoding return address, balancing register allocation, dynamically determining register spilling and leveraging the recent Intel Memory Protection Extensions (MPX) for control data lookup during register restoring. We implement Niffler based on LLVM and conduct a set of evaluations on SPECCPU 2006 and real-world applications. Performance evaluation shows that Niffler introduces an average of only 6.3 percent overhead on SPECCPU 2006 C programs and an average of 28.2 percent overhead on C++ programs.
Applicatives for Anaphora and Presupposition

In this paper, we construct an effectful semantic fragment using the applicative abstraction. Empirically, we focus primarily on the dynamics of anaphora, and secondarily on presupposition projection. We aim to show that a dynamic semantics can be constructed in a fully modular fashion with applicative functors; we don’t need the full power of a monad (c.f. [4]). We take advantage of the fact that, unlike monads, applicative functors compose – and the result is guaranteed to be an applicative functor. Once we introduce the applicative abstraction, it turns out that the machinery necessary for dealing with the dynamics of anaphora and presupposition projection is already implicit in the machinery used in an orthodox static setting for dealing with assignment sensitivity, scope, and partiality.
Formation of Two-Wheeled Mobile Robots Moving in the Task Space with Static Obstacles - Numerical Verification for Bounded Controls

This paper presents control algorithm for formation of multiple non-holonomic mobile robots. It combines persistent excitation trajectory tracking algorithm and collision avoidance based on artificial potential functions. The robots avoid collision with each other and static obstacles existing in the task-space. Stability analysis of the closed-loop system based on Lyapunov-like function is presented. Effectiveness of the proposed method is illustrated by simulation results. They include also case of bounded wheel controls.