Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Articles 1 - 30 of 397

Full-Text Articles in Physical Sciences and Mathematics

A Data Hiding Scheme Based On Chaotic Map And Pixel Pairs, Sengul Dogan Sd Dec 2017

A Data Hiding Scheme Based On Chaotic Map And Pixel Pairs, Sengul Dogan Sd

Journal of Digital Forensics, Security and Law

Information security is one of the most common areas of study today. In the literature, there are many algorithms developed in the information security. The Least Significant Bit (LSB) method is the most known of these algorithms. LSB method is easy to apply however it is not effective on providing data privacy and robustness. In spite of all its disadvantages, LSB is the most frequently used algorithm in literature due to providing high visual quality. In this study, an effective data hiding scheme alternative to LSB, 2LSBs, 3LSBs and 4LSBs algorithms (known as xLSBs), is proposed. In this method, random …


Process Models Discovery And Traces Classification: A Fuzzy-Bpmn Mining Approach., Kingsley Okoye Dr, Usman Naeem Dr, Syed Islam Dr, Abdel-Rahman H. Tawil Dr, Elyes Lamine Dr Dec 2017

Process Models Discovery And Traces Classification: A Fuzzy-Bpmn Mining Approach., Kingsley Okoye Dr, Usman Naeem Dr, Syed Islam Dr, Abdel-Rahman H. Tawil Dr, Elyes Lamine Dr

Journal of International Technology and Information Management

The discovery of useful or worthwhile process models must be performed with due regards to the transformation that needs to be achieved. The blend of the data representations (i.e data mining) and process modelling methods, often allied to the field of Process Mining (PM), has proven to be effective in the process analysis of the event logs readily available in many organisations information systems. Moreover, the Process Discovery has been lately seen as the most important and most visible intellectual challenge related to the process mining. The method involves automatic construction of process models from event logs about any domain …


A Forensic Email Analysis Tool Using Dynamic Visualization, Johannes Stadlinger, Andreas Dewald Mar 2017

A Forensic Email Analysis Tool Using Dynamic Visualization, Johannes Stadlinger, Andreas Dewald

Journal of Digital Forensics, Security and Law

Communication between people counts to the most important information of today’s business. As a result, in case of forensic investigations in big companies, analysis of communication data in general and especially email, as the still most widely used business communication platform with an immense and still growing volume, is a typical task in digital forensics. One of the challenges is to identify the relevant communication partners and structures in the suspects surrounding as quickly as possible in order to react appropriately and identify further targets of evaluation. Due to the amount of emails in typical inboxes, reading through all the …


Find Me If You Can: Mobile Gps Mapping Applications Forensic Analysis & Snavp The Open Source, Modular, Extensible Parser, Jason Moore, Ibrahim Baggili, Frank Breitinger Mar 2017

Find Me If You Can: Mobile Gps Mapping Applications Forensic Analysis & Snavp The Open Source, Modular, Extensible Parser, Jason Moore, Ibrahim Baggili, Frank Breitinger

Journal of Digital Forensics, Security and Law

The use of smartphones as navigation devices has become more prevalent. The ubiquity of hand-held navigation devices such as Garmins or Toms Toms has been falling whereas the ownership of smartphones and their adoption as GPS devices is growing. This work provides a comprehensive study of the most popular smartphone mapping applications, namely Google Maps, Apple Maps, Waze, MapQuest, Bing, and Scout, on both Android and iOS. It details what data was found, where it was found, and how it was acquired for each application. Based on the findings, the work allowed for the construction of a tool capable of …


Compression Of Virtual-Machine Memory In Dynamic Malware Analysis, James E. Fowler Ph.D. Mar 2017

Compression Of Virtual-Machine Memory In Dynamic Malware Analysis, James E. Fowler Ph.D.

Journal of Digital Forensics, Security and Law

Lossless compression of memory dumps from virtual machines that run malware samples is considered with the goal of significantly reducing archival costs in dynamic-malware-analysis applications. Given that, in such dynamic-analysis scenarios, malware samples are typically run in virtual machines just long enough to activate any self-decryption or other detection- avoidance maneuvers, the virtual-machine memory typically changes little from that of the baseline state, with the difference being attributable in large degree to the loading of additional executables and libraries. Consequently, delta coding is proposed to compress the current virtual-machine memory dump by coding its differences with respect to a predicted …


Table Of Contents Mar 2017

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.


Front Matter Mar 2017

Front Matter

Journal of Digital Forensics, Security and Law

No abstract provided.


Special Issue Of Best Papers From The 11th International Conference On Systematic Approaches To Digital Forensic Engineering (Sadfe 2016) Mar 2017

Special Issue Of Best Papers From The 11th International Conference On Systematic Approaches To Digital Forensic Engineering (Sadfe 2016)

Journal of Digital Forensics, Security and Law

The SADFE series feature the different editions of the International Conference on Systematic Approaches to Digital Forensics Engineering. Now in its eleventh edition, SADFE has established itself as the premier conference for researchers and practitioners working in Systematic Approaches to Digital Forensics Engineering.

SADFE 2016, the eleventh international conference on Systematic Approaches to Digital Forensic Engineering was held in Kyoto, Japan, September 20 - 22, 2016.

Digital forensics engineering and the curation of digital collections in cultural institutions face pressing and overlapping challenges related to provenance, chain of custody, authenticity, integrity, and identity. The generation, analysis and sustainability of digital …


Android Malware Classification Based On Anfis With Fuzzy C-Means Clustering Using Significant Application Permissions, Altyeb Altaher, Omar Barukab Jan 2017

Android Malware Classification Based On Anfis With Fuzzy C-Means Clustering Using Significant Application Permissions, Altyeb Altaher, Omar Barukab

Turkish Journal of Electrical Engineering and Computer Sciences

Mobile phones have become an essential part of our lives because we depend on them to perform many tasks, and they contain personal and important information. The continuous growth in the number of Android mobile applications resulted in an increase in the number of malware applications, which are real threats and can cause great losses. There is an urgent need for efficient and effective Android malware detection techniques. In this paper, we present an adaptive neuro-fuzzy inference system with fuzzy c-means clustering (FCM-ANFIS) for Android malware classification. The proposed approach utilizes the FCM clustering method to determine the optimum number …


Naive Forecasting Of Household Natural Gas Consumption With Sliding Window Approach, Mustafa Akpinar, Nejat Yumuşak Jan 2017

Naive Forecasting Of Household Natural Gas Consumption With Sliding Window Approach, Mustafa Akpinar, Nejat Yumuşak

Turkish Journal of Electrical Engineering and Computer Sciences

Household consumption has a significant importance for natural gas wholesale companies. These companies make one-day-ahead forecasting daily. However, there are penalties depending on the error of the estimates. These penalties increase exponentially depending on the error rate. Several studies have been done to develop mathematical models to forecast natural gas consumption and minimize the error rate. However, before mathematical model predictions, a previous step, data preparation, is also important. The data must be prepared correctly before the mathematical model. At this point, prior to the mathematical model, selecting the appropriate data set size has a vital role. In this study, …


A Comparative Analysis Of Classification Methods For Hyperspectral Images Generated With Conventional Dimension Reduction Methods, Ozan Arslan, Özer Akyürek, Şi̇nasi̇ Kaya Jan 2017

A Comparative Analysis Of Classification Methods For Hyperspectral Images Generated With Conventional Dimension Reduction Methods, Ozan Arslan, Özer Akyürek, Şi̇nasi̇ Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

This paper compared performances of classification methods for a hyperspectral image dataset in view of dimensionality reduction (DR). Among conventional DR methods, principal component analysis, maximum noise fraction, and independent component analysis were used for the purpose of dimension reduction. The study was conducted using these DR techniques on a real hyperspectral image, an AVIRIS dataset with 224 bands, throughout the experiments. It was observed that DR may have a significant effect on the classification performance. After the DR methods were applied to the image dataset, the extracted reduced bands were used for testing classification performances. Four commonly used classification …


A Game-Theoretic Framework For Active Distribution Network Planning To Benefit Different Participants Under The Electricity Market, Bo Zeng, Jinyue Shi, Junqiang Wen, Jianhua Zhang Jan 2017

A Game-Theoretic Framework For Active Distribution Network Planning To Benefit Different Participants Under The Electricity Market, Bo Zeng, Jinyue Shi, Junqiang Wen, Jianhua Zhang

Turkish Journal of Electrical Engineering and Computer Sciences

With the deregulation of the power sector, distribution system planning is transforming from the traditional integrated decision mode to the multiple-player-based decentralized paradigm. However, this could potentially cause an adverse impact on the performance of the system due to interest conflict of market players during operations. To address such an issue, this paper develops a game-theoretic framework for active distribution network planning under the electricity market. The interplay between the distribution utility (DISCO) and distributed generation investors (DGO) is formulated as a noncooperative, two-person-based Stackelberg game in which the DISCO, as the leader of the game, makes expansion of the …


Unknown Input Observer Based On Lmi For Robust Generation Residuals, Souad Tahraoui, Abdelmadjid Meghabbar, Djamila Boubekeur Jan 2017

Unknown Input Observer Based On Lmi For Robust Generation Residuals, Souad Tahraoui, Abdelmadjid Meghabbar, Djamila Boubekeur

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a method of generating robust residuals of a linear system, subject to unknown inputs, is proposed. The impact of disturbances and uncertainty may create difficulties at the decision stage of diagnosis (false alarm); this has resulted in the use of a robust observer for the unknown inputs to ensure the robustness of the system based on the unknown input observer with an optimal decoupling approach, which has a sensitivity that is minimal to unknown inputs and maximal to faults. A generation of robust residuals is then transformed into a problem of robustness/sensitivity constraints (H$_{\infty }$, H and …


Dtreesim: A New Approach To Compute Decision Tree Similarity Using Re-Mining, Gözde Bakirli, Derya Bi̇rant Jan 2017

Dtreesim: A New Approach To Compute Decision Tree Similarity Using Re-Mining, Gözde Bakirli, Derya Bi̇rant

Turkish Journal of Electrical Engineering and Computer Sciences

A number of recent studies have used a decision tree approach as a data mining technique; some of them needed to evaluate the similarity of decision trees to compare the knowledge reflected in different trees or datasets. There have been multiple perspectives and multiple calculation techniques to measure the similarity of two decision trees, such as using a simple formula or an entropy measure. The main objective of this study is to compute the similarity of decision trees using data mining techniques. This study proposes DTreeSim, a new approach that applies multiple data mining techniques (classification, sequential pattern mining, and …


Robust Adaptive Fuzzy Control Of A Three-Phase Active Power Filter Based On Feedback Linearization, Shixi Hou, Juntao Fei Jan 2017

Robust Adaptive Fuzzy Control Of A Three-Phase Active Power Filter Based On Feedback Linearization, Shixi Hou, Juntao Fei

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a robust adaptive fuzzy control system using feedback linearization is proposed for a three-phase active power filter (APF). The APF system is divided into two separate loops: the current dynamic inner loop and the DC voltage dynamic outer loop. Adaptive fuzzy tracking control using feedback linearization is employed for the current dynamic inner loop to overcome the drawbacks of the conventional method. The proposed controller can ensure proper tracking of the reference current and impose desired dynamic behavior, giving robustness and insensitivity to parameter variations. Adaptive fuzzy proportional-integral control is applied to the DC voltage dynamics outer …


An Online Approach For Feature Selection For Classification In Big Data, Nasrin Banu Nazar, Radha Senthilkumar Jan 2017

An Online Approach For Feature Selection For Classification In Big Data, Nasrin Banu Nazar, Radha Senthilkumar

Turkish Journal of Electrical Engineering and Computer Sciences

Feature selection (FS), also known as attribute selection, is a process of selection of a subset of relevant features used in model construction. This process or method improves the classification accuracy by removing irrelevant and noisy features. FS is implemented using either batch learning or online learning. Currently, the FS methods are executed in batch learning. Nevertheless, these techniques take longer execution time and require larger storage space to process the entire dataset. Due to the lack of scalability, the batch learning process cannot be used for large data. In the present study, a scalable efficient Online Feature Selection (OFS) …


The Impact Of Sampling Frequency And Amplitude Modulation Index On Low Order Harmonics In A 3-Phase Sv-Pvm Voltage Source Inverter, Qamil Kabashi, Myzafere Limani, Nebi Caka, Milaim Zabeli Jan 2017

The Impact Of Sampling Frequency And Amplitude Modulation Index On Low Order Harmonics In A 3-Phase Sv-Pvm Voltage Source Inverter, Qamil Kabashi, Myzafere Limani, Nebi Caka, Milaim Zabeli

Turkish Journal of Electrical Engineering and Computer Sciences

Nowadays, variable speed AC motors are widely used in industry and there are many speed adjustment techniques available. In the last decade there has been a trend towards the use of space vector PWM--IGBT inverters, due to easier digital realization and better utilization of the DC bus. Every power inverter produces a total harmonic distortion (THD) on its output that causes extra losses in stator of induction motors. By eliminating a number of low order voltage/current harmonics it is possible to reduce harmonic losses (stator losses) and mechanical oscillations in general. This could be achieved by implementing filters in the …


Gica: Imperialist Competitive Algorithm With Globalization Mechanism For Optimization Problems, Yousef Abdi, Mahmoud Lak, Yousef Seyfari Jan 2017

Gica: Imperialist Competitive Algorithm With Globalization Mechanism For Optimization Problems, Yousef Abdi, Mahmoud Lak, Yousef Seyfari

Turkish Journal of Electrical Engineering and Computer Sciences

The imperialist competitive algorithm (ICA) is a recent global search strategy developed based on human social evolutionary phenomena in the real world. However, the ICA has the drawback of trapping in local optimum solutions when used for high-dimensional or complex multimodal functions. In order to deal with this situation, in this paper an improved ICA, named GICA, is proposed that can enhance ICA performance by using a new assimilation method and establishing a relationship between countries inspired by the globalization concept in the real world. The proposed algorithm is evaluated using a set of well-known benchmark functions for global optimization. …


Dynamic Model Of Wind Power Balancing In Hybrid Power System, Audrius Jonaitis, Renata Miliune, Tomas Deveikis Jan 2017

Dynamic Model Of Wind Power Balancing In Hybrid Power System, Audrius Jonaitis, Renata Miliune, Tomas Deveikis

Turkish Journal of Electrical Engineering and Computer Sciences

The paper presents a dynamic model of a hybrid power system composed of a wind park, a diesel generator, and an electrochemical energy storage system. The purpose of conventional generating units and energy storage equipment in the hybrid power system is the balancing of fluctuating power generated by renewable energy sources as well as an increase in supplied power quality. The composed dynamic model describes characteristics of the power governor of the diesel generator and dynamic behavior of the energy storage system based on a vanadium redox battery. Simulations are based on sampled data of real wind park power installed …


Implementation Of A Personal Area Network For Secure Routing In Manets By Using Low-Cost Hardware, Himadri Nath Saha, Rohit Singh, Debika Bhattacharyya, Pranab Kumar Banerjee Jan 2017

Implementation Of A Personal Area Network For Secure Routing In Manets By Using Low-Cost Hardware, Himadri Nath Saha, Rohit Singh, Debika Bhattacharyya, Pranab Kumar Banerjee

Turkish Journal of Electrical Engineering and Computer Sciences

Presently, mobile ad hoc networks (MANETs) are being used extensively in the defense, private, domestic, etc. fields and each of these emulates a personal area network (PAN). A MANET does not require any infrastructure; moreover, it can behave as a mobile network. These features have boosted the popularity of MANETs in the community. As more and more fields become dependent on MANETs, the system needs to be more energy aware and low cost. To commercialize MANETs, the routing protocols need to be lightweight, secure, and energy efficient, and the hardware on which it is to be implemented should be low …


Novel Scheduling Algorithm For Optimizing Real-Time Multimedia Performance In Long Term Evolution-Advanced, Huda Adibah Mohd Ramli, Zairi Ismael Rizman Jan 2017

Novel Scheduling Algorithm For Optimizing Real-Time Multimedia Performance In Long Term Evolution-Advanced, Huda Adibah Mohd Ramli, Zairi Ismael Rizman

Turkish Journal of Electrical Engineering and Computer Sciences

Real-time multimedia applications are becoming increasingly popular among mobile cellular users. Given that Long Term Evolution-Advanced (LTE-A), which is an emerging mobile cellular standard, needs to support these multimedia applications, packet scheduling is of paramount importance in LTE-A. This paper proposes a packet scheduling algorithm known as novel scheduling for usage in the downlink of LTE-A. It takes channel quality, average throughput, and packet delay into account when determining the priority of each user. Simulation results demonstrate the efficacy of the proposed algorithm in optimizing real-time multimedia performance for more mobile cellular users.


Application Of Singular Value Decomposition Algorithm For Implementing Power Amplifier Linearizer, Rajbir Kaur, Manjeet Singh Patterh Jan 2017

Application Of Singular Value Decomposition Algorithm For Implementing Power Amplifier Linearizer, Rajbir Kaur, Manjeet Singh Patterh

Turkish Journal of Electrical Engineering and Computer Sciences

A power amplifier (PA) is an integral component of all base stations in wireless communication systems and is used for converting DC power supply into radio frequency output power, but PAs are highly nonlinear. To achieve high power conversion efficiency, the PA is operated near saturation, which causes intermodulation products and hence results in nonlinear distortion. Digital predistortion (DPD) is a technique used to compensate for the nonlinear distortion without compromising its efficiency. Fourth Generation Long Term Evolution (4G LTE) systems use a carrier aggregation scheme to combine separate available bandwidths to deliver high data speeds. In this paper the …


Sotarm: Size Of Transaction-Based Association Rule Mining Algorithm, Asha Pandian, Jebarajan Thaveethu Jan 2017

Sotarm: Size Of Transaction-Based Association Rule Mining Algorithm, Asha Pandian, Jebarajan Thaveethu

Turkish Journal of Electrical Engineering and Computer Sciences

Mining of association rules tries to identify the existence of promising and fruitful relations among the items present in a database. The basic a priori algorithm suffers from multiple database scans, and if the database is large, then the time taken for scanning and generation of candidates is also large. The proposed algorithm attempts to reduce the repeated scanning of the whole database. Using this algorithm, scanning time and also the generation of subitems that are not frequent can be reduced. The former can be done by sorting the transaction records in descending order based on the size of transaction …


A Symmetrically Feeding Structure For Dual-Polarized Feeds, Jinyuan Liu, Hui Deng, Bin Ding, Xiaolong Niu Jan 2017

A Symmetrically Feeding Structure For Dual-Polarized Feeds, Jinyuan Liu, Hui Deng, Bin Ding, Xiaolong Niu

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a symmetrically feeding structure for linear dual-polarized feeds for a compensated compact test range (CCR) and a corresponding wideband balun are put forward. $TM_{01}$ and $TE_{21} $ modes within the circular feeding waveguide are compressed due to its electrical balance. The polarization purity of feeds is then improved. Thus, the level of cross-polarization can be very low, which is the key requirement for CCR. A new wideband balun that acts as a power-divider and phase shifter with low amplitude unbalance and phase unbalance is designed for the new feeding structure. The return loss equation derived from an …


Channel Estimation Using An Adaptive Neuro Fuzzy Inference System In The Ofdm-Idma System, Necmi̇ Taşpinar, Şaki̇r Şi̇mşi̇r Jan 2017

Channel Estimation Using An Adaptive Neuro Fuzzy Inference System In The Ofdm-Idma System, Necmi̇ Taşpinar, Şaki̇r Şi̇mşi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a channel estimator based on an adaptive neuro fuzzy inference system (ANFIS) is proposed for the purpose of estimating channel frequency responses in orthogonal frequency division multiplexing-interleave division multiple access (OFDM-IDMA) systems. To see the performance of our proposed channel estimation method, five different techniques including well-known pilot-based estimation algorithms such as least squares (LS) and minimum mean square error (MMSE) with other heuristic methods like multilayered perceptron (MLP) trained by a backpropagation (BP) algorithm (MLP-BP), MLP trained by the Levenberg--Marquardt (LM) algorithm (MLP-LM), and radial basis function neural network (RBFNN) are compared with our proposed method …


Pixel- Versus Object-Based Classification Of Forest And Agricultural Areas From Multiresolution Satellite Images, Di̇jle Boyaci, Mustafa Erdoğan, Ferruh Yildiz Jan 2017

Pixel- Versus Object-Based Classification Of Forest And Agricultural Areas From Multiresolution Satellite Images, Di̇jle Boyaci, Mustafa Erdoğan, Ferruh Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

Managing of natural resources including agriculture and forestry is a very important subject for governments and decision makers. Up-to-date, accurate, and timely geospatial information about natural resources is needed in the management process. Remote sensing technology plays a significant role in the production of this geospatial information. Compared to terrestrial work, the analysis of larger areas with remote sensing techniques can be done on a shorter timescale and at lower cost. Image classification in remote sensing is one of the most popular methods used for the detection of forest and agricultural areas. However, the accuracy of classification changes according to …


Implementation Of Svc Based On Grey Theory And Fuzzy Logic To Improve Lvrt Capability Of Wind Distributed Generations, Mohammad Mehdi Karami, Akbar Itami Jan 2017

Implementation Of Svc Based On Grey Theory And Fuzzy Logic To Improve Lvrt Capability Of Wind Distributed Generations, Mohammad Mehdi Karami, Akbar Itami

Turkish Journal of Electrical Engineering and Computer Sciences

Due to the great absorption of reactive power after voltage drops caused by faults in network, the low-voltage ride through (LVRT) capability of squirrel cage induction generators (SCIGs) in wind farms is a great challenge. If a static VAR compensator (SVC) is installed at the point of common coupling (PCC) of a wind farm with a main network, it can improve the wind generation's LVRT capability with reactive power compensation. In the voltage control loop of a conventional SVC, the voltage actual value of the PCC is compared with the reference voltage value. This paper presents a method for implementation …


Probabilistic Data Fusion Model For Heart Beat Detection From Multimodal Physiological Data, Tehseen Zia, Zulqarnian Arif Jan 2017

Probabilistic Data Fusion Model For Heart Beat Detection From Multimodal Physiological Data, Tehseen Zia, Zulqarnian Arif

Turkish Journal of Electrical Engineering and Computer Sciences

Automatic detection of heart beats constitutes the basis for electrocardiogram (ECG) analysis and mainly relies on detecting QRS complexes. Detection is typically performed by analyzing the ECG signal. However, when signal quality is low, it often leads to the triggering of false alarms. A contemporary approach to reduce false alarm rate is to use multimodal data such as arterial blood pressure (ABP) or photoplethysmogram (PPG) signals. To leverage the correlated temporal nature of these signals, a probabilistic data fusion model for heart beat detection is proposed. A hidden Markov model is used to decode waveforms into segments. A Bayesian network …


A New Efficient Block Matching Data Hiding Method Based On Scanning Order Selection In Medical Images, Turgay Aydoğan, Cüneyt Bayilmiş Jan 2017

A New Efficient Block Matching Data Hiding Method Based On Scanning Order Selection In Medical Images, Turgay Aydoğan, Cüneyt Bayilmiş

Turkish Journal of Electrical Engineering and Computer Sciences

Digital technology and the widespread use of the Internet has increased the speeds at which digital data can be obtained and shared in daily life. In parallel to this, there are important concerns regarding the confidentiality of private data during data transmissions and the possibility that data might fall into the hands of third parties. Issues relating to data safety can also affect patients' medical images and other information relating to these images. In this study, we propose a new method based on block matching that can be used to hide the patient information in medical images. In this method, …


A Data-Aware Cognitive Engine For Scheduling Data Intensive Applications In A Grid, Vijaya Nagarajan, Maluk Mohamed Mulk Abdul Jan 2017

A Data-Aware Cognitive Engine For Scheduling Data Intensive Applications In A Grid, Vijaya Nagarajan, Maluk Mohamed Mulk Abdul

Turkish Journal of Electrical Engineering and Computer Sciences

Data-intensive applications produce huge amounts of data that need to be stored, analyzed, and interpreted. A data grid serves as a cost-effective infrastructure for solving these data-intensive applications. Existing scheduling strategies are best suited for handling compute-intensive applications, although they lack in performance while handling data-intensive applications. In this work, a novel mechanism of incorporating cognitive science in a data grid is proposed for scheduling data-intensive workflows. A unique model is derived in which a cognitive engine (CE) is built into the middleware of the data grid. The intelligent agents present in the CE handle the request for data sets …