bluuebunny/crossref_metadata_2025 huggingface dataset:
Projection pursuit random forest using discriminant feature analysis model for churners prediction in telecom industry
Authors: Naser alzubaidi Asia Mahdi , Al-Shamery Eman Salih
Published: March 2020

A major and demanding issue in the telecommunications industry is the prediction of churn customers. Churn describes the customer who is attrite from one Telecom service provider to competitors searching for better services offers. Companies from the Telco sector frequently have customer relationship management offices it is the main objective in how to win back defecting clients because preserve long-term customers can be much more beneficial to a company than gain newly recruited customers. Researchers and practitioners are paying great attention and investing more in developing a robust customer churn prediction model, especially in the telecommunication business by proposed numerous machine learning approaches. Many approaches of Classification are established, but the most effective in recent times is a tree-based method. The main contribution of this research is to predict churners/non-churners in the Telecom sector based on project pursuit Random Forest (PPForest) that uses discriminant feature analysis as a novelty extension of the conventional Random Forest approach for learning oblique Project Pursuit tree (PPtree). The proposed methodology leverages the advantage of two discriminant analysis methods to calculate the project index used in the construction of PPtree. The first method used Support Vector Machines (SVM) as a classifier in the construction of PPForest to differentiate between churners and non-churners customers. The second method is a Linear Discriminant Analysis (LDA) to achieve linear splitting of variables node during oblique PPtree construction to produce individual classifiers that are robust and more diverse than classical Random Forest. It found that the proposed methods enjoy the best performance measurements e.g. Accuracy, hit rate, ROC curve, Gini coefficient, Kolmogorov-Smirnov statistic and lift coefficient, H-measure, AUC. Moreover, PPForest based on direct applied of LDA on the raw data delivers an effective evaluator for the customer churn prediction model.
Miniaturized UWB elliptical patch antenna for skin cancer diagnosis imaging
Authors: Alani Sameer , Zakaria Zahriladha , Ahmad A.
Published: March 2020

The biomedical imaging shows promising results in many applications such as protein characterization and cancer detection using non-ionizing radiation. Skin cancer is one of the most common types of cancer because it is exposed by sun rays during the day. Many techniques have been offered to detect the tumor in the early stage such as ultrasonic and MW imaging. However, most of these studies showed a large printing area with lower BW so as the low resolution. To overcome these drawbacks, a new low profile UWB elliptical patch antenna with high performance is designed on PTFE as a substrate. Then a layer of Indium Tin Oxide (ITO) applies to improve the antenna radiation characteristics. The proposed antenna has a broad BW from 3.9 GHz to 30 GHz along with a resonance at 2.4 GHz. Furthermore, the antenna presents a maximum gain of 7.3 dB, maximum directivity of 7.78 dBi, the maximum radiation efficiency of 92 %, and consistent, stable radiation pattern throughout the frequency band. Besides, the time-domain characteristics show that the antenna can be a suitable candidate for microwave imaging of skin cancer.
A new RSA public key encryption scheme with chaotic maps
Authors: Tahat Nedal , Tahat Ashraf A. , Abu-Dalu Maysam , Albadarneh Ramzi B. , Abdallah Alaa E. , Al-Hazaimeh Obaida M.
Published: March 2020

Public key cryptography has received great attention in the field of information exchange through insecure channels. In this paper, we combine the Dependent-RSA (DRSA) and chaotic maps (CM) to get a new secure cryptosystem, which depends on both integer factorization and chaotic maps discrete logarithm (CMDL). Using this new system, the scammer has to go through two levels of reverse engineering, concurrently, so as to perform the recovery of original text from the cipher-text has been received. Thus, this new system is supposed to be more sophisticated and more secure than other systems. We prove that our new cryptosystem does not increase the overhead in performing the encryption process or the decryption process considering that it requires minimum operations in both. We show that this new cryptosystem is more efficient in terms of performance compared with other encryption systems, which makes it more suitable for nodes with limited computational ability.
Study and analysis of mobility, security, and caching issues in CCN
Authors: Rais Rao Naveed Bin , Khalid Osman
Published: March 2020

Existing architecture of Internet is IP-centric, having capability to cope with the needs of the Internet users. Due to the recent advancements and emerging technologies, a need to have ubiquitous connectivity has become the primary focus. Increasing demands for location-independent content raised the requirement of a new architecture and hence it became a research challenge. Content Centric Networking (CCN) paradigm emerges as an alternative to IP-centric model and is based on name-based forwarding and in-network data caching. It is likely to address certain challenges that have not been solved by IP-based protocols in wireless networks. Three important factors that require significant research related to CCN are mobility, security, and caching. While a number of studies have been conducted on CCN and its proposed technologies, none of the studies target all three significant research directions in a single article, to the best of our knowledge. This paper is an attempt to discuss the three factors together within context of each other. In this paper, we discuss and analyze basics of CCN principles with distributed properties of caching, mobility, and secure access control. Different comparisons are made to examine the strengths and weaknesses of each aforementioned aspect in detail. The final discussion aims to identify the open research challenges and some future trends for CCN deployment on a large scale.
Design and implementation of log domain decoder
Authors: Mosleh Mahmood Farhan , Hasan Fadhil Sahib , Azeez Ruaa Majeed
Published: March 2020

Low-Density-Parity-Check (LDPC) code has become famous in communications systems for error correction, as an advantage of the robust performance in correcting errors and the ability to meet all the requirements of the 5G system. However, the mot challenge faced researchers is the hardware implementation, because of higher complexity and long run-time. In this paper, an efficient and optimum design for log domain decoder has been implemented using Xilinx system generator with FPGA device Kintex 7 (XC7K325T-2FFG900C). Results confirm that the proposed decoder gives a Bit Error Rate (BER) very closed to theory calculations which illustrate that this decoder is suitable for next generation demand which needs high data rate with very low BER.
The new integer factorization algorithm based on Fermat’s Factorization Algorithm and Euler’s theorem
Authors: Somsuk Kritsanapong
Published: March 2020

Although, Integer Factorization is one of the hard problems to break RSA, many factoring techniques are still developed. Fermat’s Factorization Algorithm (FFA) which has very high performance when prime factors are close to each other is a type of integer factorization algorithms. In fact, there are two ways to implement FFA. The first is called FFA-1, it is a process to find the integer from square root computing. Because this operation takes high computation cost, it consumes high computation time to find the result. The other method is called FFA-2 which is the different technique to find prime factors. Although the computation loops are quite large, there is no square root computing that included into the computation. In this paper, the new efficient factorization algorithm is introduced. Euler’s theorem is chosen to apply with FFA to find the addition result between two prime factors. The advantage of the proposed method is that almost of square root operations are left out from the computation while loops are not increased, they are equal to the first method. Therefore, if the proposed method is compared with the FFA-1, it implies that the computation time is decreased, because there is no the square root operation and the loops are same. On the other hand, the loops of the proposed method are less than the second method. Therefore, time is also reduced. Furthermore, the proposed method can be also selected to apply with many methods which are modified from FFA to decrease more cost.
The optimal synthesis of scanned linear antenna arrays
Authors: Amaireh Anas A. , Al-Zoubi Asem S. , Dib Nihad I.
Published: March 2020

In this paper, symmetric scanned linear antenna arrays are synthesized, in order to minimize the side lobe level of the radiation pattern. The feeding current amplitudes are considered as the optimization parameters. Newly proposed optimization algorithms are presented to achieve our target; Antlion Optimization (ALO) and a new hybrid algorithm. Three different examples are illustrated in this paper; 20, 26 and 30 elements scanned linear antenna array. The obtained results prove the effectiveness and the ability of the proposed algorithms to outperform and compete other algorithms like Symbiotic Organisms Search (SOS) and Firefly Algorithm (FA).
Duplexing mode, ARB and modulation approaches parameters affection on LTE uplink waveform
Authors: Al-Azzawi Fatima Faydhe , Abid Faeza Abas , Al-azzawi Zainab faydhe
Published: March 2020

The next generation of radio technologies designed to increase the capacity and speed of mobile networks. LTE is the first technology designed explicitly for the Next Generation Network NGN and is set to become the de-facto NGN mobile access network standard. It takes advantage of the NGN's capabilities to provide an always-on mobile data experience comparable to wired networks. In this paper LTE uplink waveforms displayed with various duplexing mode, Allocated Resources Blocks ARB, Modulation types and total information per frame, QPSK and 16 QAM used as modulation techniques and tested under AWGN and Rayleigh channels, similarity and interference of the generated waveforms tested using auto-correlation and cross-correlation respectively.
Abnormal gait detection by means of LSTM
Authors: Pachon-Suescun Cesar G. , Pinzon-Arenas Javier O. , Jimenez-Moreno Robinson
Published: March 2020

This article presents a system focused on the detection of three types of abnormal walk patterns caused by neurological diseases, specifically Parkinsonian gait, Hemiplegic gait, and Spastic Diplegic gait. A Kinect sensor is used to extract the Skeleton from a person during its walk, to then calculate four types of bases that generate different sequences from the 25 points of articulations that the Skeleton gives. For each type of calculated base, a recurrent neural network (RNN) is trained, specifically a Long short-term memory (LSTM). In addition, there is a graphical user interface that allows the acquisition, training, and testing of trained networks. Of the four trained networks, 98.1% accuracy is obtained with the database that was calculated with the distance of each point provided by the Skeleton to the Hip-Center point.
Performance analysis of container-based networking solutions for high-performance computing cloud
Authors: Lim Sang Boem , Woo Joon , Li Guohua
Published: March 2020

Recently, cloud service providers have been gradually changing from virtual machine-based cloud infrastructures to container-based cloud-native infrastructures that consider performance and workload-management issues. Several data network performance issues for virtual instances have arisen, and various networking solutions have been newly developed or utilized. In this paper, we propose a solution suitable for a high-performance computing (HPC) cloud through a performance comparison analysis of container-based networking solutions. We constructed a supercomputer-based test-bed cluster to evaluate the serviceability by executing HPC jobs.
Evaluate the performance of K-Means and the fuzzy C-Means algorithms to formation balanced clusters in wireless sensor networks
Authors: Hassan Ali Abdul-hussian , Md Shah Wahidah , Iskandar Othman Mohd Fairuz , Hussien Hassan Hayder Abdul
Published: March 2020

The clustering approach is considered as a vital method for wireless sensor networks (WSNs) by organizing the sensor nodes into specific clusters. Consequently, saving the energy and prolonging network lifetime which is totally dependent on the sensors battery, that is considered as a major challenge in the WSNs. Classification algorithms such as K-means (KM) and Fuzzy C-means (FCM), which are two of the most used algorithms in literature for this purpose in WSNs. However, according to the nature of random nodes deployment manner, on certain occasions, this situation forces these algorithms to produce unbalanced clusters, which adversely affects the lifetime of the network. Based for our knowledge, there is no study has analyzed the performance of these algorithms in terms clusters construction in WSNs. In this study, we investigate in KM and FCM performance and which of them has better ability to construct balanced clusters, in order to enable the researchers to choose the appropriate algorithm for the purpose of improving network lifespan. In this study, we utilize new parameters to evaluate the performance of clusters formation in multi-scenarios. Simulation result shows that our FCM is more superior than KM by producing balanced clusters with the random distribution manner for sensor nodes.
Power consumption prediction in cloud data center using machine learning
Authors: T. Deepika , P. Prakash
Published: March 2020

The flourishing development of the cloud computing paradigm provides several services in the industrial business world. Power consumption by cloud data centers is one of the crucial issues for service providers in the domain of cloud computing. Pursuant to the rapid technology enhancements in cloud environments and data centers augmentations, power utilization in data centers is expected to grow unabated. A diverse set of numerous connected devices, engaged with the ubiquitous cloud, results in unprecedented power utilization by the data centers, accompanied by increased carbon footprints. Nearly a million physical machines (PM) are running all over the data centers, along with (5 – 6) million virtual machines (VM). In the next five years, the power needs of this domain are expected to spiral up to 5% of global power production. The virtual machine power consumption reduction impacts the diminishing of the PM’s power, however further changing in power consumption of data center year by year, to aid the cloud vendors using prediction methods. The sudden fluctuation in power utilization will cause power outage in the cloud data centers. This paper aims to forecast the VM power consumption with the help of regressive predictive analysis, one of the Machine Learning (ML) techniques. The potency of this approach to make better predictions of future value, using Multi-layer Perceptron (MLP) regressor which provides 91% of accuracy during the prediction process.
Multi-objective optimization for preemptive & predictive supply chain operation
Authors: Chandriah Kiran Kumar , Raghavendra N. V.
Published: March 2020

At present, the manufacturing industry has undergone a tremendous change in its operating principle with respect to the supply chain management system where the demands of consumers are dynamically and exponentially rising. Although Industry 4.0 offers a significant solution to this principle with the aid of its predictive automated operating process, till date there is less number of fault tolerant model that can effectively meet the standard demands of supply chain planning. Therefore, the proposed system introduces an analytical model where predictive optimization is carried out towards bridging the gap between supply and demands in supply chain 4.0. An analytical framework is a design from constraints derived from practical environment in order to offer better applicability of it. The study outcome shows that the proposed model could offer better performance in comparison to the existing optimization method with respect to the better budget control system for offering predictive and preemptive model design.
Myanmar named entity corpus and its use in syllable-based neural named entity recognition
Authors: Mo Hsu Myat , Soe Khin Mar
Published: March 2020

Myanmar language is a low-resource language and this is one of the main reasons why Myanmar Natural Language Processing lagged behind compared to other languages. Currently, there is no publicly available named entity corpus for Myanmar language. As part of this work, a very first manually annotated Named Entity tagged corpus for Myanmar language was developed and proposed to support the evaluation of named entity extraction. At present, our named entity corpus contains approximately 170,000 name entities and 60,000 sentences. This work also contributes the first evaluation of various deep neural network architectures on Myanmar Named Entity Recognition. Experimental results of the 10-fold cross validation revealed that syllable-based neural sequence models without additional feature engineering can give better results compared to baseline CRF model. This work also aims to discover the effectiveness of neural network approaches to textual processing for Myanmar language as well as to promote future research works on this understudied language.
Novel framework using dynamic passphrase towards secure and energy-efficient communication in MANET
Authors: B. K. Chethan , Siddappa M. , H. S. Jayanna
Published: March 2020

At Mobile Adhoc Network (MANET) has been long-researched topic in adhoc network owing to the associated advantages in its cost-effective application as well as consistent loophopes owing to its inherent charecteristics. This manuscript draws a relationship between the energy factor and security factor which has not been emphasized in any existing studies much. Review of existing security approaches shows that they are highly attack specific, uses complex encryption, and overlooks the involvement of energy factor in it. Therefore, the proposed system introduces a novel mechanism where security tokens and passphrases are utilized in order to offer better security. The proposed system also introduces the usage of an agent node which communications with mobile nodes using group-based communication system thereby ensuring reduced computational effort of mobile nodes towards establishing secured communication. The outcome shows proposed system offers better outcome in contrast to existing system.
Trust correlation of mobile agent nodes with a regular node in a Adhoc network using decision-making strategy
Authors: B. K. Chethan , Siddappa M. , H. S. Jayanna
Published: March 2020

A mobile agent offers discrete advantage both in facilitating better transmission as well as controlling the traffic load in Mobile Adhoc Network (MANET). Hence, such forms of network offers maximized dependencies on mobile agents in terms of its trust worthiness. At present, there are various work being carried out towards resisting security breach in MANET; however approaches using mobile agent based mechanism is few to found. Therefore, the proposed system introduces a novel mathematical model where an extensive decision making system has been constructed for identifying the malicious intention of mobile agents in case they go rogues. By adopting multi-tier communication policy and fairness concept, the proposed system offers the capability to resist any form of malicious activity of mobile agent without even presence of any apriori information of adversary. The outcome shows proposed system outshines existing security scheme in MANET.
Hardware description of a simplified 4-bit softcore processor with BCD capabilities
Authors: Santa Fernando Martínez , Jacinto Edwar , Montie Holman
Published: March 2020

The objective of the work reported in this paper is to improve a 4-bit softcore processor previously designed in Verilog language, keeping its compact size. This processor was thought to be used as academic and didactic tool for teaching as computers architecture subject as digital circuits subject in the technology faculty of the Universidad Distrital. The new features include arithmetic instruction with input carry, BCD operations enabling, rotating instructions, implementation of input and output register banks, increase of the number of general purpose registers of the data memory, and the reduction of the execution clock cycles per instruction. Additionally, the assembler software was enabled to support macro-instructions to make easy the comprehension of some composed functions. As result, a very compact softcore processor was obtained, by means of a Verilog description done in a single file. This implementation occupies only the 2% of the medium-size FPGA used for the application, reaching a maximum possible working clock frequency of 929 Mhz.
An approach to designing and developing an LMS framework appropriate for young pupils
Authors: Kraleva Radoslava , Sabani Mehrudin , Kralev Velin , Kostadinova Dafina
Published: March 2020

The lifestyle of the new people generation, called in the scientific literature Generation Z, is closely related to the Internet, computer and information technology. Therefore, people and children belonging to this group can be viewed in terms of software technology as specific users who have high requirements regarding the functions and interface of the software applications, connectivity to social networks and instant communication via the Internet. This influenced not only on the teaching and learning methods but also on the software applications used in the learning process. In recent years, new theoretical teaching methods have emerged, and the number of electronic learning systems increased. However, students lack motivation for the learning process. This requires developing new conceptual models of training and learning software, tailored to the skills and preferences of the end-users. The young students up to 12 years of age: from kindergartens to preschools and primary schools are special users who have not been studied exhaustively. In order to present the problem related to the development of learning and training software thoroughly, the most commonly used standards and current trends, as well as the advantages and disadvantages of LMS platforms have been reviewed. Attention is drawn to the commonly used software design and development technologies. This is the reason to propose a strategy for developing a web-based e-learning management system according to the possibilities of young pupils as a specific user. Having in mind this strategy we described a software architecture, based on SCORM's specification, and we developed an LMS prototype. Its design was tailored to the skills of young children. The basic methodology used in the design and creation of the system we propose is user-centered design. The document is intended for developers, educators and scientists, studying child-computer interaction.
Trust-based secure routing against lethal behavior of nodes in wireless adhoc network
Authors: Neeli Jyoti , Cauvery N. K.
Published: March 2020

Offering a secure communication in wireless adhoc network is yet an open-end problem irrespective of archives of existing literatures towards security enhancement. Inclination towards solving specific forms of attack in adhoc network is majorly seen as an existing trend which lowers the applicability of existing security solution while application environment or attack scenario is changed. Therefore, the proposed system implements an analytical secure routing modeling which performs consistent monitoring of the malicious behaviour of its neighboring node and formulates decision towards secure routing by the source nodes. Harnessing the potential ofconceptual probabilistic modeling, the proposed system is capable as well as applicable for resisting maximum number / types of threats in wireless network. The study outcome show proposed scheme offer better performance in contrast to existing secure routing scheme.
Preemptive modelling towards classifying vulnerability of DDoS attack in SDN environment
Authors: M. Narender , B. N. Yuvaraju
Published: March 2020

Software-Defined Networking (SDN) has become an essential networking concept towards escalating the networking capabilities that are highly demanded future internet system, which is immensely distributed in nature. Owing to the novel concept in the field of network, it is still shrouded with security problems. It is also found that the Distributed Denial-of-Service (DDoS) attack is one of the prominent problems in the SDN environment. After reviewing existing research solutions towards resisting DDoS attack in SDN, it is found that still there are many open-end issues. Therefore, these issues are identified and are addressed in this paper in the form of a preemptive model of security. Different from existing approaches, this model is capable of identifying any malicious activity that leads to a DDoS attack by performing a correct classification of attack strategy using a machine learning approach. The paper also discusses the applicability of best classifiers using machine learning that is effective against DDoS attack.
Interference aware resource allocation model for D2D under cellular network
Authors: Fatima Ruksar , Khanam Rohina , Tauseef Shaik Humera
Published: March 2020

Device-to-Device communication (D2D) has emerged as an efficient communication model in future generation cellular network for offloading cellular traffic and enhance overall network performance. D2D communication aid in attaining better spectrum utilization, lower delay, and less energy consumption, which can well adapt to meet demand of higher transmission rate, larger network capacity. Further, enhances spectral efficiency by reutilizing resource. However, it may result in severe cross-tier interference and co-tier interference. Therefore, efficient interference modelling design are required to address performance degradation caused by the interferences. The existing model has focused on addressing interference considering D2D association operating on same cell with the cellular association. As a result, it incurs interference to the cellular user located in the same cell. However, practically D2D association in overlapping area will reutilize spectrum of multiple neighboring cells. As a result, it incurs interference in multiple cells. For overcoming research challenges, this work presented Interference Aware Resource Allocation (IARA) model for D2D under cellular network as a game theory model. This work consider a resource allocation game where base station as a contender for catering D2D resource needs under different assumptions. Experiment are conducted to evaluate performance of IARA. The outcome shows IARA attained significant performance improvement over state-of-art models in terms of sum rate (utility), successful packet transmission, revenue, and delay.
Energy efficient clustering using the AMHC (adoptive multi-hop clustering) technique
Authors: M. Vimala , Ranjan Rajeev
Published: March 2020

IoT has gained fine attention in several field such as in industry applications, agriculture, monitoring, surveillance, similarly parallel growth has been observed in field of WSN. WSN is one of the primary component of IoT when it comes to sensing the data in various environment. Clustering is one of the basic approach in order to obtain the measurable performance in WSNs, Several algorithms of clustering aims to obtain the efficient data collection, data gathering and the routing. In this paper, a novel AMHC (Adaptive Multi-Hop Clustering) algorithm is proposed for the homogenous model, the main aim of algorithm is to obtain the higher efficiency and make it energy efficient. Our algorithm mainly contains the three stages: namely assembling, coupling and discarding. First stage involves the assembling of independent sets (maximum), second stage involves the coupling of independent sets and at last stage the superfluous nodes are discarded. Discarding superfluous nodes helps in achieving higher efficiency. Since our algorithm is a coloring algorithm, different color are used at the different stages for coloring the nodes. Afterwards our algorithm (AMHC) is compared with the existing system which is a combination of Second order data CC(Coupled Clustering) and Compressive-Projection PCA(Principal Component Analysis), and results shows that our algorithm excels in terms of several parameters such as energy efficiency, network lifetime, number of rounds performed.
An efficient approach for secured communication in wireless sensor networks
Authors: R. Jyothi , Cholli Nagaraj G.
Published: March 2020

Wireless sensor network (WSN) have limited bandwidth, low computational functions, energy constraints. Inspite of these constraints, WSN is useful where communication happens without infrastructure support. The main concern of WSN is the security as the sensor nodes may be attacked and information may be hacked. Security of WSN should have the capability to ensure that the message received was sent by the particular sent node and not modified during transmission. WSN applications require lightweight and strong authentication mechanisms for obtaining data from unprivileged users. In wireless sensor networks, authentication is the effective method to stop unauthorized and undisrupted communication service. In order to strengthen the authenticated communication, several researchers have developed mechanisms. Some of the techniques work with identifying the attacked node or detecting injected bogus message in the network. Encryption and decryption are the popular methods of providing the security. These are based on either public-key or symmetric-key cryptosystems Many of the existing solutions have limitations in communication and computational expertise. Also, the existing mechanisms lack in providing strength and scalability of the network. In order address these issues; a polynomial based method was introduced in recent days. Key distribution is a significant aspect in key management in WSNs. The simplest method of distribution of key is by hand which was used in the days of couriers. Now a days, most distribution of keys is done automatically. The automatic distribution of keys is essential and convenient in networks that require two parties to transmit their security keys in the same communication medium. In this work, a new type of key exchange mechanism is proposed. The proposed method for authentication among sensor nodes proves to be promising as per the simulation results. The nodes which are unknown to each other setup a private however arbitrary key for the symmetric key cryptosystem.
Approximating offset Curves using Bezier curves with high accuracy
Authors: Rababah Abedallah , Jaradat Moath
Published: March 2020

In this paper, a new method for the approximation of offset curves is presented using the idea of the parallel derivative curves. The best uniform approximation of degree 3 with order 6 is used to construct a method to find the approximation of the offset curves for Bezier curves. The proposed method is based on the best uniform approximation, and therefore; the proposed method for constructing the offset curves induces better outcomes than the existing methods.
Edge detection algorithm based on quantum superposition principle and photons arrival probability
Authors: Ezzaki Ayoub , Masmoudi Lhoussaine , El Ansari Mohamed , Moreno Francisco-Angel , Zenouhi Rachid , Jimenez Javier Gonzalez
Published: March 2020

The detection of object edges in images is a crucial step employed in a vast amount of computer vision applications, for which a series of different algorithms has been developed in the last decades. This paper proposes a new edge detection method based on quantum information, which is achieved in two main steps: (i) an image enhancement stage that employs the quantum superposition law and (ii) an edge detection stage based on the probability of photon arrival to the camera sensor. The proposed method has been tested on synthetic and real images devoted to agriculture applications, where Fram & Deutsh criterion has been adopted to evaluate its performance. The results show that the proposed method gives better results in terms of detection quality and computation time compared to classical edge detection algorithms such as Sobel, Kayyali, Canny and a more recent algorithm based on Shannon entropy.
A survey on power management strategies of hybrid energy systems in microgrid
Authors: Prudhvi Kumar G. R. , Sattianadan D. , Vijayakumar K.
Published: March 2020

The power generation through renewable energy resources is increasing vastly, Solar energy and Wind Energy are the most abundantly available renewable energy resources. The growth of small scale distributed grid networks increasing rapidly in the modern power systems and Distributed Generation (DG) plays a predominant role. Microgrid is one among the emerging techniques in power systems. Power Management is mainly required to have control over the real and reactive power of individual DG and for smooth operation, maintaining stability and reliability. This paper presents a survey of the research works already reported focusing on power management of hybrid energy systems such as mainly solar and wind systems in microgrid. Six different approaches have been studied in detail for AC,DC and hybrid AC/DC microgrid.
Exciting field and quadrature-axis armature reaction in a cascade equivalent A-H-circuit of a salient-pole generator
Authors: Blanc Alexey
Published: March 2020

Cartesian and cylindrical laminated models are well known in calculations of electric machines. In such models, general solutions of partial differential equations are transformed into four-terminal network equations, and this makes possible to synthesize cascade equivalent circuits of electric machines. In salient-pole machines, solutions of partial differential equations are formed on the base of piecewise continuous Sturm-Liouville eigenfunctions. However, in this case, cascade equivalent circuits cannot be synthesized since it needs many piecewise continuous eigenfunctions in the zone of poles and many smooth functions in the zone of the air gap for ensuring uniqueness of a solution. Meanwhile the author of this paper had offered an approximate method on the base of the single piecewise continuous Sturm-Liouville eigenfunction in the zone of poles and many smooth functions in the zone of the air gap. This method allows transforming a solution of a partial differential equation into four-terminal network equations and synthesizing cascade equivalent circuits of salient-pole machines. In this paper, electromagnetic field of a synchronous salient-pole generator is calculated with a cascade equivalent A-H-circuit. The cell that corresponds to rotor poles is synthesized on the base of a solution of Laplace's equation with the single piecewise continuous Sturm-Liouville eigenfunction.
Electrical treeing and partial discharge characteristics of silicone rubber filled with nitride and oxide based nanofillers
Authors: M. Nasib A. H. , Ahmad M. H. , Nawawi Z. , Sidik M. A. B. , Jambak M. I.
Published: March 2020

This article presents a study on electrical treeing performances with its associated partial discharge (PD) and the influence of filler concentration in silicone rubber (SiR) samples which are filled with silicon dioxide (SiO2) and silicon nitride (Si3N4) as nanofillers for electrical tree growth suppression. There are many researches on electrical treeing in SiR with SiO2 nanofillers but none of the publication have reported on Si3N4 nanofillers for suppression of the electrical tree growth. In this study, the treeing experiments were conducted by applying a fixed AC voltage of 10 kV and 12 kV at power frequency of 50 Hz on unfilled SiR, SiR/SiO2, and SiR/Si3N4 nanocomposites with different filler concentrations by 1, 3, and 5 weight percentage (wt%) and the electrical treeing parameters were observed with its correlated PD patterns. The outcome from this study found that the SiR/Si3N4 nanocomposites were able to withstand the electrical treeing better than the pure SiR or SiR/SiO2 nanocomposites. Furthermore, the increase in filler concentration improved the electrical tree performances of the nanocomposites. This finding suggests the Si3N4 can be used as filler in polymeric insulating materials for electrical tree inhibition. Meanwhile, the PD activity shows increment when the tree progresses thereby indicating correlation in both parameters which can be as key parameter for monitoring unseen electrical treeing in the opaque samples.
Quantification of operating reserves with high penetration of wind power considering extreme values
Authors: Obando Johan S. , González Gabriel , Moreno Ricardo
Published: March 2020

The high integration of wind energy in power systems requires operating reserves to ensure the reliability and security in the operation. The intermittency and volatility in wind power sets a challenge for day-ahead dispatching in order to schedule generation resources. Therefore, the quantification of operating reserves is addressed in this paper using extreme values through Monte-Carlo simulations. The uncertainty in wind power forecasting is captured by a generalized extreme value distribution to generate scenarios. The day-ahead dispatching model is formulated as a mixed-integer linear quadratic problem including ramping constraints. This approach is tested in the IEEE-118 bus test system including integration of wind power in the system. The results represent the range of values for operating reserves in day-ahead dispatching.
Development of DC voltage control from wind turbines using proportions and integrals for three-phase grid-connected inverters
Authors: Chaithanakulwat Arckarakit
Published: March 2020

This research article presents the method to control the DC voltage of the boost converter by using a proportional-integral (PI) controller. With AC voltage from a wind turbine generator, converting to DC voltage level by rectifier, this DC voltage controlled by PI controller is to control boost converter that sends DC links to the inverter which converting alternating current voltage to direct current voltage through three-phase load and to the grid-connected system. For switching the IGBTs in the inverter, the PWM signal, on the hysteresis current control, is controlled by the signal from the detected reference voltage based on the grid-connected system and the voltage from a wind turbine generator. The tests made the comparison of results from the simulation with the MATLAB/Simulink program and result from the hardware on the prototype. The power quality results, such as harmonic, power factor, are in acceptable ranges.
Transmission line short circuit analysis by impedance matrix method
Authors: Anyaka Boniface Onyemaechi , Ozioko Innocent Onyebuchi
Published: March 2020

Fault analysis is the process of determining the magnitude of fault voltage and current during the occurrence of different types of fault in electrical power system. Transmission line fault analysis is usually done for both symmetrical and unsymmetrical faults. Symmetrical faults are called three-phase balance fault while unsymmetrical faults include: single line-to-ground, line-to-line, and double line-to-ground faults. In this research, bus impedance matrix method for fault analysis is presented. Bus impedance matrix approach has several advantages over Thevenin’s equivalent method and other conventional approaches. This is because the off-diagonal elements represent the transfer impedance of the power system network and helps in calculating the branch fault currents during a fault. Analytical and simulation approaches on a single line-to-ground fault on 3-bus power system network under bolted fault condition were used for the study. Both methods were compared and result showed negligible deviation of 0.02% on the average. The fault currents under bolted condition for the single line-to-ground fault were found to be 4. 7244p.u while the bus voltage is 0. 4095p.u for buses 1 and 2 respectively and 0. 00p.u for bus 3 since the fault occurred at this bus. Therefore, there is no need of burdensomely connecting the entire three sequence network during fault analysis in electrical power system.
Switching pulse generation for DC-DC boost converter using Xilinx-ISE with FPGA processor
Authors: Palanisamy R. , Boopathi C. S. , Selvakumar K. , Vijayakumar K.
Published: March 2020

This paper explains steps to generate switching pulse using Xilinx-ISE with FPGA processor for DC-DC boost converter. The switching pulse generated using Very high speed integrated circuit Hardware Description Language (VHDL) with Xilinx-ISE. VHDL is a programming language, which is used to model and design any complex circuits in a dynamic environment. This paper gives the course of action for generation of switching pulses for dc-dc boost converter using Xilinx-ISE and matlab simulink. The switching pulse generated using Xilinx-ISE with FPGA-Spartan 6 processor compared with switching pulse generated using matlab.
New proposed spherical slotted antenna covered by the layers of dielectric material and plasma
Authors: Dautov Osman Shakirovich , AL-Abadi Mohammad Sadon , Al-Anbagi Haidar N.
Published: March 2020

The operation of the new proposed spherical slotted antenna covered by layers of dielectric material and plasma was analyzed numerically in this paper. By utilizing the Integra-functional equations method, the optimum thickness of dielectric material layer and suitable conditions which improve the operation of this antenna are analyzed here by MATHCAD. The thickness of dielectric layer must not be less or more than λ/6. Furthermore, the authors propose manipulating the operation frequency to enable such antenna to work in most circumstances.
Noninvasive blood glucose monitoring system based on near-infrared method
Authors: Al-dhaheri Mustafa Ayesh , Mekkakia-Maaza Nasr-Eddine , Mouhadjer Hassan , Lakhdari Abdelghani
Published: March 2020

Diabetes is considered one of the life-threatening diseases in the world which need continuous monitoring to avoid the complication of diabetes. There is a need to develop a non-invasive monitoring system that avoids the risk of infection problems and pain caused by invasive monitoring techniques. This paper presents a method for developing a noninvasive technique to predict the blood glucose concentration (BCG) based on the Near-infrared (NIR) light sensor. A prototype is developed using a finger sensor based on LED of 940 nm wavelength to collect photoplethysmography (PPG) signal which is variable depending on the glucose concentration variance, a module circuit to preprocess PPG signals is realized, which includes an amplifier and analog filter circuits, an Arduino UNO is used to analog-to-digital conversion. A digital Butterworth filterer is used to remove PPG signal trends, then detect the PPG data peaks to determine the relationship between the PPG signal and (BCG) and use it as input parameters to build the calibration model based on linear regression. Experiments show that the Root Mean Squares Error (RMSE) of the prediction is between 8.264mg/dL and 13.166 mg/dL, the average of RMSE is about 10.44mg/dL with a correlation coefficient (R^2) of 0.839, it is observed that the prediction of glucose concentration is in the clinically acceptable region of the standard Clark Error Grid (CEG).
Subthreshold swing model using scale length for sub-10 nm junction-based double-gate MOSFETs
Authors: Jung Hakkee
Published: March 2020

We propose an analytical model for subthreshold swing using scale length for sub-10 nm double gate (DG) MOSFETs. When the order of the calculation for the series type potential distribution is increased it is possible to obtain accuracy, but there is a problem that the calculation becomes large. Using only the first order calculation of potential distribution, we derive the scale length λ1 and use it to obtain an analytical model of subthreshold swing. The findings show this subthreshold swing model is in concordance with a 2D simulation. The relationship between the channel length and silicon thickness, which can analyze the subthreshold swing using λ1, is derived by the relationship between the scale length and the geometric mean of the silicon and oxide thickness. If the silicon thickness and oxide film thickness satisfy the condition of (Lg-0.215)/6.38 > tsi(=tox), it is found that the result of this model agrees with the results using higher order calculations, within a 4% error range.
Area efficient parallel lfsr for cyclic redundancy check
Authors: Mahajan Rita , Devi Komal , Bagai Deepak
Published: March 2020

Cyclic Redundancy Check (CRC), code for error detection finds many applications in the field of digital communication, data storage, control system and data compression. CRC encoding operation is carried out by using a Linear Feedback Shift Register (LFSR). Serial implementation of CRC requires more clock cycles which is equal to data message length plus generator polynomial degree but in parallel implementation of CRC one clock cycle is required if a whole data message is applied at a time. In previous work related to parallel LFSR, hardware complexity of the architecture reduced using a technique named state space transformation. This paper presents detailed explaination of search algorithm implementation and technique to find number of XOR gates required for different CRC algorithms. This paper presents a searching algorithm and new technique to find the number of XOR gates required for different CRC algorithms. The comparison between proposed and previous architectures shows that the number of XOR gates are reduced for CRC algorithms which improve the hardware efficiency. Searching algorithm and all the matrix computations have been performed using MATLAB simulations.
Threshold voltage model for hetero-gate-dielectric tunneling field effect transistors
Authors: Singh Ajay Kumar , Fui Tan Chun , Xin Wilson Tan Wee
Published: March 2020

In this paper, a two dimensional analytical model of the threshold voltage for HGD TFET structure has been proposed. We have also presented the analytical models for the tunneling width and the channel potential. The potential model is used to develop the physics based model of threshold voltage by exploring the transition between linear to exponential dependence of drain current on the gate bias. The proposed model depends on the drain voltage, gate dielectric near the source and drain, silicon film thickness, work function of gate metal and oxide thickness. The accuracy of the proposed model is verified by simulation results of 2-D ATLAS simulator. Due to the reduction of the equivalent oxide thickness, the coupling between the gate and the channel junction enhances which results in lower threshold voltage. Tunneling width becomes narrower at a given gate voltage for the optimum channel concentration of 1016 /cm3. The higher concentration in the source (Ns) causes a steep bending in the conduction and valence bands compared to the lower concentration which results in smaller tunneling width at the source-channel interface.