Multi Source Research Articles

Case study on ventilation and cooling control technology of multi heat source coupling in long distance subsea tunnel construction

To solve the high-temperature environmental hazards caused by concrete hydration heat release in tunnel construction, this paper studies the heat generation mechanism of heat source in the tunnel using theoretical analysis and numerical simulation, and analyzes the temperature control in the tunnel under different ventilation wind speed (1 m/s, 2 m/s, 3 m/s, 4 m/s, 5 m/s) and ventilation temperature (298 K, 293 K, 288 K, 283 K, 278 K). The results show that: increasing the ventilation speed can effectively reduce the environmental temperature in the tunnel, and the ventilation cooling effect is the best when the air duct outlet speed is 3 m/s. Reducing the ventilation temperature can further reduce the tunnel temperature based on increasing the ventilation speed. When the ventilation temperature is set at 293 K, it can meet the needs of ventilation and cooling at the tunnel face. The simulation results show that when the tunnel ventilation speed is 3 m/s and the ventilation temperature is 293 k, the maximum cooling value of the working face can reach 6.66 k, and the maximum cooling rate is 2.18%. Within 5 m from the tunnel working face, the cooling effect of the enclosure structure is the most obvious, which can effectively ensure the comfort of the working environment.

Earth Observation for Sustainable Infrastructure: A Review

Infrastructure is a fundamental sector for sustainable development and Earth observation has great potentials for sustainable infrastructure development (SID). However, implementations of the timely, large–scale and multi–source Earth observation are still limited in satisfying the huge global requirements of SID. This study presents a systematical literature review to identify trends of Earth observation for sustainable infrastructure (EOSI), investigate the relationship between EOSI and Sustainable Development Goals (SDGs), and explore challenges and future directions of EOSI. Results reveal the close associations of infrastructure, urban development, ecosystems, climate, Earth observation and GIS in EOSI, and indicate their relationships. In addition, from the perspective of EOSI–SDGs relationship, the huge potentials of EOSI are demonstrated from the 70% of the infrastructure influenced targets that can be directly or indirectly derived from Earth observation data, but have not been included in current SDG indicators. Finally, typical EOSI cases are presented to indicate challenges and future research directions. This review emphasizes the contributions and potentials of Earth observation to SID and EOSI is a powerful pathway to deliver on SDGs.

Optimization of Two-Stage IPD-(1+I) Controllers for Frequency Regulation of Sustainable Energy Based Hybrid Microgrid Network

Sustainable energy based hybrid microgrids are advantageous in meeting constantly increasing energy demands. Conversely, the intermittent nature of renewable sources represents the main challenge to achieving a reliable supply. Hence, load frequency regulation by adjusting the amount of power shared between subsystems is considered as a promising research field. Therefore, this paper presents a new stratagem for frequency regulation by developing a novel two stage integral-proportional-derivative with one plus integral (IPD-(1+I)) controller for multi sources islanded microgrid system (MS-IμGS). The proposed stratagem has been tested in an MS-IμGS comprising of a wind turbine, parabolic trough, biodiesel generators, solid-oxide fuel cell, and electric water heater. The proposed model under different scenarios is simulated in MATLAB environment considering the real-time recorded wind data. A recently developed sine-cosine algorithmic technique (SCA) has been leveraged for optimal regulation of frequency in the considered microgrid. To identify the supremacy of the proposed technique, comparative studies with other classical controllers with different optimization techniques have been performed. From the comparison, it is clearly evident that, SCA-(IPD-(1+I)) controller gives better performance over other considered stratagems in terms of various time domain specific parameters, such as peak deviations (overshoot, undershoot) and settling time. Finally, the robustness of the proposed stratagem is evaluated by conducting sensitivity analysis under ±30% parametric variations and +30% load demand. The lab tests results validate the operation of the proposed system and show that it can be used to regulate the frequency in stand-alone microgrids with a high penetration of renewable energy.

Narrowband multi-source direction-of-arrival estimation in the spherical harmonic domain.

A conventional approach to wideband multi-source (MS) direction-of-arrival (DOA) estimation is to perform single source (SS) DOA estimation in time-frequency (TF) bins for which a SS assumption is valid. Such methods use the W-disjoint orthogonality (WDO) assumption due to the speech sparseness. As the number of sources increases, the chance of violating the WDO assumption increases. As shown in the challenging scenarios with multiple simultaneously active sources over a short period of time masking each other, it is possible for a strongly masked source (due to inconsistency of activity or quietness) to be rarely dominant in a TF bin. SS-based DOA estimators fail in the detection or accurate localization of masked sources in such scenarios. Two analytical approaches are proposed for narrowband DOA estimation based on the MS assumption in a bin in the spherical harmonic domain. In the first approach, eigenvalue decomposition is used to decompose a MS scenario into multiple SS scenarios, and a SS-based analytical DOA estimation is performed on each. The second approach analytically estimates two DOAs per bin assuming the presence of two active sources per bin. The evaluation validates the improvement to double accuracy and robustness to sensor noise compared to the baseline methods.

ANALISIS FLYPAPER EFFECT PADA BELANJA DAERAH KOTA DAN KABUPATEN DI INDONESIA

The aims of local autonomy is to achieve local independence funding, so that the areas can organize themselves without any central government interference. The direct implications for the implementation of the above is needed great for adequate funding. Local government's main funding source, comes from the PAD and othe PAD which is used to finance all expenditures and development. But in some of the current and multi years funding sources not only from the PAD. Local governments also get help from central government transfers such as Equalization Fund in this case is General Allocation Fund (DAU) The aim of this research is to analyse influences of DAU and PAD’s to district’s spending in Indonesia. The samples of this research are taken from the budget report of Kabupaten/Kota within the Province of Sumatera and Java and used 15 province in the periode 2010-2012. Testing to all hypothesis done with SmartPLS. The results show that DAU and PAD partially as well as collectively have indeed influenced the realisation of budget. Furthermore, we might conclude from the results that there has been a flypaper effect which is showed by the DAU which has higher ability to predict district’s spending than the PAD.

Characterization of the Groundwater within Regional Aquifers and Suitability Assessment for Various Uses and Purposes-Western Iraq

Groundwater quality investigation has been carried out in the western part of Iraq (west longitude '40°40). The physicochemical analyses of 64 groundwater samples collected from seven aquifers were used in the determination of groundwater characterization and assessment. The concept of spatial hydrochemical bi-model was prepared for quantitative and qualitative interpretation. Hydrogeochemical data referred that the groundwater is of meteoric origin and has processes responsible for observed brackishness. The geochemical facies of the groundwater reveal that none of the anions and cations pairs exceed 50% and there are practically mixtures of multi-water types (such as Ca–Mg–Cl–HCO3 and Na+K–SO4–Cl water type) as dominant types. The hydrogeochemical evolution indicates that the groundwater is mainly controlled by the leaching and dissolution process of carbonate minerals. Increasing salt content is observed at different static water levels (groundwater flow) confirming mixing cases with multi water sources. Anthropogenic activities do not have a significant alteration in the geochemical nature of groundwater in aquifer systems. Most of the groundwater is classified within the category of C3S1 and C2S1 denoting admissible to good quality of water for irrigation in 67% of the total samples. On the other hand, 33% of samples are classified as bad to very bad. The groundwater of most aquifers has precedence for irrigation, agricultural purposes, animal drinking, and good to fair class for natural preserve activities. While the groundwater of Mullusi and Jeed-Rattga aquifers are suggested for human drinking purposes. Also, the groundwater within the hydrogeologic system can be used in low-pressure boilers, mining, construction industry, and unsafe in high-pressure boilers due to the relatively high total hardness (237 to 1456 mg/l). Corrosively ratio indicates that 83 % of exploited groundwater from boreholes is safe for long transport through metallic pipelines.

A Dynamic Pyramid Tilling Method for Traffic Data Stream Based on Flink

Traffic guidance, traffic management and emergency vehicle traffic all require keeping abreast of traffic status. Intelligent Transportation Systems (ITS) is highly expected to provide real-time traffic condition information service. To achieve this, the capability of handling dynamic data stream collected from multi traffic monitoring sources and serving the public with information timely is essential for ITS. With the wide spread of Internet of Things technology, not only the amount, but also the spatial and temporal resolutions of real-time traffic data have explosive growth, thereby enhancing the difficulty of real-time traffic data processing in ITS. Web pyramid map tiles is wide accepted for massive spatial data service, and the latency of tile generation significantly reduces the timeliness of information transmission and the reliability of services. A Flink-based method for dynamic pyramid tile generation and updating is proposed here. Take advantages of combining grid indexes, employing data partition and window selection mechanisms, and applying iterative computational characteristics for resampling, the distributed dynamic pyramid map tile generation algorithm (DPTG), can quickly visualize real-time spatial traffic data with digital map tiles. Taking the national highway road data from China as an example, the experimental results show that the Flink-based DPTG method has high efficiency and scalability in both batch processing and stream processing mode, which highlights the capability of the proposed method to support real-time traffic monitoring data processing for timely large-scale public service in ITS.

Research on adaptive thermal control system of space optical remote sensor

The traditional thermal control system of the space optical remote sensor is mainly based on passive thermal control and supplemented by active thermal control of electric heater. But with the development of the remote sensor in the direction of multi-task and multi-function, the thermal control system needs to meet the requirements of low thermal control resource consumption under the condition of multi heat source and large heat load, and high adaptability under the condition of multi attitude complex orbit. The traditional thermal control system can not satisfy these new requirements. In this paper, a new adaptive thermal control system is studied. A geostationary orbit camera as an example is taken to compare the design scheme of the traditional thermal control system and the new thermal control system. The simulation results show that the new thermal control has the advantages of more optimized system resources and stronger temperature adaptability under complex tasks, which provides a new idea for the subsequent thermal control design of complex large space optical remote sensor.

A Developed H-Bridge Cascaded Multilevel Inverter with Reduced Switch Count

Multilevel Inverter integrates several Direct Current (DC) sources to produce a single-phase Alternating Current (AC) waveform that can be used to meet the domestic and commercial power demand. This article introduces a novel Multi Source Cascaded Multilevel Inverter with a reduced number of switches for the efficient use of DC voltage sources. The conversion efficiency can be increased by the presented topology which is simple in design to overcome the significant switching losses in the power electronics devices. Optimal Firing Angle and Phase Opposition Disposition Pulse width Modulation Techniques were used to reduce the harmonics at the desired output of the inverter and also to improve the power quality of the presented topology. This article also proposes two Asymmetric Multilevel Inverter Topologies. A comparison has been made, on the number of switches required and the efficiency of the inverters to differentiate the presented Topologies from other topologies of the multilevel inverter. Finally, the performance characteristics of the presented topologies have been designed and investigated using MATLAB Simulation. Simulation results were validated using an experimental setup.

Red algae natural products for prevention of lipopolysaccharides (LPS)-induced liver and kidney inflammation and injuries.

Background: The liver and kidney inflammation due to bacterial infection is one of the most common pathological problems leading to tissue damage or disease. In many liver and kidney disorders, which represent serious global health burden with a high economic cost, oxidative stress-related inflammation and apoptosis are important pathogenic components, finally resulting in acute liver and/or kidney failure. Erythropoietin and its analogues are well known to influence the interaction between apoptosis and inflammation in liver and kidney. Objective: The aim of the present study is to investigate and clarify the effect of Galaxaura oblongata (G. oblongata) red algae on lipopolysaccharides (LPS)-induced acute liver and kidney injury of mice with endotoxemia and associated molecular mechanism from inflammation, apoptosis and oxidative stress levels. Results: The current study cleared out that treatment of rats with the G. oblongata extract prior to LPS injection significantly lowered serum cytokines, including NF-κB, MPO and LPO, and improved liver apoptosis through suppressing protein tyrosine kinase signaling pathway, and that may be due to antibacterial activity as well antioxidant capacity of G. oblongata extract. Conclusion: The present study was cleared out the possibility of administration of G. oblongata red algae as a multi products source for biotechnological, medical, nutraceutical and pharmaceutical applications due to highly antioxidant and anti-inflammatory capacities even although more investigations are required for separating, purifying and characterizing these bioactive compounds.

Quantifying and Evaluating the Cultivated Areas Suitable for Fallow in Chongqing of China Using Multisource Data

The quantitative evaluation of the suitability of land fallow is of great significance to the effective implementation of fallow system in rural China. The purpose of this study is to systematically evaluate the cultivated areas suitable for fallow in Chongqing, China. The results show that: (1) a comprehensive index of cultivated land fallow (ILF) was developed by employing a series of multi—source data, and the ILF has been proven as an effective proxy to identify the cultivated areas suitable for fallow; (2) cultivated land with ILF values above the average value accounts for 34.38% (9902 km2) of the total cultivated land; (3) the ILF is negatively correlated with the population density, transportation proximity, and proportion of inclined area. This study argued that the ILF can reflect the cultivated areas suitable for fallow in Chongqing and can provide guidance for the spatial distribution of cultivated land fallow. The findings indicated that the differences in geographical elements between karst and non—karst areas must be further investigated, and the evaluation accuracy of the cultivated areas suitable for fallow must be improved.

Relative Study of Ni Sulfides Synthesized from Single and Multi Source Precursors for Photocatalytic and Battery Applications

Chalcogenide nanoparticles and their morphologies have contributed towards the most prominent field of nano-chemistry by the virtue of their ease of fabrication and assorted appositeness. Herein, we demonstrate the two antithetic pathways viz., single source (S-S) and multisource (M-S) precursors to fabricate nano-material. The motive of the stated research work was to identify any alteration in morphologies of the resulting product by shifting the fabrication pathways. Wherefore, to deduct the results, photocatalytic activity (covered by full spectrum versus four contrasting dyes) and battery application (electrochemical discharge/charge at voltage limits of 0.01 – 3.0 V against Li/Li + ) of both materials have been executed. The nano-material gathered from S-S protocol has an immense exterior area that acknowledges the photocatalytic activity rather than the product obtained from M-S protocol.

Multi source retinal fundus image classification using convolution neural networks fusion and Gabor-based texture representation

Glaucoma is one of the most known irreversible chronic eye disease that leads to permanent blindness but its earlier diagnosis can be treated. Convolutional neural networks (CNNs), a branch of deep learning, have an impressive record for applications in image analysis and interpretation, including medical imaging. This necessity is justified by their capacity and adaptability to extract pertinent features automatically from the original image. In other hand, the use of ensemble learning algorithms has an important impact to improve the classification rate. In this paper, a two-stage-based image processing and ensemble learning approach is proposed for automated glaucoma diagnosis. In the first stage, the generation of different modalities from original images is adopted by the application of advanced image processing techniques especially Gabor filter-based texture image. Next, each dataset constructing from the corresponding modality will be learned by an individual CNN classifier. Aggregation techniques will be then applied to generate the final decision taking into account the outputs of all CNNs classifiers. Experiments were carried out on Rime-One dataset for glaucoma diagnosis. The obtained results proved the superiority of the proposed ensemble learning system compared to the existing studies with classification accuracy of 89.63%.

Improved loss function strategy for multi source face image retrieval

Improved loss function strategy for multi source face image retrieval

Multi source retinal fundus image classification using convolution neural networks fusion and Gabor-based texture representation

Glaucoma is one of the most known irreversible chronic eye disease that leads to permanent blindness but its earlier diagnosis can be treated. Convolutional neural networks (CNNs), a branch of deep learning, have an impressive record for applications in image analysis and interpretation, including medical imaging. This necessity is justified by their capacity and adaptability to extract pertinent features automatically from the original image. In other hand, the use of ensemble learning algorithms has an important impact to improve the classification rate. In this paper, a two-stage-based image processing and ensemble learning approach is proposed for automated glaucoma diagnosis. In the first stage, the generation of different modalities from original images is adopted by the application of advanced image processing techniques especially Gabor filter-based texture image. Next, each dataset constructing from the corresponding modality will be learned by an individual CNN classifier. Aggregation techniques will be then applied to generate the final decision taking into account the outputs of all CNNs classifiers. Experiments were carried out on Rime-One dataset for glaucoma diagnosis. The obtained results proved the superiority of the proposed ensemble learning system compared to the existing studies with classification accuracy of 89.63%.

Remaining Useful Life Prediction of Nonlinear Wiener Process-Based Degradation Model Based on Multi Source Information with Considering Random Effects

Accurate parameters estimation is the premise of accurate remaining useful life (RUL) prediction. This paper proposes a RUL prediction method of nonlinear Wiener process based on multi source information with considering random effects. First, a nonlinear Wiener process with considering random effects is used to model the degradation process of equipment. Then, according to the nature of parameters estimation, nonlinear parameter can be obtained based on historical degradation data. After that, the expectation maximization (EM) algorithm is used to calculate fixed parameter and random coefficient in model with fusing prior degradation information and prior failure time data information. Finally, fatigue crack data are used for experimental verification. Compared with the method based on historical degradation data or failure time data, the method based on multi source information with considering random effects can effectively improve the accuracy of parameters estimation and RUL estimation.

Assessing the performance of vehicles powered by battery, fuel cell and ultra-capacitor: Application to light-duty vehicles and buses

As alternative vehicle technologies gain more importance in the market, this work assesses the possibility of a multi power source vehicle configuration by evaluating the performance of an electric vehicle powered by battery (BEV), fuel cell (FCEV), ultra-capacitor (UC) and combination of the former. A flexible vehicle simulation model was developed in MATLAB-Simulink and vehicle performance was evaluated in various 1 Hz certified cycles, enabling the assessment of light duty and heavy-duty vehicles powered by various power sources. The developed model accurately estimates energy consumption and range of passenger vehicle with an average absolute error of less than 4% and 2% for the electric bus. The study showed that BEV has the least energy consumption (23%), followed by FCEV (65%) compared to internal combustion engine (ICE) vehicles in real world conditions. Regarding the combination of energy sources, an increase in range by 10% is estimated when battery is combined with fuel cell, while combining ultra-capacitor with battery enables a lifetime extension of battery life by 10%, with negligible change in range. Combining secondary sources with fuel cell shows a reduction of total fuel cell capacity by 40% for the same operation. Analysis on ultra-capacitor showed negative response with light duty vehicle, while for buses the usage of batteries shows positive results with negative impacts on cost and recharging time. Ultra-capacitors are highly recommended for short-frequent trips with fast recharging and a life of 20 years, while fuel cells as a primary energy source are recommended for the long-range trips in coaches and trucks.

Multi Source Bidirectional DC/DC Converter by Using PV-Wind-Battery based Integration for Domestic Applications

Multi Source Bidirectional DC/DC Converter by Using PV-Wind-Battery based Integration for Domestic Applications

Urban resilience assessment based on contradiction between supply and demand of the daily activity–environment system: A case study on Nanjing, China

In addition to safety and risk issues, urban resilience research should focus more comprehensive and universal contradictions. Considering the main contradictions of Chinese urban development, and the connotation of urban resilience, a theoretical framework is constructed based on the contradiction between supply and demand of the daily activity–environment system. Furthermore, an assessment index system of urban resilience is also developed that considers both volume and quality of demand and supply and has a grade standard. Finally, utilizing multi–source geographic big data, Nanjing is taken as a case study, the spatial characteristics and optimization path of urban resilience are identified. The main conclusions are as follows: (1) The activity–environment system resilience presents a “center–periphery” sprawling spatial structure, and it is mainly at the level of “reluctant resilience” and “almost lack of resilience”. (2) The evolution of the activity–environment system resilience is still absolutely volume driven, and the positive drive of relative quality is limited or even reversed. In addition, all the bilateral local spatial autocorrelations are generally represented as “center–periphery” separated spatial structures, but it is not always consistent with the overall trend. (3) For the governance of urban resilience, it is necessary to focus on common improvement and matching of absolute volume and relative quality in contents, orderly flow, accumulation and dispersion of supply and demand in ideas, and the strong support of new ideas and technologies in methods.

Modelling of plug-in hybrid electric vehicle (PHEV) with multi source

Abstract In this paper, we are discussing how to implement the efficiency of an Electrical Vehicle. Nowadays automobile’s are running by using gasoline as a fuel such as petrol, diesel, etc. By using this gasoline, the cost of the fuel is increasing and they release Chlorofluorocarbon (CFC). Because of these Chlorofluorocarbons (CFC), the atmosphere will be getting polluted. To overcome this problem we are moving into the vehicles which are consuming electrical energy as a fuel. The types of these vehicles are Electric Vehicle (EV), Hybrid Electric Vehicle (HEV), Plug-in- Hybrid Electric Vehicle (PHEV). The batteries used in these electric vehicles are Lead-acid battery, Nickel-Metal Hydride battery, Lithium-Ion battery, Ultracapacitors. This pollution can be controlled by using electric vehicles, and also at the same time the noise polluted by these vehicles is very less when compared to gasoline vehicles, and also they can drive with greater speed.