bluuebunny/crossref_metadata_2025 huggingface dataset:
An efficient resource sharing technique for multi-tenant databases
Authors: G. B. Pallavi , Jayarekha P.
Published: March 2020

Multi-tenancy is one of the key components of cloud computing environment. Multi-tenant database system in SaaS (Software as a Service) has gained a lot of attention in academics, research and business arena. These database systems provide scalability and economic benefits for both cloud service providers and customers(organizations/companies referred as tenants) by sharing same resources and infrastructure in isolation of shared databases, network and computing resources with Service level agreement (SLA) compliances. In a multitenant scenario, active tenants compete for resources in order to access the database. If one tenant blocks up the resources, the performance of all the other tenants may be restricted and a fair sharing of the resources may be compromised. The performance of tenants must not be affected by resource-intensive activities and volatile workloads of other tenants. Moreover, the prime goal of providers is to accomplish low cost of operation, satisfying specific schemas/SLAs of each tenant. Consequently, there is a need to design and develop effective and dynamic resource sharing algorithms which can handle above mentioned issues. This work presents a model embracing a query classification and worker sorting technique to efficiently share I/O, CPU and Memory thus enhancing dynamic resource sharing and improvising the utilization of idle instances proficiently. The model is referred as Multi-Tenant Dynamic Resource Scheduling Model (MTDRSM) .The MTDRSM support workload execution of different benchmark such as TPC-C(Transaction Processing Performance Council), YCSB(The Yahoo! Cloud Serving Benchmark)etc. and on different database such as MySQL, Oracle, H2 database etc. Experiments are conducted for different benchmarks with and without SLA compliances to evaluate the performance of MTDRSM in terms of latency and throughput achieved. The experiments show significant performance improvement over existing Mute Bench model in terms of latency and throughput.
The pertinent single-attribute-based classifier for small datasets classification
Authors: Jamjoom Mona
Published: March 2020

Classifying a dataset using machine learning algorithms can be a big challenge when the target is a small dataset. The OneR classifier can be used for such cases due to its simplicity and efficiency. In this paper, we revealed the power of a single attribute by introducing the pertinent single-attribute-based-heterogeneity-ratio classifier (SAB-HR) that used a pertinent attribute to classify small datasets. The SAB-HR’s used feature selection method, which used the Heterogeneity-Ratio (H-Ratio) measure to identify the most homogeneous attribute among the other attributes in the set. Our empirical results on 12 benchmark datasets from a UCI machine learning repository showed that the SAB-HR classifier significantly outperformed the classical OneR classifier for small datasets. In addition, using the H-Ratio as a feature selection criterion for selecting the single attribute was more effectual than other traditional criteria, such as Information Gain (IG) and Gain Ratio (GR).
An enhanced lossless compression with cryptography hybrid mechanism for ECG biomedical signal monitoring
Authors: Hameed Mustafa , Ibrahim Masrullizam Mat , Manap Nurulfajar Abd , Mohammed Ali A.
Published: March 2020

Due to their use in daily life situation, demand for remote health applications and e-health monitoring equipment is growing quickly. In this phase, for fast diagnosis and therapy, information can be transferred from the patient to the distant clinic. Nowadays, the most chronic disease is cardiovascular diseases (CVDs). However, the storage and transmission of the ECG signal, consumes more energy, bandwidth and data security which is faced many challenges. Hence, in this work, we present a combined approach for ECG data compression and cryptography. The compression is performed using adaptive Huffman encoding and encrypting is done using AES (CBC) scheme with a 256-bit key. To increase the security, we include Diffie-Hellman Key exchange to authenticate the receiver, RSA key generation for encrypting and decrypting the data. Experimental results show that the proposed approach achieves better performance in terms of compression and encryption on MIT-BIH ECG dataset.
An exploratory research on grammar checking of Bangla sentences using statistical language models
Authors: Rahman M. D. Riazur , Habib M. D. Tarek , Rahman M. D. Sadekur , Islam Gazi Zahirul , Khan M. D. Abbas Ali
Published: March 2020

N-gram based language models are very popular and extensively used statistical methods for solving various natural language processing problems including grammar checking. Smoothing is one of the most effective techniques used in building a language model to deal with data sparsity problem. Kneser-Ney is one of the most prominently used and successful smoothing technique for language modelling. In our previous work, we presented a Witten-Bell smoothing based language modelling technique for checking grammatical correctness of Bangla sentences which showed promising results outperforming previous methods. In this work, we proposed an improved method using Kneser-Ney smoothing based n-gram language model for grammar checking and performed a comparative performance analysis between Kneser-Ney and Witten-Bell smoothing techniques for the same purpose. We also provided an improved technique for calculating the optimum threshold which further enhanced the the results. Our experimental results show that, Kneser-Ney outperforms Witten-Bell as a smoothing technique when used with n-gram LMs for checking grammatical correctness of Bangla sentences.
Transmitting audio via fiber optics under nonlinear effects and optimized tuning parameters based on Co-simulation of matlab and optisystemTM
Authors: Al-Hayder Abdulrasul A. , Abd H. J. , Alkhafaji Ahmed Samawi
Published: March 2020

Limitations of conventional wires such as copper wires are causing dispersion and distortion of the message signal for long distances communication especially for the wide bandwidths. The ability of fiber optic to overcome this problem is making it a dominant transmission medium. Despite of this major positive attribute of optic fibers, there is still a downside for using the fiber optic communication; that is the nonlinearity problem especially at the very high frequency bandwidth. For the first time, a desigen of an audio signal is suggested and executed in MatLab with an integration with OptiSystemTM software to discuss and solve this issu. The audio signal is then transmitted in different shapes of modulation signals (NRZ, RZ & RC) for different distances (100 km & 75 km) via a fiber optic media to be received in a receiving part of the simulated system. Three tests are used to do so. The first is the Quality-factor (Q-Factor) against the received power, second test is eye diagram performance and finally is the measuring of the amplitude of output (received) signal for each modulation signal shape using the Oscilloscope Visualizer. The NZR modulation signal was found to be the best one of the three used signals’ types in all three tests. The Q-factor for NRZ pulse shape (=12) was higher than that for RZ (=10) and RC (=8) for a 100 km distance at the same received power level.
Population based optimization algorithms improvement using the predictive particles
Authors: Elroby M. M. H. , Mekhamer S. F. , Talaat H. E. A. , Hassan M. A. Moustafa
Published: March 2020

A new efficient improvement, called Predictive Particle Modification (PPM), is proposed in this paper. This modification makes the particle look to the near area before moving toward the best solution of the group. This modification can be applied to any population algorithm. The basic philosophy of PPM is explained in detail. To evaluate the performance of PPM, it is applied to Particle Swarm Optimization (PSO) algorithm and Teaching Learning Based Optimization (TLBO) algorithm then tested using 23 standard benchmark functions. The effectiveness of these modifications are compared with the other unmodified population optimization algorithms based on the best solution, average solution, and convergence rate.
Network efficiency enhancement by reactive channel state based allocation scheme
Authors: G. B. Umesh , Swamy M. N. Shanmukha
Published: March 2020

Now a day the large MIMO has considered as the efficient approach to improve the spectral and energy efficiency at WMN. However, the PC is a big issue that caused by reusing similar pilot sequence at cells, which also restrict the performance of massive MIMO network. Here, we give the alternative answer, where each of UEs required allotting a channel sequences before passing the payload data, so as to avoid the channel collision of inter-cell. Our proposed protocol will ready to determine the channel collisions in distributed and scalable process, however giving unique properties of the large MIMO channels. Here we have proposed a RCSA (Reactive channel state based allocation) scheme, which will very productively work with the RAP blockers at large network of MIMO. The position of time-frequency of RAP blocks is modified in the middle of the adjacent cells, because of this design decision the RAP defend from the hardest types of interference at inter-cell. Further, to validate the performance of our proposed scheme it will be compared with other existing technique.
Maximize resource utilization based channel access model with presence of reactive jammer for underwater wireless sensor network
Authors: Bagali Sheetal , Sundaraguru R.
Published: March 2020

Underwater sensor networks (UWSNs) are vulnerable to jamming attacks. Especially, reactive jamming which emerged as a greatest security threat to UWSNs. Reactive jammer are difficult to be removed, defended and identified. Since reactive jammer can control and regulate (i.e., the duration of the jam signal) the probability of jamming for maintaining high vulnerability with low detection probability. The existing model are generally designed considering terrestrial wireless sensor networks (TWSNs). Further, these models are limited in their ability to detect jamming correctly, distinguish between the corrupted and uncorrupted parts of a packet, and be adaptive with the dynamic environment. Cooperative jamming model has presented in recent times to utilize resource efficiently. However, very limited work is carried out using cooperative jamming detection. For overcoming research challenges, this work present Maximize Resource Utilization based Channel Access (MRUCA). The MRUCA uses cross layer design for mitigating reactive jammer (i.e., MRUCA jointly optimizes the cooperative hopping probabilities and channel accessibility probabilities of authenticated sensor device). Along with channel, load capacity of authenticated sensor device is estimated to utilize (maximize) resource efficiently. Experiment outcome shows the proposed MRUCA model attain superior performance than state-of-art model in terms of packet transmission, BER and Detection rate.
Efficient two-stage cryptography scheme for secure distributed data storage in cloud computing
Authors: Abdel-Kader Rabab F. , El-sherif Samar H. , Rizk Rawya Y.
Published: March 2020

Cloud computing environment requires secure access for data from the cloud server, small execution time, and low time complexity. Existing traditional cryptography algorithms are not suitable for cloud storage. In this paper, an efficient two-stage cryptography scheme is proposed to access and store data into cloud safely. It comprises both user authentication and encryption processes. First, a two-factor authentication scheme one-time password is proposed. It overcomes the weaknesses in the existing authentication schemes. The proposed authentication method does not require specific extra hardware or additional processing time to identity the user. Second, the plaintext is divided into two parts which are encrypted separately using a unique key for each. This division increases the security of the proposed scheme and in addition decreases the encryption time. The keys are generated using logistic chaos model theory. Chaos equation generates different values of keys which are very sensitive to initial condition and control parameter values entered by the user. This scheme achieves high-security level by introducing different security processes with different stages. The simulation results demonstrate that the proposed scheme reduces the size of the ciphertext and both encryption and decryption times than competing schemes without adding any complexity.
Analysis on techniques used to recognize and identifying the Human emotions
Authors: Kulkarni Praveen , T. M. Rajesh
Published: March 2020

Facial expression is a major area for non-verbal language in day to day life communication. As the statistical analysis shows only 7 percent of the message in communication was covered in verbal communication while 55 percent transmitted by facial expression. Emotional expression has been a research subject of physiology since Darwin’s work on emotional expression in the 19th century. According to Psychological theory the classification of human emotion is classified majorly into six emotions: happiness, fear, anger, surprise, disgust, and sadness. Facial expressions which involve the emotions and the nature of speech play a foremost role in expressing these emotions. Thereafter, researchers developed a system based on Anatomic of face named Facial Action Coding System (FACS) in 1970. Ever since the development of FACS there is a rapid progress of research in the domain of emotion recognition. This work is intended to give a thorough comparative analysis of the various techniques and methods that were applied to recognize and identify human emotions. This analysis results will help to identify the proper and suitable techniques, algorithms and the methodologies for future research directions. In this paper extensive analysis on the various recognition techniques used to identify the complexity in recognizing the facial expression is presented. This work will also help researchers and scholars to ease out the problem in choosing the techniques used in the identification of the facial expression domain.
LSTM deep learning method for network intrusion detection system
Authors: Boukhalfa Alaeddine , Abdellaoui Abderrahim , Hmina Nabil , Chaoui Habiba
Published: March 2020

The security of the network has become a primary concern for organizations. Attackers use different means to disrupt services or steal information, these various attacks push to think of a new way to block them all in one manner. In addition, these intrusions can change and penetrate the devices of security. To solve these issues, we suggest, in this paper, a new idea for Network Intrusion Detection System (NIDS) based on Long Short-TermMemory (LSTM) to recognize menaces and to obtain a long-term memory on them, inorder to stop the new attacks that are like the existing ones, and at the sametime, to have a single mean to block intrusions. According to the results of the experiments of detections that we have carried out, the Accuracy reaches upto 99.98 % and 99.93 % for respectively the classification of two classes and several classes, Also the False Positive Rate (FPR) reaches up to only 0,068 % and 0,023 % for respectively the classification of two classes and several classes, which proves that the proposed model is very effective, it has a great ability to memorize and differentiate between normal traffic and attack traffic and its identification is more accurate than other Machine Learning classifiers.
Improved magnetic behavior of hemicycle PM motor via stator modification
Authors: T. C. Kwang , Mohd Jamil Mohd Luqman , Jidin Auzani
Published: March 2020

This article presents the simple basic sizing approaches to decrease overall weight of motor and improve magnetic characteristics in PM motor. A review on various stator design in PM motor i.e. radial-flux or axial-flux with slotted or non-slotted is presented. As magnetic and electric loading influence the electromagnetic motor performance, modification on stator body are included in investigation for a desired electromagnetic torque performance. Influences of tooth body width sizing and additional stator slots sizing in PM motor equip with hemicycle stator design are carried out. Two designs are included, both having similar semi-circle stator but different in additional slot tooth within and over 180 ○ i.e. Design 2 and 3 respectively. For optimization using 2D-Finite Element Analysis, optimal tooth body sizing and additional stator tooth result the weight significantly reduce by 44%, 5.9 Nm output torque and 30% torque ripple.
Analysis of direct power control AC-DC converter under unbalance voltage supply for steady-state and dynamic response
Authors: Mohd Yusoff Nor Azizah , Razali Azziddin M. , Karim Kasrul Abdul , Raja Othman Raja Nor Firdaus Kashfi , Jidin Auzani , Md Zuki Nor Aishah , Abdullah Nurfaezah
Published: March 2020

This paper presents an analysis of Direct Power Control (DPC) technique for the Three-Phase Pulse Width Modulation (PWM) AC-DC converter under unbalanced supply condition. Unbalance condition will cause the presence of unbalanced current and voltages thus produce the negative components on the grid voltage as well as severe performance degradation of a grid connected Voltage Source Inverter (VSI). The input structures for conventional DPC has been modified with a three simpler sequence networks instead of coupled by a detailed Three-Phase system method. The imbalance voltage can be resolved by separating from the individual elements of voltage and current into symmetrical components called Sequence Network. Consequently, the input power relatively improved during unbalanced condition almost 70% through the measurement of Total Harmonic Distortion (THD) from the conventional Direct Power Control (DPC) in individual elements which is higher compared to separate components. Hence, several analyses are performed in order to analyze the steady state and dynamic performance of the converter, particularly during the load and DC voltage output reference variations.
Comparative study of the price penalty factors approaches for Bi-objective dispatch problem via PSO
Authors: Meziane Mohammed Amine , Mouloudi Youssef , Draoui Abdelghani
Published: March 2020

One of the main objectives of electricity dispatch centers is to schedule the operation of available generating units to meet the required load demand at minimum operating cost with minimum emission level caused by fossil-based power plants. Finding the right balance between the fuel cost the green gasemissionsis reffered as Combined Economic and Emission Dispatch (CEED) problem which is one of the important optimization problems related the operationmodern power systems. The Particle Swarm Optimization algorithm (PSO) is a stochastic optimization technique which is inspired from the social learning of birds or fishes. It is exploited to solve CEED problem. This paper examines the impact of six penalty factors like "Min-Max", "Max-Max", "Min-Min", "Max-Min", "Average" and "Common" price penalty factors for solving CEED problem. The Price Penalty Factor for the CEED is the ratio of fuel cost to emission value. This bi-objective dispatch problem is investigated in the Real West Algeria power network consisting of 22 buses with 7 generators. Results prove capability of PSO in solving CEED problem with various penalty factors and it proves that Min-Max price penalty factor provides the best compromise solution in comparison to the other penalty factors.
Optimized placement of multiple FACTS devices using PSO and CSA algorithms
Authors: Patil Basanagouda , Karajgi S. B.
Published: March 2020

This paper is an attempt to develop a multi-facts device placementin deregulated power system using optimization algorithms. The deregulated power system is the recent need in the power distribution as it has many independent sellers and buyers of electricity. The problem of deregulation is the quality of the power distribution as many sellers are involved. The placement of FACTS devices provides the solution for the above problem. There are researches available for multiple FACTS devices. The optimization algorithms like Particle Swarm Optimization (PSO) and Cuckoo Search Algorithm (CSA) are implemented to place the multiple FACTS devices in a power system. MATLAB based implementation is carried out for applying Optimal Power Flow (OPF) with variation in the bus power and the line reactance parameters. The cost function is used as the objective function. The cost reduction of FACTS as well as generation by placement of different compensators like, Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC) and Unified Power Flow Controller (UPFC). The cost calculation is done on the 3-seller scenario. The IEEE 14 bus is taken here as 3-seller system.
Hybrid method for achieving Pareto front on economic emission dispatch
Authors: Rajesh Kummari , Visali N.
Published: March 2020

In this paper hybrid method, Modified Nondominated Sorted Genetic Algorithm (MNSGA-II) and Modified Population Variant Differential Evolution(MPVDE) have been placed in effect in achieving the best optimal solution of Multiobjective economic emission load dispatch optimization problem. In this technique latter, one is used to enforce the assigned percent of the population and the remaining with the former one. To overcome the premature convergence in an optimization problem diversity preserving operator is employed, from the tradeoff curve the best optimal solution is predicted using fuzzy set theory. This methodology validated on IEEE 30 bus test system with six generators, IEEE 118 bus test system with fourteen generators and with a forty generators test system. The solutions are dissimilitude with the existing metaheuristic methods like Strength Pareto Evolutionary Algorithm-II, Multiobjective differential evolution, Multi-objective Particle Swarm optimization, Fuzzy clustering particle swarm optimization, Nondominated sorting genetic algorithm-II.
Voltage profile enhancement in distribution network using static synchronous compensator STATCOM
Authors: Suliman Mohammed Yahya
Published: March 2020

STATCOM is one of FACTS devices that used as regulator for transmission and distribution systems which works for reactive power compensation. STATCOM utilisation in distribution system mostly for enhancing the profile of voltage, where used for adjusting the disturbance voltage by injecting into the system a controllable voltage. This paper present a Fuzzy controller based on STATCOM to enhance the voltage profile in distribution network. The controller of STATCOM has simulated for different types of abnormal load conditions of balance and unbalance load. The results of simulation show ability of proposed design to enhance the load voltage which was 96% of the nominal value.
Loss allocation in distribution networks with distributed generators undergoing network reconfiguration
Authors: Hota Ambika Prasad , Mishra Sivkumar
Published: March 2020

In this paper, a branch exchange based heuristic network reconfiguration method is proposed for obtaining an optimal network in a deregulated power system. A unique bus identification scheme is employed which makes the load flow and loss calculation faster due to its reduced search time under varying network topological environment. The proposed power loss allocation technique eliminates the effect of cross-term analytically from the loss formulation without any assumptions and approximations. The effectiveness of the proposed reconfiguration and loss allocation methods are investigated by comparing the results obtained by the present approach with that of the existing “Quadratic method” using a 33-bus radial distribution system with/without DGs.
A comparison of single phase standalone square waveform solar inverter topologies: half bridge and full bridge
Authors: Chemseddine Aicha , Benabadji Noureddine , Cheknane Ali , Mankour Salah Eddine
Published: March 2020

In stand-alone photovoltaic installations the photovoltaic inverter allows transforming the DC power produced by the photovoltaic modules into an AC power. Depending on the shape of the AC output voltage generated by the inverter there exist three main types of stand-alone PV inverters: pure sine waveform inverters, modulated sine waveform inverters and square waveform inverters and each type of these inverters is also divided into different topologies. In this paper we will be interested and study the square waveform stand-alone inverter topologies which are the half bridge and the full-bridge inverter topologies.
Enhancement of power quality using microprocessor based shunt active power filter for unbalanced load
Authors: B. R. Madhu , M. N. Dinesh , Thinlas Tsewang , Menezes Deril
Published: March 2020

Power quality is the most significant factor of power sector. The end user equipment such as induction motor, inverters, rectifiers inject harmonics into power system that influences the quality of power delivered. The presence of harmonics forces the use of instantaneous reactive power theory to calculate instantaneous power that helps in finding the compensating currents to eliminate harmonics. The control action required by active filter is accomplished by STM32F303RET6 microcontroller. Single phase induction motor is used as a dynamic nonlinear load in one of the three phases and resistive loads on the other two phases. TRIAC based RC triggering circuit was used to control the single phase induction motor. This paper presents the simulation and hardware implementation of shunt active power filter for 3 phase 4 wire unbalanced system. The hardware results show that THD in the source side has been reduced from 50.7% to 9.6% by implementing the SAPF.
A feasibility study of electrical energy generation from municipal solid waste in Iraq: Najaf case study
Authors: Anssari Othman M. , Alkaldy Esam A. , Almudhaffar Naseem , AlTaee Abbas Nasir , Ali Nabeel Salih
Published: March 2020

In several developing countries, the electricity crisis obstructs both socio-economic and technological sustainable evolution. Also, it leads to reducing job availability due to shut down several industries or relocate to neighbouring countries to such an issue. A Najaf City is an important holy and tourist city in the middle of Iraq country. Indeed, waste management in An Najaf City needs to be reconsidered to be used as an energy source. In this article, we investigated and listed the waste quantity which produced recently (one year) respect to waste types and types of content. Data collected from the waste products for one year and are used as a key factor to study the feasibility of generating electrical energy from collected MSWs. The proposed model was simulated and tested respect to cost analysis factor of the suggested power plant by Homer pro simulation software. Results were very encouraging and competitive to the current energy production cost based on the production cost of the Kwh prospective among the conventional methods in Iraq. The proposed scenario provide proper and secure waste proposal technique with low-cost.
Active power ouptut optimization for wind farms and thermal units by minimizing the operating cost and emissions
Authors: Cherkaoui Nazha , Belfqih Abdelaziz , El Mariami Faissal , Boukherouaa Jamal , Berdai Abdelmajid
Published: March 2020

In recent years, many works have been done in order to discuss economic dispatch in which wind farms are installed in electrical grids in addition to conventional power plants. Nevertheless, the emissions caused by fossil fuels have not been considered in most of the studies done before. In fact, thermal power plants produce important quantities of emissions for instance, carbon dioxide (CO2) and sulphur dioxide (SO2) that are harmful to the environment. This paper presents an optimization algorithm with the objective to minimize the emission levels and the production cost. A comparison of the results obtained with different optimization methods leads us to opt for the grey wolf optimizer technique (GWO) to use for solving the proposed objective function. First, the method used to estimate the wind power of a plant is presented. Second, the economic dispatch models for wind and thermal generators are presented followed by the emission dispatch model for the thermal units.Then, the proposed objective function is formulated. Finally, the simulation results obtained by applying the GWO and other known optimization techniques are analysed and compared.
Performance enhancement of DC/DC converters for solar powered EV
Authors: S. Nagaraj , R. Ranihemamalini , L. Rajaji
Published: March 2020

The paper initially presents the essential drive arrangement required for electric vehicle. It requests high power bidirectional stream ability, with wide info voltage range, and yield voltage of vitality stockpiling gadgets, for example, super capacitors or batteries shift with the adjustment in stack. At that point the tenacity and outline of previously mentioned converter is proposed in this paper. The converter which relates a half extension topology, has high power stream ability and least gadget focuses on that can appropriately interface a super capacitor with the drive prepare of a crossover electric vehicle. Besides, by contrasting the fundamental qualities and applications with some ordinary bidirectional DC/DC converter, the proposed converter has low gadget rating and can be controlled by obligation cycle and stage move. Finally, the most essential attributes of this converter is that it utilizes the transformer spillage inductance as the essential vitality exchange component and control parameters, Simulation waveforms in light of MATLAB recreation are given to exhibit the integrity of this novel topology, and this converter is additionally reasonable for high power application, specifically to control the charge-release of super capacitors or batteries that can be utilized as a part of cross breed solar based electric vehicle.
Solving practical economic load dispatch problem using crow search algorithm
Authors: Spea Shaimaa R.
Published: March 2020

The practical economic load dispatch problem is a non-convex, non-smooth, and non-linear optimization problem due to including practical considerations such as valve-point loading effects and multiple fuel options. An optimization algorithm named crow search algorithm is proposed in this paper to solve the practical non-convex economic load dispatch problem. Three cases with different economic load dispatch configurations are studied. The simulation results and statistical analysis show the efficiency of the proposed crow search algorithm. Also, the simulation results are compared to the other reported algorithms. The comparison of results confirm the high-quality solutions and the effectiveness of the proposed method for solving the non-convex practical economic load dispatch problem.
Fuzzy logic applications for data acquisition systems of practical measurement
Authors: Haddin Muhammad , Marwanto Arief , Suprajitno Agus , Ismail Munaf
Published: March 2020

In laboratory works, the error in measurement, reading the measurring devices, similarity of experimental data and lack of understanding of practicum materials are often found. These will lead to the inacurracy and invalid in data obtanined. As an alternative solution, application of fuzzy logic to the data acquisition system using a web server can used. This research focuses on the design of data acquisition systems with the target of reducing the error rate in measuring experimental data on the laboratory. Data measurement on laboratory practice module is done by taking the analog data resulted from the measurement. Furthermore, the data are converted into digital data via arduino and stored on the server. To get valid data, the server will process the data by using fuzzy logic method. The valid data are integrated into a web server so that it can be accessed as needed. The results showed that the data acquisition system based on fuzzy logic is able to provide recommendation of measurement result on the lab works based on the degree value of membership and truth value. Fuzzy logic will select the measured data with a maximum error percentage of 5% and select the measurement result which has minimum error rate.
Tactical approach to identify and quarantine spurious node participation request in sensory application
Authors: Parande Somu , Mallapur Jayashree D.
Published: March 2020

Securing Wireless Sensor Network (WSN) from variable forms of adversary is still an open end challenge. Review of diversified security apprroaches towards such problems that they are highly symptomatic with respect to resiliency strength against attack. Therefore, the proposed system highlights a novel and effective solution that is capable of identify the spurios request for participating in teh network building process from attacker and in return could deviate the route of attacker to some virtual nodes and links. A simple trust based mechanism is constructed for validating the legitimacy of such request generated from adversary node. The proposed system not only presents a security solution but also assists in enhancing the routing process significantly. The simulated outcome of the study shows that proposed system offers significantly good energy conservation, satisfactory data forwarding performance, reduced processing time in contrast to existing standard security practices.
Design of smart wireless changeover for continuous electric current feeding from power sources of variable capacities
Authors: Alobaidy Haider A. H. , Abdullah Hikmat N. , Salman Tariq M.
Published: March 2020

Electric power has become a vital element for life today. Despite this importance, electric power consumers in Iraq suffer from the problem of noncontinuity and daily electric power supply interruption. This problem led to the use of various sources of electric power as an alternative to compensate for the shortage of electric power provided by the Iraqi national grid. In this work, a smart wireless changeover device is designed using wireless sensor networks technology aiming to solve problem caused by the multiplicity of power sources received at home and governmental buildings in Iraq by controlling operation of some electrical devices (which consume high current) in the home or workplace automatically when changing source of electricity from one to another. This solution will help to ensure the continuity of electric current feeding from power sources of variable capacities, also, to rationalize power consumption by assigning an operation priority to electric devices. Furthermore, a statistical measurement as a case study was performed in a building with a total power consumption of 160.8 KW/h. The result showed that the device functions effectively and it is capable of achieving an average saving in power of about 50% to 86% depending on the applied priorities and case study scenario.
Design of probe for NQR/NMR detection
Authors: Hemnani Preeti , Rajarajan A. K. , Joshi Gopal , Ravindranath S. V. G.
Published: March 2020

Nuclear Magnetic Resonance (NMR) is a RF technique that is able to detect any compound by sensing the excited resonance signals from atomic nuclei having non-zero spin. NQR is similar to NMR but the only difference is NMR needs a DC magnetic field and due to this its application in the field is limited. A FPGA based NQR spectrometer is designed using a single FPGA chip to perform the digital tasks required for NQR spectrometer. Design of Probe for NMR/NQR spectrometer is researched. Parallel tuned and series tuned Probes are discussed and simulated.14N NQR from NaNO2 is observed from spectrometer designed with parallel tuned probe.
Hybrid branch prediction for pipelined MIPS processor
Authors: Al-Khalid Ali S. , Omran Safaa S.
Published: March 2020

In the modern microprocessors that designed with pipeline stages,

the performance of these types of processors will be affected when executing branch instructions, because in this case there will be stalls in the pipeline. In turn this causes in reducing the Cycle Per Instruction (CPI) of the processor. In the case of executing a branch instruction, the processor needs an extra clocks to know if that branch will happen (Taken) or not (Not Taken) and also it requires calculating the new address in the case of the branch is Taken. The prediction that the branch is T / NT is an important stage in enhancing the processor performance. In this research more than one method of branch prediction (hybrid) is used and the designed circuit will choose different types of prediction algoritms depending on the type of the branch. Some of these methods were used are static while the other are dynamic. All circuits were built practically and examined by applying different programs on the designed predictor algorithm to compute the performance of the processor.
The design of IPT system for multiple kitchen appliances using class E LCCL circuit
Authors: Yin N. X. , Saat Shakir , Husin S. H. , Yusop Y. , Awal M. R.
Published: March 2020

Since many years ago, kitchen appliances are powered up by cable connected. This create a troublesome case as wire might tangle together and cause kitchen table messy. Due to this, wireless power technology (WPT) is introduced as its ability is to transmit power to load without physical contact. This leads to cordless solution better in safety as the product can be completely seal, highly expandable power range. This work focuses on the design of WPT based on inductive approach to power up multiple kitchen appliances. The selection of inductive approach over its partners capacitive and acoustic is mainly due to high power efficiency. Class E inverter is proposed here to convert the DC to AC current to drive the inductive link. A 1 MHz operating frequency is used. To ensure the circuit is robust with load variations, an LCCL impedance matching is proposed. This solution is table to maintain the output power if there is a slight change in load impedance. Finally, the developed prototype is able to supply 50V utput which can achieve power transmission up to 81.76%.
Analyzing and evaluating the energy efficiency based on multi-5G small cells with a mm-waves in the next generation cellular networks
Authors: Alsharif Mohammed H. , Yahya Khalid , Chaudhry Shehzad Ashraf
Published: March 2020

This paper evaluates the impact of multi-5G small cell systems on the energy efficiency (EE) in a Fifth Generation (5G) of cellular networks. Both the proposed model and the analysis of the EE in this study take into account (i) the path losses, fading, and shadowing that affect the received signal at the user equipment (UE) within the same cell, and (ii) the interference effects of adjacent cells. In addition, the concepts of new technologies such as large MIMO in millimeter range communication have also been considered. The simulation results show that the interference from adjacent cells can degrade the EE of a multi-cell cellular network. With the high interference the number of bits that will be transferred per joule of energy is 1.29 Mb/J with a 0.25 GHz bandwidth and 16 transmit antennas. While, with a 1 GHz bandwidth the transfer rate increases to 5.17 Mb/J. Whereas, with 64 transmit antennas the EE improved to 5.17 Mb/J with a 0.25 GHz BW and 20.70 Mb/J with a 1 GHz BW. These results provide insight into the impact of the number of antennas in millimeter range communication and the interference from adjacent cells on achieving real gains in the EE of multi-5G small cells cellular network.
Enhancing the CRI and lumen output for the 6600 K WLED with convex-dual-layer remote phosphor geometry by applying red-emitting MGSR3SI2O8:EU2+,MN2+ phosphor
Authors: Bui Thuc Minh , Loan Nguyen Thi Phuong , Le Phan Xuan , Quoc Anh Nguyen Doan , Le Anh Tuan , Tho Le Van
Published: March 2020

The traditional white LED product established with a single chip and a single phosphor results in a low color rendering index (CRI). The upgrade of LED package is comprised of two chips and one phosphor material and gives the higher CRI while keeping high luminous efficiency. Based on previous findings, the research paper performs the application of the two chips and two phosphors to enhance the color tunability of LEDs with different amounts and intensities of the two employed phosphors. Additionally, a color design model is built to serve the purpose of bettering the color fine-tuning of the white-light LED module. The maximum value of the difference between the measured CIE 1931 color coordinates and that of the simulated model is approximately 0.0063 around the 6600 K correlated color temperature (CCT). From the results, this study offers a quick approach to achieve the color fine tuning of a white-light LED module with a high CRI and luminous efficiency.
Speaker specific feature based clustering and its applications in language independent forensic speaker recognition
Authors: Singh Satyanand , Singh Pragya
Published: March 2020

Forensic speaker recognition (FSR) is the process of determining whether the source of a questioned voice recording (trace) is a specific individual (suspected speaker). The role of the forensic expert is to testify by using, if possible, a quantitative measure of this value to the value of the voice evidence. Using this information as an aid in their judgments and decisions are up to the judge and/or the jury. Most existing methods measure inter-utterance similarities directly based on spectrum-based characteristics, the resulting clusters may not be well related to speaker’s, but rather to different acoustic classes. This research addresses this deficiency by projecting language-independent utterances into a reference space equipped to cover the standard voice features underlying the entire utterance set. The resulting projection vectors naturally represent the language-independent voice-like relationships among all the utterances and are therefore more robust against non-speaker interference. Then a clustering approach is proposed based on the peak approximation in order to maximize the similarities between language-independent utterances within all clusters. This method uses a K-medoid, Fuzzy C-means, Gustafson and Kessel and Gath-Geva algorithm to evaluate the cluster to which each utterance should be allocated, overcoming the disadvantage of traditional hierarchical clustering that the ultimate outcome can only hit the optimum recognition efficiency. The recognition efficiency of K-medoid, Fuzzy C-means, Gustafson and Kessel and Gath-Geva clustering algorithms are 95.2%, 97.3%, 98.5% and 99.7% and EER are 3.62%, 2.91 %, 2.82%, and 2.61% respectively. The EER improvement of the Gath-Geva technique based FSRsystem compared with Gustafson and Kessel and Fuzzy C-means is 8.04% and 11.49% respectively
Reversible color video watermarking scheme based on hybrid of integer-to-integer wavelet transform and Arnold transform
Authors: Malallah Fahad Layth , Jafaar Awatif Ali , Abbas Nidaa Hasan , Saeed Mustafa Ghanem
Published: March 2020

Unauthorized redistribution and illegal copying of digital contents are serious issues which have affected numerous types of digital contents such as digital video. One of the methods, which have been suggested to support copyright protection, is to hide digital watermark within the digital video. This paper introduces a new video watermarking system which based on a combination of Arnold transform and integer wavelet transforms (IWT). IWT is employed to decompose the cover video frames whereby Arnold transform is used to scramble the watermark which is a grey scale image. Scrambling the watermark before the concealment makes the transmission more secure by disordering the information. The system performance was benchmarked against related video watermarking schemes, in which the evaluation processes consist of testing against several video operations and attacks. Consequently, the scheme has been demonstrated to be perfectly robust.
ELM and K-nn machine learning in classification of breath sounds signals
Authors: Neili Z. , Fezari M. , Redjati A.
Published: March 2020

The acquisition of Breath sounds (BS) signals from a human respiratory system with an electronic stethoscope, provide and offer prominent information which helps the doctors to diagnosis and classification of pulmonary diseases. Unfortunately, this BS signals with other biological signals have a non-stationary nature according to the variation of the lung volume, and this nature makes it difficult to analyze and classify between several diseases. In this study, we were focused on comparing the ability of the extreme learning machine (ELM) and k-nearest neighbour (K-nn) machine learning algorithms in the classification of adventitious and normal breath sounds. To do so, the empirical mode decomposition (EMD) was used in this work to analyze BS, this method is rarely used in the breath sounds analysis. After the EMD decomposition of the signals into Intrinsic Mode Functions (IMFs), the Hjorth descriptors (Activity) and Permutation Entropy (PE) features were extracted from each IMFs and combined for classification stage. The study has found that the combination of features (activity and PE) yielded an accuracy of 90.71%, 95% using ELM and K-nn respectively in binary classification (normal and abnormal breath sounds), and 83.57%, 86.42% in multiclass classification (five classes).
Measuring information credibility in social media using combination of user profile and message content dimensions
Authors: Setiawan Erwin B. , Widyantoro Dwi H. , Surendro Kridanto
Published: March 2020

Information credibility in social media is becoming the most important part of information sharing in the society. The literatures have shown that there is no labeling information credibility based on user competencies and their posted topics. This study increases the information credibility by adding new 17 features for Twitter and 49 features for Facebook. In the first step, we perform a labeling process based on user competencies and their posted topic to classify the users into two groups, credible and not credible users, regarding their posted topics. These approaches are evaluated over ten thousand samples of real-field data obtained from Twitter and Facebook networks using classification of Naive Bayes (NB), Support Vector Machine (SVM), Logistic Regression (Logit) and J48 algorithm (J48). With the proposed new features, the credibility of information provided in social media is increasing significantly indicated by better accuracy compared to the existing technique for all classifiers.
Text hiding in text using invisible character
Authors: Mustafa Nada Abdul Aziz
Published: March 2020

Steganography can be defined as the art and science of hiding information in the data that could be read by computer. This science cannot recognize stego-cover and the original one whether by eye or by computer when seeing the statistical samples. This paper presents a new method to hide text in text characters. The systematic method uses the structure of invisible character to hide and extract secret texts. The creation of secret message comprises four main stages such using the letter from the original message, selecting the suitable cover text, dividing the cover text into blocks, hiding the secret text using the invisible character and comparing the cover-text and stego-object. This study uses an invisible character (white space) position of in the cover text that used to hide the the secrete sender masseges. The experiments results show that the suggested method presents highly secret due to use the multi-level of complexity to avoid the attackers.