bluuebunny/crossref_metadata_2025 huggingface dataset:
Sliding mode control-based system for the two-link robot arm
Authors: Nguyen Trong-Thang
Published: October 2019

In this research, the author presents the model of the two-link robot arm and its dynamic equations. Based on these dynamic equations, the author builds the sliding mode controller for each joint of the robot. The tasks of the controllers are controlling the Torque in each Joint of the robot in order that the angle coordinates of each link coincide with the desired values. The proposed algorithm and robot model are built on Matlab-Simulink to investigate the system quality. The results show that the quality of the control system is very high: the response angles of each link quickly reach the desired values, and the static error equal to zero.
Power distribution system fault monitoring device for supply networks in Nigeria
Authors: Kareem Olalekan Kabiru , Adekitan Aderibigbe , Awelewa Ayokunle
Published: October 2019

Electric power is the bedrock of our modern way of life. In Nigeria, power supply availability, sufficiency and reliability are major operational challenges. At the generation and transmission level, effort is made to ensure status monitoring and fault detection on the power network, but at the distribution level, particularly within domestic consumer communities there are no fault monitoring and detection devices except for HRC fuses at the feeder pillar. Unfortunately, these fuses are sometimes replaced by a copper wire bridge at some locations rendering the system unprotected and creating a great potential for transformer destruction on overload. This study is focused on designing an on-site power system monitoring device to be deployed on selected household entry power cables for detecting and indicating when phase off, low voltage, high voltage, over current, and blown fuse occurs on the building’s incomer line. The fault indication will help in reducing troubleshooting time and also ensure quick service restoration. After design implementation, the test result confirms design accuracy, device functionality and suitability as a low-cost solution to power supply system fault monitoring within local communities.
Novel framework of retaining maximum data quality and energy efficiency in reconfigurable wireless sensor network
Authors: Prathiba B. , Sankar K. Jaya , Sumalatha V.
Published: October 2019

There are various unseen and unpredictable networking states in Wireless Sensor Network (WSN) that adversely affect the aggregated data quality. After reviewing the existing approaches of data quality in WSN, it was found that the solutions are quite symptomatic and they are applicable only in a static environment; however their successful applicability on dynamic and upcoming reconfigurable network is still a big question. Moreover, data quality directly affects energy conservation among the nodes. Therefore, the proposed system introduces a simple and novel framework that jointly addresses the data quality and energy efficiency using probability-based design approach. Using a simplified analytical methodology, the proposed system offers solution in the form of selection transmission of an aggergated data on the basis of message priority in order to offer higher data utilization factor. The study outcome shows proposed system offers a good balance between data quality and energy efficiency in contrast to existing system.
Natural language description of images using hybrid recurrent neural network
Authors: Jishan Md. Asifuzzaman , Mahmud Khan Raqib , Azad Abul Kalam Al
Published: October 2019

We presented a learning model that generated natural language description of images. The model utilized the connections between natural language and visual data by produced text line based contents from a given image. Our Hybrid Recurrent Neural Network model is based on the intricacies of Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Bi-directional Recurrent Neural Network (BRNN) models. We conducted experiments on three benchmark datasets, e.g., Flickr8K, Flickr30K, and MS COCO. Our hybrid model utilized LSTM model to encode text line or sentences independent of the object location and BRNN for word representation, this reduced the computational complexities without compromising the accuracy of the descriptor. The model produced better accuracy in retrieving natural language based description on the dataset.
Modified CSLBP
Authors: Patil Varsha , Sarode Tanuja
Published: October 2019

Image hashing is an efficient way to handle digital data authentication problem. Image hashing represents quality summarization of image features in compact manner. In this paper, the modified center symmetric local binary pattern (CSLBP) image hashing algorithm is proposed. Unlike CSLBP 16 bin histogram, Modified CSLBP generates 8 bin histogram without compromise on quality to generate compact hash. It has been found that, uniform quantization on a histogram with more bin results in more precision loss. To overcome quantization loss, modified CSLBP generates the two histogram of a four bin. Uniform quantization on a 4 bin histogram results in less precision loss than a 16 bin histogram. The first generated histogram represents the nearest neighbours and second one is for the diagonal neighbours. To enhance quality in terms of discrimination power, different weight factor are used during histogram generation. For the nearest and the diagonal neighbours, two local weight factors are used. One is the Standard Deviation (SD) and other is the Laplacian of Gaussian (LoG). Standard deviation represents a spread of data which captures local variation from mean. LoG is a second order derivative edge detection operator which detects edges well in presence of noise. The proposed algorithm is resilient to the various kinds of attacks. The proposed method is tested on database having malicious and non-malicious images using benchmark like NHD and ROC which confirms theoretical analysis. The experimental results shows good performance of the proposed method for various attacks despite the short hash length.
Efficient bridgeless SEPIC converter fed PMBLDC motor using artificial neural network
Authors: R. Meena Devi , Premalatha L.
Published: October 2019

In this paper, a new design of Bridgeless SEPIC (Single Ended Primary Inductance converter) with Artificial neural network (ANN) fed PMBLDC Motor drive is proposed to improve Power Factor. The proposed converter has single switching device of MOSFET, so the switching losses is reduced.ANN is used to achieve the higher power factor and fixed dc link voltage. Also the ANN methodology the time taken for computation is less since there is no mathematical model. The output voltage depends on the switching frequency of the MOSFET. The BLSEPIC act as a buck operation in continuous conduction mode. Detailed converter analysis, equivalent circuit and closed-loop analysis are presented for 36V, 120W, 1500rpm BLDC Motor drive. This proposed converter produces low conduction loss, low total harmonic reduction, low settling time and high power factor reaching near-unity. All the simulation work is verified with MATLAB – Simulink.
Design of encrypted transceiver Non-coherent OFDM with ability to correct coding bits of information
Authors: Thajeel Kareem J. , Abboud Izz K. , Kunbar Laith A.
Published: October 2019

A differential encrypted transceiver was designed in the signal-to-noise ratio systems. A time"-"spread" frequency-"encoded (TSFE) algorithm was proposed using the orthogonal frequency multiplexing multiplier OFDM. The proposed design was verified under the Doppler frequency effect and there was an improvement in the performance of the signal-to-noise ratio system. As a result, the reliability of decoded data was increased and achieves the ability to correct coding bits of information.
Parallelising reception and transmission in queues of secondary users
Authors: Sad Lak
Published: October 2019

In a cognitive radio network, the secondary users place the packets to be transmitted on a queue to control the order of arrival and to adapt to the network state. Previous conceptions
assigned to each secondary user a single queue that contains both received and forwarded packets. Our present article divides the main queue into two sub queues: one to receive the arrived packets and the other to transmit the available packets. This approach reduces the transmission delay due on the one hand; to the shifting of data placed on the single queue, and on the other hand; to the sequential processing of reception and transmission, in theprevious designs. All without increasing the memory capacity of the queue, in the new approach.
Certificateless and provably-secure digital signature scheme based on elliptic curve
Authors: Toradmalle Dhanashree , Muthukuru Jayabhaskar , Sathyanarayana B
Published: October 2019

With the internet today available at the user’s beck, and call data or Information Security plays a vital role. Confidentiality, Integrity, Availability, and Non-repudiation are the pillars of security on which every application on the web is based on. With these basic requirements the users also need the security in low resource constrained environments making it more challenging for the security experts to design secured cryptographic algorithms. Digital Signatures play a pivotal role in Authentication. They help in verifying the integrity of the data being exchanged. Elliptical curves are the strongest contenders in Digital Signatures, and much research is being done to enhance the method in many ways. The paper briefs a secured and improved ECDSA Elliptical Curve Digital Signature Algorithm which is an improved and secured version of the Digital Signature Algorithm.
An improved ant system algorithm for maximizing system reliability in the compatible module
Authors: Sopa Mana , Angkawisittpan Niwat
Published: October 2019

This paper presents an improved Ant System (AS) algorithm called AS-2Swap for solving one of the reliability optimization problems. The objective is to selection a compatible module in order to maximize the system reliability and subject to budget constraints. This problem is NP-hard and formulated as a binary integer-programming problem with a nonlinear objective function. The proposed algorithm is based on the original AS algorithm and the improvement, focused on choosing the feasible solutions, neighborhood search with Swap technique for each loop of finding the solution. The implementation was tested by the five groups of data sets from the existing meta-heuristic found in the literature. The computational results show that the proposed algorithm can find the global optimal solution and is more accurate for larger problems.
Reliability estimation for the randomly censored pareto distribution
Authors: Smadi Mahmoud M. , Ansari Saiful Islam , Jaradat Ahmed A.
Published: October 2019

Widespread applications of random censoring in life testing experiments to estimate reliability of engineering products or systems are avialable. Different parametric statistical models such as exponential, Rayleigh, Weibull and Maxwell distributions are used under random censoring scheme. In this paper, random censoring under Pareto distribution is considered. The maximum likelihood estimators (MLE’s) of the model parameters and survival function were derived along with Fisher information matrix and asymptotic confidence intervals. A simulation study was performed to observe the behavior of the MLE’s. The simulation results showed that the bias and MSE were reasonably small in all cases.
Multi-scale morphological gradient algorithm based ultra-high-speed directional transmission line protection for internal and external fault discrimination
Authors: Khoudry Elmahdi , Belfqih Abdelaziz , Ouaderhman Tayeb , Boukherouaa Jamal , Elmariami Faissal
Published: October 2019

This paper introduces an ultra-high-speed directional transmission line protection scheme based on multi-scale morphological gradient algorithm (MSMGA). The directional protection scheme sets down the rules for determining the fault position in relation to the relaying point. The MSMGA is used to extract the fault-induced transient characteristics contained in the voltage and current signals. The associated signals are formed from these transient characteristics and the polarity of their local modulus maxima allow the discrimination between internal and external faults.
Solar radiation forecasting in nigeria based on hybrid PSO-ANFIS and WT-ANFIS approach
Authors: Salisu Sani , Mustafa Mohd Wazir , Mustapha Mamunu , Mohammed Olatunji Obalowu
Published: October 2019

For an effective and reliable solar energy production, there is need for precise solar radiation knowledge. In this study, two hybrid approaches are investigated for horizontal solar radiation prediction in Nigeria. These approaches combine an Adaptive Neuro-fuzzy Inference System (ANFIS) with Particle Swarm Optimization (PSO) and Wavelet Transform (WT) algorithms. Meteorological data comprising of monthly mean sunshine hours (SH), relative humidity (RH), minimum temperature (Tmin) and maximum temperature (Tmax) ranging from 2002-2012 were utilized for the forecasting. Based on the statistical evaluators used for performance evaluation which are the root mean square error and the coefficient of determination (RMSE and R²), the two models were found to be very worthy models for solar radiation forecasting. The statistical indicators show that the hybrid WT-ANFIS model’s accuracy outperforms the PSO-ANFIS model by 65% RMSE and 9% R². The results show that hybridizing the ANFIS by PSO and WT algorithms is efficient for solar radiation forecasting even though the hybrid WT-ANFIS gives more accurate results.
A Shortest Data Window Algorithm for Detecting the Power Factor in presence of non-sinusoidal load current
Authors: Omran Safaa S. , Al-Khalid Ali Sh. , Yaseen Amer Atta
Published: October 2019

During recent years, nonlinear power electronic equipments introduce harmonic pollution on electric power systems. It makes the traditional power factor meter can not act accurately when it monitors unbalanced and harmonic loads. In this paper, a new algorithm for detecting the power factor in presence of non-sinusoidal load current is proposed. The proposed algorithm detects the true power factor exactly. By uses only two successive sampled data points of the voltage and the current for each displacement power factor value calculation and two sampled data points for each distortion power factor value calculation, the total/true power factor becomes easy to measure using these values directly. The proposed detector implemented using microcontroller as a main part and has been tested for single phase power system. The test results show that it can measure the true power factor of the loads quickly and accurately.
A voltage electrical distance application for power system load shedding considering the primary and secondary generator controls
Authors: Nghia Le Trong , Anh Quyen Huy , Thanh Binh Phan Thi , An N Thai , Hau P. H.
Published: October 2019

This paper proposes a method for determining location and calculating the minimum amount of power load needed to shed in order to recover the frequency back to the allowable range. Based on the consideration of the primary control of the turbine governor and the reserve power of the generators for secondary control, the minimum amount of load shedding was calculated in order to recover the frequency of the power system. Computation and analysis of the voltage electrical distance between the outage generator and the loads to prioritize distribution of the amount power load shedding at load bus positions. The nearer the load bus from the outage generator is, the higher the amount of load shedding will shed and vice versa. With this technique, a large amount of load shedding could be avoided, hence, saved from economic losses, and customer service interruption. The effectiveness of the proposed method tested on the IEEE 37 bus 9 generators power system standard has demonstrated the effectiveness of this method.
A novel and integrated architecture for identification and cancellation of noise from GSM signal
Authors: N Rekha , Jabeen Fathima
Published: October 2019

There are multiple reasons for the evolution as well as the presence of noise over transmitted GSM signal. In spite of various approaches towards noise cancellation techniques, there are less applicable techniques for controlling noise in acoustic GSM signal. Therefore, the proposed manuscript presents an integrated modelling which performs modelling of noise identification that could significantly assist in successful noise cancellation. The proposed system uses three different approach viz. i) stochastic based approach for noise modelling, ii) analytical-based approach where allocated power acts as one of the prominent factors of noise, and iii) wavelet-based approach for effective decomposition of GSM signal for assisting better noise cancellation technique followed by better retention of signal quality. Simulated in MATLAB, the study outcome shows that it offers a cost-effective implementation, A Practical Approach for Noise identification, and Effective Noise Cancellation with Signal quality retention. The proposed system offers approximately 24% of enhancement in noise reduction as compared to any existing digital filters with 1.6 seconds faster in processing speed.
A novel optimization framework for controlling stabilization issue in design principle of FinFET based SRAM
Authors: H Girish , R Shahshikumar D.
Published: October 2019

The conventional design principle of the finFET offers various constraints that act as an impediment towards improving ther performance of finFET SRAM. After reviewing existing approaches, it has been found that there are not enough work found to be emphasizing on cost-effective optimization by addressing the stability problems in finFET design.Therefore, the proposed system introduces a novel optimization mechanism considering some essential design attributes e.g. area, thickness of fin, and number of components. The contribution of the proposed technique is to determine the better form of thickness of fin and its related aspect that can act as a solution to minimize various other asscoiated problems in finFET SRAM. Implemented using soft-computational approach, the proposed system exhibits that it offers better energy retention, lower delay, and potential capability to offer higher throughput irrespective of presence of uncertain amount of noise within the component.
Sensitivity and packaging improvement of an LCP pressure sensor for intracranial pressure measurement via FEM simulation
Authors: Sattayasoonthorn Preedipat , Suthakorn Jackrit , Chamnanvej Sorayouth
Published: October 2019

A biocompatible liquid crystal polymer (LCP) pressure sensor is proposed for measuring intracranial pressure (ICP) in Traumatic Brain Injury (TBI) patients. Finite element method using COMSOL multiphysics is employed to study the mechanical behavior of the packaged LCP pressure sensor in order to optimize the sensor design. A 3D model of the 8x8x0.2 mm LCP pressure sensor is simulated to investigate the parameters that significantly influence the sensor characteristics under the uniform pressure range of 0 to 50 mmHg. The simulation results of the new design are compared to the experimental results from a previous design. The result shows that reducing the thickness of the sensing membrane can increase the sensitivity up to six times of that previously reported. An improvement of fabrication methodology is proposed to complete the LCP packaging.
A computationally efficient detector for MIMO systems
Authors: Alabed Samer
Published: October 2019

In this work, a newly designed multiple-input multiple-output (MIMO) detector for implementation on software-defined-radio platforms is proposed and its performance and complexity are studied. In particular, we are interested in proposing and evaluating a MIMO detector that provides the optimal trade-off between the decoding complexity and bit error rate (BER) performance as compared to the state of the art detectors. The proposed MIMO decoding technique appears to find the optimal compromise between competing interests encountered in the implementation of advanced MIMO detectors in practical hardware systems where it i) exhibits deterministic decoding complexity, i.e., deterministic latency, ii) enjoys a good complexity–performance trade-off, i.e., it keeps the complexity considerably lower than that of the maximum likelihood detectors with almost optimal performance, iii) allows fully parameterizable performance to complexity trade-off where the performance (or complexity) of the MIMO detector can be adaptively adjusted without the requirement of changing the implementation, iv) enjoys simple implementation and fully supports parallel processing, and v) allows simple and efficient extension to soft-bit output generation for support of turbo decoding. From the simulation results, the proposed MIMO decoding technique shows a substantially improved complexity–performance trade-off as compared to the state of the art techniques.
Design of a compact hexagonal structured dual band MIMO antenna using orthogonal polarization for WLAN and satellite applications
Authors: Dkiouak Aziz , Ouahabi Mohssine El , Zakriti Alia , Khalladi Mohsine , Mchbal Aicha
Published: October 2019

In this paper, a compact dual band multiple-input multiple-output (MIMO) antenna system for WLAN and X-band satellite applications (2.4/9.8 GHz respectively) is proposed. On the top face of the substrate, two antenna elements with a size of 20 × 24 mm2 are placed side by side and fed with matched orthogonal micro-strip lines. The two antenna elements have orthogonal polarization which can reduce the mutual coupling between its ports. The designed antenna system is fabricated and measured to validate the simulation results. The impedance bandwidths are about 370 MHz (2.19 to 2.56 GHz) and 630 MHz (9.44 to 10.07 GHz), while the obtained isolation is greater than 14 dB at the operating bands. Furthermore, the envelope correlation is less than 0.052 and 0.008 at 2.4 and 9.8 GHz, respectively. Hence the diversity gain is higher than 9.98 in the frequency bands of interest.
Implementation of AES using biometric
Authors: R. Srividya , B. Ramesh
Published: October 2019

Mobile Adhoc network is the most advanced emerging technology in the field of wireless communication. MANETs mainly have the capacity of self-forming, self-healing, enabling peer to peer communication between the nodes, without relying on any centralized network architecture. MANETs are made applicable mainly to military applications, rescue operations and home networking. Practically, MANET could be attacked by several ways using multiple methods. Research on MANET emphasizes on data security issues, as the Adhoc network does not befit security mechanism associated with static networks. This paper focuses mainly on data security techniques incorporated in MANET. Also this paper proposes an implementation of Advanced Encryption Standard using biometric key for MANETs. AES implementation includes, the design of most robust Substitution-Box implementation which defines a nonlinear behavior and mitigates malicious attacks, with an extended security definition. The key for AES is generated using most reliable, robust and precise biometric processing. In this paper, the input message is encrypted by AES powered by secured nonlinear S-box using finger print biometric feature and is decrypted using the reverse process.
The impact of the image processing in the indexation system
Authors: Elfakir Youssef , Khaissidi Ghizlane , Mrabti Mostafa , Chenouni Driss
Published: October 2019

This paper presents an efficient word spotting system applied to handwritten Arabic documents, where images are represented with bag-of-visual-SIFT descriptors and a sliding window approach is used to locate the regions that are most similar to the query by following the query-by-example paragon. First, a pre-processing step is used to produce a better representation of the most informative features. Secondly, a region-based framework is deployed to represent each local region by a bag-of-visual-SIFT descriptors. Afterward, some experiments are in order to demonstrate the codebook size influence on the efficiency of the system, by analyzing the curse of dimensionality curve. In the end, to measure the similarity score, a floating distance based on the descriptor’s number for each query is adopted. The experimental results prove the efficiency of the proposed processing steps in the word spotting system.
Optimizing requirement analysis by the use of meta-heuristic in search based software engineering
Authors: Kumar Rajesh , Kumar Rakesh
Published: October 2019

Requirements analysis is the first phase of software development process and it is one of the main concerns of software engineers. The selection of requirements is a complex problem caused by the heterogeneity of the users and their varied interests and demands. In this paper, it is justified that their is a strong need of optimization in requirement analysis. The paper argues that requirement selection can be viewed as an application area of Search-Based Software Engineering(SBSE). The aim is to justify the claim that requirement engineering can be re-formulated as search problem to which meta-heuristic technique can be applied.
Multi-dimensional parametric assessment with IoT in acquaintance of digital pipeline
Authors: Kumar N. Suresh , Rao K Mallikharjuna , Kothuru Mahesh , Narasimha Rao Y.
Published: October 2019

In IoT researches are found millions of devices are connected in global digital infrastructure framed in network fashion. Most of the things on the network use cloud or central database to share their data and control signals to control and manage the devices on the IoT network. Devices on the network need fast traversing paths, to take correct decision in right time. The data synchronization between source and destination is very important in real time parameter maintenance. The multidimensional parametric evaluation of the environment or the surrounding area is facing problems with data synchronization and congestion in the sensor network. This will lead arrival of fault data at the destination. The fault data also leads a misconception at user end. In the present work pipeline integration is proposed to overcome the misconception and synchronization failures. The pipeline and Arduino UNO processor are integrated on Proteus simulation tool. Transducer nodes and the functionalities are analysed with pipeline.
Emergent situations for smart cities: A survey
Authors: Al-Smadi Ahmad Mohamad , Alsmadi Mutasem K. , Karim Baareh Abdel , Almarashdeh Ibrahim , Abouelmagd Hayam , Shidwan Ahmed Osman Saad
Published: October 2019

A smart city is a community that uses communication and information technology to improve sustainability, livability, and feasibility. As any community, there are always unexpected emergencies, which must be treated to preserve the regular order. However, a smart system is needed to be able to respond effectively to these emergent situations. The contribution made in this survey is twofold. Firstly, it provides a comprehensive exhaustive and categorized overview of the existing surveys for smart cities.  The categorization is based on several criteria such as structures, benefits, advantages, applications, challenges, issues, and future directions. Secondly, it aims to analyze several studies with respect to emergent situations and management to smart cities. The analysis is based on several factors such as the challenges and issues discussed, the solutions proposed, and opportunities for future research. The challenges include security, privacy, reliability, performance, scalability, heterogeneity, scheduling, resource management, and latency. Few studies have investigated the emergent situations of smart cities and despite the importance of latency factor for smart city applications, it is rarely discussed.
Design and simulation of UWB microstrip patch antenna for Ku/K bands applications
Authors: El Jourmi Mohammed , Ouahmane Hassan , Kharroubi Fouad
Published: October 2019

In this paper, a compact Rectangular Microstrip Patch Antenna (RMPA) fed by microstrip line has been designed to operate for Ku/K bands applications. The proposed antenna is slotted and optimized to reach a large bandwidth and cover various applications such as 5G communication (in frequency range 24.25-27.5 GHz), fixed and mobile satellite, radionavigation, space research, radiolocation etc. In this design, the substrate used is FR4 with a relative permittivity of 4.4 and a thickness of 1.6 mm. The slotted RMPA has been simulated using Advanced Design System (ADS) software and the obtained results are presented and discussed. The proposed antenna achieves a return loss less than -10 dB and VSWR (voltage standing wave ratio) < 2 in frequency range from 16.58 to 25.29 GHz. The percentage bandwidth provided by the proposed microstrip antenna is 41.61%.
Comparative study of several operation modes of AES algorithm for encryption ECG biomedical signal
Authors: Hameed Mustafa Emad , Mat Ibrahim Masrullizam , Abd Manap Nurulfajar , L. Attiah Mothana
Published: October 2019

Biomedical signal processing provides a cross-disciplinary international forum through which research on signal and images measurement and analysis in clinical medicine as well as biological sciences is shared. Electrocardiography (ECG) signal is more frequently used for diagnosis of cardiovascular diseases. However, the ECG signals contain sensitive private health information as well as details that serve to individually distinguish patients. For this reason, the information must be encrypted prior to transmission across public media so as to prevent unauthorized access by adversaries. In this paper, the proposed the use of the Advanced Encryption Standard algorithm (AES), which is one of a symmetric key block cipher with lightweight properties for enhances confidentiality, integrity and authentication in ECG signal transmission. However, some of the challenges arising from the use of this algorithm are computational overhead and level of security, which occur when handling more complex.The AES algorithm has different operation modes using three different key sizes which can be utilized in encrypting the whole sample of ECG biomedical signal in electronic healthcare. The experiments in this research, exhibit comparative study of using five modes of operation in AES algorithm, which are coupled with three key sizes based on the execution time and security level for the encryption of ECG biomedical signals in electronic healthcare application. Thus, we reported that the CBC mode of the AES algorithm is suitable to be applied of security purpose.
Performance analysis of direction of arrival algorithms for Smart Antenna
Authors: Boustani Btissam , Baghdad Abdennaceur , Sahel Aicha , Badri Abdelmajid
Published: October 2019

This paper presents the performance analysis of the direction of arrival estimation algorithms such as Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), Multiple Signal Classification (MUSIC), Weighted Subspace Fitting (WSF), The Minimum Variance Distortionless Response (MVDR or capon) and beamspace. These algorithms are necessary to overcome the problem of detecting the arrival angles of the received signals in wireless communication. Therefore, these algorithms are evaluated and compared according to several constraints required in smart antenna system parameters, as the number of array elements, number of samples (snapshots), and number of the received signals. The main purpose of this study is to obtain the best estimation of the direction of arrival, which can be perfectly implemented in a smart antenna system. In this context, the ROOT-Weighted Subspace Fitting algorithm provides the most accurate detection of arrival angles in each of the proposed scenarios.
Channel capacity and performance evaluation of precoded MIMO-OFDM system with large-size constellation
Authors: Leftah Hussein A. , Alminshid Huda N.
Published: October 2019

Multiple input-multiple output (MIMO) is a multipath diversity exploring approach which is emerged with orthogonal frequency division multiplexing (OFDM) to produce MIMO-OFDM that is widely used in wireless communications. This paper presents a discrete Hart-ley transform (DHT) precoded MIMO-OFDM system over multipath frequency-selective fading channel with large-size quadrature amplitude modulation (16-QAM, 64-QAM and 256-QAM). A mathematical models for the BER and channel capacity over mutlipath fading channels are also derived in this paper. Average Bit-error-rate (BER) and channel capacity of the presented system is considered and compared with that of the traditional MIMO-OFDM. Simulation results shows that the transmission performance and channel capacity of the proposed schemes is better than that of the traditional MIMO-OFDM without a pre-coder.
Direct solution of uncertain bratu initial value problem
Authors: Anakira N. R. , Shather A. H. , Jameel A. F. , Alomari A. K. , Saaban A.
Published: October 2019

In this paper, an approximate analytical solution for solving the fuzzy Bratu equation based on variation iteration method (VIM) is analyzed and modified without needed of any discretization by taking the benefits of fuzzy set theory. VIM is applied directly, without being reduced to a first order system, to obtain an approximate solution of the uncertain Bratu equation. An example in this regard have been solved to show the capacity and convenience of VIM.
Impacts of photovoltaic power source intermittence on a distribution network
Authors: Garfi Oumaima , Aloui Helmi , Chaker Nadia
Published: October 2019

The integration of the photovoltaic (PV) solar systems into distribution networks has brought new challenges to the network planners. One of the most interesting is to prevent the impacts of the PV intermittent character on the steady state system operation conditions. This work is aimed to investigate such effect on voltage performance, conventional generator daily behavior and automatic voltage regulator operation. Simulations were conducted on a 33-bus IEEE radial distribution power system. In order to provide a reliable study, a real PV power profile was considered. Obtained results over a period of 24 hours revealed that the PV integration contributes to an enhancement of the overall voltage profile, a considerable saving in the total amount of the produced active power and a reduction of power losses. However, the PV intermittent character causes significant transformation in buses voltages daily profiles as well as changes in production plan. To sum up, this paper reports the alterations, caused by the PV source intermittence, which must be taken into consideration by the distribution networks planners to maintain the overall network parameters within safe operating condition
Optimetric analysis of 1x4 array of circular microwave patch antennas for mammographic applications using adaptive gradient descent algorithm
Authors: Adedayo Ojo O. , Onibonoje Moses Oluwafemi , Michael Adegoke Ogunlade
Published: October 2019

Interest in the use of microwave equipment for breast imagery is on the increase owing to its safety, ease of use and friendlier cost. However, some of the pertinent blights of the design and optimization of microwave antenna include intensive consumption of computing resources, high price of software acquisition and very large optimization time. This paper therefore attempts to address these concerns by devising a rapid means of designing and optimizing the performance of a 1×4 array of circular microwave patch antenna for breast imagery applications by deploying the adaptive gradient descent algorithm (AGDA) for a circumspectly designed artificial neural network. In order to cross validate the findings of this work, the results obtained using the adaptive gradient descent algorithm was compared with those obtained with the deployment of the much reported Levenberg-Marquardt algorithm for the same dataset over same frequency range and training constraints. Analysis of the performance of the AGDA neural network shows that the approach is a viable and accurate technique for rapid design and analysis of arrays of circular microwave patch antenna for breast imaging.
Self-organizing map (SOM) for species distribution modelling of birds species at Kenyir landscape
Authors: Asmara Salwana Mohamad , David Gertrude , Abdullah Mohd Tajuddin , Wan Din Wan Isni Sofiah , Eh Phon Danakorn Nincarean a/l , Abidin Ahmad Firdaus Zainal
Published: October 2019

Identifying which biodiversity species are more dominant than others in any area is a very challenging task. This is because of the abundant of biodiversity species that may become the majority species in any particular region. This situation create a large dataset with a complex variables to be analysed. Moreover, the responds of organisms and environmental factors are occurred in a non-linear correlation. The effort to do so is really important in order to conserve the biodiversity of nature. To understand the complex relationships that exist between species distribution and their habitat, we analysed the interactions among bird diversity, spatial distribution and land use types at Kenyir landscape in Terengganu, Malaysia by using artificial neural network (ANN) method of self-organizing map (SOM) analysis. SOM performs an unsupervised and non-linear analysis on a complex and large dataset. It is capable to handle the non-linear correlation between organism and environmental factors because SOM identifies clusters and relationships between variables without the fixed assumptions of linearity or normality. The result suggested that SOM analysis was suited for understanding the relationships between bird species assemblages and habitat characteristics.
Estimation of fines amount in syariah criminal offences using adaptive neuro-fuzzy inference system (ANFIS) enhanced with analytic hierarchy process (AHP)
Authors: Mazlam Ahmad Fitri , Yussof Wan Nural Jawahir Hj Wan , Mamat Rabiei
Published: October 2019

All syariah criminal cases, especially in khalwat offence have their case-fact, and the judges typically look forward to all the facts which were tabulated by the prosecutors. A variety of criteria is considered by the judge to determine the fines amount that should be imposed on an accused who pleads guilty. In Terengganu, there were ten (10) judges, and the judgments were made by the individual decision upon the trial to decide the case. Each judge has a stake, principles and distinctive criteria in determining fines amount on an accused who pleads guilty and convicted. This research paper presents an Adaptive Neuro-fuzzy Inference System (ANFIS) technique combining with Analytic Hierarchy Process (AHP) for estimating fines amount in Syariah (khalwat) criminal. Datasets were collected under the supervision of registrar and syarie judge in the Department of Syariah Judiciary State Of Terengganu, Malaysia. The results showed that ANFIS+AHP could estimate fines efficiently than the traditional method with a very minimal error.
Security assessment framework for educational ERP systems
Authors: Ashraf Hafsa , Alenezi Mamdouh , Nadeem Muhammad , Javid Yasir
Published: October 2019

The educational ERP systems have vulnerabilities at the different layers such as version-specific vulnerabilities, configuration level vulnerabilities and vulnerabilities of the underlying infrastructure. This research has identified security vulnerabilities in an educational ERP system with the help of automated tools; penetration testing tool and public vulnerability repositories (CVE, CCE) at all layers. The identified vulnerabilities are analyzed for any false positives and then clustered with mitigation techniques, available publicly in security vulnerability solution repository like CCE and CWE. These mitigation techniques are mapped over reported vulnerabilities using mapping algorithms. Security vulnerabilities are then prioritized based on the Common Vulnerability Scoring System (CVSS). Finally, open standards-based vulnerability mitigation recommendations are discussed.
An accurate pattern classification for empty fruit bunch based on the age profile of oil palm tree using neural network
Authors: Aziz Wafi , Kasno Afif , Kamarudin Nurkamilia , Tumari Zaidi , Aras Shahrieel , Rusnandi Herdy , Musa Kamal
Published: October 2019

This paper proposes an efficient method for pattern classification system of empty fruit bunch (EFB) by using a neural network technique. The main advantage of this method is the accuracy and speed of algorithm such that it can be computed rapidly with the proposed system. To test the effectiveness of the proposed method, 120 of EFB’s data with different ages and length that been obtained from Malaysian Palm Oil Board (MPOB) are use in the pattern classification process. In addition, there  are three classes of EFB in this system, which are Class 1 (less than 7 year old), Class 2 (8 to 17 year old) and Class 3 (more than 17 year old). It is envisaged that the proposed method is very useful in classifying the EFB and  90% of the sample parameters are successfully classified to its class.
Association of Lipids With Ischemic and Hemorrhagic Stroke
Authors: Gu Xiaoying , Li Yunzhi , Chen Shuohua , Yang Xueli , Liu Fangchao , Li Ying , Li Jianxin , Cao Jie , Liu Xiaoqing , Chen Jichun , Shen Chong , Yu Ling , Huang Jianfeng , Lam Tai-Hing , Fang Xianghua , He Yao , Zhang Xinhua , Lu Xiangfeng , Wu Shouling , Gu Dongfeng
Published: October 2019

Background and Purpose—

Previous results on the association between lipids and stroke were controversial. We investigated the association of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C ), high-density lipoprotein cholesterol (HDL-C), and triglyceride with stroke.

Methods—

Six cohort studies in China with 267 500 participants were included. Cox proportional hazards regression models and restricted cubic spline analyses were used to estimate hazard ratios and 95% CIs and explore linear and nonlinear relationships of lipids and stroke, respectively.

Results—

The median follow-up duration ranged from 6 to 19 years. During 2 295 881 person-years, 8072 people developed stroke. Multivariable adjusted hazard ratios (95% CIs) per 1 mmol/L increase in TC, LDL-C, triglyceride were 1.08 (1.05–1.11), 1.08 (1.04–1.11), 1.07 (1.05-1.09) for ischemic stroke, respectively. Compared with participants with TC 160-199.9 mg/dL, hazard ratios (95% CIs) were 1.43 (1.11–1.85) for hemorrhagic stroke in those with TC <120 mg/dL. Compared with participants with HDL-C 50 to 59.9 mg/dL, hazard ratios (95% CIs) were 1.23 (1.12–1.35), 1.13 (1.04–1.22) for ischemic stroke, and 1.28 (1.10–1.49), 1.17 (1.03–1.33) for hemorrhagic stroke in those with HDL-C <40 and 40 to 49.9 mg/dL, respectively. Restricted cubic spline analyses showed linear relationships of TC and LDL-C, and nonlinear relationships of HDL-C and triglyceride with ischemic stroke (all
P
<0.001). Hemorrhagic stroke showed linear relationships with TC and HDL-C (
P
=0.029 and <0.001 respectively), but no relationship with LDL-C and triglyceride (all
P
>0.05).

Conclusions—

TC, LDL-C, and triglyceride showed positive associations with ischemic stroke. The risk of hemorrhagic stroke was higher when TC was lower than 120 mg/dL. LDL-C and triglyceride showed no association with hemorrhagic stroke. The risks of ischemic and hemorrhagic stroke might be higher when HDL-C was lower than 50 mg/dL.
Language Experience Impacts Brain Activation for Spoken and Signed Language in Infancy: Insights From Unimodal and Bimodal Bilinguals
Authors: Mercure Evelyne , Evans Samuel , Pirazzoli Laura , Goldberg Laura , Bowden-Howl Harriet , Coulson-Thaker Kimberley , Beedie Indie , Lloyd-Fox Sarah , Johnson Mark H. , MacSweeney Mairéad
Published: October 2019

Recent neuroimaging studies suggest that monolingual infants activate a left-lateralized frontotemporal brain network in response to spoken language, which is similar to the network involved in processing spoken and signed language in adulthood. However, it is unclear how brain activation to language is influenced by early experience in infancy. To address this question, we present functional near-infrared spectroscopy (fNIRS) data from 60 hearing infants (4 to 8 months of age): 19 monolingual infants exposed to English, 20 unimodal bilingual infants exposed to two spoken languages, and 21 bimodal bilingual infants exposed to English and British Sign Language (BSL). Across all infants, spoken language elicited activation in a bilateral brain network including the inferior frontal and posterior temporal areas, whereas sign language elicited activation in the right temporoparietal area. A significant difference in brain lateralization was observed between groups. Activation in the posterior temporal region was not lateralized in monolinguals and bimodal bilinguals, but right lateralized in response to both language modalities in unimodal bilinguals. This suggests that the experience of two spoken languages influences brain activation for sign language when experienced for the first time. Multivariate pattern analyses (MVPAs) could classify distributed patterns of activation within the left hemisphere for spoken and signed language in monolinguals (proportion correct = 0.68; p = 0.039) but not in unimodal or bimodal bilinguals. These results suggest that bilingual experience in infancy influences brain activation for language and that unimodal bilingual experience has greater impact on early brain lateralization than bimodal bilingual experience.
Two new species of Peperomia Ruiz & Pavon (Piperaceae) from southeastern Brazil and four new synonymies

Authors: CARVALHO-SILVA MICHELINE , GUIMARÃES ELSIE FRANKLIN , SARNAGLIA JUNIOR VALDERES BENTO
Published: October 2019

Of the 173 species of Peperomia in Brazil, 108 are endemic. Two new species of Peperomia are described from the state of Espírito Santo: P. aggregata and Peperomia spiritus-sancti, the latter one also occurring in Minas Gerais. Both species show characteristics of Peperomia subg. Leptorhynchum (Dahlst.) Trel. ex Samain. Illustrations and morphological comparisons are presented. Four new synonymies are proposed.
Review of the world Monoctonina Mackauer 1961 (Hymenoptera, Braconidae, Aphidiinae): key for their identification and descriptions of five new species
Authors: ČKRKIĆ JELISAVETA , PETROVIĆ ANDJELJKO , KOCIĆ KORANA , KAVALLIERATOS NICKOLAS G. , HEBERT PAUL D.N. , TOMANOVIĆ ŽELJKO
Published: October 2019

The subtribe Monoctonina has long been overlooked when it comes to morphological studies, probably due to the low economic importance of its members. Mainly distributed in high montane areas and forest ecosystems, species of Monoctonina are not often found in large populations and do not parasitize pests of cultivated plants. Our research uncovered five new species belonging to this subtribe (Monoctonus brachyradius sp. n., M. canadensis sp. n., M. inexpectatus sp. n., M. luteus sp. n., and M. parvipalpus sp. n.). We also redescribe species originally described over a century ago, and discuss the utility of certain morphological characters, as well as status of some species within Monoctonina.