Miracle-dz/UniFAR-FTUs huggingface dataset:
Dependency Syntactic Analysis for Opinion Mining

Background/Objectives: Dependency parsing is one of the remaining problems that attracts researchers’ interest because of its contribution to natural language processing applications. This paper presents a dependency parser and provides an effective sentiment analysis model for Vietnamese. Methods/Statistical Analysis: Up to now, there has been some remarkable work on dependency parsing for Vietnamese, of which the approach of transforming the constituents into a dependency grammar has been proven to give the best performance. In this study, we proposed another way to parse Vietnamese sentences to create dependency trees based on the incremental algorithm by Covington and Graph Unification Programming. We have also combined a dependency parser, sentiment dictionary, domain ontology, and syntactic dependency rules for solving the sentiment analysis problem. Findings: We found that the experiments using simple sentences collected from Vietnamese reviews provided better results than with other methods. The combination of dependency parser, sentiment dictionary, domain ontology, and syntactic dependency rules may be helpful when dealing with a sentiment analysis problem. This model can be applied to Vietnamese and other languages. Application/Improvements: The positive results, which came from an experimental period, will provide us with a basis from which to expand grammar rules to build a parser for more complicated Vietnamese sentences and to integrate it into many cognitive tasks, such as sentiment analysis.
Energy‐Connectivity Tradeoff through Topology Control in Wireless Ad Hoc Networks

In this study, we investigate topology control as a means of obtaining the best possible compromise between the conflicting requirements of reducing energy consumption and improving network connectivity. A topology design algorithm capable of producing network topologies that minimize energy consumption under a minimum‐connectivity constraint is presented. To this end, we define a new topology metric, called connectivity efficiency, which is a function of both algebraic connectivity and the transmit power level. Based on this metric, links that require a high transmit power but only contribute to a small fraction of the network connectivity are chosen to be removed. A connectivity‐efficiency‐based topology control (CETC) algorithm then assigns a transmit power level to each node. The network topology derived by the proposed CETC heuristic algorithm is shown to attain a better tradeoff between energy consumption and network connectivity than existing algorithms. Simulation results demonstrate the efficiency of the CECT algorithm.
Essays on Asset Pricing with Financial Frictions

The investment premium — the finding that firms with low asset growth deliver high average returns — is an integral part of recent factor models. I document empirically that the investment premium (1) reflects financial leverage, (2) does not exist among zero-leverage firms, and (3) increases with firms’ refinancing intensities. This new evidence challenges prominent explanations of the investment premium including the q-theory of investment and behavioral finance. To explain the evidence, I develop a model in which firms make both optimal investment and financing decisions. The model shows that the investment premium reflects both leverage and refinancing intensities consistent with my empirical findings. *Center for Financial Frictions (FRIC), Department of Finance, Copenhagen Business School, Solbjerg Plads 3, DK-2000 Frederiksberg, E-mail: tkp.fi@cbs.dk. I am grateful to Hui Chen, Jens Dick-Nielsen, Peter Feldhütter, Nils Friewald (discussant), Thomas Geelen, Lasse Heje Pedersen, Kristian R. Miltersen, Christian Wagner, and Ramona Westermann for helpful comments and discussions. In addition, I thank seminar participants at the PhD Nordic Finance Workshop 2017, BI Norwegian Business School, Copenhagen Business School, Erasmus School of Economics, University of Oxford (Säıd Business School), Université Paris-Dauphine, University of Toronto Scarborough, Stockholm School of Economics, and Vienna University of Economics and Business (WU) for their comments. Any remaining errors are solely my own. Support from the Center for Financial Frictions (FRIC), grant no. DNRF102, is gratefully acknowledged.
An Improved Memristor SPICE Model and Simulation

Memristor is a passive electronic device with a non-volatile memory,which is proposed by Leon Chua in 1971.A 2-terminal non-volatile memory device based on resistance switching was found in HP labs in 2008,and that proved the existing of memristor.In this paper we analyze two modeling methods of memristor and then design an improved model of memristor based on the physical model of memristor that found by HP labs.It can be found that the characteristics of the improved model correspond to the physical model of HP labs by PSPICE simulation.
Radio Resource Management in Cognitive Radio Sensor Networks

Wireless Sensor Networks (WSNs) use the unlicensed Industrial, Scientific, and Medical (ISM) band for transmissions. However, with the increasing usage of these networks for diverse applications, the currently available ISM band does not suffice for their transmissions and a new challenge appears before the WSNs’ research community. One of the candidate approaches to tackle this spectrum insufficiency problem is to incorporate the opportunistic spectrum access capability of Cognitive Radio (CR) into the existing WSN, thus giving birth to Cognitive Radio Sensor Network (CRSN). Efficient spectrum utilization is another approach to overcome this challenging problem. Another challenge associated to WSN operation is the dependability of sensor nodes on battery supplied power where the batteries in general are not replaceable. Therefore, advanced and intelligent radio resource management schemes are very essential to perform dynamic and efficient spectrum allocation among multiple sensor nodes and to optimize the power consumption of each individual node in the network. Radio resource management enables the sensor nodes to efficiently utilize the available spectrum and power, which in turn ensures QoS transmissions, maximizes the network lifetime, and reduces the inter-node and inter-network interferences. In this chapter, the authors present a comprehensive overview of the recent advances in radio resource management for CRSN. Radio resource management in CRSN has been reviewed in various scenarios (i.e., centralized, cluster-based, and distributed). The related issues and challenges are discussed, and future research directions are highlighted. Ayaz Ahmad COMSATS Institute of Information Technology, Pakistan Sadiq Ahmad COMSATS Institute of Information Technology, Pakistan
Growth and Instability in Area, Production and Productivity of Barley in Haryana vis-à-vis India

The present study has made an attempt to examine the instability in the area, production and productivity of barley crop in India and Haryana during three phases i.e. pre-green revolution, green revolution and post green revolution period. The study is based on secondary data and used three analytical methods. The results showed that in case of area, the instability is more in the post-green revolution than pre-green revolution period as the focus of the green revolution was mainly on other crops like rice and wheat. In case of production, instability showed a decreasing trend from pre- to post-green revolution period due to the adoption of new technology and good quality seeds during the green revolution. A same decreasing trend was observed in yield instability also. In case of growth pattern, the area in Haryana and India both shows a negative growth trend in the pre-green revolution. In case of production, in Haryana, negative growth trends were observed in the green revolution period but in the post-green revolution, it was positive growth; while in India as a whole growth rate was negative. In case of yield, the growth rate was positive in both Haryana and India.
Boundary detection in wireless sensor network based on 2-neighbor graph

Aimed at traditional boundary detection algorithms ignores the boundary width,a boundary detection algorithm based on 2-neighbor graph(2NG) is proposed,which could get proper boundary width by adjusting node communication radius.The algorithm detected boundary only by analyzing the connectivity of 2NG,and did not require any information about node location.Simulation results indicate that the algorithm can detect boundary nodes exactly,also apply to the local boundary with low nodes density.Applicated in managing of coverage quality and connectivity,energey,etc.prolongs network lifetime efficaciously.
Mobile Stroke Unit Hits the Road in Houston

Touch MEdical MEdia 59 The nation’s first Mobile Stroke Unit (MSU) was launched in February, 2014 by James Grotta, MD, and colleagues at the Texas Medical Center in Houston. The concept, pioneered by Marie Curie when she loaded an X-ray machine onto an ambulance during World War I, is logical: to take emergency care to the patient in order to allow accurate diagnosis and urgent treatment earlier when it may do more good. Now 100 years later, instead of a physicist and X-ray machine, it is a vascular neurologist (VN) and computed tomography (CT) scanner.
Détection d'opinion : Apprenons les bons adjectifs !

L'expression d'opinions sur Internet se developpe de plus en plus. Recemment, de nouveaux travaux de recherche se sont interesses a l'extraction automatique des opinions exprimees. Traditionnellement, l'extraction d'opinion dans les textes est basee sur la recherche des adjectifs pour cela, les methodes existantes sont souvent basees sur des dictionnaires generaux. Malheureusement ce type d'approche trouve ses limites : pour certains domaines, des adjectifs peuvent etre inexistants voire contradictoires. Dans cet article, nous proposons une nouvelle approche de creation automatique de dictionnaire d'adjectifs qui integre la connaissance du domaine. Les experiences menees sur des donnees reelles ont montre l'interet de notre approche.
DETERMINANTS OF ISLAMIC BANK’S LEVERAGE RATIO IN MALAYSIA

This study examines the relationship between leverage ratio, bank’s performance, size and profit equalisation reserve. Using GMM estimators, both difference and system, we find significant relationship between current leverage ratio and previous leverage ratio and profit equalization reserve. Overall, our results are consistent with the several past literatures with addition of determining impact of profit equalization reserve on leverage ratios of Islamic banks in Malaysia.
The global rise of “fake news” and the threat to democratic elections in the USA

Purpose Since the end of 2016, “fake news” has had a clear meaning in the USA. After years of scholarship attempting to define “fake news” and where it fits among the larger schema of media hoaxing and deception, popular culture and even academic studies converged following the 2016 US presidential election to define “fake news” in drastically new ways. The paper aims to discuss these issues. Design/methodology/approach In light of the recent elections in the USA, many fear “fake news” that have gradually become a powerful and sinister force, both in the news media environment as well as in the fair and free elections. The scenario draws into questions how the general public interacts with such outlets, and to what extent and in which ways individual responsibility should govern the interactions with social media. Findings Fake news is a growing threat to democratic elections in the USA and other democracies by relentless targeting of hyper-partisan views, which play to the fears and prejudices of people, in order to influence their voting plans and their behavior. Originality/value Essentially, “fake news” is changing and even distorting how political campaigns are run, ultimately calling into question legitimacy of elections, elected officials and governments. Scholarship has increasingly confirmed social media as an enabler of “fake news,” and continues to project its potentially negative impact on democracy, furthering the already existing practices of partisan selective exposure, as well as heightening the need for individual responsibility.
A Video Watermarking DRM Method Based on H.264 Compressed Domain with Low Bit-Rate Increasement

It gets more and more important for video copyright protection, it is necessary to provide efficient H.264 compression domain watermarking for video Digital rights management(DRM). A new watermarking method based on H.264 compressed domain is proposed for video DRM, in which the embedding and extracting procedure are performed using the syntactic elements of the compressed bit stream. In this way, complete decoding is unnecessary in both embedding and extracting processes. Based on the analysis of the time and space, some appropriate sub-blocks are selected for embedding watermarks, increasing watermark robustness while reducing the declination of the visual quality. In order to avoid bit-rate increasing and strengthen the security of the proposed video watermarking scheme, only a set of nonzero coefficients quantized in different parts of macroblocks is chosen for inserting watermark. The experiment results show the proposed scheme can achieve excellent robustness against some common attacks, the proposed scheme is secure and efficient for video content DRM protection.
The preservation of disk-based content at the British Library

This article introduces the British Library’s Flashback project, which is exploring the practical challenges of preserving digital content currently stored on physical media (magnetic and optical disks). It reports on a Flashback proof of concept that conducted experiments on a sample of content from hybrid collection items dating from between 1980 and 2000. It describes some of the activities undertaken by the proof-of-concept stage of the project from July 2015 to February 2016, including the initial collection profiling and sampling of content, the extraction of content from the disks, and the project team’s experiments with identifying and applying preservation approaches to the content, which included both emulation and migration. It concludes with some general observations on the approaches taken by the proof of concept and shares some recent findings from the second phase of the project, which is concerned with the practical challenges of developing an implementation strategy for the Library’s capture and preservation of digital content currently stored on physical media.
Tools for Knowledge Sharing Phases among Knowledge Society: A Case Study on Indonesia Institute of Sciences (LIPI)

The purpose of this article is to gain a better understanding of how some tools are critical for the successful application of knowledge sharing. Knowledge sharing with some tools covers a wide range of functionalities and supports different sets of activities such as, intranet, blogger, wiki, and yahoo groups. Therefore, to achieve knowledge sharing, this work limits the field of investigation to that knowledge sharing tools such as intranet, devoted to the formalization and sharing of best practices and experiences within the organization. Usability issues are also considered when choosing the tools for knowledge sharing in order to build systems which people with limited technological skills could readily use. The paper discusses two key forms of knowledge sharing usability, interface usability and the human-computer-interaction which has helped tools that support knowledge sharing principles improve interface usability. The study covers the following phases with KS tools: (a) The tools which is quite obvious in terms of knowledge sharing from an organizational perspective such as intranet (Model I); (b) The communicative tools of knowledge sharing which is used as a means of organizing learning processes which are collaborative, cooperative and which exchange knowledge processes, such as Yahoo groups or mailing-list (Model III); (c) Knowledge sharing on certain topics, which will have major consequences on librarianâ€™s work and the structure of information transfer institutions (Model IV and V) and is exemplified by combined functions of the intranet and internet. The outcome of this empirical study indicates that the effective development and management of KS is dependent on the interactions between internal and external factors.
An Estimation of the Effects of Brexit on Trade and Migration

This paper uses a gravity model approach to estimate the effects of Brexit in two dimensions: trade in goods and migration. We simulate two scenarios: 1) no agreement with reversion to WTO rules and no special treatment for migrants; 2) signature of a bilateral free trade agreement (FTA). According to our results, Brexit may have large negative effects on trade and migration flows between the EU and the UK. In the WTO scenario, trade flows are predicted to drop by 30% and migration by close to 25%. If the UK and the EU sign an FTA-like agreement (which does not include free mobility of labour), the negative effects on trade are lessened although there is no significant difference in terms of migration with respect to the WTO scenario.
Tomato recognition based on feature analysis and fast development of recognition software

In order to guide manipulator to pick tomato,an automatic tomato recognition based on shape and texture features analysis and development method of recognition software are researched.First,child images of tomato and disturbed objects are extracted re-spectively from tomato images captured under outdoor scene.Three shape parameters and five texture parameters are chosen to do stati-stical analyses.The algorithm of tomato recognition is verified quickly under the enviroment of Matlab.And then,OpenCV function library is used to reproduce the recognition process under VC++ development environment to improve real-time of tomato recognition.Fast development of software is realized.By processing of 674 tomato images,the tests show that right recognition ratio of harvesting mature tomatoes can reach more than 90 percent when growth state of tomatoes is seperated each other.By processing of different size of tomato images,the tests show that the implementation efficiency of the codes programmed with OpenCV is risen considerably in com-parison with the codes programmed with Matlab.Morever,the software can capture real-time image and process synchronously binocular image,and may provide a reference for development of fruit-picking robotic vision software.
Mining Specifications of Malicious Behaviors Based on Multiple Paths in Linux

The malware detection is one of the important parts in a secure Linux frame.Most existing malware detection methods are based on the signature and generally leave behind the development of the malware technology, which cannot meet the ever increaing needs of security.Behavior-based detectors require high-quality specifications of malicious behavior.This paper introduces an automatic technique to mine specifications of malicious behavior based on system calls and explores multiple execution paths for malware specifications, which helps the specifications to be more specific and more comprehensive, and improves the rate of detection of the behavior-based detectors.
XAC project: Towards a middleware for open wireless sensor networks

In pervasive computing environment (Satyanarayanan, 2001), common context management system, that make context of the real world be shared among the context-aware applications, is required to reduce development cost of each context-aware applications. A wireless sensor network (WSN) will be a key infrastructure for the context management system. Towards pervasive computing, a WSN integrated into context management system should be open infrastructure. In an open WSN should (1)handle various kinds of tasks, (2)manage tasks at runtime, (3)save resource consumption, and (4)adapt to changes of environments. To develop such an open WSN, middleware supports are needed, and our XAC project tries to develop a middleware for the open WSN. The XAC project is a research project to develop a middleware for open WSN. In this chapter, the auhors show research issues related to open WSN from the viewpoints of task description language, runtime task management, self-adaptability, and security. Kenji Tei Waseda University, Japan & National Institute of Informatics, Japan Shunichiro Suenaga Nihon Unisys Ltd., Japan Yoshiyuki Nakamura Waseda University, Japan Yuichi Sei Mitsubishi Research Institute, Inc., Japan Hikotoshi Nakazato Waseda University, Japan Yoichi Kaneki The University of Tokyo, Japan Nobukazu Yoshioka National Institute of Informatics, Japan Yoshiaki Fukazawa Waseda University, Japan Shinichi Honiden National Institute of Informatics, Japan & The University of Tokyo, Japan DOI: 10.4018/978-1-61520-843-2.ch011
Evaluating the asymmetric effects of production, interest rate and exchange rate on the Turkish stock prices.

The relationship between stock prices and macro variables has been studied exhaustively in the literature. However, most of the studies assume that this relationship is linear. In this paper, we evaluate the asymmetric effects of production, the interest rate and the exchange rate on Turkish stock prices using non-linear autoregressive distributed lags models. We find that there are both long-run and short-run asymmetric relationships between macro variables and Turkish stock prices. Our results indicate that non-linear models can yield more plausible results compare to linear models. The relationship between stock prices and macro variables has been studied exhaustively in the literature. However, most of the studies assume that this relationship is linear. In this paper, we evaluate the asymmetric effects of production, the interest rate and the exchange rate on Turkish stock prices using non-linear autoregressive distributed lags models. We find that there are both long-run and short-run asymmetric relationships between macro variables and Turkish stock prices. Our results indicate that non-linear models can yield more plausible results compare to linear models.
Personalized Audio Assessment and Temporal Patterns of Dementia- Related Behavioral Disturbances

Behavioral disturbances are common clinical features of many neuropsychiatric disorders, including dementia, that are challenging to assess and treat [1,2], diminishes quality of life of patients and caregivers [3] and precipitates institutionalization [4]. A key challenge in improving care and developing more effective interventions is the accurate assessment of behavioral disturbances [5], which is at present largely limited to observer-rated scales at a specific point in time. In this case report, we describe a novel method of assessing dementiarelated vocally disruptive behaviors (VDB) [6] using audio recordings and automated analysis to objectively measure VDB and their temporal patterns and response to treatment. This method of assessment may potentially be developed and implemented in care settings to more effectively measure specific types of behavioral disturbances and guide treatment for individual patients.
Spectral change representation and feature selection for accent identification tasks

In this paper, a novel approach to model the spectral movement of phonemes called spectral change representation (SCR) is proposed as a feature representation for accent identification. SCR is a procedure of feature selection in the temporal domain, which tries to limit the influence of noisy observations at the phoneme boundaries, and to reduce the redundancy due to the similarity of observations in the steady state. The general power of SCR is shown in a vowel recognition experiment in which it clearly beats HMMs. For accent identification SCR beats the classical frame based cepstral representation and the spectral distance cepstrum. Best results are obtained when SCR is combined with feature selection.