bluuebunny/crossref_metadata_2025 huggingface dataset:
On stability of time marching in numerical solutions of rayleigh-plesset equation for ultrasonic cavitation
Authors: Tey Wah Yen , Alehossein Habib , Qin Zonyi , Lee Kiat Moon , Kang Hooi Siang , Lee Kee Quen
Published: April 2020

Ultrasonic irradiation approach has become one of the most popular methods applied in chemical processing including lignocellulosic biomass pretreatment and industrial cleansing. The phenomenon of ultrasonic cavitation can be indeed delineated via the Rayleigh-Plesset equation (RPE), which governs the transient radius of the bubble. Nonetheless, the time marching in the numerical solutions for RPE is highly unstable, which cannot be assured using von Neumann analysis. High sensitivity of RPE to time step may lead to extremely long computational time. The lack of numerical investigation into the time stepping issue of RPE has hindered in-depth simulation of ultrasonic cavitation. Therefore, the purpose of this paper is to investigate the stability criterion of time stepping for RPE in different time progression schemes, namely Euler explicit, 2nd order Taylor’s method, 4th order Runge-Kutta, Runge-Kutta Fehlberg and Cash-Karp Runge-Kutta method. A simple modified adaptive time step method and α independence study has been introduced in this paper for fast, stable and accurate computation of RPE. Compared with the traditional constant time marching method, the new model is able to improve the computational cost significantly without affecting the time marching stability and resolution of the results. Among the investigated method, Runge-Kutta family solvers have higher computational accuracy, with the cost of higher critical α value. The model is also applied to compute the pressure and temperature hike during bubble collapse due to different sonication power. The simulation results show that the ultrasonic irradiation with higher sonication power could produce a higher energy to break the lignocellulose wall.
Flow analysis of the deep dynamic stall of wind turbine airfoil with single-row and double-row passive vortex generators
Authors: Zhu Chengyong , Wang Tongguang , Chen Jie , Zhong Wei
Published: April 2020

This paper aims to understand the influence of vortex generators (VGs) on deep dynamic stall of the NREL S809 airfoil. The fully-resolved URANS method is used to predict aerodynamic responses of the airfoil with both single-row and double-row VGs. On one hand, single-row and double-row VGs are found to attenuate the force fluctuation and postpone the extension of flow separation when the airfoil pitches up. The onset of deep dynamic stall is therefore significantly delayed with the maximum lift coefficient increased beyond 40%. This indicates that VGs are effective in controlling deep dynamic-stall behavior. On the other hand, single-row and double-row VGs are found to make a great difference in aerodynamic responses when the airfoil pitches down. Single-row VGs undermine the torsional aeroelastic stability and have the potential risk of making the airfoil flutter. Double-row VGs can accelerate the flow reattachment effectively, and quickly restore the decreased aerodynamic force near the maximum angle of attack. These findings also imply that deep dynamic stall with VGs becomes highly complicated, because VGs can be fully submerged in separation vortices. In general, double-row VGs perform better than single-row VGs to control deep dynamic stall. This study is believed to assess the VG performance in controlling highly unsteady aerodynamic loads on wind turbines.
The effect of pretreatment methods for improved biogas production from oil-palm empty fruit bunches (EFB): experimental and model
Authors: Wadchasit Pornwimon , Siripattana Chairat , Nuithitikul Kamchai
Published: April 2020

The production of biogas from solid wastes in addition to palm oil mill effluents is necessary due to the shortage of the effluents, operation of biogas plants at low to moderate capacities, and large amount of solid wastes, particularly oil-palm empty fruit bunches (EFB). However, the biogas production from raw EFB gives low yield. This study therefore aims to investigate the effect of EFB pretreatment methods on the improvement of biogas production. The pretreatment of EFB was carried out through chemical (NaOH solutions), physical (size reduction) and biological (activated sludge and bio-scrubber effluent) processes. The experimental data was tested against corrected Gompertz model. The results showed that size reduction and pretreatments of EFB with 7% w/v NaOH, activated sludge and bio-scrubber effluent could improve biogas yield significantly and differently. The highest yield of methane was 429.9 ml/g.VS, obtained from EFB with size reduction. For the pretreatments of EFB with 7% w/v NaOH, bio-scrubber effluent and activated sludge, the methane yields were 345.5, 326.4 and 297.3 ml/g.VS, respectively. Without pretreatment, the methane yield was only 226.0 ml/g.VS. The change in cellulose and lignin compositions of EFB after pretreatment is attributed to the improvement of biogas yield. It is economically interesting that the bio-scrubber effluent from palm oil mills can be recycled to treat EFB. In the modeling study, the corrected Gompertz model could fit all data sets reasonably well.
Parameters estimation of hydraulic power take-off system for wave energy conversion system using genetic algorithm
Authors: Jusoh M. A. , Ibrahim M. Z. , Daud M. Z. , Yusop Z. M. , Albani A. , Rahman S. J. , Mohad S.
Published: April 2020

This paper presents accurate control parameters estimation of the hydraulic Power Take-Off (PTO) model for the wave energy conversion system to maximise energy production. In general, the performance of the hydraulic PTO system depends on the parameters setting of hydraulic PTO system components such as hydraulic motor displacement setting, pre-charge of the hydraulic accumulator, and et cetera. Conventionally, it requires to manually obtain the optimal parameters of a hydraulic PTO system by repeating the simulation process. However, this estimation method exposed to human error and would easily be resulting in a non-optimal selection of hydraulic PTO parameters for the wave energy conversion system. Therefore, an easy and accurate approach of using the GA optimisation method for determining hydraulic PTO parameters was introduced in the present study. This approach is simple and more accurate compared to the conventional optimisation method. The hydraulic PTO model was developed in SIEMENS/Amesim environment using available components in the library. The specifications of the actual hydraulic PTO system components from the manufacturer were used during the simulation set-up. The complete hydraulic PTO system was optimised using a special genetic algorithm (GA) optimisation tools in the SIEMENS/Amesim software. The simulation results showed that GA was effective to determine the optimal configuration parameters of hydraulic PTO system. From the results, the optimal configuration parameters of hydraulic PTO system were successfully reduced about 38%. Consequently, the maximum force applied to the WEC devices was reduced up to 34%. This force reduction is important since it will enable the WECS to be operated during a smaller wave condition.
Performance analysis of solar tunnel dryer with thermal storage and Photovoltaic system for drying star fruit
Authors: Kondareddy Rajesh , Sivakumaran N , Radhakrishnan K. , Nayak Prakash Kumar
Published: April 2020

The aim of this research work to analyse the performance of the proposed solar tunnel dryer and photovoltaic (PV) system to dry star fruit. Star fruit (Averrhoa carambola L.) is a native fruit in the north eastern states of India. Due to its rich nutritional composition and medicinal property, the demand for this fruit increased nationally. The proposed design consists of a tunnel type drying chamber and thermal storage unit. Paraffin wax (PCM) was used as a thermal storing material mounted in the tunnel dryer chamber to use the thermal energy at off sunshine hours. The thermal insulation coating on the outer surface of the solar drying chamber enhances the thermal performance of the tunnel dryer. The overall efficiency of this proposed design was analysed. The results indicated that drying of star fruit occurred in the falling rate period, where no constant rate period of drying rate was observed. The quality analyses data revealed that higher values of TPC (47.59 mg GAE/gram of sample) and DPPH (73.59 μ mol of TE/gram of sample) are obtained in the samples dried in solar dried as compared to open sun-dried samples. Sensory analysis (taste, aroma and flavour) carried out on slices of star fruit indicated that the solar-dried slices provided better scores compared to open sun-dried samples.
Optimal reactive power dispatch using particle swarm optimization algorithm for Yangon distribution network
Authors: Htay Tin Tin , Mon Khine Khine , Lin Ohn Zin
Published: April 2020

Optimal Reactive Power Dispatch (ORPD) is very efficient to optimize the control variables like as generator voltages, transformer tap setting and values of reactive power injection for loss reduction in power system. ORPD is the one of the complexity of optimization problems including with equality and inequality constraints of power systems. Many research papers have developed in ORPD applied to the IEEE test systems with various intelligent methods for the loss reduction. In this paper, the test system is carried out on Yangon Distribution Network (YDN) composed of different voltage level such as 230 kV, 66 kV and 33 kV, and supplied by various types of generation sources. Thus, it is very high in losses and difficult to find out the control variables of ORPD in YDN. The main objective is to reduce the both active and reactive power losses in YDN. Particle Swarm Optimization (PSO) method implemented in ORPD problem of YDN is very applicable and effective to obtain the minimum losses while all the bus voltage profile is acceptable in voltage constraints. The obtained results from ORPD using PSO algorithm could enhance YDN efficiently.
Qualitative framework based on intelligent robotics for safe and efficient disassembly of battery modules for recycling purposes
Authors: Garg Akhil , Zhou Lin , Zheng Jun , Gao Liang
Published: April 2020

In next 5-10 years, there will be 5-8 million tons of spent batteries accumulated as waste. There exists methods for recovery of materials from a battery for reuse or remanufacturing purposes. The research question arises on how about the recycling of batteries stacked in the battery modules in series or parallel configurations. This paper shall propose the qualitative framework based on intelligent robots for safer and efficient disassembly of battery modules for recycling. The framework combines the battery pack’s automatic removal procedure with the battery’s intelligent sorting program to recycle the reusable batteries. It has higher degree of automation and higher recycling efficiency than the existing frameworks. This also includes a smart battery information collection system (machine vision based information reading), an intelligent robot based battery disassembly system and a smart battery classification system. In addition, the framework also includes AI model based programming of robot so that it can sort out the batteries in ascending order of their remaining life.
Realising the ASEAN power grid through unbundling: takeaways from the Philippines’ and Singapore’s experience
Authors: Aris Hazleen , Jørgensen Bo Nørregaard
Published: April 2020

The ASEAN Power Grid (APG) is a flagship initiative mooted in 1997 to strengthen and promote power interconnection and trade in the ASEAN region. The ultimate aim of the APG is to ensure energy security and sustainability in the region, particularly the electricity. One way to achieve this, as demonstrated by the Nordic countries, is by having a regional electricity market, on top of the physical interconnection of the grids. Thus, taking the cue from the Nordic region, a pre-requisite to the regional electricity market is the liberalisation of the electricity supply industry (ESI) of each of the ASEAN member countries. Although there is no one-size-fits-all solution to the establishment of the regional electricity market, liberalisation of the ESIs can potentially be the path for the ASEAN countries too, with the necessary modifications and localisations in place. Furthermore, ESI liberalisation or unbundling is not entirely new to the ASEAN countries. Nine out of the ten of its member countries have implemented unbundling, although the degree of implementation varies. To date, two ASEAN countries have unbundled their ESIs fully, namely Singapore and the Philippines. However, the two countries underwent different experience in liberalising their ESIs. While it was a ‘bumpy ride’ for the Philippines, Singapore had a smoother and more orderly transition. As such, deliberation of their experience in liberalising their ESIs would provide good insights for the other ASEAN countries to consider in liberalising their ESIs, should it become the direction. This paper therefore presents a brief overview of the Philippines’ and Singapore’s experience in their transformation towards liberalised ESIs with the aim to identify the good practices, the challenges as well as the lessons learnt from these transformations. Findings from the study show the importance of the governance and legislative framework to instate reform, as well as the gradual introduction of the reform moves. This is especially necessary as the lack of homogeneity and harmonisation of the regulatory framework and ESI structure of the ASEAN countries was found to be amongst the barriers towards the full realisation of the APG.
Simulation for CO2capture using tubular dual-phase membrane module
Authors: Yee Liow Ju , Lai Li Sze , Tay Wee Horng
Published: April 2020

Dual-phase membrane is a newly developed membrane that is capable of capturing carbon dioxide (CO2) from flue gas at high temperature up to 823 K. To date, the researches on CO2capture using dual-phase membrane are performed experimentally. However, the gas separation performance of the scale-up tubular dual-phase membrane module is scarcely studied. Therefore, the potential application of the dual-phase membrane module remains as a challenge. The design of membrane module and its implementation in actual operating conditions can be analyzed beforehand by using Computational Fluid Dynamics (CFD) simulation. In this paper, the hydrodynamic profile of the gas flowing inside a tubular dual-phase membrane module was studied to investigate its potential for industrial application. CFD simulation of gas mixture consisting of CO2and nitrogen (N2) that flowing through the membrane module was performed at 823 K. Among the parameters investigated are the absolute pressure, concentration of CO2and gas velocity within the tubular membrane module. The inlet mass flow rate was set at 0.00448 kg s−1and the total volume of the membrane module was 0.031 m3. Based on the simulation, 0.09 bar of pressure drop was observed when the feed gas stream passed across the membrane zone to the outlet zone. There was about 86 % of CO2recovery with the CO2concentration decreased from 20 mol % to 3.3 mol %. Besides, the membrane stage cut was around 0.17 with 83 % of the gas leaving the membrane module at the retentate side. The simulation results give reliable statement over the separation efficiency of CO2and flow pattern in membrane module. The scale-up performance of single membrane module has been predicted through the simulation based on the experimental data.
Iron oxide decorated graphene oxide embedded polysulfone mixed-matrix membrane: Comparison of different types mixed-matrix membranes on antifouling and performance
Authors: Chai P.V. , Mahmoudi E. , Mohammad A.W. , Choy P.Y.
Published: April 2020

Polymeric membrane is widely adopted for water treatment due to its stability in thermal and chemical resistance, smaller footprints and relatively low cost. However, polymer membrane always suffers the poor performance due to its hydrophobic nature. In the recent years, nanomaterials were introduced into membrane matrices to increase the hydrophilicity. In this study, three different types of nanomaterial, iron oxide (Fe3O4), graphene oxide (GO), and iron oxide-decorated graphene oxide (Fe3O4/GO) were embedded in the polysulfone (PSf) mixed-matrix membranes (MMM). This study investigated the effect of three different nanomaterials on the membrane characteristics, performance, and antifouling properties. Membrane characterization, performance, and antifouling was carried out by pore size, porosity, contact angle analysis, zeta potential analysis, flux measurements and flux recovery ratio respectively. First, GO, Fe3O4and Fe3O4/GO nanomaterials were synthesized using Hummers method, co-precipitation method, and co-precipitation method in the presence of GO. After that, membranes were fabricated using phase inversion method. In this study, Fe3O4/GO-PSf MMM (76.35%) and GO-PSf MMM (64.39%) showed enhanced porosity as compared to the pure PSf membrane (56.89%) due to the presence of abundance hydrophilic group in GO nanoplates. However, the Fe3O4-PSf MMM show slightly lower porosity (53.82%). Contact angle analysis also revealed that Fe3O4-PSf MMM (71.47°), GO-PSf MMM (69.17°), Fe3O4/GO-PSf MMM (69.97°) showed improved hydrophilicity as compared to the pure PSf membrane (78.80°). Experiment also demonstrated that all the MMMs exhibit higher negatively surface zeta potential as compared to pure PSf membrane. The membrane performances were investigated using pure water flux and congo red (CR) dye removal. Study showed that Fe3O4/GO-PSf MMM give the best membrane performance with the flux of 112.47 L/m2. h and CR dye removal of 97%±2. Fouling analysis reveal that all MMMs exhibit high flux recovery ratio (>80%) as compare to pure PSf membrane.
Crucial factors in shaping strategies for Thai energy business in the dynamic era
Authors: Nakapreecha N , Pongthanaisawan J , Wangjiraniran W
Published: April 2020

In an era of rapid change, adequate strategy formulation is crucial to an organization, not just to overcome obstacles but to thrive in the business sustainably. To survive in the dynamic environment of the energy business, strategy formulation for energy enterprise need to consider various potential factors, together with their impacts. This includes social factors, innovation and technology factors, economic factors, environmental factors, as well as government policies and directions. The strategy formulation must be based on accurate and sufficient data, which indicates a level of impact and their uncertainties that may occur in the future. This paper presents analytical sets of key challenges, drivers, and critical uncertainties, which are expected to have significant impacts on the Thailand energy business in the next 30 years. The research starts with examining the global energy situation and challenges for the Thai energy business. The sustainable development goal is defined as a key decision focus at this step. Next, the STEEP analysis is employed to evaluate the impacts of factors on the energy business ranging from social factors, technology factors, economic factors, environmental factors to political factors. Foresight workshop with stakeholders is arranged to identify critical uncertainties. The result will be beneficial to both government and private enterprises in designing appropriate energy strategies.
Multi-criteria assessment of energy sector nationally appropriate mitigation actions in Sri Lanka
Authors: Sugathapala Thusitha
Published: April 2020

Sri Lanka has shown its commitment for greenhouse gas mitigation by publishing nationally determined contributions. Key share of mitigation targets is from the energy sector, amounting to about 40 Mt CO2e during 2020-2030. 52 mitigation options (MOs), referred to as nationally appropriate mitigation actions (NAMAs), were identified with a total mitigation potential of 75 Mt CO2e. Globally, the commonly used methodology for prioritization of NAMAs is the marginal abatement cost (MAC) analysis. However, this approach has received criticism over the effectiveness due to its inability to consider other important aspects such as barriers, enablers and co-benefits. The present study proposes a multi-criteria assessment (MCA) methodology involving more comprehensive characteristics of MOs and use of sustainability criteria/indicators to broaden the applicability of MAC analysis. The proposed methodology involves a stage-wise evaluation in three levels. Firstly, MOs identified are pre-screened based on technology maturity and information availability as indicators for chance of success in implementation. Among 52 MOs, 38 qualified for the next assessment level. These MOs are then undergone screening, where MAC and mitigation potential are combined with a scoring system together with a prescribed benchmark value as a qualifying criterion. Accordingly, 31 MOs are qualified, which represent a total mitigation potential of 62 Mt CO2e.Finally, at third level, indicators in relation to barriers, enablers and co-benefits are used to derive an overall score of MCA. The results of MAC and MCA analyses are used in conjunction to prioritize MOs under three appealing levels as 07 highly, 14 moderately and 10 least, with a total mitigation potentials of about 17.1, 32.4 and 12.8 Mt CO2e, respectively. Accordingly, the 21 high and moderate appealing MOs could contribute to the NDC targets. It is concluded that MCA methodology proposed is a sound approach in prioritizing MOs.
Magnetite activated carbon/chitosan composite from biomass for removal of diclofenac in aqueous solution
Authors: Yoong Yee How , Chong Woon Chan , Chung Ying Tao , Teoh Hui Chieh
Published: April 2020

Diclofenac (DCF) is a type of micropollutant from pharmaceutical waste which brings adverse effect to the aquatic environment if the wastewater is not well-treated. The impregnation of biopolymer on activated carbon has recently gained increasing attention to improve the removal efficiency of micropollutant from wastewater. Magnetite rice husk activated carbon/chitosan composite (MACCS) with high adsorption capacity was developed in this study by modifying rice husk activated carbon (RHAC) with iron oxide (Fe3O4) nanoparticles and cross-linked with chitosan. The adsorption performance of the synthesized MACCS was compared with rice husk activated carbon (RHAC) and magnetite chitosan (MCS) for DCF removal from aqueous solution. The physical and chemical properties of the synthesized biosorbents were investigated via scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR). MACCS was identified as the best performing biosorbent and its DCF removal ability was further tested in batch with different parameters. The parameters reported in this study were solution pH and the synthesis ratio of activated carbon and chitosan. The most effective adsorption of DCF with MACCS was achieved at solution pH of 2.5 and activated carbon to chitosan ratio of 1:2. In acidic condition, the perfect coating of chitosan which contained abundance of amine group attached on the RHAC with high porosity had achieved 94% removal of DCF with maximum adsorption capacity of 270 mg/g. Besides, the MACCS could easily be separated from the aqueous solution due to its magnetic property. From the results, the MACCS biosorbent showed its potential to be an excellent alternative adsorbent for the removal of micropollutant from wastewater.
Incentivizing geothermal energy business with G20 collaboration
Authors: Tharom Tabratas , Hadi Hendro Sasasongko
Published: April 2020

Indonesia has an abundance of geothermal energy potential (29 GWe) and becomes the second-largest geothermal power plant installed capacity after the United States. Geothermal is the most reliable renewable energy due to its highest capacity factor. It works as the base load in the electric grid. Unfortunately, the installed geothermal power plant was only approximately 6.3 % in 2018. Although the Government of Indonesia (GoI) has already given and supported in terms of financial incentives, regulation, technical assistance, it could not boost geothermal development significantly. Recent geothermal based electricity generation cost is rising, especially for the greenfield, caused by rising exploration cost could lead to geothermal development unfavorable, especially for affordability policy in Indonesia energy. All the incentives could not yet accelerate geothermal development significantly due to the risk and cost of geothermal exploration. Facing the fact that exploration cost tends to rise over time, G20 collaboration should be able to reduce the risk and cost associated with geothermal exploration with effective incentives. This paper aims to provide solutions and recommendations regarding exploration cost reduction through geothermal technology research and development with an emphasis on cost and risk reduction among G20 collaboration. The proposed incentives are then constructed for Indonesia’s requirement to meet geothermal conditions and requirements from the trilemma energy aspect, especially for geothermal technology to reduce exploration cost and risk. The proposed incentives also deal with human resource development for improvement in learning rates to have better technology adoption and acquisition by using SWOT and Policy Gap Analysis.
Generation of Orthogonal Sequence Sets for M-ary Spread Spectrum Communications with OFDM Modulation
Authors: Xuan Guixin , Zhang Zhenyu , Zhang Bo , Zeng Fanxin
Published: April 2020

The number of orthogonal sequences is a key point of M-ary spread spectrum (MSS) communication system since more sequences mean higher data rate. When orthogonal frequency division multiplexing (OFDM) modulation is used into MSS system, the additional low peak-to-average power ratio (PAPR) property is required due to high power efficiency. Based on the segmentation-shift operation, multiple orthogonal sequence sets with the same size and sequence length are generated in this paper. By combining these orthogonal sequence sets, the number of the generated orthogonal sequences is very large. For any two orthogonal sequence sets, there exists good cross-correlation performance between them at zero shift. In addition to large set size and good correlation property, the generated multiple orthogonal sequence sets possess low PAPR, which is very suitable for OFDM modulation. The generation algorithm of multiple orthogonal sequence sets is provided in this paper, and the corresponding simulation results show the effectiveness of the provide method.
A Research of Instant Survey Based on Typical Scenario
Authors: Cheng Yinchao , Xie Qifang , Ma Yan
Published: April 2020

With the advent of 5G era and the continuous improvement of users’ demands for intelligent services, traditional online research methods cannot meet the survey needs of the communication industry at the present stage. In order to collect user feedback more accurately and improve survey efficiency, this paper proposes an instant survey based on typical scenarios. This method can effectively obtain the most authentic feedback information from users by establishing the intelligent user invitation and accurate questionnaire release of the contact points between enterprises and users in typical scenarios. The research results show that the method in this paper is 3.75 times higher than the traditional online research in terms of user participation, and about 6 times higher in terms of the survey result recovery, which significantly enhances the accuracy of the survey and effectively shortens the survey cycle. This paper introduces the idea of instant survey into the field of communication for the first time, and widely applied to the user survey in the communication field.
Design of Real-time Video Transmission System for Drone Reliability
Authors: Guo Jin , Li Xiaoyan , Lv Zhigang , Yang Yongxia , Li Liangliang
Published: April 2020

The low-latency reliability video transmission system designed in this paper can complete the functions of real-time image acquisition, transmission and display. The system uses Raspberry Pi 3B+ controller as the core; the 500W pixel camera OV5647 module with CSI interface feature is used as the acquisition module to collect image data in real time and perform compression coding processing; adaptive control of image measurement and control data through 4G public mobile communication network transmission. The experimental results show that the reliability video transmission method designed in this paper can achieve low latency reliability transmission of 480P and 720P resolutions. It can ensure low-latency reception of HD images at the receiving end, and the receiving frame rate is stable above 11FPS, which satisfies the system design requirements.
Screen-Camera Communication System Based on Dynamic QR Code
Authors: Liu Wenkai , Wang Biqi , Li Yan , Wu Menglong
Published: April 2020

Screen-camera communication is a new information communication method based on visible light. However, such communication mechanism relies on barcodes to transmit information which suffers a limited capacity and a low communication rate. Hence, we proposed a color multiplexed dynamic QR Code communication system based on mobile devices. Use this method can further improve the communication rates over the system. In our system, a self-defined frame structure has been designed for a better reliability and diversity in the transmission. The experiment results indicated that in the traditional dynamic QR Code transmission mechanism, the real-time communication rate is 150 Kbit/s and the non-real-time communication rate is 300 Kbit/s. While, under the proposed color multiplexed dynamic QR Code communication system, the real-time communication rate can reach 320 Kbit/s and the non-real-time communication rate can reach 900 Kbit/s. After multiple experimental tests, it can transfer text, picture and audio files with no error.
Research on the Sea Surface Waveguide Inversion of Radar Sea Clutters Based on Five-parameter Method
Authors: Zuo Lei
Published: April 2020

In this paper, a method for the formation of the oceanic atmospheric refractive index based on Five Parameters, which uses the power information of radar sea clutter. By comparing the surface waveguides measured in some experimental sea areas in China, the feasibility of this method is verified, which is beneficial to overcome the difficulty of directly measuring the atmospheric refractive index profile under harsh conditions at sea.
Expert System about Remote Support for Rushing to Repair the Damaged Power Equipment
Authors: Yang Xinyu , Lu Liming , Jiao Kaizhe , Zhang Lin
Published: April 2020

Combined the theory of equipment battle filed damage and the information technology, the design model about remote technology support for power equipment battle field damage was put forward. The system was composed of site monitor diagnosis, network transmission gallery and the service center of remote technology support. The center of remote damage evaluation was established by using the structure of B/S and ASP + SQLServer2012. The key technologies of this system involve battle field damage data collection, data transmission, expert system and so on. It provides a good foundation for the development of repair technology through research and application of the system.
A Composite Detection Method for Direct GPS Deception Attack
Authors: Hu Kunjun , Huang Yuanfeng
Published: April 2020

On account of the GPS initial technology limitations, it is vulnerable to interference, deception and other security attacks; GPS is widely used. If it is attacked, it will bring very serious consequences. Due to the problem of cost, civil GPS seldom considers how to defend against security attack. Therefore, it is necessary to study a fast and efficient GPS deception signal detection method to resist the attack. By improving the existing detection methods of GPS deception signal, a composite detection method of GPS deception signal is proposed. Based on DOA detection, the detection of signal propagation time difference is added, and the existence of GPS deception signal is judged synthetically according to whether the signal angle of arrival and the signal propagation time difference exceed the threshold value of real signal. The improved method improves the detection efficiency by reducing the calculation times of the signal angle of arrival. By reducing the number of detection signals to improve the detection accuracy of signal propagation time difference when there are more detection signals and less deception signals, thus ensuring the accuracy of composite detection. And subsequent simulation experiments successfully detected direct GPS deception signals, which verified the feasibility of this method for rapid detection of direct deception signals.
Dynamic Update Siamese Networks with Deeper Features
Authors: Tan Jianhao , Tan Shanshan , Yin Wang , Liu Liming , Zhang Siyuan , Wang Yaonan
Published: April 2020

Visual object tracking has been a concern topic these years, and many trackers have achieved good results in various fields. These researches and breakthroughs have made many improvements to solve problems such as drift, lighting, deformation and occlusion. In this paper, we improve the structure of the AlexNet[1] network by designing the three important influencing factors of the receptive field size, total network step size, and feature filling of the twin network. Apart from this, we add a smoothing matrices and a background suppression matrices to effectively learn the features of the first few frames as much as possible. Fuse multilayer feature elements can learn online about target appearance changes and background suppression, and we train them by using continuous video sequences.
Target Tracking Based on Correlation Filter for Scale Offset
Authors: Tan Jianhao , Ma Xiaoping , Wang Yaonan
Published: April 2020

Existing scale estimation methods mainly use fixed-size tracking box for target tracking. However, when the moving direction of the target changes from near to far or from far to near, the size of the current tracking box cannot adapt to the scale change. In order to overcome the disadvantage of invariant size of tracking box in the scale change, this paper proposes a scale offset estimation method based on correlation filter by combining the state of previous frame and current frame of the target. Select the scale proposal box in the scale layer, and adjust the position and size of the actual tracking box in real time according to the size of the proposal box, target position and scale offset. In this paper, OTB-100 is used as the dataset. The obtained tracking results show that our algorithm Ours has better tracking performance than the existing others tracking algorithm in scale variation, and it has better tracking effect and stronger robustness in drift and occlusion events.
Quantitative Analysis of Discharging Speed of a Horizontally Rotating Drum with Internal Baffles by Using DEM Simulation
Authors: Tian Zhongke , Yu Haiyong , Han Congcong
Published: April 2020

Although the concept seems simple, the motion of bulk materials in a rotating drum is rather complex. In this paper, the process of throwing the evenly mixed materials out of a horizontally rotating mixing tank with internal baffles was concerned. The reasonable rotary speeds for the discharging process as well as the ideal process durations were quantitatively determined by running simulations based on the Discrete Element Method (DEM) software PFC3D. The particle-counting codes, developed in PFC3D built-in programming language FISH, took important roles in evaluating the corresponding effects of different process parameters, which overcame the uncertainty of usual qualitative analysis of simulation results.
Implicit Community Discovery Based on Microblog Theme Homogeneity
Authors: Sun Zefen , Du Yajun , Chen Xiaoliang , Wang Chunjia
Published: April 2020

With the rapid development of various social platforms, social networks have accumulated more and more data. These huge and complex data contain valuable information in many fields. It is of far-reaching significance to conduct statistical analysis of these data and dig out valuable information and apply it in real life. Based on the homogeneity of social networks, our paper proposes a framework of discovery algorithms based on the homogeneity of microblogs to realize the theme community discovery of microblog social networks. Firstly, the data set is preprocessed, the invalid data is removed and classified by microblog users. Secondly, the LDA model is used to extract the topic of microblog user blogs to describe the characteristics of microblog users. Thirdly, two users are calculated based on the theme interest. The homogeneity measure between them is used to represent the relationship of social networks. Finally, the community of the implicit social network is realized through unsupervised algorithms to build communities with the same interest as the theme. In order to verify the validity of our proposed algorithm framework, this paper uses data sets from microblog network to conduct experiments. The experimental results show that the algorithm effectively combines the homogeneity measure of the network and has achieved very good results in the implicit community discovery.
The Application of the Integrated Machine Learning Model in the Financial Crisis of Imbalanced Samples
Authors: Lu Zhang , Liu Jiapeng , Jiang Minqi
Published: April 2020

In this paper, the financial crisis of the enterprise in the t-period is predicted by the financial index data of the non-financial industry A-share enterprise in the main board market of the Shanghai Stock Exchange in the t-3 period. Then we use the integrated machine learning models to select the financial crisis enterprises, and the problem of failure of classifiers in unbalanced samples is solved through bagging and sampling techniques. The highest probability of correctly selecting enterprises with financial crisis is 92.86%. With the integration of the model, the overall accuracy is improved to 88%. We help the enterprise to complete the forward-looking financial crisis forecast and provide some reference for the business activities and investment activities of the enterprise.
Short-Term Load Forecasting Using Modified Sequence-to-Sequence Deep Learning Framework
Authors: Luo Jun , Zhu Keyu , Wang Xiaojia
Published: April 2020

The future of smart grids promises unprecedented flexibility in energy management. Therefore, it is crucial to accurately predict the energy load demand of individual power grid stations and overall levels. In this paper, a Sequence to Sequence learning method based on long short-term memory neural network (Seq2Seq) forecast model is proposed to predict the load of the community microgrid. In particular, this paper studies the effectiveness of Seq2Seq in community microgrid load forecasting, avoiding overfitting through weight attenuation regularization, and reducing the impact of interference and noise on training data. The proposed method is implemented on the base load data set of multi-user. The results of Seq2Seq were compared with the results of two well-known methods, one is traditional LSTM and the other is Support Vector Machine (SVM) on the same datasets. Experimental results show that compared with SVM and traditional LSTM, Seq2Seq has better learning effect. Finally, we calculate the performance index. When using load data to train and test the model, it was noted that compared with traditional LSTM and SVM, the root mean square error (RMSE) of Seq2Seq was decreased by 44.07% and 64.06%, respectively. Our research offers a decent reference for the application of deep learning in the field of energy management.
A New Fast Computation of a Permanent
Authors: Niu Xuewei , Su Shenghui , Zheng Jianghua
Published: April 2020

Store-zechin is a general algorithm for computing the permanent of a square matrix, and the core ideas of this algorithm are multiplexing, recursion and storage. It means we just calculate once for every sub-items and for the second time, the previous result is substituted into the calculation. The advantage of Store-zechin algorithm is that it can make full use of computer memories and accelerate the calculations. In fact, it needs 2
n-1
(n- 2) + 1 additions and (2
n-1
- 1)n multiplications for computing the permanent of an n ± n matrix by Store-zechin algorithm. In the same situation, Ryser algorithm requires (2
n
- n)(n + 1) – 2 additions and (2
n
- 1) (n – 1) multiplications, R-NW algorithm requires 2
n-1
(n + 1) + n
2 - n -1 additions and 2
n-1

n + n + 2 multiplications. So Store-zechin has n2
n-1
+2
n+1
-n
2-n-3 additions, n2
n-1
-2
n
+1 multiplications less than the Ryser algorithm, and 2
n-1
+2
n
+n
2-n-2 additions, 2n+2 multiplications less than the R-NW algorithm. It can be confirmed that the Store-zechin can indeed calculate a permanent in fewer steps.
A Comparative Study of Moving Target Detection Algorithms
Authors: Wang Yuanyuan , Zhou Xiaolei , Zuo Yuanyuan , Wu Zhuang
Published: April 2020

This paper wants to analyze and compare the mainstream algorithms for moving target detection and lay a foundation for algorithm improvements as well as for such research directions as intelligent transportation system and traffic calculation, this paper selects three target detection algorithms for comparative study: methods of interframe difference, background difference and optical flow. It conducts simulation experiment on traffic surveillance videos with MATLAB programming, selects the threshold for frame difference method suitable for the current video and improves detection accuracy by binaryzation, expansion, corrosion and other processing methods. Interframe difference method compares the effects between the original difference image and grayscale difference image and considers bad difference caused by excessive moving distance. Background difference method compares the effect images after morphological processing, and reduces the impact of noises. The advantages are shown by comparing the original image with the labeled optical flow diagram using the optical flow method. By comparing the recognition effect images and processing time of these three algorithms, it analyzes and concludes the strengths and weaknesses as well as the ranges of application in intelligent transportation system.
A Bearing Fault Diagnosis Method Based on Dictionary Learning and Parameter-Optimized Support Vector Machine
Authors: Yang Jing , Hao Yan , Xu Ting , Yan Huichao , Hu Hongping , Bai Yanping
Published: April 2020

Aiming at the problem of fault diagnosis, a novel method based on dictionary learning and parameter-optimized Support Vector Machine (SVM) was proposed in this paper and applied it to bearing fault diagnosis. Firstly, the collected bearing fault signals are transformed into gray images after data processing. Then, using dictionary learning, the gray images are denoised and output them as signal data. Finally, the SVM multi-classification model obtained by using Grid Search (GS) algorithm to optimize penalty parameter c and kernel function parameter g is used to classify and identify the fault type. This paper is based on data from Case Western Reserve University Bearing Center for experimental verification. The results show that the proposed model can continuously achieve the accuracy of 100% in the process of bearing fault diagnosis in different environments, which proves that the proposed method can accurately and effectively realize the fault diagnosis classification of bearings.
Research on Integrated Scheduling Optimization of Double-trolley Quay Crane and AGV in Automated Terminal
Authors: Chen Jiajuan , Du Wei , Wang Hongxuan , Guo Dong
Published: April 2020

With the upsizing of ships, the operating efficiency of automated container terminals is becoming increasingly important. Based on the operation mode of loading and unloading synchronization, we first established an integrated scheduling optimization model of Double-trolley Quay Crane (QC) and AGV. Secondly, we designed a genetic algorithm embedded in tabu search to improve its local optimization ability. Finally, we conduct an empirical analysis. In the same case size, compared with the traditional genetic algorithm, the genetic algorithm embedded in tabu search has shorter model solving time and lower model optimal solution fitness. The maximum difference of the model solving time and the optimal solution fitness value can reach 165.113% and 7.71%, respectively. The results verify the rationality of the model and the effectiveness of the algorithm.
The Unipotent Condition of Linear Groups Generated by Matrices with Primitive Elements Jorden Blocks of Orders no More Than Eight
Authors: Yang Xin-Song , Pan Guosheng
Published: April 2020

In this paper, the combinatorial properties of free group generators are studied with help of calculation tool, matrix logarithm, and Jacobson radical. The unipotency of matrix groups can be better delineated by these new combinatorial properties, and a new necessary and sufficient unipotent condition of matrix group whose primitive elements Jordan blocks have orders no more than eight, as well as of free groups, will be given. Our result improves the relative theories.
List all Maximal Cliques of an Undirected Graph: A Parallable Algorithm
Authors: Hua Xin , Zhong Maosheng , Liu Qun , Wang Mingwen
Published: April 2020

Listing all the maximal cliques of an undirected graph is considered as a NP-complete problem, even if the existing fastest algorithm for listing all the maximal cliques also needs an exponential time complexity, and these algorithms are not able to be reconstructed into parallel processing algorithms, therefore, which are also unsuited to solve all maximal cliques of a complex undirected graph with a large number of maximal cliques or vertices. This paper aims to develop a parallable algorithm for listing all maximal cliques of the large size complex undirected graph. Firstly we gave some definitions, including adjacent sub-graph, suspended sub-graph and so on, then adopted a partition and recursive strategy to partition equivalently a parent-graph into smaller sub-graphs, so we can get all maximal cliques of parent-graph by recursively listing all maximal cliques of sub-graphs. we have developed a single-thread and a multi-thread program of the algorithm by using Java language. Lastly, we compared the performance of our algorithm in a benchmark data set DIMACS with the existing main algorithms. The results show that our single-thread program is basically equivalent performance with existing algorithms, but the multi-thread program has better performance than the existing algorithms. Because our method is to divide the complex problem into some smaller sub-problems and achieve the solution of the original problem by solving these sub-problems, our algorithm is easy to be implemented by using multi-thread, and also easy to be expanded to the parallel algorithm, which has better feasibility and practicability in solving the large scale complex graph.
Influences of Floating-ring Seal Parameters on Clearance Leakage
Authors: Yuan Zhenwei , Chen Junqi
Published: April 2020

For a type of floating-ring seal widely used in the fields of aeronautics and astronautics, power and energy, and petrochemical engineering, the influences of various parameters on clearance leakage behavior of floating-ring seal are analyzed using numerical method and by means of MATLAB programming. Based on Bulk-flow model, the governing equations of the flow field in the clearance of floating-ring seal are established. The finite difference method and the staggered grid are used to discretize the governing equations. The SIMPLE algorithm is used to solve the discretized equations. The self-locking position of the floating-ring is calculated by analyzing the equilibrium condition of the floating ring, and accordingly the leakage flowrate of the flow field in the clearance of the floating-ring seal are obtained. Finally, the influences of fluid viscosity, inlet swirl, width of floating ring, and relative roughness of floating-ring and rotor surface s on the leakage flowrate are discussed.