nils-herrmann/clean_scirepeval huggingface dataset:
Image Alignment and Stitching : A Tutorial 1

This tutorial reviews image alignment and image stitching algorithms. Image alignment algorithms can discover the correspondence relationships among images with varying degrees of overlap. They are ideally suited for applications such as video stabilization, summarization, and the creation of panoramic mosaics. Image stitching algorithms take the alignment estimates produced by such registration algorithms and blend the images in a seamless manner, taking care to deal with potential problems such as blurring or ghosting caused by parallax and scene movement as well as varying image exposures. This tutorial reviews the basic motion models underlying alignment and stitching algorithms, describes effective direct (pixel-based) and feature-based alignment algorithms, and describes blending algorithms used to produce seamless mosaics. It closes with a discussion of open research problems in the area.
GLSR-VAE: Geodesic latent space regularization for variational autoencoder architectures

VAEs (Variational AutoEncoders) have proved to be powerful in the context of density modeling and have been used in a variety of contexts for creative purposes. In many settings, the data we model possesses continuous attributes that we would like to take into account at generation time. We propose in this paper GLSR-VAE, a Geodesic Latent Space Regularization for the Variational AutoEncoder architecture and its generalizations which allows a fine control on the embedding of the data into the latent space. When augmenting the VAE loss with this regularization, changes in the learned latent space reflects changes of the attributes of the data. This deeper understanding of the VAE latent space structure offers the possibility to modulate the attributes of the generated data in a continuous way. We demonstrate its efficiency on a monophonic music generation task where we manage to generate variations of discrete sequences in an intended and playful way.
Protocol for developing ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling

The application of Artificial Neural Networks (ANNs) in the field of environmental and water resources modelling has become increasingly popular since early 1990s. Despite the recognition of the need for a consistent approach to the development of ANN models and the importance of providing adequate details of the model development process, there is no systematic protocol for the development and documentation of ANN models. In order to address this shortcoming, such a protocol is introduced in this paper. In addition, the protocol is used to critically review the quality of the ANN model development and reporting processes employed in 81 journal papers since 2000 in which ANNs have been used for drinking water quality modelling. The results show that model architecture selection is the best implemented step, while greater focus should be given to input selection considering input independence and model validation considering replicative and structural validity.
A Priority based Round Robin CPU Scheduling Algorithm for Real Time Systems

The main objective of this paper is to develop a new approach for round robin C P U scheduling a l g o r i t h m which improves the performance of CPU in real time operating system. The proposed Priority based Round-Robin CPU Scheduling algorithm is based on the integration of round-robin and priority scheduling algorithm. It retains the advantage of round robin in reducing starvation and also integrates the advantage of priority scheduling. The proposed algorithm also implements the concept of aging by assigning new priorities to the processes. Existing round robin CPU scheduling algorithm cannot be implemented in real time operating system due to their high context switch rates, large waiting time, large response time, large turnaround time and less throughput. The proposed algorithm improves all the drawbacks of round robin C P U scheduling algorithm. The paper also presents the comparative analysis of proposed algorithm with existing round robin scheduling algorithm on the basis of varying time quantum, average waiting time, average turnaround time and number of context switches.
Stochastic Security for Operations Planning With Significant Wind Power Generation

In their attempt to cut down on greenhouse gas emissions from electricity generation, several countries are committed to install wind power generation up to and beyond the 10%-20% penetration mark. However, the large-scale integration of wind power represents a challenge for power system operations planning because wind power 1) cannot be dispatched in the classical sense; and 2) its output varies as weather conditions change. This warrants the investigation of alternative short-term power system operations planning methods capable of better coping with the nature of wind generation while maintaining or even improving the current reliability and economic performance of power systems. To this end, this paper formulates a short-term forward electricity market-clearing problem with stochastic security capable of accounting for nondispatchable and variable wind power generation sources. The principal benefit of this stochastic operation planning approach is that, when compared to a deterministic worst-case scenario planning philosophy, it allows greater wind power penetration without sacrificing security.
Cluster validity functions for categorical data: a solution-space perspective

For categorical data, there are three widely-used internal validity functions: the $$k$$ k -modes objective function, the category utility function and the information entropy function, which are defined based on within-cluster information only. Many clustering algorithms have been developed to use them as objective functions and find their optimal solutions. In this paper, we study the generalization, effectiveness and normalization of the three validity functions from a solution-space perspective. First, we present a generalized validity function for categorical data. Based on it, we analyze the generality and difference of the three validity functions in the solution space. Furthermore, we address the problem whether the between-cluster information is ignored when these validity functions are used to evaluate clustering results. To the end, we analyze the upper and lower bounds of the three validity functions for a given data set, which can help us estimate the clustering difficulty on a data set and compare the performance of a clustering algorithm on different data sets.
A study in two-handed input

Two experiments were run to investigate two-handed input. The experimental tasks were representative of those found in CAD and office information systems.
Experiment one involved the performance of a compound selection/positioning task. The two sub-tasks were performed by different hands using separate transducers. Without prompting, novice subjects adopted strategies that involved performing the two sub-tasks simultaneously. We interpret this as a demonstration that, in the appropriate context, users are capable of simultaneously providing continuous data from two hands without significant overhead. The results also show that the speed of performing the task was strongly correlated to the degree of parallelism employed.
Experiment two involved the performance of a compound navigation/selection task. It compared a one-handed versus two-handed method for finding and selecting words in a document. The two-handed method significantly outperformed the commonly used one-handed method by a number of measures. Unlike experiment one, only two subjects adopted strategies that used both hands simultaneously. The benefits of the two-handed technique, therefore, are interpreted as being due to efficiency of hand motion. However, the two subjects who did use parallel strategies had the two fastest times of all subjects.
Protection in Operating Systems

A model of protection mechanisms in computing systems is presented and its appropriateness is argued. The “safety” problem for protection systems under this model is to determine in a given situation whether a subject can acquire a particular right to an object. In restricted cases, it can be shown that this problem is decidable, i.e. there is an algorithm to determine whether a system in a particular configuration is safe. In general, and under surprisingly weak assumptions, it cannot be decided if a situation is safe. Various implications of this fact are discussed.
Sexual stigma and sexual prejudice in the United States: a conceptual framework.

In 1972, psychologist George Weinberg’s book, Society and the Healthy Homosexual , introduced readers to a new term, homophobia , and to the then-novel idea that hostility to homosexuality, rather than homosexuality itself, posed a threat to mental health (Weinberg, 1972 ; see also Herek, 2004) . The following year, the American Psychiatric Association’s Board of Directors declared that homosexuality is not inherently associated with mental illness and voted to remove it from the Diagnostic and Statistical Manual of Mental Disorders , or DSM (Bayer, 1987 ; Minton, 2002) .  Thus, a major cultural institution renounced its longstanding role in legitimating society’s stigmatization of homosexuality just when the psychological manifestations of such stigma were beginning to be redefined as a social problem. This historic confluence of events provides an appropriate starting point for the present chapter. The term homophobia has gained widespread usage since 1972, even as its limitations have become increasingly apparent. Chief among these is its construction of prejudice as an individual pathology. As I have explained elsewhere (Herek, 2004) , this clinically derived perspective limits our ability to understand hostility toward sexual minorities, both among individuals and in society at large. I have argued instead for the value of framing heterosexuals’ negative responses to sexual minorities in terms of sexual prejudice and of conceptualizing sexual prejudice as the internalization of societal stigma (Herek, 2000a, 2004, 2007 ; Herek, Chopp, & Strohl, 2007) . In the present chapter, I elaborate on these points and provide a more detailed framework than I have previously presented for conceptualizing both societal and individual reactions to homosexuality and sexual minorities in the United States.
Information security incident management process

The modern requirements and the best practices in the field of Information Security (IS) Incident Management Process (ISIMP) are analyzed. "IS event" and "IS incident" terms, being used for ISIMP, have been defined. An approach to ISIMP development has been created. According to this approach ISIMP processes are described. As an example the «Vulnerabilities, IS events and incidents detection and notification» joint process is examined in detail.
Layout Analysis for Scanned PDF and Transformation to the Structured PDF Suitable for Vocalization and Navigation

Information can include text, pictures and signatures that can be scanned into a document format, such as the Portable Document Format (PDF), and easily emailed to recipients around the world. Upon the document’s arrival, the receiver can open and view it using a vast array of different PDF viewing applications such as Adobe Reader and Apple Preview. Hence, today the use of the PDF has become pervasive. Since the scanned PDF is an image format, it is inaccessible to assistive technologies such as a screen reader. Therefore, the retrieval of the information needs Optical Character Recognition (OCR). The OCR software scans the scanned PDF file and through text extraction generates an editable text formatted document. This text document can then be edited, formatted, searched and indexed as well as translated or converted to speech. A problem that the OCR software does not solve is the accurate regeneration of the full text layout. This paper presents a technology that addresses this issue by closely preserving the original textual layout of the scanned PDF using the open source document analysis and OCR system (OCRopus) based on geometric layout and positioning information. The main issues considered in this research are the preservation of the correct reading order, and the representation of common logical structured elements such as section headings, line breaks, paragraphs, captions, and sidebars, foot-bars, running headers, embedded images, graphics, tables and mathematical expressions.
Characterizing Cloud Applications on a Google Data Center

In this paper, we characterize Google applications, based on a one-month Google trace with over 650k jobs running across over 12000 heterogeneous hosts from a Google data center. On one hand, we carefully compute the valuable statistics about task events and resource utilization for Google applications, based on various types of resources (such as CPU, memory) and execution types (e.g., whether they can run batch tasks or not). Resource utilization per application is observed with an extremely typical Pareto principle. On the other hand, we classify applications via a K-means clustering algorithm with optimized number of sets, based on task events and resource usage. The number of applications in the K-means clustering sets follows a Pareto-similar distribution. We believe our work is very interesting and valuable for the further investigation of Cloud environment.
Towards Natural Interactive Question Answering

Interactive question answering systems should allow users to lead a coherent information seeking dialogue. Compared with systems that only locally evaluate a question, interactive systems facilitate the information seeking process and provide a more natural feel. We show that by extending a QA system to handle several types of anaphora and ellipsis, the naturalness of the interaction can be considerably improved. We describe an implementation in our prototype QA system for German and give a walk-through example of the enhanced interaction capabilities.
Flexible job-shop scheduling with parallel variable neighborhood search algorithm

Flexible job-shop scheduling problem (FJSP) is an extension of the classical job-shop scheduling problem. FJSP is NP-hard and mainly presents two difficulties. The first one is to assign each operation to a machine out of a set of capable machines, and the second one deals with sequencing the assigned operations on the machines. This paper proposes a parallel variable neighborhood search (PVNS) algorithm that solves the FJSP to minimize makespan time. Parallelization in this algorithm is based on the application of multiple independent searches increasing the exploration in the search space. The proposed PVNS uses various neighborhood structures which carry the responsibility of making changes in assignment and sequencing of operations for generating neighboring solutions. The results obtained from the computational study have shown that the proposed algorithm is a viable and effective approach for the FJSP.
A Survey of Machine Learning Techniques for Spam Filtering

Email spam or junk e-mail (unwanted e-mail “usually of a commercial nature sent out in bulk”) is one of the major problems of the today's Internet, bringing financial damage to companies and annoying individual users. Among the approaches developed to stop spam, filtering is an important and popular one. Common uses for mail filters include organizing incoming email and removal of spam and computer viruses. A less common use is to inspect outgoing email at some companies to ensure that employees comply with appropriate laws. Users might also employ a mail filter to prioritize messages, and to sort them into folders based on subject matter or other criteria. Mail filters can be installed by the user, either as separate programs, or as part of their email program (email client). In email programs, users can make personal, "manual" filters that then automatically filter mail according to the chosen criteria. In this paper, we present a survey of the performance of five commonly used machine learning methods in spam filtering. Most email programs now also have an automatic spam filtering function.
Wolverine: A Wearable Haptic Interface for Grasping in VR

The Wolverine is a mobile, wearable haptic device designed for simulating the grasping of rigid objects in virtual environment. In contrast to prior work on force feedback gloves, we focus on creating a low cost, lightweight, and wireless device that renders a force directly between the thumb and three fingers to simulate objects held in pad opposition type grasps. Leveraging low-power brake-based locking sliders, the system can withstand over 100N of force between each finger and the thumb, and only consumes 2.78 Wh(10 mJ) for each braking interaction. Integrated sensors are used both for feedback control and user input: time-of-flight sensors provide the position of each finger and an IMU provides overall orientation tracking. This design enables us to use the device for roughly 6 hours with 5500 full fingered grasping events. The total weight is 55g including a 350 mAh battery.
Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognition

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). GECCO ’18 Companion, July 15--19, 2018, Kyoto, Japan  978-1-4503-57647/18/07...$15.00 DOI https://doi.org/10.1145/3205651.3207859
Evaluating the Impact of Social Selfishness on the Epidemic Routing in Delay Tolerant Networks

To cope with the uncertainty of transmission opportunities between mobile nodes, Delay Tolerant Networks (DTN) routing exploits opportunistic forwarding mechanism. This mechanism requires nodes to forward messages in a cooperative and altruistic way. However, in the real world, most of the nodes exhibit selfish behaviors such as individual and social selfishness. In this paper, we investigate the problem of how social selfishness influences the performance of epidemic routing in DTN. First, we model the message delivery process with social selfishness as a two dimensional continuous time Markov chain. Then, we obtain the system performance of message delivery delay and delivery cost by explicit expressions. Numerical results show that DTN is quite robust to social selfishness, which increases the message delivery delay, but there is more reducing of delivery cost.
Designing good algorithms for MapReduce and beyond

As MapReduce/Hadoop grows in importance, we find more exotic applications being written this way. Not every program written for this platform performs as well as we might wish. There are several reasons why a MapReduce program can underperform expectations. One is the need to balance the communication cost of transporting data from the mappers to the reducers against the computation done at the mappers and reducers themselves. A second important issue is selecting the number of rounds of MapReduce. A third issue is that of skew. If wall-clock time is important, then using many different reduce-keys and many compute nodes may minimize the time to finish the job. Yet if the data is uncooperative, and no provision is made to distribute the data evenly, much of the work is done by a single node.
A Linear Algorithm for Embedding Planar Graphs Using PQ-Trees

This paper presents a simple linear algorithm for embedding (or drawing) a planar graph in the plane. The algorithm is based on the “vertex-addition” algorithm of Lempel, Even, and Cederbaum (“Theory of Graphs,” Intl. Sympos. Rome, July 1966,  1967) for the planarity testing, and is a modification of Booth and Lueker’s ( (1976), 335379) implementation of the testing algorithm using a PQ-tree. Compared with the known embedding algorithm of Hopcroft and Tarjan ( 21, No. 4 (1974), 549-568), this algorithm is conceptually simple and easy to understand or implement. Moreover this embedding algorithm can find all the embeddings of a planar graph.
Spam Detection Using Artificial Neural Networks ( Perceptron Learning Rule )

Spam is email sent in bulk where there is no direct agreement in place between the recipient and the sender to receive email solicitation. To prevent the delivery of this so called spam, an automated tool called a spam filter is used to recognize spam. The circular nature of these definitions along with their appeal to the intent of sender and recipient make them difficult to formalize. The spam problem seems to persist and the current state of the art techniques in fighting this problem seems not to provide full proof. There are several approaches which try to stop or reduce the huge amount of spam on individuals. These approaches include legislative measures such as anti-spam laws over world-wide. Other techniques are known as Origin-Based filters which are based on using network information and IP addresses in order to detect whether a message is spam or not. The most common techniques are the filtering techniques attempting to identify whether a message is spam or not based on the content and other characteristics of the message. In this paper, we present a technique to spam filtering using Artificial Neural Networks, and the perceptron learning rule.
Neural mechanisms of empathy in humans: a relay from neural systems for imitation to limbic areas.

How do we empathize with others? A mechanism according to which action representation modulates emotional activity may provide an essential functional architecture for empathy. The superior temporal and inferior frontal cortices are critical areas for action representation and are connected to the limbic system via the insula. Thus, the insula may be a critical relay from action representation to emotion. We used functional MRI while subjects were either imitating or simply observing emotional facial expressions. Imitation and observation of emotions activated a largely similar network of brain areas. Within this network, there was greater activity during imitation, compared with observation of emotions, in premotor areas including the inferior frontal cortex, as well as in the superior temporal cortex, insula, and amygdala. We understand what others feel by a mechanism of action representation that allows empathy and modulates our emotional content. The insula plays a fundamental role in this mechanism.
Satisfaction, trust and online purchase intention: A study of consumer perceptions

This paper tries to do the research of analyzing the relation of the customer trust, the customer satisfaction and purchase intention under the electronic commerce shopping environment. Drawing on the theory of customer trust, customer satisfaction and purchase intention, based on a survey of 102 respondents from the University in China, the United Kingdom, and the United States, the results showed that there is significant correlation between satisfaction and trust, satisfaction and purchase intention, trust and purchase intention, and more than 50% of respondents chose Taobao and Tmall, and the second is Amazon when they shopping onling. It could be expected that this kind of study is able to provide suggestion and guide for internet merchant.
Identification of Photovoltaic Source Models

This paper presents a photovoltaic (PV) model estimation method from the PV module data. The model is based on a single-diode model of a PV cell. The cell model of a module is extended to estimate the parameters of arrays. The variation of the parameters with change in temperature and irradiance is also studied. Finally, estimation of the maximum power point from the estimated parameters under varying environmental conditions is presented.