Miracle-dz/UniFAR-FTUs huggingface dataset:
Communications of the Association for Information Systems Information Technology Issues in Healthcare: Hospital Ceo and Cio Perspectives Information Technology Issues in Healthcare: Hospital Ceo and Cio Perspectives Information Technology Issues in Healthcare: Hospital Ceo and Cio Perspectives Infor

This material is brought to you by the Journals at AIS Electronic Library (AISeL). It has been accepted for inclusion in Communications of the Association for Information Systems by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact elibrary@aisnet.org. Healthcare Information Technology (HIT) is widely regarded as a key to improving the quality of healthcare in the United States and potentially reducing its cost. Yet, its implementation is a continuous challenge for the healthcare industry. In this article, we report the results of a survey distributed to CEOs and CIOs at 1400 U.S. hospitals regarding their perceptions of the key information technology (IT) issues in healthcare. Among the top ten issues, the implementation of electronic medical records is ranked the highest. Included in the top ten are issues related to: improving healthcare quality by the use of information technology; change management, privacy, security, and accuracy of electronic records; and decision support applications. While some differences existed, we found much similarity between the views of the CEOs and the CIOs with both groups being characterized as conservative and risk-averse in their entrepreneurial orientation. No major differences were observed between urban and rural hospitals, or large and small hospitals. Given the heightened interest in healthcare IT, these results have wide implications for many stakeholders in this burgeoning industry.
The Opportunity Costs of Elder Care

This study uses data from the 1987 National Survey of Families and Households to estimate the impact of caring for disabled elderly parents on the work hours of men and women. Instrumental variable techniques were used to correct for possible endogeneity bias. Work hours were consistently reduced by caregiving, although the effect was significant only for women providing care to parents residing outside the household. The magnitude of the caregiving effect was larger for women than for men and for coresidence than for non-coresidential care.
Efficient fdCas9 Synthetic Endonuclease with Improved Specificity for Precise Genome Engineering

The Cas9 endonuclease is used for genome editing applications in diverse eukaryotic species. A high frequency of off-target activity has been reported in many cell types, limiting its applications to genome engineering, especially in genomic medicine. Here, we generated a synthetic chimeric protein between the catalytic domain of the FokI endonuclease and the catalytically inactive Cas9 protein (fdCas9). A pair of guide RNAs (gRNAs) that bind to sense and antisense strands with a defined spacer sequence range can be used to form a catalytically active dimeric fdCas9 protein and generate double-strand breaks (DSBs) within the spacer sequence. Our data demonstrate an improved catalytic activity of the fdCas9 endonuclease, with a spacer range of 15–39 nucleotides, on surrogate reporters and genomic targets. Furthermore, we observed no detectable fdCas9 activity at known Cas9 off-target sites. Taken together, our data suggest that the fdCas9 endonuclease variant is a superior platform for genome editing applications in eukaryotic systems including mammalian cells.
A case study of comparison of several methods for corpus-based speech intention identification

Dialogue analysis is one of the most important tasks for human-machine interaction. It is important for dialogue systems to recognize the intention of an utterance and the intentional structure of a discourse. If a system identifies the intentions of each utterance in a dialogue correctly, it can recognize the structure of the dialogue. This paper describes methods for intention identification of an utterance. In this paper we apply two methods to the task and evaluate the performance. The 1st method is based on a similarity measure between an input utterance and utterances in the corpus (Case examples). We compare several similarity measures in the experiment. The 2nd method is based on the Maximum Entropy (ME) method. We compare our methods with related work. In the experiment, the ME method produced the best performance. For the coverage, the similarity based method with the inner product outperformed the ME method. In addition, we verify the effect of dependency relations between words and context information for this intention identification task.
Automatic Detection and Reconstruction of Building Radar Footprints From Single VHR SAR Images

The spaceborne synthetic aperture radar (SAR) systems Cosmo-SkyMed, TerraSAR-X, and TanDEM-X acquire imagery with very high spatial resolution (VHR), supporting various important application scenarios, such as damage assessment in urban areas after natural disasters. To ensure a reliable, consistent, and fast extraction of the information from the complex SAR scenes, automatic information extraction methods are essential. Focusing on the analysis of urban areas, which is of prime interest of VHR SAR, in this paper, we present a novel method for the automatic detection and 2-D reconstruction of building radar footprints from VHR SAR scenes. Unlike most of the literature methods, the proposed approach can be applied to single images. The method is based on the extraction of a set of low-level features from the images and on their composition to more structured primitives using a production system. Then, the concept of semantic meaning of the primitives is introduced and used for both the generation of building candidates and the radar footprint reconstruction. The semantic meaning represents the probability that a primitive belongs to a certain scattering class (e.g., double bounce, roof, facade) and has been defined in order to compensate for the lack of detectable features in single images. Indeed, it allows the selection of the most reliable primitives and footprint hypotheses on the basis of fuzzy membership grades. The efficiency of the proposed method is demonstrated by processing a 1-m resolution TerraSAR-X spotbeam scene containing flat- and gable-roof buildings at various settings. The results show that the method has a high overall detection rate and that radar footprints are well reconstructed, in particular for medium and large buildings.
THE HUMAN GENOME

understanding a host of human diseases. With advances in genetic research, a more rapid and accurate diagnosis of genetic disease is now possible, and genetic methods can even be used as a form of therapy. Genomic physical mapping experiments were facilitated by the development of pulsed field gel electrophoresis and accompanying techniques. Arrays of tandemly repeated sequences predominantly locate in the centromeric chromatin and the physical ends, or telomeres, of different chromosomes. The human genome contains a large number of relatively short sequences that are related. The Alu sequences are most common, and can cause genetic disease in various ways. Also, the human genome contains multiple classes of endogenous retroviruses. Revolutionary improvements in our ability to map human disease genes have come from molecular biology. Comparing expression profiles of normal and disease systems offers new insights into the molecular mechanisms of disease, identifying new diagnostic markers and potential therapeutic targets. The uniparental inheritance of mtDNA means that all the human mtDNAs in the world today must trace back to a single common ancestor who most likely lived in Africa about 150 000–200 000 years ago.
Taming the Skew: Higher-Order Moments in Modeling Asset Price Processes in Finance

It is widely acknowledged that many financial markets exhibit a considerably greater degree of kurtosis (and sometimes also skewness) than is consistent with the Geometric Brownian Motion model of Black and Scholes (1973). Among the many alternative models that have been proposed in this context, two have become especially popular in recent years: models of jump-diffusions, and models of stochastic volatility. This paper explores the statistical properties of these models with a view to identifying simple criteria for judging the consistency of either model with data from a given market; our specific focus is on the patterns of skewness and kurtosis that arise in each case as the length of the interval of observations changes. We find that, regardless of the precise parameterization employed, these patterns are strikingly similar within each class of models, enabling a simple consistency test along the desired lines. As an added bonus, we find that for most parameterizations, the set of possible patterns differs sharply across the two models, so that data from a given market will typically not be consistent with both models. However, there exist exceptional parameter configurations under which skewness and kurtosis in the two models exhibit remarkably similar behavior from a qualitative standpoint. The results herein will be useful to empiricists, theorists and practitioners looking for parsimonious models of asset prices.
Design and Implementation of Ad Hoc Communication and Applications on Mobile Phone Terminals

Recent advancements in wireless communication technologies have attracted ad-hoc networking, which enables mobile users to communicate with each other without any infrastructure. While many ad-hoc routing protocols have been proposed, ad-hoc communication and its applications are not widespread. To expedite the widespread use of ad-hoc communications, we turn our attention to the handiest wireless device, namely, a mobile phone terminal. More mobile phones have been equipped with short distance wireless interfaces such as wireless LAN and Bluetooth. When ad-hoc communication is realized on such mobile phones with these wireless interfaces, ad-hoc communications will be available almost anytime and anywhere, which we believe will become a driving force for ad-hoc networking technology. On the other hand, while the performance of mobile phones has improved greatly over the past several years, their resources are still limited compared to laptop PCs. Therefore, to realize ad-hoc communication in mobile phones, this limitation should be considered. In this paper, we first set the design principles for mobile ad-hoc communications based on the assumed use cases and implement ad-hoc networking protocols as well as their applications on mobile phone terminals to verify their effectiveness. Through the performance evaluations, we discuss performance characteristics and potential application areas.
Season of Hope: Economic Reform under Mandela and Mbeki

When the African National Congress inherited an economy in 1994 that had been shrinking for 5 years, and that had not grown in per capita terms for almost 15, it was also one of the most unequal societies in the world. The government deficit had risen to 9.5 per cent of GDP, and inflation had been in double figures for 20 years. How could an organisation with no previous experience of governing and a history of socialist rhetoric accomplish both a peaceful transition to democracy and set South Africa on a path toward sustained economic growth and development? How did they do it and where are they going? These are the questions addressed in this book. Very little has been written on South African economic reform since 1994, and there are no booklength studies at all. This study, written by an insider who is a former economic historian, offers an insight into the circumstances under which the policies were developed, implemented and reviewed, as well as a thorough study of the outcomes. South Africa today enjoys an economy which is booming and this is providing support for expanded options required for the delivery of social policy goals.
Corporate Responses to the Year 2000 Problem: An Organizational Learning Perspective

Companies have invested billions of dollars in Year 2000 remedies. Given the poor track record of IT projects, one of the major questions is whether companies used this “crisis” to identify changes to improve the delivery of future projects and other IT management practices. This research proposes a model based on the crisis management and learning theories to argue that the learning orientation of an organization is associated with the Y2K strategy adopted and associated learning outcomes.
How Not to Be Seen — Object Removal from Videos of Crowded Scenes

Removing dynamic objects from videos is an extremely challenging problem that even visual effects professionals often solve with time‐consuming manual frame‐by‐frame editing. We propose a new approach to video completion that can deal with complex scenes containing dynamic background and non‐periodical moving objects. We build upon the idea that the spatio‐temporal hole left by a removed object can be filled with data available on other regions of the video where the occluded objects were visible. Video completion is performed by solving a large combinatorial problem that searches for an optimal pattern of pixel offsets from occluded to unoccluded regions. Our contribution includes an energy functional that generalizes well over different scenes with stable parameters, and that has the desirable convergence properties for a graph‐cut‐based optimization. We provide an interface to guide the completion process that both reduces computation time and allows for efficient correction of small errors in the result. We demonstrate that our approach can effectively complete complex, high‐resolution occlusions that are greater in difficulty than what existing methods have shown.
DEEP LEARNING METHOD FOR SATELLITE IMAGE CLASSIFICATION:A LITERATURE REVIEW

Many traditional signal processing techniques and machine learning utilize shallow architectures which consist of a single layer of non-linear feature transformation. Examples of shallow models are nonlinear or linear dynamic models, conditional random models, maximum entropy models, markov hidden models, maximum entropy models, multilayer perceptron and kernel regression with only one hidden layer. A property mutual to these shallow architectures models are simple architecture which consists of only one layer responsible for altering the basic input signals into a problem specific feature space, which we can’t observe. The deep learning paradigm tackles problems on which shallow architectures (e.g. SVM) are altered by the express of dimensionality. Some Part of a two stage method learning involving many layers of nonlinear processing a set of statistically substantial characteristics are automatically extracted from data. Deep learning method can be used in applications like remote sensing such as Land cover Classification, Detection of Vehicle in Satellite Images, Hyper spectral Image classification. Keywords—Deep learning, deep belief net, Auto Encoder Land cover classification, hyper-spectral data classification, Restricted Boltzmann Machines (RBMs), PolSAR
Predicting result quality in Crowdsourcing using application layer monitoring

Crowdsourcing has become a valuable tool for many business applications requiring to meet a certain quality of the results generated by the workers. Therefore, several quality assurance mechanisms have been developed which are partly deployed in commercial crowdsourcing platforms. However, these mechanisms usually impose additional work overhead for the worker, e.g. by adding test questions, or increase the costs for the employer, e.g. by replicating the task for majority decisions. In this work, we analyze the applicability of implicit measurements to objectively estimate the quality of the workers' results. First efforts in this area have already been made by investigating the impact of the task completion time. We extend this research by deploying an application layer monitoring (ALM), which enables monitoring the workers' interactions with our task interface on a much more detailed level. Based on an exemplary use case, we discuss a possible implementation and demonstrate the potential of the approach by predicting the quality of the workers' submission based on our monitoring results. This ALM provides a new way to identify low quality work as well as difficulties in fulfilling the formulated tasks in the domain of Crowdsourcing.
Power Quality Performance of an Active Harmonic Filter with a Power Converter Feeding Magnet Load

In particle accelerator environment, most of the power converters feeding magnet-loads have either thryristorized or diode bridge at their input stage. Loads to these power converters are fixed but they are operated through a wide current range. Such converters being non-linear loads to the mains produce considerable distortion in the supply current. Hereby, results in a poor total harmonic distortion (THDi). An active harmonic filter (AHF) is provided in parallel with the power converter to give a path for the harmonic and reactive current demand of the power converter. The pure AHF scheme implemented using analog control is simple, rugged, and cost effective. In earlier literatures, ways to determine filter ratings of constant power type loads are given. In this paper, apart from describing the filter design and its performance in terms of power quality, a proper way to decide filter rating for the power converters feeding fixed loads like magnets is explained. A prototype 5 kVA AHF design-implementation has brought down THDi to 6.67% from 57.46%.
Stradx : Real-time Acquisition andVisualisation of Freehand 3 D

Conventional freehand 3D ultrasound is a multi-stage process. First, the clinician scans the area of interest. Next, the ultrasound data is used to construct a 3D voxel array, which can then be visualised by, for example, any-plane slicing. The strict separation of data acquisition and visualisation disturbs the interactive nature of the ultrasound examination. Furthermore, some systems require the clinician to wait for an unacceptable amount of time while the voxel array is constructed. In this paper, we describe a novel freehand 3D ultrasound system which allows exceptionally accurate acquisition of the raw data and immediate visualisation of arbitrary slices through the data. Minimal processing separates the acquisition and visualisation processes, with the result that ne detail present in the B-scans is preserved in the synthesised slices.
ekoNET - Environmental Monitoring Using Low-Cost Sensors for Detecting Gases, Particulate Matter, and Meteorological Parameters

This paper presents the environmental monitoring solution ekoNET, developed for a real-time monitoring of air pollution and other atmospheric condition parameters such as temperature, air pressure and humidity. The system is based on low-cost gas, PM and meteorological sensors providing cost-efficient, simple to deploy, use and maintain solution targeted for the usage within the Internet of Things domain of smart cities and smart enterprises. The paper gives an overview of the system architecture, encompassing the ekoNET device, back-end cloud infrastructure, data handling and visualization engine as well as the application-level components and modules. Furthermore, initial field trial data of twelve ekoNET devices is presented, enabling the overall system operation performance testing.
REFINTO: An Ontology-Based Requirements Engineering Framework for Business-IT Alignment in Financial Services Organizations

This paper proposes an ontology-based framework and tool to guide the requirements engineering process in RAD projects for financial solution application development. The framework is aimed at empowering IT, business and solutions analysts with a knowledge repository that helps to address terminology gaps between different project stakeholders and quickly manage the requirements engineering process in response to rapidly changing business demands. We also illustrate how the framework and tool are being used to support RAD projects in the development of financial trading systems for a top 5 global investment bank. The framework and tool help to bridge the knowledge and communication gap alleviating the business-IT alignment problem in financial solution application development.
Curve Estimation using Wavelets and MDL

where f is an unknown function, and the ei's are noise. Our goal is to recover f using wavelet methods. We shall assume that n = 2 is an integer power of 2, and consider both the cases of independent and correlated noise. Let f = (f0; : : : ; fn 1) T , y = (y0; : : : ; yn 1) T and W be the discrete wavelet transform (DWT) matrix (e.g., see Donoho & Johnstone 1994). A wavelet{based estimate f̂ of f can be obtained by the following three steps:
Partial CSI Designs of Distributed Space-Time Coding in Wireless Relay Networks

We study the impact of channel state information at transmitter (CSIT) in a wireless relay network in which M relays cooperate via distributed space-time coding (DSTC) togeth er with an amplify-and-forward protocol. Under individual po wer constraints at relays, we aim at finding the optimal amplifier powers such that pairwise error probability conditioned on CSIT is minimized. With perfect CSIT the optimum solution reduces to a power on-off strategy, and we propose on-off gradient algo rithm that efficiently finds the set of relays to switch on. This algo rithm can be eventually implemented at the receiver without CSIT i f the receiver can send a one-bit feedback to each of the relays . With partial and statistical CSIT, we propose a simple waterfilling solution. Moreover, for a two-relay case we provide a graphi cal representation of the proposed power allocation, which ena bles an easy interpretation. Numerical examples show that the DS TC with appropriate power allocation yields diversity gain with statistical CSIT and further provides power gain with addit ional CSIT. I. M OTIVATION We consider a wireless relay network illustrated in Fig.1 where a transmitter communicates with a receiver via M ≥ 2 relays and each terminal has a single antenna. For its simplicity, we focus on an amply-and-forward (AF) protocol [1] in a two-hop communication: in the first T channel uses the transmitter broadcasts a codeword, then in the second T channel uses relays amplify and forward the observed codeword by applying some linear precoder (to be specified later). We assume that a transmitter and M relays have individual power constraints rather than a total power constraint. The indiv dual power constraint is more meaningful in a practical wireless network where terminals are physically distributed and hen ce are subject to their own power supplies. In a classical AF protocol, the amplifier coefficients have been determined so as to satisfy required power constraint (either a long-term or a short-term) [1]. In order to improve the performance, a large number of recent works have considered some additional linear processing at relays. These works can be classified roughly into two classes according to their assumption of channel state information at transmitt er (CSIT) and their objective. The first class assumes perfect CSIT and aims to maximize either the achievable rate or the instantaneous receive SNR [2], [3], [4], [5]. The resulting transmit scheme yields beamforming with appropriate power allocation. The second class assumes only statistical CSIT and aims to minimize the error probability by designing some type of linear precoder [6], [7], [8], [9]. In particular, a relay 1
Chapter 5 - Common Military Task: Materials Handling

Abstract : Lifting and lifting and carrying(L-L&C) tasks are the most common physically demanding tasks performed by the Armed Force of many NATO nations. These tasks contribute to overexertion injuries, particularly low back pain and disability. This review of the literature describes published recommendations for safe loads, the use of teamwork to reduce the load, equations used to predict the energy cost of L-L&C tasks, methods used by NATO nations to evaluate L-L&C performance and training methods to improve L-L&C task performance.