bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fusion of clinical data: A case study to predict the type of treatment of bone fractures
Authors: Haq Anam , Wilk Szymon , Abelló Alberto 
Published: April 2019

Abstract
A prominent characteristic of clinical data is their heterogeneity—such data include structured examination records and laboratory results, unstructured clinical notes, raw and tagged images, and genomic data. This heterogeneity poses a formidable challenge while constructing diagnostic and therapeutic decision models that are currently based on single modalities and are not able to use data in different formats and structures. This limitation may be addressed using data fusion methods. In this paper, we describe a case study where we aimed at developing data fusion models that resulted in various therapeutic decision models for predicting the type of treatment (surgical vs. non-surgical) for patients with bone fractures. We considered six different approaches to integrate clinical data: one fusion model based on combination of data (COD) and five models based on combination of interpretation (COI). Experimental results showed that the decision model constructed following COI fusion models is more accurate than decision models employing COD. Moreover, statistical analysis using the one-way ANOVA test revealed that there were two groups of constructed decision models, each containing the set of three different models. The results highlighted that the behavior of models within a group can be similar, although it may vary between different groups.
Exploiting multi–core and many–core parallelism for subspace clustering
Authors: Datta Amitava , Kaur Amardeep , Lauer Tobias , Chabbouh Sami 
Published: April 2019

Abstract
Finding clusters in high dimensional data is a challenging research problem. Subspace clustering algorithms aim to find clusters in all possible subspaces of the dataset, where a subspace is a subset of dimensions of the data. But the exponential increase in the number of subspaces with the dimensionality of data renders most of the algorithms inefficient as well as ineffective. Moreover, these algorithms have ingrained data dependency in the clustering process, which means that parallelization becomes difficult and inefficient. SUBSCALE is a recent subspace clustering algorithm which is scalable with the dimensions and contains independent processing steps which can be exploited through parallelism. In this paper, we aim to leverage the computational power of widely available multi-core processors to improve the runtime performance of the SUBSCALE algorithm. The experimental evaluation shows linear speedup. Moreover, we develop an approach using graphics processing units (GPUs) for fine-grained data parallelism to accelerate the computation further. First tests of the GPU implementation show very promising results.
Optimal state observation using quadratic boundedness: Application to UAV disturbance estimation
Authors: Cayero Julián , Rotondo Damiano , Morcego Bernardo , Puig Vicenç 
Published: April 2019

Abstract
This paper presents the design of a state observer which guarantees quadratic boundedness of the estimation error. By using quadratic Lyapunov stability analysis, the convergence rate and the ultimate (steady-state) error bounding ellipsoid are identified as the parameters that define the behaviour of the estimation. Then, it is shown that these objectives can be merged in a scalarised objective function with one design parameter, making the design problem convex. In the second part of the article, a UAV model is presented which can be made linear by considering a particular state and frame of reference. The UAV model is extended to incorporate a disturbance model of variable size. The joint model matches the structure required to derive an observer, following the lines of the proposed design approach. An observer for disturbances acting on the UAV is derived and the analysis of the performances with respect to the design parameters is presented. The effectiveness and main characteristics of the proposed approach are shown using simulation results.
Constrained spectral clustering via multi–layer graph embeddings on a grassmann manifold
Authors: Trokicić Aleksandar , Todorović Branimir 
Published: April 2019

Abstract
We present two algorithms in which constrained spectral clustering is implemented as unconstrained spectral clustering on a multi-layer graph where constraints are represented as graph layers. By using the Nystrom approximation in one of the algorithms, we obtain time and memory complexities which are linear in the number of data points regardless of the number of constraints. Our algorithms achieve superior or comparative accuracy on real world data sets, compared with the existing state-of-the-art solutions. However, the complexity of these algorithms is squared with the number of vertices, while our technique, based on the Nyström approximation method, has linear time complexity. The proposed algorithms efficiently use both soft and hard constraints since the time complexity of the algorithms does not depend on the size of the set of constraints.
Recommendation systems with the quantum k–NN and Grover algorithms for data processing
Authors: Sawerwain Marek , Wróblewski Marek 
Published: April 2019

Abstract
In this article, we discuss the implementation of a quantum recommendation system that uses a quantum variant of the k-nearest neighbours algorithm and the Grover algorithm to search for a specific element in an unstructured database. In addition to the presentation of the recommendation system as an algorithm, the article also shows the main steps in construction of a suitable quantum circuit for realisation of a given recommendation system. The computational complexity of individual calculation steps in the recommendation system is also indicated. The verification of the correctness of the proposed system is analysed as well, indicating an algebraic equation describing the probability of success of the recommendation. The article also shows numerical examples presenting the behaviour of the recommendation system for two selected cases.
Synchronization of fractional–order discrete–time chaotic systems by an exact delayed state reconstructor: Application to secure communication
Authors: Djennoune Said , Bettayeb Maamar , Al-Saggaf Ubaid Muhsen 
Published: April 2019

Abstract
This paper deals with the synchronization of fractional-order chaotic discrete-time systems. First, some new concepts regarding the output-memory observability of non-linear fractional-order discrete-time systems are developed. A rank criterion for output-memory observability is derived. Second, a dead-beat observer which recovers exactly the true state system from the knowledge of a finite number of delayed inputs and delayed outputs is proposed. The case of the presence of an unknown input is also studied. Third, secure data communication based on a generalized fractional-order Hénon map is proposed. Numerical simulations and application to secure speech communication are presented to show the efficiency of the proposed approach.
New Insights in Treatment Options in Pediatric Urinary Tract Infection
Authors: Duicu Carmen , Armean Iulia , Aldea Cornel 
Published: April 2019

Abstract
Urinary tract infection (UTI) represents one of the most frequent infections with bacterial etiology during childhood. In infants and toddlers with fever without source UTI’ investigation should be carried out, since signs and symptoms are nonspecific. However, obtaining uncontaminated urine samples from these patients can be challenging and time consuming; all current collection methods (clean-catch, plastic collection bag, catheterization, etc) have disadvantages. Criteria for UTI definition are represented by the presence of significant number of a single uropathogen, this number being different depending on the collection method: at least 1000 colony-forming unit (CFU/ml) for catheter samples and at least 100.000 CFU/ml from midstream clean-catch samples or 50.000 CFU/ml and significant pyuria in a symptomatic or febrile child. Accurate diagnosis of UTI is essential to avoid any antibiotic overuse and expensive investigations. UTI caused by resistant bacterial strains has an increasing prevalence in children. In pediatric population, extended spectrum beta-lactamase-producing Enterobacteriaceae (ESBLPE) represent the etiology of around 15% of UTIs. Because of limited therapeutic options the reintroduction of some old antimicrobial agents is necessary, therefore Nitrofurantoin and Fosfomycin, can represent alternatives for oral treatment and prophylaxis of UTIs in children or in case of resistance suspicion to other drug classes. It is important to recognize patients at risk, such as children with recurrent UTIs, kidney abnormalities, like vesicoureteral reflux and previous antibiotherapy, in order to recommend adequate empiric treatment, especially against resistant bacteria.
Public Health in the Framework of the International Security. A Constructive Approach
Authors: Borsa Sergiu Viorel 
Published: April 2019

Abstract
The article highlights the fact that public health is an element of the security dimension that must be included on the priority agenda of specialists in the fields of international relations and security studies. There are arguments in favor of this theory. The costs of materializing threats to human security in general and public health in particular are particularly high, with serious long-term consequences. Global trends and prospects for the implications that can be generated are likely to change the world’s security landscape, and increasing global connectivity increases the degree of uncertainty about public health implications. Non-traditional issues arising from technological change can induce risks, whose management may go beyond institutional capacities. On the other hand, the new types of wars, increasingly interconnected with various forms of risk materialization, make this mission more difficult. The final conclusion is that these risks need to be assessed to ensure national, regional or even global security, and international cooperation for prevention and counseling.
The Influence of GPX1 Pro198Leu, CAT C262T and MnSOD Ala16Val Gene Polymorphisms on Susceptibility for Non-Hodgkin Lymphoma and Overall Survival Rate at Five Years from Diagnosis
Authors: Cosma Adriana-Stela , Radu Cristina , Moldovan Alexandra , Bogliș Alina , Crauciuc George Andrei , Horváth Emőke , Cândea Marcela , Tripon Florin 
Published: April 2019

Abstract

Objective: The aim of the current study was to investigate possible associations between catalase C262T (CAT C262T), glutathione peroxidase 1 Pro198Leu (GPX1 Pro198Leu), manganese superoxide dismutase Ala16Val (MnSOD Ala16Val) gene polymorphisms and non-Hodgkin Lymphoma risk (NHL) in a Romanian population and the five-year overall survival rate of the NHL patients.

Methods: We included in this case-control study 406 individuals, divided into two groups: the control group (n=315) and the patients group (n=91). The DNA was extracted from peripheral blood and amplified using specific techniques.

Results: The variant homozygous genotype of GPX1 Pro198Leu represents a risk factor for NHL development and no associations regarding the risk for NHL were found for MnSOD Ala16Val and CAT C262T gene polymorphisms. Two of the studied polymorphisms were associated with the overall survival rate thus: negative association regarding MnSOD Ala16Val, associated with higher overall survival rate and a positive one regarding CAT C262T, associated with lower overall survival rate.

Conclusions: According to our results, the mentioned polymorphisms may be considered as susceptible markers of the five-year overall survival rate for NHL patients. Future studies with a larger number of patients are needed to confirm our results.
Effect of Different Ratios of Biomaterials to Banana Peels on the Weight Loss of Biodegradable Pots
Authors: Mohd Rafee Siti Nor Amirah , Lee Yit Leng , Jamalludin Mohd Riduan , Abdul Razak Norawanis , Makhtar Nur Lailina , Ismail Ras Izzati 
Published: April 2019

Abstract
The present study was undertaken to determine the weight loss of pots made of different ratios of biomaterials and banana peels. Two types of biodegradable pots were produced using different ratios of biomaterials (B) and banana peels (BP). The ratios of B to BP tested in this study were B50% : BP50% and B30% : BP 70%. The weight loss of biodegradable pot with ratio B30% : BP70% was significantly higher than biodegradable pot with ratio B50% : BP50% after the empty biodegradable pots were left to decompose on the ground for 60 days. This result suggests that higher content of banana peels increase the microbial decomposition of the biodegradable pot. On the contrary, the weight loss of biodegradable pot with ratio B50%:BP50% was higher when they were filled with soil and left to decompose on the ground for 60 days. This is probably due to the lower content of banana peels, what decreased the tensile strength of biodegradable pot filled with soil, making it highly decomposable in such manner. In terms of degradability, biodegradable pot with ratio B30% : BP70% is more appropriate than pot with ratio B50% : BP50%.
Operational Degradation of Engine Oil in Agricultural Technology
Authors: Dostál Petr , Rozlivka Jakub , Kumbár Vojtěch 
Published: April 2019

Abstract
Proposed paper is focused on description and observation of operational degradation of engine oil in agricultural technology. Engine oil is one of the most important liquids used in combustion engines. Correct function of any machine is based on the appropriate selection of lubricants; moreover, it is also important to care for the entire lubrication system. Determining the condition of the oil used in operational conditions is very important for potential further oil use. Previously, engine oil had to be changed after expiration of legally valid intervals regardless of its actual performance parameters. However, its usage may be extended if engine oil parameters meet the legal requirements. This can be achieved by removing engine oil samples from machines on a regular basis. By examining the samples taken, it is possible to determine the actual oil state. In such manner, it is possible to prolong interchange periods and save both the financial resources and environment.
Determining specific thyroid transcripts in peripheral blood: A single center study experience
Authors: Makazlieva T , Eftimov A , Vaskova O , Tripunoski T , Miladinova D , Risteski S , Jovanovic H , Jakovski Z 
Published: April 2019

Abstract
Thyroid carcinoma (TC) comprises a spectrum of different tumors with a wide range of biological behavior and prognosis. The techniques based on the latest trends in molecular biology may have application in diagnosis of metastatic TC. The aim of this study was to apply and analyze mRNA expression in peripheral blood of thyrotropin receptor [thyroid stimulating hormone receptor (TSHR-mRNA)] gene and thyroglobulin (Tg-mRNA) gene using 2–ΔΔCt method in differentiated TC patients and healthy individuals. Fifty-seven subjects were included in the study, consisting of 40 patients with TC and 17 healthy volunteers as a control group. Total RNA was isolated from peripheral blood and used for two-step reverse transcriptase-polymerase chain reaction (PCR). Real-time PCR was performed with appropriate primers. Relative quantification using the 2–ΔΔCt method was applied. Thyroid carcinoma patients with metastatic disease or loco-regional relapse expressed TSHR-mRNA by a 8.57-fold higher level than healthy controls. Thyroid carcinoma patients with biochemical relapse expressed TSHR-mRNA by a 14.17-fold higher level than healthy controls, while expression of Tg-mRNA was 6.6-fold higher in TC patients with metastatic disease and loco-regional relapse than healthy controls and 8.34-fold higher level compared with TC patients with excellent response to treatment. Our preliminary study showed that the TSHR gene expression might have more useful application as a biomarker compared to detection of Tg gene expression.
Recent Development in Smart Grid Authentication Approaches: A Systematic Literature Review
Authors: Qasaimeh Malik , Al-Qassas Raad S. , Aljawarneh Shadi 
Published: April 2019

Abstract
Smart Grid (SG) is a major electricity trend expected to replace traditional electricity systems. SG has faster response to electricity malfunctions and improved utilization of consumed power, and it has two-way communication between providers and consumers. However, SG is vulnerable to attacks and requires robust authentication techniques to provide secure authenticity for its components. This paper analyses previous literature, comprising 27 papers on the status of SG authentication techniques, main components, and kinds of attacks. This paper also highlights the main requirements and challenges for developing authentication approaches for the SG system. This can serve as useful guidance for the development and deployment of authentication techniques for SG systems and helps practitioners select authentication approaches applicable to system needs.
Efficient Dynamic Bloom Filter Hashing Fragmentation for Cloud Data Storage
Authors: Jegadeeswari S. , Dinadayalan P. , Gnanambigai D. 
Published: April 2019

Abstract
Security is important in cloud data storage while using the cloud services provided by the service provider in the cloud. Most of the research works have been designed for a secure cloud data storage. However, cloud users still have security issues with their outsourced data. In order to overcome such limitations, a Dynamic Bloom Filter Hashing based Cloud Data Storage (DBFH-CDS) Technique is proposed. The main goal of DBFH-CDS Technique is to improve confidentiality and security of data storage in a cloud environment. The proposed Technique is implemented using data fragmentation model and Bloom filter. The DBFH-CDS Technique uses data fragmentation model for fragmenting the large cloud datasets. After that, Bloom Filter is employed in DBFH-CDS Technique for storing the fragmented sensitive data along with higher security. The DBFH-CDS Technique ensures high data confidentiality and security for cloud data storage with the help of Bloom Filter. The performance of proposed DBFH-CDS Technique is measured in terms of Execution time and Data retrieval efficiency. The experimental results show that the DBFH-CDS Technique is able to improve the cloud data storage security with minimum space complexity as compared to state-of-the-art-works.
Optimum Design of CDM-Backstepping Control with Nonlinear Observer for Electrohydraulic Servo System Using Ant Swarm
Authors: Haouari Fouad , Bali Nourdine , Tadjine Mohamed , Boucherit Mohamed Seghir 
Published: April 2019

Abstract
This paper introduces an application of an Ant Colony Optimization algorithm to optimize the parameters in the design of a type of nonlinear robust control algorithm based on coefficient diagram method and backstepping strategy with nonlinear observer for the electrohydraulic servo system with supply pressure under the conditions of uncertainty and the action of external disturbance. Based on this model, a systematic analysis and design algorithm is developed to deal with stabilization and angular displacement tracking, one feature of this work is employing the nonlinear observer to achieve the asymptotic stability with state estimations. Finally, numerical simulations are given to demonstrate the usefulness and advantages of the proposed optimization method.
Application of Information Technologies and Algorithms in Ship Passage Planning
Authors: Belev Blagovest , Dimitranov Dilyan , Spasov Alexandar , Ivanov Aleksandar 
Published: April 2019

Abstract
With the continuous increase of international oil prices, more and more shipping companies look for new solutions to the ever present question: How to reduce operational fuel consumption and decrease air pollution. Ship route planning is an indispensable part of the ship navigation process. In the modern world, the passage planning aspect of navigation is shifting. No longer do we see mariners drawing course lines on a paper chart. No longer do they calculate distances with compasses. Elaborate algorithms on various digital devices perform all these tasks. Algorithms plot the optimum tracks on digital charts and algorithms can decide how to avoid collision situations. Nowadays charter companies do not rely solely on the experienced navigators on board their vessels to decide the best route. Instead, this task is outsourced ashore to routing and weather-routing enterprises. The algorithms used by those enterprises are continuously evolving and getting better and better. They are coming popular because of another reason – more and more the shipping society support the newly idea for using crewless ships. However, are they up to the task to eliminate the human element in passage planning? In this article, we are going to review some of the weak points of the algorithms in use.
Smart method of agricultural drought regionalization: A winter wheat case study
Authors: Středa Tomáš , Středová Hana , Chuchma Filip , Kučera Josef , Rožnovský Jaroslav 
Published: April 2019

Abstract
The occurrence of drought during flowering (usually from the end of May to the beginning of June) is the most hazardous timing in terms of the possible negative impact of agricultural drought on winter wheat, which is the most cultivated crop in the Czech Republic (about 800000 ha). Lack of water, often accompanied by high temperatures, negatively affects the number of grains in the wheat ear and the tissue development of the developing grain, with consequent impacts on yield and quality of product. With the use of a) long-term time series of agrometeorological data (1961–2010), b) long-term phenological time series of winter wheat (1981–2010), and c) soil conditions data (available water capacity of soils of the Czech Republic) for the arable soil, the ratio of actual evapotranspiration and potential evapotranspiration for the period of 1961–2010, used as an indicator of agricultural drought (lack of water) for wheat, was calculated. The innovative aspect of this categorization of the territory of the Czech Republic according to the risk of occurrence of agricultural drought for winter wheat is considering drought from the aspect of the plant, i.e., evaluation based on the actual consumption of water by the vegetation. This is a very sophisticated procedure. Frequently, water content in soils data, presented as an output of some models, do not fully indicate the possible negative impacts on yield generation because the plants themselves are typically not considered. The method used in this study is universally applicable and allows comparisons of regions at the local, regional, and supra-regional levels. For estimation of the development of agronomic drought in the future, the basic water balances in the growing seasons of 1961–2010 and 2071–2100 were compared using a climate scenario. The forecast indicates a significant deterioration of agricultural drought in the region with probable direct impacts on agricultural production.