bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of coherent optical transmission systems performance by DP-QAM levels
Authors: Gafur Abdul , Islam M.S. , Rashid Syed Zahidur
Published: March 2020

In this paper, we investigated the Coherent Optical Transmission System (COTS) performance for multiple types of DP-QAM levels considering various CW laser input power. We compared the performance of COTS for 100 Gb/s with DP-32QAM, DP-64QAM and DP-128QAM respectively. We also inspected the relationship among Optical Signal to Noise Ratio (OSNR), Error Vector Magnitude (EVM) and Bit Error Rate (BER) which are found in accordance for both simulation curves and constellation diagrams. Results are obtained by experiments with DP-32QAM, DP-64QAM and DP-128QAM modulations techniques at symbol rate of 10 Gsymbol/s, 8.33 Gsymbol/s and 7.142 Gsymbol/s respectively. This work is completely based on simulation in Optisystem simulation setup.
Inter-connected coupled lines Resonator topology for bandpass filter application
Authors: Hushim Mohd Nasiruddin , Wahab Norfishah Ab , Tn. Mat Zin Tn. Syarifah Atifah , Ghazali Norlia
Published: March 2020

This paper presents an inter-connected side-shorted coupled-line resonator topology as a base cell. The base cell is built from two single-shorted quarter-wavelength coupled-line sections, connected in series to give a half-wavelength coupled-line that creates a single resonance of bandpass filter response. Higher-order bandpass filter is produced by adding new single-shorted coupled-line sections, cascaded in an inter-connected manner to the base cell. This new topology creates a unique arrangement that caused cross coupling effects between the resonators, resulting to the occurrence of transmission zeros that lead to the improvement of selectivity of the higher order bandpass filter response. For validation of concept, 2nd and 3rd order bandpass filters were fabricated using microstrip technology on Roger 3210 substrate with parameter of Ɛr = 10.2, h = 1.27 mm and tan δ = 3x10-3. The filters were measured and the results show good agreement with simulation results.
On the performance of code word diversity based quasi orthogonal space time block codes in multiple-input-multiple-output systems
Authors: Kumaraswamy SenthilKumar , Manickavel Palanivelan , Valimohamad Noormohammed , Thankaraj Helanvidhya , Venkatesan Yogalakshmi , Veeraragavan Bakyalakshmi
Published: March 2020

In the recent past, a lot of researches have been put into designing a Multiple-Input-Multiple-Output (MIMO) system to provide multimedia services with higher quality and at higher data rate. On par with these requirements, a novel Quasi Orthogonal Space Time Block Code (QOSTBC) scheme based on code word diversity is proposed, which is a multi-dimensional approach, in this paper. The term code word diversity is coined, since the information symbols were spread across many code words in addition to traditional time and spatial spreading, without increasing transmission power and bandwidth. The receiver with perfect channel state information estimates the transmitted symbols with less probability of error, as more number of samples is available to estimate given number of symbols due to the extra diversity due to code words. The simulation results show a significant improvement in the Bit Error Rate (BER) performance of the proposed scheme when compared with the conventional schemes.
Botnet detection using ensemble classifiers of network flow
Authors: Algelal Zahraa M. , Ghani Aldhaher Eman Abdulaziz , Abdul-Wadood Dalia N. , Abdulzhraa Al-Sagheer Radhwan Hussein
Published: March 2020

Recently, Botnets have become a common tool for implementing and transferring various malicious codes over the Internet. These codes can be used to execute many malicious activities including DDOS attack, send spam, click fraud, and steal data. Therefore, it is necessary to use Modern technologies to reduce this phenomenon and avoid them in advance in order to differentiate the Botnets traffic from normal network traffic. In this work, ensemble classifier algorithms to identify such damaging botnet traffic. We experimented with different ensemble algorithms to compare and analyze their ability to classify the botnet traffic from the normal traffic by selecting distinguishing features of the network traffic. Botnet Detection offers a reliable and cheap style for ensuring transferring integrity and warning the risks before its occurrence.
Approach to minimizing consumption of energy in wireless sensor networks
Authors: Noureddine Seddiki , Khelifa Benahmed , Mohammed Belgachi
Published: March 2020

The Wireless Sensor Networks (WSN) technology has benefited from a central position in the research space of future emerging networks by its diversity of applications fields and also by its optimization techniques of its various constraints, more essentially, the minimization of nodal energy consumption to increase the global network lifetime. To answer this saving energy problem, several solutions have been proposed at the protocol stack level of the WSN. In this paper, after presenting a state of the art of this technology and its conservation energy techniques at the protocol stack level, we were interested in the network layer to propose a routing solution based on a localization aspect that allows the creation of a virtual grid on the coverage area and introduces it to the two most well-known energy efficiency hierarchical routing protocols, LEACH and PEGASIS. This allowed us to minimize the energy consumption and to select the clusters heads in a deterministic way unlike LEACH which is done in a probabilistic way and also to minimize the latency in PEGASIS, by decomposing its chain into several independent chains. The simulation results, under "MATLABR2015b", have shown the efficiency of our approach in terms of overall residual energy and network lifetime.
Performance evaluation of high mobility OFDM channel estimation techniques
Authors: Abboud Maryam K. , Sabbar Bayan M.
Published: March 2020

In wireless communication, Orthogonal Frequency Division Multiplexing (OFDM) has been adopted due to its robustness to multipath fading and high data rate transmissions. At the other hand, the performance of OFDM systems severely degraded due to multi-path fading and Doppler frequency shifts in mobile systems, which causes inter-carrier-interference (ICI). Thus, Estimation of channel parameters is required at the receiver using a pre designed estimator where pilot tones are inserted in each OFDM symbol. In this paper, a random pilot data are generated and inserted in each OFDM symbol at equally spaced locations. The performance test of Least Square (LS) and Linear Minimum Mean Square (LMMSE) estimation methods are proposed with Discrete Fourier Transform (DFT) based on both LS and LMMSE, where different ITU channel models are considered in order to compare their performance for data transmission in high mobile systems with different Doppler frequencies exceeds 200 Hz and minimal number of pilots.
Fiber optics based schemes modeling and simulation of QoS for Wi-Fi scenarios using OPNET modeler
Authors: Rhaif Suhad Hasan , Ali Adnan Hussein , Abdulnabi Rana K. , Abdulrazzaq Ali Abdulwahhab
Published: March 2020

Wireless Fidelity (Wi-Fi) network is created on the IEEE 802.11 standard. Connections for local devices in homes and business arenas are provided by Wi-Fi units. With the growing demand as well as penetration of wireless services, the wireless networks users now assume Quality of Service (QoS) besides performances comparable to what is accessible from secure networks. In this paper, OPNET Modeler is used as module and for the simulation of a fiber optic-based Wi-Fi network within a fixed local area network. The aim of this paper is to evaluate their Quality of service (QoS) performances in terms of Wi-Fi voice-packet delay and End-to-End for both Wi-Fi base fiber and Wi-Fi base line. Many scenarios, with same Physical and MAC parameters, have many subnet networks are implementing with fiber optics baseline in addition to Wi-Fi baseline, were created in the network OPNET simulation tool for obtaining the results. The results of simulation reveal that base line demonstrated more delay than base fiber.
Performance assessment of antenna array for an unmanned air vehicle
Authors: Ali Ameer H. , M. Al-Ja'afari Mohannad A. , Abdulwahed Saif H.
Published: March 2020

In this paper, the performance of Linear Antenna Array Element (LAAE) has been evaluated at the Base Station (BS) with a different number of elements for Unmanned Air Vehicle UAV application. The Switched Beam (SB) and Phase Array (PA) have been used as a steering beam mechanism. The beam steering tracker is based on the GPS points of the UAV and the BS. In addition, the Misalignment angle has been analyzed for SB and PA corresponding to the maximum speed of the UAV. The compression between SB and PA in term of Bit Error Rate (BER) vs. Signal to Noise Ratio (SNR) and BER vs. Misalignment angle have been examined by using Matlab. The results show that the PA has better performance than SB in both terms under Additive White Gaussian Noise (AWGN) channel with an interference signal. When the number of the elements is eight provides longer distance than four by the factor (1.5 in SB case and 2 in PA case) and wider Misalignment angle range than twelve by factor (2 in SW case and 3 in PA case). Therefore, it is becoming a useful option for many applications.
Security-aware fair transmission scheme for 802.11 based cognitive IoT
Authors: Oh Hayoung
Published: March 2020

Cognitive IoT is exponentially increased because of various real time and robust applications with sensor networks and big data analysis. Each IoT protocol of network layer can be RPL, COAP and so on based on IETF standards. But still collision problems and security-aware fair transmission on top of scalable IoT devices were not solved enough. In the open wireless LAN system based cognitive IoTs, IoT node that is continuously being stripped of its transmission opportunity will continue to accumulate packets to be sent in the butter and spoofing attacks will not allow the data transfer opportunities to be fair. Therefore, in this paper, we propose a method to reduce the average wait time of all packets in the system by dynamically controlling the contention window (CW) in a wireless LAN based cognitive IoT environment where there are nodes that do not have fair transmission opportunities due to spoofing attacks. Through the performance evaluation, we have proved that the proposed technique improves up to 80% in terms of various performance evaluation than the basic WLAN 802.11 based IoT.
Improved handoff mechanism for infiltrating user equipments in composite networks
Authors: Padyala Venkata Vara Prasad , Kiran K.V.D.
Published: March 2020

The wireless technology and communication plays a vital role in our daily life. The end users are expecting more Quality of Experience (QOE) rather than the Quality of Service (QOS). In order to provide full signal coverage the entire cellular network coverage is divided in to small cells called as femtocells, those femtocells are covered with femtocell antennas which are very small in size compared with regular antennas. With these femtocell coverage problem is solved but when a user moves from one location to another location the user has to switch from one base station to so many base station which cannot be maintained with present handoff methods. The present hand off methods working on distance calculation approach, the proposed method is based on the velocity and device direction calculated based on GPS location toward the Base Station (BS) of the device which may ping pong handoff effect.
Comprehensive investigation of coherent optical OFDM-RoF employing 16QAM external modulation for long-haul optical communication system
Authors: Hussien Anas Ali , Ali Adnan Hussein
Published: March 2020

Given the growing need for long haul transmission that requires a high rate of data, the orthogonal frequency division multiplexing scheme (OFDM), is regarded as a technique with high potentials for high-capacity optical networks. OFDM transmits over both optical and wireless channels, with the data distributed over a huge amount of the subcarrier, and the data is distributed over a huge number of subcarriers. OFDM achieves RF signal for a long-haul transmitting by utilizing Radio over Fiber (RoF) system, which is known to produce higher orthogonality of the OFDM modulated signal designed for the wireless network. RoF systems comprise of heterogeneous networks designed through the use of wireless and optical links. The aim of this paper is to carry out an investigation of the performance of the external modulation in RoF links, while analyzing the shortcomings caused by the various elements of the optical system. The Mach–Zehnder modulator (MZM) can be applied in external modulation, and exhibits a more robust performance when implemented with the OFDM modulation technique.
Design and implementation home security system and monitoring by using wireless sensor networks WSN/internet of things IOT
Authors: Qasim H. H. , Hamza A. E. , Ibrahim H. H. , Saeed H. A. , Hamzah M. I.
Published: March 2020

The dramatic advancments on communication and networking technologies have led to the emergence of Internet-of-Things (IoT). IoT technology has opened the door for various applications. In particular, the home automation was one of the common applications that took the advantage of IoT. Several research efforts have addressed the home automation system using IoT covering wide range of functionalities. One of the concerning tasks is providing a secure system that can give alarms for suspicious activities within the house. This paper presents a secure house system based on IoT where several activities are being sensed and detected. Specifically, gas, humidity, body temperature and motion have been considered within the sensing based on two main types of micro-controller including Arduino and Raspberry Pi. Consequentially, an Android prototype has bene developed in order to give an interactive interface for warning the house owner regarding any suscpicious activities. Results of simulation demonstrated the efficancy of the proposed system
Analysis and simulations of optimal geometry shapes of the 4 and 9 nano hole arrays (NHAs) with surface plasmonics and optical properties of biosensors systems
Authors: Duhis Ahmed hussein , Aljanabi Mohanad
Published: March 2020

The possibility to limit and manipulate photons at nanometer scales attracted a lot of interest for exciting applications from subwavelength in laser, biosensors, biomedical and optoelectronics devices, the sensor optical properties, however; are complex due to two resonances through propagating and localized surface plasmons. The optical properties of surface plasmons (SPs) at the resonant wavelength is depending on the geometrical nanostructure of materials. In this article, we used different geometry of nanoholes array, 4 and 9 nanoholes array in a metallic film gold nanoparticle with different thickness (20,50,100) nm on SiO2 substrate with refractive index 1.46, we designed two different geometries; 4- holes: hole radius r1=200 nm, period p1=600 nm; and 9- holes: r2=100 nm, period p2=300 nm. Transmission and reflection spectrum have been calculated and simulated by FDTD Lumerical program. From results are observed the effect of thickness is interesting, transmission is increased at (t=20nm) for two arrays. Furthermore, the number of hole and its area has an influence on optical transmission and other parameters (E, H, Ref) which are characteristics of design of metallic nanostructure. We can see that there is a peak value of the wavelength at 519 nm approximately to 73% strong light transmission with 4-NHA in the other hand wavelength of 519 nm transmission is 45% with 9-NHA. strong light transmission is hopeful for many applications (biomedical devices, nanoantennas and laser optical fiber).
Two-level scheduling scheme for integrated 4G-WLAN network
Authors: Taha Mohammed Qasim , Hussien Ali Zaid , Ahmed Abdullah Khalid
Published: March 2020

In this paper, a novel scheduling scheme for the Fourth Generation (4G)-Wireless Local Area Network (WLAN) network is proposed to ensure that end to end traffic transaction is provisioned seamlessly. The scheduling scheme is divided into two stages; in stage one, traffic is separated into Actual Time Traffic (ATT) and Non-Actual-Time Traffic (NATT), while in stage two, complex queuing strategy is performed. In stage one, Class-Based Queuing (CBQ) and Deficit Round Robin (DRR) are used for NATT and ATT applications, respectively to separate and forward traffic themselves according to source requirements. Whereas in the stage, two Control Priority Queuing (CPQ) is used to assign each class the appropriate priority level. Evaluation of the performance of the integrated network was done according to several metrics such as end-to-end delay, jitter, packet loss, and network’s throughput. Results demonstrate major improvements for AT services with minor degradation on NAT applications after implementing the new scheduling scheme.
Enhanced direct sequence spread spectrum (eDSSS) Method to Mitigate SINR mismatch in LTE-Wi-Fi integrated networks
Authors: Yusof Azita Laily , Azhar Ainnur Eiza , Ya'acob Norsuzila
Published: March 2020

Demand of data usage and increase of subscribers in Long Term Evolution (LTE) has urged Third Group Partnership Project (3GPP) to find a solution of traffic data growth. In Release 12, the 3GPP introduced Wi-Fi as an alternative to ease the heavy traffic at the LTE base station in dense areas. In contrary with the traffic offloading, Wi-Fi users suffer the worst network degradation because of co-channel interference at frequency 2.4GHz due to collided with LTE band 40. Interference management in LTE-Wi-Fi integrated network is crucial as it affect user’s experiences and services. In this paper, we enhanced a method which is Direct Sequence Spread Spectrum (DSSS) to improve user’s performance in LTE-Wi-Fi network. The DSSS has advantages such as more robust and ability to expand to higher data rates. We introduce a new coefficient called as chip rate coefficient (α) to investigate Signal-to-Interference-Noise Ratio (SINR) expression for User Equipments (UEs) in LTE-Wi-Fi networks. The simulation results discovered that proposed α with value of 0.2 gave the optimum improvement of SINR for LTE and Wi-Fi users. By modifying the SINR expression of the standard DSSS, SINR values at MUE and WUE show better improvement with 4.69% and 17.94%, respectively.
Predictive geospatial analytics using principal component regression
Authors: Khine Kyilai Lai , Nyunt ThiThi Soe
Published: March 2020

Nowadays, exponential growth in geospatial or spatial data all over the globe, geospatial data analytics is absolutely deserved to pay attention in manipulating voluminous amount of geodata in various forms increasing with high velocity. In addition, dimensionality reduction has been playing a key role in high-dimensional big data sets including spatial data sets which are continuously growing not only in observations but also in features or dimensions. In this paper, predictive analytics on geospatial big data using Principal Component Regression (PCR), traditional Multiple Linear Regression (MLR) model improved with Principal Component Analysis (PCA), is implemented on distributed, parallel big data processing platform. The main objective of the system is to improve the predictive power of MLR model combined with PCA which reduces insignificant and irrelevant variables or dimensions of that model. Moreover, it is contributed to present how data mining and machine learning approaches can be efficiently utilized in predictive geospatial data analytics. For experimentation, OpenStreetMap (OSM) data is applied to develop a one-way road prediction for city Yangon, Myanmar. Experimental results show that hybrid approach of PCA and MLR can be efficiently utilized not only in road prediction using OSM data but also in improvement of traditional MLR model.
User experience improvement of japanese language mobile learning application through mental model and A/B testing
Authors: Brata Komang Candra , Brata Adam Hendra
Published: March 2020

Advances in smartphone technology have led to the strong emergence of mobile learning (m-learning) on the market to support foreign language learning purposes, especially for the Japanese language. No matter what kind of m-learning application, their goal should help learners to learn the Japanese language independently. However, popular Japanese m-learning applications only accommodate on enhancing reading, vocabulary and writing ability so that user experience issues are still prevalent and may affect the learning outcome. In the context of user experience, usability is one of the essential factors in mobile application development to determine the level of the application’s user experience. In this paper, we advocate for a user experience improvement by using the mental model and A/B testing. The mental model is used to reflect the user’s inner thinking mode. A comparative approach was used to investigate the performance of 20 high-grade students with homogenous backgrounds and coursework. User experience level was measured based on the usability approach on pragmatic quality and hedonic quality like effectiveness (success rate of task completion), efficiency (task completion time) and satisfaction. The results then compared with an existing Japanese m-learning to gather the insight of improvement of our proposed method. Experimental results show that both m-learning versions proved can enhance learner performance in pragmatic attributes. Nevertheless, the study also reveals that an m-learning that employs the conversational mental model in the learning process is more valued by participants in hedonic qualities. Mean that the proposed m-learning which is developed with the mental model consideration and designed using A/B testing is able to provide conversational learning experience intuitively.
Transforming a Traditional Home Gateway into a Hardware-accelerated SDN Switch
Authors: Miano Sebastiano , Risso Fulvio
Published: March 2020

Nowadays, traditional home gateways must support increasingly complex applications while keeping their cost reasonably low.
Software Defined Networking (SDN) would simplify the management of those devices, but such an approach is typically reserved for new hardware devices, specifically engineered for this paradigm.
As a consequence, typical SDN-based home gateway performs the switching in software, resulting in non-negligible performance degradation.
In this paper, we provide our experience and findings of adding the OpenFlow support into a non-OpenFlow compatible home gateway, exploiting the possible hardware speedup available in the existing platform.
We present our solution that transparently offloads a portion of the OpenFlow rule into the hardware, while keeping the remaining ones in software, being able to support the presence of multiple hardware tables with a different set of features.
Moreover, we illustrate the design choices used to implement the functionalities required by the OpenFlow protocol (e.g., packet-in, packet-out messages) and finally, we evaluate the resulting architecture, showing the significant advantage in terms of performance that can be achieved by exploiting the underlying hardware, while maintaining an SDN-type ability to program and to instantiate desired network operations from a central controller.
Prediction prices of basrah light oil using artificial neural networks
Authors: Ulkareem Naser Maysaa Abd
Published: March 2020

The global economy is assured to be very sensitive to the volatility of the oil market. The beneficial from oil prices collapse are both consumers and developed countries. Iraq economy is a one-sided economy which is completely depends on oil revenue to charge the economic activity. Hence, the current decline in oil prices will produce serious concerns. Some factors stopped most investment projects, rationalize the recurrent outflow, and decrease the development of economic activity. The study of forecast oil prices is considered among the most complex studies because of the different dynamic variables that affects the strategic goods. Moreover, the laws of economics controlling the prices of oil such as the supply and demand law. Some other variables that control the oil prices are the political conditions when these conditions contribute to the world production. The subject of forecasting has been extremely developing during recent years and some modern methods have been appeared in this regards, for example, Artificial Neural Networks. In this study, an artificial neural network (FFNN) is adopted to extract the complex relationships among divergent parameters that have the abilities to predict oil prices serving as an inputs to the network data collected in this research represent monthly time series data are Oil prices series in (US dollars) over a period of 11 years (2008–2018) in Iraq
Stateful library service system design and implementation in Saudi Arabia
Authors: Bramantoro Arif
Published: March 2020

Service system has become one of the most challenging research issues in industry. Most of organizations in Saudi Arabia build their services with state-less technique to avoid many issues although there are some acknowledged advantages of using state-full technique. These issues are mainly related to the low number of visitors, low number of services, storage capacity and organization size. The purpose of this research is to create services that have capability in reading all required data from library management system, improving the service by applying state-full technique. Technology acceptance model is used to measure the acceptance of state-full service system through organizations and customers which gave some prediction to library high management to support them in decision making.
A technical review and comparative analysis of machine learning techniques for intrusion detection systems in MANET
Authors: Laqtib Safaa , El Yassini Khalid , Hasnaoui Moulay Lahcen
Published: March 2020

Machine learning techniques are being widely used to develop an intrusion detection system (IDS) for detecting and classifying cyber attacks at the network-level and the host-level in a timely and automatic manner. However, Traditional Intrusion Detection Systems (IDS), based on traditional machine learning methods, lacks reliability and accuracy. Instead of the traditional machine learning used in previous researches, we think deep learning has the potential to perform better in extracting features of massive data considering the massive cyber traffic in real life. Generally Mobile Ad Hoc Networks have given the low physical security for mobile devices, because of the properties such as node mobility, lack of centralized management and limited bandwidth. To tackle these security issues, traditional cryptography schemes can-not completely safeguard MANETs in terms of novel threats and vulnerabilities, thus by applying Deep learning methods techniques in IDS are capable of adapting the dynamic environments of MANETs and enables the system to make decisions on intrusion while continuing to learn about their mobile environment. An IDS in MANET is a sensoring mechanism that monitors nodes and network activities in order to detect malicious actions and malicious attempt performed by Intruders. Recently, multiple deep learning approaches have been proposed to enhance the performance of intrusion detection system. In this paper, we made a systematic comparison of three models, Inceprtion architecture convolutional neural network Inception-CNN, Bidirectional long short-term memory (BLSTM) and deep belief network (DBN) on the deep learning-based intrusion detection systems, using the NSL-KDD dataset containing information about intrusion and regular network connections, the goal is to provide basic guidance on the choice of deep learning methods in MANET.
Convolutional recurrent neural network with template based representation for complex question answering
Authors: Obula Reddy A. Chandra , Madhavi K.
Published: March 2020

Complex Question answering system is developed to answer different types of questions accurately. Initially the question from the natural language is transformed to an internal representation which captures the semantics and intent of the question. In the proposed work, internal representation is provided with templates instead of using synonyms or keywords. Then for each internal representation, it is mapped to relevant query against the knowledge base. In present work, the Template representation based Convolutional Recurrent Neural Network (T-CRNN) is proposed for selecting answer in Complex Question Answering (CQA) framework. Recurrent neural network is used to obtain the exact correlation between answers and questions and the semantic matching among the collection of answers. Initially, the process of learning is accomplished through Convolutional Neural Network (CNN) which represents the questions and answers separately. Then the representation with fixed length is produced for each question with the help of fully connected neural network. In order to design the semantic matching between the answers, the representation of Question Answer (QA) pair is given into the Recurrent Neural Network (RNN). Finally, for the given question, the correctly correlated answers are identified with the softmax classifier.
A study of code change patterns for adaptive maintenance with AST analysis
Authors: Meqdadi Omar , Aljawarneh Shadi
Published: March 2020

Example-based transformational approaches to automate adaptive maintenance changes plays an important role in software research. One primary concern of those approaches is that a set of good qualified real examples of adaptive changes previously made in the history must be identified, or otherwise the adoption of such approaches will be put in question. Unfortunately, there is rarely enough detail to clearly direct transformation rule developers to overcome the barrier of finding qualified examples for adaptive changes. This work explores the histories of several open source systems to study the repetitiveness of adaptive changes in software evolution, and hence recognizing the source code change patterns that are strongly related with the adaptive maintenance. We collected the adaptive commits from the history of numerous open source systems, then we obtained the repetitiveness frequencies of source code changes based on the analysis of Abstract Syntax Tree (AST) edit actions within an adaptive commit. Using the prevalence of the most common adaptive changes, we suggested a set of change patterns that seem correlated with adaptive maintenance. It is observed that 76.93% of the undertaken adaptive changes were represented by 12 AST code differences. Moreover, only 9 change patterns covered 64.69% to 76.58% of the total adaptive change hunks in the examined projects. The most common individual patterns are related to initializing objects and method calls changes. A correlation analysis on examined projects shows that they have very similar frequencies of the patterns correlated with adaptive changes. The observed repeated adaptive changes could be useful examples for the construction of transformation approaches
A predictive model for network intrusion detection using stacking approach
Authors: Rajagopal Smitha , Kundapur Poornima Panduranga , Katiganere Siddaramappa Hareesh
Published: March 2020

Due to the emerging technological advances, cyber-attacks continue to hamper information systems. The changing dimensionality of cyber threat landscape compel security experts to devise novel approaches to address the problem of network intrusion detection. Machine learning algorithms are extensively used to detect intrusions by dint of their remarkable predictive power. This work presents an ensemble approach for network intrusion detection using a concept called Stacking. As per the popular no free lunch theorem of machine learning, employing single classifier for a problem at hand may not be ideal to achieve generalization. Therefore, the proposed work on network intrusion detection emphasizes upon a combinative approach to improve performance. A robust processing paradigm called Graphlab Create, capable of upholding massive data has been used to implement the proposed methodology. Two benchmark datasets like UNSW NB-15 and UGR’ 16 datasets are considered to demonstrate the validity of predictions. Empirical investigation has illustrated that the performance of the proposed approach has been reasonably good. The contribution of the proposed approach lies in its finesse to generate fewer misclassifications pertaining to various attack vectors considered in the study.
A comprehensive insight towards Pre-processing Methodologies applied on GPS data
Authors: Prabha R. , Kabadi Mohan G
Published: March 2020

Reliability in the utilization of the Global Positioning System (GPS) data demands a higher degree of accuracy with respect to time and positional information required by the user. However, various extrinsic and intrinsic parameters disrupt the data transmission phenomenon from GPS satellite to GPS receiver which always questions the trustworthiness of such data. Therefore, this manuscript offers a comprehensive insight into the data preprocessing methodologies evolved and adopted by present-day researchers. The discussion is carried out with respect to standard methods of data cleaning as well as diversified existing research-based approaches. The review finds that irrespective of a good number of work carried out to address the problem of data cleaning, there are critical loopholes in almost all the existing studies. The paper extracts open end research problems as well as it also offers an evidential insight using use-cases where it is found that still there is a critical need to investigate data cleaning methods.
Simulation, modelling and packet sniffing facilities for IoT: A systematic analysis
Authors: Patel Bimal , Shah Parth
Published: March 2020

Man and Machine in terms of heterogeneous devices and sensors collaborate giving birth to the Internet of Things, Internet of future. Within a short span of time 30billions intelligent devices in form of smart applications will get connected making it difficult to test and debug in terms of time and cost.Simulators play vital role in verifying application and providing security before actually deploying it in real environment.Due to constraint environment in terms of memory, computation, and energy this review paper under a single umbrella will throw insight on comprehensive and in-depth analysis keeping in mind various barriers, critical design characteristics along with the comparison of candidate simulator and packet sniffing tool. Post simulated analysis play vital role in deciding behavior of data and helping research community to satisfy quality of service parameters.This review makes it feasible to make an appropriate choice for simulators and network analyzer tool easy fulfilling needs and making IoT a reality
Classification of instagram fake users using supervised machine learning algorithms
Authors: Purba Kristo Radion , Asirvatham David , Murugesan Raja Kumar
Published: March 2020

On Instagram, the number of followers is a common success indicator. Hence, followers selling services become a huge part of the market. Influencers become bombarded with fake followers and this causes a business owner to pay more than they should for a brand endorsement. Identifying fake followers becomes important to determine the authenticity of an influencer. This research aims to identify fake users' behavior, and proposes supervised machine learning models to classify authentic and fake users. The dataset contains fake users bought from various sources, and authentic users. There are 17 features used, based on these sources: 6 metadata, 3 media info, 2 engagement, 2 media tags, 4 media similarity. Five machine learning algorithms will be tested. Three different approaches of classification are proposed, i.e. classification to 2-classes and 4-classes, and classification with metadata. Random forest algorithm produces the highest accuracy for the 2-classes (authentic, fake) and 4-classes (authentic, active fake user, inactive fake user, spammer) classification, with accuracy up to 91.76%. The result also shows that the five metadata variables, i.e. number of posts, followers, biography length, following, and link availability are the biggest predictors for the users class. Additionally, descriptive statistics results reveal noticeable differences between fake and authentic users.
Design and implement a new mechanism for audio, video and screen recording based on WebRTC technology
Authors: Edan Naktal , Mahmood Sanabil A
Published: March 2020

Many years ago, Flash was essential in browsers to interact with the user media devices, such as a microphone and camera. Today, Web Real-Time Communication (WebRTC) technology has come to substitute the flash, so browsers do not need the flash to access media devices or establish their communication. However, WebRTC standards do not express precisely how browsers can record audios, videos or screen instead of describing getUserMedia API that enables a browser to access microphone and camera. The prime objective of this research is to create a new WebRTC recording mechanism to record audios, videos, and screen using Google Chrome, Firefox, and Opera. This experiment applied through Ethernet and Wireless of the Internet and 4G networks. Also, the recording mechanism of this research was obtained based on JavaScript Library for audio, video, screen (2D and 3D animation) recording. Besides, different audio and video codecs in Chrome, Firefox and Opera were utilised, such as VP8, VP9, and H264 for video, and Opus codec for audio. Not only but also, various bitrates (100 bytes bps, 1 Kbps, 100 Kbps, 1 MB bps, and 1 GB bps), different resolutions (1080p, 720p, 480p, and HD (3840* 2160)), and various frame-rates (fps) 5, 15, 24, 30 and 60 were considered and tested. Besides, an evaluation of recording mechanism, Quality of Experience (QoE) through actual users, resources, such as CPU performance was also done. In this paper, a novel implementation was accomplished over different networks, different browsers, various audio and video codecs, many peers, opening one or multi browsers at the same time, keep the streaming active as much as the user needs, save the record, using only audio and/or video recording as conferencing with full screen, etc.
Performance comparison of selection nanoparticles for insulation of three core belted power cables
Authors: Thabet Ahmed , Mobarak Youssef , Salem Nourhan , El-noby A. M.
Published: March 2020

This paper presents an investigation on the enhancement of electrical insulations of power cables materials using a new multi-nanoparticles technique. It has been studied the effect of adding specified types and concentrations of nanoparticles to polymeric materials such as PVC for controlling on electric and dielectric performance. Prediction of effective dielectric constant has been done for the new nanocomposites based on Interphase Power Law (IPL) model. The multi-nanoparticles technique has been succeeded for enhancing electric and dielectric performance of power cables insulation compared with adding individual nanoparticles. Finally, it has been investigated on electric field distribution in the new proposed modern insulations for three-phase core belted power cables. This research has focused on studying development of PVC nanocomposite materials performance with electric field distribution superior to the unfilled matrix, and has stressed particularly the effect of filler volume fraction on the electric field distribution.
Blockchain outlook for deployment of IoT in distribution networks and smart homes
Authors: Hosseinian Heliasadat , Shahinzadeh Hossein , B. Gharehpetian Gevork , Azani Zohreh , Shaneh Mahdi
Published: March 2020

Nowadays, unlike depleting fossil fuel resources, the integration of different types of renewable energy, as distributed generation sources, into power systems is accelerated and the technological development in this area is evolving at a frantic pace. Thus, inappropriate use of them will be irrecoverably detrimental. The power industry will reach a turning point in the pervasiveness of these infinite energy sources by three factors. Climate changes due to greenhouse gas accumulation in the atmosphere; increased demand for energy consumption all over the world, especially after the genesis of Bitcoin and base cryptocurrencies; and establishing a comprehensive perspective for the future of renewable energy. The increase in the pervasiveness of renewable energy sources in small-scale brings up new challenges for the power system operators to manage an abundant number of small-scale generation sources, called microsources. The current structure of banking systems is unable to handle such massive and high-frequency transactions. Thus the incorporation of cryptocurrencies is inevitable. In addition, by utilization of IoT-enabled devices, a large body of data will be produced must be securely transferred, stored, processed, and managed in order to boost the observability, controllability, and the level of autonomy of the smart power systems. Then the appropriate controlling measures must be performed through control signals in order to serve the loads in a stable, uninterruptible, reliable, and secure way. The data acquires from IoT devices must be analyzed using artificial intelligence methods such as big data techniques, data mining, machine learning, etc. with a scant delay or almost real-time. These measures are the controversial issues of modern power systems, which are yet a matter of debate. This study delves into the aforementioned challenges and opportunities, and the corresponding solutions for the incorporation of IoT and blockchain in power systems, particularly in the distribution level and residential section, are addressed. In the last section, the role of IoT in smart buildings and smart homes, especially for energy hubs schemes and the management of residential electric vehicle supply equipment is concisely discussed.
Behaviour of solar wireless sensor network in saharan region under different scenarios consideration
Authors: Hamlili Boubakeur , Benahmed Khelifa , Gasbaoui Brahim
Published: March 2020

This paper deals with the Wireless Sensor Network comportment in the south west region precisely Bechar city. Algeria has the highest technical and economic potentials for solar power exploitation in the Middle East and North Africa region. In this paper, the focus is on the behaviour of Wireless Sensor Network (WSNs) supplied by solar panel PV connected to node via boost converter (DC/DC) controlled by maximum power point tracking (MPPT) technique, using the incremental conductance (IC) algorithm to extract maximum power. In Our present work, many tests were carried out. The WSNs are examined under sever and different temperature and irradiation variation. The obtained result is satisfactory for our (WSNs) simulated in a MATLAB / SIMULINK environment. The performances of the proposed strategy controller give a satisfactory simulation results.
Short-circuit fault diagnosis of the DC-Link capacitor and its impact on an electrical drive system
Authors: Khelif Amine Mohamed , Bendiabdellah Azeddine , Cherif Bilal Djamal Eddine
Published: March 2020

The reliability of a motor control based on a variable speed drive is an important issue for industrial applications. Most of these machines are inverter based induction motors and are used in specific and complex industrial installations. Unlike the induction motor, the feeding part is very delicate and sensitive to faults. In order to improve system performance, it is therefore very important for a researcher to know the impact of a fault on the whole of his drive system. This paper discusses the short-circuit fault of the DC-link capacitor of an inverter fed induction motor. The simulation results of this type of faults are presented and its impact on the behavior of the rectifier, the inverter as well as the induction motor analyzed and interpreted.
Nonlinear control of WECS based on PMSG for optimal power extraction
Authors: Makhad Mohamed , Zazi Malika , Loulijat Azeddine
Published: March 2020

This paper proposes a robust control strategy for optimizing the maximum power captured in Wind Energy Conversion Systems (WECS) based on permanent magnet synchronous generators (PMSG), which is integrated into the grid. In order to achieve the maximum power point (MPPT) the machine side converter regulates the rotational speed of the PMSG to track the optimal speed. To evaluate the performance and effectiveness of the proposed controller, a comparative study between the IBC control and the vector control based on PI controller was carried out through computer simulation. This analysis consists of two case studies including stochastic variation in wind speed and step change in wind speed.
Generalized optimal placement of PMUs considering power system observability, communication infrastructure, and quality of service requirements
Authors: Elroby M. M. H. , Mekhamer S. F. , Talaat H. E. A. , Hassan M. A. Moustafa
Published: March 2020

This paper presents a generalized optimal placement of Phasor Measurement Units (PMUs) considering power system observability, reliability, Communication Infrastructure (CI), and latency time associated with this CI. Moreover, the economic study for additional new data transmission paths is considered as well as the availability of predefined locations of some PMUs and the preexisting communication devices (CDs) in some buses. Two cases for the location of the Control Center Base Station (CCBS) are considered; predefined case and free selected case. The PMUs placement and their required communication network topology and channel capacity are

co-optimized simultaneously. In this study, two different approaches are applied to optimize the objective function; the first approach is combined from Binary Particle Swarm Optimization-Gravitational Search Algorithm (BPSOGSA) and the Minimum Spanning Tree (MST) algorithm, while the second approach is based only on BPSOGSA. The feasibility of the proposed approaches are examined by applying it to IEEE 14-bus and IEEE 118-bus systems.
A review of optimal operation of microgrids
Authors: Karthik N. , Parvathy A. K. , Arul R.
Published: March 2020

The term microgrid refers to small-scale power grid that can operate autonomously or in concurrence with the area’s main electrical grid.

The intermittent characteristic of DGs which defies the power quality and voltage manifests the requirement for new planning and operation approaches for microgrids. Consequently, conventional optimization methods in new power systems have been critically biased all through

the previous decade. One of the main technological and inexpensive tools in this regard is the optimal generation scheduling of microgrid. As a primary optimization tool in the planning and operation fields, optimal operation has an undeniable part in the power system. This paper reviews and evaluates

the optimal operation approaches mostly related to microgrids. In this work, the foremost optimal generation scheduling approaches are compared in terms of their objective functions, techniques and constraints. To conclude,

a few fundamental challenges occurring from the latest optimal generation scheduling techniques in microgrids are addressed.