Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantic Role Labeling based on Japanese FrameNet

本稿では, 日本語フレームネットを背景に, 述語項構造における項の意味役割を推定する統計モデルの定義, および獲得手法を提案する. 本モデルの目的は, 表層格では区別できない意味の区別である. 本モデルは文と述語から述語項構造を同定して意味役割を付与すべき項を抽出し, それらに適切な意味役割を付与する. 評価実験の結果, 尤度が閾値を超える意味役割のみを付与する条件の下, 意味役割を付与すべき項がわかっている文に対して精度77%, 再現率68%, また, 意味役割を付与すべき項がわかっていない文に対して精度63%, 再現率43%で意味役割推定を実現し, 本手法の有効性を示した. また, 同一の表層格をもつ項に対して, 複数の異なる意味役割の付与を実現した.
A Bayesian recommender model for user rating and review profiling

Intuitively, not only do ratings include abundant information for learning user preferences, but also reviews accompanied by ratings. However, most existing recommender systems take rating scores for granted and discard the wealth of information in accompanying reviews. In this paper, in order to exploit user profiles’ information embedded in both ratings and reviews exhaustively, we propose a Bayesian model that links a traditional Collaborative Filtering (CF) technique with a topic model seamlessly. By employing a topic model with the review text and aligning user review topics with “user attitudes” (i.e., abstract rating patterns) over the same distribution, our method achieves greater accuracy than the traditional approach on the rating prediction task. Moreover, with review text information involved, latent user rating attitudes are interpretable and “cold-start” problem can be alleviated. This property qualifies our method for serving as a “recommender” task with very sparse datasets. Furthermore, unlike most related works, we treat each review as a document, not all reviews of each user or item together as one document, to fully exploit the reviews’ information. Experimental results on 25 real-world datasets demonstrate the superiority of our model over state-of-the-art methods.
Development and Evaluation of Game-Like Phonological Awareness Software for Kindergarteners

The major goal of this study was to develop a game-like software application for phonological awareness training and to evaluate its role in improving phonological awareness skills at the kindergarten level, with the intention to eventually help reading acquisition in Turkish. The participants of the study came from two kindergarten classrooms in a public elementary school in Istanbul that served socioeconomically disadvantaged families. The experimental group used the software three times a week for nine weeks, while the control played unrelated math games. At posttest, the children in the experimental group scored significantly higher in phoneme segmentation, letter-name, and letter-sound knowledge than those in the control group. The experimental group also showed significant gains for six other subskills when their pre- and posttest scores were compared. Classroom observations and teacher interviews provided insight for interface design for young learners, as well as computer use in early literacy instruction.
Post operative complications of mid-urethral slings: Is it possible to use Clavien’s classification?

Study design, materials and methods Pub Med search for post-operative surgical complication after midurethral sling was carried out. Reported complications were stratified according to Dindo-Clavien’s classification (1). Resultant classification of “sling-related complications” was applied on 160 females who underwent 3 different procedures of mid-urethral slings (TVT, TOT and autologous fascial sling) and followed with minimal follow up 24-months.
The Relationship Between Workplace Absenteeism and Alcohol Use: A Day-to-Day Examination

THE RELATIONSHIP BETWEEN WORKPLACE ABSENTEEISM AND ALCOHOL USE: A DAY-TO-DAY EXAMINATION Susan Kay McFarlin Old Dominion University, 2001 Director: Dr. Robert M. McIntyre This investigation examined the conditional day-to-day relationship between alcohol use and workplace absenteeism among participants (N = 302) employed full-time in one o f three large companies located in the northeastern U.S. Semi-structured interviews were used to gather information from employees on their daily use o f alcohol and other drugs during a 1-month period. Employees’ absenteeism and work injury data during the same target time period were gathered from personnel files residing in the companies’ human resources departments. The presence o f a current alcohol use disorder also was determined. The following primary hypotheses were tested: (a) there would be a significant conditional relationship between alcohol use and workplace absence the following day, and (b) workplace absence would be more likely on days after heavy drinking than on days after nonheavy drinking. This investigation also explored: (a) whether the presence of an alcohol use disorder influences the day-to-day conditional relationship between alcohol use and subsequent workplace absence; (b) the conditional relationship between employees’ use o f psychoactive substances, other than alcohol, and workplace absence the following day; (c) the day-to-day relationship between alcohol consumption during working hours and the occurrence o f workplace injury; and (d) the day-to-day conditional relationship between alcohol consumption and workplace absence among different classifications (e.g., executives, administrators, skilled laborers) o f Reproduced with permission of the copyright owner. Further reproduction prohibited without permission. employees. The findings support the primary hypotheses. There was a significant conditional day-to-day relationship between alcohol use and workplace absence the following day. Those who engaged in any drinking the day before a scheduled workday were roughly 1.5 times more likely to be absent than on a day after no drinking. Moreover, workplace absence was more likely on days after heavy drinking than on days after nonheavy drinking. Those who engaged in heavy drinking 1 day before a scheduled workday were 1.7 times more likely to be absent the next day. Results indicate no relationship between nonheavy drinking 1 day before a scheduled workday and workplace absence. In addition, drinking was not associated with workplace absence when alcohol was consumed 2 days before a scheduled workday. The exploratory hypotheses were not supported. Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Stroke Survivors on Twitter: Sentiment and Topic Analysis From a Gender Perspective

Background Stroke is the worldwide leading cause of long-term disabilities. Women experience more activity limitations, worse health-related quality of life, and more poststroke depression than men. Twitter is increasingly used by individuals to broadcast their day-to-day happenings, providing unobtrusive access to samples of spontaneously expressed opinions on all types of topics and emotions. Objective This study aimed to consider the raw frequencies of words in the collection of tweets posted by a sample of stroke survivors and to compare the posts by gender of the survivor for 8 basic emotions (anger, fear, anticipation, surprise, joy, sadness, trust and disgust); determine the proportion of each emotion in the collection of tweets and statistically compare each of them by gender of the survivor; extract the main topics (represented as sets of words) that occur in the collection of tweets, relative to each gender; and assign happiness scores to tweets and topics (using a well-established tool) and compare them by gender of the survivor. Methods We performed sentiment analysis based on a state-of-the-art lexicon (National Research Council) with syuzhet R package. The emotion scores for men and women were first subjected to an F-test and then to a Wilcoxon rank sum test. We extended the emotional analysis, assigning happiness scores with the hedonometer (a tool specifically designed considering Twitter inputs). We calculated daily happiness average scores for all tweets. We created a term map for an exploratory clustering analysis using VosViewer software. We performed structural topic modelling with stm R package, allowing us to identify main topics by gender. We assigned happiness scores to all the words defining the main identified topics and compared them by gender. Results We analyzed 800,424 tweets posted from August 1, 2007 to December 1, 2018, by 479 stroke survivors: Women (n=244) posted 396,898 tweets, and men (n=235) posted 403,526 tweets. The stroke survivor condition and gender as well as membership in at least 3 stroke-specific Twitter lists of active users were manually verified for all 479 participants. Their total number of tweets since 2007 was 5,257,433; therefore, we analyzed the most recent 15.2% of all their tweets. Positive emotions (anticipation, trust, and joy) were significantly higher (P<.001) in women, while negative emotions (disgust, fear, and sadness) were significantly higher (P<.001) in men in the analysis of raw frequencies and proportion of emotions. Happiness mean scores throughout the considered period show higher levels of happiness in women. We calculated the top 20 topics (with percentages and CIs) more likely addressed by gender and found that women’s topics show higher levels of happiness scores. Conclusions We applied two different approaches—the Plutchik model and hedonometer tool—to a sample of stroke survivors’ tweets. We conclude that women express positive emotions and happiness much more than men.
The Renaissance of Developmental Biology

Since its heyday in the 1980s and 90s, the field of developmental biology has gone into decline; in part because it has been eclipsed by the rise of genomics and stem cell biology, and in part because it has seemed less pertinent in an era with so much focus on translational impact. In this essay, I argue that recent progress in genome-wide analyses and stem cell research, coupled with technological advances in imaging and genome editing, have created the conditions for the renaissance of a new wave of developmental biology with greater translational relevance.
Optimization of Horizontal Aggregation in SQL by using C4.5 Algorithm and K-Means Clustering

Datasets in the horizontal aggregated layout are preferred by most of data mining algorithms, machine learning algorithm. Major efforts are required to compute data in the horizontal aggregated format. There are many inbuilt aggregation functions in SQL, namely, minimum, maximum, average, sum and count. These aggregation functions are used with a query evaluation method to retrieve data in the horizontal aggregation format. Optimization techniques used for vertical aggregation is not appropriate for horizontal aggregation. Standard aggregations are hard to interpret when there are many result rows, especially when grouping attributes having high cardinalities. That is why we proposed C4.5 classification algorithm and K- means clustering algorithm with query evaluation method and aggregation function for optimizing horizontal aggregation. Horizontal aggregation is a method which generates SQL code to return aggregated columns in the horizontal tabular layout. It returns a set of numbers instead of one number per row. There are various applications where the horizontal aggregation is used such as electrical billing, banks, hospital management system, pharmacy, and online library etc. (6).
The Social Promise of Educational Technology: The Case of the Time To Know Program

This article explores the effects of Time To Know, a comprehensive technology-rich learning environment, on low-SES students' learning achievements in Mathematics, Hebrew and English as a Foreign Language (EFL) in Israel. The study is based on the assumption that one of the possible solutions for bridging the social gap can be achieved through narrowing the digital divide, particularly by bringing a 1:1 computing social-constructivist learning environment to the low-SES students. The subjects were 49 5th-grade students from low-SES, who joined a Time To Know program in Israel, and 42 5th-grade students who learned in a traditional setting. Findings indicated that learning with the Time To Know program significantly enhanced students’ Mathematics, Hebrew and EFL achievements. In addition, the findings showed that as a result of learning in the Time To Know environment, the knowledge and skills gap between the students was significantly narrowed. This article is based on data collected in an evaluation study conducted by Manny-Ikan, E. , & Berger-Tikochonski, T. (2010).
Investigations of outdoor-to-indoor mobile-to-mobile radio communication channels

The mobile-to-mobile radio channel was investigated in different suburban outdoor-to-indoor environments. System performance parameters in terms of un-encoded BER and outage probability have been extracted from hardware and software TETRA simulations. In several scenarios, the measured signal envelope statistics were found to be a combination of single and double Rayleigh distributions. The system performances obtained in these scenarios were in general lower than the reference ETSI limits.
Example-based image relighting

Synthesizing photo-realistic images under different illumination conditions remains an important but challenging problem in both computer vision and graphics communities. Over the past few years, many researchers in both communities have tried inventing new methods to capture the complex light interactions existing in nature. However, most of them either rely on expensive custom-built equipment, or only focus on a class of objects, such as faces, to make the problem tractable with their approaches. Our research focuses on an example-based relighting framework for general objects. In this thesis, a review of the representative existing works on image relighting is provided. To avoid explicit 3D model acquisition as required in geometry-based methods and tedious laboratory setups as required for existing image-based methods, an example-based framework is proposed and analyzed. In this framework, we use a database of reference objects captured under different illumination conditions. Given one or several input image(s) of a new object captured under illumination conditions present in the reference database, new images can be synthesized for the input object under novel illumination conditions. We start from a single image approach with spherical surface and Lambertian model assumptions. The analysis is extended to nonspherical surface and more general BRDF models. Finally, a multiple image approach is introduced. Given limited sample images of the input object, the example-based relighting method can synthesize realistic images under different lighting conditions. It is a general and purely data-driven method which does not require an analytical model of the surface geometry or reflectance. The framework is demonstrated on standard real image databases and our own collected data, with comparisons showing that it outperforms image-based model fitting methods. This thesis concludes with a discussion of future work for example-based relighting. These include applying the framework to more complex images using sophisticated similarity estimation methods. Besides exploring physically correct solutions, we may also consider research methods for achieving perceptually appropriate relighting.
PERFORMANCE ANALYSIS OF OPEN SOURCE STORAGE CLOUDS IN CLOUD COMPUTING

Cloud computing is one of the latest research area that helps in storing the information permanently on the servers and manages the different resources for the requested users to provide on-demand services. In order to create the more usable and economic value based cloud computing, the principles, goals and structure of the cloud engineering is of vital importance. The objective of this study is to analyze the CPU and memory performance of different open source clouds. We will use different open source cloud to measure the different performance metrics like CPU time for downloading and uploading of file, memory usage while downloading and uploading the file, standard deviation of CPU usage and standard deviation of memory usage.
Efficient Range-based Query Processing on the Hadoop Distributed File System

There was a common belief that the performance of query in a data warehousing system built on top of Hadoop Distributed File System (HDFS) does not meet the performance in traditional data warehousing systems. Therefore, in the past five years, there has been considerable effort to improve the query performance on data warehousing systems running on the HDFS. The main goal of this work is to develop the mechanisms to support an efficient processing of range-based queries over large size of data stored in the HDFS. In particular, we present the data storage scheme which logically partitions each HDFS block based on the user-specified columns.
Global Adaptive Lyapunov-Based Control of a Robot and Mass-Spring System Undergoing An Impact Collision

The control of dynamic systems that undergo an impact collision is both theoretically challenging and of practical importance. An appeal of studying systems that undergo an impact is that short-duration effects such as high stresses, rapid dissipation of energy, and fast acceleration and deceleration may be achieved from low-energy sources. However, colliding systems present a difficult control challenge because the equations of motion are different when the system status changes suddenly from a non-contact state to a contact state. In this paper an adaptive nonlinear controller is designed to regulate the states of two dynamic systems that collide. The academic example of a planar robot colliding with an unactuated spring-mass system is used to represent a broader class of such systems. The control objective is defined as the desire to command a robot to collide with an unactuated system and regulate the spring-mass to a desired compressed state while compensating for the unknown constant system parameters. Lyapunov-based methods are used to develop a continuous adaptive controller that yields global asymptotic regulation of the spring-mass and robot links. It is interesting to note that one controller is responsible for achieving the control objective when the robot is in free motion (i.e., decoupled from the mass-spring system), when the systems collide, and when the system dynamics are coupled
Common Techniques and Tools for the Analysis of Open Source Software in Order to Detect Code Clones: A Study

Code clone detection and its elimination are introduced as an influential factor in improving software quality, especially in large software systems. The code that duplicates and is in similar files of source is called code clone. So far, researchers introduced and presented many tools and techniques to analyze and identify clones. But given the importance of this paper, some common techniques and tools used to identify clones should be examined and 4 open-source software systems are analyzed using CloneDr tool. According to the results, many clones were identified and the results show that further improvements are needed for high quality software.
Analysis of Protein Interactions

M ost of the work of living organisms is performed by proteins. Proteins do their work by acting on other macromolecules: nucleic acids, carbohydrates, lipids, and, especially, other proteins. Inside cells, protein-protein interactions are instrumental in enzymatic actions upon protein substrates and in the fleeting and lasting protein assemblies that govern signal transduction, cell division, DNA replication, and transcription initiation. Outside cells, protein interactions allow cells to talk with each other: ligands expressed on the cell surface often bind protein receptors expressed on adjacent cells, and secreted protein ligands bind receptors on distant cells. Techniques to detect and study protein-protein interactions have become steadily more easy to use in recent years. This chapter lays them out.
Touch Driven Interaction via NFC EnabledSmartphone

Near Field Communication (NFC) is a set of standards for smart phones and similar devices to establish radio communication with each other by touching them together or bringing them into close proximity, within few inches. Present and anticipated applications include contactless transactions, data exchange, and simplified setup of more complex communications such as Wi-Fi. The NFC is a promising technology for Internet of Things (IoT), refers to uniquely identifiable objects and their virtual representations in an Internet-like structure. In this paper, we propose a system to control electronics appliances through NFC using Internet of Things.
All-N-logic high-speed true-single-phase dynamic CMOS logic

In this paper, a novel all-N-logic single-phase high speed dynamic CMOS logic is introduced and analyzed. The circuits achieve high speed by eliminating the need for the low-speed P-logic blocks. The use of all-N-logic allows the speed of the proposed circuits to be two to three times the speed of conventional CMOS dynamic circuits. An 2:1 frequency divider, using proposed ANL2 circuits, is simulated using 0.8 /spl mu/m CMOS technology with the operating clock frequency reaching as high as 1.5 GHz. A pipelined 8-b carry generator of five-stacked NMOS transistors, which operates at a clock rate of over 710 MHz, has also been simulated. Experimental results show that the proposed circuits operate over 910 MHz implemented in a 1.2 /spl mu/m CMOS technology.
Assessment of Serum Uric Acid Levels According to Sex and Stage for Patients with Alzheimer-type Dementia

Objective: The aim of this study was to identify serum uric acid (UA) concentrations according to disease stage in patients with Alzheimer-type dementia (AD), and to collect data related to the hypothesis that oxidative stress is effective on the etiopathogenesis and progression of disease stage. Materials and Methods: The study was conducted with 180 patients who were categorized into disease stages in accordance with the Clinical Dementia Rating Scale (CDR) and 150 healthy individuals of the same age group. In our retrospective study, patients who showed more than one cognitive deficit and diagnosed with possible AD according to the diagnostic criteria of National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer’s Disease and Related Disorders Association were administered the CDR, Mini-Mental Test (MMSE), Geriatric Depression Rating Scale (GDRS), and individuals in the control group were administered the MMSE and GDRS. Venous blood samples for biochemical studies were collected after 12-14 hours of fasting in the patient and control groups. Results: In patients diagnosed as having AD, it was found that there was a statistically significant increase in age and duration of disease parallel with the progression of disease stages, and a decrease in UA and albumin concentrations in both males and females (p<0.05). Conclusion: Our study supports the hypothesis that the decrease detected in serum UA concentrations in parallel with the progression of disease stages is directly related to the pathogenesis of AD. For the identification of chronic progressive diseases such as AD and to take precautions, the identification of variations in easily accessible and low-cost parameters such as serum albumin and UA concentrations in the early stages becomes important. In future years, when neuroprotective and neuro-restorative treatment options are available, identification of serum UA values as a marker of disease progression and knowledge of the association between serum UA concentrations and disease stage in our data will guide and support research into disease etiology.