bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of coatings on lifetime of composite dampers
Authors: Horng J H , Shkalei I V , Muravyeva T I , Morozov A V , Yu Tsukanov I , Torskaya E V
Published: January 2020

A comprehensive study of the mechanical and tribological properties of the carbon composite material of coated and uncoated damping spacers was carried out. Indentation techniques, microscopy, friction tests at different scale levels were used in this study. Previously developed models were used to determine the mechanical properties of coatings. It is shown that the presence of the coating has small effect on the friction coefficient, and the wear rate for coated samples is lower than for uncoated ones. It is obtained that under high loads, which may randomly occur at contact, there is a probability of coating delamination. The influence of the coating thickness on the probability of delamination is calculated and analyzed.
Combination effects of fault resistance and remote in feed current on simple impedance based fault location
Authors: Hafizi Bin Idris Muhd
Published: January 2020

There are many types of fault location algorithms and one of it is simple impedance based fault location algorithm which is still widely used by power system utilities around the world mainly because of no communication channel exists between local and remote substations. The aim of this research is to study the combination effects of remote in feed current and fault resistance on the accuracy of simple impedance based fault location algorithm which is used to estimate fault location when the transmission line is connected to equivalent Thevenin sources from both ends. Simulation has been carried out using Matlab Simulink software for single line-to-ground fault and line-to-line fault. For each type of fault, fault location and fault resistance were varied for two conditions which were when remote breaker in open and remote breaker in close conditions. From the results, it can be concluded that remote in feed current will add additional error to the error due to the existence of fault resistance when fault resistance not equal to zero.
A Review: Partial Discharge Detection using UHF sensor on High Voltage Equipment
Authors: Roslizan N D , Rohani M N K H , Wooi C L , Isa M , Ismail B , Rosmi A S , Mustafa W A
Published: January 2020

Partial discharge (PD) is one of the most popular failure or breakdown that can happen at high voltage (HV) equipment. PD is the fault that causes the insulation breakdown occurred between two electrodes. It happened or occurred because of the improper insulation, ageing, environment effect and manufacturing defects. The loss of the power will affect consumer and system operation. One of the technique that can measure or detect the PD is by using ultra high frequency (UHF) method for HV equipment insulation condition monitoring and assessment. In this paper, the application of UHF method have been reviewed as the best method to detect PD in transformer, GIS and cable. The UHF method for every electrical equipment is described in order to detect the PD and the laboratory result shows that this method can be considered as suitable technique. Based on this review, the new design in UHF sensor is required in order to improve the sensitivity and bandwidth for PD detection in HV equipment. The valuable parameter such as size and PD frequency range can be used for early stage of designing new the UHF sensor.
Investigation the optimum performance of the surface-mounted PMSM under different magnetization patterns
Authors: Akmar Mohd-Shafri Syauqina , Leong Tiang Tow , Ishak Dahaman , Hwai Leong Jenn , Jun Tan Choo , Lin Ong Hui
Published: January 2020

This paper investigates the influence of different magnetization patterns on the performances of the surface-mounted permanent magnet synchronous machines (SMPMSMs). Three magnetization patterns are employed, which are radial, parallel, and ideal Halbach magnetizations. These magnetization patterns are applied to 9-slot/10-pole and 15-slot/4-pole permanent magnet (PM) machines. The PM machines are designed and simulated by using Opera 2D finite element. The performances of three PM motors, such as airgap flux density, phase back-EMF, and cogging torque, are evaluated under the influence of different magnetization patterns. The total harmonic distortion of phase back-EMF (THDv) for the motors are investigated. The PM motors with ideal Halbach magnetization provide the lowest cogging torque and the lowest total harmonic distortion of phase back-EMF. Besides that, the optimum setting of the magnet pole-arc can reduce the total harmonic distortion of phase back-EMF and achieve lower cogging torque. The optimum magnet pole-arc produced by radial magnetization in 9-slot/10-pole motor is 24.8° mech., with cogging torque of 0.45 Nm, and THDv of 2.69 %. Meanwhile, the optimum magnet pole-arc produced by parallel magnetization in 9-slot/10-pole motor is 26.0° mech., with cogging torque of 0.41 Nm, and THDv of 2.00 %.
Fault detection and classification in three phase series compensated transmission line using ANN
Authors: Rosle N , Fadzail N F , Halim M I A , Rohani M N K H , Fahmi M I , Leow W Z , Bakar N N A
Published: January 2020

Series compensation consists of capacitors in series is used in the transmission lines as a tool to improve the performance after disturbed by a fault. Transmission line needs a protection scheme to protect the lines from faults due to natural disturbances, short circuit and open circuit faults. The fault can happen in any location of transmission line and it is important to know which location has been affected. So that, the fault can be eliminated and can maintain the optimum performance. Therefore, in this paper Artificial Neural Network (ANN) is used to detect and classified the fault happen in single line to ground fault and three phase to ground fault. Two different tests of each types of fault have been tested in order to prove the effectiveness of ANN to detect the fault location by using different length and fault resistance. The simulation has been accomplished in MATLAB with ANN fitting tool which build and train the network before evaluated its performance using regression analysis. The analysis shows that the ANN can accurately detect the different types of faults and classified it into the respective category even the random vectors are put on the system are used.
Development of fault distance locator for underground cable detection
Authors: Md Arifin FH , Hasan MZ , Mahyudin ISA , Arshad SNM
Published: January 2020

This project proposes fault distance locator model for underground power cable using an Arduino uno. The use of underground cables arise a problem of identifying the fault location and the distance of cable fault as it is not open to view as in case of overhead cable. Thus, the underground cable fault distance locator is develop to detect the exact fault location and the distance of underground cable fault from based station in kilometers as the system will detect the faulted cable on underground and will send the information to the control room by using a relay. An underground cable system is a common practice followed in major urban area. The concepts of Ohm’s law are used in this project and are placed underground with short circuit type fault condition. If any fault occurs, the voltage drop will vary depending on the length of fault in cable since the current varies. Tracer method is used to detect faulted by walk through the cable lines. Fault point is traced by the audible signal or electromagnetic signal. These projects are equipped with a set of resistors, power supply, a set of switches, Arduino Uno and LCD. The prototype of an underground cable fault distance locator is designed with the performance of Tracer method.
The effect of semi-conductive and non-conductive nano particles in sunflower oil based insulation
Authors: Hussin Nuriziani , Kwong Yeaw Lim , Nabil Mohd Khalil Ahmad , Kamarol Mohd Jamil Mohamad , Nayan NorkharzianaMohd , Nizam Md Arshad Syahrun , Ainanie Azizie Nurin
Published: January 2020

Following the improvement of technology, more and more alternatives are introduced to improve the insulation material and one of them is the nanotechnology. Research had been done which confirm the enhancement of the transformer oil upon adding nanoparticles in term of dielectric strength, viscosity, relative permittivity and others. In this research, semi-conductive (ZnO) and non-conductive (ZrO2) nanoparticles with weigh to volume ratio of 0.05g/l are added to the sunflower oil based insulation and the effects are observed. The relative permittivity of added ZnO is higher compare to ZrO2 in mineral oil. The situation is opposite as ZrO2 yield higher permittivity with sunflower oil. In term of breakdown voltage, the addition of ZnO shows a better dielectric strength compare to ZrO2. The kinematic viscosity is also increase when both nanoparticles are added in which ZnO contributes a higher value.
Control of a multi-functional grid-connected solar PV system using instantaneous reactive power (PQ) theory for current harmonic alleviations
Authors: Baharudin N H , Mansur T M N T , Ali R , Azahid W N A , Ananda-Rao K , Irwanto M , Abdullah A M , Suboh S M
Published: January 2020

In recent years, the advance usages of non-linear loads have led to the serious power quality problem in the distribution system. Non-linear load will inject the current harmonics and cause power quality problem at Point of Common Coupling (PCC). This problem can be improved by using power filter. Power filter can be divided into passive power filter and active power filter. Passive filter is an appropriate solution to solve power quality problem in term of harmonic mitigation due to a simple circuit, low cost and less energy requirement. However, active power filter (APF) is more suitable due to better performance to solve power quality problem for current harmonics issue. This paper focuses in designing the application of a multi-functional grid-connected solar PV system integrated with DSTATCOM by using Instantaneous Reactive Power (PQ) theory controller to mitigate the current harmonics injected by non-linear load at the distribution system. MATLAB/SIMULINK software is used to simulate the performance of the multi-functional GCPV based SAPF according to IEEE Standard 519:2014 which THD of the line current at the Pont of Common Coupling (PCC) should be less than 8%.
Preparation of vegetable oil-based nanofluid and studies on its insulating property: A review
Authors: Ainanie Azizie Nurin , Hussin Nuriziani
Published: January 2020

The application of vegetable oil as an insulating fluid is gaining a lot of interest from researchers all over the world because of the fact that it is a renewable source and is easily available. This paper reviews and compares the preparation methods of vegetable oil-based nanofluids that have been used by many different authors. The experimental results obtained by previous researchers on the insulating properties of the vegetable oil-based nanofluids are also analysed and discussed in detail. In addition, future improvements for experimental works with insulating nanofluids are also proposed.
Analysis behavior of soil resistivity profiling base on UniMAP condition
Authors: Arshad S N M , Wahib A H , Halim N H , Yousof M F M , Ariffen A M , Wooi C L , Abd Rahman M S
Published: January 2020

The main purpose of the earthing is to ensure that every electrical equipment, house and human are safe when lightning strikes. Lightning phenomenon occur scan produced high voltage and current ant it can caused electrical equipment damage and life danger. Therefore, this project will analyze the behavior of the soil. The main purpose of this project was to select the soil structure and the depth of the electrode suitable for grounding system in UniMAP. Additionally, this project will also analyze the soil resistance for grounding systems using MATLAB Software. From the result it can shows the best point for located grounding rod to ensure optimum grounding system.
A Dragonfly Algorithm Application: Optimizing Solar Cell Single Diode Model Parameters
Authors: Mat Isa Zainuddin , Mohd Nayan Norkharziana , Ashbahani Mohamad Kajaan Nor , Hafiz Arshad Mohd
Published: January 2020

This paper provides an overview of optimizing solar cell single diode parameters using Dragonfly Algorithm. The 57 mm diameter commercial (R.T.C. France) silicon solar cell measurement data are taking as the data source for the optimization process. The results produced are compared with NM-PSO and IJAYA algorithms to observe the efficiency, accuracy and reliability of the proposed approach
I-V performance analysis of flexible back Illuminated Dye Sensitized Solar cells (DSSCS) with various platinum catalyst contents
Authors: Shamsudin N H , Shafie S , Ab. Kadir M Z A , Ahmad F , Chachuli S A M , Sulaiman Y
Published: January 2020

Flexible based Dye Sensitized Solar Cells (DSSCs) in nanotechnology revolution have always been in the thick of things where fabrication method and achieving good performances are concerned. Such concerns were adjudicated by improvising four(4) innate DSSCs structures composed of photoanode, semiconductor, electrolyte and counter electrode. This paper aims to observe the impact of changing Platinum(Pt) volumes on the counter electrodes of DSSCs by conducting tests on 0.2mm Titanium (Ti) foil based photoanode DSSCs. The deposition of Pt was varied into 70µl, 50µl and 30µl accordingly by spin coating technique at 1500 rpm. All samples were synthesized, deposited with Pt and assembled before being tested under solar light simulator of 1000W/cm2. Samples with 70µl Pt deposition indicated a higher efficiency (Ƞ) of 2.83%, even though it allowed less light penetration, while the 30µl Pt deposition sample provided efficiency (Ƞ) of 0.88% with more light penetration.
Comprehensive performance analysis of model predictive current control based on-grid photovoltaic inverters
Authors: Podder A K , Tariquzzaman M , Habibullah M
Published: January 2020

A considerable amount of energy is lost by utilizing the traditional pulse width modulation (PWM) based inverters in an on-grid PV system. Therefore, a model predictive current control (MPCC) based control strategy is proposed in this research work. The controller works based on a predefined cost function. The cost function includes deviation of current from its reference and a switching frequency term to reduce the average switching frequency. All the possible control actions i.e. inverter switching states are tested against the cost function. The state which yields minimum cost is selected as an optimal control action for the inverter. Simulation results show that the proposed controller tracks the reference current accurately with a mean absolute error of 2.5% which is 30% for the PI-PWM based controller. The MPCC based inverter yields low current THD of 2.07%, whereas in traditional PI-PWM based inverter the current THD is 7.26%. The energy efficient operation of the MPCC based inverter is also verified by doing loss analysis. It is shown that conduction, switching, and harmonic losses of the inverter are reduced by 36.8%, 50%, and 91.9%, respectively, in comparison with the PIP-WM based inverter.
Effect of different types of blades on miniature wind turbine energy harvesting output
Authors: Umar Muhammad , Jame Nursabirah , Mohd Nayan Norkharziana
Published: January 2020

This paper presents a simulation and experimental setup for miniature wind turbine energy harvesting using different types of material and blades. Three different cut in wind as low as 3.34 m/s, 4.00 m/s and 5.12 m/s were used to evaluate the miniature wind turbine. MATLAB software is used to design and run the simulation of the system. The result shows that type A PVC blades with the radius of 0.035 m provides the highest output with 19.41 V during cut in wind of 5.12 m/s.
Design of MPPT charge controller using zeta converter for battery integrated with solar Photovoltaic (PV) system
Authors: Ananda-Rao Kumuthawathe , Matar Yazan , Hanisah Baharudin Nor , Alif Ismail Mohd , Muiez Abdullah Abdul
Published: January 2020

In this work, the advantage of using Maximum Power Point Tracking (MPPT) algorithm in solar Photovoltaic (PV) system was investigated. By simulation, the performance and efficiency of the system with and without the tracking algorithm was analyzed. By using MATLAB’s SimPower System block set, a model compromised of KC130TM solar panel powering a Zeta converter controlled by MPPT algorithm driving a lead acid battery as a load was designed. The main objective was to track the Maximum Power Point (MPP) of the solar PV module by modulating the zeta converter’s duty cycle, thereby, optimizing the power output of the panel. The Perturb and Observe (P&O) algorithm preformed with higher overall efficiency compared with the system without MPPT. Additionally, the tracking algorithm was able to track the MPP quickly. The analysis of the algorithm led to a greater understanding of where the inefficiencies of this type of system are located, allowing improvement in future work on this field.
Proposing an integrated multi-criteria decision making approach to evaluate total quality management best practices in Malaysia hotel industry
Authors: Sin K Y , Jusoh M S , Mardani A
Published: January 2020

Although numerous studies have focused on significant role of total quality management (TQM) in literature, little attention has been paid to using the multi-criteria decision making (MCDM) approach for analysis of TQM practices especially in the context of hospitality. The purpose of this study is to identify, prioritize and evaluate the TQM best practices in hotel industry by integrating the DEMATEL and ANP approaches. DEMATEL is employed to determine the interrelationships among the main practices and sub-practices while ANP is employed to examine the weights of main practices and sub-practices. The results of this study indicated that employee management had the first rank among other practices whereas the second and third rank encompass customer relationship management and leadership respectively. The findings of this study has shown guidance to practitioners to implement proper TQM in their organizations, effectively by using the suggested set of identified TQM best practices.
Design of a hybrid free space optical and visible light communication system for indoor wireless data broadcasting
Authors: Lee I E , Chung G C , Pang W L , Anas S S , Cheong M Y
Published: January 2020

The continuous development of online social services and the ever-increasing number of devices demanding high-speed and ubiquitous broadband wireless access have resulted in severe bandwidth congestion, such that the radio frequency (RF) spectrum will no longer be able to support the exponential growth in demand. Along with being faster, cheaper, greener, cleaner, and safer than current technology, visible light communication (VLC) can overcome the bottleneck issues with last-mile connectivity by offering 10, 000 times broader bandwidth. In this paper, we propose a system with portable, low-cost hybrid RF/VLC and free-space optics (FSO) transceivers with a simple graphical user interface and the capability of indoor wireless communication and multimedia broadcasting, thus presenting an economical and cable-free solution to various multimedia applications, such as file transmission and real-time audio and video streaming. The proposed system deploys VLC as a hotspot for data broadcasting within an enclosed room, FSO as the backbone for data transmission between multiple rooms, and Wi-Fi for lights-off mode. Preliminary results show a transmission rate of 1kbps at a maximum distance of 4 cm.
Analysis of flexible antenna performance on partial discharges detection
Authors: Affendi N A M , Amirruddin M , Ahmad S
Published: January 2020

This paper reports a short finding on the use of a flexible substrate in the design of Partial discharge (PD) detection antenna. This flexible antenna was designed and simulated using CST Microwave Studio to detect corona discharge which is one types of PD that occur in power transformers. The flexible substrate that been used in designing the antenna is paper that has permittivity of 3.2 and the chosen frequency is between 300MHz until 3GHz. The overall dimension is 208×168×1.6 mm3. The simulations of the antenna’s return loss were conducted under two conditions; 1) flat and 2) bending along H- planes. The result were been analysed to understand the performance of paper properties, so that practical system requirements are met. This implies that the performance of paper antennas can be used in the PD field with altering some of the characteristic to upgrade its performance.
Fault detection for PEM fuel cell using kalman filter
Authors: Ramamoorthy D , Che Mid E
Published: January 2020

Fault detection plays a key role in high cost and safe-critical systems to avoid the occurrence of an abnormal event. This work presents a model-based fault detection in the water management system of proton-exchange membrane (PEM) fuel cell stack using Kalman filter (KF). The KF is a model-based FD method relies on analytical redundancy to predict the related fault disturbed by some noise. Then, it corrected the faults with its mathematical model to minimize the error covariance between the normal and faulty scenarios by a repetitive process. Two faulty scenarios; flooding and drying which happen at anode and cathode side of PEM fuel cell are investigated. The proposed FD method using KF has successfully detected flooding and drying faults in PEMFC.
Triple-band antenna with defected ground structure (DGS) for WLAN/WiMAX applications
Authors: Ibrahim Amirudin , Arina Fazil Nur , Dewan Raimi
Published: January 2020

This paper presents a triple-band rectangular patch antenna that can be operated in three different resonance frequencies of 2.40 GHz, 3.50 GHz, and 5.80 GHz for WLAN and WiMAX applications. The FR-4 substrate with dielectric constant of 4.3 is used, with the dimensions of the substrate 34×30×1.6mm3. The performance of the rectangular patch antenna has been simulated and measured and the proposed patch antenna operates at three different resonance frequencies of WLAN and WiMAX which are 2.35-2.54 GHz, 3.45-3.57 GHz and 5.74-5.83 GHz. These results correspond to a simulated bandwidth of 197 MHz, 118 MHz and 90 MHz. The radiation pattern of nearly omni-directional is obtained. Overall, the results obtained show the designed antenna have a good performances of the three operating bands
Big Data and Automatic Detection of Topics: Social Network Texts
Authors: Silva Jesús , Hernández Palma Hugo , Niebles Núñez William , Ruiz-Lazaro Alex , Varela Noel
Published: January 2020

This paper proposes the analysis of the influence of terms that express feelings in the automatic detection of topics in social networks. This proposal uses an ontology-based methodology which incorporates the ability to identify and eliminate those terms that present a sentimental orientation in social network texts, which can negatively influence the detection of topics. To this end, two resources were used to analyze feelings in order to detect these terms. The proposed system was evaluated with real data sets from the Twitter and Facebook social networks in English and Spanish respectively, demonstrating in both cases the influence of sentimentally oriented terms in the detection of topics in social network texts.
Using Big Data to Determine Potential Dropouts in Higher Education
Authors: Viloria Amelec , Senior Naveda Alexa , Hernández Palma Hugo , Niebles Núñez William , Niebles Núñez Leonardo
Published: January 2020

In higher education, student dropout is a relevant problem, not just in Latin America but also in developed countries. Although there is no consensus to measure the education quality, one of the important indicators of university success is the time to graduation (TTG), which is directly related to student dropout [1]. Global estimates put this dropout rate at 42% [2]. In the United States, this rate is around 30% and represents a loss of 9 billion dollars in the education of these students [3]. However, desertion not only affects the quality of education and the economy of a country, but also has effects on the development of society, since society demands the contributions derived from the population with higher education such as: innovation, knowledge production and scientific discovery [4]. Using basic statistical learning techniques, this paper presents a simple way to predict possible dropouts based on their demographic and academic characteristics.
Implementation of Micro CT in CAD/CAM dentistry for image processing and soft computing: a review
Authors: Yajvinder  , Gulati V
Published: January 2020

All This review discusses the merits and area of improvement of various radiology aids employed in current dentistry and also refers to scope in CAD/CAM dentistry. However, present radiology devices are playing an important role in clinical dentistry but their area of application is limited due to harmful effects of x-ray exposure to human and high operating cost. Radiology device like Micro CT (μ-CT) is powerful tool to assess the dental prosthesis fabricated using CAD/CAM but radiology devices can also be used in whole process of dental prosthesis manufacturing using CAD/CAM. This study retrieves the interaction of advanced radiology devices in current CAD/CAM dentistry and also highlights the correlation of Micro CT’s input variables and acquired image resolutions using available data in reviewed studies.
An efficient high speed squaring and multiplier architecture using yavadunam sutra and bit reduction technique
Authors: Deepa A , Marimuthu C N , Murugesan C
Published: January 2020

Vedic Mathematics, an ancient Indian technique can be used to solve any arithmetic problems in an easy and simple way. A novel high speed Vedic squaring and multiplier unit is designed using the principles of Yavadunam sutra and the bit reduction technique is projected in this paper. The complexity of the multiplier is reduced as the bit reduction technique is employed and later the Yavadunam sutra is implemented for the calculation of the deficiency. The size of the proposed N bit multiplier is reduced to N-1 bit and also considerable speed improvement is achieved. The architecture is designed and realized using Xilinx Spartan FPGA and synthesized using 90nm and 180nm technology synopsys device.
SPPBPS: A Secure Privacy-Preservation Bilinear Pairing Scheme for Bitcoin Cryptocurrency
Authors: Kofi Kwansah Ansah Albert , Lu Li , Adu-Gyamfi Daniel , Anokye Stephen , Tang Chenfeng
Published: January 2020

Despite the existing advances on research and education in cybersecurity and its applications, the field is still under discovery and new technologies are evolving. In recent years, Bitcoin as a cryptocurrency cyber application that records all financial transactions present on a blockchain where users can reach a secure and robust consensus on transactions emerges as the most popular peer-to-peer electronic payment system. Cryptocurrencies mostly rely on blockchain, as a secure decentralised append-only ledger to exchange digital currencies, and thereby attracting a billion-dollar economy. Bitcoin allows input transactions to link addresses and this can be used by an adversary to reveal real user identity. This obviously attracts privacy issues such as user’s information and identity leakage. Several existing techniques are found not satisfactory to fulfil practical and compatible anonymity requirements for users and their transaction. We present in this paper, a secure privacy-preservation scheme based on bilinear pairing and other cryptographic primitives. We proved that our proposed scheme is robust and can be implemented to preserve users and transaction privacy in the Bitcoin system by theoretical analysis and evaluation.
Data Mining Applied in School Dropout Prediction
Authors: Viloria Amelec , García Guliany Jesús , Niebles Núñez William , Hernández Palma Hugo , Niebles Núñez Leonardo
Published: January 2020

In recent years, many studies have emerged about regarding the topic of school failure, showing a growing interest in determining the multiple factors that may influence it [1]. Most of the researches that attempt to solve this issue [2] are focused on determining the factors that most affect the performance of students (dropout and failure) at the different educational levels (basic, middle and higher education) through the use of the large amount of information that current computer equipment allows to store in databases. All these data constitute a real gold mine of valuable information about students. But, identifying and finding useful and hidden information in large databases is a difficult task [3]. A very promising solution to achieve this goal is the use of knowledge mining techniques or data mining in education, which has resulted in so-called Educational Data Mining (EDM) [4]. This new area of research is concerned with the development of methods for exploring data in education, as well as the use of these methods to better understand students and the contexts where they learn [5].
Parallel Algorithm for Reduction of Data Processing Time in Big Data
Authors: Silva Jesús , Hernández Palma Hugo , Niebles Núñez William , Ovallos-Gazabon David , Varela Noel
Published: January 2020

Technological advances have allowed to collect and store large volumes of data over the years. Besides, it is significant that today’s applications have high performance and can analyze these large datasets effectively. Today, it remains a challenge for data mining to make its algorithms and applications equally efficient in the need of increasing data size and dimensionality [1]. To achieve this goal, many applications rely on parallelism, because it is an area that allows the reduction of cost depending on the execution time of the algorithms because it takes advantage of the characteristics of current computer architectures to run several processes concurrently [2]. This paper proposes a parallel version of the FuzzyPred algorithm based on the amount of data that can be processed within each of the processing threads, synchronously and independently.
Single and Double-Threaded Offloading Strategies and Computational Analysis in Mobile Cloud Computing
Authors: Xia Siyu , Jiu Mingyuan , Fan Chenglong
Published: January 2020

At present, mobile devices are hard to support the increasing number of intensive applications due to their limited power and fixed storage size, therefore, how to improve the computing power and also reduce the energy consumption is a crucial problem in the development of mobile terminals. In order to solve this problem, a new offloading scheme is proposed based on the combination of double-thread computing scheme and offloading strategy in this paper. First, we combine single and double-threaded computing with mobile cloud computing and obtain the optimal offloading strategy through component partitioning and the single-threaded application theorem. Then the energy consumption is analyzed on the basis of double-thread calculation. Finally, we compare the performance of single-thread and double-thread offloading strategy in terms of energy consumption and delay of mobile cloud computing. The results show that the double-thread offloading strategy has the least energy consumption and has better characteristics.
Estimating Median in The Multi-sourced Heterogeneous Data Set: A distributed implementation
Authors: Gao Tian , Zhao Yanyu , Deng Xinyi , Li Wenze , Li Hongjun , Zhao Xin
Published: January 2020

The continuous running of enterprise applications produces a huge volume of business data that reside in different storage and system environments and owned by different companies or organizations, which forms a typical distributed, multi-sourced heterogeneous dataset. The multi-sourced heterogeneous data set provides big potential values for official statistics. While the median is a commonly used indicator in official statistics, it is not a trivial task to estimate the median in the distributed computing environment of multi-sourced heterogeneous data set due to its mathematical nature. In this paper, we proposed a distributed method to estimate the median value for the multi-sourced heterogeneous data set. Mainly considering the different size of multi-sourced data set and unevenly distribution of their data values, we first improve the traditional interpolation based median estimation method for the multi-sourced heterogeneous data set. Then, we propose distributed implementation for the proposed median estimation method based on web service technology. Finally, we evaluate the accuracy and performance of proposed method through experimental study.

CCS Concepts

Information systems ➝ Data management systems ➝ Information integration ➝ Mediators and data integration
A New Adaptive Differential Evolution Algorithms
Authors: Tian Yu , Li Tinghui
Published: January 2020

In this paper, we describe a New Adaptive Differential Evolution algorithm (NADE) based on adaptive mutation operator, crossover operator and new mutation strategy. It is mainly aimed at the existence of individual aggregation and the reduction of population diversity in the calculation process of Differential Evolution algorithm (DE), which makes the algorithm easy to get early. The problems of ripeness, slow convergence speed and low convergence accuracy are improved. The improved differential evolution algorithm is tested by five commonly used test functions, and the test results are compared with the other three algorithms. The results show that the proposed algorithm performs better in convergence speed, convergence precision and global convergence ability.
Research on Network Attack Effect Evaluation Based on Confrontational Perspective
Authors: li Jingxuan , Qiu Han , Zhu Junhu
Published: January 2020

The cyberspace battlefield is full of strategic confrontations between attack and defense sides. However, the existing evaluation methods do not consider the impact of defense strategies on attack effect, and only carry out unilateral attack effect evaluation from the perspective of attacker, which cannot reflect the dynamic changes of attack effect against different defense strategies. To solve this problem, we propose the Confrontation Oriented Attack Effect Evaluation Model (CO-AEEM) to evaluate the attack effect from the perspective of both attack and defense sides. By creating CO-AEEM, we establish a multi-level evaluation index system covering all-assests-elements of the target object, and propose an attack effect evaluation algorithm to reduce the impact of subjective factors and adapt to the complex characteristics of network confrontation, then design the comparison and evaluation process of attack test and confrontation test according to the changes of defense measures. Finally, the simulation experiments in various confrontation scenarios are carried out in network range, which show that the model can not only describe the actual attack effect in confrontation with different defense strategies, but also the effectiveness degree of defense strategies against various types of attacks. Thus, the evaluation results of CO-AEEM can provide scientific guidance of action decision making and equipment development in network counterwork.

CCS Concepts

•Security and privacy➝Formal methods and theory of security •Computing methodologies➝Modeling and simulation.
Real-time Online Prediction of Data Driven Bearing Residual Life
Authors: Wang Haiya , Yu Zhongqing , Guo Lu
Published: January 2020

In order to realize the predictive maintenance of key components under massive vibration data, real-time online prediction of the remaining life of different types of bearings, a data driven real-time online prediction method for bearing residual life is introduced. The method realizes the construction of the data-driven bearing residual life prediction model by selecting the bearing vibration data Spearman characteristic parameter selection, principal component analysis (PCA), health index fusion, and BP neural network fitting. The built model is continuously updated by real-time online acquisition of data to achieve real-time online prediction of bearing residual life. The accuracy and feasibility of the method for predicting the remaining life of different types of bearings are verified by experiments. Using this method to predict the remaining life of the bearing helps to achieve predictive maintenance of critical components, reduce unplanned downtime, increase production efficiency, and reduce production costs.
The Influence Analysis of Time Synchronization Error on Direct Source Position Algorithm
Authors: Zhao Yu , Xiao Ling , Si Chang Zhe , Liu Jianfeng
Published: January 2020

It is very difficult to eliminate the time synchronization error completely. The influence of time synchronization error on direct source position algorithm was researched. The signal model with time synchronization error was given firstly. Then the CRLB of position estimation under the condition that the time synchronization error is exist was derived. In the last, the influence was analyzed by Monte Carlo simulations. The simulation results show that the Cramer-Rao lower bound, under the condition the time synchronization error is exist, is deteriorated obviously compared with the condition the time is synchronized perfectly; when the time synchronization error is shorter than the signal sample period, the CRLBs are same with different time synchronization errors; however the position accuracy of direct source position algorithm drops sharply, if the time synchronization error is not being considered.
Research on Calibration of Short Base Metal Thermocouples
Authors: Zhe Wang , Songlin Yu , Xinming Zhao , Qiangguang Li , Wenjie Shen
Published: January 2020

Short and cheap metal thermocouple is a general term for detachable short base metal thermocouple (electrode length is about 300mm-500mm) and short base metal armored couple (metal sleeve length is about 300mm-500mm). Their electrodes are short in length. Traditional measuring equipment often fails to accurately measure the indication deviation in the high temperature region (above 300 °C). Through experiments, this paper finds out the reasons of inaccurate measurement. Then, this paper designs a thermostat at the terminal, which can solve this problem. The design can effectively reduce the extended uncertainty of short-form even value deviation.
Application of GBDT for division of petroleum reservoirs
Authors: Qin Yaqiong , Ye Zhaohui , Zhang Conghui
Published: January 2020

Traditional methods of dividing petroleum reservoirs are inefficient. The machine learning method has been applied in the two-class and three-class tasks of the reservoir, but there is no research on the classification of all classes. In this paper, the GBDT (Gradient Boosting Decision Tree) model is proposed for the reservoir classification problem in argillaceous sandstone areas, and the model is implemented by XGBoost algorithm. The classification effect of this model is better than that of multiple-hidden-layer neural networks, and the macro-average AUC is 0.89.
Short-term Prediction of the CSI 300 Based on the BP Neural Network Model
Authors: Ning Shunyu
Published: January 2020

In this paper, BP neural network is adopted to predict the Shanghai-Shenzhen 300 Index (CSI 300) during a short period of 60 days (beginning from March 7th, 2018), results of which are used to determine the prediction effect of the BP neural network model on CSI (China Securities Index) 300. In addition, the present study explores the prediction effect of the BP neural network during different time periods by grouping predicted results according to the length of time. It is found that the BP neural network model performs well in predicting the CSI 300. The prediction results reveal that the price would overall decline, the fluctuation frequency would be small, and the price fluctuations would be small. Comparison between the groups during different time periods shows that prediction during a time period of less than 20 days or more than 50 days incurs larger errors, the prediction during a time period of 30 to 40 days is more accurate, and predictions errors increase sharply during the time period of more than 50 days.
Research on Customer Satisfaction Measurement of Online Tourism Platform Based on Value Chain- Take Company X for example
Authors: Wang Ying , Liu Xi
Published: January 2020

With the vigorous development of the economy and Internet, improving customer satisfaction has become an important issue faced by online tourism platform providers. How to scientifically evaluate customer satisfaction is the key factor to accurately define the impact of customer satisfaction, and also the premise and basis to effectively improve customer satisfaction. This paper decomposes the value chain of Online Travel Agency (OTA) and constructs OTA customer satisfaction model from the perspective of OTA value chain activities. According to the characteristics of OTA value chain flow; this paper puts forward OTA customer satisfaction measurement scale, and takes Company X as an example to make an empirical analysis. Entropy weight method calculates the weight of all levels of indicators. Fuzzy comprehensive evaluation method is used to determine the level of customer satisfaction of all levels of indicators. Through the analysis of empirical results, countermeasures and suggestions are put forward to improve the overall service quality of OTA and customer satisfaction, which can provide reference for the service quality of online tourism industry in China.
Business Value of Telecom Operators’ Big Data
Authors: Hong Ying , Li Zheng , Wang Jun
Published: January 2020

Big data is one of the infrequent resources in the 21st century, especially for Internet & Mobile Internet industries. Telecom operators have large amount of precious data. Through analysis of the features of telecom operators’ data, this study highlights the value of telecom big data in business and classifies it into two major categories. The first one is enhancing existing business to optimize traditional telecom services, like customer experience, telecom product design and network management. The other is developing derivative business such as advertisement, marketing, financial or credit services based on the strength of telecom big data. This preliminary research provides insights into the value development of telecom operators’ data on account of targeted discussion about practical application for telecom big data.
Sampling Statistics Research Based on Quality Evaluation of Electricity Meters from Different Manufacturers
Authors: Gu Zhen , Zhao Fang , Chen Jintao , Jiang Jianfeng
Published: January 2020

It is of great significance to study and analyze the measurement performance and sampling inspection methods of smart meters, and to conduct sampling inspection according to the quality status of smart meters, so as to improve the reliability of smart meters. On the basis of qualified rate test and error test of electric energy meters, radar chart and Wilcoxon rank sum test method are adopted to carry out quality inspection comparison of electric energy meters of the same specification from different manufacturers, and sampling statistical test method is studied accordingly. The method described in this paper is suitable for quality analysis and sampling inspection of electric energy meters.
Identification of maize disease based on transfer learning
Authors: Sun Xiaolin , Wei Jiangshu
Published: January 2020

To reduce the time and energy needed by agricultural experts to evaluate maize diseases and improve the accuracy of image recognition of maize diseases, considering that the maize disease dataset is a small sample dataset, a method of image recognition of maize disease based on transfer learning is proposed, which is to fine tune the pre-trained convolutional neural network model. This paper compares and analyzes the experimental results of training only the last layer of Inception-v3 / Inception-v4 model and training all parameters of Inception-v3 / Inception-v4 model, and compares the results with the initial training VGG16, AlexNet and other models. The experimental results show that the method of transfer learning can reduce the training time of network, and the trained deep convolutional neural network can recognize maize diseases.
Cluster Discriminant Prediction of Oil Well Production Based on Mahalanobis Distance
Authors: Huang Bo , Kang Yunwei , Chen Ang , Guo Zixi , Sun Yicheng
Published: January 2020

The cost of oil field drilling engineering is very high. Effective well selection and formation selection will avoid waste of energy and resources. Aiming at the problem of well selection and reservoir selection in oilfield, this paper presents a clustering discriminant prediction method for oil well production based on Mahalanobis distance. Based on the field data of Xinjiang oilfield, the main control factors with greater influence are selected after data pretreatment in this paper. Then we randomly divide the data into training data set and prediction data set, and establish a discriminant model of oil well classification based on Mahalanobis distance. Finally, the model is used to predict the production of oil wells in the forecasting data set, and the prediction accuracy reaches 87.5%.
Research on Collaborative Filtering Recommendation Algorithm Based on Mahout and User Model
Authors: Song Bo , Gao Yue , Li Xiao-Mei
Published: January 2020

Based on the research status of recommendation system, the traditional collaborative filtering algorithm is explored. By establishing the concept of training sample and Mahout framework, a collaborative filtering algorithm based on Mahout and extracted user model can be proposed. Using this algorithm in the system of recommendation aims to solve the problem of transforming the traditional recommendation problem into the classification problem in machine learning. In this way, it can provide personalized recommendations for users. The analysis of the experimental results of the collected some data sets suggests that the algorithm based on user model and machine learning is effective and optimal, at the same time, the efficiency of the algorithm under Mahout framework is also verified.
Method Research and Realization of Noise FM Jamming Based on DDS Technology
Authors: Chuyang Zeng , Shang Gao , Jianyi Xiao , Jianwen Huang , minnuo He , Qiang Lin , Kaitong Huang , Jutao Huang , Ruiwen Ma
Published: January 2020

Noise FM jamming which has wide jamming band and large noise power is widely used in processing backup jamming to radar, fuze and communication. The paper adopt DDS combines with characteristic of FPGA chip to generate noise FM jamming. The method has large improvement in precision, structure and speed, and has broad application and prospect.
Stealthy Malware Detection Based on Deep Neural Network
Authors: Lu Shoupu , Li Qingbao , Zhu Xinbing
Published: January 2020

Network attacks using advanced local hiding technology have not only increased, but also become a serious threat. However, attacks using these technologies can not be detected through traffic detection, and some attacks imitate benign traffic to avoid detection. To solve these problems, a malware process detection method based on process behavior in possibly infected terminals is proposed. In this method, a deep neural network is introduced to classify malware processes. Firstly, the recurrent neural network is trained to extract the characteristics of process behavior. Secondly, training convolutional neural network is used to classify feature images generated by trained RNN features. The experiments results show that this method can effectively extract the features of malicious processes, and the AUC of ROC curve is 0.97 in the best case.