nils-herrmann/clean_scirepeval huggingface dataset:
Towards Understanding Adversarial Learning for Joint Distribution Matching

We investigate the non-identifiability issues associated with bidirectional adversarial training for joint distribution matching. Within a framework of conditional entropy, we propose both adversarial and non-adversarial approaches to learn desirable matched joint distributions for unsupervised and supervised tasks. We unify a broad family of adversarial models as joint distribution matching problems. Our approach stabilizes learning of unsupervised bidirectional adversarial learning methods. Further, we introduce an extension for semi-supervised learning tasks. Theoretical results are validated in synthetic data and real-world applications.
Clustering with Normalized Cuts is Clustering with a Hyperplane

We present a set of clustering algorithms that identify cluster boundaries by searching for a hyperplanar gap in unlabeled data sets. It turns out that the Normalized Cuts algorithm of Shi and Malik , originally presented as a graph-theoretic algorithm, can be interpreted as such an algorithm. Viewing Normalized Cuts under this light reveals that it pays more attention to points away from the center of the data set than those near the center of the data set. As a result, it can sometimes split long clusters and display sensitivity to outliers. We derive a variant of Normalized Cuts that assigns uniform weight to all points, eliminating the sensitivity to outliers.
Expressive writing can increase working memory capacity.

The effect of emotional disclosure through expressive writing on available working memory (WM) capacity was examined in 2 semester-long experiments. In the first study, 35 freshmen assigned to write about their thoughts and feelings about coming to college demonstrated larger working memory gains 7 weeks later compared with 36 writers assigned to a trivial topic. Increased use of cause and insight words was associated with greater WM improvements. In the second study, students (n = 34) who wrote about a negative personal experience enjoyed greater WM improvements and declines in intrusive thinking compared with students who wrote about a positive experience (n = 33) or a trivial topic (n = 34). The results are discussed in terms of a model grounded in cognitive and social psychological theory in which expressive writing reduces intrusive and avoidant thinking about a stressful experience, thus freeing WM resources.
Mind map generator software

In our previous research we have made literature analysis and discovered possible mind map application areas. We have pointed out why currently developed software and methods are not adequate and why we are developing a new one. We have defined system architecture and functionality that our software would have. After that, we proceeded with text-mining algorithm development and testing after which we have concluded with our plans for further research. In this paper we will give basic notions about previously published article and present our custom developed software for automatic mind map generation. This software will be tested. Generated mind maps will be critically analyzed. The paper will be concluded with research summary and possible further research and software improvement.
Single Miller capacitor frequency compensation with nulling resistor for three-stage amplifiers

A frequency compensation technique for three- stage amplifiers is introduced. The proposed solution exploits only one Miller capacitor and a resistor in the compensation network. The straightness of the technique is used to design, using a standard CMOS 0.35-mum process, a 1.5-V OTA driving a 150-pF load capacitor. The dc current consumption is about 14 muA at DC and a 1.6-MHz gain-bandwidth product is obtained, providing significant improvement in both MHz-pF/mA and (V/mus)-pF/mA performance parameters.
A vibration damping optimization algorithm for a parallel machines scheduling problem with sequence-independent family setup times

Parallel machines scheduling problem is a branch of production scheduling, which is among the most difficult combinatorial optimization problems. This paper develops a meta-heuristic algorithm based on the concept of the vibration damping in mechanical vibration, called vibration damping optimization (VDO) algorithm for optimizing the identical parallel machine scheduling problem with sequence-independent family setup times. The objective function of this problem is to minimize the total weighted completion time. Furthermore, the Taguchi experimental design method is applied to set and estimate the appropriate values of the parameters required in our proposed VDO. We computationally compare the results obtained by the proposed VDO with the results of the genetic algorithm (GA) and branch-and-bound method. Consequently, the computational results validate the quality of the proposed algorithm.
MIMO Performance at 700MHz: Field Trials of LTE with Handheld UE

MIMO is one of the techniques used in LTE Release 8 to achieve very high data rates. A field trial was performed in a pre-commercial LTE network. The objective is to investigate how well MIMO works with realistically designed handhelds in band 13 (746-756 MHz in downlink). In total, three different handheld designs were tested using antenna mockups. In addition to the mockups, a reference antenna design with less stringent restrictions on physical size and excellent properties for MIMO was used. The trial comprised test drives in areas with different characteristics and with different network load levels. The effects of hands holding the devices and the effect of using the device inside a test vehicle were also investigated. In general, it is very clear from the trial that MIMO works very well and gives a substantial performance improvement at the tested carrier frequency if the antenna design of the hand-held is well made with respect to MIMO. In fact, the best of the handhelds performed similar to the reference antenna.
Genome-wide atlas of gene expression in the adult mouse brain

Molecular approaches to understanding the functional circuitry of the nervous system promise new insights into the relationship between genes, brain and behaviour. The cellular diversity of the brain necessitates a cellular resolution approach towards understanding the functional genomics of the nervous system. We describe here an anatomically comprehensive digital atlas containing the expression patterns of ∼20,000 genes in the adult mouse brain. Data were generated using automated high-throughput procedures for in situ hybridization and data acquisition, and are publicly accessible online. Newly developed image-based informatics tools allow global genome-scale structural analysis and cross-correlation, as well as identification of regionally enriched genes. Unbiased fine-resolution analysis has identified highly specific cellular markers as well as extensive evidence of cellular heterogeneity not evident in classical neuroanatomical atlases. This highly standardized atlas provides an open, primary data resource for a wide variety of further studies concerning brain organization and function.
Toward Large-Scale Vulnerability Discovery using Machine Learning

With sustained growth of software complexity, finding security vulnerabilities in operating systems has become an important necessity. Nowadays, OS are shipped with thousands of binary executables. Unfortunately, methodologies and tools for an OS scale program testing within a limited time budget are still missing.
 In this paper we present an approach that uses lightweight static and dynamic features to predict if a test case is likely to contain a software vulnerability using machine learning techniques. To show the effectiveness of our approach, we set up a large experiment to detect easily exploitable memory corruptions using 1039 Debian programs obtained from its bug tracker, collected 138,308 unique execution traces and statically explored 76,083 different subsequences of function calls. We managed to predict with reasonable accuracy which programs contained dangerous memory corruptions.
 We also developed and implemented VDiscover, a tool that uses state-of-the-art Machine Learning techniques to predict vulnerabilities in test cases. Such tool will be released as open-source to encourage the research of vulnerability discovery at a large scale, together with VDiscovery, a public dataset that collects raw analyzed data.
Exploring the Communication of Social Support within Virtual Communities: A Content Analysis of Messages Posted to an Online HIV/AIDS Support Group

The present study examined the nature of social support exchanged within an online HIV/AIDS support group. Content analysis was conducted with reference to five types of social support (information support, tangible assistance, esteem support, network support, and emotional support) on 85 threads (1,138 messages). Our analysis revealed that many of the messages offered informational and emotional support, followed by esteem support and network support, with tangible assistance the least frequently offered. Results suggest that this online support group is a popular forum through which individuals living with HIV/AIDS can offer social support. Our findings have implications for health care professionals who support individuals living with HIV/AIDS.
Modeling and simulation of quadcopter using PID controller

Quadcopter also called as quadrotor helicopter, is popular in Unmanned Aerial Vehicles (UAV). They are widely used for variety of applications due to its small size and high stability. In this paper design and development of remote controlled quadcopter using PID (Proportional Integral Derivtive) controller implemented with Ardupilot Mega board is presented. The system consists of IMU (Inertial Measurement Unit) which consists of accelerometer and gyro sensors to determine the system orientation and speed control of four BLDC motors to enable the quadcopter fly in six directions. Simulations analysis of quadcopter is carried out using MATLAB Simulink. Pitch, roll and yaw responses of quadcopter is obtained and PID controller is used to stabilize the system response. Finally the prototype of quadcopter is build PID logic is embedded on it. The working and performance of quadcopter is tested and desired outputs were obtained.
Theoretical Design of Broadband Multisection Wilkinson Power Dividers With Arbitrary Power Split Ratio

This paper describes a new approach for the theoretical design of unequal multisection Wilkinson power dividers, using single-layer microstrip lines. Similar to most multisection structures, the presented unequal divider can provide a broadband performance. To provide the design guideline, closed-form formulas are derived for the divider with odd or even number of sections. In each case, various simulations have been conducted to investigate the performance of dividers over the frequency band. For experimental verifications, two 1:2 power dividers with a center frequency of 1 GHz are fabricated, having three and four sections. The simulated and measured results are presented, and good agreements between them are observed.
An Ontology for Software

The domain of software is a primary candidate for being formalized in an ontology. On the one hand, the domain is sufficiently complex with different paradigms (e.g., object orientation) and different aspects (e.g., security, legal information, interface descriptions, etc.). On the other hand, the domain is sufficiently stable, i.e., new paradigms and aspects occur rather seldom. Capturing this stable core in a reference ontology for software can be fruitful in order to prevent modeling from scratch. For example, the approaches described in the Chapter “Ontologies and Software Engineering” introduce individual formalizations of at least one paradigm or aspect although they share basic principles. In this chapter, we present such a reference ontology for software, called the Core Software Ontology, which formalizes common concepts in the software engineering realm, such as data, software with its different shades of meaning, classes, methods, etc. As we cannot possibly formalize a complete and comprehensive view of software, the Core Software Ontology is designed for extensibility in different directions. In order to demonstrate the extensibility, the chapter presents three examples of how to extend the core ontology with the notions of libraries, policies, and software components. The reference nature of such an ontology makes it important to clarify the intended meanings of its concepts and associations. Otherwise, users often have a hard time untangling the intended meanings. The prevailing type of ontologies, namely ones which are lightweight and quite often reduced to simple taxonomies, are not eligible for this purpose because they exhibit the following shortcomings (as identified in ):
The Integrative Action of the Nervous System

In this book Professor Holmes discusses some of the evidence relating to one of the most baffling problems yet recognized by biologists-the factors involved in the regulation of growth and form. A wide range of possible influences, from enzymes to cellular competition, is considered. Numerous experiments and theories are described, with or without bibliographic citation. There is a list of references for each chapter and an index. The subject from a scientific standpoint is an exceedingly difficult one, for the reason that very little indeed is understood regarding such phenomena as differentiation. It follows that the problem offers fine opportunities for intellectual jousting by mechanists and vitalists, that hypotheses and theories must often be the weapons of choice, and philosophy the armor. Professor Holmes gives us a good seat from which to watch the combats, explains clearly what is going on, and occasionally slips away to enter the lists himself. This stereoscopic atlas of anatomy was designed as an aid in teaching neuro-anatomy for beginning medical students and as a review for physicians taking Board examinations in Psychiatry and Neurology. Each plate consists of a pair of stereoscopic photographs and a labelled diagram of the important parts seen in the photograph. Perhaps in this day of scarcity of materials, particularly of human brains hardened for dissection, photographs of this kind conceivably can be used as a substitute. Successive stages of dissection are presented in such a fashion that, used in conjunction with the dissecting manual, a student should be able to identify most of the important components of the nervous system without much outside help. The area covered is limited to the gross features of the brain and brain stem and perhaps necessarily does not deal with any of the microscopic structure. So much more can be learned from the dissection of the actual brain that it is doubtful if this atlas would be useful except where brains are not available. A good deal of effort has been spent on the preparation of this atlas, with moderately successful results.
Orientation robust object detection in aerial images using deep convolutional neural network

Detecting objects in aerial images is challenged by variance of object colors, aspect ratios, cluttered backgrounds, and in particular, undetermined orientations. In this paper, we propose to use Deep Convolutional Neural Network (DCNN) features from combined layers to perform orientation robust aerial object detection. We explore the inherent characteristics of DC-NN as well as relate the extracted features to the principle of disentangling feature learning. An image segmentation based approach is used to localize ROIs of various aspect ratios, and ROIs are further classified into positives or negatives using an SVM classifier trained on DCNN features. With experiments on two datasets collected from Google Earth, we demonstrate that the proposed aerial object detection approach is simple but effective.
Culture , product type , and price influences on consumer purchase intention to buy personalized products online

With personalization, consumers can choose from various product attributes and a customized product is assembled based on their preferences. Marketers often offer personalization on websites. This paper investigates consumer purchase intentions toward personalized products in an online selling situation. The research builds and tests three hypotheses: (1) intention to purchase personalized products will be affected by individualism, uncertainty avoidance, power distance, and masculinity dimensions of a national culture; (2) consumers will be more likely to buy personalized search products than experience products; and (3) intention to buy a personalized product will not be influenced by price premiums up to some level. Results indicate that individualism is the only culture dimension to have a significant effect on purchase intention. Product type and individualism by price interaction also have a significant effect, whereas price does not. Major findings and implications are discussed. a Department of Business Administration, School of Economics and Business, Hanyang University, Ansan, South Korea b Department of International Business, School of Commerce and Business, University of Auckland, Auckland, New Zealand c School of Business, State University of New York at New Paltz, New Paltz, New York 12561, USA This work was supported by a Korea Research Foundation Grant (KRF-2004-041-B00211) to the first author.  E-mail addresses: jmoon@hanyang.ac.kr (J. Moon), d.chadee@auckland.ac.nz (D. Chadee), tikoos@newpaltz.edu (S. Tikoo). 1 Tel.: +64 9 373 7599 x85951. 2 Tel.: +1 845 257 2959.
'One flew over the psychiatric unit': mental illness and the media.

Media representation of mental illness has received growing research attention within a variety of academic disciplines. Cultural and media studies have often dominated in this research and discussion. More recently healthcare professionals have become interested in this debate, yet despite the importance of this subject only a selection of papers have been published in professional journals relating to nursing and healthcare. This paper examines the way in which mental illness in the United Kingdom is portrayed in public life. Literature from the field of media studies is explored alongside the available material from the field of mental healthcare. Three main areas are used to put forward an alternative approach: film representation and newspaper reporting of mental illness; the nature of the audience; and finally the concept of myth. The paper concludes by considering this approach in the context of current mental health policy on mental health promotion.
The performance of universal encoding

iI31 --; “The accuracy of radar angle measurements,” Hughes Aircraft Comoanv. Tech. Reo. IDC 2764/63. Auz. 13. 1973. -; “Monopulse accuracy-scintillatingvtargets,” Hughes Aircraft Company, Tech. Rep. IDC 2241/S, Feb. II, 1974. R. A. Dibos, Nonlinear mapping of MLE angle information,” Hughes Aircraft Company, Tech. Rep. IDC 23 12.00/l 84, Mar. 1978. E. M. Hofstetter and D. F. Delong, Jr., “Detection and parameter estimation in an amplitude comparison monopulse radar,”  Jan. 1969. A. M. Kagan and V. V. Pits, “An invariant detection of signal by a monopulse radar receiver,” Radio Eng.  21, no. 11, pp 42-46, 1976. A. K. Zhuravlev and N. A. Suslov, “Statistical characteristics of signals at the output of the receiving equipment of a monopulse aoniometer.” Rodio Ena. Electron. Phvs.. vol. 14. no. 12. vv 1945i948, 1969. __
Software paradigms, assessment types and non-functional requirements in model-based integration testing: a systematic literature review

In modern systems, like cyber-physical systems, where software and physical services are interacting, safety, security or performance play an important role. In order to guarantee the correct interoperability of such systems, with respect to functional and non-functional requirements, integration testing is an effective measure to achieve this. Model-based testing moreover not only enables early definition and validation, but also test automation. This makes it a good choice to overcome urgent challenges of integration testing.  Many publications on model-based integration testing (MBIT) approaches can be found. Nevertheless, a study giving a systematic overview on the underlying software paradigms, measures for guiding the integration testing process as well as non-functional requirements they are suitable for, is missing. The aim of this paper is to find and synthesize the relevant primary studies to gain a comprehensive understanding of the current state of model-based integration testing.  For synthesizing the relevant studies, we conducted a systematic literature review (SLR) according to the guidelines of Kitchenham.  The systematic search and selection retrieved 83 relevant studies from which data has been extracted. Our review identified three assessment criteria for guiding the testing process, namely static metrics, dynamic metrics and stochastic &random. In addition it shows that just a small fraction considers non-functional requirements. Most approaches are for component-oriented systems.  Results from the SLR show that there are two major research gaps. First, there is an accumulated need for approaches in the MBIT field that support non-functional requirements, as they are gaining importance. Second, means for steering the integration testing process, especially together with automation, need to evolve.
Incentivizing the dissemination of truth versus fake news in social networks

The concept of “truth,” as a public good is the production of a collective understanding, which emerges from a complex network of social interactions. The recent impact of social networks on shaping the perception of truth in political arena shows how such perception is corroborated and established by the online users, collectively. However, investigative journalism for discovering truth is a costly option, given the vast spectrum of online information. In some cases, both journalist and online users choose not to investigate the authenticity of the news they receive, because they assume other actors of the network had carried the cost of validation. Therefore, the new phenomenon of “fake news” has emerged within the context of social networks. The online social networks, similarly to System of Systems, cause emergent properties, which makes authentication processes difficult, given availability of multiple sources. In this study, we show how this conflict can be modeled as a volunteer's dilemma. We also show how the public contribution through news subscription (shared rewards) can impact the dominance of truth over fake news in the network.
SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes

This paper presents SceneCut, a novel approach to jointly discover previously unseen objects and non-object surfaces using a single RGB-D image. SceneCut's joint reasoning over scene semantics and geometry allows a robot to detect and segment object instances in complex scenes where modern deep learning-based methods either fail to separate object instances, or fail to detect objects that were not seen during training. SceneCut automatically decomposes a scene into meaningful regions which either represent objects or scene surfaces. The decomposition is qualified by an unified energy function over objectness and geometric fitting. We show how this energy function can be optimized efficiently by utilizing hierarchical segmentation trees. Moreover, we leverage a pre-trained convolutional oriented boundary network to predict accurate boundaries from images, which are used to construct high-quality region hierarchies. We evaluate SceneCut on several different indoor environments, and the results show that SceneCut significantly outperforms all the existing methods.