arXiv subjects

Yong Shi

Publications and source records attributed to Yong Shi.

At least 127 records · Page 7Linked to original sources

arXiv2019

A Pyramid Scheme Model Based on "Consumption Rebate" Frauds

There are various types of pyramid schemes which have inflicted or are inflicting losses on many people in the world. We propose a pyramid scheme model which has the principal characters of many pyramid schemes appeared in recent years: promising high returns, rewarding the participants recruiting the next generation of participants, and the organizer will take all the money away when he finds the money from the new participants is not enough to pay the previous participants interest and rewards. We assume the pyramid scheme carries on in the tree network, ER random network, SW small-world network or BA scale-free network respectively, then give the analytical results of how many generations the pyramid scheme can last in these cases. We also use our model to analyse a pyramid scheme in the real world and we find the connections between participants in the pyramid scheme may constitute a SW small-world network.

physics.soc-ph↗

arXiv2019

What drives the velocity dispersion of ionized gas in star-forming galaxies?

We analyze the intrinsic velocity dispersion properties of 648 star-forming galaxies observed by the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, to explore the relation of intrinsic gas velocity dispersions with star formation rates (SFRs), SFR surface densities ($\rm{Σ_{SFR}}$), stellar masses and stellar mass surface densities ($\rm{Σ_{*}}$). By combining with high z galaxies, we found that there is a good correlation between the velocity dispersion and the SFR as well as $\rm{Σ_{SFR}}$. But the correlation between the velocity dispersion and the stellar mass as well as $\rm{Σ_{*}}$ is moderate. By comparing our results with predictions of theoretical models, we found that the energy feedback from star formation processes alone and the gravitational instability alone can not fully explain simultaneously the observed velocity-dispersion/SFR and velocity-dispersion/$\rm{Σ_{SFR}}$ relationships.

astro-ph.GA↗

arXiv2019

The first 62 AGN observed with SDSS-IV MaNGA -- III: stellar and gas kinematics

We investigate the effects of Active Galactic Nuclei (AGN) on the gas kinematics of their host galaxies, using MaNGA data for a sample of 62 AGN hosts and 109 control galaxies (inactive galaxies). We compare orientation of the line of nodes (kinematic Position Angle - PA) measured from the gas and stellar velocity fields for the two samples. We found that AGN hosts and control galaxies display similar kinematic PA offsets between gas and stars. However, we note that AGN have larger fractional velocity dispersion $σ$ differences between gas and stars [$σ_{frac}=(σ_{\rm gas}-σ_{stars})/σ_{\rm stars}$] when compared to their controls, as obtained from the velocity dispersion values of the central (nuclear) pixel (2.5" diameter). The AGN have a median value of $σ_{\rm frac}$ of $<σ_{frac}>_{\rm AGN}=0.04$, while the the median value for the control galaxies is $<σ_{frac}>_{\rm CTR}=-0.23$. 75% of the AGN show $σ_{frac}>-0.13$, while 75% of the normal galaxies show $σ_{\rm frac}<-0.04$, thus we suggest that the parameter $σ_{\rm frac}$ can be used as an indicative of AGN activity. We find a correlation between the [OIII]$λ$5007 luminosity and $σ_{frac}$ for our sample. Our main conclusion is that the AGN already observed with MaNGA are not powerful enough to produce important outflows at galactic scales, but at 1-2 kpc scales, AGN feedback signatures are always present on their host galaxies.

astro-ph.GA↗

arXiv2018

A generalized concept-cognitive learning: A machine learning viewpoint

Concept-cognitive learning (CCL) is a hot topic in recent years, and it has attracted much attention from the communities of formal concept analysis, granular computing and cognitive computing. However, the relationship among cognitive computing (CC), concept-cognitive computing (CCC), CCL and concept-cognitive learning model (CCLM) is not clearly described. To this end, we first explain the relationship of CC, CCC, CCL and CCLM. Then, we propose a generalized concept-cognitive learning (GCCL) from the point of view of machine learning. Finally, experiments on some data sets are conducted to verify the feasibility of concept formation and concept-cognitive process of GCCL.

cs.AI↗

arXiv2018

A Novel Large-scale Ordinal Regression Model

Ordinal regression (OR) is a special multiclass classification problem where an order relation exists among the labels. Recent years, people share their opinions and sentimental judgments conveniently with social networks and E-Commerce so that plentiful large-scale OR problems arise. However, few studies have focused on this kind of problems. Nonparallel Support Vector Ordinal Regression (NPSVOR) is a SVM-based OR model, which learns a hyperplane for each rank by solving a series of independent sub-optimization problems and then ensembles those learned hyperplanes to predict. The previous studies are focused on its nonlinear case and got a competitive testing performance, but its training is time consuming, particularly for large-scale data. In this paper, we consider NPSVOR's linear case and design an efficient training method based on the dual coordinate descent method (DCD). To utilize the order information among labels in prediction, a new prediction function is also proposed. Extensive contrast experiments on the text OR datasets indicate that the carefully implemented DCD is very suitable for training large data.

cs.LG↗

arXiv2018

Research on Artificial Intelligence Ethics Based on the Evolution of Population Knowledge Base

The unclear development direction of human society is a deep reason for that it is difficult to form a uniform ethical standard for human society and artificial intelligence. Since the 21st century, the latest advances in the Internet, brain science and artificial intelligence have brought new inspiration to the research on the development direction of human society. Through the study of the Internet brain model, AI IQ evaluation, and the evolution of the brain, this paper proposes that the evolution of population knowledge base is the key for judging the development direction of human society, thereby discussing the standards and norms for the construction of artificial intelligence ethics.

cs.OH↗

arXiv2018

Mildly Suppressed Star Formation in Central Regions of MaNGA Seyfert Galaxies

Negative feedback from accretion onto super-massive black holes (SMBHs), that is to remove gas and suppress star formation in galaxies, has been widely suggested. However, for Seyfert galaxies which harbor less active, moderately accreting SMBHs in the local universe, the feedback capability of their black hole activity is elusive. We present spatially-resolved H$α$ measurements to trace ongoing star formation in Seyfert galaxies and compare their specific star formation rate with a sample of star-forming galaxies whose global galaxy properties are controlled to be the same as the Seyferts. From the comparison we find that the star formation rates within central kpc of Seyfert galaxies are mildly suppressed as compared to the matched normal star forming galaxies. This suggests that the feedback of moderate SMBH accretion could, to some extent, regulate the ongoing star formation in these intermediate to late type galaxies under secular evolution.

astro-ph.GA↗

arXiv2018

JINGLE, a JCMT legacy survey of dust and gas for galaxy evolution studies: I. Survey overview and first results

JINGLE is a new JCMT legacy survey designed to systematically study the cold interstellar medium of galaxies in the local Universe. As part of the survey we perform 850um continuum measurements with SCUBA-2 for a representative sample of 193 Herschel-selected galaxies with M*>10^9Msun, as well as integrated CO(2-1) line fluxes with RxA3m for a subset of 90 of these galaxies. The sample is selected from fields covered by the Herschel-ATLAS survey that are also targeted by the MaNGA optical integral-field spectroscopic survey. The new JCMT observations combined with the multi-wavelength ancillary data will allow for the robust characterization of the properties of dust in the nearby Universe, and the benchmarking of scaling relations between dust, gas, and global galaxy properties. In this paper we give an overview of the survey objectives and details about the sample selection and JCMT observations, present a consistent 30 band UV-to-FIR photometric catalog with derived properties, and introduce the JINGLE Main Data Release (MDR). Science highlights include the non-linearity of the relation between 850um luminosity and CO line luminosity, and the serendipitous discovery of candidate z>6 galaxies.

astro-ph.GA↗

arXiv2018

The MALATANG Survey: the L_gas-L_IR correlation on sub-kiloparsec scale in six nearby star-forming galaxies as traced by HCN J=4-3 and HCO^+ J=4-3

We present HCN J=4-3 and HCO^+ J=4-3 maps of six nearby star-forming galaxies, NGC 253, NGC 1068, IC 342, M82, M83, and NGC 6946, obtained with the James Clerk Maxwell Telescope as part of the MALATANG survey. All galaxies were mapped in the central 2 arcmin $\times$ 2 arcmin region at 14 arcsec (FWHM) resolution (corresponding to linear scales of ~ 0.2-1.0 kpc). The L_IR-L'_dense relation, where the dense gas is traced by the HCN J=4-3 and the HCO^+ J=4-3 emission, measured in our sample of spatially-resolved galaxies is found to follow the linear correlation established globally in galaxies within the scatter. We find that the luminosity ratio, L_IR/L'_dense, shows systematic variations with L_IR within individual spatially resolved galaxies, whereas the galaxy-integrated ratios vary little. A rising trend is also found between L_IR/L'_dense ratio and the warm-dust temperature gauged by the 70 μm/100 μm flux ratio. We find the luminosity ratios of IR/HCN(4-3) and IR/HCO^+(4-3), which can be taken as a proxy for the efficiency of star formation in the dense molecular gas (SFE_dense), appears to be nearly independent of the dense-gas fraction (f_dense) for our sample of galaxies. The SFE of the total molecular gas (SFE_mol) is found to increase substantially with f_dense when combining our data with that on local (ultra)luminous infrared galaxies and high-z quasars. The mean L'_HCN(4-3)/L'_HCO^+(4-3) line ratio measured for the six targeted galaxies is 0.9+/-0.6. No significant correlation is found for the L'_HCN(4-3)/L'_HCO^+(4-3) ratio with the SFR as traced by L_IR, nor with the warm-dust temperature, for the different populations of galaxies.

astro-ph.GA↗

arXiv2018

Diffusion Based Network Embedding

In network embedding, random walks play a fundamental role in preserving network structures. However, random walk based embedding methods have two limitations. First, random walk methods are fragile when the sampling frequency or the number of node sequences changes. Second, in disequilibrium networks such as highly biases networks, random walk methods often perform poorly due to the lack of global network information. In order to solve the limitations, we propose in this paper a network diffusion based embedding method. To solve the first limitation, our method employs a diffusion driven process to capture both depth information and breadth information. The time dimension is also attached to node sequences that can strengthen information preserving. To solve the second limitation, our method uses the network inference technique based on cascades to capture the global network information. To verify the performance, we conduct experiments on node classification tasks using the learned representations. Results show that compared with random walk based methods, diffusion based models are more robust when samplings under each node is rare. We also conduct experiments on a highly imbalanced network. Results shows that the proposed model are more robust under the biased network structure.

cs.LG↗

arXiv2018

The Physical Characteristics of Interstellar Medium in NGC 3665 with Herschel Observations

We present the analysis of the physical properties of the interstellar medium (ISM) in the nearby early-type galaxy NGC 3665, based on the far-infrared (FIR) photometric and spectroscopic data as observed by the Herschel Space Observatory. The fit to the spectral energy distribution reveals a high dust content in the galaxy, with the dust-to-stellar mass ratio of $M_{\rm dust}$/$M_\ast$ $\sim$ 1.1 $\times$ 10$^{-4}$ that is nearly three times larger than the mean value of local S0+S0a galaxies. For the ionized regions (H~\textsc{ii} regions), the electron density (n$_e$) is around 49.5 $\pm$ 11.9 cm$^{-3}$ based on the [N~\textsc{ii}]\,122\,\mum/[N~\textsc{ii}]\,205\,\mum\ ratio. For the photodissociation regions, the heating efficiency is in the range of 1.26 $\times$ 10$^{-3}$ and 1.37 $\times$ 10$^{-3}$ based on the ([C~\textsc{ii}$]+[$O~\textsc{i}]\,63\,\mum)/$L_{\rm TIR}$, which is slightly lower than other local galaxies; the hydrogen nucleus density and the strength of FUV radiation field are n $\sim$ 10$^{4}$ cm$^{-3}$ and G$_0$ $\sim$ 10$^{-0.25}$, respectively. The above results are consistent with the presence of weak AGN and a low level of star-forming activity in NGC 3665. Our results give strong support to the `morphological quenching' scenario, where a compact, massive bulge can stabilize amount of cool gas against star formation.

astro-ph.GA↗

arXiv2018

Re-visiting the extended Schmidt law: the important role of existing stars in regulating star formation

We revisit the proposed extended Schmidt law (Shi et al. 2011) which points that the star formation efficiency in galaxies depends on the stellar mass surface density, by investigating spatially-resolved star formation rates (SFRs), gas masses and stellar masses of star formation regions in a vast range of galactic environments, from the outer disks of dwarf galaxies to spiral disks and to merging galaxies as well as individual molecular clouds in M33. We find that these regions are distributed in a tight power-law as Sigma_SFR ~(Sigma_star^0.5 Sigma_gas )^1.09, which is also valid for the integrated measurements of disk and merging galaxies at high-z. Interestingly, we show that star formation regions in the outer disks of dwarf galaxies with Sigma_SFR down to 10^(-5) Msun/yr/kpc^2, which are outliers of both Kennicutt-Schmidt and Silk-Elmegreen law, also follow the extended Schmidt law. Other outliers in the Kennicutt-Schmidt law, such as extremely-metal poor star-formation regions, also show significantly reduced deviations from the extended Schmidt law. These results suggest an important role for existing stars in helping to regulate star formation through the effect of their gravity on the mid-plane pressure in a wide range of galactic environments.

astro-ph.GA↗

arXiv2018

Analysis of the Relation between Artificial Intelligence and the Internet from the Perspective of Brain Science

Artificial intelligence (AI) like deep learning, cloud AI computation has been advancing at a rapid pace since 2014. There is no doubt that the prosperity of AI is inseparable with the development of the Internet. However, there has been little attention to the link between AI and the internet. This paper explores them with brain insights mainly from four views:1) How is the general relation between artificial intelligence and Internet of Things, cloud computing, big data and Industrial Internet from the perspective of brain science. 2) Construction of a new AI system model with the Internet and brain science.

cs.CY↗

arXiv2017

Three IQs of AI Systems and their Testing Methods

The rapid development of artificial intelligence has brought the artificial intelligence threat theory as well as the problem about how to evaluate the intelligence level of intelligent products. Both need to find a quantitative method to evaluate the intelligence level of intelligence systems, including human intelligence. Based on the standard intelligence system and the extended Von Neumann architecture, this paper proposes General IQ, Service IQ and Value IQ evaluation methods for intelligence systems, depending on different evaluation purposes. Among them, the General IQ of intelligence systems is to answer the question of whether the artificial intelligence can surpass the human intelligence, which is reflected in putting the intelligence systems on an equal status and conducting the unified evaluation. The Service IQ and Value IQ of intelligence systems are used to answer the question of how the intelligent products can better serve the human, reflecting the intelligence and required cost of each intelligence system as a product in the process of serving human.

cs.AI↗

arXiv2017

Tidally disrupted dusty clumps as the origin of broad emission lines in active galactic nuclei

Type 1 active galactic nuclei display broad emission lines, regarded as arising from photoionized gas moving in the gravitational potential of a supermassive black hole. The origin of this broad-line region gas is unresolved so far, however. Another component is the dusty torus beyond the broad-line region, likely an assembly of discrete clumps that can hide the region from some viewing angles and make them observationally appear as Type 2 objects. Here we report that these clumps moving within the dust sublimation radius, like the molecular cloud G2 discovered in the Galactic center, will be tidally disrupted by the hole, resulting in some gas becoming bound at smaller radii while other gas is ejected and returns to the torus. The clumps fulfill necessary conditions to be photoionized. Specific dynamical components of tidally disrupted clumps include spiral-in gas as inflow, circularized gas, and ejecta as outflow. We calculate various profiles of emission lines from these clouds, and find they generally agree with H$β$ profiles of Palomar-Green quasars. We find that asymmetry, shape and shift of the profiles strongly depend on [O III], luminosity, which we interpret as a proxy of dusty torus angles. Tidally disrupted clumps from the torus may represent the source of the broad-line region gas.

astro-ph.GA↗

arXiv2017

Intelligence Quotient and Intelligence Grade of Artificial Intelligence

Although artificial intelligence is currently one of the most interesting areas in scientific research, the potential threats posed by emerging AI systems remain a source of persistent controversy. To address the issue of AI threat, this study proposes a standard intelligence model that unifies AI and human characteristics in terms of four aspects of knowledge, i.e., input, output, mastery, and creation. Using this model, we observe three challenges, namely, expanding of the von Neumann architecture; testing and ranking the intelligence quotient of naturally and artificially intelligent systems, including humans, Google, Bing, Baidu, and Siri; and finally, the dividing of artificially intelligent systems into seven grades from robots to Google Brain. Based on this, we conclude that AlphaGo belongs to the third grade.

cs.AI↗

arXiv2017

The dependence of the IR-radio correlation on the metallicity

We have compiled a sample of 26 metal-poor galaxies with 12 + log(O/H) < 8.1 with both infrared continuum and 1.4 GHz radio continuum data. By comparing to galaxies at higher metallicity, we have investigated the dependence on the metallicity of the IR-radio relationship at 24 um, 70 um, 100 um and 160 um bands as well as the integrated FIR luminosity. It is found that metal-poor galaxies have on average lower qIR than metal-rich ones with larger offsets at longer IR wavelengths, from -0.06 dex in q24um to -0.6 dex in q160um. The qIR of all galaxies as a whole at 160 um show positive trends with the metallicity and IR-to-FUV ratio, and negative trends with the IR color, while those at lower IR wavelengths show weaker correlations. We proposed a mechanism that invokes combined effects of low obscured-SFR/total-SFR fraction and warm dust temperature at low metallicity to interpret the above behavior of qIR, with the former reducing the IR radiation and the latter further reducing the IR emission at longer IR wavelength. Other mechanisms that are related to the radio emission including the enhanced magnetic field strength and increased thermal radio contribution are unable to reconcile the IR-wavelength-dependent differences of qIR between metal-poor and metal- rich galaxies. In contrast to qIR, the mean total-SFR/radio ratio of metal-poor galaxies is the same as the metal-rich one, indicating the 1.4 GHz radio emission is still an effective tracer of SFRs at low metallicity.

astro-ph.GA↗

arXiv2017

Extended Schmidt law holds for faint dwarf irregular galaxies

The extended Schmidt law (ESL) is a variant of the Schmidt law which relates the surface densities of gas and star formation, with the surface density of stellar mass added as an extra parameter. We empirically investigate for the first time whether low metallicity faint dwarf irregular galaxies (dIrrs) follow the ESL. Here we consider the `global' law where surface densities are averaged over the galactic discs. dIrrs are unique not only because they are at the lowest end of mass and star formation scales for galaxies, but also because they are metal-poor compared to the general population of galaxies. Our sample is drawn from the Faint Irregular Galaxy GMRT Survey (FIGGS) which is the largest survey of atomic hydrogen in such galaxies. The gas surface densities are determined using their atomic hydrogen content. The star formation rates are calculated using GALEX far ultraviolet fluxes after correcting for dust extinction, whereas the stellar surface densities are calculated using Spitzer 3.6 $μ$m fluxes. All surface densities are calculated over stellar discs defined by the 3.6 $μ$m images. We find dIrrs indeed follow the extended Schmidt law. The mean deviation of the FIGGS galaxies from the relation is 0.01 dex, with a scatter around the relation of less than half that seen in the original relation. In comparison, we also show that the FIGGS galaxies are much more deviant when compared to the `canonical' Kennicutt-Schmidt relation. Our results help strengthen the universality of the extended Schmidt law, especially for galaxies with low metallicities. We suggest that models of star formation in which feedback from previous generations of stars set the pressure in the ISM, are promising candidates for explaining the ESL. We also confirm that ESL is an independent relation and not a form of a relation between star formation efficiency and metallicity.

astro-ph.GA↗