926 resultados para Gaussian convolution


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Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

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The aim of this paper is the investigation of the error which results from the method of approximate approximations applied to functions defined on compact in- tervals, only. This method, which is based on an approximate partition of unity, was introduced by V. Mazya in 1991 and has mainly been used for functions defied on the whole space up to now. For the treatment of differential equations and boundary integral equations, however, an efficient approximation procedure on compact intervals is needed. In the present paper we apply the method of approximate approximations to functions which are defined on compact intervals. In contrast to the whole space case here a truncation error has to be controlled in addition. For the resulting total error pointwise estimates and L1-estimates are given, where all the constants are determined explicitly.

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Den Schwerpunkt dieser Dissertation bildet zum einen die Entwicklung eines theoretischen Modells zur Beschreibung des Strukturbildungsprozesses in organisch/anorganischen Doppelschichtsystemen und zum anderen die Untersuchung der Übertragbarkeit dieser theoretisch gewonnenen Ergebnisse auf reale Systeme. Hierzu dienen systematische experimentelle Untersuchungen dieses Phänomens an einem Testsystem. Der Bereich der selbstorganisierenden Systeme ist von hohem wissenschaftlichen Interesse, erlaubt er doch die Realisierung von Strukturen, die nicht den Begrenzungen heutiger Techniken unterliegen, wie etwa der Beugung bei lithographischen Verfahren. Darüber hinaus liefert ein vertieftes Verständnis des Strukturbildungsprozesses auch eine Möglichkeit, im Falle entsprechender technischer Anwendungen Instabilitäten innerhalb der Schichtsysteme zu verhindern und somit einer Degradation der Bauteile entgegenzuwirken. Im theoretischen Teil der Arbeit konnte ein Modell im Rahmen der klassischen Elastizitätstheorie entwickelt werden, mit dessen Hilfe sich die Entstehung der Strukturen in Doppelschichtsystemen verstehen läßt. Der hier gefundene funktionale Zusammenhang zwischen der Periode der Strukturen und dem Verhältnis der Schichtdicken von organischer und anorganischer Schicht, wird durch die experimentellen Ergebnisse sehr gut bestätigt. Die Ergebnisse zeigen, daß es technologisch möglich ist, über die Vorgabe der Schichtdicke in einem Materialsystem die Periodizität der entstehenden Strukturen vorzugeben. Darüber hinaus liefert das vorgestellte Modell eine Stabilitätsbedingung für die Schichtsysteme, die es ermöglicht, zu jedem Zeitpunkt die dominierende Mode zu identifizieren. Ein Schwerpunkt der experimentellen Untersuchungen dieser Arbeit liegt auf der Strukturbildung innerhalb der Schichtsysteme. Das Testsystem wurde durch Aufbringen einer organischen Schicht - eines sog. Molekularen Glases - auf ein Glassubstrat realisiert, als Deckschicht diente eine Siliziumnitrid-Schicht. Es wurden Proben mit variierenden Schichtdicken kontrolliert erwärmt. Sobald die Temperatur des Schichtsystems in der Größenordnung der Glasübergangstemperatur des jeweiligen organischen Materials lag, fand spontan eine Strukturbildung auf Grund einer Spannungsrelaxation statt. Es ließen sich durch die Wahl einer entsprechenden Heizquelle unterschiedliche Strukturen realisieren. Bei Verwendung eines gepulsten Lasers, also einer kreisförmigen Wärmequelle, ordneten sich die Strukturen konzentrisch an, wohingegen sich ihre Ausrichtung bei Verwendung einer flächenhaften Heizplatte statistisch verteilte. Auffällig bei allen Strukturen war eine starke Modulation der Oberfläche. Ferner konnte in der Arbeit gezeigt werden, daß sich durch eine gezielte Veränderung der Spannungsverteilung innerhalb der Schichtsysteme die Ausrichtung der Strukturen (gezielt) manipulieren ließen. Unabhängig davon erlaubte die Variation der Schichtdicken die Realisierung von Strukturen mit einer Periodizität im Bereich von einigen µm bis hinunter zu etwa 200 nm. Die Kontrolle über die Ausrichtung und die Periodizität ist Grundvoraussetzung für eine zukünftige technologische Nutzung des Effektes zur kontrollierten Herstellung von Mikro- bzw. Nanostrukturen. Darüber hinaus konnte ein zunächst von der Strukturbildung unabhängiges Konzept eines aktiven Sensors für die optische Raster-Nahfeld-Mikroskopie vorgestellt werden, das das oben beschriebene System, bestehend aus einem fluoreszierenden Molekularen Glas und einer Siliziumnitrid-Deckschicht, verwendet. Erste theoretische und experimentelle Ergebnisse zeigen das technologische Potential dieses Sensortyps.

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A comparison between the charge transport properties in low molecular amorphous thin films of spiro-linked compound and their corresponding parent compound has been demonstrated. The field-effect transistor method is used for extracting physical parameters such as field-effect mobility of charge carriers, ON/OFF ratios, and stability. In addition, phototransistors have been fabricated and demonstrated for the first time by using organic materials. In this case, asymmetrically spiro-linked compounds are used as active materials. The active materials used in this study can be divided into three classes, namely Spiro-linked compounds (symmetrically spiro-linked compounds), the corresponding parent-compounds, and photosensitive spiro-linked compounds (asymmetrically spiro-linked com-pounds). Some of symmetrically spiro-linked compounds used in this study were 2,2',7,7'-Tetrakis-(di-phenylamino)-9,9'-spirobifluorene (Spiro-TAD),2,2',7,7'-Tetrakis-(N,N'-di-p-methylphenylamino)-9,9'-spirobifluorene (Spiro-TTB), 2,2',7,7'-Tetra-(m-tolyl-phenylamino)-9,9'-spirobifluorene (Spiro-TPD), and 2,2Ž,7,7Ž-Tetra-(N-phenyl-1-naphtylamine)-9,9Ž-spirobifluorene (Spiro alpha-NPB). Related parent compounds of the symmetrically spiro-linked compound used in this study were N,N,N',N'-Tetraphenylbenzidine (TAD), N,N,N',N'-Tetrakis(4-methylphenyl)benzidine (TTB), N,N'-Bis(3-methylphenyl)-(1,1'-biphenyl)-4,4'-diamine (TPD), and N,N'-Diphenyl-N,N'-bis(1-naphthyl)-1,1'-biphenyl-4,4'-diamine (alpha-NPB). The photosensitive asymmetrically spiro-linked compounds used in this study were 2,7-bis-(N,N'-diphenylamino)-2',7'-bis(biphenyl-4-yl)-9,9'-spirobifluorene (Spiro-DPSP), and 2,7-bis-(N,N'-diphenylamino)-2',7'-bis(spirobifluorene-2-yl)-9,9'-spirobifluorene (Spiro-DPSP^2). It was found that the field-effect mobilities of charge carriers in thin films of symmetrically spiro-linked compounds and their corresponding parent compounds are in the same order of magnitude (~10^-5 cm^2/Vs). However, the thin films of the parent compounds were easily crystallized after the samples have been exposed in ambient atmosphere and at room temperature for three days. In contrast, the thin films and the transistor characteristics of symmetrically spiro-linked compound did not change significantly after the samples have been stored in ambient atmosphere and at room temperature for several months. Furthermore, temperature dependence of the mobility was analyzed in two models, namely the Arrhenius model and the Gaussian Disorder model. The Arrhenius model tends to give a high value of the prefactor mobility. However, it is difficult to distinguish whether the temperature behaviors of the material under consideration follows the Arrhenius model or the Gaussian Disorder model due to the narrow accessible range of the temperatures. For the first time, phototransistors have been fabricated and demonstrated by using organic materials. In this case, asymmetrically spiro-linked compounds are used as active materials. Intramolecular charge transfer between a bis(diphenylamino)biphenyl unit and a sexiphenyl unit leads to an increase in charge carrier density, providing the amplification effect. The operational responsivity of better than 1 A/W can be obtained for ultraviolet light at 370 nm, making the device interesting for sensor applications. This result offers a new potential application of organic thin film phototransistors as low-light level and low-cost visible blind ultraviolet photodetectors.

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The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).

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The modification of the two center screened electronic Coulomb potential due to relativistic kinematical effects is investigated in the Coulomb gauge. Both nuclear and electronic charges were approximated by Gaussian distributions. For ion velocities v/c =0.1 the effect may roughly be approximated by a 0.1% increase in the effective strength for the monopole term of the two center potential. Thus for ion kinetic energies not exceeding a few MeV/nucleon this relativistic contribution induces small effects on the binding energy of the 1 \omega-electrons except for super critical charges.

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Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

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We had previously shown that regularization principles lead to approximation schemes, as Radial Basis Functions, which are equivalent to networks with one layer of hidden units, called Regularization Networks. In this paper we show that regularization networks encompass a much broader range of approximation schemes, including many of the popular general additive models, Breiman's hinge functions and some forms of Projection Pursuit Regression. In the probabilistic interpretation of regularization, the different classes of basis functions correspond to different classes of prior probabilities on the approximating function spaces, and therefore to different types of smoothness assumptions. In the final part of the paper, we also show a relation between activation functions of the Gaussian and sigmoidal type.

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Support Vector Machines Regression (SVMR) is a regression technique which has been recently introduced by V. Vapnik and his collaborators (Vapnik, 1995; Vapnik, Golowich and Smola, 1996). In SVMR the goodness of fit is measured not by the usual quadratic loss function (the mean square error), but by a different loss function called Vapnik"s $epsilon$- insensitive loss function, which is similar to the "robust" loss functions introduced by Huber (Huber, 1981). The quadratic loss function is well justified under the assumption of Gaussian additive noise. However, the noise model underlying the choice of Vapnik's loss function is less clear. In this paper the use of Vapnik's loss function is shown to be equivalent to a model of additive and Gaussian noise, where the variance and mean of the Gaussian are random variables. The probability distributions for the variance and mean will be stated explicitly. While this work is presented in the framework of SVMR, it can be extended to justify non-quadratic loss functions in any Maximum Likelihood or Maximum A Posteriori approach. It applies not only to Vapnik's loss function, but to a much broader class of loss functions.

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We formulate density estimation as an inverse operator problem. We then use convergence results of empirical distribution functions to true distribution functions to develop an algorithm for multivariate density estimation. The algorithm is based upon a Support Vector Machine (SVM) approach to solving inverse operator problems. The algorithm is implemented and tested on simulated data from different distributions and different dimensionalities, gaussians and laplacians in $R^2$ and $R^{12}$. A comparison in performance is made with Gaussian Mixture Models (GMMs). Our algorithm does as well or better than the GMMs for the simulations tested and has the added advantage of being automated with respect to parameters.

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Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. We propose a performance criterion for a local descriptor based on the tradeoff between selectivity and invariance. In this paper, we evaluate several local descriptors with respect to selectivity and invariance. The descriptors that we evaluated are Gaussian derivatives up to the third order, gray image patches, and Laplacian-based descriptors with either three scales or one scale filters. We compare selectivity and invariance to several affine changes such as rotation, scale, brightness, and viewpoint. Comparisons have been made keeping the dimensionality of the descriptors roughly constant. The overall results indicate a good performance by the descriptor based on a set of oriented Gaussian filters. It is interesting that oriented receptive fields similar to the Gaussian derivatives as well as receptive fields similar to the Laplacian are found in primate visual cortex.

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Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. Such a descriptor--based on a set of oriented Gaussian derivative filters-- is used in our recognition system. We report here an evaluation of several techniques for orientation estimation to achieve rotation invariance of the descriptor. We also describe feature selection based on a single training image. Virtual images are generated by rotating and rescaling the image and robust features are selected. The results confirm robust performance in cluttered scenes, in the presence of partial occlusions, and when the object is embedded in different backgrounds.

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Building robust recognition systems requires a careful understanding of the effects of error in sensed features. Error in these image features results in a region of uncertainty in the possible image location of each additional model feature. We present an accurate, analytic approximation for this uncertainty region when model poses are based on matching three image and model points, for both Gaussian and bounded error in the detection of image points, and for both scaled-orthographic and perspective projection models. This result applies to objects that are fully three- dimensional, where past results considered only two-dimensional objects. Further, we introduce a linear programming algorithm to compute the uncertainty region when poses are based on any number of initial matches. Finally, we use these results to extend, from two-dimensional to three- dimensional objects, robust implementations of alignmentt interpretation- tree search, and ransformation clustering.

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Holes with different sizes from microscale to nanoscale were directly fabricated by focused ion beam (FIB) milling in this paper. Maximum aspect ratio of the fabricated holes can be 5:1 for the hole with large size with pure FIB milling, 10:1 for gas assistant etching, and 1:1 for the hole with size below 100 nm. A phenomenon of volume swell at the boundary of the hole was observed. The reason maybe due to the dose dependence of the effective sputter yield in low intensity Gaussian beam tail regions and redeposition. Different materials were used to investigate variation of the aspect ratio. The results show that for some special material, such as Ni-Be, the corresponding aspect ratio can reach 13.8:1 with Cl₂ assistant etching, but only 0.09:1 for Si(100) with single scan of the FIB.

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We report on a new class of nonionic, photosensitive surfactants consisting of a polar di(ethylene oxide) head group attached to an alkyl spacer of between two and eight methylene groups, coupled through an ether linkage to an azobenzene moiety. Structural changes associated with the interconversion of the azobenzene group between its cis and trans forms as mediated by the wavelength of an irradiating light source cause changes in the surface tension and self-assembly properties. Differences in saturated surface tensions (surface tension at concentrations above the CMC) were as high as 14.4 mN/m under radiation of different wavelengths. The qualitative behavior of the surfactants changed as the spacer length changed, attributed to the different orientations adopted by the different surfactants depending on their isomerization states, as revealed by neutron reflection studies. The self-assembly of these photosensitive surfactants has been investigated by light scattering, small angle neutron scattering, and cryo-TEM under different illuminations. The significant change in the self-assembly in response to different illumination conditions was attributed to the sign change in Gaussian rigidity, which originated from the azobenzene photoisomerization.