bluuebunny/crossref_metadata_2025 huggingface dataset:
A Comparative Analysis of Factor Effecting the Buying Judgement of Smart Phone
Authors: Bhalla Rajni , Amandeep Amandeep , Jain Prateek
Published: January 2019

Smart phone has various utilizations to various clients as per their necessities. With sensational rise in the usage of smart phone the individuals are considering different factors while purchasing a smart phone. This paper has put endeavor to reveal the fundamental factors which effect clients in picking up of the smart phone. A sample of 512 responses was taken through questionnaire. An organized questionnaire was planned with five point Likert scale was utilized to meeting respondent’s .Factor analysis and descriptive statistical tools were applied to extricate the basic variables influence cell phone acquiring choice. The result shows that the most important factors are physical attributes, apps and sounds while the less importance is given to other factors such as convenience, price which can also vary by age, service and gender. The future scope of this paper lies in the fact that whether age, occupation, gender makes any difference in purchasing decision of smart phone.
Load Balance in Data Center SDN Networks
Authors: Emad Ali Tariq , Hussein Morad Ameer , Abdala Mohammed A.
Published: January 2019

In the last two decades, networks had been changed according to the rapid changing in its requirements.  The current Data Center Networks have large number of hosts (tens or thousands) with special needs of bandwidth as the cloud network and the multimedia content computing is increased. The conventional Data Center Networks (DCNs) are highlighted by the increased number of users and bandwidth requirements which in turn have many implementation limitations.  The current networking devices with its control and forwarding planes coupling result in network architectures are not suitable for dynamic computing and storage needs.  Software Defined networking (SDN) is introduced to change this notion of traditional networks by decoupling control and forwarding planes. So, due to the rapid increase in the number of applications, websites, storage space, and some of the network resources are being underutilized due to static routing mechanisms. To overcome these limitations, a Software Defined Network based Openflow Data Center network architecture is used to obtain better performance parameters and implementing traffic load balancing function. The load balancing distributes the traffic requests over the connected servers, to diminish network congestions, and reduce underutilization problem of servers. As a result, SDN is developed to afford more effective configuration, enhanced performance, and more flexibility to deal with huge network designs
Hexa-band MIMO CPW Bow-tie Aperture Antenna Using Particle Swarm Optimization
Authors: Hamid A.K. , Obaid W.
Published: January 2019

A MIMO hexa-band Bowtie Antenna for Wi-Fi is proposed. The MIMO antenna can operate at six frequency bands: 2.4, 4.4, 6.1, 8.5, 10.25 and 12.8 GHz. The MIMO antenna consists of four loaded bowtie hexa-band antennas having the same structure. Each single antenna element is loaded with six metallic strips as well as interconnected parasitic rectangular components. The presented HFSS simulations will show that the MIMO loaded antenna can operate at six frequency bands including 2.4 GHz by obtaining the return loss results, radiation patterns, and other antenna parameters. It will be shown also that the MIMO bowtie antenna has a very low mutual coupling at all the operating frequencies for the specific loaded metallic strips width which was obtained using Particle Swarm Optimization technique.
Review on Security Aspects for Cloud Architecture
Authors: Alam Shaz , Muqeem Mohd , Khan Suhel Ahmad
Published: January 2019

Cloud computing is one of the fastest growing and popular technology in the field of computing. As the concept of cloud computing was introduced in 2006. Since then large number of IT industries join the queue to develop many cloud services and put sensitive information over cloud. In fact cloud computing is no doubt the great innovation in the field of computing but at the same time also poses many challenges. Since a large number of organizations migrate their business to cloud and hence it appears as an attractive target for the malicious attack. The purpose of the paper is to review the available literature for security concerns and highlight a relationship between vulnerabilities, attacks and threats in SaaS model. A mapping is being presented to highlight the impact of vulnerabilities and attacks.
Automation of Air Traffic Management Using Fuzzy Logic Algorithm to Integrate Unmanned Aerial Systems into the National Airspace
Authors: Jenab Kouroush , Pineau Joseph
Published: January 2019

Unmaned Aircraft Systems (UAS) have been increasing in popularity in personal, commercial, and military applications. The increase of the use of UAS poses a significant risk to general air travel, and will burden an already overburdened Air Traffic Control (ATC) network if the Air Traffic Management (ATM) system does not undergo a revolutionary change. Already there have been many near misses reported in the news with personal hobbyist UAS flying in controlled airspace near airports almost colliding with manned aircraft. The expected increase in the use of UAS over the upcoming years will exacerbate this problem, leading to a catastrophic incident involving substantial damage to property or loss of life. ATC professionals are already overwhelmed with the air traffic that exists today with only manned aircraft. With UAS expected to perform many tasks in the near future, the number of UAS will greatly outnumber the manned aircraft and overwhelm the ATC network in short order to the point where the current system will be rendered extremely dangerous, if not useless. This paper seeks to explore the possibility of using the artificial intelligence concept of fuzzy logic to automate the ATC system in order to handle the increased traffic due to UAS safely and efficiently. Automation would involve an algorithm to perform arbitration between aircraft based on signal input to ATC ground stations from aircraft, as well as signal output from the ATC ground stations to the aircraft. Fuzzy logic would be used to assign weights to the many different variables involved in ATM to find the best solution, which keeps aircraft on schedule while avoiding other aircraft, whether they are manned or unmanned. The fuzzy logic approach would find the weighted values for the available variables by running a simulation of air traffic patterns assigning different weights per simulation run, over many different runs of the simulation, until the best values are found that keep aircraft on schedule and maintain the required separation of aircraft
An Enhancement Role and Attribute Based Access Control Mechanism in Big Data
Authors: Meneka M , Meenakshisundaram K.
Published: January 2019

To be able to leverage big data to achieve enhanced strategic insight and make informed decision, an efficient access control mechanism is needed for ensuring end to end security of such information asset. Attribute Based Access Control (ABAC), Role Based Access Control (RBAC) and Event Based Access Control (EBAC) are widely used access control mechanisms. The ABAC system is much more complex in terms of policy reviews, hence analyzing the policy and reviewing or changing user permission are quite complex task. RBAC system is labor intensive and time consuming to build a model instance and it lacks flexibility to efficiently adapt to changing user’s, objects and security policies. EBAC model considered only the events to allocate access controls. Yet these mechanisms have limitations and offer feature complimentary to each other. So in this paper, Event-Role-Attribute based fine grained Access Control mechanism is proposed, it provide a flexible boundary which effectively adapt to changing user’s, objects and security policies based on the event. The flexible boundary is achieved by using temporal and environment state of an event. It improves the big data security and overcomes the disadvantages of the ABAC and RBAC mechanisms. The experiments are conducted to prove the effectiveness of the proposed Event-Role-Attribute based Access Control mechanism over ABAC and RBAC in terms of computational overhead.
Optimisation towards Latent Dirichlet Allocation: Its Topic Number and Collapsed Gibbs Sampling Inference Process
Authors: Subeno Bambang , Kusumaningrum Retno , Farikhin Farikhin
Published: January 2019

Latent Dirichlet Allocation (LDA) is a probability model for grouping hidden topics in documents by the number of predefined topics. If conducted incorrectly, determining the amount of K topics will result in limited word correlation with topics. Too large or too small number of K topics causes inaccuracies in grouping topics in the formation of training models. This study aims to determine the optimal number of corpus topics in the LDA method using the maximum likelihood and Minimum Description Length (MDL) approach. The experimental process uses Indonesian news articles with the number of documents at 25, 50, 90, and 600; in each document, the numbers of words are 3898, 7760, 13005, and 4365. The results show that the maximum likelihood and MDL approach result in the same number of optimal topics. The optimal number of topics is influenced by alpha and beta parameters. In addition, the number of documents does not affect the computation times but the number of words does. Computational times for each of those datasets are 2.9721, 6.49637, 13.2967, and 3.7152 seconds. The optimisation model has resulted in many LDA topics as a classification model. This experiment shows that the highest average accuracy is 61% with alpha 0.1 and beta 0.001.
A Deterministic Eviction Model for Removing Redundancies in Video Corpus
Authors: Malhotra Jyoti , Bakal Jagdish
Published: January 2019

The traditional storage approaches are being challenged by huge data volumes. In multimedia content, every file does not necessarily get tagged as an exact duplicate; rather they are prone to editing and resulting in similar copies of the same file. This paper proposes the similarity-based deduplication approach to evict similar duplicates from the archive storage, which compares the samples of binary hashes to identify the duplicates. This eviction is done by initially dividing the query video into dynamic key frames based on the video length. Binary hash codes of these frames are then compared with existing key frames to identify the differences. The similarity score is determined based on these differences, which decides the eradication strategy of duplicate copy. Duplicate elimination goes through two levels, namely removal of exact duplicates and similar duplicates. The proposed approach has shortened the comparison window by comparing only the candidate hash codes based on the dynamic key frames and aims the accurate lossless duplicate removals. The presented work is executed and tested on the produced synthetic video dataset. Results show the reduction in redundant data and increase in the storage space. Binary hashes and similarity scores contributed to achieving good deduplication ratio and overall performance.
Detection of Proximal Caries at The Molar Teeth Using Edge Enhancement Algorithm
Authors: Na'am Jufriadif , Harlan Johan , Madenda Sarifuddin , Santony Julius , Suharinto Catur
Published: January 2019

Panoramic X-Ray produces produces the most common oral digital radiographic image that it used in dentistry practice. The image can further improve accuracy compared to analog one. This study aims to establish proximal caries edge on enhancement images so they can be easily recognized. The images were obtained from the Department of Radiology, General Hospital of M. Djamil Padang Indonesia. Total file of images to be tested were 101. Firstly, the images are analyzed by dentists who practiced at Segment Padang Hospital Indonesia. They concluded that there is proximal caries in 30 molar teeth. Furthermore, the images were processed using Matlab software with the following steps, i.e. cropping, enhancement, edge detection, and edge enhancement. The accuracy rate of detection of edge enhancement images being compared with that of dentist analysis was 73.3%. In the edge enhancement images proximal caries edge can be found conclusively in 22 teeth and dubiously in eight teeth. The results of this study convinced that edge enhancement images can be recommended to assist dentists in detecting proximal caries. 
Pupil Detection Based on Color Difference and Circular Hough Transfor
Authors: Daway Hazim G. , Kareem Hana H. , Hashim Ahmed Rafid
Published: January 2019

Human pupil eye detection is a significant stage in iris segmentation which is representing one of the most important steps in iris recognition. In this paper, we present a new method of highly accurate pupil detection. This method is consisting of many steps to detect the boundary of the pupil. First, the read eye image (R, G, B), then determine the work area which is consist of many steps to detect the boundary of the pupil. The determination of the work area contains many circles which are larger than pupil region. The work area is necessary to determine pupil region and neighborhood regions afterward the difference in color and intensity between pupil region and surrounding area is utilized, where the pupil region has color and intensity less than surrounding area. After the process of detecting pupil region many steps on the resulting image is applied in order to concentrate the pupil region and delete the others regions by using many methods such as dilation, erosion, canny filter, circle hough transforms to detect pupil region as well as apply optimization to choose the best circle that represents the pupil area. The proposed method is applied for images from palacky university, it achieves to 100 % accurac
Application of the ELECTRE III Method at the Moroccan Rural Electrification Program
Authors: El Mazouri Fatima Zahra , Abounaima Mohammed Chaouki , Zenkouar Khalid , Hilali Alaoui Ahmed El
Published: January 2019

As part of the integrated strategy of the Moroccan state aimed at the social and economic development of the Moroccan rural community, an electrification program has been in place since the 90s. This program, called PEGR, has for main objective the improvement of the electrification rate for the national rural world. Given the large number of villages to be electrified and the colossal budget that will induce, several criteria have been retained to objectively distinguish the villages with the highest priority for electrification. Given the nature of this problem to be solved, which is a multicriteria decision aid problem, we propose in this article to use the multicriteria aggregation method ELECTRE III to rank the villages from the highest priority to the lowest priority for the electrification.
Framework to Analyze Customer’s Feedback in Smartphone Industry Using Opinion Mining
Authors: Gupta Mayank , Sebastian Shoney
Published: January 2019

In the present age, cellular phones are the largest selling products in the world. Big Data Analytics is a method used for examining large and varied data, which we know as big data. Big data analytics is very useful for understanding the world of cellphone business. It is important to understand the requirements, demands, and opinions of the customer. Opinion Mining is getting more important than ever before, for performing analysis and forecasting customer behavior and preferences. This study proposes a framework about the key features of cellphones based on which, customers buy them and rate them accordingly. This research work also provides  balanced and well researched reasons as to why few companies enjoy dominance in the market, while others do not make as much of an impact.
Mining Fuzzy Time Interval Periodic Patterns in Smart Home Data
Authors: Mukhlash Imam , Yuanda Desna , Iqbal Mohammad
Published: January 2019

A convergence of technologies in data mining, machine learning, and a persuasive computer has led to an interest in the development of smart environment to help human with functions, such as monitoring and remote health interventions, activity recognition, energy saving. The need for technology development was confirmed again by the aging population and the importance of individual independent in their own homes. Pattern mining on sensor data from smart home is widely applied in research such as using data mining. In this paper, we proposed a periodic pattern mining in smart house data that is integrated between the FP-Growth PrefixSpan algorithm and a fuzzy approach, which is called as fuzzy-time interval periodic patterns mining. Our purpose is to obtain the periodic pattern of activity at various time intervals. The simulation results show that the resident activities can be recognized by analyzing the triggered sensor patterns, and the impacts of minimum support values to the number of fuzzy-time-interval periodic patterns generated. Moreover, fuzzy-time-interval periodic patterns that are generated encourages to find daily or anomalies resident’s habits.
Feature Extraction of Chest X-ray Images and Analysis using PCA and kPCA
Authors: H Roopa , T Asha
Published: January 2019

Tuberculosis (TB) is an infectious disease caused by mycobacterium which can be diagnosed by its various symptoms like fever, cough, etc. Tuberculosis can also be analyzed by understanding the chest x-ray of the patient which is revealed by an expert physician .The chest x-ray image contains many features which cannot be directly used by any computer system for analyzing the disease. Features of chest x-ray images must be understood and extracted, so that it can be processed to a form to be fed to any computer system for disease analysis. This paper presents feature extraction of chest x-ray image which can be used as an input for any data mining algorithm for TB disease analysis. So texture and shape based features are extracted from x-ray image using image processing concepts. The features extracted are analyzed using principal component analysis (PCA) and kernel principal component analysis (kPCA) techniques. Filter and wrapper feature selection method using linear regression model were applied on these techniques. The performance of PCA and kPCA are analyzed and found that the accuracy of PCA using wrapper approach is 96.07%   when compared to the accuracy of kPCA which is 62.50%. PCA performs well than kPCA with a good accuracy.
Simplified Space Vector Pulse Width Modulation based on Switching Schemes with Reduced Switching Frequency and Harmonics for Five Level Cascaded H-Bridge Inverter
Authors: Sirisha B. , Satishkumar P.
Published: January 2019

This paper presents a simplified control strategy of spacevector pulse width modulation technique with a three segment switching sequence and seven segment switching sequence for high power applications of multilevel inverters. In the proposed method, the inverter switching sequences are optimized for minimization of device switching frequency and improvement of harmonic spectrum by using the three most desired switching states and one suitable redundant state for each space vector. The proposed three-segment sequence is compared with conventional seven-segment sequence for five level Cascaded H-Bridge inverter with various values of switching frequencies including very low frequency. The output spectrum of the proposed sequence design shows the reduction of device switching frequency, current and line voltage THD, thereby minimizing the filter size requirement of the inverter, employed in industrial applications, where sinusoidal output voltage is required.
Optimization for Electric Power Load Forecast
Authors: Ethmane I. A. , Maaroufi M. , Mahmoud A. K. , Yahfdhou A.
Published: January 2019

Load flow studies are one of the most important aspects of power system planning and operation. The main information obtained from this study comprises the magnitudes and phase angles of load bus voltages, reactive powers at generators buses, real and reactive power flow on transmission lines, other variables being known. To solve the problem of load flow, we use the iterative method, of Newton-Raphson. Analysis of the found results using numerical method programmed on the Matlab software and PSS/E Simulator lead us to seek means of controlling the reactive powers and the bus voltages of the Nouakchott power grid in 2030 year. In our case, we projected the demand forecast at 2015 to 2030 years. To solve the growing demand we injected the power plants in the system firstly and secondly when the production and energy demand are difficult to match due to lack of energy infrastructures in 2030.It is proposed to install a FACTS (Flexible Alternative Current Transmission Systems) system at these buses to compensate or provide reactive power in order to maintain a better voltage profile and transmit more power to customers.
A New Windings Design of 24 Slot Capacitor-Start Capacitor-Run Induction Motor
Authors: Anthony Zuriman , Erhaneli Erhaneli
Published: January 2019

The conventional method of a single phase induction motor windings design usually constructed the main and auxiliary windings in both slot. So, there was a complicated winding design if that compare to the three-phase induction motor. Because of that, this study was aimed to design a new windings design of a single phase induction motor that construction like a three-phase induction motor. This study was focused to design a 24 slot capacitor-start capacitor-run induction motor. The windings in the motor are divided in 3 group like a three-phase induction motor. The two windings act as a main windings and the other winding act as auxiliary winding. The current rating of the winding of the proposed single-phase induction motor was 2.74A. The performances of the proposed method were compared with the performances of a three-phase induction motor that had the same current rating. The motor used as a comparator was a three-phase induction of 380/220V, 2.74/4.7A, Y/Δ, cage rotor, 4 poles, 1.5 HP, 1400 RPM, 50Hz. The result of this study showed that the proposed design of single phase induction motor could be operated with better performances than the three-phase comparator induction motor’s.
Design of Wide-band Power Amplifier based on Power Combiner Technique with Low Intermodulation Distortion
Authors: Mabrok Mussa , Zakaria Zahriladha , Saifullah Nasrullah
Published: January 2019

RF power amplifiers are one of challenging blocks in designing radio frequency transceivers, this is due to non-linearity behavior of power amplifiers that leads to inter-modulation distortion. This paper presents the design of wide-band power amplifier which combined with parallel coupled line band pass filter at the input and output of power amplifier to allow the only required frequency band to pass through the power amplifier. Class-A topology and ATF-511P8 transistor are used in this design. Advanced Design System software used as a simulation tool to simulate the designed wide-band power amplifier. The simulation results showed an input return loss (S11) which less than -10dB, and gain (S21) is higher than 10 dB over the entire frequency band and considers as flat as well. The designed amplifier is stable over the bandwidth (K>1). Inter-modulation distortion is -56.919dBc which is less than -50dBc with 10dBm input power. The designed amplifier can be used for the microwave applications which include weather radar, satellite communication, wireless networking, mobile, and TV.
Predicting the Brand Popularity from the Brand Metadata
Authors: K Bhargavi , Babu B Sathish , Iyengar S. S.
Published: January 2019

Social networks have become one of the primary sources of big data, where a variety of posts related to brands are liked, shared, and commented, which are collectively called as brand metadata. Due to the increased boom in E/M-commerce, buyers often refer the brand metadata as a valuable source of information to make their purchasing decision. From the literature study, we found that there are not many works on predicting the popularity of the brand based on the combination of brand metadata and comment’s thoughtfulness analysis. This paper proposes a novel framework to classify the comment’s as thoughtful favored or disfavored comment’s, and later combines them with the brand metadata to forecast the popularity of the brand in near future. The performance of the proposed framework is compared with some of the recent works w.r.t. thoughtful comment’s identification accuracy, execution time, prediction accuracy and prediction time, the results obtained are found to be very encouraging.
Design and Simulation of Novel 11-level Inverter Scheme with Reduced Switches
Authors: Palanisamy R. , Singh Gaurav , Das Priyanka , Selvabharathi D. , Sinha Sourav , Nag Arnab
Published: January 2019

This work recommends the performance of coupled inductor based novel 11-level inverter with reduced number of switches. The inverter which engender the sinusoidal output voltage by the use of split inductor with minimised total harmonic distortion (THD). The voltage stress on each controlled switching devices, capacitor balancing and switching losses can be reduced. The proposed system which gives better controlled output current and improved output voltage with moderate THD value. The switching devices of the system are controlled by using multicarrier sinusoidal pulse width modulation algorithm by comparing the carrier signals with sinusoidal signal. The simulation and experimental results of the proposed 11-level inverter system outputs are established using matlab/Simulink and dsPIC microcontroller respectively.
Balancing Compression and Encryption of Satellite Imagery
Authors: Abboud Ali J. , Albu-Rghaif Ali N. , Jassim Abbood Kirebut
Published: January 2019

With the rapid developments in the remote sensing technologies and services, there is a necessity for combined compression and encryption of satellite imagery. The onboard satellite compression is used to minimize storage and communication bandwidth requirements of high data rate satellite applications. While encryption is employed to secure these resources and prevent illegal use of image sensitive information. In this paper, we propose an approach to address these challenges which raised in the highly dynamic satellite based networked environment. This approach combined compression algorithms (Huffman and SPIHT) and encryptions algorithms (RC4, blowfish and AES) into three complementary modes: (1) secure lossless compression, (2) secure lossy compression and (3) secure hybrid compression. The extensive experiments on the 126 satellite images dataset showed that our approach outperforms traditional and state of art approaches by saving approximately (53%) of computational resources. In addition, the interesting feature of this approach is these three options that mimic reality by imposing every time a different approach to deal with the problem of limited computing and communication resources.
Pilot Decontamination over Time Frequency and Space Domains in Multi-Cell Massive MIMO System
Authors: Hachad Lamiae , Mrabti Fatiha , Ghennioui Hicham , Zouak Mohcine
Published: January 2019

In this article, we show that Pilot contamination problem can be seen as a source separation problem using time, frequency, and space domains. Our method capitalizes on a nonunitary joint diagonalization of spatial quadratic time-frequency (STFD) signal representation to identify the desired and interfering users. We first compute the noise subspace from the STFD matrices selected appropriately. Secondly, we use the noise subspace obtained to estimate the Elevation (El) and the Azimuth (Az) angles for which the MUSIC cost function is maximized. Numerical simulations are provided to illustrate the effectiveness and the behavior of the proposed approach.
Simulink and Simelectronics based Position Control of a Coupled Mass-Spring Damper Mechanical System
Authors: K. Oyetola O. , O. Olaluwoye O.
Published: January 2019

This paper presents the use of Simelectronics Program for modeling and control of a two degrees-of freedom coupled mass-spring-damper mechanical system.The aims of this paper are to establish a mathematical model that represents the dynamic behaviour of a coupled mass-spring damper system and effectively control the mass position using both Simulink and Simelectronics.The mathematical model is derived based on the augmented Lagrange equation and to simulate the dynamic accurately a PD controller is implemented to compensate for the oscillation sustained by the system as a result of the complex conjugate pair poles near to the imaginary axis.The input force has been subjected to an obstacle to mimic actual challenges and to validate the mathematical model a Simulink and Simelectronics models were developed, consequently, the results of the models were compared. According to the result analysis, the controller tracked the position errors and stabilized the positions to zero within a settling time of 6.5sec and significantly reduced the overshoot by 99.5% and 99. 7% in Simulink and Simelectronics respectively. Furthermore, it is found that Simelectronics model proved to be capable having advantages of simplicity, less time-intense and requires no mathematical model over the Simulink approach.
Nonlinear Control of an Active Magnetic Bearing with Output Constraint
Authors: Nguyen Danh Huy , Nguyen Tung Lam , Nguyen Manh Linh , Nguyen Huy Phuong
Published: January 2019

In this paper, an appropriate control strategy is proposed to handle the nonlinear dynamics ofan active magnetic bearing (AMB). The goal of the control design is to drive the AMB rotor to the origin with improved transient response. In order to achieve this task, back stepping control technique with a barrier Lyapunov function are employed to keep the tracking error trajectory inside a predefined zone to avoid possible mechanical contact between rotor and stator. Besides, a speed observer is also used since information about rotor speed is not always available. The stability of the closed-loop system is proven. The effectiveness of the proposed control strategy is verified by numerical simulations.
Near Optimal Receive Antenna Selection Scheme for MIMO System under Spatially Correlated Channel
Authors: Sagar Patel , Jaymin Bhalani
Published: January 2019

Spatial correlation is a critical impairment for practical Multiple Input Multiple Output (MIMO) wireless communication systems. To overcome from this issue, one of the solutions is receive antenna selection. Receive antenna selection is a low-cost, low-complexity and no requirement of feedback bit alternative option to capture many of the advantages of MIMO systems. In this paper, symbol error rate (SER) versus signal to noise ratio (SNR) performance comparasion of proposed receive antenna selection scheme for full rate non-orthogonal Space Time Block Code (STBC) is obtained using simulations in MIMO systems under spatially correlated channel at transmit and receive antenna compare with several existing receive antenna selection schemes. The performance of proposed receive antenna selection scheme is same as conventional scheme and beat all other existing schemes.
The Impact of Social Media Technologies on Adult Learning
Authors: Alsaadat Khalil
Published: January 2019

Technology and social media have presented significant tools for adult learners to learn and advance continually. Fast technological advancements have enabled development of technologies used for learning. Expansion of various tools has given professors, educaters, trainers, instructers, many alternatives towards the implementation of the technology supported learning. The use of social media can improve adult learning outcomes and academic accomplishment. Social media is increasingly proven to be beneficial in adult learning and has a huge potential for adult education. This paper sheds some lights on benefits of social media for adult learners, this is incorporated through the review of previous work and some barriers that encounters social media for learning purposes. Also some social media models are reviewed to show the growth and effect of social media in adult learning context, and suggestions and recommendations are provided.
CSPCR: Cloud Security, Privacy and Compliance Readiness - A Trustworthy Framework
Authors: Bhatia Sugandh , Malhotra Jyoteesh
Published: January 2019

The privacy, handling, management and security of information in a cloud environment are complex and tedious tasks to achieve. With minimum investment and reduced cost of operations an organization can avail and apply the benefits of cloud computing into its business. This computing paradigm is based upon a pay as per your usage model. Moreover, security, privacy, compliance, risk management and service level agreement are critical issues in cloud computing environment. In fact, there is dire need of a model which can tackle and handle all the security and privacy issues. Therefore, we suggest a CSPCR model for evaluating the preparation of an organization to handle or to counter the threats, hazards in cloud computing environment. CSPCR discusses rules and regulations which are considered as pre-requisites in migrating or shifting to cloud computing services.
CBIR of Batik Images using Micro Structure Descriptor on Android
Authors: Minarno Agus Eko , Munarko Yuda , Kurniawardhani Arrie
Published: January 2019

Batik is part of a culture that has long developed and known by the people of Indonesia and the world. However, the knowledge is only on the name of batik, not at a more detailed level, such as image characteristic and batik motifs. Batik motif is very diverse, different areas have their own motifs and patterns related to local customs and values. Therefore, it is important to introduce knowledge about batik motifs and patterns effectively and efficiently. So, we build CBIR batik using Micro-Structure Descriptor (MSD) method on Android platform. The data used consisted of 300 images with 50 classes with each class consists of six images. Performance test is held in three scenarios, which the data is divided as test data and data train, with the ratio of scenario 1 is 50%: 50%, scenario 2 is 70%, 30%, and scenario 3 is 80%: 20%. The best results are generated by scenario 3 with precision valur 65.67% and recall value 65.80%, which indicates that the use of MSD on the android platform for CBIR batik performs well.
An Event-based Middleware for Syntactical Interoperability in Internet of Things
Authors: Pramukantoro Eko Sakti , Anwari Husnul
Published: January 2019

Internet of Things (IoT) connecting sensors or devices that record physical observations of the environment and a variety of applications or other Internet services. Along with the increasing number and diversity of devices connected, there arises a problem called interoperability. One type of interoperability is syntactical interoperability, where the IoT should be able to connect all devices through various data protocols. Based on this problem, we proposed a middleware that capable of supporting interoperability by providing a multi-protocol gateway between COAP, MQTT, and WebSocket. This middleware is developed using event-based architecture by implementing publish-subscribe pattern. We also developed a system to test the performance of middleware in terms of success rate and delay delivery of data. The system consists of temperature and humidity sensors using COAP and MQTT as a publisher and web application using WebSocket as a subscriber. The results for data transmission, either from sensors or MQTT COAP has a success rate above 90%, the average delay delivery of data from sensors COAP and MQTT below 1 second, for packet loss rate varied between 0% - 25%. The interoperability testing has been done using Interoperability assessment methodology and found out that ours is qualified.
A Miniature Microstrip Antenna Array using Circular Shaped Dumbbell for ISM Band Applications
Authors: Ghaloua Ahmed , Zbitou Jamal , Abdellaoui Larbi El , Latrach Mohamed , Errkik Ahmed , Tajmouati Abdelali
Published: January 2019

The aim of this work is the achievement, and the validation of a small microstrip patch antenna array using a circular shaped dumbbell defected ground structure. This work has been dividing into two stages: The first step is to miniaturize a microstrip patch antenna resonating at 5.8GHz, which operate in the Industrial Scientific Medical band (ISM) and the second is to use a circular defected ground structure to shift the resonance frequency of the antenna array from 5.8GHz to 2.45GHz. At last, a miniaturization up to 74.47%, relative to the original microstrip antenna array has accomplished. The antenna structure has designed, optimized and miniaturized using CST MW Studio. The obtained results have compared with Ansoft’s HFSS electromagnetic solver. The antenna array has fabricated on FR-4 substrate, and its reflection coefficient is measured.
Design of CW THz PhotonicTtransmitter based on Low Pass-Filter and Bow-tie Wideband Antenna
Authors: Moumane Ibtissame , Zbitou J. , Latrach M. , Errkik A. , Chakkor O. , Fouad A.
Published: January 2019

This paper presents the design of Continuous Wave Terahertz photonic transmitters which is composed from photodetector (PD) associated to a wideband antenna, low–pass filter (LPF) and DC Probe. Firstly, we have developed the bow-tie wideband antenna using an EM solver Momentum integrated in ADS “Advanced Design System”. Then we had optimized a low-pass filter which is responsible of blocking the RF signal providing from the antenna to reach the DC probe. And finally, we have validated into simulation the CW THz photonic transmitter. The three structures are based on multi-layers GaAs substrate, which is the most widely used for THz circuit design. The dimensions of the Whole circuit are 776.788 × 303.39〖μm〗^2.
Performance Analysis of Adaptive Filter Channel Estimated MIMO OFDM Communication System
Authors: Pyla Srinu , Padma Raju K , Subrahmanyam N Bala
Published: January 2019

Advanced Communication Systems are wideband systems to support multiple applications such as audio, video and data so and so forth. These systems require high spectral efficiency and data rates. In addition, they should provide multipath fading and inter-symbol interference (ISI) free transmission. Multiple input multiple output orthogonal frequency division multiplexing (MIMO OFDM) meets these requirements Hence, MIMO-OFDM is the most preferable technique for long term evaluation advanced (LTE-A). The primary objective of this paper is to control bit error rate (BER) by proper channel coding, pilot carriers, adaptive filter channel estimation schemes and space time coding (STC). A combination of any of these schemes results in better BER performance over individual schemes. System performance is analyzed for various digital modulation schemes. In this paper,adaptive filter channel estimated MIMO OFDM system is proposed by integrating channel coding, adaptivefilter channel estimation, digital modulation and space time coding. From the simulation results, channel estimated 2×2 MIMO OFDM system shows superior performance over individual schemes.
A Novel Technique to Enhance the Lifetime of Wireless Sensor Networks through Software Realization
Authors: Sagar Adarsh , Basavaraju T. G. , Surekha K. B.
Published: January 2019

In the most of the real world scenarios, wireless sensor networks are used. Some of the major tasks of these types of networks is to sense some information and sending it to monitoring system or tracking some activity etc. In such applications, the sensor nodes are deployed in large area and in considerably large numbers [1]-[3]. Each of these node will be having constrained resources whether it might be energy, memory or processing capability. Energy is the major resource constraint in these types of networks. Hence enough care to be taken in all aspects such that energy can be used very efficiently. Different Activities which will be taking place in a sensor node are sensing, radio operations and receiving and computing. Among all these operations, radio consumes maximum power. Hence there is a need of reducing the power consumption in such radio operations. In the proposed work a software module is developed which will reduce the number of transmissions done to the base station. The work compares the consecutively sensed data and if these data are same then the old data then the old data will be retained. In other case the newly sensed data will be sent to the sink node. This technique reduces the number of data transmissions in a significant way. With the reduced number of transmissions, the energy saved in each node will be more, which will increase the lifetime of the entire network.
Mushroom-Like EBG to Improve Patch Antenna Performance For C-Band Satellite Application
Authors: Abdulhameed M. K. , Isa M. S. Mohamad , Zakaria Z. , Mohsin Mowafak K. , Attiah Mothana L.
Published: January 2019

In order to suppress the surface waves excitation that are caused by thick substrate in a patch antenna, a mushroom-like EBG (Electromagnetic Band Gap) structure is used. Such structures enhance its characteristics of gain, directivity, bandwidth and efficiency. Firstly, we determined frequency band gap characteristics of mushroom like EBG unit cell value by using CST software with 3mm (0.06λo) for covering 6 GHz. The periodic arrangement of such mushroom-like EBG structures was not limited by any interconnecting microstrip lines. Four columns of EBGs shifted inwards to antenna edges by 0.3mm (0.06λo) or a gap of its design around the patch from the left and right sides. Different configurations were also examined in order to get the better improvement in antenna performance. The final design of this mushroom-like shifted periodic structure shows an effective increase in the directivity by 77%, gain by 108%, bandwidth by 29% and the efficiency by 20% for the antenna. This structure has diversified application possibility for wireless and satellite communications.
Two Level Disambiguation Model for Query Translation
Authors: Bajpai Pratibha , Verma Parul , Abbas Syed Q.
Published: January 2019

Selection of the most suitable translation among all translation candidates returned by bilingual dictionary has always been quiet challenging task for any cross language query translation. Researchers have frequently tried to use word co-occurrence statistics to determine the most probable translation for user query. Algorithms using such statistics have certain shortcomings, which are focused in this paper. We propose a novel method for ambiguity resolution, named ‘two level disambiguation model’. At first level disambiguation, the model properly weighs the importance of translation alternatives of query terms obtained from the dictionary. The importance factor measures the probability of a translation candidate of being selected as the final translation of a query term. This removes the problem of taking binary decision for translation candidates. At second level disambiguation, the model targets the user query as a single concept and deduces the translation of all query terms simultaneously, taking into account the weights of translation alternatives also. This is contrary to previous researches which select translation for each word in source language query independently. The experimental result with English-Hindi cross language information retrieval shows that the proposed two level disambiguation model achieved 79.53% and 83.50% of monolingual translation and 21.11% and 17.36% improvement compared to greedy disambiguation strategies in terms of MAP for short and long queries respectively.
Sleep Apnea Identification using HRV Features of ECG Signals
Authors: Sulistyo Billy , Surantha Nico , Isa Sani M.
Published: January 2019

Sleep apnea is a common sleep disorder that interferes with the breathing of a person. During sleep, people can stop breathing for a moment that causes the body lack of oxygen that lasts for several seconds to minutes even until the range of hours. If it happens for a long period, it can result in more serious diseases, e.g. high blood pressure, heart failure, stroke, diabetes, etc. Sleep apnea can be prevented by identifying the indication of sleep apnea itself from ECG, EEG, or other signals to perform early prevention. The purpose of this study is to build a classification model to identify sleep disorders from the Heart Rate Variability (HRV) features that can be obtained with Electrocardiogram (ECG) signals. In this study, HRV features were processed using several classification methods, i.e. ANN, KNN, N-Bayes and SVM linear Methods. The classification is performed using subject-specific scheme and subject-independent scheme. The simulation results show that the SVM method achieves higher accuracy other than three other methods in identifying sleep apnea. While, time domain features shows the most dominant performance among the HRV features.
Cognitive Architecture to Analyze the Effect of Intrinsic Motivation with Metacognition over Extrinsic Motivation on Swarm Agents
Authors: Kodipalli Ashwini
Published: January 2019

This research work describes the setup of framework for testing the performance of intrinsically motivated swarm agents over extrinsic motivation. The performance is tested through the simulation. The result demonstrates that agents with intrinsic motivation for specific goal have high metacognitive ability. It also shows group performance of agents with metacognitive ability is better than the group of agents with extrinsic motivation exhibiting cognitive ability. Goal setting theory of motivation is applied to the group of agents in order to analyse the intelligent behaviour of the agents. This research is mainly focusing on why and how group performance by swarm agents is better than individuals. This approach requires design of ambient testbed where swarm agents demonstrate cognitive actions to metacognitive actions. This research is aiming to prove that group performance by swarm agents is higher due to type of agents chosen with intrinsic motivation and thus proves intrinsic motivation is better than extrinsic motivation. Agent behaviour in a group can be analysed using different metrics like resource collection, life expectancy, level of motivation and task assigned.
Forecasting Short-term Wholesale Prices on the Irish Single Electricity Market
Authors: Arci Francesco , Reilly Jane , Li Pengfei , Curran Kevin , Belatreche Ammar
Published: January 2019

Electricity markets are different from other markets as electricity generation cannot be easily stored in substantial amounts and to avoid blackouts, the generation of electricity must be balanced with customer demand for it on a second-by-second basis. Customers tend to rely on electricity for day-to-day living and cannot replace it easily so when electricity prices increase, customer demand generally does not reduce significantly in the short-term. As electricity generation and customer demand must be matched perfectly second-by-second, and because generation cannot be stored to a considerable extent, cost bids from generators must be balanced with demand estimates in advance of real-time. This paper outlines a a forecasting algorithm built on artificial neural networks to predict short-term wholesale prices on the Irish Single Electricity Market so that market participants can make more informed trading decisions. Research studies have demonstrated that an adaptive or self-adaptive approach to forecasting would appear more suited to the task of predicting energy demands in territory such as Ireland. We have identified the features that such a model demands and outline it here.