bluuebunny/crossref_metadata_2025 huggingface dataset:
Meso-Analysis of Dynamic Compressive Behavior of Recycled Aggregate Concrete Using BFEM
Authors: Ying Liping , Peng Yijiang , Yang Hongming
Published: January 2019

In this paper, the base force element method (BFEM) for dynamic damage problems is proposed. And the BFEM model was applied to investigate the dynamic mechanical behavior of recycled aggregate concrete (RAC). Any convex polygon recycled aggregate was simulated. A constitutive relationship of dynamic damage was given. The compression test under dynamic loadings on the recycled concrete specimen was simulated. The stress–strain softening curve, variation law of dynamic enhancement coefficient and the damage pattern were researched under different strain rates. The dynamic properties of recycled concrete materials at high strain rate are also studied. The effect of different aggregate distribution on the mechanical properties of concrete was studied. The results of dynamic calculation of recycled concrete materials by this method are compared with the experimental results. The numerical simulation results are in good agreement with the experimental results. The comparative analysis on the dynamic mechanical properties of RAC and natural aggregate concrete (NAC) was also studied. The results show that the BFEM can be used to analyze the dynamic mechanical properties of RAC and NAC under high strain rate, and can be used for large-scale engineering calculations.
Global convergence of a modified Fletcher–Reeves conjugate gradient method with Wolfe line search
Authors: Sellami Badreddine , Chiheb Eddine Sellami Mohamed
Published: January 2019

In this paper, we are concerned with the conjugate gradient methods for solving unconstrained optimization problems. we propose a modified Fletcher–Reeves (abbreviated FR) [Function minimization by conjugate gradients, Comput. J. 7 (1964) 149–154] conjugate gradient algorithm satisfying a parametrized sufficient descent condition with a parameter [Formula: see text] is proposed. The parameter [Formula: see text] is computed by means of the conjugacy condition, thus an algorithm which is a positive multiplicative modification of the Hestenes and Stiefel (abbreviated HS) [Methods of conjugate gradients for solving linear systems, J. Res. Nat. Bur. Standards Sec. B 48 (1952) 409–436] algorithm is obtained, which produces a descent search direction at every iteration that the line search satisfies the Wolfe conditions. Under appropriate conditions, we show that the modified FR method with the strong Wolfe line search is globally convergent of uniformly convex functions. We also present extensive preliminary numerical experiments to show the efficiency of the proposed method.
Weighted fractional composition operators on certain function spaces
Authors: Borgohain D. , Naik S.
Published: January 2019

In this paper, we give some characterizations for the boundedness of weighted fractional composition operator [Formula: see text] from [Formula: see text]-Bloch spaces into weighted type spaces by deriving the bounds of its norm. Also, estimates for essential norm are obtained which gives necessary and sufficient conditions for the compactness of the operator [Formula: see text].
Bigeometric Cesàro difference sequence spaces and Hermite interpolation
Authors: Mahto Sanjay Kumar , Manna Atanu , Srivastava P. D.
Published: January 2019

In this paper, we introduce some difference sequence spaces in bigeometric calculus. We determine the [Formula: see text]-duals of these sequence spaces and study their matrix transformations. We also develop an interpolating polynomial in bigeometric calculus which is analogous to the classical Hermite interpolating polynomial.
Class p-wA(s,t) composition operators
Authors: Prasad T.
Published: January 2019

In this paper, we discuss the measure theoretic composition operators on [Formula: see text] in some operator classes, such as class [Formula: see text]-[Formula: see text], class [Formula: see text]-[Formula: see text] and class [Formula: see text]-[Formula: see text]. We also study some spectral properties of class [Formula: see text]-[Formula: see text] composition operators on [Formula: see text].
China—US Trade War: A Modern Version of the Thucydides Trap
Authors: XING Yuqing
Published: January 2019

China—US trade war looks like a modern version of the Thucydides Trap. The devastating consequences of the trade war can be avoided if China takes the drastic step to open its market to US firms and allow foreign firms to have a level playing field to compete with Chinese firms. It is time that Chinese consumers embrace products “made beyond China”.

Strengthening economic cooperation with the European Union (EU) and Japan would give China the leverage to counterbalance the pressure of the United States. China, however, should be ready to offer significant concessions in opening its domestic market too.
Structural Changes in Chinese Economy: Progress and Challenges
Authors: WU Yanrui
Published: January 2019

This article presents a review of the progress in economic restructuring in the Chinese economy. It explores the role of consumption versus investment in economic growth, trends in inequality, growth of the state and non-state sectors, and balancing between short-term and long-term development goals. It also discusses the major challenges in China’s economy and hence Chinese policymakers’ possible responses in the coming decade.
Accelerating Sustainability by Hydropower Development in China
Authors: ZHANG Yan
Published: January 2019

China, with the biggest electricity system, now leads the world on its global share in electricity production and consumption, as well as greenhouse gas emission. However, its incomplete power system reforms left an uncoordinated development between the generator and the grid. Despite intensive investment and construction of power generation infrastructure, the lagging grid reform has become a bottleneck in the sector. The benefits of electricity sector reform, if designed and proceeded carefully, can be substantial.
Big Data Development in China
Authors: SHIH Huimin , XUE Jianyue
Published: January 2019

Since 2012, the Chinese government has released several national-level plans to develop the big data industry, with an aim to improve governance and to push Chinese manufacturing up the value chain. Over the years, the Chinese big data industry has experienced rapid but uneven growth.

Although more Chinese companies and government departments are adopting big data technologies, administrative fragmentation and privacy protection policies remain obstacles to further development.
Islam in China: Current Conditions and State Policies
Authors: SHAN Wei , HO Ryan
Published: January 2019

In recent years, Muslim-related ethnic tensions and the Chinese government’s iron-fisted response have drawn controversies and attention from international society. The Islamic issue in China is intertwined with ethnic issues as a majority of the Muslims in China are ethnic minorities. The thrust of China’s policy for Islam is to promote its fusion with Chinese culture and to prevent influence of Arabic customs. These policies have failed to alleviate tensions between the Han-majority population and Muslim groups, and the government will face greater challenges in the future.
Mammal Conservation: Old Problems, New Perspectives, Transdisciplinarity, and the Coming of Age of Conservation Geopolitics
Authors: Macdonald David W.
Published: January 2019

I review the shocking current status of terrestrial mammals and then describe an approach to solving it, embracing a continuum of spatial and intellectual scales, from groundedness to geopolitics. Starting with an illustrative arena, the interface between agriculture and wildlife, I then outline the litany of threats to mammals and some successful approaches to their conservation, and document some broad-scale patterns regarding ecosystems, the mammalian communities within, and some implications for conservation. Observing that the battle for mammalian conservation is being badly lost, I dedicate the third part of this article to a combination of top-down and bottom-up, interdisciplinary studies, aspiring to a holistic approach that sets conservation in the wider sphere of the human enterprise and that I term transdisciplinary conservation.
Activation of Notch signaling by soluble Dll4 decreases vascular permeability via a cAMP/PKA-dependent pathway
Authors: Boardman Rachel , Pang Vincent , Malhi Naseeb , Lynch Amy P. , Leach Lopa , Benest Andrew V. , Bates David O. , Machado Maria J. C.
Published: January 2019

The Notch ligand delta-like ligand 4 (Dll4), upregulated by VEGF, is a key regulator of vessel morphogenesis and function, controlling tip and stalk cell selection during sprouting angiogenesis. Inhibition of Dll4 results in hypersprouting, nonfunctional, poorly perfused vessels, suggesting a role for Dll4 in the formation of mature, reactive, functional vessels, with low permeability and able to restrict fluid and solute exchange. We tested the hypothesis that Dll4 controls transvascular fluid exchange. A recombinant protein expressing only the extracellular portion of Dll4 [soluble Dll4 (sDll4)] induced Notch signaling in endothelial cells (ECs), resulting in increased expression of vascular-endothelial cadherin, but not the tight junctional protein zonula occludens 1, at intercellular junctions. sDll4 decreased the permeability of FITC-labeled albumin across EC monolayers, and this effect was abrogated by coculture with the γ-secretase inhibitor N-[ N-(3,5-difluorophenacetyl)-l-alanyl]- S-phenylglycine t-butyl ester. One of the known molecular effectors responsible for strengthening EC-EC contacts is PKA, so we tested the effect of modulation of PKA on the sDll4-mediated reduction of permeability. Inhibition of PKA reversed the sDll4-mediated reduction in permeability and reduced expression of the Notch target gene Hey1. Knockdown of PKA reduced sDLL4-mediated vascular-endothelial cadherin junctional expression. sDll4 also caused a significant decrease in the hydraulic conductivity of rat mesenteric microvessels in vivo. This reduction was abolished upon coperfusion with the PKA inhibitor H89 dihydrochloride. These results indicate that Dll4 signaling through Notch activation acts through a cAMP/PKA pathway upon intercellular adherens junctions, but not tight junctions, to regulate endothelial barrier function.

NEW & NOTEWORTHY Notch signaling reduces vascular permeability through stimulation of cAMP-dependent protein kinase A.
Role of gut metabolism of adrenal corticosteroids and hypertension: clues gut-cleansing antibiotics give us
Authors: Morris David J. , Brem Andrew S.
Published: January 2019

Intestinal bacteria can metabolize sterols, bile acids, steroid hormones, dietary proteins, fiber, foodstuffs, and short chain fatty acids. The metabolic products generated by some of these intestinal bacteria have been linked to a number of systemic diseases including obesity with Type 2 diabetes mellitus, some forms of inflammation, and more recently, systemic hypertension. In this review, we primarily focus on the potential role selected gut bacteria play in metabolizing the endogenous glucocorticoids corticosterone and cortisol. Those generated steroid metabolites, when reabsorbed in the intestine back into the circulation, produce biological effects most notably as inhibitors of 11β-hydroxysteroid dehydrogenase (11β-HSD) types 1 and 2. Inhibition of the dehydrogenase actions of 11β-HSD, particularly in kidney and vascular tissue, allows both corticosterone and cortisol the ability to bind to and activate mineralocorticoid receptors with attended changes in sodium handling and vascular resistance leading to increases in blood pressure. In several animal models of hypertension, administration of gut-cleansing antibiotics results in transient resolution of hypertension and transfer of intestinal contents from a hypertensive animal to a normotensive animal produces hypertension in the recipient. Moreover, fecal samples from hypertensive humans transplanted into germ-free mice resulted in hypertension in the recipient mice. Thus, it appears that the intestinal microbiome may not just be an innocent bystander but certain perturbations in the type and number of bacteria may directly or indirectly affect hypertension and other diseases.
tRNA-DL: A Deep Learning Approach to Improve tRNAscan-SE Prediction Results
Authors: Gao Xin , Wei Zhi , Hakonarson Hakon
Published: January 2019

Background: tRNAscan-SE is the leading tool for transfer RNA (tRNA) annotation, which has been widely used in the field. However, tRNAscan-SE can return a significant number of false positives when applied to large sequences. Recently, conventional machine learning methods have been proposed to address this issue, but their efficiency can be still limited due to their dependency on handcrafted features. With the growing availability of large-scale genomic data­sets, deep learning methods, especially convolutional neural networks, have demonstrated excellent power in characterizing sequence patterns in genomic sequences. Thus, we hypothesize that deep learning may bring further improvement for tRNA prediction. Methods: We proposed a new computational approach based on deep neural networks to predict tRNA gene sequences. We designed and investigated various deep neural network architectures. We used the tRNA sequences as positive samples, and the false-positive tRNA sequences predicted by tRNAscan-SE in coding sequences as negative samples, to train and evaluate the proposed models by comparison with the conventional machine learning methods and popular tRNA prediction tools. Results: Using the one-hot encoding method, our proposed models can extract features without involving extensive manual feature engineering. Our proposed best model outperformed the existing methods under different performance metrics. Conclusion: The proposed deep learning methods can substantially reduce the false positive output by the state-of-the-art tool tRNAscan-SE. Coupled with tRNAscan-SE, it can serve as a useful complementary tool for tRNA annotation. The application to tRNA prediction demonstrates the superiority of deep learning in automatic feature generation for characterizing sequence patterns.
Vaporized Cannabis Is Effective and Well-Tolerated in an Adolescent with Tourette Syndrome
Authors: Szejko Natalia , Jakubovski Ewgeni , Fremer Carolin , Müller-Vahl Kirsten R.
Published: January 2019

We present the case of a 12-year-old boy diagnosed with Tourette syndrome, who was successfully treated with a combination of vaporized medicinal cannabis and oral pure tetrahydrocannabinol (THC). Due to severe motor tics resulting in insomnia, the parents – both of whom were medical doctors – decided to initiate treatment with 0.02 g vaporized cannabis (Bedrocan with a THC content of 22% and a cannabidiol content of 1%; corresponding to a dose equivalent to 4.4 mg THC) without prior consultation of a Tourette expert. This treatment resulted – according to the parents’ report – in an immediate and nearly complete remission of the tics. Due to a further increase in tics, the parents therefore decided to implement a regular treatment with a combination of vaporized medicinal cannabis (up to 0.1 g cannabis per day, varieties Bedrocan and Amnesia Haze, corresponding to 22 mg THC/day) plus orally administered oil-based THC drops (maximum daily dose = 12.5 mg THC) resulting in a marked tic reduction. During a visit in our clinic, we were able to observe the reported beneficial effects 30 min after vaporization of 0.15 g cannabis (Amnesia Haze, equivalent to 33 mg THC; in addition, 7 mg oral THC were taken at home 6 h before the visit): tics, premonitory urges, and overall impairment significantly improved according to self-ratings, parent and clinician questionnaires. Importantly, no adverse events were reported. From this single case study, it is suggested that cannabis-based medicines and their combination (such as oral THC plus vaporized medicinal cannabis) are effective and safe in the treatment of severe tics in minors with TS. However, long-term follow-up is needed to confirm the beneficial treatment effects. We want to emphasize that in this boy treatment with cannabis was initiated by the parents before a consultation in our clinic has taken place. In our opinion, treatment with cannabis-based medicine in children should be regarded as a last-line treatment, when well-established treatments have failed to improve tics.
ZZ/ZW Sex Chromosomes in the Endemic Puerto Rican Leaf-Toed Gecko (Phyllodactylus wirshingi)
Authors: Nielsen Stuart V. , Daza Juan D. , Pinto Brendan J. , Gamble Tony
Published: January 2019

Investigating the evolutionary processes influencing the origin, evolution, and turnover of vertebrate sex chromosomes requires the classification of sex chromosome systems in a great diversity of species. Among amniotes, squamates (lizards and snakes) - and gecko lizards in particular - are worthy of additional study. Geckos possess all major vertebrate sex-determining systems, as well as multiple transitions among them, yet we still lack data on the sex-determining systems for the vast majority of species. We here utilize restriction-site associated DNA sequencing (RADseq) to identify the sex chromosome system of the Puerto Rican endemic leaf-toed gecko (Phyllodactylidae: Phyllodactylus wirshingi), in order to confirm a ZZ/ZW sex chromosome system within the genus, as well as to better categorize the diversity within this poorly characterized family. RADseq has proven an effective alternative to cytogenetic methods for determining whether a species has an XX/XY or ZZ/ZW sex chromosome system - particularly in taxa with non-differentiated sex chromosomes - but can also be used to identify which chromosomes in the genome are the sex chromosomes. We here identify a ZZ/ZW sex chromosome system in P. wirshingi. Furthermore, we show that 4 of the female-specific markers contain fragments of genes found on the avian Z and discuss homology with P. wirshingi sex chromosomes.
An approach to Measure Transition Density of Binary Sequences for X-filling based Test Pattern Generator in Scan based Design
Authors: Hussain Sabir , Rao V. Malleshwara
Published: January 2019

Switching activity and Transition density computation is an essential stage for dynamic power estimation and testing time reduction. The study of switching activity, transition densities and weighted switching activities of pseudo random binary sequences generated by Linear Feedback shift registers and Feed Forward shift registers plays a crucial role in design approaches of Built-In Self Test, cryptosystems, secure scan designs and other applications. This paper proposed an approach to find transition densities, which plays an important role in choosing of test pattern generator We have analyze conventional and proposed designs using our approache, This work also describes the testing time of benchmark circuits. The outcome of this paper is presented in the form of algorithm, theorems with proofs and analyses table which strongly support the same. The proposed algorithm reduces switching activity and testing time up to 51.56% and 84.61% respectively.
CCTV Surveillance System, Attacks and Design Goals
Authors: B. Muthusenthil , Sung Kim Hyun
Published: January 2019

Closed Circuit Tele-Vision surveillance systems are frequently the subject of debate. Some parties seek to promote their benefits such as their use in criminal investigations and providing a feeling of safety to the public. They have also been on the receiving end of bad press when some consider intrusiveness has outweighed the benefits. The correct design and use of such systems is paramount to ensure a CCTV surveillance system meets the needs of the user, provides a tangible benefit and provides safety and security for the wider law-abiding public. In focusing on the normative aspects of CCTV, the paper raises questions concerning the efficiency of understanding contemporary forms of ‘social ordering practices’ primarily in terms of technical rationalities while neglecting other, more material and ideological processes involved in the construction of social order. In this paper, a 360-degree view presented on the assessment of the diverse CCTV video surveillance systems (VSS) of recent past and present in accordance with technology. Further, an attempt been made to compare different VSS with their operational strengths and their attacks. Finally, the paper concludes with a number of future research directions in the design and implementation of VSS.
Extensive Analysis on Generation and Consensus Mechanisms of Clustering Ensemble: A Survey
Authors: Sandhya Rani Yalamarthi Leela , Sucharita V. , Satyanarayana K. V. V.
Published: January 2019

Data analysis plays a prominent role in interpreting various phenomena. Data mining is the process to hypothesize useful knowledge from the extensive data. Based upon the classical statistical prototypes the data can be exploited beyond the storage and management of the data. Cluster analysis a primary investigation with little or no prior knowledge, consists of research and development across a wide variety of communities. Cluster ensembles are melange of individual solutions obtained from different clusterings to produce final quality clustering which is required in wider applications. The method arises in the perspective of increasing robustness, scalability and accuracy. This paper gives a brief overview of the generation methods and consensus functions included in cluster ensemble. The survey is to analyze the various techniques and cluster ensemble methods.
Development of a Spatial Path-Analysis Method for Spatial Data Analysis
Authors: Sulistyo Wiwin , Subanar Subanar , Pulungan Reza
Published: January 2019

Path analysis is a method used to analyze the relationship between independent and dependent variables to identify direct and indirect relationship between them. This method is developed by Sewal Wright and initially only uses correlation analysis results in identifying the variables' relationship. Path analysis method currently is mostly used to deal with variables with non-spatial data type. When analyzing variables that have elements of spatial dependency, path analysis could result in a less precise model. Therefore, it is necessary to build a path analysis model that is able to identify and take into account the effects of spatial dependencies. Spatial autocorrelation and spatial regression methods can be used to develop path analysis method so as to identify the effects of spatial dependencies. This paper proposes a method in the form of path analysis method development to process data that have spatial elements. This study also discusses our effort on establishing a method that could be used to identify and analyze the spatial effect on data in the framework of path analysis; we call this method spatial path analysis.
Protecting Data by Improving Quality of Stego Image based on Enhanced Reduced difference Expansion
Authors: Ntahobari Maurice , Ahmad Tohari
Published: January 2019

In this era of internet development, security of information sharing is the main problem faced by human being. Data hiding technique is one of the solutions. However, hiding credential information within a multimedia file such as image reduces its visual quality. Therefore, unauthorized users may suspect the existance of secret data within that image. In the past years, various data hiding algorithms have been developed by researchers to overcome the problem of high distortion of image after data embedding process. Achieving a high quality stego image, however, is still a challenging problem. In this paper, we proposed a new data hiding algorithm based on different expansion. It aims to enhance the quality of stego image for a given payload size. The new algorithm is evaluated on various medical images. Thereafter, the experimental results show that the visual quality is improved; and increasing the embedding capacity leads to more noises. Therefore, a better choice of base point and a reduced difference expansion affect the quality of stego image.
Design of Linear Plasma Position Controllers with Intelligent Feedback Systems for Aditya Tokamak
Authors: Roseline J Femila , Nandhitha N M.
Published: January 2019

In order to increase the performance of Aditya tokamak, it is necessary to determine the feedback coil current for positioning the plasma within the magnetic chamber. In this paper, transfer functions are obtained for the plasma position prediction system. Four different feedback controllers are developed to improve the performance of the prediction system. From the analysis, Neural Network controller does not have overshoot while the PID controller has lesser settling time than the other two controllers. 
Performance Comparison of Multi Input Capacitor Converter Circuits
Authors: S Sreejith , Balasubramanian Karthik
Published: January 2019

This paper analyze the operation of a multi input switched capacitor (MIC) converters using a couple of switches, diodes and capacitors for several levels. With two input sources it is possible to obtain 8 output voltage levels. Here, 5 topologies of switched capacitor circuits namely summation, subtraction, inverting, double and half circuits are simulated and their performances are analyzed. Multi Input Converters have a high regard for multiple renewable energy sources used in smart grid systems, especially for distributed generators. The effects on output voltage with variation in load for different frequencies are also analyzed. Hardware implementation of summation and subtraction circuit is carried out and the results are compared with the simulated results
Computer Simulation of PMSM Motor with Five Phase Inverter Control using Signal Processing Techniques
Authors: Gaeid Khalaf S. , Asker Mshari Aead , Tawfeeq Nada N. , Mahdi Salam Razooky
Published: January 2019

The signal processing techniques and computer simulation play an important role in the fault diagnosis and tolerance of all types of machines in the first step of design. Permanent magnet synchronous motor (PMSM) and five phase inverter with sine wave pulse width modulation (SPWM) strategy is developed. The PMSM speed is controlled by vector control. In this work, a fault tolerant control (FTC) system in the PMSM using wavelet switching is introduced. The feature extraction property of wavelet analysis used the error as obtained by the wavelet de-noised signal as input to the mechanism unit to decide the healthy system. The diagnosis algorithm, which depends on both wavelet and vector control to generate PWM as current based manage any parameter variation. An open-end phase PMSM has a larger range of speed regulation than normal PMSM. Simulation results confirm the validity and effectiveness of the switching strategy.
Information System Success Framework based on Interpersonal Conflict Factors
Authors: Aboaoga Mohammed , Aziz Mohd Juzaiddin Ab , Mohamed Ibrahim
Published: January 2019

Information system success (ISS) has received considerable attention from researchers as it plays an important role in improving the efficiency and productivity of an organization. Several researchers have conducted empirical studies using numerous factors (e.g. organizational, technological, and individual factors) which affect the information system success. However, there are several factors which are related to interpersonal conflict which may affect information system success. The interpersonal conflict is a critical dimension which can greatly influence information system success in a competitive environment such as the financial sector. Therefore, this study introduces a framework to investigate the influence of interpersonal conflict factors on information system success in the Ministry of Finance, Yemen. The study employed a quantitative method which consists of the following steps: survey design, data collection and data analysis. A sample size comprising 130 employees were distributed in the Ministry of Finance, Yemen. Questionnaires were used to collect data from this sample. Data analysis (reliability, validity, correlation and factor analysis) has been carried out using SPSS.  In addition, structural equation modelling (SEM) has been used for evaluation the research model. Based on the experimental results, the findings in this study revealed that the interpersonal factors (interference, disagreement and instability) significantly negatively (at 0.05 level of significance) influence user satisfaction of information system success.
Performance Enhancement of MIMO-OFDM using Redundant Residue Number System
Authors: Youssef M. I. , Emam A. E. , Elghany M. Abd
Published: January 2019

Telecommunication industry requires high capacity networks with high data rates which are achieved through utilization of Multiple-Input-Multiple-Output (MIMO) communication along with Orthogonal Frequency Division Multiplexing (OFDM) system. Still, the communication channel suffers from noise, interference or distortion due to hardware design limitations, and channel environment, and to combat these challenges, and achieve enhanced performance; various error control techniques are implemented to enable the receiver to detect any possible received errors and correct it and thus; for a certain transmitted signal power the system would have lower Bit Error Rate (BER). The provided research focuses on Redundant Residue Number System (RRNS) coding as a Forward Error Correction (FEC) scheme that improves the performance of MIMO-OFDM based wireless communications in comparison with current methods as Low-Density Parity Check (LDPC) coders at the transmitter side or equalizers at receiver side. The Bit Error Rate (BER) performance over the system was measured using MATLAB tool for different simulated channel conditions, including the effect of signal amplitude reduction and multipath delay spreading. Simulation results had shown that RRNS coding scheme provides an enhancement in system performance over conventional error detection and correction coding schemes by utilizing the distinct features of Residue Number System (RNS).
Data Mining Approach of Accident Occurrences Identification with Effective Methodology and Implementation
Authors: Gupta Meenu , Solanki Vijender Kumar , Singh Vijay Kumar , García-Díaz Vicente
Published: January 2019

Data mining is used in various domains of research to identify a new cause for tan effect in the society over the globe. This article includes the same reason for using the data mining to identify the Accident Occurrences in different regions and to identify the most valid reason for happening accidents over the globe. Data Mining and Advanced Machine Learning algorithms are used in this research approach and this article discusses about hyperline, classifications, pre-processing of the data, training the machine with the sample datasets which are collected from different regions in which we have structural and semi-structural data. We will dive into deep of machine learning and data mining classification algorithms to find or predict something novel about the accident occurrences over the globe. We majorly concentrate on two classification algorithms to minify the research and task and they are very basic and important classification algorithms. SVM (Support vector machine), CNB Classifier. This discussion will be quite interesting with WEKA tool for CNB classifier, Bag of Words Identification, Word Count and Frequency Calculation.
Low Complexity Fluctuation Measurement in Image Processing Considering Order
Authors: Khan Tareq
Published: January 2019

The standard deviation can measure the spread out of a set of numbers and entropy can measure the randomness. However, they do not consider the order of the numbers. This can lead to misleading results where the order of the numbers is vital. An image is a set of numbers (i.e. pixel values) that is sensitive to order. In this paper, a low complexity and efficient method for measuring the fluctuation is proposed considering the order of the numbers. The proposed method sums up the changes of consecutive numbers and can be used in image processing applications. Simulation shows that the proposed method is 8 to 33 times faster than other related works.
Robust Counterpart Open Capacitated Vehicle Routing (RC-OCVRP) Model in Optimization of Garbage Transportation in District Sako and Sukarami, Palembang City
Authors: Puspita Fitri Maya , Hartono Yusuf , Syaputri Nadia Zuliaty , Yuliza Evi , Pratiwi Weni Dwi
Published: January 2019

In this paper, the Robust Counterpart Open Capacitation Vehicle Rounting Problem (RC-OCVRP) Model has been established to optimize waste transport in districts Sako and districts Sukarami, Palembang City. This model is completed with the aid of LINGO 13.0 by using Branch and Bound solver to get the optimum route. For Sako districs, the routes are as follows: working area 1 is TPS 1-TPS 2-TPS 3-TPA with distance 53.39 km, working area 2 is TPS 1-TPS 2-TPS 3-TPA with distance 48.14 km, working area 3 is TPS 1-TPA with a distance of 22.98 km, and working area 4 is TPS 1-TPS 2-TPS 3-TPS 4-TPA with 45.45 km distance, and obtained the optimum route in Sukarami districts is as follows: working area 1 is TPS 1-TPS 2-TPA 44.39 km, working area 2 is TPS 1-TPS 2-TPS 3-TPA with distance 49.32 km, working area 3 is TPS 1-TPS 3-TPA-TPS 2-TPA with distance 58.57 km, and working area 4 is TPS 1-TPA with a distance of 24.07 km, working area 5 is TPS 1-TPS 3-TPA-TPS 2-TPS 4-TPA with a distance of 77.66 km, and working area 6 is a TPS 1-TPS 2-TPS 3-TPA with a distante 44.94 km.
SCDT: FC-NNC-structured Complex Decision Technique for Gene Analysis Using Fuzzy Cluster based Nearest Neighbor Classifier
Authors: V Sudha , A. Girijamma H.
Published: January 2019

In many diseases classification an accurate gene analysis is needed, for which selection of most informative genes is very important and it require a technique of decision in complex context of ambiguity. The traditional methods include for selecting most significant gene includes some of the statistical analysis namely 2-Sample-T-test (2STT), Entropy, Signal to Noise Ratio (SNR). This paper evaluates gene selection and classification on the basis of accurate gene selection using structured complex decision technique (SCDT) and classifies it using fuzzy cluster based nearest neighborclassifier (FC-NNC). The effectiveness of the proposed SCDT and FC-NNC is evaluated for leave one out cross validation metric(LOOCV) along with sensitivity, specificity, precision and F1-score with four different classifiers namely 1) Radial Basis Function (RBF), 2) Multi-layer perception(MLP), 3) Feed Forward(FF) and 4) Support vector machine(SVM) for three different datasets of DLBCL, Leukemia and Prostate tumor. The proposed SCDT &FC-NNC exhibits superior result for being considered more accurate decision mechanism.
Misusability Measure Based Sanitization of Big Data for Privacy Preserving MapReduce Programming
Authors: Radhika D. , Kumari D. Aruna
Published: January 2019

Leakage and misuse of sensitive data is a challenging problem to enterprises. It has become more serious problem with the advent of cloud and big data. The rationale behind this is the increase in outsourcing of data to public cloud and publishing data for wider visibility. Therefore Privacy Preserving Data Publishing (PPDP), Privacy Preserving Data Mining (PPDM) and Privacy Preserving Distributed Data Mining (PPDM) are crucial in the contemporary era. PPDP and PPDM can protect privacy at data and process levels respectively. Therefore, with big data privacy to data became indispensable due to the fact that data is stored and processed in semi-trusted environment. In this paper we proposed a comprehensive methodology for effective sanitization of data based on misusability measure for preserving privacy to get rid of data leakage and misuse. We followed a hybrid approach that caters to the needs of privacy preserving MapReduce programming. We proposed an algorithm known as Misusability Measure-Based Privacy serving Algorithm (MMPP) which considers level of misusability prior to choosing and application of appropriate sanitization on big data. Our empirical study with Amazon EC2 and EMR revealed that the proposed methodology is useful in realizing privacy preserving Map Reduce programming.
Design and Implementation of Low Power Multiplier Using Proposed Two Phase Clocked Adiabatic Static CMOS Logic Circuit
Authors: Keote Minal , Karule P. T.
Published: January 2019

This paper presents a design and implementation of 2*2 array and 4*4 array multiplier using proposed Two Phase Clocked Adiabatic Static CMOS logic (2PASCL) circuit. The proposed 2PASCL circuit is based on adiabatic energy recovery principle which consumes less power. The proposed 2PASCL uses two sinusoidal power clocks which are 1800 phase shifted with each other. The measurement result of 2*2 array proposed 2PASCL multiplier gives 80.16 % and 97.67 %power reduction relative to reported 2PASCL and conventional CMOS logic and the measurement result of 4*4 array proposed 2PASCL multiplier demonstrate 32.88 % and 82.02 %power reduction compared to reported 2PASCL and conventional CMOS logic . Another advantage of the proposed circuit is that it gives less power though the number of transistor in proposed and reported 2PASCL circuit is same. From the result we conclude that proposed 2PASCL technology is advantageous to application in low power digital systems, pacemakers and sensors. The circuits are simulated at 180nm technology mode.
Establishment Network by Using FSO Link Based on MD Code for Hybrid SCM-SAC-OCDMA Wireless System
Authors: Fayadh Rashid Ali , Wali Mousa K. , Bonneya Mehdi F.
Published: January 2019

Since the wireless systems are working under nature environments and influenced by turbulence, weather in Iraq that leads to extended amount of fading signal, dissipation or attenuation. Basic “hybrid Subcarrier Multiplying Spectral Amplitude Coding (SCM-SAC) of Optical Code Division Multiple Access (OCDMA)" indoor or outdoor optical system depends on generally “Multi-Diagonal (MD)" security code by using optical space known as “Free Space Optic (FSO)" that was proposed in this work. It is found that the mention hybrid wireless systems can be used in operating mesh networks. The main proposed idea of hybrid optical technique was analyzed and simulated by normally taking into simulation account that the directly effecting by rain and haze attenuations. In addition, there are mention and description for atmospheric effects, FSO mesh network, modulation scheme, simulation, and the data security. From simulation results, the hybrid system using MD code produces reduced “bit-error rate (BER)" at heavy storm rain to distance or range of 500 m and at drizzle rain up to 2500 m range. And also investigates the performance of using the proposed system with radio over fiber (RoF) for UWB signals through indoor propagation in building applications of wireless channel.
A Miniaturized Patch Antenna Designed and Manufactured Using Slot's Technique for RFID UHF Mobile Applications
Authors: Hachimi Younes El , Gmih Yassine , Makroum El Mostafa , Farchi Abdelmajid
Published: January 2019

In this research work, a novel compact antenna with rectangular slots is presented for radio frequency identification (RFID) handled applications in the ultrahigh frequency (UHF) band that can be manufactured and integrated into RFID readers without difficult. A prototype demonstrating the aforementioned features was constructed and measured. The proposed antenna is fed by 50-Ω coaxial cable and printed on a 1.6mm thick FR4 substrate which has a small size and occupies a volume of 68×66 ×1.6mm3. The patch, the feed-line and ground plane are made of PEC (Perfect Electric Conductor) with a thickness of 0.035 mm. Measured results indicate that the proposed antenna has a good impedance matching characteristic ranging from 889 to 939MHz, which covers the USA RFID-band (902–928MHz), the Chinese RFID-operating-band (920–924.5MHz), and the Korea and Japan RFID-band (917–923.5MHz). These results were achieved by the insertion of slots in the compact structure of the antenna. The electromagnetic simulators HFSS (High Frequency structure simulator) and CST (Computer Simulation Technology) microwave studio were used for the design, modeling and simulation of the antenna. The focus of the study of our antenna was on the parameters of return loss, bandwidth, Voltage Standing Wave Ratio (VSWR), input impedance and gain.
Prediction Based Efficient Resource Provisioning and Its Impact on QoS Parameters in the Cloud Environment
Authors: Gadhavi Lata J , Bhavsar Madhuri D
Published: January 2019

The purpose of this paper is to provision the on demand resources to the end users as per their need using prediction method in cloud computing environment. The provisioning of virtualized resources to cloud consumers according to their need is a crucial step in the deployment of applications on the cloud. However, the dynamical management of resources for variable workloads remains a challenging problem for cloud providers. This problem can be solved by using a prediction based adaptive resource provisioning mechanism, which can estimate the upcoming resource demands of applications. The present research introduces a prediction based resource provisioning model for the allocation of resources in advance. The proposed approach facilitates the release of unused resources in the pool with quality of service (QoS), which is defined based on prediction model to perform the allocation of resources in advance. In this work, the model is used to determine the future workload prediction for user requests on web servers, and its impact toward achieving efficient resource provisioning in terms of resource exploitation and QoS. The main contribution of this paper is to develop the prediction model for efficient and dynamic resource provisioning to meet the requirements of end users.
Identification of Plant Types by Leaf Textures Based on the Backpropagation Neural Network
Authors: Hidayat Taufik , Ramadona Nilawati Asyaroh
Published: January 2019

The number of species of plants or flora in Indonesia is abundant. The wealth of Indonesia's flora species is not to be doubted. Almost every region in Indonesia has one or some distinctive plant(s) which may not exist in other countries. In enhancing the potential diversity of tropical plant resources, good management and utilization of biodiversity is required. Based on such diversity, plant classification becomes a challenge to do. The most common way to recognize between one plant and another is to identify the leaf of each plant. Leaf-based classification is an alternative and the most effective way to do because leaves will exist all the time, while fruits and flowers may only exist at any given time. In this study, the researchers will identify plants based on the textures of the leaves. Leaf feature extraction is done by calculating the area value, perimeter, and additional features of leaf images such as shape roundness and slenderness. The results of the extraction will then be selected for training by using the backpropagation neural network. The result of the training (the formation of the training set) will be calculated to produce the value of recognition accuracy with which the feature value of the dataset of the leaf images is then to be matched. The result of the identification of plant species based on leaf texture characteristics is expected to accelerate the process of plant classification based on the characteristics of the leaves.
Optimization of the Thyristor Controlled Phase Shifting Transformer using PSO Algorithm
Authors: Suyono Hadi , Hasanah Rini Nur , Pranyata Paramita Dwi Putri
Published: January 2019

The increase of power system demand leads to the change in voltage profile, reliability requirement and system robustness against disturbance. The voltage profile can be improved by providing a source of reactive power through the addition of new power plants, capacitor banks, or implementation of Flexible AC Transmission System (FACTS) devices such as Static VAR Compensator (SVC), Unified Power Flow Control (UPFC), Thyristor Controlled Series Capacitor (TCSC), Thyristor Controlled Phase Shifting Transformer (TCPST), and many others. Determination of optimal location and sizing of device injection is paramount to produce the best improvement of voltage profile and power losses reduction. In this paper, optimization of the combined advantages of TCPST and TCSC has been investigated using Particle Swarm Optimization (PSO) algorithm, being applied to the 30-bus system IEEE standard. The effectiveness of the placement and sizing of TCPST-TCSC combination has been compared to the implementation of capacitor banks. The result showed that the combination of TCPST-TCSC resulted in more effective improvement of system power losses condition than the implementation of capacitor banks.  The power losses reduction of 46.47% and 42.03% have been obtained using of TCPST-TCSC combination and capacitor banks respectively. The TCPST-TCSC and Capacitor Bank implementations by using PSO algorithm have also been compared with the implementation of Static VAR Compensator (SVC) using Artificial Bee Colony (ABC) Algorithm. The implementation of the TCSC-TCPST compensation with PSO algorithm have gave a better result than using the capacitor bank with PSO algorithm and SVC with the ABC algorithm.
Embedded Patient Monitoring System
Authors: Kanchikere Jayanna , Ghosh A.K. , Kalyankumar Kalyankumar
Published: January 2019

ICU remains for Intensive Care Unit, a place in the recuperating office where wiped out patients are checked eagerly. Commonly, the patient-staff extent is low and the LIFE-SAVING EQUIPMENT used is outstandingly bleeding edge Generally ICU is a healing facility for course of action of genuine nursing and remedial consideration of essentially wiped out patients, depicted by high bore and measure of unending nursing and restorative supervision and by use of cutting edge checking and resuscitative equipment The patients in the ICU require a predictable seeing of their Temperature and pulse circulatory strain. This undertaking is a working model, which wires sensors to evaluate imperative parameters specifically the Temperature, Respiratory temperature and Heart Beat. The sensors are interfaced to PC, with the objective that the condition of a patient can be explored by masters in any bit of the center wherever they are. At whatever point there is a variety from the standard felt by the patient, the particular patient will give an alert movement, by which the pro can race to the patient. Despite when the patient is in a careless condition, each one of the parameters will be identified and pro will be admonished, thusly it diminishes master's remaining task at hand and besides gives more correct results .Our endeavor is a working model which wires sensors to measure each one of these parameters like body temperature, Respiratory Temp and Heart Beat rate and trade it to the PC, with the objective that the patient condition can be examined to by authorities in any bit of the recuperating focus wherever they are. In this way it decreases experts work stack and besides gives more exact results, wherever there is a variety from the standard felt by the patient, we have in like manner combined saline watching system which gives an alert when the saline container going to cleanse.