nils-herrmann/clean_scirepeval huggingface dataset:
THE IMPORTANCE OF PERSONAL FINANCE FOR INVESTMENT AND APPLYING FINANCIAL BEHAVIOUR PRINCIPLES IN PERSONAL FINANCE INVESTMENT DECISIONS IN LITHUANIA

The aim of each state to ensure social and economic progress, to increase the welfare of the population. Therefore various measures are fulfilled, which accelerating economic growth, enabling conditions to take care for residents own well being. Personal finance has become particularly relevant for population nowadays so it is important to learn how to manage them effectively the proper allocation of income and to minimize costs, to find ways not only to preserve, but also increase the value of personal property. Finance is based on behavior because somebody's costs, savings and investment leads not only the present financial situation, but also the expectations, attitudes and emotions. Identify the main financial behavioral characteristics and the factors that determine the return of investment, provides that personal financial understanding is formed on the basis of economic, psychological and sociological principles set.
Escaping financial crises? Macro evidence from sovereign wealth funds' investment behaviour

This paper investigates the determinants of the investment activity of Sovereign Wealth Funds (SWFs) at a macro level, with special emphasis on the possible reaction to a financial crisis in a potential target economy. The analysis relies upon a specially built proprietary database, which encompasses 1,903 acquisition deals spanning the period 1995 2010 and involving 29 out of the 79 existing SWFs. According to a three step modelling approach, we find that this class of investors prefers to invest in countries with a higher degree of economic development, larger and more liquid financial markets, institutions that offer better protection of legal rights, and a more stable macroeconomic environment. Most importantly, and in stark contrast with the existing empirical literature on other major institutional investors, SWFs seem to engage in 'contrarian' investment behaviour, i.e. increasing their acquisitions in countries where crises hit. The results are shown to be valid if we consider both the likelihood of a country being the target of SWFs' investments and the amount SWFs choose to invest in each country. Capital flows stemming from SWFs' acquisition activity worldwide may therefore have a stabilizing effect on local markets during periods of financial turmoil, protecting the targeted countries from foreign shocks instead of propagating them globally.
Recent Trends in Household Financial Behaviour

This paper identifies general patterns of household financial behaviour for three groups of countries: The Early Financialisers, the Economic and Monetary Union Core and the Latecomers. Even though they stand in different positions as regards the development of their respective financial systems and household engagement with finance, there is a shared trend of growth of household debt and financial wealth, denoting common institutional changes across Europe and thus the systematic character of financialisation as an overall process of transformation of the economy and society. The evolution of pension and life insurance funds is highlighted, becoming the second most important financial asset held by households. This underlines the role of reforms of pension systems in promoting household financial relations, more than a shift towards investment in capital markets stimulated by new investment opportunities supplied by finance. Despite the exposure of private schemes to the financial turmoil, the current crisis has presented itself as an opportunity to bring the pension reform agenda even further forward. However, the trend towards the privatisation of social protection systems, enhancing individual responsibility through growing access to financial markets, must be assessed against the background of greater levels of unemployment and increasingly precarious employment relations that undermine it.
Low Feedback Sampling Rate Digital Predistortion for Wideband Wireless Transmitters
Venue: IEEE Transactions on Microwave Theory and Techniques

A novel digital predistortion (DPD) with an ultralow feedback sampling rate is proposed for wideband wireless communications. Analytical groundwork is carried out to support the rationale of the proposed method. Due to the power amplifier (PA) spectral expansion, the sampling rate of the feedback loop in the DPD architecture generally requires several times the input signal bandwidth, which presents challenges for the analog to digital converter, especially in broadband applications. In order to remove this bottleneck in real world implementation, a forward behavioral modeling method with low rate aliasing PA output signals is adopted to estimate the model coefficients. The obtained coefficients are then used to predict the high rate PA output, using the input signal with an adequate sampling rate, and to further generate the predistorter for the nonlinear PA with the conventional indirect learning architecture. To validate the proposed method, different PAs driven with a 40 MHz two carrier Long Term Evolution are used for linearization purposes. Experimental results based on the instrument platform show that the proposed algorithm achieves almost equivalent results with only a 2.5 Msamples/s feedback sampling rate. Further experimental verification is also demonstrated on an FPGA platform, which achieves an adjacent channel power ratio that is better than 47 dBc for 40 MHz signals with a feedback sampling rate of 20 Msamples/s.
An Improved Digital Predistortion in Wideband Wireless Transmitters Using an Under Sampled Feedback Loop
Venue: IEEE Communications Letters

This letter presents an improved digital predistortion (DPD) method to optimize the linearization of power amplifiers (PAs) when an under sampled feedback loop is used in the transmitter. The proposed approach is based on an adaptive piecewise Lagrange (APL) basis digital predistorter and a variable fractional delay (VFD) finite length impulse response (FIR) filter. A normalized least mean square (NLMS) algorithm with a direct learning structure is used to update the DPD parameters, and the VFD FIR filter is used to periodically vary the fractional delay of the transmitted signal. This changes the initial phase of the under sampled feedback signal to preserve the peak power information from the full sampling rate signal. Experiment results show that there is 10 dB improvement in the normalized mean square error (NMSE) for a 70 MHz Long Term Evolution advanced signal, even when the sampling rate of feedback is reduced from 491.52 Msps to 122.88 Msps.
Diminuer l'impact des troubles obsessionnels compulsifs par des modifications de l'environnement physique

Le trouble obsessionnel compulsif (TOC) est classiquement considere comme une maladie neuropsychiatrique. Les approches therapeutiques actuellement disponibles sont destinees a agir sur le fonctionnement intrapsychique des individus/patients, par des moyens pharmacologiques et/ou psychotherapiques. Bien qu'ils aient une efficacite demontree, certains troubles persistent et engendrent un retentissement fonctionnel parfois handicapant, ce qui engage a chercher de nouvelles solutions complementaires aux traitements. Dans cette perspective, nous avons developpe une demarche qui elargit les mecanismes strictement individuels, cibles par les therapeutiques actuelles, pour penser la personne dans ses interactions avec l'environnement. Nous faisons l'hypothese que l'environnement peut favoriser ou non l'expression de TOC et qu'il existe des elements tocogenes (generateurs de TOC) et tocolytiques (destructeurs de TOC) Lors de ses TOC, la personne exprime ses compulsions en lien avec les elements presents dans son environnement avec lesquels elle entretient une relation tocifiee. Suivant cette hypothese il devient possible d'intervenir par des moyens techniques ou technologiques specifiquement concus pour agir sur les mecanismes de cette relation. Nous presentons les resultats d'une etude de preuve de concept s'appuyant sur une methodologie innovante de conception participative visant a tester empiriquement cette hypothese.
A Study on Water Pollution Source Localization in Sensor Networks
Venue: J. Sensors

The water pollution source localization is of great significance to water environment protection. In this paper, a study on water pollution source localization is presented. Firstly, the source detection is discussed. Then, the coarse localization methods and the localization methods based on diffusion models are introduced and analyzed, respectively. In addition, the localization method based on the contour is proposed. The detection and localization methods are compared in experiments finally. The results show that the detection method using hypotheses testing is more stable. The performance of the coarse localization algorithm depends on the nodes density. The localization based on the diffusion model can yield precise localization results; however, the results are not stable. The localization method based on the contour is better than the other two localization methods when the concentration contours are axisymmetric. Thus, in the water pollution source localization, the detection using hypotheses testing is more preferable in the source detection step. If concentration contours are axisymmetric, the localization method based on the contour is the first option. And, in case the nodes are dense and there is no explicit diffusion model, the coarse localization algorithm can be used, or else the localization based on diffusion models is a good choice.
Data Preparation for Longitudinal Data Mining: a case study on human ageing
Venue: J. Inf. Data Manag.

An adequate preparation of a database is essential to the extraction of useful knowledge contained in it. On longitudinal studies, that follow a fixed set of records through a time period, the data preparation process should adapt to the features added to the database by the temporal aspect of data. This article presents the data preparation process of a real longitudinal database, from a human ageing study. The process addresses the conceptual feature selection of the attributes in the database, and its preprocessing, including noisy data elimination, variable merging, discretization, outlier detection, and missing data analysis. The guidelines to the procedures were generalized, allowing their replication on other longitudinal databases, for similar studies.
The importance of sampling: Building complementary insights about reception experiences of the Hobbit film trilogy with different survey sampling techniques

The worldwide survey of the experiences of The Hobbit trilogy (spring 2015) has enabled the participating researchers from 46 countries to explore the reception of these international blockbusters from a variety of perspectives to do with global audiences, national readings, language cultures, gender, age, etc. The research carried out in Denmark additionally enabled the researchers to analyze in detail the consequences of adopting two different kinds of sampling strategies: In Denmark, in addition to the online self selected convenience sample, we also had a market research company recruit a controlled quota sample, which is near representative of Danish cinema goers. These two samples filled out identical questionnaires. This setup enabled us to explore the methodological consequences of building a questionnaire based reception analysis on, respectively, a sample which is representative of 'ordinary' Danish cinema goers, and a sample arising from the recruiting efforts of the research team through email lists, websites, and networks in social media, mainly Facebook. The network based convenience sample can be seen as a 'fannish' population consisting of more committed and enthusiastic viewers than those recruited in the systematic quota sample. Volume 13, Issue 2 November 2016 Page 329 In this article we first analyze the two samples based on their demographic profiles. Next, based both on the closed and the qualitative questions in the questionnaire, we make a comparative analysis of the two samples' responses to do with people's motivations for seeing the Hobbit films, the genre labels they attach to the films, their perception of fantasy fiction, whether they have read The Hobbit novel, etc. These variables are analyzed in relation to age and gender. Among the key findings are that the two sample groups are often unanimous about which experiences are most salient, but the two groups differ, sometimes significantly, with respect to the relative strength of these experiences. Moreover, fandom appears to have a consistent levelling effect on the film related views and activities between age groups, while among ordinary cinema goers there are systematic differences differentiating the experiences of groups defined by age demographics. An analysis of the content and length of respondents' qualitative explanations of the grades they award to the films suggests that their different argumentative stances may originate in fannish audiences feeling a more urgent need to provide elaborate reasons for their disappointment. In addition to shedding light on the diverse experiences of a global blockbuster film trilogy, the article enlightens the research community about the methodological consequences of applying different sampling strategies in cultural research.
Organizational work family support as universal remedy? A cross cultural comparison of China, India and the USA

In both industrialized and emerging countries, organizations increasingly seek to support employees' efforts to maintain a healthy work family balance. Research has identified two types of organizational support in this context: formal work family programs and informal work family cultures. This study examines the relative effects of work family programs versus work family culture on employees' job satisfaction and performance in various cultural environments. Drawing on the individualism collectivism cultural dimension introduced by Hofstede, it is argued that employees' cultural background may affect family models, which in turn determine employees' need for formal organizational work family support, but are not related to employees' need for informal support. In line with this notion, the results from comparisons of an industrialized country (the USA) with two emerging countries (China and India) show that work family culture has positive effects in all three contexts. However, formal work family programs positively affect job satisfaction and job performance only in India and the USA, whereas they exhibit no significant effect in the more collectivist setting of China.
The Effect Of Compensation, Career Development, Work Family Support On Job Satisfaction

The objective of this study was to analyze the effect of compensation, career development, and work family support on job satisfaction. The sample consisted of 175 employees working in state owned banks in Jember Regency, East Java, Indonesia. Multiple linear regression was used to test the proposed hypothesis. The results showed that compensation and work family support had significant effects on job satisfaction. On the other hand, career development did not significantly affect job satisfaction
Disfluency Detection Using a Bidirectional LSTM
Venue: INTERSPEECH

We introduce a new approach for disfluency detection using a Bidirectional Long Short Term Memory neural network (BLSTM) In addition to the word sequence, the model takes as input pattern match features that were developed to reduce sensitivity to vocabulary size in training, which lead to improved performance over the word sequence alone. The BLSTM takes advantage of explicit repair states in addition to the standard reparandum states. The final output leverages integer linear programming to incorporate constraints of disfluency structure. In experiments on the Switchboard corpus, the model achieves state of the art performance for both the standard disfluency detection task and the correction detection task. Analysis shows that the model has better detection of non repetition disfluencies, which tend to be much harder to detect.
Heat input and metal transfer influences on the weld geometry and microstructure during underwater wet FCAW

FCAW experiments were conducted under water and in the air. Influences of surrounding water on the weld geometry and weld metal microstructure were investigated through analyzing the heat input and metal transfer. The underwater welds have a lower proportion of acicular ferrite and pro eutectoid ferrite. Two metal transfer modes in wet FCAW were observed, i.e. repelled globular transfer and surface tension based quasi short circuit transfer. The former one is the main cause of asymmetric and less uniform weld appearance.
InaNLP: Indonesia natural language processing toolkit, case study: Complaint tweet classification
Venue: 2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA)

This research discusses how natural language processing (NLP) toolkit for Indonesia formal text and social media text, named as InaNLP, has been developed. Several NLP modules were integrated into InaNLP to make people easier in building an NLP system for Indonesia language. The toolkit contains several NLP modules such as sentence splitter, tokenization, Part of Speech (POS) tagger, phrase chunker, named entity (NE) tagger, syntactic parser, semantic analyzer, and word normalization. Several NLP modules were built using rule based approach, whereas several others implemented statistical based approach. Here, the accuracy of several modules such as the POS tagger, NE tagger, syntactic parser and semantic analyzer are shown. In the NE tagger, five (5) word windows with features of POS, orthography, and word list are used. In the NE tagger experiment for evaluating the features, using SMO algorithm and 1500 sentences, for 15 NE classes, token classification accuracy of 93.419% which outperform related work, could be achieved. For the POS tagger, using 12,000 token as the training data and 3,000 token as the testing data, the accuracy of 96.50% was achieved. For the syntactic parser, using CYK algorithm and 100 sentences as the training data and 36 sentences as the testing data, the experiment achieved the accuracy of 47.22% For the semantic analyzer, using 200 sentences as the training data, the experiment achieved the accuracy of 62.50% This research also shows an example in building an Indonesia NLP system using InaNLP for complaint tweet classification. In the experiment for the complaint classification, using 7440 data, the experiment achieved 0.892 of average F measure score.
Natural Language Processing Using Natural Language Toolkit

Natural Language Processing (NLP) is an application field of Artificial Intelligence (AI) It refers to all processes that applied to text such as: tokenization, stemming, lemmatizing, and other operations. In this paper, NLP applied to English text in order to find Part Of Speech POS tagging that corresponding to the English sentence by using NLTK. The first part of any machine translation system is NLP. The source language text must be processed by applying NLP tools to produce good translation. In order to simplify the most widely used NLP operations, the built _ in toolkits has been produced. They provide modules and libraries that are easy to use and apply NLP operations. Using NLTK as an NLP tool recorded accuracy ratio of 70% with the test cases have been selected randomly. The system has been implemented on PC with WINDOWS8.1 using Python programming language.
SecComp: Towards Practically Defending Against Component Hijacking in Android Applications
Venue: ArXiv

Cross app collaboration via inter component communication is a fundamental mechanism on Android. Although it brings the benefits such as functionality reuse and data sharing, a threat called component hijacking is also introduced. By hijacking a vulnerable component in victim apps, an attack app can escalate its privilege for originally prohibited operations. Many prior studies have been performed to understand and mitigate this issue, but component hijacking remains a serious open problem in the Android ecosystem due to no effective defense deployed in the wild. In this paper, we present our vision on practically defending against component hijacking in Android apps. First, we argue that to fundamentally prevent component hijacking, we need to switch from the previous mindset (i.e. performing system level control or repackaging vulnerable apps after they are already released) to a more proactive version that aims to help security inexperienced developers make secure components in the first place. To this end, we propose to embed into apps a secure component library (SecComp) which performs in app mandatory access control on behalf of app components. An important factor for SecComp to be effective is that we find it is possible to devise a set of practical in app policies to stop component hijacking. Furthermore, we allow developers design custom policies, beyond our by default generic policies, to support more fine grained access control. We have overcome challenges to implement a preliminary SecComp prototype, which stops component hijacking with very low performance overhead. We hope the future research that fully implements our vision can eventually help real world apps get rid of component hijacking.
The support of Quality Management to sustainable development: a literature review

Quality Management is considered to be suitable as support for the integration of sustainability considerations in areas such as product development. The purpose of this paper is to review research in which Quality Management methods, tools or practices have been used in conjunction with sustainable development initiatives. We have identified four themes that synthesize the research on Quality Management and its support to approaches for sustainable development: (I) supporting sustainability through integration of management systems, (II) Quality Management as support to the implementation of Environmental Management Systems and to the management of sustainability, (III) supporting integration of sustainability considerations in daily work, and (IV) supporting stakeholder management and customer focus. By far the most research has been conducted within the first two themes. This paper also contributes with proposals for future research, such as the need to move beyond existing standards and management systems to enable more radical improvements, and the need for empirical evidence of the effect of integrated management systems on environmental performance. We also highlight the point that Quality Management practices and tools must be developed and adapted in order to support sustainability considerations.
Travel time prediction with immune genetic algorithm and support vector regression
Venue: 2016 12th World Congress on Intelligent Control and Automation (WCICA)

Travel time prediction, one of the most fundamental problems in almost all subsystems of Intelligent Transportation Systems (ITS) has attracted great attention in recent years. Lots of methods have been researched for this problem, including historical averages method, multiple linear regression and BP neural network. In this paper, an algorithm which combines support vector regression (SVR) and immune genetic algorithm (IGA) is designed for travel time prediction. SVR is used for establishing prediction model and IGA is used for optimizing the parameters of the model. To avoid over fitting problem, a new set which is called the validation set is introduced for the selection of fitness in IGA. Based on the actual traffic data from Langfang City, it is proved that the integration of SVR and IGA is applicable and performs better than historical averages method, multiple linear regression and BP neural network in travel time prediction.