Special effects artist Rick Baker created the practical aliens and prosthetic makeup for the film, reprising his role from the previous two Men in Black films. In designing the look for the alien creatures, Baker used the time travel plot device as a reason to design "retro" looking aliens reminiscent of science fiction B movies of the era, saying, "In 2012 the aliens should look like Men in Black aliens and in 1969 they should be retro aliens. Fishbowl space helmets, guys with space suits with ribbed things on it, exposed brains, [and] bug eyes."[21]
Upcoming and planned channels:National channels: Hindi movies: Star Gold Romance Star Gold Thrills Star Gold 2 English movies: Star Movies Select SD Kids: Hungama Disney ChannelRegional languages: Tamil: Vijay Super Star Sports 1 Tamil Telugu: Star Sports 1 Telugu Malayalam: Asianet Movies Bengali: Jalsha Josh
telugu Men In Black 3 movies
Problem setting Support vector machines (SVMs) are very popular tools for classification, regression and other problems. Due to the large choice of kernels they can be applied with, a large variety of data can be analysed using these tools. Machine learning thanks its popularity to the good performance of the resulting models. However, interpreting the models is far from obvious, especially when non-linear kernels are used. Hence, the methods are used as black boxes. As a consequence, the use of SVMs is less supported in areas where interpretability is important and where people are held responsible for the decisions made by models. Objective In this work, we investigate whether SVMs using linear, polynomial and RBF kernels can be explained such that interpretations for model-based decisions can be provided. We further indicate when SVMs can be explained and in which situations interpretation of SVMs is (hitherto) not possible. Here, explainability is defined as the ability to produce the final decision based on a sum of contributions which depend on one single or at most two input variables. Results Our experiments on simulated and real-life data show that explainability of an SVM depends on the chosen parameter values (degree of polynomial kernel, width of RBF kernel and regularization constant). When several combinations of parameter values yield the same cross-validation performance, combinations with a lower polynomial degree or a larger kernel width have a higher chance of being explainable. Conclusions This work summarizes SVM classifiers obtained with linear, polynomial and RBF kernels in a single plot. Linear and polynomial kernels up to the second degree are represented exactly. For other kernels an indication of the reliability of the approximation is presented. The complete methodology is available as an R package and two apps and a movie are provided to illustrate the possibilities offered by the method. PMID:27723811
Simultaneous spaceborne and ground based measurements of the scattered solar radiation, create a powerful tool for determination of dust absorption. Absorption of solar radiation is a key component in understanding dust impact on radiative forcing at the top of the atmosphere, on the temperature profile and on cloud formation. We use Landsat spaceborne measurements at seven spectral channels in the range of 0.47 to 2.2 microns over Senegal with corresponding measurements of the aerosol spectral optical thickness by ground based sunphotometers, to find that Saharan dust absorption of solar radiation is two to four times smaller than measured in situ and represented in models. Though dust was found to absorb in the blue (single scattering albedo wo = 0.88), almost no absorption, wo = 0.98, was found for 1 greater than 0.6 microns. The results are in agreement with dust radiative measurements reported in the literature, and explain some previously reported but unexplained dust radiative properties. Therefore, the new finding should be of general relevance. The new finding increases by 50% recently estimated solar radiative forcing by dust at the top of the atmosphere and decreases the estimated dust heating of the lower troposphere due to absorption of solar radiation. Dust transported from Asia shows slightly higher absorption for wavelengths under 1 @im, that can be explained by the presence of black carbon from urban/industrial pollution associated with the submicron size mode.
Simultaneous spaceborne and ground based measurements of the scattered solar radiation, create a powerful tool for determination of dust absorption and scattering properties. Absorption of solar radiation is a key component in understanding dust impact on radiative forcing at the top of the atmosphere, on the temperature profile and on cloud formation. We use Landsat spaceborne measurements at seven spectral channels in the range of 0.47 to 2.2 microns over Senegal with corresponding measurements of the aerosol spectral optical thickness by ground based sunphotometers, to find that Saharan dust absorption of solar radiation is two to four times smaller than measured in situ and represented in models. Though dust was found to absorb in the blue (single scattering albedo w = 0.88), almost no absorption, w = 0.98, was found for wavelengths > 0.6 microns. The new finding increases by 50% recently estimated solar radiative forcing by dust at the top of the atmosphere and decreases the estimated dust heating of the lower troposphere due to absorption of solar radiation. Dust transported from Asia shows slightly higher absorption for wavelengths under 1 micron, that can be explained by the presence of black carbon from urban/industrial pollution associated with the submicron size mode. In the talk I shall also discuss recent observation of the impact of dust shape on the dust scattering properties.
Aerosol absorption in the atmosphere poses a major uncertainty in assessing the aerosol climate effects. This uncertainty arises from the poorly quantified aerosol sources, especially black carbon emissions, and our limited knowledge of aerosol mixing state and optical properties. Here we use a global model GOCART to simulate atmospheric aerosols, including sulfate, black carbon, organic carbon, dust, and sea salt. We compare the model calculated total aerosol optical thickness, extinction, and absorption with those quantities from the ground-based sun photometer measurements from AERONET, satellite retrievals from the TOMS instrument, and field observations from ACE-Asia. We will examine the most sensitive factors in determining the aerosol absorption. and the consequences of assessing the aerosol radiative forcing and atmospheric heating associated with those factors.
Aerosol absorption in the atmosphere poses a major uncertainty in assessing the aerosol climate effects. This uncertainty arises from the poorly quantified aerosol sources, especially black carbon emissions, and our limited knowledge of aerosol mixing state and optical properties. Here we use a global model GOCART to simulate atmospheric aerosols, including sulfate, black carbon, organic carbon, dust, and sea salt. We compare the model calculated total aerosol optical thickness, extinction, and absorption with those quantities from the ground-based sun photometer measurements from AERONET at several different wavelengths and the field observations from ACE-Asia. We will examine what are the most sensitive factors in determining the aerosol absorption, and the consequences of assessing the aerosol radiative forcing and atmospheric heating associated with those factors.
Aerosol absorption in the atmosphere poses a major uncertainty in assessing the aerosol climate effects. This uncertainty arises from the poorly quantified aerosol sources, especially black carbon emissions, and our limited knowledge of aerosol mixing state and optical properties. Here we use a global model GOCART to simulate atmospheric aerosols, including sulfate, black carbon, organic carbon, dust, and sea salt. We compare the model calculated total aerosol optical thickness, extinction, and absorption with those quantities from the ground-based sun photometer measurements from AERONET at several different wavelengths and the field observations from ACE-Asia. We will examine the most sensitive factors in determining the aerosol absorption, and the consequences of assessing the aerosol radiative forcing and atmospheric heating associated with those factors.
We provide satellite-based evidence of the spectral dependence of absorption in biomass burning aerosols over South America using near-UV measurements made by the Ozone Monitoring Instrument (OMI) during 2005-2007. In the current near-UV OMI aerosol algorithm (OMAERUV), it is implicitly assumed that the only absorbing component in carbonaceous aerosols is black carbon whose imaginary component of the refractive index is wavelength independent. With this assumption, OMI-derived aerosol optical depth (AOD) is found to be significantly over-estimated compared to that of AERONET at several sites during intense biomass burning events (August-September). Other well-known sources of error affecting the near-UV method of aerosol retrieval do not explain the large observed AOD discrepancies between the satellite and the ground-based observations. A number of studies have revealed strong spectral dependence in carbonaceous aerosol absorption in the near-UV region suggesting the presence of organic carbon in biomass burning generated aerosols. A sensitivity analysis examining the importance of accounting for the presence of wavelength-dependent aerosol absorption in carbonaceous particles in satellite-based remote sensing was carried out in this work. The results convincingly show that the inclusion of spectrally-dependent aerosol absorption in the radiative transfer calculations leads to a more accurate characterization of the atmospheric load of carbonaceous aerosols.
Potatoes are one of the major food crops in the world. Potato black heart is a kind of defect that the surface is intact while the tissues in skin become black. This kind of potato has lost the edibleness, but it's difficult to be detected with conventional methods. A nondestructive detection system based on the machine vision technology was proposed in this study to distinguish the normal and black heart of potatoes according to the different transmittance of them. The detection system was equipped with a monochrome CCD camera, LED light sources for transmitted illumination and a computer. Firstly, the transmission images of normal and black heart potatoes were taken by the detection system. Then the images were processed by algorithm written with VC++. As the transmitted light intensity was influenced by the radial dimension of the potato samples, the relationship between the grayscale value and the potato radial dimension was acquired by analyzing the grayscale value changing rule of the transmission image. Then proper judging condition was confirmed to distinguish the normal and black heart of potatoes after image preprocessing. The results showed that the nondestructive system built coupled with the processing methods was accessible for the detection of potato black heart at a considerable accuracy rate. The transmission detection technique based on machine vision is nondestructive and feasible to realize the detection of potato black heart.
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