Multi-sensory storytelling: a tool for teaching or an intervention technique

This article reports on research undertaken to investigate how multisensory storytelling (MSST) was being used within schools for students with profound and multiple learning difficulties and other special educational needs. Semi-structured interviews (n=27) and observations (n=18) were undertaken in five schools in the East Midlands and south-east of England. The study identified that MSST was considered to contribute to the curriculum access, assessment, learning and socialisation of students across a wide range of special educational needs. Key opportunities, applications and barriers to use were identified. Findings from this study indicated that the way these teachers used MSST differed from extant research in this area with regard to both design and delivery. It is suggested that the desire to develop a quantitative evidence base may present unnecessary restrictions which inhibit the recognition of pedagogic issues; and that a more fluid conceptualisation of MSST would be reflective of real-world practice

Data locality in Hadoop

Current market tendencies show the need of storing and processing rapidly growing amounts of data. Therefore, it implies the demand for distributed storage and data processing systems. The Apache Hadoop is an open-source framework for managing such computing clusters in an effective, fault-tolerant way. Dealing with large volumes of data, Hadoop, and its storage system HDFS (Hadoop Distributed File System), face challenges to keep the high efficiency with computing in a reasonable time. The typical Hadoop implementation transfers computation to the data, rather than shipping data across the cluster. Otherwise, moving the big quantities of data through the network could significantly delay data processing tasks. However, while a task is already running, Hadoop favours local data access and chooses blocks from the nearest nodes. Next, the necessary blocks are moved just when they are needed in the given ask. For supporting the Hadoop’s data locality preferences, in this thesis, we propose adding an innovative functionality to its distributed file system (HDFS), that enables moving data blocks on request. In-advance shipping of data makes it possible to forcedly redistribute data between nodes in order to easily adapt it to the given processing tasks. New functionality enables the instructed movement of data blocks within the cluster. Data can be shifted either by user running the proper HDFS shell command or programmatically by other module like an appropriate scheduler. In order to develop such functionality, the detailed analysis of Apache Hadoop source code and its components (specifically HDFS) was conducted. Research resulted in a deep understanding of internal architecture, what made it possible to compare the possible approaches to achieve the desired solution, and develop the chosen one

The Quagmire of Mortgage Short Sale Transactions Under Current Homeownership Tax Policy in a Time of Crisis

The 2007 financial crisis continues to loom over homeowners who own underwater properties. What owning underwater property means for homeowners is that the home’s current market value is less than the mortgage balance, making it impossible to sell or refinance the home without the lender’s approval. The quagmire of financial indebtedness created by current tax laws and policy related to Mortgage Short Sale Transactions, or MSSTs, for homeowners creates an onerous tax liability on taxpayers selling underwater properties. The government and lenders, through various programs implemented to help distressed homeowners with underwater properties, created a belief among homeowners that MSSTs are a positive vehicle for selling their underwater properties. Prior to 2007, MSSTs were virtually non-existent. By forgiving the mortgage loan balance, however, lenders exposed homeowners to two situations. First, homeowners face exposure to possible deficiency judgments for the amounts of the forgiven loan balances, which some state laws addressed. Second, homeowners incur potential unavoidable tax liability created by federal and state tax laws for the forgiven indebtedness, which is considered taxable income. It is the latter of these two situations facing middle-class homeowners with properties underwater that this article addresses

Separation of Agile Waveform Time-Frequency Signatures from Coexisting Multimodal Systems

abstract: As the demand for wireless systems increases exponentially, it has become necessary for different wireless modalities, like radar and communication systems, to share the available bandwidth. One approach to realize coexistence successfully is for each system to adopt a transmit waveform with a unique nonlinear time-varying phase function. At the receiver of the system of interest, the waveform received for process- ing may still suffer from low signal-to-interference-plus-noise ratio (SINR) due to the presence of the waveforms that are matched to the other coexisting systems. This thesis uses a time-frequency based approach to increase the SINR of a system by estimating the unique nonlinear instantaneous frequency (IF) of the waveform matched to the system. Specifically, the IF is estimated using the synchrosqueezing transform, a highly localized time-frequency representation that also enables reconstruction of individual waveform components. As the IF estimate is biased, modified versions of the transform are investigated to obtain estimators that are both unbiased and also matched to the unique nonlinear phase function of a given waveform. Simulations using transmit waveforms of coexisting wireless systems are provided to demonstrate the performance of the proposed approach using both biased and unbiased IF estimators.Dissertation/ThesisMasters Thesis Electrical Engineering 201

On the soft limit of closed string amplitudes with massive states

We extend our analysis of the soft behaviour of string amplitudes with massive insertions to closed strings at tree level (sphere). Relying on our previous results for open strings on the disk and on KLT formulae we check universality of the soft behaviour for gravitons to sub-leading order for superstring amplitudes and show how this gets modified for bosonic strings. At sub-sub-leading order we argue in favour of universality for superstrings on the basis of OPE of the vertex operators and gauge invariance for the soft graviton. The results are illustrated by explicit examples of 4-point amplitudes with one massive insertion in any dimension, including D=4, where use of the helicity spinor formalism drastically simplifies the expressions. As a by-product of our analysis we confirm that the `single valued projection' holds for massive amplitudes, too. We briefly comment on the soft behaviour of the anti-symmetric tensor and on loop corrections.Comment: 18+7 pages; added some important references and corrected some typo

School Failure and Intergenerational “Human Capital” Transmission in Portugal

School Failure and Intergenerational Human Capital Transmission… ABSTRACT A new education reform is about to be passed into Law, in Portugal, the extension of compulsory education until the 12th grade being one of the main goals. Given huge value school failure indicators (e.g., illiteracy rates, drop-outs, retention rates) still exhibit for Portuguese education system, we keep large doubts on the effectiveness of such an aim. Moreover, education outcomes inertia between generations appears to be strong, in the light of some indirect indicators, although no recent specific research has been addressing such an issue. In this paper we therefore try to shed some light on the potential impact intergenerational school achievement would exert upon actual school failing and also control for possible endogeneity both with students' own previous trajectory indicators and school effect. For that purpose, we rely on 2003 data relative to Lisbon Metropolitan Area four schools as case studies (author abstract)School failure; father’s, mother’s education; students’ previous school trajectories; school effect; Portugal

Generate Analytics from a Product based Company Web Log

The next generation of industries will be using Big Data to remedy the unsolved data difficulties within the physical global. Big Data analysis may be about constructing systems around the data that is generated. Every department of an organisation consisting of advertising and marketing, finance and HR are actually getting direct get admission to to their own statistics. This is developing a huge activity opportunity and there may be an pressing requirement for the experts to master Big Data Hadoop abilities. Nowadays most of the groups have became to Ecommerce which has grow to be a vital element for business approach and a catalyst for economic improvement. These groups need to predict the evaluation approximately their services and products to tune their commercial enterprise from the customers end. The response from the customers based totally on their sports on the web sites makes a decision the future modifications required to enhance the commercial enterprise values. These companies stores the statistics of all clients in element for destiny analysis which is commonly referred as large statistics, as it's far developing at high costs every day. One of the main programs of large statistics intelligence is Clickstream data which is ideal for e-commerce websites and websites that rely upon clicks. Clickstreams are records of consumer interactions with web sites and other packages. A common technique to load those facts and processing is through the use of traditional databases, however it involves many complexities even as appearing different operations. Here in this paper clickstream records is processed, analysed with the structure of Hadoop the usage of Hortonworks Data Platform (HDP) which offers massive scale processing overall performance and visualized thru strength