bluuebunny/crossref_metadata_2025 huggingface dataset:
Graphic health warnings on tobacco packets and containers: compliance status in Bangladesh
Authors: Rahman Syed Mahbubur , Alam Md Shariful , Zubair ABM , Shahriar Md Hasan , Hossein Monowar , Alam Md Shahedul , Hefler Marita
Published: April 2019

Objective

This study describes and analyses compliance with tobacco product graphic health warning (GHW) legislation introduced in Bangladesh in March 2016.

Methods

A survey based on a structured questionnaire was conducted in April 2016 (immediately following the law coming into force), and 8 months later in November 2016, in eight divisional cities in Bangladesh. Five stores from three categories of retailers of combustible and smokeless tobacco products were surveyed, providing a total of 120 completed questionnaires. The study investigated a range of measures including the image and text of GHW, their ratio and colour use, and prescribed rotation.

Findings

Warning labels for 3312 tobacco items were assessed. In April 2016, 75% of tobacco products surveyed did not have GHWs. In November 2016, 19% were still found to not have the prescribed warnings. Even among products which did include GHW, there was significant non-compliance with the full range of requirements, in both survey periods. Compliance was highest for cigarette packets and lowest among smokeless tobacco products. In addition, awareness among tobacco retailers about the range of GHW requirements was low.

Conclusion

Effective implementation of GHW labels in low-income and middle-income countries requires awareness-raising among key stakeholders, combined with focused monitoring and compliance strategies. This should take into account different product categories and manufacturers, as well as measures targeted at retailers.
Charge–mass sum rules for unified spinor fields in extradimensions and the prediction for the existence of tachyon quarks and tachyon leptons
Authors: Duc Dao Vong , Giao Nguyen Mong , Dung Tran Thanh
Published: April 2019

Within the framework of the mechanism proposed in our previous works [Duc and Giao, J. Mod. Phys. 5, 477 (2014); Duc et al., Int. J. Theor. Phys. 54, 1071 (2015); Duc and Giao, Int. J. Theor. Phys. 55, 959 (2016)] for mass and charge creation, we consider the charge and mass spectrum of spinor fields in extradimensions. It is shown that a single spinor field in spacetime with extradimensions corresponds to a set of effective spinor fields in ordinary four-dimensional spacetime with charges and masses obeying the sum rules dictated from some specific assumptions related to the compactification of extradimensions. The obtained results allow us to present an example for unifying six existing flavor quarks, as well as for unifying three existing lepton generators. On the base of the derived charge–mass sum rules, we would predict the existence of some hidden tachyon quarks with fractional charges, as well as some hidden tachyon leptons, neutral or negative charged.
Analysis and Research on the Structure Selection of BeiDou Navigation Array Antenna Based on Optimized PI Algorithm
Authors: Lei Guoping , He Hongliang , Xiao Ke , Dai Minlu
Published: April 2019

To overcome the disadvantages of the traditional power inversion algorithm, which has obvious suppression effect on strong interference signals but unobvious effect on suppression of weak interference signals, a matrix decomposition method is proposed to extract the interference sub-matrix and noise sub-matrix, so that the power inversion algorithm can be adopted to weaken and filter out the signals in the case of weak interference. Through the optimized power inversion algorithm, the interference signal can be weakened obviously at the antenna receiving end, and the quality of the effective signal received by the antenna can be improved significantly. Afterwards, the algorithm was used to carry out MATLAB simulation in space based on the anti-jamming performance of different array models, which determined the anti-jamming antenna array structure as a uniform matrix and optimized the array structure. The simulation results show that the optimized power inversion algorithm can filter strong and weak interference better, and the anti-jamming performance is better under different array models and two kinds of interferences. Through comparative analysis, it is concluded that the four elements have the best interference suppression effect in uniform circular array structure, which provides an important reference for the selection of antenna array in adaptive interference suppression hardware structure. At the same time, the BeiDou four-element adaptive circular array antenna, as an important part of intelligent geological disaster monitoring and early warning system, has good anti-jamming ability.
On the codimension of Noether–Lefschetz loci for toric threefolds
Authors: Lanza Valeriano , Martino Ivan
Published: April 2019

In this paper, we sharpen the lower bound on the codimension of the irreducible components of the Noether–Lefschetz locus of surfaces in projective toric threefolds given in [U. Bruzzo and A. Grassi, The Noether–Lefschetz locus of surfaces in toric threefolds, Commun. Contemp. Math. 20(5) (2018) 1–22]. We also provide a simpler proof of Theorem 4.11 in [U. Bruzzo and A. Grassi, The Noether–Lefschetz locus of surfaces in toric threefolds, Commun. Contemp. Math. 20(5) (2018) 1–22], which allows one to avoid some technical assumptions.
Real hypersurfaces with isometric Reeb flow in Kähler manifolds
Authors: Berndt Jürgen , Suh Young Jin
Published: April 2019

We investigate the structure of real hypersurfaces with isometric Reeb flow in Kähler manifolds. As an application we classify real hypersurfaces with isometric Reeb flow in irreducible Hermitian symmetric spaces of compact type.
Interval topology in contact geometry
Authors: Chernov Vladimir , Nemirovski Stefan
Published: April 2019

A topology is introduced on spaces of Legendrian submanifolds and groups of contactomorphisms. The definition is motivated by the Alexandrov topology in Lorentz geometry.
Some Bernstein processes similar to Cox–Ingersoll–Ross ones
Authors: Houda Mohamad , Lescot Paul
Published: April 2019

We present some results on Bernstein processes, which are Brownian diffusions that appear in Euclidean Quantum Mechanics. We express the distributions of these processes with the help of those of Bessel processes. We then determine two solutions of the dual equation of the heat equation with potential. These results first appeared in the first author’s PhD thesis (Rouen, 2013).
Macromolecular hexa-asymmetric zinc(II) phthalocyanines bearing triazole-modified triphenylene core: Synthesis, spectroscopy and analysis towards volatile organic compounds on Surface Acoustic Wave devices
Authors: Kus Funda , Tasaltin Cihat , Albakour Mohamad , Gürek Ayşe Gül , Gürol İlke
Published: April 2019

The synthesis and characterization of novel asymmetric zinc(II) phthalocyanines (4–9) and their linking through peripheral and nonperipheral positions on the phthalocyanine ring via click coupling to alkyne-functionalized 2,3,6,7,10,11-hexakis(prop-2-ynyloxy)triphenylene core are described for the first time. These phthalocyanines (Pcs) (4–12) were characterized by elemental analysis and different spectroscopic techniques such as UV-vis, 1H-NMR, FT-IR and mass spectroscopy. Furthermore, the utilization of thin films of novel Pcs as a sensitive layer for detection of lung cancer from exhaled human breath at room temperature under exposure to marker volatile organic compounds (VOCs) are presented. The developed sensors were tested for acetone, ethanol, [Formula: see text]-hexane, toluene, chloroform and isoprene in a range of 300–14560 ppm. The obtained results have confirmed the possibility of utilization of Pc-based Surface Acoustic Wave (SAW) sensors for medical diagnosis based on exhaled breath analysis.
Research on the Impacts of Real Estate on Economic Growth: A Theoretical Model-Based Analysis
Authors: ZHANG Xiaoxi , GUO Lu
Published: April 2019

As the pillar industry of China’s economy, the real estate sector has a significant impact on macroeconomic growth. We assume that the first stage of economic actors’ working lives is a low-income one, while their second stage is a high-income one. Then, relying on an Overlapping-Generations Model, we analyze how, via real estate, the behaviors of different income groups affect the macroeconomy. The results show that when the supply of real estate market fluctuates then this has an impact on economic growth, but the extent of the impact depends on the relationship between the real estate and the consumer markets. We also find that when economic actors more greatly prefer their current situations of well-being, no matter whether there takes place or not a new increase in real estate stocks, a negative correlation will exist in the relation between real estate stocks and their prices. Lastly, we come to the conclusion that increases in property taxes can effectively reduce housing prices, but the impact of transaction taxes on housing prices can still not be determined.
Efficient Straggler Replication in Large-Scale Parallel Computing
Authors: Wang Da , Joshi Gauri , Wornell Gregory W.
Published: April 2019

In a cloud computing job with many parallel tasks, the tasks on the slowest machines (straggling tasks) become the bottleneck in the job completion. Computing frameworks such as MapReduce and Spark tackle this by replicating the straggling tasks and waiting for any one copy to finish. Despite being adopted in practice, there is little analysis of how replication affects the latency and the cost of additional computing resources. In this article, we provide a framework to analyze this latency-cost tradeoff and find the best replication strategy by answering design questions, such as (1) when to replicate straggling tasks, (2) how many replicas to launch, and (3) whether to kill the original copy or not. Our analysis reveals that for certain execution time distributions, a small amount of task replication can drastically reduce both latency and the cost of computing resources. We also propose an algorithm to estimate the latency and cost based on the empirical distribution of task execution time. Evaluations using samples in the Google Cluster Trace suggest further latency and cost reduction compared to the existing replication strategy used in MapReduce.
Share-n-Learn
Authors: Rokni Seyed Ali , Ghasemzadeh Hassan
Published: April 2019

Wearable sensors utilize machine learning algorithms to infer important events such as the behavioral routine and health status of their end users from time-series sensor data. A major obstacle in large-scale utilization of these systems is that the machine learning algorithms cannot be shared among users or reused in contexts different from the setting in which the training data are collected. As a result, the algorithms need to be retrained from scratch in new sensor contexts, such as when the on-body location of the wearable sensor changes or when the system is utilized by a new user. The retraining process places significant burden on end users and system designers to collect and label large amounts of training sensor data. In this article, we challenge the current algorithm training paradigm and introduce
Share-n-Learn
to automatically detect and learn physical sensor contexts from a repository of shared expert models without collecting any new labeled training data. Share-n-Learn enables system designers and end users to seamlessly share and reuse machine learning algorithms that are trained under different contexts and data collection settings. We develop algorithms to autonomously identify sensor contexts and propose a gating function to automatically activate the most accurate machine learning model among the set of shared expert models. We assess the performance of Share-n-Learn for activity recognition when a dynamic sensor constantly migrates from one body location to another. Our analysis based on real data collected with human subjects on three datasets demonstrates that Share-n-Learn achieves, on average, 68.4% accuracy in detecting physical activities with context-varying wearables. This accuracy performance is about 19% more than ‘majority voting,’ 10% more than the state-of-the-art transfer learning, and only 8% less than the experimental upper bound.
Welcome to AI matters 5(1)
Authors: McGovern Amy , Leite Iolanda
Published: April 2019

Welcome to the first issue of the fifth volume of the AI Matters Newsletter! This issue opens with some news on a new SIGAI Student Travel Scholarship where we aim to encourage students from traditionally underrepresented geographic locations to apply and attend SIGAI supported events. We also summarize the fourth AAAI/ACM SIGAI Job Fair, which continues to grow with the increasing popularity of AI. In our interview series, Marion Neumann interviews Tom Dietterich, an Emeritus Professor at Oregon State University and one of the pioneers in Machine Learning.
Study on Calculation of Pile Sliding Interval of Large‐Diameter Steel Pipe Piles on Offshore Platforms
Authors: Kong Desen , Deng Meixu , Xu Yu
Published: April 2019

In ocean engineering, pile sliding often occurs in the driving process of large‐diameter pipe piles and will affect the engineering quality, so accurate pile sliding interval is necessary. According to the stress situation of steel pipe pile out of actual engineering, the causes of pile sliding are analysed. Using the static equilibrium equation, the mud depth at which the pipe pile may slip is calculated. The influence of pile siding friction was considered when calculating the second pile sliding, and the pile siding friction is divided into three influential areas. Using integrating method, the work done by pile resistance is calculated. Combined with the working principle and power principle, the energy transformation equation of the pipe pile in the process of sliding is obtained, and the sliding length and interval of the pile are calculated. A comparison between the measured results and the real case calculation was conducted using this new method. The comparison indicated that the total relative errors in pile sliding interval are 8% to 16%, and the new method has high accuracy. The results of the new method are in accord with the measured data, which can provide a reference for predicting the interval of pile sliding in the project.
Characterization of Initial Stages of Diabetic Macular Edema
Authors: Santos Ana Rita , Santos Torcato , Alves Dalila , Marques Inês P. , Lobo Conceição , Cunha-Vaz José
Published: April 2019

Purpose: This study is aimed at characterizing the type of retinal edema in the initial stages of retinopathy in type 2 diabetes. Methods: In this retrospective cross-sectional study, spectral domain optical coherence tomography (OCT) layer by layer analysis of the retina in association with OCT-Leakage, an algorithm to detect sites of low optical reflectivity, were used to examine eyes with minimal, mild, and moderate diabetic retinopathy (DR). Results: A total of 142 eyes from 142 patients (28% women) aged 52–88 years were imaged. Macular edema, either subclinical (SCME) or central-involved macular edema (CIME), was present in 43% of eyes in group 10–20, 41% of eyes in group 35, and 38% of eyes in group 43–47. The inner nuclear layer (INL) was the layer showing higher and most frequent increases in retinal thickness (79%). The edema was predominantly intracellular in group 10–20 (65%) and extracellular in groups 35 (77%) and 43–47 (69%). Conclusions: Eyes from diabetic patients in the initial stages of DR with different Early Treatment Diabetic Retinopathy Study gradings show similar prevalence of SCME and CIME, independent of the severity of the retinopathy. Retinal edema is located mainly in the INL and appears to be mostly extracellular except in the earliest stages of diabetic retinal disease where intracellular edema predominates.
Time-Based Raga Recommendation and Information Retrieval of Musical Patterns in Indian Classical Music Using Neural Networks
Authors: Roy Samarjit , Chakrabarty Sudipta , De Debashis
Published: April 2019

In Indian Classical Music (ICM) perspective, Raga is formed from the different and correct combination of notes. If it is observed the history of Indian Classical Raga in ICM, the playing or serving each of the ragas has some unique sessions. The procedure is to suggest the classifications of playing a raga has been attempted to display by explaining unique musical features and pattern matching. This contribution has been represented how music structures can be advanced through a more conceptual demonstration and consent to unambiguously describe process of computational modeling of Musicology which signify the challenge on complete musical composition from the elementary vocal objects of ICM usage using Neural Networks. In Neural network the samples of various ragas have been taken as input and classify them according to the times of the performance. Over 90% accuracy level has achieved using entire Confusion Matrices and Error Histogram performance evaluation technique.
A Decision System for Predicting Diabetes using Neural Networks
Authors: Rani K. Chandana , Prasanth Y.
Published: April 2019

Diabetic retinopathy (DR) is an eye fixed ill complete by the impairment of polygenic disorder and that we purchased to acknowledge it before of calendar for sensible treatment. On these lines, 2 social occasions were perceived, specifically non-proliferative diabetic retinopathy (NPDR), proliferative diabetic retinopathy (PDR). During this paper, to dissect diabetic retinopathy, 3 models like Probabilistic Neural framework (PNN), Bayesian Classification and Support vector machine (SVM) square measure pictured and their displays square measure thought-about. The live of the unwellness unfold within the membrane are often recognized by analytic the elements of the membrane. The elements like veins, hemorrhages of NPDR image and exudates of PDR image square measure off from the unrefined photos victimization the icon prepare techniques, fed to the classifier for gathering a complete of 350 structure photos were used, out of that100 were used for designing and 250 pictures were used for testing. Exploratory results show that PNN has an accuracy of 89.6 % Bayes Classifier incorporates a exactness of 94.4% and SVM has an exactitude of 97.6%. What is more our system is equally continue running on 130 pictures open from "DIARETDB0: Evaluation Database and Procedure for Diabetic Retinopathy" and also the results show that PNN incorporates a exactness of 87.69% Bayes Classifier has an accuracy of 90.76% and SVM has a precision of 95.38%.
Incremental Approach of Neural Network in Back Propagation Algorithms for Web Data Mining
Authors: Tawdar A. P. , Bewoor M. S. , Patil S. H.
Published: April 2019

Text Classification is also called as Text Categorization (TC), is the task of classifying a set of text documents automatically into different categories from a predefined set. If a text document relates to exactly one of the categories, then it is called as single-label classification task; otherwise, it is called as multi-label classification task. For Information Retrieval (IR) and Machine Learning (ML), TC uses several tools and has received much attention in the last decades. In this paper, first classifies the text documents using MLP based machine learning approach (BPP) and then return the most relevant documents. And also describes a proposed back propagation neural network classifier that performs cross validation for original Neural Network. In order to optimize the classification accuracy, training time. Proposed web content mining methodology in the exploration with the aid of BPP. The main objective of this investigation is web document extraction and utilizing different grouping algorithm. This work extricates the data from the web URL.
Improved Sensorless Direct Torque Control of Induction Motor Using Fuzzy Logic and Neural Network Based Duty Ratio Controller
Authors: H Sudheer , SF Kodad , B Sarvesh
Published: April 2019

This paper presents improvements in Direct Torque control of an induction motor using Fuzzy logic with Fuzzy logic and neural network based duty ratio controller. The conventional DTC (CDTC) of induction motor suffers from major drawbacks like high torque and flux ripples and poor transient response. Torque and flux ripples are reduced by replacing hysteresis controller and switching table with Fuzzy logic switching controller (FDTC). In FDTC the selected switching vector is applied for the complete switching time period. The FDTC steady state performance can be improved by using duty ratio controller, the selected switching vector is applied only for the time determined by the duty ratio (δ) and for the remaining time period zero switching vector is applied. The selection of duty ratio using Fuzzy logic and neural networks is projected in this paper. The effectiveness proposed methods are evaluated using simulation by Matlab/Simulink.
Identification of Rare Genetic Disorder from Single Nucleotide Variants Using Supervised Learning Technique
Authors: K Sathyavikasini , M S Vijaya
Published: April 2019

Muscular dystrophy is a rare genetic disorder that affects the muscular system which deteriorates the skeletal muscles and hinders locomotion. In the finding of genetic disorders such as Muscular dystrophy, the disease is identified based on mutations in the gene sequence. A new model is proposed for classifying the disease accurately using gene sequences, mutated by adopting positional cloning on the reference cDNA sequence. The features of mutated gene sequences for missense, nonsense and silent mutations aims in distinguishing the type of disease and the classifiers are trained with commonly used supervised pattern learning techniques.10-fold cross validation results show that the decision tree algorithm was found to attain the best accuracy of 100%. In summary, this study provides an automatic model to classify the muscular dystrophy disease and shed a new light on predicting the genetic disorder from gene based features through pattern recognition model.
Optimization of Digital Histopathology Image Quality
Authors: Tawfeeq Furat Nidhal , Alwan Nada A.S. , Khashman Basim M.
Published: April 2019

One of the biomedical image problems is the appearance of the bubbles in the slide that could occur when air passes through the slide during the preparation process. These bubbles may complicate the process of analysing the histopathological images. The objective of this study is to remove the bubble noise from the histopathology images, and then predict the tissues that underlie it using the fuzzy controller in cases of remote pathological diagnosis. Fuzzy logic uses the linguistic definition to recognize the relationship between the input and the activity, rather than using difficult numerical equation. Mainly there are five parts, starting with accepting the image, passing through removing the bubbles, and ending with predict the tissues. These were implemented by defining membership functions between colours range using MATLAB. Results: 50 histopathological images were tested on four types of membership functions (MF); the results show that (nine-triangular) MF get 75.4% correctly predicted pixels versus 69.1, 72.31 and 72% for (five- triangular), (five-Gaussian) and (nine-Gaussian) respectively. Conclusions: In line with the era of digitally driven e-pathology, this process is essentially recommended to ensure quality interpretation and analyses of the processed slides; thus overcoming relevant limitations.
Classification of Atrial Arrhythmias using Neural Networks
Authors: Utkarsh Jai , Kumar Pandey Raju , Kumar Dubey Shrey , Sinha Shubham , Sahu S. S.
Published: April 2019

Electrocardiogram (ECG) is an important tool used by clinicians for successful diagnosis and detection of Arrhythmias, like Atrial Fibrillation (AF) and Atrial Flutter (AFL). In this manuscript, an efficient technique of classifying atrial arrhythmias from Normal Sinus Rhythm (NSR) has been presented. Autoregressive Modelling has been used to capture the features of the ECG signal, which are then fed as inputs to the neural network for classification. The standard database available at Physionet Bank repository has been used for training, validation and testing of the model. Exhaustive experimental study has been carried out by extracting ECG samples of duration of 5 seconds, 10 seconds and 20 seconds. It provides an accuracy of 99% and 94.3% on training and test set respectively for 5 sec recordings. In 10 sec and 20 sec samples it shows 100% accuracy. Thus, the proposed method can be used to detect the arrhythmias in a small duration recordings with a fairly high accuracy.
Dwindling of Real Power Loss by Enriched Big Bang-Big Crunch Algorithm
Authors: Lenin K.
Published: April 2019

In this paper, Enriched Big Bang-Big Crunch (EBC) algorithm is proposed to solve the reactive power problem. The problem of converging to local optimum solutions occurred for the Bang-Big Crunch (BB-BC) approach due to greedily looking around the best ever found solutions. The proposed algorithm takes advantages of typical Big Bang-Big Crunch (BB-BC) algorithm and enhances it with the proper balance between exploration and exploitation factors. Proposed EBC algorithm has been tested in standard IEEE 118 & practical 191 bus test systems and simulation results show clearly the improved performance of the proposed algorithm in reducing the real power loss.
An STATCOM-based Hybrid Shunt Compensation Scheme Capable of Damping Subsynchronous Resonance
Authors: Mehdizadeh F. Reyhaneh , Nazarpour Daryoush
Published: April 2019

The paper presents the potential use of supplemental control of a new economical phase imbalanced shunt compensation concept for damping sub synchronous resonance (SSR) oscillations. In this scheme, the shunt capacitive compensation in one phase is created by using a Single-Phase Static Synchronous Compensator (STATCOM) in parallel with a fixed capacitor (Cc), and the other two phases are compensated by fixed shunt capacitor (C). The proposed arrangement would, certainly, be economically attractive when compared with a full three-phase STATCOM which have been used/proposed for power swings and SSR damping. SSR mitigation is achieved by introducing a supplemental signal into the control loops of single phase STATCOM. The validity and effectiveness of the proposed structure and supplemental control are demonstrated on a modified version of the IEEE second benchmark model for computer simulation of sub synchronous resonance by means of time domain simulation analysis using the Matlab program.
Vector Control of VSC HVDC System under Single Line to Ground Fault Condition
Authors: Rath Prabodha Kumar , Bhuyan Kanhu Charan
Published: April 2019

This paper proposes a model of a VSC (voltage source converter) based Back to Back HVDC system and its control technique under fault condition. From the mathematical model of the system relationship between the controlling and the controlled variables is determined to control the system parameters. An appropriate vector control technique is used to control active and reactive power and to maintain DC link voltage. The proposed controlling unit consists of outer control loop and inner control loop which effectively damped out the system oscillation and maintains the system stability. The validity of the model and the feasibility of the control method have been proved by the simulation results. In this paper the system performance is studied under fault condition is studied.
Harmonic Mitigation for Non-Linear Load using TSH Active Power Filter with PID Controller
Authors: Sinha Garima , Goswami Pankaj Kumar , Sharma Sudhir Kr.
Published: April 2019

Electronic equipments, widely used in present living era, required to have improved power quality. When such type of equipments are connected to electric supply distribution system, they introduce non sinusoidal effect in the line current because of their non-linear relationship in voltage and current. Moreover, harmonics in the line current are also produced. With constantly growing imploration of such type of nonlinear equipments at a large scale, harmonic distortions in line current have become a significant crunch. This required some methods involving the reduction of harmonics in the line current as well as Power Factor Improvement/Correction. The primary goal of this proposed work is to reduce the harmonics produced in line current and to improve power quality of non-linear load by designing a converter with parallel processing scheme, named TSH Active power filter (Transformer less shunt active power filter) with PID controller. Here a separate dc source is employed to supply the shunt connected converter, a voltage source inverter, to remove the requirement of bulky transformer at supply end. This paper depicted the process of reduction of total harmonic distortion (THD), generated due to nonlinear characteristics of load and power factor improvement by shunt compensation. The proposed designs are modeled and simukated using Matlab simulation software.
Meleagris Gallopavo Algorithm for Solving Optimal Reactive Power Problem
Authors: Lenin K.
Published: April 2019

In this paper, Meleagris Gallopavo Algorithm (MGA) is proposed for solving optimal reactive power problem.As a group-mate Meleagris gallopavo follow their poultry to  explore food,  at the same time it prevent the  same ones  to eat their own food. Always the overriding individuals have the lead to grab more food and Meleagris gallopavo would arbitrarily pinch the high-quality food which has been already found by other Meleagris gallopavo. In the region of the mother Meleagris gallopavo, Poults always search for food. In the Projected Meleagris Gallopavo Algorithm (MGA) additional parameters are eliminated, in order to upsurge the search towards global optimization solution.Proposed Meleagris Gallopavo Algorithm (MGA) has been tested on two modes a. with the voltage stability Evaluation in standard IEEE 30 bus test system, b. Without voltage stability Evaluation in standard IEEE 30, 57,118 bus test systems & practical 191 test system. Simulation results show clearly the better performance of the proposed Meleagris Gallopavo Algorithm (MGA) in reducing the real power loss, enhancement of static voltage stability Index and particularly voltage profiles within the specified limits.
Multicarrier SPWM Control Techniques for Three Phase Eleven Level Diode Clamped Multilevel Inverter and Hybrid Inverter with Reduced Number of Components
Authors: Susheela N. , Kumar P. Satish
Published: April 2019

A comparative analysis of three phase eleven level diode clamped multilevel inverter (DCMLI) and hybrid inverter is performed in this paper in which the later requires fewer carrier signals, less number of devices and gate drive circuits. The performance is evaluated using phase disposition (PD), alternate phase opposition disposition (APOD) and carrier overlapping (CO) sinusoidal pulse width modulation (SPWM) methods. The hybrid multilevel inverter has superior features over diode clamped multilevel inverters and is more efficient since the positive levels of the inverter that are generated  by high frequency switches (level generation part), are reversed by low frequency switches (polarity generation part) when the voltage polarity is required to be changed for negative polarity. Therefore, the overall cost and complexity of the hybrid inverter are greatly reduced particularly for higher inverter output voltage levels. Simulation is performed for three phase eleven level diode clamped multilevel inverter and hybrid multilevel inverter using MATLAB/Simulink for induction motor load and the total harmonic distortion is evaluated at different load torques.
Implementation of Ultra-Modified Symmetric Sequence Algorithm for Space Vector Modulation of Matrix Converter
Authors: Tawfiq Kotb B. , Mansour A. S. , EL-Kholy E. E.
Published: April 2019

This paper proposes an ultra- modified symmetric sequence algoritm of space vector modulation of matrix converter. The ultra-modified technique improves the drawbacks of the modified one where it provides a reduction of the total harmonic distortion for both output voltage and output current. Some of the advantages of matrix converter are introduced in this paper. These advantages represented in the output frequency of matrix converter which may be greater than input frequency, controlling rms value of the output voltage and the ability to control the input displacement factor.At the end of this paper simulation and experimental results are introduced which give a presice proof to the proposed algorithms.
Developing a battery monitoring system software in matlab simulink environment using kalman filter
Authors: Rahighi Alireza , Seyed Kashani Seyed Mohammad Hadi , Sakhaee Behrang
Published: April 2019

Batteries play a vital role in electrical equipments and electrical engineering tools. In addition, in vehicles, the duties of the battery is very important, both in providing initial start energy for conventional cars and movement energy for electric vehicles. Therefore, the batteries could be counted as one of the most important segments of the electric vehicles. The batteries used in vehicles have various types. The most utilized of which in vehicles are the lead-acid batteries. Due to the noticeable privileges of the lead-acid batteries, they have been widely used in vehicles. The battery of the system, which have been processed in this project, is a traction battery with 24V nominal voltage and 500Ahours nominal capacity. In this project, the Kalman filter method has been used in order to estimate the remaining amount of battery’s charge. Kalman filter is an algorithm that estimates the state of a dynamic system using a set of measurements including fault in a specific time period. Having implemented the Kalman filter to the dynamic model of the battery, an estimation of state of the charge (SOC) and battery parameters have been acquired. This operation was simulated in Matlab Simulink environment and the results of the simulation were compared with the real amounts of the parameters achieved from prior experiments to make sure about the accuracy of the results. In the designed software, a graphical environment has been developed in order to providing an appropriate interface and simplifying the software performance. The program can be easily implemented to a real battery and calculate the desired parameters.
A wide area fault detection algorithm for transmission networks equipped with series compensation units
Authors: Ebrahim Mohamed A. , Wadie Fady , Abd-Allah Mousa A.
Published: April 2019

In this paper, a wide area back-up protection (WABP) algorithm is presented based on phasor measurement units (PMUs) measurements placed across the transmission network. The proposed algorithm computes a selected index named as positive sequence power index (PSPI) to detect faults in the network. Firstly, the network is subdivided into back-up protection zones. For each zone, the PSPI index is computed as absolute the value of the difference between the positive sequence sent and received phasor powers across the terminals of the zone. For each zone, the PSPI is compared to a predefined threshold to detect faults. One of the contributions in this paper is the usage of mathematical formulation to set the threshold values for each zone rather than experimental trials usually used in previous literature. In addition, the algorithm doesn’t depend iterative solutions nor line parameters of the network as usually used in WABP schemes. These advantages enhance the degree of confidence in decisions of the algorithm and reduces computational burdens to trivial amount. The presented algorithm (Level-1) could be enhanced into (level-2) if PMUs are available on all buses and in such case, the faulty line could be detected directly in a single step. WSCC 9-bus system and NE 39-bus systems were considered to accomplish this study. Severe cases for series compensated lines were taken into consideration including voltage or current inversion. Simulation results emphasis on algorithm’s robustness and adaptability.
The use of Markov Chain method to determine spare transformer number and location
Authors: Marbun Musa Partahi , Sinisuka Ngapuli Irmea , Hariyanto Nanang
Published: April 2019

The purpose of this study is to develop a method to determine spare transformer number and location. Using Markov Chain method, state transition model and steady state probability was used on each 500-kV substation in order to analyze the effect of spare number and location variation with the reliability changes.  To give an actual result of the case study, calculation of spare transformer number and location on 500/150 kV transformers in Java Bali System was analyzed. The steady state probability results will vary depending on the number of spare transformer, these results can then be used to assess the spare transformer needed. The variation of spare transformer location can be used to analyze the best possible location of the spare in order to satisfy the reliability required. The methodology presented shows an integrated calculation for determining the spare transformer number and location.
Energy and exergy analysis of air based photovoltaic thermal (PVT) collector: a review
Authors: Fudholi Ahmad , Musthafa Mariyam Fazleena , Ridwan Abrar , Yendra Rado , Desvina Ari Pani , Rahmadeni Rahmadeni , Suyono Tri , Sopian Kamaruzzaman
Published: April 2019

Photovoltaic thermal (PVT) collectors convert solar radiation directly to both electrical and thermal energies. A PVT collector basiccaly combines the functions of a flat plate solar collector and those of a PV panel. This review presents thermodinamics fundamentals, descriptions, and previous works conducted on energy and exergy analysis of air based PVT collector. Studies in 2010 to 2018 of the energy and exergy analysis of air based PVT collectors are summarized. The energy and exergy efficiency of air based PVT collector ranges from 31% to 94% and 8.7% to 18%, respectively. In addition, flat plate solar collector is presented. Studies conducted on air based PVT collectors are reviewed.
A transient current based micro-grid connected power system protection scheme using wavelet approach
Authors: Shekar S. Chandra , Kumar G.Ravi , Lalitha S.V.N.L
Published: April 2019

Micro-grids comprise Distributed Energy Resources (DER’s) with low voltage distribution networks having controllable loads those can operate with different voltage levels are connected to the micro-grid and operated in grid mode or islanding mode in a coordinated way of control. DER’s provides clear environment-economical benefits for society and consumer utilities. But their development poses great technical challenges mainly protection of main and micro grid. Protection scheme must have to respond to both the main grid and micro-grid faults. If the fault is occurs on main grid, the response must isolate the DER’s from the main grid rapidly to protect the system loads. If the fault ocuurs within the micro-grid, the protection scheme must coordinate and isolates the least priority possible part of the grid to eliminate the fault. In order to deal with the bidirectional energy flow due to large numbers of micro sources new protection schemes are required. The system is simulated using MATLAB Wavelet Tool box and Wavelet based Multi-resolution Analysis is considered. Wavelet based Multi-resolution Analysis is used for detection, discrimination and location of faults on transmission network.  This paper is discussed a transient current based micro-grid connected power system protection scheme using Wavelet Approach described on wavelet detailed-coefficients of Mother Biorthogonal 1.5 wavelet. The proposed algorithm is tested in micro-grid connected power systems environment and proved for the detection, discrimination and location of faults which is almost independent of fault impedance, fault inception angle (FIA) and fault distance of feeder line.
A comparative approach between different optimize result in hybrid energy system using HOMER
Authors: Goyal Shweta , Mishra Sachin , Bhatia Anamika
Published: April 2019

To compare the different result of optimization of a hybrid energy system. A hybrid renewable energy system (HRES) is the combination of renewable and non-renewable sources which is playing a very important role for rural area electrification when grid extension is not possible or excessively expensive. Non renewable sources like diesel power generator (optional) are used in a HRES for backup when renewable energy supply is not sufficient. While the HRES is very important due to the smallest natural and physical contact compared to non renewable sources, this work proposed a comparison outcome with the help of different component by using HOMER software and get best optimize result for the model. This paper presents a wide-ranging review of various aspects of HRES. This paper discusses study, best sizing, and model, organize aspect and reliability issue.
Hardware simulation for exponential blind equal throughput algorithm using system generator
Authors: Yusuf Yusmardiah , Ali Darmawaty Mohd , Ya’acob Norsuzila
Published: April 2019

Scheduling mechanism is the process of allocating radio resources to User Equipment (UE) that transmits different flows at the same time. It is performed by the scheduling algorithm implemented in the Long Term Evolution base station, Evolved Node B. Normally, most of the proposed algorithms are not focusing on handling the real-time and non-real-time traffics simultaneously. Thus, UE with bad channel quality may starve due to no resources allocated for quite a long time. To solve the problems, Exponential Blind Equal Throughput (EXP-BET) algorithm is proposed. User with the highest priority metrics is allocated the resources firstly which is calculated using the EXP-BET metric equation. This study investigates the implementation of the EXP-BET scheduling algorithm on the FPGA platform. The metric equation of the EXP-BET is modelled and simulated using System Generator. This design has utilized only 10% of available resources on FPGA. Fixed numbers are used for all the input to the scheduler. The system verification is performed by simulating the hardware co-simulation for the metric value of the EXP-BET metric algorithm. The output from the hardware co-simulation showed that the metric values of EXP-BET produce similar results to the Simulink environment.  Thus, the algorithm is ready for prototyping and Virtex-6 FPGA is chosen as the platform.
Priority based round robin (PBRR) CPU scheduling algorithm
Authors: Zouaoui Sonia , Boussaid Lotfi , Mtibaa Abdellatif
Published: April 2019

This paper introduce a new approach for scheduling algorithms which aim to improve real time operating system CPU performance. This new approach of CPU Scheduling algorithm is based on the combination of round-robin (RR) and Priority based (PB) scheduling algorithms. This solution maintains the advantage of simple round robin scheduling algorithm, which is reducing starvation and integrates the advantage of priority scheduling. The proposed algorithm implements the concept of time quantum and assigning as well priority index to the processes. Existing round robin CPU scheduling algorithm cannot be dedicated to real time operating system due to their large waiting time, large response time, large turnaround time and less throughput. This new algorithm improves all the drawbacks of round robin CPU scheduling algorithm. In addition, this paper presents analysis comparing proposed algorithm with existing round robin scheduling algorithm focusing on average waiting time and average turnaround time.
Negative image amplifier technique for performance enhancement of ultra wideband LNA
Authors: Sawarkar Kishor G. , Tuckley Kushal R.
Published: April 2019

The paper aims at designing of two stage cascaded ultra-wideband (UWB) low noise amplifier (LNA) by using negative image amplifier technique. The objective of this article is to show the performance improvement using negative image amplifier technique and realization of negative valued lumped elements into microstrip line geometry. The innovative technique to realize the negative lumped elements are carried out by using Richard’s Transformation and transmission line calculation. The AWR microwave office tool is used to obtain characteristics of UWB LNA design with hybrid microwave integrated circuit (HMIC) technology. The 2-stage cascaded LNA design using negative image amplifier technique achieves average gain of 23dB gain and low noise figure of less than 2dB with return loss less than -8dB for UWB 3-10GHz. The Proper bias circuit is extracted using DC characteristics of transistor at biasing point 2V, 20mA and discussed in detail with LNA layout. The negative image matching technique is applied for both input and output matching network. This work will be useful for all low power UWB wireless receiver applications.
Modeling of the magnetizing phenomena of doubly fed induction generator using neuro-fuzzy algorithm considering non-linearity
Authors: Jose Julia Tholath , Chattopadhyay Adhir Baran
Published: April 2019

Doubly fed Induction Generators (DFIGs) are quite common in wind energy conversion systems because of their variable speed nature and the lower rating of converters. Magnetic flux saturation in the DFIG significantly affect its behavior during transient conditions such as voltage sag, sudden change in input power and short circuit. The effect of including saturation in the DFIG modeling is significant in determining the transient performance of the generator after a disturbance. To include magnetic saturation in DFIG model, an accurate representation of the magnetization characteristics is inevitable. This paper presents a qualitative modeling for magnetization characteristics of doubly fed induction generator using neuro-fuzzy systems. Neuro-fuzzy systems with one hidden layer of Gaussian nodes are capable of approximating continuous functions with arbitrary precision. The results obtained are compared with magnetization characteristics obtained using discrete fourier transform, polynomial and exponential curve fitting. The error analysis is also done to show the effectiveness of the neuro fuzzy modeling of magnetizing characteristics. By neuro-fuzzy algorithm, fast learning convergence is observed and great performance in accuracy is achieved.
Spam image email filtering using K-NN and SVM
Authors: Zamil Yasmine Khalid , Ali Suhad A. , Naser Mohammed Abdullah
Published: April 2019

The developing utilization of web has advanced a simple and quick method for e-correspondence. The outstanding case for this is e-mail. Presently days sending and accepting email as a method for correspondence is prominently utilized. Be that as it may, at that point there stand up an issue in particular, Spam mails. Spam sends are the messages send by some obscure sender just to hamper the improvement of Internet e.g. Advertisement and many more.  Spammers introduced the new technique of embedding the spam mails in the attached image in the mail. In this paper, we proposed a method based on combination of SVM and KNN. SVM tend to set aside a long opportunity to prepare with an expansive information set. On the off chance that "excess" examples are recognized and erased in pre-handling, the preparation time could be diminished fundamentally. We propose a k-nearest neighbor (k-NN) based example determination strategy. The strategy tries to select the examples that are close to the choice limit and that are effectively named. The fundamental thought is to discover close neighbors to a question test and prepare a nearby SVM that jelly the separation work on the gathering of neighbors. Our experimental studies based on a public available dataset (Dredze) show that results are improved to approximately 98%.