Higher Output Values Research Articles

The Effect of Using Different Refrigerants on System Performance in Two-Stage Organic Rankine Cycle

In this study, energy analysis of a double-stage Organic Rankine Cycle (ORC) was performed using the Engineering Equation Solver program (EES). In the first and second stages, eight different organic working fluids (R134a, R410a, RC318, R407c, R22, R23, R116, and R218) were used in pairs for certain temperature limits. Choosing a suitable refrigerant or refrigerant pair is crucial for the ORC’s high thermal efficiency and net work output value. This study aims to determine the effect of working fluid on system efficiency and find out the most suitable working fluid pair. The results showed that the highest net power output and the highest thermal efficiency were obtained from the R23+R23 pair. It was also observed that the lowest net power output from the RC318+RC318 pair and the lowest thermal efficiency was obtained from the R218+R218 pair.

Identification of SNPs associated with disease resistance in juveniles of Sinonovacula constricta using RNA-seq and high-resolution melting analysis

Sinonovacula constricta is one of the important economic bivalves in the world with high output value. However, vibriosis is a serious threat to the razor clam aquaculture industries, especially Vibrio parahaemolyticus. Molecular breeding such as marker-assisted selection or genomic selection is an efficient method for genetic improvement of disease resistance. In this study, the resistant and susceptible juvenile clams were evaluated according to the survival time after V. parahaemolyticus challenge and the two groups were genotyped by RNA sequencing technology to develop disease-resistant single nucleotide polymorphism (SNP) markers. The reference transcriptome was de novo assembled by Trinity, containing a total of 146,651 unigenes and 40,574 unigenes annotated. Almost 2 million SNPs were called from the two groups, of which, 23,970 SNPs showed significant allelic imbalance between groups (P valve <0.05). As shown by functional annotation, 396 SNPs were selected as significantly immune-related SNPs, which presented in immune-related genes participating in pathogen infection. It is interesting that significant SNPs in ABC transporters pathways were enriched, and some of SNPs located in ABC transporter genes were exclusive in the susceptible group indicating they maybe deleterious, which can be used as biomarker to distinguish disease-susceptible individuals. Six SNPs were further validated by High-resolution melting analysis in wild population, and five SNPs were verified successfully, which were correlated significantly with disease. These single nucleotide polymorphisms located in coding regions can be applied in the further studies elucidating the molecular mechanisms of immune responses. And the SNPs identified in this study could be used as molecular markers for molecular breeding of disease resistance in S. constricta.

Analysis of the application of refined management in engineering construction management based on the Computer Dynamic Network System

At present, China’s construction engineering field shows a trend of high output value, low profit input and small output. The main reason for this problem is the serious shortage of construction engineering management, which makes the enterprise have no method to reduce production cost and input. Therefore, the construction and construction industry should apply the fine management in the development, which is of great importance to the production, cost reduction and efficiency enhancement in the actual construction process. Using computer network technology and database technology to construct a computer dynamic network system, based on the system, this paper discusses the application of fine management in the construction process management, and elaborates on the economic management application strategy for cost management and quality management in the project production.

东北老工业基地产业结构与用水结构关系——以辽宁省本溪市为例

为破解东北经济社会发展受水资源承载力刚性约束的迷局，以典型老工业基地辽宁本溪市为例，通过产业结构区位熵明确本溪市各产业在全国的发展水平，采用灰色关联度、结构协调度分析产业结构和用水结构的相关程度和协调程度，并通过结构偏差系数对各产业间和行业间的协调程度进行对比分析。结果表明：从2008-2017年，本溪市一产发展稳定，二产在经历过大幅下跌之后缓慢增长，三产在2016年之后成为本溪市的支柱产业；三大产业比例由2008年的0.06 ∶ 0.60 ∶ 0.34调整为2017年的0.06 ∶ 0.44 ∶ 0.50，曾经占主导优势的重工业及化工业都呈现下降趋势，产业结构发生转变。三大产业平均用水量比例由2008年的0.39 ∶ 0.59 ∶ 0.02 调整为2017年的0.41 ∶ 0.51 ∶ 0.07，总用水量减少了1/4以上；规模以上行业中，大部分行业的用水量随着产值的增加而增加，需要进一步转换生产工艺；产值最高的黑色金属冶炼和压延加工业从水资源高效利用角度可作为大力扶持发展的产业。行业生产规模比较大的黑色金属矿采选业、医药制造业、非金属矿物制品业和黑色金属冶炼和压延加工业等产业与用水的结构逐渐朝着均衡的状态发展，仍需要一定时间才能达到协调。;To clarify the interaction and response relationship between industrial structure and water consumption structure in Benxi City, the location entropy, grey correlation degree, coordination degree of industrial structure and water structure and structural deviation coefficient were analyzed. The results are as follows. From 2008 to 2017, the development of primary industry in Benxi was stable, the secondary industry grew slowly after a sharp decline, and the tertiary industry became the pillar industry of Benxi after 2016. The proportion of industries was adjusted from 0.06 ∶ 0.60 ∶ 0.34 in 2008 to 0.06 ∶ 0.44 ∶ 0.50 in 2017. Heavy industry and chemical industry, which used to be dominant in the past, showed a downward trend, and the industrial structure has changed. The average water consumption ratio of the three industries was adjusted from 0.39 ∶ 0.59 ∶ 0.02 in 2008 to 0.41 ∶ 0.51 ∶ 0.07 in 2017 and the total water consumption decreased by more than one fourth. In the industries above designated size, the water consumption of most industries increased with the increase of output value, and the production process should be further transformed; Smelting and Pressing of Ferrous Metals, with the highest output value, can be used as an industry to support the development from the perspective of water resources development and utilization. Ferrous Metals Mining and Dressing, Medical and Pharmaceutical Products, Nonmetal Minerals Products and Smelting and Pressing of Ferrous Metals industries with relatively large production scale gradually developed towards a balanced state of water use structure, and it still needs some time to achieve coordination.

Modeling of CIGS single–junction solar cell using multiple quantum well structure with enhanced efficiency

Multiple quantum wells (MQWs) are incorporated in the standard CIGS single–junction solar cell. The aim of the present study is to enhance the efficiency of the solar cell by increasing the short circuit current (Jsc) while preserving the open circuit voltage (Voc). The simulation process was initiated by modeling of a standard CIGS solar cell followed by optimization of the thickness for different layers to achieve the highest efficiency. Then, using k.p and QWELL models in ATLAS Silvaco software, a single QW in the cell with different widths is modelled. After that, the concentration of Ga is varied for bandgap tuning. The modelled solar cell with optimized Ga concentration and QW width, showed higher output values than the conventional sample. Addition of more QWs resulted in higher Jsc and the efficiency enhancement. An excellent efficiency of 24.23% along with privileged output parameters were attained for the single–junction CIGS solar cell possessing six back–to–back QWs.

Molecular dynamics simulation as a tool for prediction of the properties of TiO2 and TiO2:MoO3 based chemical gas sensors

Fast and simple molecular dynamics simulation method was used to investigate the interaction of water, hydrogen, methane, and ethanol molecules with {100} set atomic planes of anatase TiO2 and α-MoO3 at 300 K and 573 K. Preliminary molecular simulation of gas molecules interaction with oxide surface provides an opportunity to eliminate empirical search of the oxide material with preassigned gas sensing properties. Facilities of molecular dynamics simulation approach without involving time-consuming quantum chemical calculations turn to be sufficient for this purpose. From the molecular simulation results it followed, that the most energy-efficient interaction of hydrogen molecules turned to be with (001) anatase plane. The less energy-efficient and localized among all the investigated processes was the interaction of methane molecules both with anatase and MoO3 surfaces. Interaction of water molecules was more energy-efficient with anatase surface than with MoO3 surface. Molecular dynamics simulation results were confronted with experimental results on gas sensing properties of one-electrode thermocatalytic chemical gas sensors on the basis of anatase TiO2 and TiO2:MoO3 composite materials. Predicted low output signal value of the sensors towards CH4, high output value towards hydrogen with its decrease at high MoO3 content in TiO2:MoO3 composite and sufficiently high sensitivity towards ethanol were proved in practice.

Synthesis, structural features and gas-sensing properties of highly defective titanium dioxide

By the chemical reduction of sol-gel synthesized TiO2, nanoscale black titanium dioxide in anatase modification, characterized by the presence of large quantity of oxygen vacancies and pronounced extrinsic absorption, was obtained. Semiconducting chemical gas sensors on the basis of the obtained highly defective titanium dioxide demonstrate high output value towards ethanol vapor. The output value significantly increases additionally under actinic radiation conditions.

W‐Band MMIC chipset in 0.1‐μm mHEMT technology

We developed a 0.1-μm metamorphic high electron mobility transistor and fabricated a W-band monolithic microwave integrated circuit chipset with our in-house technology to verify the performance and usability of the developed technology. The DC characteristics were a drain current density of 747 mA/mm and a maximum transconductance of 1.354 S/mm; the RF characteristics were a cutoff frequency of 210 GHz and a maximum oscillation frequency of 252 GHz. A frequency multiplier was developed to increase the frequency of the input signal. The fabricated multiplier showed high output values (more than 0 dBm) in the 94 GHz–108 GHz band and achieved excellent spurious suppression. A low-noise amplifier (LNA) with a four-stage single-ended architecture using a common-source stage was also developed. This LNA achieved a gain of 20 dB in a band between 83 GHz and 110 GHz and a noise figure lower than 3.8 dB with a frequency of 94 GHz. A W-band image-rejection mixer (IRM) with an external off-chip coupler was also designed. The IRM provided a conversion gain of 13 dB–17 dB for RF frequencies of 80 GHz–110 GHz and image-rejection ratios of 17 dB–19 dB for RF frequencies of 93 GHz–100 GHz.

Human motion interactive mechanical energy harvester based on all inorganic perovskite-PVDF

Benefited with the advantage of easy assembly and conformal structure, flexible and self-powered piezoelectric nanogenerators (PNGs) have become a sustainable and accessible energy alternative. Here, novel piezoelectric sensor is fabricated by a composite of room temperature processed all-inorganic cesium lead bromide (CsPbBr 3 ) perovskite rod and polyvinylidene fluoride (PVDF) nanofiber. CsPbBr 3 enables nucleation of electroactive β phase in PVDF >90% and makes it suitable for piezoelectric energy harvesting. Piezoelectric energy generation from the devices has been investigated under several simple human movements like hammering by hand, finger touch, toe pressing, bending by arm, etc. Optimized CsPbBr 3 -PVDF composite (with 5 wt% of CsPbBr 3 loading) based PNG delivered an output power 4.24 mW with high open-circuit voltage of 120 V and short-circuit current of 35 μA. Such high output value for the composite sample suggests much improved energy conversion efficiency as compared to the building blocks separately. Fatigue test of the PNG under continuous mechanical impact (over 4 months) showed its possibilities as a robust wearable mechanical energy harvester. This device is also able to light up several commercial LEDs. Increase in output values is attributed to the improved polarization in PVDF by CsPbBr 3 incorporation. Additionally, photosensitivity of the composite is demonstrated under light, which indicates its potential as photodetector. Considering the photoresponse and electroactive features, a new class of self-powered photoactive piezoelectric energy harvester has also been fabricated. Such results highlight the rational design of all inorganic perovskite based nanoforms in maximizing device performance and thereby providing a useful pathway to develop new materials for piezo-phototronics. • CsPbBr 3 perovskite has been utilized as a filler material in piezoelectric nanogenerator in PVDF matrix. • Strong cyan emission capability of the device is useful in optoelectronic fields. • PNG delivered an output power 4 mW with high open-circuit voltage of 120 V and a short-circuit current 35 μA. • DFT shows the change of electronic property in composite due to intercalation between Pb and F atom.

Role of brassinosteroids in horticultural crops (Reviews)

With the progress of chemical synthesis technology, structurally modified brassinosteroids (BRs) with greater stability, under field conditions have been synthesized on a commercial scale and registered as plant growth regulators for specific horticultural crops. In both fundamental and application-oriented research, BRs and their analogues play prominent roles in various physiological processes including, seed development and germination, flower sex expression, fruit development, improvement of quantity and quality of crops, and resistance to various biotic and abiotic stresses. It is worthy to note here that the involvement of BRs in plant protection from adverse environmental stress and pesticides seems to have good prospects, since BRs appear nontoxic and environmentally friendly. It is well known that horticultural crops have a great variety of produce organs as well as high yield and output values. Moreover, their production is susceptible to sub-optimum environmental conditions, especially in facilities cultivation. Thus, practical application of BRs to horticultural crops for enhancing crops production and protection may have a promising prospect in the near future.

Rural finance, scale management and rural industrial integration

PurposeThe purpose of this paper is to empirically investigate the effect of rural finance on industrial integration of rural primary, secondary and tertiary industries.Design/methodology/approachUsing household-level data collected by Third National Agricultural Census and the provincial-level data collected from Wind database, the authors estimated the impacts of rural finance on rural industrial integration using Logit and Probit regression models. Further, the authors examined how the effect of rural finance varies with the age and education of householders, and with household and provincial characteristics by investigating the moderating effect.FindingsThe findings show that rural finance has a significant and positive effect on promoting farmers’ participation in new agricultural management organizations. This effect is more obvious in families whose householders are 40–50 years old, or families that have more educated members. This is because the middle-aged or educated people are more willing to accept and take part in industrial integration. The results further indicate that rural finance has a greater effect on industrial integration in provinces with a high degree of marketization, and in provinces with the high output value of industries and services in agricultural intermediate input.Originality/valueThe authors investigated the impact of rural finance on rural industrial integration empirically, and this topic is rarely covered before. The findings of this study also enrich the literature on financial development and economic growth as well as provide policy suggestions on how to promote rural industrial integration.

Convolutional neural networks based indoor Wi-Fi localization with a novel kind of CSI images

Indoor Wi-Fi localization of mobile devices plays a more and more important role along with the rapid growth of location-based services and Wi-Fi mobile devices. In this paper, a new method of constructing the channel state information (CSI) image is proposed to improve the localization accuracy. Compared with previous methods of constructing the CSI image, the new kind of CSI image proposed is able to contain more channel information such as the angle of arrival (AoA), the time of arrival (TOA) and the amplitude. We construct three gray images by using phase differences of different antennas and amplitudes of different subcarriers of one antenna, and then merge them to form one RGB image. The localization method has off-line stage and on-line stage. In the off-line stage, the composed three-channel RGB images at training locations are used to train a convolutional neural network (CNN) which has been proved to be efficient in image recognition. In the on-line stage, images at test locations are fed to the well-trained CNN model and the localization result is the weighted mean value with highest output values. The performance of the proposed method is verified with extensive experiments in the representative indoor environment.

Investigating the prospect of micro-energy generation in S.Anisatum Dye-sensitized solar cells (DSCs)

Energy is a requirement for daily existence and a necessity for driving all technology. Thus, indices for generating energy will always be a valid reason for research. It therefore stands to reason that; numerous experimental effort has been devoted to the quest of energy generation. This quest has witnessed a lot of progression, newer innovations being an improvement over older editions. Recent energy studies have shifted its focus from dominant monocrystalline silicon solar cells to organic material sources. This is in the wake of the high expenses incurred in installation of any silicon solar technology. Although the economy of scale applies to increased use of silicon panels, it does not delete the looming future threat of disposal of expired silicon solar panels. This brings to fore, a need for an energy substitute that possesses the salient attributes of monocrystalline silicon solar cells without the limitations. Amongst all the alternatives, the low cost and environmentally benign dye-sensitized solar cells (DSCs) has remained prominent. Other desirable characteristics of dye-sensitized solar cells is all-year availability of raw materials, capacity to perform under low diffuse light conditions, ability to withstand extreme conditions contrary to their silicon counterparts are sterling qualities which necessitate detailed enquiry into dye-sensitized solar technology. In spite of these excellent properties, wide adoption of DSCs is limited by its poor output efficiency relative to monocrystalline silicon solar cells. The significance of this research is thus to investigate optical spectral responses of S.Anisatum dye-sensitized solar cells with an objective to analyze its photovoltaic output and prospect for micro-energy production. Preliminary phytochemical analysis portends S.Anisatum dye as rich in phenols. UV/VIS spectroscopy reveals a porphyrin characteristic absorbance. This research corroborates previousstudies such as photovoltaic output of B.spectabilis DSCs to different electrolytes. The spectral responses revealed 0.065 mA, 140 mV, 5.32 X 10−6 W and 0.86 % respectively as Isc, Voc, Pmax and η highest output value. Although this result is comparatively low to monocrystalline silicon panels, it conforms with existing standard porphyrin efficiency. This study provides impetus for further studies of S.Anisatum DSCs co-sensitization with other dyes and finds application in modelling of material of synthetic origin.

Construct the prediction model for China agricultural output value based on the optimization neural network of fruit fly optimization algorithm

Since agriculture is the foundation of a country and the industry that people depend on for life, it is particularly important for the development of national economy, and it has a higher output value than forestry, fishery and animal husbandry, so it occupies a very important position in the economic development of a country. The aim of this paper is to strengthen the capacity of prediction mode for total agricultural output value. This paper provides relevant government departments a reference and solves the problem of the lack of predictive ability of prediction mode for total agricultural output value in previous study. Different from previous literature, this paper adopts the new CFOA to optimize the parameters of GRNN, which contains innovative and reference value in some degree. Besides the way to validate this new model is to take the agricultural output value of the past years as a research sample and test it repeatedly. The study results have indicated that the total agricultural production value accounts for a higher proportion of agriculture, forestry, fishery and animal husbandry and the proportion tends to decline year by year; it can be found through 4 evaluation indexes that the prediction model that optimizes the smoothing parameters of GRNN through CFOA has a better predictive ability than the other two prediction models.

Investigation of Fuel Characterisation of Waste Sludge from Sewage Treatment Plants (STP)

Sewage treatment plants (STP’s) throughout Malaysia are facing escalating issues on sewage disposable and environmental impact. Investigation on the sewage sludge for possible fuel formulation as renewable energy is being considered. The characterization of waste sludge on its volatility, High Heating Value and Energy output value will provide a preliminary finding for usage as potential biomass fuel. Co-combustion of sewage sludge and coal provide another formulation for potential biomass fuel depend on its technical viability and economical input.

Spatial-temporal change in urban agricultural land use efficiency from the perspective of agricultural multi-functionality: A case study of the Xi’an metropolitan zone

The excessive expansion of urbanized areas has resulted in haphazard land utilization, immoderate consumption of superior agricultural land and water resources, significant fragmentation of agricultural landscape, and gradual deterioration of the agro-ecological environment. Combined, these factors cause poor land use efficiency. Under these circumstances, comprehensively assessing land use efficiency for urban agriculture is a key issue in land use research. Currently, evaluation methods for agricultural land use efficiency narrowly concentrate on aspects of economic input and output. However, urban agro-ecosystems can provide diverse economic, social, and ecological services and functions. In particular, the social and ecological services and functions originating from agricultural land, which have a higher value than economic services, play a significant role in ensuring regional social, ecological, and environmental security. However, recent research has rarely taken these benefits into consideration. Therefore, land use value has been greatly underestimated, which has resulted in mishandled and poor land use policies. In this study, we apply Landsat imagery and social and economic statistical data for the Xi’an metropolitan zone (XMZ) to investigate agricultural multi-functionality. We develop an evaluation framework for urban agricultural land use efficiency and identify agro-ecosystem services and functions as important outputs from agricultural land. The land use efficiency of urban agriculture is then evaluated using ecosystem services models, providing a mechanism for assessing spatial-temporal changes in land use efficiency in the XMZ from 1999 to 2015. Four important conclusions are reached from this analysis. First, the rapid urbanization and agricultural transformation from traditional cereal cultivation to modern urban agriculture has resulted in steadily increasing costs, outputs, and land use efficiency of urban agriculture. The total output value increased 41% and land use efficiency per hectare increased by 33.13% on average. Second, the spatial patterns of comprehensive output and land use efficiency were dominated by economic outputs from agricultural land. Areas near cities, which are dominated by orchard and arable land, provide more economic functions. These areas support and regulate services due to the transformation from extensive cereal production to intensive modern urban agriculture; therefore, they have higher output value and land use efficiency. In contrast, areas distant from cities, towns, and high traffic roads, namely, remote rural areas, provide more support and regulating services, but have relatively lower economic function due to inaccessibility to urban markets and slow agricultural transformation. Therefore, these areas have lower output value and land use efficiency. The spatial change in agricultural output and land use efficiency in urban areas is strongly dependent on the degree of urbanization and agricultural transformation. Third, the total output value and land use efficiency of urban agriculture measured with our approach are much higher than evaluations using traditional methods. However, the spatial patterns measured using the two approaches are in agreement. The evaluation framework integrates ecological services and economic and social functions into a comprehensive output from agricultural land. This approach is more methodical and accurate for evaluating the comprehensive efficiency of land use based on quantities and spatial scale because they are at the pixel scale. Finally, the evaluation results have important implications for enhancing current agricultural subsidies and even implementing ecological payment policies in China. Most importantly, they can be directly applied to agricultural transformation regulations, decision- making, and guidance for rational land utilization.

ConFi: Convolutional Neural Networks Based Indoor Wi-Fi Localization Using Channel State Information

As the technique that determines the position of a target device based on wireless measurements, Wi-Fi localization is attracting increasing attention due to its numerous applications and the widespread deployment of Wi-Fi infrastructure. In this paper, we propose ConFi, the first convolutional neural network (CNN)-based Wi-Fi localization algorithm. Channel state information (CSI), which contains more position related information than traditional received signal strength, is organized into a time-frequency matrix that resembles image and utilized as the feature for localization. The ConFi models localization as a classification problem and addresses it with a five layer CNN that consists of three convolutional layers and two fully connected layers. The ConFi has a training stage and a localization stage. In the training stage, the CSI is collected at a number of reference points (RPs) and used to train the CNN via stochastic gradient descent algorithm. In the localization stage, the CSI of the target device is fed to the CNN and the localization result is calculated as the weighted centroid of the RPs with high output value. Extensive experiments are conducted to select appropriate parameters for the CNN and demonstrate the superior performance of the ConFi over existing methods.

The associate impact of individual internal experiences and reference groups on buying behavior: A case study of animations, comics, and games consumers

Among the entertainment and media market, it can be observed that animations, comics, and video games (hereinafter abbreviated as ACG) have the highest output value and most market influence. Moreover, ACG also incorporates various industries and creates many derivative products. As the ACG industry emphasizes acousto-optics, imagery, and storylines, personal impressions derived from consumer experiences will influence consumer decisions. In addition, the ACG industry is mainly marketed towards younger age groups, with younger people being the main consumers; as such, these consumers’ decisions are more easily affected by peer behavior.This study aims to analyze the effects of internal cognitions and external influences on buying behavior of ACG consumers by applying the uncomplicated decision tree data mining algorithm. We analyze and develop the target attributes on measures of customer loyalty for ACG industry to set up the decision trees from the collected questionnaire data. The decision tree data mining method is applied to analyze the hidden association rules between the target attributes (i.e., consumer loyalty) and the critical influencing factors of consumer’s internal impressions and external influences for ACG consumers. The results and suggestions of this paper can be used as a reference for enterprises in the ACG industry to help with business policies concerning products’ extensional design, marketing, and CRM, and to further strengthen customer satisfaction and loyalty, thus increasing company profits.

Solution processed inorganic V2O x as interfacial function materials for inverted planar-heterojunction perovskite solar cells with enhanced efficiency

An inverted planar heterojunction perovskite solar cell (PSC) is one of the most competitive photovoltaic devices exhibiting a high power conversion efficiency (PCE) and nearly free hysteresis in the voltage–current output. However, the band alignment between the transport materials and the perovskite absorber has not been optimized, resulting in a lower open-circuit voltage (V oc) than that of regular PSCs. To address this issue, we tune the band alignment in perovskite photovoltaic architecture by introducing bilayer structured transport materials, e.g., the hole transport material poly(ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS)/V2O5. In this study, solution processed inorganic V2O x interlayer is incorporated into PEDOT:PSS for achieving improved film surface properties as well as optical and electrical properties. For example, the work function (WF) was changed from 5.1 to 5.4 eV. A remarkably high PCE of 17.5% with nearly free hysteresis and a stabilized efficiency of 17.1% have been achieved. Electronic impedance spectra (EIS) demonstrate a significant increase in the recombination resistance after introducing the interlayer, associated with the high V oc output value of 1.05 V. Transient photocurrent and photovoltage measurements indicate that a comparable charge transport process and an inhibited recombination process occur in the PSC with the introduction of the V2O x interlayer.

An Analytical Study on Reasoning of Extreme Learning Machine for Classification from Its Inductive Bias

Since extreme learning machine (ELM) was proposed, hundreds of studies have been conducted on this subject in various areas, from theoretical researches to practical applications. However, there are very few papers in the literature to reveal the reasons why in ELM classification the class with the highest output value is being chosen as the predicted class for a given input. In order to give a clear insight into this question, this paper analyzes the rationality of ELM reasoning from the perspective of its inductive bias. The analysis results show that the choice of highest output in ELM is reasonable for both binary and multiclass classification problems. In addition, to deal with multiclass problems ELM uses the well-known one-against-all strategy, in which unclassifiable regions may exist. This paper also gives a clear explanation on how ELM resolves the unclassifiable regions, through both analysis and experiments.