bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interairline Equity in Airport Scheduling Interventions
Authors: Jacquillat Alexandre , Vaze Vikrant 
Published: March 2018

In the absence of opportunities for capacity expansion or operational enhancements, air traffic congestion mitigation may require scheduling interventions to control overcapacity scheduling at busy airports. Previous research has shown that large delay reductions could be achieved through comparatively small changes in the schedule of flights. While existing approaches have focused on minimizing the overall impact across the airlines, this paper designs, optimizes, and assesses a novel approach for airport scheduling interventions that incorporates interairline equity objectives. It relies on a multilevel modeling architecture based on on-time performance (i.e., mitigating airport congestion), efficiency (i.e., meeting airline scheduling preferences), and equity (i.e., balancing scheduling adjustments fairly among the airlines) objectives, subject to scheduling and network connectivity constraints. Theoretical results show that, under some scheduling conditions, equity and efficiency can be jointly maximized. Computational results suggest that, under a wide range of current and hypothetical scheduling settings, ignoring interairline equity can lead to highly inequitable outcomes, but that our modeling approach achieves interairline equity at no, or small, losses in efficiency. The online appendix is available at https://doi.org/10.1287/trsc.2017.0817 .
Energy Efficient and robust routing with RPAR Protocol in Ad Hoc Networks
Authors: Reginald Pullagura Joshua , Venkata Rao D 
Published: March 2018

In ad hoc network, the topology of network changes frequently due to the mobile nature of nodes where the communication is possible without any fixed network infrastructure. Mobile nodes are battery operated and so energy efficient routing should be provided which increases the network life time. The existing routing mechanisms do not consider both hop count and energy of nodes for data transmission. In this paper we propose a routing mechanism where data transfer from source to destination is based on the minimum hop count and residual energy of mobile nodes. The proposed RPAR protocol shows better performance when compared to existing Energy power aware routing protocol .The analysis is carried out by using network simulator (NS-2), the simulation results shows that the proposed routing mechanism provides energy efficient and reliable routing in ad hoc networks.
Optimization of biometric recognition using cuckoo search algorithm: a preliminary version for minutia based fingerprint identification
Authors: Thangamanimaran Dhileepan , Chandar M. Sharat , Chandia S. 
Published: March 2018

Currently Behavioural Biometrics is the most widely used means of security. Though Behavioural Biometrics is highly reliable and secure, the data handling process is quite complex. This Problem can be solved by optimizing the process using cuckoo search algorithm.This Paper seeks to optimize the process of fingerprint matching by using an optimal algorithm. The Minutiae in the form of a matrix is extracted from a fingerprint. The Matrix is then split into smaller matrices with increasing dimension and then compared. The matrix with least dimension it is matched. If the Match is true then the verification of next generation bigger matrix is done. If the Match tends to be false then the matrix is skipped and the process is continued for the next matrix in the database. The Process is repeated until accurate match is obtained.Though the time reduced by the optimization of the finger print matching algorithm is insignificant for a smaller data set such as finger print data, it can be a key factor when a larger set of Behavioural biometrics data is considered.
Optimal signal mapping scheme for MIMO-BICM-ID transmission over the different fading channel using whale algorithm
Authors: Nandal Vikas , Kumar Suresh 
Published: March 2018

The designing of signal mapping scheme for bit-interleaved coded modulation (BICM) systems has been received significant interest among the researchers recently due to the growing interest of using Multiple Input Multiple Output (MIMO) system. The bit-interleaved coded modulation systems are need of effective design in constellation mapping with iterative decoding that outperformed the existing BICM coding in time varying characteristics of the channel. In this paper, the design of optimal constellation mapping of the BICM system with iterative decoding for MIMO channel is proposed. Based on minimizing cost, a design criterion is proposed to find the optimal constellation mapping for an MIMO-BICM-ID system. Here, a cost function is designed to search an optimal mapping scheme using the well-known optimization algorithm called, whale algorithm. Using this method, we find some optimal constellation mapping for 2-dimensional and 3-dimensional cases. The designed technique is evaluated with the help of BER curve for different fading channels.
Applicability of Sudoku game for building the cognitive model of a student for career assessment - an analytical study
Authors: Chandra Prakash V. , Sastry J. K. R. , Anusha K.B. , Spandana A.B. , Dhatrija N. , Nikhil V. 
Published: March 2018

Career assessment helps a student understand how a variety of personal attributes (i.e., academic record, aptitudes, skills, preferences, motivations, etc.) impact his/her successful professional career and satisfaction. The professional life of a student is very much dependent on the initial choice of the career that the student would like to pursue. Nowadays, during job recruitment process, a student is assessed based on IQ tests, Verbal tests, Reasoning tests, etc. Every student has some psychological factors (i.e., decision-making, patience & perseverance, logical thinking, learning ability, etc.) that are not considered during these tests. As a result, some students may not lead successful careers in future. There are a very few ways to assess those psychological factors of a student and one such way is through Game playing. Through an analytical study, it was found that "Sudoku" is the best game to assess psychological factors, especially decision-making power, of a student. The authors proposed an Expert system that conducts Sudoku game for a student, assesses various psychological factors, builds a cognitive model of the student and provides career assessment.
Index split decision tree and compositional deep neural network for text categorization
Authors: Ravikumar N , P. Tamil Selvan Dr 
Published: March 2018

Text categorization with machine learning algorithms generally reckons to possess horizontal set of classes. Several advanced machine learning algorithms have been designed in the past few decades. With the growing research work for text categorization, it has become important to categorize the research outcome and provide the learners with an effective machine learning method, a framework called, Hierarchical Decision Tree and Deep Neural Network (HDT-DNN).It investigates machine learning algorithms to create horizontal set of classes and it is used for classification of text. With this objective, a novel and efficient text categorization framework based on decision tree model is used in order to categorize text according to superior and subordinate level. The text to be categorized is presented in the form of a tree with parent text category being superior to all. The intermediate level represents the text that is both superior and subordinate. Then Deep Neural Network model is presented initiating compositional model, where the text has to be categorized, as a layered integration of primitives from the constructed decision tree model. The extra layers enable composition of features from lower layers, potentially modeling complex text with fewer units than a similarly carried out shallow network producing hierarchical classification. The significance of the impact of HDT-DNN framework is evaluated through empirical study. Extensive experiments are carried out and the performance of HDT-DNN framework is evaluated and compared with existing state-of-art methods using parameters such as precision, classification accuracy, classification time, with respect to varied number of features and document size.
Improvement of the efficiency of booth multiplier
Authors: Siva Kumar M , Kumar Tulasi Sanath , Srinivasulu N , Krishnam Naidu Yedla G S , Raghuveer E , Hari Kishore K 
Published: March 2018

Objective: To Improve the performance of Booth Multiplier and reduce power consumption.Method: The most essential form of multiplication consists of framing the result of two unsigned (positive) binary numbers.Finding: Booth Multiplier consists of pre-defined table. According to this algorithm, multiplication of two numbers x and y (x*y) is same as multiplication of y and x (y*x). At times this rule fails due to which we modify the logic by converting the decimal number in to 4 bit binary number and appending (n-2) zeros at most significant bit and one zero at least significant bit.Improvement: By using this method we can get accurate results in multiplication by multiplying like (x*y) and (y*x).
EMD based Hilbert energy spectrum analysis of adventitious lung wave signals
Authors: B. B. Shankar , Jayadevappa D. 
Published: March 2018

The respiratory adventitious waves are analyzed effectively by time frequency analysis. In this paper, we present a new approach for rectifying the abnormality in adventitious wave. Basically, there are two types of respiratory sound waves and these are classified as wheezes and crackles. The proposed method utilizes the time frequency analysis using spectrum analysis method. The modified Empirical Mode Decomposition (EMD) called Ensemble Empirical Mode Decomposition (EEMD) to plot energy spectrum of adventitious wave is used in this work. The proposed method decomposes the respiratory adventitious wave into a different Intrinsic Mode Function (IMF). The long and short duration adventitious waves are present in a wheezing subject and this leads to production of non stationary and nonlinear sound waves. The empirical mode decomposition (EMD) decomposes such characteristic waves. The available spectrogram analyzes techniques related to additive expansions and explore amplitude wise time-frequency distribution. The methodology discussed in this context responding greatly even for correlative noise and explores energy spectra in addition to amplitude spectra. The various IMFs such produced are exhibits the fine details of adventitious wave and thus pattern can be predicted for final residual. The energy spectrum can be viewed as a diagnostic tool for accurate analysis of wheezing pattern. The decomposed frequency patterns indicate the physiological aspects. The instantaneous frequency and Hilbert energy spectrum based on above mentioned a method are employed by IMF to analyze and present the result in time-frequency distribution to explore the characteristics of inherent properties adventitious signals. The Hilbert marginal spectrum has been used to indicate overall energy distribution from each frequency component. Finally, the resultant EMD analysis along with EEMD energy spectrum is better for asthmatic subject and solves mode mixing problems.
Design of low power 10GS/s 6-Bit DAC using CMOS technology
Authors: Ramakrishna P. , Hari Kishore K 
Published: March 2018

A Low power 6-bit R-2R ladder Digital to Analog Converter is presented in this paper. Here the R-2 R network designed using resistors with only two values-R and 2xRand the switch is designed by using both NMOS and PMOS Transistors. This Digital to Analog Converters operated with low voltage, by applying dynamic threshold MOSFET (DTMOS) logic. This design achieved less INL and DNL which is 0.3 and 0.06 respectively. Power supply required to operate this device is only 1V with10GHzconversion rate. This design is implemented by using 0.18μm CMOS technology.
Facets extraction-based approach for query recommendation using data mining approach
Authors: Zadgaonkar A. V. , Agrawal A. J. , Aote S. 
Published: March 2018

Search engines are popularly utilized for extracting desired information from World Wide Web by users. Efficiency of these search engines are dependent on how fast search results can be retrieved and whether these results reflects the desired info or not. For a particular query, vast amount of relevant information is scattered across the multiple web pages. Search engines generate multiple web links as a output. It has been a jigsaw puzzle for users to identify and select relevant links to extract further desired information. To address this issue, we are proposing an approach for Query Recommendation for getting relevant search results from web using facet mining techniques. Facets are the semantically related words for a query which defines its multiple aspects. We are extracting these aspects of a query from Wikipedia pages which is considered to be a trustworthy resource on the web. Our proposed system uses various text processing techniques to refine the results using lexical resource like WorldNet. In this paper we are discussing our approach and its implementation and results obtained. In the paper , Discussion on future research direction is included to conclude.
Data analytic framework for crime sector using open grid rule generation algorithm
Authors: Sharmila begum M , George A 
Published: March 2018

Data analytics (DA) is the process of exploring datasets in order to illustrate conclusions about the information they contain. It is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information. A database contains both structured and semi-structured data. The semi-structured data are from different sources. The system is provided with an open grid rule generationfor analyzing the data from whole data container. According to this concept, the analysis is much absolute rather than other, data mining technique.The main objective of the proposed study is to provide data having better and significant perspective.
Deep CNN based MR image denoising for tumor segmentation using watershed transform
Authors: Latif Ghazanfar , N.F. Awang Iskandar D , Alghazo Jaafar , Butt Mohsin , H. Khan Adil 
Published: March 2018

Magnetic Resonance Imaging (MRI) is considered one of the most effective imaging techniques used in the medical field for both clinical investigation and diagnosis. This is due to the fact that MRI provides many critical features of the tissue including both physiological and chemical information. Rician noise affects MR images during acquisition thereby reducing the quality of the image and complicating the accurate diagnosis. In this paper, we propose a novel technique for MR image denoising using Deep Convolutional Neural Network (Deep CNN) and anisotropic diffusion (AD) which we will refer to as Deep CNN-AD. Watershed transform is then used to segment the tumorous portion of the denoised image. The proposed method is tested on the BraTS MRI datasets. The proposed denoising method produced better results compared to previous methods. As denoising process affect the segmentation process therefore better denoised images by proposed technique produced more accurate segmentation with an average Specificity of 99.85% and dice coefficient of 90.46% thus indicating better performance of proposed technique.
K-core analysis and modeling for network centralities
Authors: MNSSVKR Gupta V , V.Phani Krishna Ch 
Published: March 2018

Network modeling is the interdisciplinary study of relationships. Network analysis deals with relational data and Network modeling represents the interdisciplinary study of relationships. Network structure can be studied at many different levels. Around 1000 article titles on cancer, published in journal resources were considered as a dataset. Data exploration was done through displaying nodes and edges in various layouts. With a term frequency limit of 100, nearly 64 terms appeared which less than 1% sparse is. Word cloud data was plotted using word frequencies from term matrix data. An undirected network graph plotted and evaluated density, average path length and modularity, which were found to be within limits. K-cores have also been used to analyze the connectivity of a network. Network centralities such as Degree centrality, Closeness, Eigenvector and between’s centrality resulted in node carcinoma being more central in the network.
Metabolic and genetic markers’ associations with elevated levels of alanine aminotransferase in adolescents
Authors: Ramírez-López Guadalupe , Morán-Villota Segundo , Mendoza-Carrera Francisco , Portilla-de Buen Eliseo , Valles-Sánchez Victoria , Castro-Martínez Xochitl H. , Sánchez-Corona José , Salmerón Jorge 
Published: March 2018

AbstractBackground:Non-alcoholic fatty liver disease (NAFLD), the most common chronic liver disease in adolescents, is a feature of metabolic syndrome (MetS). Obesity and insulin resistance (IR) are risk factors for NAFLD, as well as inflammation-related genetic markers. The relationship between metabolic or inflammation-related genetic markers and alanine aminotransferase (ALT) is not fully understood. We examined the relationship of MetS, metabolic and inflammation-related genetic markers with elevated ALT in adolescents.Methods:A total of 674 adolescents participated in a cross-sectional study in Guadalajara, Mexico. Elevated ALT (>40 IU/L), a surrogate marker of NAFLD, and MetS (International Diabetes Federation definition) were evaluated. Obesity, IR, lipids, C-reactive protein (CRP) and genetic markers (TNFA-308G>A,CRP+1444C>T,IL1RNandIL6-597/-572/-174 haplotype) were evaluated. Multivariate logistic regression was performed.Results:Elevated ALT was observed in 3% and 14.1% (total and obese, respectively) of the adolescents. Obesity (odds ratio [OR], 5.86; 95% confidence interval [95% CI], 1.16–25.89), insulin (OR, 8.51; 95% CI, 2.61–27.71), IR (OR, 9.10; 95% CI, 2.82–29.38), total cholesterol (TC) (OR, 3.67; 95% CI, 1.25–10.72), low-density lipoprotein-cholesterol (LDL-C) (OR, 3.06; 95% CI, 1.06–8.33), non-high-density lipoprotein-cholesterol (HDL-C) (OR, 3.88; 95% CI, 1.27–11.90) andIL1RN(OR, 4.64; 95% CI, 1.10–19.53) were associated with elevated ALT. Among males, ≥2 MetS criteria were associated with elevated ALT (OR, 4.22; 95% CI, 1.14–15.71).Conclusions:Obesity, insulin, IR, high TC, high LDL-C, high non-HDL-C andIL1RNpolymorphism were associated with elevated ALT. Among males, ≥2 MetS criteria were associated with elevated ALT. There is an urgent need to reduce obesity and IR in adolescents to prevent NAFLD.
Geriatric Cardiology-Therapeutic Strategies
Authors: Taneva Borjanka 
Published: March 2018

AbstractCardiovascular disease affects most men and women as they move through their last several decades of life. Vessels become stiffer, smooth muscle cells migrate, vasomotor functions decline, and the biology of their circulatory system is transformed. Changes in cardiovascular physiology with normal aging and prevalent comorbidities result in differences in the effects of common cardiac problems as well as in the response to their treatment. Patient-centered goals of care such as maintenance of independence and reduction of symptoms may be preferred over increased longevity. New less-invasive treatments are likely to improve outcomes in elderly patients who previously have been considered at prohibitive risk for traditional procedures.
Total Eosinophils, Ecp And IL-5 In Peripheral Blood During Treatment with Inhaled Corticosteroids in Patients with Asthma
Authors: Dimitrievska Deska , Zdraveska Marija , Todevski Dejan 
Published: March 2018

AbstractIntroduction. The main attribute of asthma is inflammation, which leads to airway remodeling, bronchial hyperreactivity and reversible or partly reversible airway obstruction. According to GINA, asthma is a chronic inflammatory disorder of the airways in which many cells play a role, in particular mast cells, eosinophils (Eo), and T lymphocytes. Many cells and mediators take part in creating the asthmatic inflammatory reaction, but eosinophils play a central role. The aim of this study was to show the values of biological inflammatory markers (IL-5 and Eo).Methods. Patients with severe asthma, 22 (73.33%) female and 8 (26.66%) male, aged 18-65 years were included in the study. The mean age was 35.30 ±9.65 years. Patients were treated with spray Beclomethasone dipropionate of 250 μg at doses from 1000 to 2000 μg/per day.Results. This study included 30 patients of the University Clinic of Pulmology and Allergology, Skopje, with confirmed bronchial asthma, treated with ICS. In all of the patients we monitored Eo count, ECP and IL-5 in peripheral blood at the beginning of the study, after 2 and 6 months treatment. During treatment with ICS we registered changes in all of the tested parameters.Conclusion. ICS objectively suppress the inflammatory reaction in asthma and the biological markers (IL-5, Eo and ECP), which we have monitored, can measure the accomplished effect. They could be used in everyday practice, not only as diagnostic parameters but also as valid therapeutic guides in treatment of asthma.
Ablation of a Left-Sided WPW in a Patient with Persistent Left Superior Vena Cava
Authors: Risteski Dejan , Taneva Borjanka 
Published: March 2018

Abstract
Anomalies of the venous system may impose serious limitations to the treatment of arrhythmias by means of ablation therapy. We describe a patient who had WPW syndrome with frequent supraventricular tachycardias in whom an ablation was performed. The patient was found to have a persistent left superior vena cava and a left-sided manifest accessory pathway. Persistent left superior vena cava is the most common congenital thoracic venous anomaly with a prevalence of 0.3-0.5% in the general population and is found more frequently in patients with accessory pathways than in patients with AV nodal reentrant tachycardia. Mapping and ablation of an accessory pathway follows the same general electrophysiology principles applicable to patients without anomalous venous return.
Praxisgerechte Vorgehensweisen zur Evaluation klassifizierender Bildverarbeitungssysteme
Authors: Neubecker Ralph , Heizmann Michael 
Published: March 2018

Zusammenfassung
Bildverarbeitungssysteme finden immer größere Verbreitung in der Industrie, zum Beispiel für Prüfanwendungen in der Qualitätssicherung. Für Anwender ist es wichtig, die Eignung für eine konkrete Aufgabe sicher beurteilen zu können. Während dies bei messenden Bildverarbeitungssystemen sehr gut im Rahmen von Standardverfahren erfolgen kann, stehen für klassifizierende Bildverarbeitungssysteme kaum anerkannte Verfahren bereit. Zudem stellt sich heraus, dass eine detaillierte, statistisch belastbare Fähigkeitsanalyse bei solchen Systemen in der industriellen Praxis oft nicht durchführbar ist. Unabhängig von konkreten Fähigkeitskennzahlen soll in diesem Beitrag eine Reihe von vereinfachten Vorgehensweisen vorgeschlagen werden, mit denen notwendige Informationen und Daten erhoben werden können. Diese sind mit unterschiedlichem Aufwand durchführbar und auf deren Grundlage können Systembewertungen mit unterschiedlicher Detailtiefe und Belastbarkeit abgeleitet werden.
Generalized Key Substitution Attacks on Message Recovery Signatures
Authors: Fujioka Atsushi 
Published: March 2018

Abstract
The generalized key substitution attacks were proposed as a generalization of the key substitution attacks to examine the security of the signature schemes adopted in ISO/IEC (1st CD) 14888-3, which standardizes appendix- -type signature schemes based on the discrete logarithm problem. This paper examines the message recovery signature schemes based on the discrete logarithm problem, adopted in ISO/IEC 9796-3:2006, and shows that all but one scheme are vulnerable to the generalized key substitution attacks.