A similar menu to the previous image version, but this time using expanding text on mouseover.

A method of replacing menu link text with rollover png images that works in IE6 and also degrades well when images are of and/or CSS is off.

Two methods to indicate text-overflow. One using CSS3 and the other using a small graphic.

Using only CSS to animate (zoom) a vertical menu list.

Using CSS3 to style text to make it look solid with a realistic shadow and no extra markup.

Centering an image between two columns of text with wrap around

Several methods of applying a 'swipe' color change to text on hover and a gradient color fill.

A CSS only method of producing percentage border widths and text sizing without using @media queries.

The 1980 eruption of Mount St. Helens produced a massive landslide and consequent pyroclastic currents, deposits of which blocked the outlet to Spirit Lake. Without an outlet, the lake began to rise, threatening a breaching of the blockage and release of a massive volume of water. To mitigate the hazard posed by the rising lake and provide an outlet, in 1984–1985 the U.S. Army Corps of Engineers bored a 2.6-km (8,500-ft) long tunnel through a bedrock ridge on the western edge of the lake.

Are you looking for some free to use Javascript or jQuery WYSIWYG HTML editors? Well, if your answer is yes, then you are lucky enough to land on the right page. In this round up, we are presenting 12 Diversified Yet Free To Use WYSIWYG Text Editors....

The post 12 Diversified Yet Free To Use WYSIWYG Text Editors appeared first on SmashingApps.com.

Learn how to create a 3D comic book text effect that pops! You will get very familiar with many different layer styles. We will start by creating the background with halftone brushes and then proceed to creating our text effect. Lastly, we will finish it off by adding a bevel effect with a stroke.

The post How to Create A Comic Book Text Effect appeared first on Photoshop Lady.

Old paper textures are one of my most commonly used design resources, as you may have noticed from my tutorials! I have always just downloaded whatever third-party assets I could find, so I thought it was about time I made a collection of my own old paper textures to keep handy in my digital toolbox. […]

The post 20 Free Old Paper Textures with Creases, Folds and Stains appeared first on Spoon Graphics.

You’re working on some text in Photoshop for your photo. Things are going along great…until you realize that your text is horribly pixelated! Why? You may have even created this exact type of file before and not had this problem. Why is the text pixelated now? There are a few things that can cause pixelated text in Photoshop. The good Continue Reading

The post 6 Causes of Pixelated Text in Photoshop and Their Fixes appeared first on Photodoto.

In this Chalkboard Text Vector tutorial, I’ll show you how to create a chalkboard vector effect with some gradients, a bristle brush, and some freebies from Vector Mill! This chalkboard text vector effect tutorial is relatively simple and can be applied to many other Illustrator projects. Use this effect for logo creation, back to school backgrounds, […]

The post 20 Minute Tut! Create Your Own Customized Chalkboard Text Vector appeared first on Vectips.

Let’s go old school with recreating a time honored printing technique in Adobe Illustrator. With a modified photo texture, we’ll quickly edit any text to look like a wood block printing text effect, ready for whatever your digital needs may be! Tutorial Details: Wood Block Printing Text Effect Program: Adobe Illustrator CS6 – CC 2015 […]

The post How to Create a Wood Block Printing Text Effect appeared first on Vectips.

Are there still folks among you who, like me, prefer handwriting to typing? If you’re in this group, you’ll love this new feature on Google Lens. The app now lets you scan your handwritten notes, copy them, and paste them straight to your computer. I gave it a spin, and I bring you my impressions […]

The post Google Lens now copies handwritten text and pastes it straight to your computer appeared first on DIY Photography.

Recent advances in deep learning have facilitated the design of speaker verification systems that directly input raw waveforms. For example, RawNet extracts speaker embeddings from raw waveforms, which simplifies the process pipeline and demonstrates competitive performance. In this study, we improve RawNet by scaling feature maps using various methods. The proposed mechanism utilizes a scale vector that adopts a sigmoid non-linear function. It refers to a vector with dimensionality equal to the number of filters in a given feature map. Using a scale vector, we propose to scale the feature map multiplicatively, additively, or both. In addition, we investigate replacing the first convolution layer with the sinc-convolution layer of SincNet. Experiments performed on the VoxCeleb1 evaluation dataset demonstrate the effectiveness of the proposed methods, and the best performing system reduces the equal error rate by half compared to the original RawNet. Expanded evaluation results obtained using the VoxCeleb1-E and VoxCeleb-H protocols marginally outperform existing state-of-the-art systems.

A recently introduced classifier, called SS3, has shown to be well suited to deal with early risk detection (ERD) problems on text streams. It obtained state-of-the-art performance on early depression and anorexia detection on Reddit in the CLEF's eRisk open tasks. SS3 was created to deal with ERD problems naturally since: it supports incremental training and classification over text streams, and it can visually explain its rationale. However, SS3 processes the input using a bag-of-word model lacking the ability to recognize important word sequences. This aspect could negatively affect the classification performance and also reduces the descriptiveness of visual explanations. In the standard document classification field, it is very common to use word n-grams to try to overcome some of these limitations. Unfortunately, when working with text streams, using n-grams is not trivial since the system must learn and recognize which n-grams are important "on the fly". This paper introduces t-SS3, an extension of SS3 that allows it to recognize useful patterns over text streams dynamically. We evaluated our model in the eRisk 2017 and 2018 tasks on early depression and anorexia detection. Experimental results suggest that t-SS3 is able to improve both current results and the richness of visual explanations.

Compromised accounts on social networks are regular user accounts that have been taken over by an entity with malicious intent. Since the adversary exploits the already established trust of a compromised account, it is crucial to detect these accounts to limit the damage they can cause. We propose a novel general framework for discovering compromised accounts by semantic analysis of text messages coming out from an account. Our framework is built on the observation that normal users will use language that is measurably different from the language that an adversary would use when the account is compromised. We use our framework to develop specific algorithms that use the difference of language models of users and adversaries as features in a supervised learning setup. Evaluation results show that the proposed framework is effective for discovering compromised accounts on social networks and a KL-divergence-based language model feature works best.

Cyber-physical systems for robotic surgery have enabled minimally invasive procedures with increased precision and shorter hospitalization. However, with increasing complexity and connectivity of software and major involvement of human operators in the supervision of surgical robots, there remain significant challenges in ensuring patient safety. This paper presents a safety monitoring system that, given the knowledge of the surgical task being performed by the surgeon, can detect safety-critical events in real-time. Our approach integrates a surgical gesture classifier that infers the operational context from the time-series kinematics data of the robot with a library of erroneous gesture classifiers that given a surgical gesture can detect unsafe events. Our experiments using data from two surgical platforms show that the proposed system can detect unsafe events caused by accidental or malicious faults within an average reaction time window of 1,693 milliseconds and F1 score of 0.88 and human errors within an average reaction time window of 57 milliseconds and F1 score of 0.76.

Generative feature matching network (GFMN) is an approach for training implicit generative models for images by performing moment matching on features from pre-trained neural networks. In this paper, we present new GFMN formulations that are effective for sequential data. Our experimental results show the effectiveness of the proposed method, SeqGFMN, for three distinct generation tasks in English: unconditional text generation, class-conditional text generation, and unsupervised text style transfer. SeqGFMN is stable to train and outperforms various adversarial approaches for text generation and text style transfer.

The history of text can be traced back over thousands of years. Rich and precise semantic information carried by text is important in a wide range of vision-based application scenarios. Therefore, text recognition in natural scenes has been an active research field in computer vision and pattern recognition. In recent years, with the rise and development of deep learning, numerous methods have shown promising in terms of innovation, practicality, and efficiency. This paper aims to (1) summarize the fundamental problems and the state-of-the-art associated with scene text recognition; (2) introduce new insights and ideas; (3) provide a comprehensive review of publicly available resources; (4) point out directions for future work. In summary, this literature review attempts to present the entire picture of the field of scene text recognition. It provides a comprehensive reference for people entering this field, and could be helpful to inspire future research. Related resources are available at our Github repository: https://github.com/HCIILAB/Scene-Text-Recognition.

In encoder-decoder neural models, multiple encoders are in general used to represent the contextual information in addition to the individual sentence. In this paper, we investigate multi-encoder approaches in documentlevel neural machine translation (NMT). Surprisingly, we find that the context encoder does not only encode the surrounding sentences but also behaves as a noise generator. This makes us rethink the real benefits of multi-encoder in context-aware translation - some of the improvements come from robust training. We compare several methods that introduce noise and/or well-tuned dropout setup into the training of these encoders. Experimental results show that noisy training plays an important role in multi-encoder-based NMT, especially when the training data is small. Also, we establish a new state-of-the-art on IWSLT Fr-En task by careful use of noise generation and dropout methods.

Low-resolution text images are often seen in natural scenes such as documents captured by mobile phones. Recognizing low-resolution text images is challenging because they lose detailed content information, leading to poor recognition accuracy. An intuitive solution is to introduce super-resolution (SR) techniques as pre-processing. However, previous single image super-resolution (SISR) methods are trained on synthetic low-resolution images (e.g.Bicubic down-sampling), which is simple and not suitable for real low-resolution text recognition. To this end, we pro-pose a real scene text SR dataset, termed TextZoom. It contains paired real low-resolution and high-resolution images which are captured by cameras with different focal length in the wild. It is more authentic and challenging than synthetic data, as shown in Fig. 1. We argue improv-ing the recognition accuracy is the ultimate goal for Scene Text SR. In this purpose, a new Text Super-Resolution Network termed TSRN, with three novel modules is developed. (1) A sequential residual block is proposed to extract the sequential information of the text images. (2) A boundary-aware loss is designed to sharpen the character boundaries. (3) A central alignment module is proposed to relieve the misalignment problem in TextZoom. Extensive experiments on TextZoom demonstrate that our TSRN largely improves the recognition accuracy by over 13%of CRNN, and by nearly 9.0% of ASTER and MORAN compared to synthetic SR data. Furthermore, our TSRN clearly outperforms 7 state-of-the-art SR methods in boosting the recognition accuracy of LR images in TextZoom. For example, it outperforms LapSRN by over 5% and 8%on the recognition accuracy of ASTER and CRNN. Our results suggest that low-resolution text recognition in the wild is far from being solved, thus more research effort is needed.

XSS is a security vulnerability that permits injecting malicious code into the client side of a web application. In the simplest situations, XSS vulnerabilities arise when a web application includes the user input in the web output without due sanitization. Such simple XSS vulnerabilities can be detected fairly reliably with blackbox scanners, which inject malicious payload into sensitive parts of HTTP requests and look for the reflected values in the web output.

Contemporary blackbox scanners are not effective against stored XSS vulnerabilities, where the malicious payload in an HTTP response originates from the database storage of the web application, rather than from the associated HTTP request. Similarly, many blackbox scanners do not systematically handle context-sensitive XSS vulnerabilities, where the user input is included in the web output after a transformation that prevents the scanner from recognizing the original value, but does not sanitize the value sufficiently. Among the combination of two basic data sources (stored vs reflected) and two basic vulnerability patterns (context sensitive vs not so), only one is therefore tested systematically by state-of-the-art blackbox scanners.

Our work focuses on systematic coverage of the three remaining combinations. We present a graybox mechanism that extends a general purpose database to cooperate with our XSS scanner, reporting and injecting the test inputs at the boundary between the database and the web application. Furthermore, we design a mechanism for identifying the injected inputs in the web output even after encoding by the web application, and check whether the encoding sanitizes the injected inputs correctly in the respective browser context. We evaluate our approach on eight mature and technologically diverse web applications, discovering previously unknown and exploitable XSS flaws in each of those applications.

Convolutional neural networks (CNN) have shown promising results for end-to-end speech recognition, albeit still behind other state-of-the-art methods in performance. In this paper, we study how to bridge this gap and go beyond with a novel CNN-RNN-transducer architecture, which we call ContextNet. ContextNet features a fully convolutional encoder that incorporates global context information into convolution layers by adding squeeze-and-excitation modules. In addition, we propose a simple scaling method that scales the widths of ContextNet that achieves good trade-off between computation and accuracy. We demonstrate that on the widely used LibriSpeech benchmark, ContextNet achieves a word error rate (WER) of 2.1\%/4.6\% without external language model (LM), 1.9\%/4.1\% with LM and 2.9\%/7.0\% with only 10M parameters on the clean/noisy LibriSpeech test sets. This compares to the previous best published system of 2.0\%/4.6\% with LM and 3.9\%/11.3\% with 20M parameters. The superiority of the proposed ContextNet model is also verified on a much larger internal dataset.

Different state-of-the-art methods of the detection of schizophrenia symptoms based on the estimation of text coherence have been analyzed. The analysis of a text at the level of phrases has been suggested. The method based on the graph of the consistency of phrases has been proposed to evaluate the semantic coherence and the cohesion of a text. The semantic coherence, cohesion, and other linguistic features (lexical diversity, lexical density) have been taken into account to form feature vectors for the training of a model-classifier. The training of the classifier has been performed on the set of English-language interviews. According to the retrieved results, the impact of each feature on the output of the model has been analyzed. The results obtained can indicate that the proposed method based on the graph of the consistency of phrases may be used in the different tasks of the detection of mental illness.

Methods, apparatuses and articles of manufacture for use in a mobile device to determine whether a dynamic user profile is to transition from a first state to a second state based, at least in part, on one or more sensed indicators. The dynamic user profile may be indicative of one or more current inferable user behavior contexts for a user co-located with the mobile device. The mobile device may transition a dynamic user profile from a first state to a second state, in response to a determination that the dynamic user profile is to transition from the first state to the second state, and operatively affect one or more functions performed, at least in part, by the mobile device based, at least in part, on the transition of the dynamic user profile to the second state.

A method for performing relational analysis of parsed input is employed to create a visual map of knowledge information. A title, header or subject line for an input item of information is parsed into syntactical components of at least a subject component and any predicate component(s) relationally linked as topic and subtopics. A search of topics and subtopics is carried out for each parsed component. If a match is found, then the parsed component is taken as a chosen topic/subtopic label. If no match is found, then the parsed component is formatted as a new entry in the knowledge map. A translation function for translating topics and subtopics from an original language into one or more target languages is enabled by user request or indicated user preference for display on a generated visual map of knowledge information.

An approach is provided for contextual content suggestion. A recommendation platform processes and/or facilitates a processing of contextual information associated with at least one device to determine one or more locations, one or more contextual parameter values, or a combination thereof. The recommendation platform also determines popularity data associated with one or more content items with respect to the one or more locations, the one or more contextual parameter values, or a combination. The popularity data is determined from one or more other devices sharing at least substantially the one or more locations, the one or more contextual parameter values, or a combination thereof. The recommendation platform then causes, at least in part, a recommendation of the one or more content items to the at least one device based, at least in part, on the popularity information.

The present invention has an object to provide an ink for inkjet textile printing which has excellent fastnesses and causes less bleeding on a textile and to provide a low cost method for inkjet textile printing by using said ink; and relates to an ink for inkjet textile printing wherein the ink contains at least one kind disperse dye, a dispersing agent, water and at least one kind (referred to as A compound) of the compounds represented by the following formula (1): (wherein, n is an integer number of 1 to 12) and at least one kind compound (referred to as B' compound) selected from the group consisting of alkanediols having 3 to 5 carbon atoms and polypropylene glycols, as organic solvents, the total content of A compound and B' compound is 12 to 50% by weight based on the total amount of the ink, and the ratio by weight of A compound to B' compound is in the range of 5:1 to 0.7:1.

A method, apparatus, and system for switching from an existing target end device to a next target end device in a multi-expander storage topology by using Fast Context Switching. The method enhances Fast Context Switching by allowing Fast Context Switching to reuse or extend part of an existing connection path to an end device directly attached to a remote expander. The method can include reusing or extending at least a partial path of an established connection between an initiator and the existing target end device for a connection between the initiator and the next target end device, whereby the existing target end device and the next target end device are locally attached to different expanders.

A method for softening laundry employs a softening composition, which includes at least one thickener containing a cationic polymer obtained by polymerization: of a cationic monomer;of a monomer with a hydrophobic nature, of formula (I): wherein R1=H or CH3 R2=alkyl chain having at least 16 carbon atomsX═O, m≧5, y=z=0, orX═NH, m≧z≧5, y=0, orX═NH, m≧y≧5, z=0, of a nonionic monomer.

Methods, systems, and apparatus, including computer program products, for extracting information from unstructured text. Fact pairs are used to extract basic patterns from a body of text. Patterns are generalized by replacing words with classes of similar words. Generalized patterns are used to extract further fact pairs from the body of text. The process can begin with fact pairs, basic patterns, or generalized patterns.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automatic text suggestion are described. One of the methods includes receiving a text item including one or more terms; determining a plurality of text strings, each text string including a matching portion and one or more suffixes, wherein the matching portion matches the text item, and the one or more suffixes are located after the matching portion; ranking the one or more suffixes based on a credibility score and a frequency score of each suffix, the credibility score indicating an estimated credibility of a source of the text string including the suffix, the frequency score indicating an estimated frequency of appearance of the suffix; and providing a group of the one or more suffixes that includes a highest ranking suffix for display as a suggestion for completing a sentence starting from the text item.

A speech recognition method including the steps of receiving a speech input from a known speaker of a sequence of observations and determining the likelihood of a sequence of words arising from the sequence of observations using an acoustic model. The acoustic model has a plurality of model parameters describing probability distributions which relate a word or part thereof to an observation and has been trained using first training data and adapted using second training data to said speaker. The speech recognition method also determines the likelihood of a sequence of observations occurring in a given language using a language model and combines the likelihoods determined by the acoustic model and the language model and outputs a sequence of words identified from said speech input signal. The acoustic model is context based for the speaker, the context based information being contained in the model using a plurality of decision trees and the structure of the decision trees is based on second training data.

Disclosed herein are systems and methods for navigating electronic texts. According to an aspect, a method may include determining text subgroups within an electronic text. The method may also include selecting a text seed within one of the text subgroups. Further, the method may include determining a similarity relationship between the text seed and one or more adjacent text subgroups that do not include the selected text seed. The method may also include associating the text seed with the one or more adjacent text subgroups based on the similarity relationship to create a text cluster.

An electronic device for text prediction in a virtual keyboard. The device includes a memory including an input determination module for execution by the microprocessor, the input determination module being configured to: receive signals representing input at the virtual keyboard, the virtual keyboard being divided into a plurality of subregions, the plurality of subregions including at least one subregion being associated with two or more characters and/or symbols of the virtual keyboard; identify a subregion on the virtual keyboard corresponding to the input; determine any character or symbol associated with the identified subregion; and if there is at least one determined character or symbol, provide the at least one determined character or symbol to a text prediction algorithm.

A handheld electronic device includes a reduced QWERTY keyboard and is enabled with a disambiguation routine that is operable to disambiguate text input. In addition to identifying and outputting representations of language objects that are stored in the memory and that correspond with a text input, the device is able to perform a spell check routine during input of a text entry and to learn and automatically correct mistakes typically made by the particular user.

An approach is disclosed that facilitates context delivery during communication sessions. The approach may be implemented in a computer infrastructure having computer executable code tangibly embodied on a computer readable storage medium having programming instructions operable to: render at least one service to a user device through a communication session; collect information of the communication session; and send the information of the communication session to a service provider when a call is setup between the user device and the service provider. The service provider renders the information of the communication session for viewing by the service provider.

A textile for providing traditional Chinese medicine therapy to a wearer using electronic stimulation includes at least two conductive paths that are made from conductive textile material, the conductive paths are separated by nonconductive textile material, at least one pair of electrodes attach to the conductive paths corresponding to specific part of body or acupoints according to traditional Chinese medicine theory, and an electronic stimulation signal controller configured to conduct electronic stimulation signals to the electrodes via the conductive paths.

Described are embodiments of an invention for a method and a tool to produce a textured surface on the retention tab of a storage cell. The tool has a form that fits within the storage cell. The form has a hard material with a hard surface with contacts a surface of the retention tab within the storage cell. The movement of the hard surface across the surface of the retention tab produces a textured surface on the retention tab. The textured interface between a notch of a data storage cartridge and a retention tab of a storage cell provides a consistent and low friction force that retains the data storage cartridge within the cell but allows the accessor to easily remove the data storage cartridge when needed.

Methods, apparatus, and articles of manufacture to encode auxiliary data into text data and methods, apparatus, and articles of manufacture to obtain encoded data from text data are disclosed. An example method to embed auxiliary data into text data includes assigning source data to one of a plurality of groups, the source data comprising text data, identifying a symbol to be added to the source data based on an assigned group of the source data, and generating encoded data by including in the source data a text character representative of the symbol.

An information storage medium storing subtitle text-based information, and a method and apparatus utilizing same, process a subtitle The information storage medium includes: dialog information which contains script text information of the subtitle and information specifying an output type of the script text; and presentation information which contains style information used to convert the script text into a bitmap format through rendering. With this structure, the amount of data required for a subtitle and the amount of data that should be processed when a subtitle is output may be greatly reduced.

A device for displaying a text message, comprising a display (10) having a plurality of characters, each of said characters being arranged at a fixed position, not overlapping with any other of said characters, and being adapted to be switched on and off, and a controller being connected to said plurality of characters and being adapted to switch on and off selected characters so that at a given time, a selected sub-group of said characters is switched on, the selected sub-group displaying a text message.

A vehicle computer system comprising a transceiver in a vehicle configured to wirelessly connect with a nomadic device, wherein the nomadic device is capable of running a contextual application which operates at least in part based on vehicle environment data. The vehicle computer system further comprises one or more vehicle modules configured to receive environment data and capable of causing the transceiver to provide the vehicle environment data to the nomadic device for processing by the contextual application.

Embodiments generally relate to optoelectronic devices and more specifically, to textured layers in optoelectronic devices. In one embodiment, a method for providing a textured layer in an optoelectronic device includes depositing a first layer of a first material and depositing an island layer of a second material on the first layer. Depositing the island layer includes forming one or more islands of the second material to provide at least one textured surface of the island layer, where the textured surface is operative to cause scattering of light.

A geotextile container has a bag section, a cover section and a stuffing space. The bag section has a bag cloth, a bag non-woven fabric and a trapezoidal longitudinal section. The cover section is integrally connected with the bag section and has a cover cloth and a cover non-woven fabric. The stuffing space is formed inside the bag section and has a first margin portion. A longitudinal section of the stuffing space is trapezoidal. The first margin portion is formed at a side of a bottom of the stuffing space. The first margin portion can be immediately unfolded and contain filling materials once the geotextile container is projected into the sea.

A textile sleeve for routing and protecting elongate members and method of construction thereof is provided. The sleeve includes an elongate wall having opposite edges extending parallel to a central axis. The wall is woven with warp yarns extending parallel to the axis and hybrid fill yarns extending transversely to the warp yarns. The hybrid fill yarns are provided having a yarn filament core and non-metallic first and second yarn filaments overlying the yarn filament core. The first yarn filament is twisted about the yarn filament core in a first helical direction and the second multifilament yarn is twisted over the first yarn filament and about the yarn filament core in a second helical direction. The first helical direction and the second helical direction being opposite one another to provide a resultant zero torque on the yarn filament core.

An anti-“Methicillin-Resistant Staphylococcus Aureus (MRSA)” chitosan containing antibacterial High Wet Modulus (HWM) rayon fiber textile for medical usage is made of the steps as following: chitin flakes made from natural shrimp or crab shells are deacetylated to generate chitosan with a high deacetylation degree of 90% or more. Next chitosan is dissolved in acetic acid and regenerated by caustic soda to form a chitosan antibacterial nanoparticles slurry, then added to HWM viscose rayon process, and spinning to produce a chitosan containing antibacterial HWM rayon fiber. The antibacterial amino groups of chitosan and the hydroxyl groups of rayon cellulose combine together via hydrogen bonding. Therefore, the fiber becomes the anti-MRSA antibacterial HWM rayon fiber containing amino groups (—NH3+). Finally the resulting HWM rayon fiber is conducted via a yarn spinning or/and weaving process to procure a medical textile with chitosan content.