bluuebunny/crossref_metadata_2025 huggingface dataset:
Multi-objective based economic environmental dispatch with stochastic solar-wind-thermal power system
Authors: Salkuti Surender Reddy
Published: June 2020

This paper presents an evolutionary based technique for solving the multi-objective based economic environmental dispatch by considering the stochastic behavior of renewable energy resources (RERs). The power system considered in this paper consists of wind and solar photovoltaic (PV) generators along with conventional thermal energy generators. The RERs are environmentally friendlier, but their intermittent nature affects the system operation. Therefore, the system operator should be aware of these operating conditions and schedule the power output from these resources accordingly. In this paper, the proposed EED problem is solved by considering the nonlinear characteristics of thermal generators, such as ramp rate, valve point loading (VPL), and prohibited operating zones (POZs) effects. The stochastic nature of RERs is handled by the probability distribution analysis. The aim of proposed optimization problem is to minimize operating cost and emission levels by satisfying various operational constraints. In this paper, the single objective optimization problems are solved by using particle swarm optimization (PSO) algorithm, and the multi-objective optimization problem is solved by using the multi-objective PSO algorithm. The feasibility of proposed approach is demonstrated on six generator power system.
28 GHz balanced pHEMT VCO with low phase noise and high output power performance for 5G mm-Wave systems
Authors: Es-saqy Abdelhafid , Abata Maryam , Mehdi Mahmoud , Mazer Said , Fattah Mohammed , El Bekkali Moulhime , Algani Catherine
Published: June 2020

This paper presents the study and design of a balanced voltage controlled oscillator VCO for 5G wireless communication systems. This circuit is designed in monolithic microwave integrated circuit (MMIC) technology using PH15 process from UMS foundry. The VCO ensures an adequate tuning range by a single-ended pHEMT varactors configuration. The simulation results show that this circuit delivers a sinusoidal signal of output power around 9 dBm with a second harmonic rejection between 25.87 and 33.83 dB, the oscillation frequency varies between 26.46 and 28.90 GHz, the phase noise is -113.155 and -133.167 dBc/Hz respectively at 1 MHz and 10 MHz offset and the Figure of Merit is -181.06 dBc/Hz. The power consumed by the VCO is 122 mW. The oscillator layout with bias and RF output pads occupies an area of 0.515 mm2.
Design of computerized monitoring and processing system for magnetic field controlling against the phenomenon of black powder in crude oil pipelines
Authors: Attia Hussain , Balhassan Saad
Published: June 2020

Black power represents the main difficulty faced by the oil flow in pipelines. The negative effect of this powder reaches to stop the oil flow due to clogging the pipelines, in addition to the damaging of the crude oil pumps. Many solutions have been proposed in literature based on chemical or physical processes. On the other side, applying the fixed magnetic field has been presented in separation and extraction process of metal impurities in water pipelines applications. From these facts, this paper proposes an alternative solution (idea, design, and methodology for future implementation) for the black power removing from oil pipelines. The proposed system works on firstly sensing the resistivity parameter in the crude oil as an indication about the oil status with respect to the quantity of the black powder particles, then works on monitoring and controlling the level, location, and polarity of the required magnetic field that to work on cracking particles cracking function that in order to facilitate the crude oil motion in the pipelines. In addition, the proposed solution presents a new design of electrical resistivity sensor as an important indication in terms of evaluating the proposed system performance
Channel encoding system for transmitting image over wireless network
Authors: Gururaj Bharathi , Sadashivappa G. N.
Published: June 2020

Various encoding schemes have been introduced till date focusing on an effective image transmission scheme in presence of error-prone artifacts in wireless communication channel. Review of existing schemes of channel encoding systems infer that they are mostly inclined on compression scheme and less over problems of superior retention of signal retention as they lacks an essential consideration of network states. Therefore, the proposed manuscript introduces a cost effective lossless encoding scheme which ensures resilient transmission of different forms of images. Adopting an analytical research methodology, the modeling has been carried out to ensure that a novel series of encoding operation be performed over an image followed by an effective indexing mechanism. The study outcome confirms that proposed system outshines existing encoding schemes in every respect.
An efficient hardware logarithm generator with modified quasi-symmetrical approach for digital signal processing
Authors: Nguyen Minh-Hong
Published: June 2020

This paper presents a low-error, low-area FPGA-based hardware logarithm generator for digital signal processing systems which require high-speed, real time logarithm operations. The proposed logarithm generator employs the modified quasi-symmetrical approach for an efficient hardware implementation. The error analysis and implementation results are also presented and discussed. The achieved results show that the proposed approach can reduce the approximation error and hardware area compared with traditional methods.
Object tracking using motion flow projection for pan-tilt configuration
Authors: Abdul-Kreem Luma Issa , Abdul-Ameer Hussam K.
Published: June 2020

We propose a new object tracking model for two degrees of freedom mechanism. Our model uses a reverse projection from a camera plane to a world plane. Here, the model takes advantage of optic flow technique by re-projecting the flow vectors from the image space into world space. A pan-tilt (PT) mounting system is used to verify the performance of our model and maintain the tracked object within a region of interest (ROI). This system contains two servo motors to enable a webcam rotating along PT axes. The PT rotation angles are estimated based on a rigid transformation of the the optic flow vectors in which an idealized translation matrix followed by two rotational matrices around PT axes are used. Our model was tested and evaluated using different objects with different motions. The results reveal that our model can keep the target object within a certain region in the camera view.
Creation of speech corpus for emotion analysis in Gujarati language and its evaluation by various speech parameters
Authors: Tank Vishal P. , Hadia S. K.
Published: June 2020

In the last couple of years emotion recognition has proven its significance in the area of artificial intelligence and man machine communication. Emotion recognition can be done using speech and image (facial expression), this paper deals with SER (speech emotion recognition) only. For emotion recognition emotional speech database is essential. In this paper we have proposed emotional database which is developed in Gujarati language, one of the official’s language of India. The proposed speech corpus bifurcate six emotional states as: sadness, surprise, anger, disgust, fear, happiness. To observe effect of different emotions, analysis of proposed Gujarati speech database is carried out using efficient speech parameters like pitch, energy and MFCC using MATLAB Software.
Design of an adaptive state feedback controller for a magnetic levitation system
Authors: Abdulwahhab Omar Waleed
Published: June 2020

This paper presents designing an adaptive state feedback controller (ASFC) for a magnetic levitation system (MLS), which is an unstable system and has high nonlinearity and represents a challenging control problem. First, a nonadaptive state feedback controller (SFC) is designed by linearization about a selected equilibrium point and designing a SFC by pole-placement method to achieve maximum overshoot of 1.5% and settling time of 1s (5% criterion). When the operating point changes, the designed controller can no longer achieve the design specifications, since it is designed based on a linearization about a different operating point. This gives rise to utilizing the adaptive control scheme to parameterize the state feedback controller in terms of the operating point. The results of the simulation show that the operating point has significant effect on the performance of nonadaptive SFC, and this performance may degrade as the operating point deviates from the equilibrium point, while the ASFC achieves the required design specification for any operating point and outperforms the state feedback controller from this point of view.
Sliding mode control design for autonomous surface vehicle motion under the influence of environmental factor
Authors: Nurhadi Hendro , Apriliani Erna , Herlambang Teguh , Adzkiya Dieky
Published: June 2020

Autonomous Surface Vehicle (ASV) is a vehicle that is operated in the water surface without any person in the vehicle. Since there is no person in the ASV, a motion controller is essentially needed. The control system is used to make sure that the water vehicle is moving at the desired speed. In this paper, we use a Touristant ASV with the following specifications: the length is 4 meters, the diameter is 1.625 meters, and the height is 1.027 meters. The main contribution of this paper is applying the Sliding Mode Control system to the Touristant ASV model under the influence of environmental factors. The environmental factors considered in this work are wind speed and wave height. The Touristant ASV model is nonlinear and uses three degree of freedom (DOF), namely surge, sway and yaw. The simulation results show that the performance of the closed-loop system by using the SMC method depends on the environmental factors. If environmental factors are higher, then the resulting error is also higher. The average error difference between those resulted from the simulation without environmental factors and those with the influence of environmental factors is 0.05% for surge, sway and yaw motions.
Campus realities: Forecasting user bandwidth utilization using monte carlo simulation
Authors: Bege Haruna , Zubairu Aminu Yusuf
Published: June 2020

Adequate network design, planning, and improvement are pertinent in a campus network as the use of smart devices is escalating. Underinvesting and overinvesting in campus network devices lead to low network performance and low resource utilization respectively. Due to this fact, it becomes very necessary to ascertain if the current network capacity satisfies the available bandwidth requirement. The bandwidth demand varies from different times and periods as the number of connected devices is on the increase. Thus, emphasizing the need for adequate bandwidth forecast. This paper presents a Monte Carlo simulation model that forecast user bandwidth utilization in a campus network. This helps in planning campus network design and upgrade to deliver available content in a period of high and normal traffic load.
A new dynamic speech encryption algorithm based on lorenz chaotic map over internet protocol
Authors: Al-hazaimeh Obaida M.
Published: June 2020

This paper introduces a dynamic speech encryption algorithm based on Lorenz chaotic map over internet protocol to enhance the services of the real-time applications such as increases the security level and reduces latency. The proposed algorithm was divided into two processes: dynamic key generation process using 128-bit hash value to dynamically alter the initial secret keys, and encryption and decryption process using Lorenz system. In the proposed algorithm, the performance evaluation is carried out through efficient simulations and implementations and statistical analysis. In addition, the average time delay in the proposed algorithm and some of the existing algorithms such as AES is compared. The obtained results concluded that, the proposed dynamic speech encryption algorithm is effectually secured against various cryptanalysis attacks and has useful cryptographic properties such as confusion and diffusion for better voice communication in the voice applications field in the Internet.
The resistance of routing protocols against DDOS attack in MANET
Authors: Abdelhaq Maha , Alsaqour Raed , Alaskar Mada , Alotaibi Fayza , Almutlaq Rawan , Alghamdi Bushra , Alhammad Bayan , Sehaibani Malak , Moyna Donia
Published: June 2020

A Mobil Ad hoc Network (MANET) is a wireless multi-hop network with various mobile, self-organized and wireless infrastructure nodes. MANET characteristics such as openness restricted resources and decentralization impact node efficiency and made them easy to be affected by various security attacks, especially Distributed Denial of Service (DDoS) attacks. The goal of this research is to implement a simulation model called DDoS Attack Simulation Model (DDoSM) in Network Simulator 2(NS-2) and to examine the effect of DDoS Attack on various routing protocol types in MANET namely: Zone Routing Protocol (ZRP), Ad hoc On-Demand Distance Vector (AODV) protocol and Location-Aided Routing (LAR) protocol. The introduced model uses the NS-2 simulator to apply DDoS on the three chosen routing protocols. In terms of throughput and end-to-end latency under the consequences of the attack, the performance of three routings protocols was analyzed.
Framework for efficient transformation for complex medical data for improving analytical capability
Authors: A. S. Chandru , K. Seetharam
Published: June 2020

The adoption of various technological advancement has been already adopted in the area of healthcare sector. This adoption facilitates involuntary generation of medical data that can be autonomously programmed to be forwarded to a destined hub in the form of cloud storage units. However, owing to such technologies there is massive formation of complex medical data that significantly acts as an overhead towards performing analytical operation as well as unwanted storage utilization. Therefore, the proposed system implements a novel transformation technique that is capable of using a template based stucture over cloud for generating structured data from highly unstructured data in a non-conventional manner. The contribution of the propsoed methodology is that it offers faster processing and storage optimization. The study outcome also proves this fact to show propsoed scheme excels better in performance in contrast to existing data transformation scheme.
Energy-aware strategy for data forwarding in IoT ecosystem
Authors: Nagarathna K.
Published: June 2020

The Internet of Things (IoT) is looming technology rapidly attracting many industries and drawing research attention. Although the scale of IoT-applications is very large, the capabilities of the IoT-devices are limited, especially in terms of energy. However, various research works have been done to alleviate these shortcomings, but the schemes introduced in the literature are complex and difficult to implement in practical scenarios. Therefore, considering the energy consumption of heterogeneous nodes in IoT eco-system, a simple energy-efficient routing technique is proposed. The proposed system has also employed an SDN controller that acts as a centralized manager to control and monitor network services, there by restricting the access of selfish nodes to the network. The proposed system constructs an analytical algorithm that provides reliable data transmission operations and controls energy consumption using a strategic mechanism where the path selection process is performed based on the remaining energy of adjacent nodes located in the direction of the destination node. The proposed energy-efficient data forwarding mechanism is compared with the existing AODV routing technique. The simulation result demonstrates that the protocol is superior to AODV in terms of packet delivery rate, throughput, and end-to-end delay.
The impact of gamification on students learning engagement
Authors: Khaleel Firas Layth , Ashaari Noraidah Sahari , Tengku Wook Tengku Siti Meriam
Published: June 2020

Gamification is to use game elements in a non-game context to increase engagement between human and computer, on the other hand, to encourage in-demand for good behaviors in learning. This research tried to increase student engagements in learning by conducted Gamification technique especially in difficult subjects such as Programming Language courses. The previous work was shown that students dropped, failed, or withdrew from the course at rates of between 35% and 50%. Therefore the main objective of this study is to increase student engagements in learning programming subject, and also to measure the impact of game elements on student’s engagements. Finally, the findings have shown the score of game elements that have a good effect on student’s engagement in the experiment group.
Modelling turn away intention of information technology professionals in Bangladesh: a partial least squares approach
Authors: Arman Md. Shohel , Akter Rozina , Mahmud Imran , Ramayah T.
Published: June 2020

Despite, Bangladesh produces many IT graduates each year but only one tenth of total graduates contribute in IT development sector. In order to keep the contribution to economy through IT development, it is crucial for IT industry to know the factors that influence turn away of IT graduates. In this paper, building upon role stress theory, we develop a research model to explore the influence of workplace exhaustion and threat of professional obsolescence (TPO). Data were gathered from 185 IT professionals from 15 different IT companies through survey questionnaire. The structural equation modelling technique was used to test the paths. The results suggests that strong influence of TPO on turn-away intentions. Result also suggests significant roles of work overload, family-career conflict and control over career and workplace exhaustion on turn away intention. This paper contributes to the body of work dedicated to helping us better understand the turn away behaviour from the workplace exhaustion and TPO perspectives. From the viewpoint of practice, this research sheds light on some of the challenges that the IT industry might face when making strategy and policy to control turn away from IT profession in Bangladesh
Distribution network reconfiguration for loss reduction using PSO method
Authors: Merzoug Yahiaoui , Abdelkrim Bouanane , Larbi Boumediene
Published: June 2020

In recent years, the reconfiguration of the distribution network has been proclaimed as a method for realizing power savings, with virtually zero cost. The current trend is to design distribution networks with a mesh network structure, but to operate them radially. This is achieved by the establishment of an appropriate number of switchable branches which allow the realization of a radial configuration capable of supplying all of the normal defects in the box of permanent defect. The purpose of this article is to find an optimal reconfiguration using a Meta heuristic method, namely the particle swarm optimization method (PSO), to reduce active losses and voltage deviations by taking into account certain technical constraints. The validity of this method is tested on a 33-IEEE test network and the results obtained are compared with the results of basic load flow.
Modified sub-gradient based combined objective technique and evolutionary programming approach for economic dispatch involving valve-point loading, enhanced prohibited zones and ramp rate constraints
Authors: Gachhayat Susanta Kumar , Dash Saroja Kumar
Published: June 2020

A security constrained non-convex power dispatch problem with prohibited operation zones and ramp rates is formulated and solved using an iterative solution method based on the feasible modified sub-gradient algorithm (FMSG). Since the cost function, all equality and inequality constraints in the nonlinear optimization model are written in terms of the bus voltage magnitudes, phase angles, off-nominal tap settings, and the Susceptance values of static VAR (SVAR) systems, they can be taken as independent variables. The actual power system loss is included in the current approach and the load flow equations are inserted into the model as the equality constraints. The proposed modified sub gradient based combined objective technique and evolutionary programming approach (MSGBCAEP) with as decision variable and cost function as fitness function is tested on the IEEE 30-bus 6 generator test case system. The absence of crossover operation and adoption of fast judicious modifications in initialization of parent population, offspring generation and normal distribution curve selection in EP enables the proposed MSGBCAEP approach to ascertain global optimal solution for cost of generation and emission level shown in Table 6 and displayed in Figure 2 and Figure 3 respectively.
Optimal power generation for wind-hydro-thermal system using meta-heuristic algorithms
Authors: Nguyen Thuan Thanh , Phan Van-Duc , Dinh Bach Hoang , Phan Tan Minh , Nguyen Thang Trung
Published: June 2020

In this paper, Cuckoo search algorithm (CSA) is suggested for determining optimal operation parameters of the combined wind turbine and hydrothermal system (CWHTS) in order to minimize total fuel cost of all operating thermal power plants while all constraints of plants and system are exactly satisfied. In addition to CSA, Particle swarm optimization (PSO), PSO with constriction factor and inertia weight factor (FCIWPSO) and Social Ski-Driver (SSD) are also implemented for comparisons. The CWHTS is optimally scheduled over twenty-four one-hour interval and total cost of producing power energy is employed for comparison. Via numerical results and graphical results, it indicates CSA can reach much better results than other ones in terms of lower total cost, higher success rate and faster search process. Consequently, the conclusion is confirmed that CSA is a very efficient method for the problem of determining optimal operation parameters of CWHTS.
The application of double-layer remote phosphor structures in increasing WLEDs color rendering index and lumen output
Authors: Phuong Loan Nguyen Thi , Quoc Anh Nguyen Doan
Published: June 2020

The remote phosphor structure often has inferior color quality but better luminous flux in than conformal or in-cup configurations. Therefore, numerous researches study remote phosphor structure for methods to enhance it chromatic quality. This study introduces the use of dual-layer remote phosphor structure in WLEDs with identical structure but at different color temperature, 6600K and 7700K, to demonstrate their effect on quality indicators. The concept is placing a green phosphor layer (Ce,Tb)MgAl11O19:Ce:Tb or a red phosphor layer MgSr3Si2O8:Eu2+,Mn2+ on the layer of yellow-emitting phosphor YAG:Ce3+ and find the suitable concentration of the additional phosphor to create the best color quality. The results showed that the increase of CRI and CQS are affected by MgSr3Si2O8:Eu2+,Mn2+, in particular, the higher the concentration of red phosphor gets the better CRI and CQS because the emitted red light in enhanced. The green phosphor layer (Ce,Tb)MgAl11O19:Ce:Tb, on the other hand, is beneficial for the luminous flux. The concentration of MgSr3Si2O8:Eu2+,Mn2+ and (Ce,Tb)MgAl11O19:Ce:Tb, however, need to be adjusted properly to avoid decreasing the luminous flux due to overgrowth. The Mie scattering theory and Beer’s law are the verification tools for these conclusions, which gives them the credibility to be applied in producing better quality WLEDs.
Novel framework for optimized digital forensic for mitigating complex image attacks
Authors: T. M. Shashidhar , Ramesh K. B.
Published: June 2020

Digital Image Forensic is significantly becoming popular owing to the increasing usage of the images as a media of information propagation. However, owing to the presence of various image editing tools and softwares, there is also an increasing threats over image content security. Reviewing the existing approaches of identify the traces or artifacts states that there is a large scope of optimization to be implmentation to further enhance teh processing. Therfore, this paper presents a novel framework that performs cost effective optmization of digital forensic tehnqiue with an idea of accurately localizing teh area of tampering as well as offers a capability to mitigate the attacks of various form. The study outcome shows that propsoed system offers better outcome in contrast to existing system to a significant scale to prove that minor novelty in design attribute could induce better improvement with respect to accuracy as well as resilience toward all potential image threats.
Cyber-physical system based on image recognition to improve traffic flow: A case study
Authors: Padilla Vladimir Sanchez , Ponguillo Ronald A. , Abad Arnaldo A. , Salas Lissette E.
Published: June 2020

Vehicular trafﬁc in metropolitan areas turns congested along either paths or periods. As a case study, we have considered a mass transport system with a bus ﬂeet that rides over exclusive lanes across streets and avenues in an urban area that does not allow

the circulation of lightweight vehicles, cargo, and motorcycles. This trafﬁc ﬂow becomes congested due to the absence of restriction policies based on criteria. Moreover, the exclusive lanes are at ground level, decreasing lanes for other vehicles. The main objective of this proposal consists of controlling the access to the exclusive lanes by a cyber-physical system following authorization conditions, verifying the permission status of a vehicle by the accurate recognition of license plates to reduce trafﬁc congestion. Therefore, in the case of invading an exclusive lane without permission, the vehicle owner gets a notiﬁcation of the ﬁne with the respective evidence.
Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer
Authors: Sule Aliyu Hamza , Mokhtar Ahmad Safawi , Bin Jamian Jasrul Jamani , Khidrani Attaullah , Larik Raja Masood
Published: June 2020

The need for tuning the PI controller is to improve its performance metrics such as rise time, settling time and overshoot. This paper proposed the Grey Wolf Optimizer (GWO) tuning method of a Proportional Integral (PI) controller for fixed speed Wind Turbine. The objective is to overcome the limitations in using the PSO and GA tuning methods for tuning the PI controller, such as quick convergence occurring too soon into a local optimum, and the controller step input response. The GWO, the Particle Swarm Optimization (PSO), and the Genetic Algorithm (GA) tuning methods were implemented in the Matlab 2016b to search the optimal gains of the Proportional and Integral controller through minimization of the objective function. A comparison was made between the results obtained from the GWO tuning method against PSO and GA tuning techniques. The GWO computed the smallest value of the objective function minimized. It exhibited faster convergence and better time response specification compared to other methods. These and more performance indicators show the superiority of the GWO tuning method.
Power fuzzy adaptive control for wind turbine
Authors: Hocini Yacine , Allali Ahmed , Boulouiha Houari Merabet
Published: June 2020

In recent years, wind energy has become one of the most promising renewable energy sources. The doubly-fed induction generator (DFIG) is currently the most common type of generator used in wind farms. This paper describes an approach for the independent control of the active and reactive power of the variable-speed DFIG. This paper deals with the control of the active and reactive powers in a DFIG designed for a wind system. The simulation model including a 7 KW - DFIG driven by a wind turbine, a PWM inverter and the proposed control strategy are developed and implemented using Matlab Simulink.
Parallel distribution compensation PID based on Takagi-Sugeno fuzzy model applied on egyptian load frequency control
Authors: Ghany M. A. , Shamseldin Mohamed A.
Published: June 2020

This paper presents a new technique for a Takagi-Sugeno (TS) fuzzy parallels distribution compensation-PID'S (TSF-PDC-PID'S) to improve the performance of Egyptian load frequency control (ELFC). In this technique, the inputs to a TS Fuzzy model are the parameters of the change of operating points. The TS Fuzzy model can definite the suitable PID control for a certain operating point. The parameters of PID'S controllers are obtained by ant colony optimization (ACO) technique in each operating point based on an effective cost function. The system controlled by the proposed TSF-PDC-PID’S is investigated under different types of disturbances, uncertainty and parameters variations. The simulation results ensure that the TSF-PDC-PID'S can update the suitable PID controller at several operating points so, it has a good dynamic response under many types of disturbances compared to fixed Optimal PID controller.
Fault diagnosis of rolling element bearings using artificial neural network
Authors: Souad Saadi Laribi , Azzedine Bendiabdellah , Meradi Samir
Published: June 2020

Bearings are essential components in the most electrical equipment. Procedures for monitoring the condition of bearings must be developed to prevent unexpected failure of these components during operation to avoid costly consequences. In this paper, the design of a monitoring system for the detection of rolling element-bearings failure is proposed. The method for detecting and locating this type of fault is carried out using advanced intelligent techniques based on a Perceptron Multilayer Artificial Neural Network (MLP-ANN); its database uses statistical indicators characterizing vibration signals. The effectiveness of the proposed method is illustrated using experimentally obtained bearing vibration data, and the results have shown good accuracy in detecting and locating defects.
On the performance of energy harvesting AF partial relay selection with TAS and outdated channel state information over identical channels
Authors: Odeyemi Kehinde O. , Owolawi Pius A.
Published: June 2020

Energy scarcity has been known to be one of the most noticeable challenges in wireless communication system. In this paper, the performance of an energy harvesting based partial relay selection (PRS) cooperative system with transmit antenna selection (TAS) and outdated channel state information (CSI) is investigated. The system dual-hops links are assumed to follow Rayleigh distribution and the relay selection is based on outdated CSI of the first link. To realize the benefit of multiple antenna, the amplified-and-forward (AF) relay nodes then employs the TAS technique for signal transmission and signal reception is achieved at the destination through maximum ratio combining (MRC) scheme. Thus, the closed-form expression for the system equivalent end-to-end cumulative distribution function (CDF) is derived. Based on this, the analytical closed-form expressions for the outage probability, average bit error rate, and throughput for the delay-limited transmission mode are then obtained. The results illustrated that the energy harvesting time, relay distance, channel correlation coefficient, the number of relay transmit antennas and destination received antenna have significant effect on the system performance. Monte-carol simulation is employed to validate the accuracy of the derived expressions.
Performance evaluation of decode and forward cooperative diversity systems over nakagami-m fading channels with non-identical interferers
Authors: Al-Mistarihi Mamoun F. , Mohaisen Rami , Darabkh Khalid A.
Published: June 2020

The deficiencies of regular cooperative relaying schemes were the main reason behind the development of Incremental Relaying (IR). Fixed relaying is one of the regular cooperative relaying schemes and it relies on using the relay node to help in transmitting the signal of the source towards the destination despite the channel’s condition. However, adaptive relaying methods allocate the channel resources efficiently; thus, such methods have drawn the attention of researchers in recent years. In this study, we analyze a two-hop Decode-and-Forward (DF) IR system’s performance via Nakagami-m fading channels with the existence of the several L distinguishable interferers placed close to the destination which diminishes the overall performance of the system due to the co-channel interference. Tight formulas for the Bit Error Rate (BER) and the Outage Probability (OP) are drawn. The assumptions are consolidated by numerical calculations.
Radiation effect of fractal sierpinski square patch antenna
Authors: Kuther Khalid Hussein , Ali Israa Hazem , Ahmed Riyadh Khlf
Published: June 2020

Biological tissue interaction with Electromagnetic fields became one of the interesting studies in the last years. Wide variety wireless electronic devices are emerged in day to day life each providing a wireless connection for a certain service such as Global Positioning System, broadcasting systems, mobile communication systems, and networking. In this research article, Fractal Sierpinski Square Patch Antenna is proposed and simulated to operate over L1 frequency range of 1.575 GHz for GPS applications using CST studio Suite where the proposed antenna has been investigated on Carpet shaped substrate made of Arlon 250 AD lossy. The dielectric constant equals to 2.5 and thickness of 1.6 mm. Thickness of patch is 0.6 mm. Also, the electromagnetic fields absorption on the human fingers is investigated where SAR levels are calculated for 0th, 1st, 2nd and 3rd iteration of the Fractal Sierpinski Square Patch Antenna. The results reported that the SAR limit of human finger tissue is enhanced with increasing the number of iteration.
A novel adaptive schema to facilitates playback switching technique for video delivery in dense LTE cellular heterogeneous network environments
Authors: Alomari Saleh Ali , Alzboon Mowafaq Salem , Al-Batah Mohammad Subhi , Zaqaibeh Belal
Published: June 2020

The services of the Video on Demand (VoD) are currently based on the developments of the technology of the digital video and the network’s high speed. The files of the video are retrieved from many viewers according to the permission, which is given by VoD services. The remote VoD servers conduct this access. A server permits the user to choose videos anywhere/anytime in order to enjoy a unified control of the video playback. In this paper, a novel adaptive method is produced in order to deliver various facilities of the VoD to all mobile nodes that are moving within several networks. This process is performed via mobility modules within the produced method since it applies a seamless playback technique for retrieving the facilities of the VoD through environments of heterogeneous networks. The main components comprise two servers, which are named as the GMF and the LMF. The performance of the simulation is tested for checking clients’ movements through different networks with different sizes and speeds, which are buffered in the storage. It is found to be proven from the results that the handoff latency has various types of rapidity. The method applies smooth connections and delivers various facilities of the VoD. Meantime, the mobile device transfers through different networks. This implies that the system transports video segments easily without encountering any notable effects.In the experimental analysis for the Slow movements mobile node handoff latency (8 Km/hour or 4 m/s) ,the mobile device’s speed reaches 4m/s, the delay time ranges from 1 to 1.2 seconds in the proposed system, while the MobiVoD system ranges from 1.1 to 1.5. In the proposed technique reaches 1.1026 seconds forming the required time of a mobile device that is switching from a single network to its adjacent one. while the handoff termination average in the MobiVoD reaches 1.3098 seconds. Medium movement mobile node handoff latency (21 Km/ hour or 8 m/s) The average handoff time for the proposed system reaches 1.1057 seconds where this implies that this technique can seamlessly provide several segments of a video segments regardless of any encountered problems. while the average handoff time for the MobiVoD reaches 1.53006623 seconds. Furthermore, Fast movement mobile node handoff latency (390 Km/ hour or 20 m/s). The average time latency of the proposed technique reaches 1.0964 seconds, while the MobiVoD System reaches to 1.668225 seconds.
Error rate detection due to primary user emulation attack in cognitive radio networks
Authors: Armi N. , Gharibi W. , Khan W.Z.
Published: June 2020

Security threat is a crucial issue in cognitive radio network (CRN). These threats come from physical layer, data link layer, network layer, transport layer, and application layer. Hence, security system to all layers in CRN has a responsibility to protect the communication between among Secondary User (SU) or to maintain valid detection to the presence of Primary User (PU) signals. Primary User Emulation Attack (PUEA) is a threat on physical layer where malicious user emulates PU signal. This paper studies the effect of exclusive region of PUEA in CRN. We take two setting of exclusive distances, 30m and 50m, where this radius of area is free of malicious users. Probability of false alarm (Pf) and miss detection (Pm) are used to evaluate the performances. The result shows that increasing distance of exclusive region may decrease Pf and Pm.
Comparison study of machine learning classifiers to detect anomalies
Authors: Shetty Nisha P , Shetty Jayashree , Narula Rohil , Tandona Kushagra
Published: June 2020

In this era of Internet ensuring the confidentiality, authentication and integrity of any resource exchanged over the net is the imperative. Presence of intrusion prevention techniques like strong password, firewalls etc. are not sufficient to monitor such voluminous network traffic as they can be breached easily. Existing signature based detection techniques like antivirus only offers protection against known attacks whose signatures are stored in the database.Thus, the need for real-time detection of aberrations is observed. Existing signature based detection techniques like antivirus only offers protection against known attacks whose signatures are stored in the database. Machine learning classifiers are implemented here to learn how the values of various fields like source bytes, destination bytes etc. in a network packet decides if the packet is compromised or not . Finally the accuracy of their detection is compared to choose the best suited classifier for this purpose. The outcome thus produced may be useful to offer real time detection while exchanging sensitive information such as credit card details.
Framework for reversible data hiding using cost-effective encoding system for video steganography
Authors: K. Manjunath Kamath , Kunte R. Sanjeev
Published: June 2020

Importances of reversible data hiding practices are always higher in contrast to any conventional data hiding schemes owing to its capability to generate distortion free cover media. Review of existing approaches on reversible data hiding approaches shows variable scheme mainly focussing on the embedding mechanism; however, such schemes could be furthermore improved using encoding scheme for optimal embedding performance. Therefore, the proposed manuscript discusses about a cost-effective scheme where a novel encoding scheme has been used with larger block sizes which reduces the dependencies over larger number of blocks. Further a gradient-based image registration technique is applied to ensure higher quality of the reconstructed signal over the decoding end. The study outcome shows that proposed data hiding technique is proven better than existing data hiding scheme with good balance between security and restored signal quality upon extraction of data.
Comparative study on machine learning algorithms for early fire forest detection system using geodata.
Authors: Mohammed Zouiten , Hanae Chaaouan , Larbi Setti
Published: June 2020

Forest fires have caused considerable losses to ecologies, societies and economies worldwide. To minimize these losses and reduce forest fires, modeling and predicting the occurrence of forest fires are meaningful because they can support forest fire prevention and management. In recent years, the convolutional neural network (CNN) has become an important state-of-the-art deep learning algorithm, and its implementation has enriched many fields. Therefore, a competitive spatial prediction model for automatic early detection of wild forest fire using machine learning algorithms can be proposed. This model can help researchers to predict forest fires and identify risk zonas. System using machine learning algorithm on geodata will be able to notify in real time the interested parts and authorities by providing alerts and presenting on maps based on geographical treatments for more efficacity and analyzing of the situation. This research extends the application of machine learning algorithms for early fire forest prediction to detection and representation in geographical information system (GIS) maps.
An intrusion detection system for packet and flow based networks using deep neural network approach
Authors: Farhana Kaniz , Rahman Maqsudur , Ahmed Md. Tofael
Published: June 2020

Study on deep neural networks and big data is merging now by several aspects to enhance the capabilities of intrusion detection system (IDS). Many IDS models has been introduced to provide security over big data. This study focuses on the intrusion detection in computer networks using big datasets. The advent of big data has agitated the comprehensive assistance in cyber security by forwarding a brunch of affluent algorithms to classify and analysis patterns and making a better prediction more efficiently. In this study, to detect intrusion a detection model has been propounded applying deep neural networks. We applied the suggested model on the latest data set available at online, formatted with packet based, flow based data and some additional metadata. The data set is labeled and imbalanced with 79 attributes and some classes having much less training samples compared to other classes. The proposed model is build using Keras and Google Tensorflow deep learning environment. Experimental result shows that intrusions are detected with the accuracy over 99% for both binary and multi-class classification with selected best features. Receiver operating characteristics (ROC) and precision-recall curve average score is also 1. The outcome implies that Deep Neural Networks offers a novel research model with great accuracy for intrusion detection model, better than some models presented in the literature.
Simulation and optimization of tuneable microstrip patch antenna for fifth-generation applications based on graphene
Authors: Marhoon Hamzah M. , Qasem Nidal
Published: June 2020

Microstrip patch antennas (MPAs) are known largely for their versatility in terms of feasible geometries, making them applicable in many distinct circumstances. In this paper, a graphene-based tuneable single/array rectangular microstrip patch antenna (MPA) utilizing an inset feed technique designed to function in multiple frequency bands are used in a fifth-generation (5G) wireless communications system. The tuneable antenna is used to eliminate the difficulties caused by the narrow bandwidths typically associated with MPAs. The graphene material has a reconfigurable surface conductivity that can be adjusted to function at the required value, thus allowing the required resonance frequency to be selected. The simulated tuneable antenna comprises a copper radiating patch with four graphene strips used for tuning purposes and is designed to cover a wide frequency band. The proposed antenna can be tuned directly by applying a direct current (DC) voltage to the graphene strips, resulting in a variation in the surface impedance of the graphene strips and leading to shifts in the resonance frequency.
Short-term optimal hydro-thermal scheduling using clustered adaptive teaching learning based optimization
Authors: Salkuti Surender Reddy
Published: June 2020

In this paper, Clustered Adaptive Teaching Learning Based Optimization (CATLBO) algorithm is proposed for determining the optimal hourly schedule of power generation in a hydro-thermal power system. In the proposed approach, a multi-reservoir cascaded hydro-electric system with a non-linear relationship between water discharge rate, net head and power generation is considered. Constraints such as power balance, water balance, reservoir volume limits and operation limits of hydro and thermal plants are considered. The feasibility and effectiveness of the proposed algorithm is demonstrated through a test system, and the results are compared with existing conventional and evolutionary algorithms. Simulation results reveals that the proposed CATLBO algorithm appears to be the best in terms of convergence speed and optimal cost compared with other techniques.
Performance of grid-connected solar photovoltaic power plants in the Middle East and North Africa
Authors: Assadeg Jalal , Sopian Kamaruzzaman , Fudholi Ahmad
Published: June 2020

A conceptual design Study of a solar electrical power system using PV array for a 5.3MW as nominal power required is presented. A Bird model has been used to estimate hourly, daily, monthly and yearly solar radiation amounts. f-f-chart is a design method was chosen to simulate the fraction of the solar energy required for the load given the PV array areas and climatic conditions. Four cities in the Middle East and North Africa representing different locations at southern Mediterranean region are selected Tripoli, Alexandria, Tunisia and Gaza city. Tripoli City has the best performance for 73% of nominal Power followed by Alexandria about 66% and then Gaza around 63%, Tunisia City has lowest solar fraction about 59% according to the Monthly and annual solar fraction Data.
Economic and emission dispatch using cuckoo search algorithm
Authors: Habachi Rachid , Boulal Abdellah , Touil Achraf , Charkaoui Abdelkabir , Echchatbi Abdelwahed
Published: June 2020

The economic dispatch problem of power plays a very important role in the exploitation of electro-energy systems to judiciously distribute power generated by all plants. This paper proposes the use of Cuckoo Search Algorithm (CSA) for solving the economic and Emission dispatch. The effectiveness of the proposed approach has been tested on 3 generator system. CSA is a new meta-heuristic optimization method inspired from the obligate brood parasitism of some cuckoo species by laying their eggs in the nests of other host birds of other species.The results shows that performance of the proposed approach reveal the efficiently and robustness when compared results of other optimization algorithms reported in literature