LLukas22/scidocs huggingface dataset:
A study in machine learning from imbalanced data for sentence boundary detection in speech

Enriching speech recognition output with sentence boundaries improves its human readability and enables further processing by downstream language processing modules. We have constructed a hidden Markov model (HMM) system to detect sentence boundaries that uses both prosodic and textual information. Since there are more nonsentence boundaries than sentence boundaries in the data, the prosody model, which is implemented as a decision tree classifier, must be constructed to effectively learn from the imbalanced data distribution. To address this problem, we investigate a variety of sampling approaches and a bagging scheme. A pilot study was carried out to select methods to apply to the full NIST sentence boundary evaluation task across two corpora (conversational telephone speech and broadcast news speech), using both human transcriptions and recognition output. In the pilot study, when classification error rate is the performance measure, using the original training set achieves the best performance among the sampling methods, and an ensemble of multiple classifiers from different downsampled training sets achieves slightly poorer performance, but has the potential to reduce computational effort. However, when performance is measured using receiver operating characteristics (ROC) or area under the curve (AUC), then the sampling approaches outperform the original training set. This observation is important if the 0885-2308/$ see front matter 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.csl.2005.06.002 * Corresponding author. Tel.: +1 510 666 2993; fax: +510 666 2956. E-mail addresses: yangl@icsi.berkeley.edu (Y. Liu), nchawla@cse.nd.edu (N.V. Chawla), harper@ecn.purdue.edu (M.P. Harper), ees@speech.sri.com (E. Shriberg), stolcke@speech.sri.com (A. Stolcke). Y. Liu et al. / Computer Speech and Language 20 (2006) 468–494 469 sentence boundary detection output is used by downstream language processing modules. Bagging was found to significantly improve system performance for each of the sampling methods. The gain from these methods may be diminished when the prosody model is combined with the language model, which is a strong knowledge source for the sentence detection task. The patterns found in the pilot study were replicated in the full NIST evaluation task. The conclusions may be dependent on the task, the classifiers, and the knowledge combination approach. 2005 Elsevier Ltd. All rights reserved.
Immunopathogenesis of idiopathic nephrotic syndrome with relapse

Idiopathic change nephrotic syndrome (INS), the most frequent glomerular disease in children and young adults, is characterized by heavy proteinuria and a relapsing remitting course. Although the mechanisms underlying the pathophysiology of proteinuria remain unclear, clinical and experimental observations suggest that lymphocyte and podocyte disturbances are two sides of the disease. The current hypothesis suggests that immune cells release a putative factor, which alters podocyte function resulting in nephrotic proteinuria. Besides T-cell abnormalities, recent evidence of B-cell depletion efficacy in sustained remissions added a new challenge in understanding the immunological mechanisms of INS. In this review, we discuss recent insights related to podocyte disorders occurring in INS and their relevance in human diseases.
Understanding family communication across time zones

Nowadays it has become increasingly common for family members to be distributed in different time zones. These time differences pose specific challenges for communication within the family and result in different communication practices to cope with them. To gain an understanding of current challenges and practices, we interviewed people who regularly communicate with immediate family members living in other time zones. We report primary findings from the interviews, and identify design opportunities for improving the experience of cross time zone family communication.
Analysis of the DC Bias Phenomenon by the Harmonic Balance Finite-Element Method

An Epstein frame-like core model is set up to study the dc-biased problem of the power transformer. The harmonic phenomenon of the model under the dc bias condition is investigated by using the harmonic-balance finite-element method (HBFEM). The harmonic-balance finite element equation is coupled with the external electric circuit. Each harmonic component of the magnetizing current and magnetic field can be calculated directly in the harmonic frequency domains. Comparing the calculated results with the experimental data shows consistency. The dc bias effects on the magnetizing current and the magnetic induction are analyzed through the harmonic solutions.
The effect of male circumcision on sexual satisfaction and function, results from a randomized trial of male circumcision for human immunodeficiency virus prevention, Rakai, Uganda.

OBJECTIVE
To investigate the relationship between adult male circumcision and sexual satisfaction and function in men, as observational studies on the effect of adult male circumcision on sexual satisfaction show conflicting results.


SUBJECTS AND METHODS
We investigated self-reported sexual satisfaction and function among men enrolled in a randomized trial of male circumcision for human immunodeficiency virus (HIV) prevention conducted in Rakai, Uganda. In all, 4456 sexually experienced HIV-negative males aged 15-49 years were enrolled; 2210 were randomized to receive immediate circumcision (intervention arm) and 2246 to circumcision delayed for 24 months (control arm). Men were followed up at 6, 12 and 24 months, and information on sexual desire, satisfaction and erectile dysfunction was collected. These variables were compared between the study arms and over time within the study arms, using chi-square or Fisher's exact tests. The trial registration number is NCT00425984.


RESULTS
There were no differences between the study arms at enrollment and problems with sexual satisfaction and function were reported by <2% of participants in both study arms at all time points. At 6 months, no difficulty with penetration was reported by 98.6% of circumcised men and 99.4% of controls (P = 0.02), and no pain on intercourse was reported by 99.4% circumcised and 98.8% of uncircumcised men (P = 0.05). There were no differences between the study arms in penetration or dyspareunia at later visits. Sexual satisfaction increased from 98.0% at enrollment to 99.9% at 2 years among the controls (P < 0.001), but there was no trend in satisfaction among circumcised men (enrollment 98.5%, 2 years 98.4%, P = 0.8).


CONCLUSION
Adult male circumcision does not adversely affect sexual satisfaction or clinically significant function in men.
A Proposed Test Case Generation Technique Based on Activity Diagrams

114703-5858 IJET-IJENS @ June 2011 IJENS I J E N S Abstract— Software testing is an essential and integral part of the software development process. The testing effort is divided into three parts: test case generation, test execution, and test evaluation. Test case generation is the core of any testing process and automating it saves much time and effort as well as reduces the number of errors and faults. This paper proposes an automated approach for generating test cases from one of the most famed UML diagrams which is the activity diagram. The proposed model introduces an algorithm that automatically creates a table called Activity Dependency Table (ADT), and then uses it to create a directed graph called Activity Dependency Graph (ADG). The ADT is constructed in a detailed form that makes the generated ADG covers all the functionalities in the activity diagram. Finally the ADG with the ADT are used to generate the final test cases. The proposed model includes validation of the generated test cases during the generation process to ensure their coverage and efficiency. The generated test cases meet a hybrid coverage criterion in addition to their form which enables using them in system, regression as well as integration testing. The proposed model saves time and effort besides, increases the quality of generated test cases. The model is implemented on three different systems and evaluated to show its effectiveness.
Interaction between High-Level and Low-Level Image Analysis for Semantic Video Object Extraction

The task of extracting a semantic video object is split into two subproblems, namely, object segmentation and region segmentation. Object segmentation relies on a priori assumptions, whereas region segmentation is data-driven and can be solved in an automatic manner. These two subproblems are not mutually independent, and they can benefit from interactions with each other. In this paper, a framework for such interaction is formulated. This representation scheme based on region segmentation and semantic segmentation is compatible with the view that image analysis and scene understanding problems can be decomposed into lowlevel and high-level tasks. Low-level tasks pertain to region-oriented processing, whereas the high-level tasks are closely related to object-level processing. This approach emulates the human visual system: what one “sees” in a scene depends on the scene itself (region segmentation) as well as on the cognitive task (semantic segmentation) at hand. The higher-level segmentation results in a partition corresponding to semantic video objects. Semantic video objects do not usually have invariant physical properties and the definition depends on the application. Hence, the definition incorporates complex domain-specific knowledge and is not easy to generalize. For the specific implementation used in this paper, motion is used as a clue to semantic information. In this framework, an automatic algorithm is presented for computing the semantic partition based on color change detection. The change detection strategy is designed to be immune to the sensor noise and local illumination variations. The lower-level segmentation identifies the partition corresponding to perceptually uniform regions. These regions are derived by clustering in an N-dimensional feature space, composed of static as well as dynamic image attributes. We propose an interaction mechanism between the semantic and the region partitions which allows to cope with multiple simultaneous objects. Experimental results show that the proposed method extracts semantic video objects with high spatial accuracy and temporal coherence.
Beyond performance: Feature awareness in personalized interfaces

Personalized graphical user interfaces have the potential to reduce visual complexity and improve interaction efficiency by tailoring elements such as menus and toolbars to better suit an individual user's needs. When an interface is personalized to make useful features more accessible for a user's current task, however, there may be a negative impact on the user's awareness of the full set of available features, making future tasks more difficult. To assess this tradeoff we introduce awareness as an evaluation metric to be used in conjunction with performance. We then discuss three studies we have conducted, which show that personalized interfaces trade off awareness of unused features for performance gains on core tasks. The first two studies, previously published and presented only in summary, demonstrate this tradeoff by measuring awareness using a recognition test of unused features in the interface. The studies also evaluated two different types of personalized interfaces: a layered interfaces approach and an adaptive split menu approach. The third study, presented in full, focuses on adaptive split menus and extends results from the first two studies to show that different levels of awareness also correspond to an impact on performance when users are asked to complete new tasks. Based on all three studies and a survey of related work, we outline a design space of personalized interfaces and present several factors that could affect the tradeoff between core task performance and awareness. Finally, we provide a set of design implications that should be considered for personalized interfaces.
Temporal motion recognition and segmentation approach

Separating or segmenting complex activities into basic action primitives is important for event recognition and other applications. In this article, simple approaches are presented for appearance-based action recognition, as well as motion segmentation into its action primitives. Optical flow is computed and split into four channels based on four directions, namely, up, down, left, and right. Based on these four motion vectors, motion history and the corresponding energy templates are generated. These are used for action recognition. Moreover, to segment sequential activity, the temporal motion segmentation (TMS) method is proposed based on the concept of history templates. Based on the total pixel volumes on these templates and their related variations, various directions of the action primitives are segmented temporally. This segmentation method can assist an intelligent system or robot to understand activities and take decisions afterwards. It is a simple and real-time approach. Based on the presented experiments, this approach can be very useful in various application areas. VC 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 91–99, 2009; Published online in Wiley InterScience (www. interscience.wiley.com). DOI 10.1002/ima.20183
Semi-supervised Semantic Pattern Discovery with Guidance from Unsupervised Pattern Clusters

We present a simple algorithm for clustering semantic patterns based on distributional similarity and use cluster memberships to guide semi-supervised pattern discovery. We apply this approach to the task of relation extraction. The evaluation results demonstrate that our novel bootstrapping procedure significantly outperforms a standard bootstrapping. Most importantly, our algorithm can effectively prevent semantic drift and provide semi-supervised learning with a natural stopping criterion.
The nondiscriminating heart: lovingkindness meditation training decreases implicit intergroup bias.

Although meditation is increasingly accepted as having personal benefits, less is known about the broader impact of meditation on social and intergroup relations. We tested the effect of lovingkindness meditation training on improving implicit attitudes toward members of 2 stigmatized social outgroups: Blacks and homeless people. Healthy non-Black, nonhomeless adults (N = 101) were randomly assigned to 1 of 3 conditions: 6-week lovingkindness practice, 6-week lovingkindness discussion (a closely matched active control), or waitlist control. Decreases in implicit bias against stigmatized outgroups (as measured by Implicit Association Test) were observed only in the lovingkindness practice condition. Reduced psychological stress mediated the effect of lovingkindness practice on implicit bias against homeless people, but it did not mediate the reduced bias against Black people. These results suggest that lovingkindness meditation can improve automatically activated, implicit attitudes toward stigmatized social groups and that this effect occurs through distinctive mechanisms for different stigmatized social groups.
“THE PLOT” THICKENS: MORE DATA, MORE DIMENSIONS, MORE USES

The scientific history of the Ramachandran plot is reviewed, emphasizing relationships to the title theme and to trends in current research. The growth and quality of macromolecular structure data have enabled the understanding of relationships with further variables and the application to an ever-widening set of uses such as prediction, simulation, design, motif identification, and structure validation and improvement. Then a current research example is explored, using a new dataset of 8000 selected protein chains and >1.5 million qualityfiltered residues. The new Ramachandran plots show an unprecedented level of detail, allow the valid addition of more subcategories and more dimensions, and point the way toward the feasibility of an essentially complete and robust treatment of torsional conformation in the near future.
Evaluation of effect of self-examination and physical examination on breast cancer.

BACKGROUND
Breast cancer is the number one cancer of women in the world. More than 90% of breast cancers can be cured with early diagnosis followed by effective multimodality treatment. The efficacy of screening by breast self-examination (BSE) and breast physical examination (BPx) is best evaluated using randomized screening trials.


METHOD
A total of 12,660 women aged 35-64 years, 6330 in the intervention group and 6330 in the control group, were randomly selected from four areas of Yazd city, I.R. of Iran. The number of detected cancers along with kind of cancer, staging of cancer, the route of detected cancer and the number of deaths during the first 5 years of the study were collected and analyzed.


RESULTS
No significance difference between the two groups was seen in respect to socio-demographic and socio-economic variables (P > 0.05). Subjects in the intervention group had a response rate of 83.5% for attending the health center and 80.2% for visiting the assigned surgeon. A total of 31 and 13 new cases of breast cancer were identified in the intervention and control groups, respectively, of which 48.5% of cases in the intervention group were <50 yr of age. A significant difference between the cumulative incidence of breast cancer in the two groups with a ratio of 2.4 was observed.


CONCLUSION
BSE & BPx have a significant effect in detecting breast cancers at early stages (<3) suggesting they are effective screening tests with high availability and low costs that can be applied at the community level.
European Geopolitics Resurgent

The Return of Geopolitics in Europe: Social Mechanisms and Foreign Policy Identity Crises. Edited by Guzzini Stefano. Cambridge, UK: Cambridge University Press, 2013. 322 pp., £68.00 hardback (ISBN 978-1-107-02734-3).

The academic field of geopolitics has experienced something of a resurgence in recent years, driven by a changing international environment and advances in the field of critical geopolitics. Moreover, with the growth of—perhaps temporary—questions relating to the future of European integration after the 2008–2009 financial crisis, there has been particular interest in the field of European geopolitics. From a more classical perspective, analysts like Simon and Rogers (2010, 2011), Kaplan (2012), and Grygiel (2012) have sought to chart the changing geopolitical dynamics on the European continent, tracing the role played by the European great powers as they jostle for wealth and power—even during European integration. At the same time, critical geopolitical analysts have sought to analyze the discourses sustaining the geopolitical perspective and worldview, which, despite their hopes to the contrary, refuse to die away.

The Return of Geopolitics in Europe —edited by Stefano Guzzini—is informed decidedly by the second camp, but does something quite unique in that it focuses on the return of geopolitical thinking within Europe before—and not after—the 2008–2009 financial crisis, and its related economic and political fallout. As Guzzini puts it: “a movement to a more Hobbesian culture happened not despite the end of the cold war but because of it” (p. 5). This book therefore shows that—contrary to received wisdom—many European countries witnessed a resurgence of geopolitical thinking after the Cold War, …
Location Identification and Vehicle Tracking using VANET ( VETRAC)

Large cities with fleet of vehicles require a system to determine location of movement of passenger vehicles at a given time. Vehicle tracking systems can be used in theft prevention, retrieval of lost vehicles, providing trafricoriented services on lanes. The Vehicle tracking systems VETRAC enables vehicle drivers or any third party to track the location of any moving vehicle. Most modern vehicle tracking systems use GPS[71 modules which is costly in usage and implementation. Many systems also combine a communications component such as cellular or satellite transmitters to communicate the vehicle's location to a remote user. VETRAC uses WiFi IEEE 802.11 b/g for easy and accurate location of the vehicle, which provides effective and simple communication. Vehicle information can be viewed on electronic maps using the Internet or specialized software. We have designed and developed an Intelligent Vehicle Navigation System, which identify an optimally minimal path for navigation with minimal traffic intensity using WiFi. The system can also be used as a city guide to locate and identify landmarks in a new city.
Segmental pigmentation disorder: A rare form of cutaneous dyspigmentation

BACKGROUND
Segmental pigmentation disorder (SegPD) is a rare type of cutaneous dyspigmentation. This hereditary disorder, first described some 20 years ago, is characterized by hypo and hyperpigmented patches on the trunk, extremities and less likely on the face and neck. These lesions are considered as a type of checkerboard pattern.


CASE PRESENTATION
Herein, we present a 26-year-old male who presented with hyperpigmented patches on his trunk, neck and upper extremities. Considering the clinical and histopathological findings, the diagnosis of SegPD was confirmed.


CONCLUSION
SegPD is a somewhat neglected entity which should be considered in differential diagnosis of pigmentation disorders.