Miracle-dz/UniFAR-FTUs huggingface dataset:
The Interviewer Model of Question Generation

Introduction The Cognitive Aspects of Survey Methodology (CASM) Movement has resulted in a closer examintion of the information processing, decision-making, and behaviors of interviewers and respondents during the survey interview. The purpose of this effort is to reduce nonsampling error during survey data collection. Several models have been produced as a result of the movement, primarily focusing on the information processing of the respondent (e.g., Tourangeau, 1984). To our knowledge, there has been no attempt to model the information processing and behaviors of the interviewer. Two models representing the interviewer's generation and clarification of a survey question will be presented, as a part of larger theory called the Information Exchange Theory. The Information Exchange Theory is a theory about what cognitive processes occur in a standardized interview from the time a question is asked to the time a response is recorded for it. It may be likened to a two-way analysis of variance: the interviewer's and respondent's cognitive processes are modelled as main effects, and the interaction between them is represented in an interviewer-respondent interaction model. The theory embraces two models for the interviewer, one of question generation and the other question clarification; one model of respondent question answering; and one model of interviewerrespondent interaction. The four models illustrate major information processes and behaviors of the interviewer and the respondent.
Using Classification and Regression Trees to Model Survey Nonresponse

In the computation of survey weights to be used for the analysis of complex sample survey data, an adjustment for nonresponse is often an important step in reducing bias. These adjustments depend upon estimated response propensities, which are traditionally obtained through empirical response rates within weighting classes or through logistic regression modeling. In this paper, we discuss possible benefits of using regression trees and random forests for estimating response propensities in surveys, and describe how these models might be used to reduce nonresponse bias. We review issues for their use with complex surveys such as the effect of survey weights and clustering, pruning criteria, and loss functions, and we explore the sensitivity of results to these conditions.
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$EVWUDFW This paper presents a new method for automatic speaker recognition. The principle is to split the whole spectral domain into partial frequency subbands on which recognizers are independently applied and then recombined to yield a global recognition decision. In this article, we particularly discuss the selection of the most critical subbands for the speaker recognition task and the choice of an optimal division of the frequency domain. Speaker recognition experiments are conducted on different subbands for a 630 population on TIMIT using second-order statistical methods. Large differences in identification between subbands are observed. In particular, the low-frequency subbands (under 600Hz) and the high-frequency subbands (over 2000Hz) are more speaker specific than middle-frequency ones. An appropriate selection of the most critical subbands shows that very good performances are still obtained with only half of the frequency domain. Finally experiments on different subband system architectures show that the correlations between frequency channels are of prime importance for the speaker recognition task. Some of these correlations are lost when the frequency domain is divided into subbands. Consequently efficient recombination procedures need to be investigated to perform enhanced speaker identification results.
A new expert system based control tool for power systems with large integration of PVs and wind power plants

In the present paper, an advanced control system for the optimal operation and management of medium size power systems with large penetration from renewable power sources (wind and photovoltaics) is presented. This control system is aimed to assist the power system operators in their management tasks, by proposing optimal actions to them for the economic and secure management of the power system. The control system is composed of various modules performing functions such as short-term forecasting of both load and of the renewable sources, economic dispatch of the power units and online dynamic security assessment. The pilot control system is being installed and evaluated on the Greek island of Lemnos.
Puerarin alleviates cognitive dysfunction in rats after anesthesia with propofol

Backgrounds: Cognitive dysfunction is a complication of anesthesia in surgery. It not only affects the outcome of the surgery, but also increases the patient’s mortality rate. This study aimed to investigate the effects of puerarin on cognitive dysfunction in rats after anesthesia with propofol. Methods: Sixty rats were randomly divided into control, model, and low-, middleand high-dose puerarin groups. The model of cognitive dysfunction after anesthesia was established by intraperitoneal injection of propofol. The low-, mediumand high-dose puerarin groups were intraperitoneally injected with 10, 20 and 40 mg/kg puerarin, respectively. After treatment, animal behaviors were tested. Serum amyloid β-protein (Aβ) and neuron-specific enolase (NSE) levels, hippocampal nerve growth factor (NGF), and brain-derived neurotrophic factor (BDNF) levels, hippocampal cAMP-response element binding protein (CREB) and extracellular signal-regulated kinase (ERK) proteins and their phosphorylated forms (p-ERK and p-CREB) were determined. Results: Compared with the model group, in the high-dose puerarin group the escape latency was significantly decreased (P < 0.05), the platform crossing times were significantly increased (P < 0.05), serum Aβ and NSE levels were significantly decreased (P < 0.05), hippocampal NGF and BDNF levels were significantly increased (P < 0.05), and p-CREB and p-ERK protein expression levels were significantly increased (P < 0.05). Conclusion: Puerarin can alleviate the cognitive dysfunction after anesthesia in rats, which may be related to its decrease of the Aβ and NSE levels, increase of hippocampal NGF and BDNF levels, and increase of hippocampal p-CREB and p-ERK protein expression.
APPLICATION OF GEOGRAPHIC INFORMATION SYSTEM IN SITE SELECTION FOR THE PRODUCTION OF IRISH POTATOES IN ADAMAWA STATE OF NIGERIA

The application of Geographic Information System in site selection for Irish Potatoes production in Adamawa State, North-Eastern Nigeria has been carried out in this study. The study area has a landmass of approximately 38,890.02 sq km. Assessment of the land in terms of the suitability is based on Boolean logic and the method described in FAO guideline 2008. A land unit resulting from the overlay process of the maps layers has unique information of land qualities (Suitable and Unsuitable) on which the suitability is based. Identified map layers used include Soil, Relief, Rainfall length, Mean annual rainfall and Temperature of the study area. These thematic land qualities with their associated attribute data were encoded in GIS database. Overlay operation was performed on those layers as the suitability model assigned. Models of overlay were applied to the overlay process and suitability classes formulated. Results indicate that the Most suitable, Suitable and marginally suitable areas for Irish Potatoes cover about 4.30%, 41.09%, and 45.66% of the total land area respectively. In conclusion, the land suitability map for Irish Potatoes established using GIS can enhance the planning alternatives within the study area (Adamawa State) with meaningful strategy in terms of location. Relevant recommendations have been provided.
671847-1 SERVICE DELIVERY STRUCTURAL DESIGN: AN INDUSTRY STUDY

This paper estimates the empirical significance of key service network design decisions in the domestic airline industry. The model tests the significance design decisions including network centrality, fleet complexity, and operations scale for airline profitability. The empirical significance of these design decisions is based on 9.3 million flight records from 2004 to 2007.
Chapter 7 Surgical Treatment for Tricuspid Valve Infective Endocarditis

Isolated tricuspid valve infective endocarditis is relatively rare. However, the frequency of tricuspid valve infective endocarditis in the United States is rapidly increasing, mainly due to the epidemic of intravenous drug use. A medical treatment is the first choice for this disease; however, surgical intervention is required when the patients suffer from heart failure, large vegetation, or persistent bacteremia despite appropriate medical treatment. Several techniques for tricuspid valve reconstruction have been proposed, and their outcomes have been reported to be good. However, in the cases of severe valve destruction, tricuspid valve replacement is required. Post-surgical management of drug-induced infective endocarditis is challenging due to its poor compliance to medication and high rate of reinfection. There is an ethical controversy as to surgical indication for reinfection induced by relapse of drug use. In addition, because reoperation for tricuspid valve carries high risk, there is also a controversy regarding valve choice in drug users.
Market Oriented New Product Development Process: a Case Study

For many industries, the development of new products is the most important factor in sustaining the success once achieved. The emphasis on development of new products has spurred researchers from strategic management, engineering, marketing and other disciplines to study the process of new product development. In recent years, new product development (NPD) process became more strategic and market oriented. Market orientation is moving from the traditional market-driven to the new driving-market approach. Such approach asks for a different leadership of the NPD process, higher coordination amongst departments (marketing, sales, accounting and engineering areas) that may share common concerns, objectives and tools during the NPD process. While these changes often pose conflicting demands on the firm, there is a growing body of evidence that the firm may employ strategies to successfully meet their objectives. The conceptual framework presented in this article was tested through an exploratory case study developed in a manufacturer of refrigerators and other refrigeration equipment for domestic, commercial and professional use. Some findings were obtained from the analysis of the data. Essentially, market-driven and driving-market approaches are different in terms of customer and competitor orientation as well as inter-functional coordination.
Verification of Continuous Time Random Walk Wind Model

This paper is focused on analysis of impact of different methods for stochastic wind field generation on fatigue loads on several wind turbine components, such as: blade root, hub, yaw bearing and tower bottom. Three methods were compared: the Veers (Sandia) method with Kaimal spectrum, the Mann method and the Continuous Time Random Walk (CTRW) method. CTRW describes the intermittent and non-Gaussian properties of 3D turbulent flows, which are not accounted for in two previous methods. The simulations were carried out according to the third edition of the IEC 61400-1 standard. A numerical model of the stateof-the-art generic onshore 7.5 MW wind turbine was used. Some first results have shown that the intermittency in the wind speed distribution impacts wind turbines loads. However, based on the obtained results it is difficult to explicitly state whether or not the intermittent wind fields would increase fatigue loads in overall.
X International Conference on Structural Dynamics , EURODYN 2017 Smartphone data streams for bridge health monitoring

Knowledge on the dynamic properties of bridges in a city can improve condition assessments, maintenance scheduling, and emergency planning to better serve the public. Currently, bridge vibration data is obtained primarily by researchers through the use of a sophisticated sensor network that is composed of fixed sensor nodes. Recent studies have supported the alternative of mobile sensor networks, which are capable of delivering important structural information, e.g., modal properties, requiring less setup efforts and using fewer sensors. Simultaneously, digital technology has spawned data initiatives such as crowdsensing, in which individuals can collectively sense the urban environment. The prevalence of smartphones, which contain various advanced sensors, is rapidly restructuring researchers’ perceptions of data collection. This paper discusses the confluence of these emerging technologies, which can provide regular infrastructure data streams, within structural health monitoring (SHM) procedures for the immediate goal of system identification (SID) and towards automated maintenance of bridges. Will researchers continue to install sensor networks and collect their own data or will they start to source resident smartphone data? One of the objectives of this ongoing work is to quantify expected smartphone data stream volumes that would be applicable to SHM processes. As an example, the number of smartphones that traverse the Harvard bridge in a month is quantified. © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the organizing committee of EURODYN 2017.
Code maps: A scalable visualisation technique for large codebases

Large codebases (in the order of millions to 10s of millions of lines of code) are notoriously difficult to understand, modify and maintain. They are the product of hundreds of developers working simultaneously over several decades and are often poorly documented. For new developers, building up a workable mental model of these systems can take a considerable amount of time. Software visualisation is one area that seems ideally suited to address this problem, but that in practice, does not see much use beyond high-level, hand-crafted architecture diagrams and node-link diagrams that typically scale poorly to larger systems. We are developing a scalable, spatial visualisation for large codebases based on a world-map metaphor. The core of the idea is mapping the continent/country/state/city/etc. hierarchy to the equivalent in a code base - the high-level architectural components down to the individual files and functions that comprise them - and laying these out so as to maintain the intuitive notion that the proximity of any two entities is proportional to their coupling. Our approach takes as input a dependency graph of the system and, optionally, a predefined abstraction hierarchy to group the low-level source code entities into their higher-level system components. If a hierarchy is not supplied, we recover one from the dependency graph using a graph clustering algorithm. From there we use a combination of force-directed graph layout, implicit surface generation, and Voronoi treemaps to produce a map of the codebase. Our approach allows users to browse the system at any level of detail using the familiar pan/zoom interaction model of web-based mapping services. It provides strong visual landmarks for faster navigation thanks to the distinctive shapes and positions of regions on the map, and lends itself to easy data overlay - the size and colour of regions are proportional to supplied code metrics, while bug locations, search results, and dependency edges can be superimposed. A formal evaluation of the prototype has not yet been undertaken, but initial feedback from internal development organisations has been very positive, particularly for the data overlay o♀capabilities and intuitive zoom-for-detail interaction model.
Prioritizing lean practices for implementation in IT support services

Purpose - The purpose of this study is to capture the perception of the IT support service practitioners regarding the applicability of the lean practices and prioritize them after analyzing the gaps with respect to current usage and importance from practitioners' perspective. Design/methodology/approach - It involved development of an instrument to capture the perceptions of the IT support service practitioners. The data collected was quantitatively analyzed by using statistical techniques and it involved testing of the hypotheses. Findings - The study conducted a gap analysis on the perceived current usage of the lean practices versus the perceived ideal usages of the lean practices from practitioners' perspective. The gap analysis report revealed that gaps of all practices are not same from the practitioners' viewpoint. This gap analysis was useful for prioritizing of the practices and resource allocation. Originality/value - This study was conducted in a relatively new domain, where mature empirically based studies are scarce. This study set out to determine the practitioners' perception of the applicability of lean practices in IT support service organizations. It provides a sound basis for further research on lean implementation in IT support service area.
Vehicle Moving State Recognition Method Based on Anomaly Detection and Its Applications on Dynamic In-car Navigation Systems ?

In order to efiectively determine whether a vehicle is turning or not, we propose a method to map arbitrary consecutive GPS heading information to two dimensional feature space. Through analyzing the distribution of the data, we decide to use two dimensional Gaussian distribution to build the anomaly detection model. After that, the feature space can be divided into two categories (one indicates the vehicle is traveling on a straight road and the other indicates it is doing a turning maneuver) by setting the threshold of the model. Finally, we make use of the labeled data and F-measure method to choose the threshold value. The experimental results show that the model built in this way has good generalization. Based on the above research achievement, a vehicle moving state recognition learning system for Dynamic In-Car Navigation Systems is designed and implemented, and this system is applied to improving the map-matching algorithm. The improved algorithm is tested on a complex urban road network and the experimental results show that the new algorithm can improve the performance of the junction match.
Performance Analysis of Selection Diversity Combining Using Improved Energy Detection over Rayleigh Fading Channel

Diversity schemes are powerful communication techniques that provide wireless link improvements at relatively lower cost and overcome deep fading scenarios. Also, Energy Detection is a technique for blind sensing of unused frequency bands, extensively used in Cognitive Radio and ultra wide-band applications due to its non-parametric and computationally low sensing ability. In this paper, by using an improved version of classical energy detection method, performance improvement of selection combining diversity scheme has been analyzed. The results demonstrate the significance of using Improved Energy Detection technique over existing methods, hence indicating remarkable improvement in the system performance. Based on the proposed algorithm, simulation results show a perfect agreement with analytical results, hence validating the proposed scheme.
Real-time face detection and tracking for vending machine data management

Usually, face detection and face recognition studies are pe formed in an ideal environment. Moreover, to do face recogn ition, it is highly recommended to use a high quality 3D camera, at the e xp nse of elevated cost and computational load. We propose a n algorithm including face detection, tracking, and identification, to managing video data coming from a vending machine. The acqui sition conditions are uncontrollable, and the real-time and cost constraints are h sh. In this context, we reach a good recognition rate of 80 %.
Characterizing the Drivers of Global Food Trade Growth in 21th Century

21st century is characterised by a steady growth in the global demand for basic foodstuffs. This paper reviews the drivers of this growth, through a descriptive analysis of the main literature on the subject, in order to synthesize the most relevant information generated by researchers and position the current state of the issue. The results of the analysis suggest that emerging economies have taken over in the increase of food imports; this is due to the potential of countries such as China, India, Brazil and Russia, which have become propellers of the global economy. From the developing countries, the increase in population and income are the driving forces behind the dynamism of world food demand, whose direct consequences are the increase in per capita consumption, the acceleration of the urbanization process in these regions and the increase in the consumption of products with greater added value. In developed economies, increases in per capita income do not translate into increases in the demand for food; rather, its role with respect to global demand is to promote it as they deepen the production of biofuels, the liberalization of the agricultural sector and the signing of trade agreements. Finally, the work concludes by warning about the uncertainties that surround the demand for food imports, including the crucial role played by climate change.
Another Look at Anonymous Communication

Anonymous communication is desirable for personal, financial, and political reasons. Despite the abundance of frameworks and constructions, anonymity definitions are usually either not well defined or too complicated to use. In between are ad-hoc definitions for specific protocols which sometimes only provide weakened anonymity guarantees. This paper addresses this situation from the perspectives of syntax, security definition, and construction. We propose simple yet expressive syntax and security definition for anonymous communication. Our syntax covers protocols with different operational characteristics. We give a hierarchy of anonymity definitions, starting from the strongest possible to several relaxations. We also propose a modular construction from any key-private public-key encryption scheme, and a new primitive—oblivious forwarding protocols, of which we give two constructions. The first is a generic construction from any random walk over graphs, while the second is optimized for the probability of successful delivery, with experimental validation for our optimization. Anonymity is guaranteed even when the adversary can observe and control all traffic in the network and corrupt most nodes, in contrast to some efficient yet not-so-anonymous protocols. We hope this work suggests an easier way to design and analyze efficient anonymous communication protocols in the future.