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Learning PowerShell is a custom-built, handcrafted, painstakingly curated book designed to get you from total PowerShell newbie to confident PowerShell user in as little as four weeks. This book assumes no prior knowledge, perfect for non-developers and GUI addicts who recognize that PowerShell is the future but need a good bit of handholding to achieve mastery. It is also a simple guide for the hundreds of thousands of PowerShell users who have not attained the level of PowerShell knowledge that they really need. With Learning PowerShell at your side, you will see that you don't have to be a developer to use PowerShell and you don't need to be a scripting wizard to derive value from integrating PowerShell into your daily administrative activities. The book is a learning resource that covers every topic worth discussing for a PowerShell beginner, with a depth of explanation unparalleled by any book currently on the market. With this book, you don't have to have a lot of time to learn the language and you can begin applying what you master almost immediately. Even skeptics of PowerShell, and command lines in general, will come away with a renewed sense of respect for the language and ideas on how to put it to use.

To improve the energy prediction performance of a building energy model, the occupancy status information is very important. This is more important in real buildings, rather than under construction buildings, because actual building occupancy can significantly influence its energy consumption. In this study, a machine learning based framework for a consecutive occupancy estimation is proposed by utilizing internet of things data, such as indoor temperature and luminance, CO2 density, electricity consumption of lighting, HVAC (heating, ventilation, and air conditioning), electric appliances, etc. Three machine learning based occupancy estimation algorithms (decision tree, support vector machine, artificial neural networks) are selected and evaluated in terms of the performance of estimating the occupancy status for each season. The selection process of the input variables that have crucial impact on the algorithms’ performance are described in detail. Finally, an occupancy estimation framework that can repeat model training and estimation consecutively in a situation when time-series data are continuously provided over the entire measurement period is suggested. In addition, the performance of the framework is evaluated to identify how it improves the energy prediction performance of the building energy model compared to conventional energy modeling practices. The suggested framework is distinguished from similar previous studies in two ways: (1) The proposed framework reveals that input variables for the occupancy estimation model can be occasionally changed by an occupant response to certain times and seasons, and (2) the framework incorporates time-series indirect occupancy sensing data and classification algorithms to consecutively provide occupancy information for the energy modeling effort.

Purpose Consumers often search for movie information and purchase tickets on the go. A synopsis is often provided by producers and theatres in mobile apps and websites. However, to the best of the authors’ knowledge, little research has investigated whether the synopsis has an impact on a movie’s box office. This research uses computerized text analysis in examining the influence of linguistic cues of a synopsis on the movie’s financial performance. This paper aims to show that language choice in a synopsis is a significant factor in predicting box office performance. Design/methodology/approach A total usable sample of 5973 movies was collected using a web crawler. Computerised text analysis using linguistic inquiry and word count was adopted to analyse the movie synopses data. The empirical study comprises two phases. Phase 1 used exploratory factor analysis on 50 per cent of the sample (Sample 1) to establish the dimensionality of psychological processes as reflected in the linguistic expressions. The analysis identified 11 linguistic variables that loaded on four dimensions. The factor structure was replicated on an independent sample (Sample 2) using confirmatory factor analysis. Phase 2 tested the hypotheses using structure equation modelling. Findings Results show that consistency between movie genres and linguistic cues in a film synopsis promotes movie box office revenue when linguistic cues shown in the synopsis confirm a consumer’s expectancies about a focal movie genre. Conversely, a synopsis reduces the movie box office revenue when the linguistic cues shown disconfirm the genre-based expectancies. These linguistic cues exert similar effects on action and crime films but different effects on comedies and drama films. Research limitations/implications It is likely that consumer tastes and linguistic styles of film synopses have evolved over time. As a cross-sectional study, such changes were not taken into consideration in the current research. A longitudinal study in the future can reveal the dynamic relationship between film synopses and audience. Practical implications Managerially, the findings show that a synopsis is an effective communication touch point to position a movie. This research provides concrete guidelines in crafting synopses with the “rights words’ aligned with movie-goers’ expectations within each specific genre. Beyond movie consumption, the research findings can be applied to other entertainment products, such as TV series and books. Originality/value To our knowledge, this research is the first in studying the linguistic cues in synopses and its relation to box office performance. It addresses this knowledge gap by answering the basic question of whether movie synopses matter. Methodically, the paper marks the first attempt to use the two-step structural equation modelling method on computerised content analysis data.

With a wide variety of forms being generated in different organizations daily, efficient and quick retrieval of information from these forms becomes a pressing need. The data on these forms are imperative to any commercial or professional purpose and thus, efficient retrieval of this data is important for further processing of the same. An automatic form processing system retrieves the content of a filled-in form image for useful storage of the same. Despite a large population of the world speaking in Bangla, to the best of our knowledge, there is no significant research work found in literature which deals with form data written in Bangla. To bridge this research gap, in the present scope of the work, we have developed a system that addresses four important aspects of processing of form data written using Bangla script. Our work has primarily been divided into four major modules: touching component separation, text non-text separation, handwritten printed text separation and alphabet numeral separation. The vital problem of touching component separation has been addressed using a novel rule-based method. For text non-text separation, handwritten printed text separation and alphabet numeral separation, we have used a machine learning based approach using feature engineering where the model for each case has been finalized after exhaustive experiments. Further, in each of the last three modules, we have applied some new features along with some existing features to appropriately tune the modules to obtain optimum results. Notably, we have also prepared a self-made database of filled-in forms. To create different training models, first the filled-in form images are binarized, and then different types of components are colored uniquely to obtain images which act as the ground truth for our reference. Evaluation of modules on the said database produces reasonably satisfactory results considering the complexity of the research problem. The code along with some filled-in sample form images and their respective ground truth images are provided in the link https://github.com/rajdeep-cse17/Form_Processing .

Reading text and unified text detection and recognition from natural images are the most challenging applications in computer vision and document analysis. Previously proposed end-to-end scene text reading methods do not consider the frequency of input images at feature extraction, which slows down the system, requires more memory, and recognizes text inaccurately. In this paper, we proposed an octave convolution (OctConv) feature extractor and a time-restricted attention encoder-decoder module for end-to-end scene text reading. The OctConv can extract features by factorizing the input image based on their frequency. It is a direct replacement of convolutions, orthogonal and complementary, for reducing redundancies and helps to boost the reading text through low memory requirements at a faster speed. In the text reading process, features are first extracted from the input image using Feature Pyramid Network (FPN) with OctConv Residual Network with depth 50 (ResNet50). Then, a Region Proposal Network (RPN) is applied to predict the location of the text area by using extracted features. Finally, a time-restricted attention encoder-decoder module is applied after the Region of Interest (RoI) pooling is performed. A bilingual real and synthetic scene text dataset is prepared for training and testing the proposed model. Additionally, well-known datasets including ICDAR2013, ICDAR2015, and Total Text are used for fine-tuning and evaluating its performance with previously proposed state-of-the-art methods. The proposed model shows promising results on both regular and irregular or curved text detection and reading tasks.

Based on this existing interface, we have developed some applications for sound recording and playing, that allows us to integrate an audio messaging system into High Fidelity platform and to play multichannel sound tracks in sync, the sound for each channel coming from a specific point in 3D space. - customizable 3D avatars with VR tracking system and default gesture desktop interface (fig.3). The presenter will talk in his native language and the translation is automatically screened as a text to each user in his preferred language (fig.5). - augmented reality system (by scanning with the VR phone of augmented images, 3D objects, animations, information or video files will be displayed) - WebRTC live streaming that allows live broadcasts in the VR environment from VR to Web and from outside to VR - user monitoring system (detailed traffic, username, date, access time, collected promotional materials) Based on these tools, we can think of many applications where we can integrate an unlimited number of tools and features. Here's some possible applications: - Virtual office - E-Learning - Virtual Exhibitions (fig.6) - Webinar - Product launch - Training - Recreational events - Scientific sessions and conferences - Videoconference from / to VR and real world - Live streaming from VR to real world CONCLUSION Using the JavaScript and qml API of the HighFidelity platform we have succeeded to extend his capabilities in order to create a truly social collaborative and immersive VR environment.

NOAA/NCEP runs a number of numerical weather prediction (NWP) modeling suites to provide operational guidance to the National Weather Service field offices and service centers. A sophisticated infrastructure, which includes a complex set of software tools, is required to facilitate running these NWP suites. This infrastructure needs to be maintained and upgraded so that continued improvements in forecast accuracy can be achieved. This contribution describes the design of a robust NWP Information Technology Environment (NITE) to support and accelerate the transition of innovations to NOAA operational modeling suites. Through consultation with and at the request of the NOAA NCEP Environmental Modeling Center, a survey of segments of the national NWP community, and a review of selected aspects of the computational infrastructure of several modeling centers was conducted, which led to the following elements being considered as key for NITE: data management, source code management and build systems, suite definition tools, scripts, workflow management, experiment database, and documentation and training. The design for NITE put forth by the DTC would make model development by NOAA staff and their external collaborators more effective and efficient. It should be noted that NITE was not designed to work exclusively for a certain modeling suite; instead it transcends the current operational suites and is applicable to the expected evolution in NCEP systems. NITE is particularly important for community engagement in the Next-Generation Global Prediction System, which is expected to be an Earth modeling system including several components.

According to Truman, the only reason these people gave communism's blatant lies any credence was that they had never heard the truth. The first broadcasts were prepared in New York, but by the middle of 1951 most of the reporting and program production had moved to facilities in Munich.4 The individual language services (or desks) were staffed primarily by exiles from the region, but with significant American oversight.5 In this early period, policy guidelines were set by the New York corporate headquarters with input from exile desk editors and CIA or State Department officials.6 Policy advisers based in New York monitored broadcasts for quality and consistency, critiquing scripts and offering suggestions for improvement.7 As an early RFE policy handbook put it, the goal of the station was to \"counter the Big Lies of Communism with the Truth, making clear that the basic struggle is world freedom versus world tyranny.

It is an exciting time to be a Windows developer. The arrival of Windows 8 is a complete game changer. The operating system and its development platform offer you an entirely new way to create rich, full-featured Windows-based applications. This team of authors takes you on a journey through all of the new development features of the Windows 8 platform specifically how to utilize Visual Studio 2012 and the XAML/C# languages to produce robust apps that are ready for deployment in the new Windows Store. Professional Windows 8 Programming: Learn how to utilize XAML to create rich content driven user interfaces Make use of the new AppBar to create a chrome-less menu system See how to support Sensors and Geo-location on Windows 8 devices Integrate your app into the Windows 8 ecosystem with Contracts and Extensions Walks you through the new Windows 8 navigation system for multi-page apps Minimize code with Data Binding and MVVM design patterns Features tips on getting your app ready for the Windows store Maximize revenue for your app by learning about available monetization strategies.

The cast and creatives behind the dystopian office drama discuss onscreen identity crises and work-life balance Britt lower I was so taken by [my character] Helly's immediate point of view - which is so strong and brave and rebellious - and the journey of discovering, like Ben said, who am I at my core, and who am I on the outside. zach cherry I was excited to play Dylan because I related to how he plugs into the tasks he's given at the office. The writing is amazing, but as a cinematographer it was quite scary to approach something that was all office space. Erickson Everything from Brazil and Being John Malkovich to The Office and Office Space.