nils-herrmann/clean_scirepeval huggingface dataset:
Negotiation and Cooperation in Multi-Agent Environments

Automated intelligent agents inhabiting a shared environment must coordinate their activities Cooperation not merely coordination may improve the performance of the individual agents or the overall behavior of the system they form Research in Distributed Arti cial Intelligence DAI addresses the problem of designing automated intelligent systems which interact e ectively DAI is not the only eld to take on the challenge of understanding cooperation and coordination There are a variety of other multi entity environments in which the entities coordinate their activity and cooperate Among them are groups of people animals particles and computers We argue that in order to address the challenge of building coordinated and collaborated intelligent agents it is bene cial to combine AI techniques with methods and techniques from a range of multi entity elds such as game theory operations research physics and philosophy To support this claim we describe some of our projects where we have successfully taken an interdisciplinary approach We demonstrate the bene ts in applying multi entity methodologies and show the adaptations modi cations and extensions necessary for solving the DAI problems This is an extended version of a lecture presented upon receipt of the Computers and Thought Award at the th International Joint Conference on Arti cial Intelligence in Montreal Canada August
Using Risk to Balance Agile and Plan-Driven Methods

M ethodologies such as Extreme Programming (XP), Scrum, and agile software development promise increased customer satisfaction, lower defect rates, faster development times, and a solution to rapidly changing requirements. Plan-driven approaches such as Cleanroom, the Personal Software Process, or methods based on the Capability Maturity Model promise predictability , stability, and high assurance. However, both agile and planned approaches have situation-dependent shortcomings that, if left unaddressed, can lead to project failure. The challenge is to balance the two approaches to take advantage of their strengths in a given situation while compensating for their weaknesses. We present a risk-based approach for structuring projects to incorporate both agile and plan-driven approaches in proportion to a project's needs. We drew this material from our book, Balancing Agility and Discipline: A Guide for the Perplexed, to be published in 2003. Our method uses risk analysis and a unified process framework to tailor risk-based processes into an overall development strategy. This method enhances the ability of key development team members to understand their environment and organizational capabilities and to identify and collaborate with the project's stakeholders. We use risk analysis to define and address risks particularly associated with agile and plan-driven methods. The Risk-Based Spiral Model Anchor Points 2 provide the framework for this process. Both the Rational Unified Process 3 (RUP) and the Model-Based Architecting and Software Engineering (Mbase) process 4 have adopted these anchor points, which are essentially an integrated set of decision criteria for stakeholder commitment at specific points in the development process. Our method consists of five steps. Step 1 First, we apply risk analysis to specific risk areas associated with agile and plan-driven methods. We identify three specific risk categories: environmental , agile, and plan-driven. While not a simple task, Step 1 provides the basis for making decisions about the development strategy later in the process. If we uncover too much uncertainty about some risk categories, spending resources early to buy information about the project aspects that create the uncertainty may prove prudent. The candidate risks we describe are just that— candidates for consideration. They are neither complete nor always applicable, but serve as guides to stimulate participants' thinking. Next, we evaluate the risk analysis results to determine if the project at hand is appropriate for either purely agile or purely plan-driven methods. In these cases, the project characteristics fall squarely in the home ground of one approach or A …
Runtime Verification of Ethereum Smart Contracts

The notion of smart contracts in distributed ledger systems have been hailed as a safe way of enforcing contracts between participating parties. However, unlike legal contracts, which talk about ideal behaviour and consequences of not adhering to such behaviour, smart contracts are by their very nature executable code, giving explicit instructions on how to achieve compliance. Executable specification languages, particularly Turing complete ones, are notoriously known for the difficulty of ensuring correctness, and recent incidents which led to huge financial losses due to bugs in smart contracts, have highlighted this issue. In this paper we show how standard techniques from runtime verification can be used in the domain of smart contracts, including a novel stake-based instrumentation technique which ensures that the violating party provides insurance for correct behaviour. The techniques we describe have been partially implemented in a proof-of-concept tool ContractLarva, which we discuss in this paper.
Towards the Success of ERP Systems : Case Study in Two Moroccan Companies

For over a decade, ERP systems in Morocco have shown a significant increase. Companies make large investments in these scale systems in order to anticipate positive impacts on their organization. Measuring ERP systems success becomes an important criterion for the stakeholders in justifying the associated investment. In this paper, we will examine the success of these systems by using a qualitative research method based on a case study approach. We will provide an insight into how two Moroccan organizations perceive the success of their ERP systems. Findings indicated that Information, system quality and net benefits are the three main dimensions of success.
Latent syntactic structure-based sentiment analysis

People share their opinions about things like products, movies and services using social media channels. The analysis of these textual contents for sentiments is a gold mine for marketing experts, thus automatic sentiment analysis is a popular area of applied artificial intelligence. We propose a latent syntactic structure-based approach for sentiment analysis which requires only sentence-level polarity labels for training. Our experiments on three domains (movie, IT products, restaurant) show that a sentiment analyzer that exploits syntactic parses and has access only to sentence-level polarity annotation for in-domain sentences can outperform state-of-the-art models that were trained on out-domain parse trees with sentiment annotation for each node of the trees. In practice, millions of sentence-level polarity annotations are usually available for a particular domain thus our approach is applicable for training a sentiment analyzer for a new domain while it can exploit the syntactic structure of sentences as well.
BM3D-PRGAMP: Compressive phase retrieval based on BM3D denoising

The explosion of computational imaging has seen the frontier of image processing move past linear problems, like denoising and deblurring, and towards non-linear problems such as phase retrieval. There has a been a corresponding research thrust into non-linear image recovery algorithms, but in many ways this research is stuck where linear problem research was twenty years ago: Models, if used at all, are simple designs like sparsity or smoothness. In this paper we use denoisers to impose elaborate and accurate models in order to perform inference on generalized linear systems. More specifically, we use the state-of-the-art BM3D denoiser within the Generalized Approximate Message Passing (GAMP) framework to solve compressive phase retrieval in a variety of different contexts. Our method demonstrates recovery performance equivalent to existing techniques using fewer than half as many measurements. This dramatic improvement in compressive phase retrieval performance opens the door for a whole new class of imaging systems.
Social Recommendation in Location Based Social Network Using Text Mining

The rapid growth of location-based social networks (LBSNs) has greatlyenriched people’s urban experience through social media and attracted increasingnumber of users in recent years. Typical location-based social networking sites allowusers to “check in” at a physical place and share the location with their onlinefriends, and therefore bridge the gap between the real world and online social networks.The purpose is that on the finalextraction of information, the results are worked for SocialRecommendation. However, the recommender systems presentsome failures in the filtering of the results and the way theyaresuggested to users.The method used here intendsto create an application thatperforms the Data Mining with textual information linked togeo-location data. The availability of large amounts of geographical and social data on LBSNsprovides an unprecedented opportunity to study human mobile behaviour throughdata analysis in a spatial-temporal-social context, enabling a variety of locationbasedservices, from mobile marketing to disaster relief.Data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information information that can be used to increase revenue, cuts costs, or both.
Mixed Reality: A Survey

This chapter presents an overview of the Mixed Reality (MR) paradigm, which proposes to overlay our real-world environment with digital, computer-generated objects. It presents example applications and outlines limitations and solutions for their technical implementation. In MR systems, users perceive both the physical environment around them and digital elements presented through, for example, the use of semitransparent displays. By its very nature, MR is a highly interdisciplinary field engaging signal processing, computer vision, computer graphics, user interfaces, human factors, wearable computing, mobile computing, information visualization, and the design of displays and sensors. This chapter presents potential MR applications, technical challenges in realizing MR systems, as well as issues related to usability and collaboration in MR. It separately presents a section offering a selection of MR projects which have either been partly or fully undertaken at Swiss universities and rounds off with a section on current challenges and trends.
Perimesencephalic subarachnoid hemorrhage. Additional perspectives from four cases.

Nonaneurysmal perimesencephalic hemorrhage, a distinct form of subarachnoid hemorrhage, is a recently described variant of intracranial hemorrhage. We describe two patients who presented with unusual features of this type of subarachnoid hemorrhage and also two patients who had a perimesencephalic pattern of hemorrhage due to a ruptured posterior circulation aneurysm.



The first patient, a 41-year-old woman with perimesencephalic hemorrhage, underwent an exploratory craniotomy because angiography had suggested an anomaly of the basilar tip. No source of hemorrhage could be identified at the time of surgery. The second patient was a 3-year-old boy who presented with opisthotonos and who was found to have a perimesencephalic hemorrhage. Angiography revealed no source for the hemorrhage. The third patient, a 54-year-old man, had a perimesencephalic pattern of subarachnoid hemorrhage from a vertebrobasilar junction aneurysm associated with a fenestration that was missed on the initial angiographic study. The fourth patient, a 43-year-old man, suffered a perimesencephalic pattern of subarachnoid hemorrhage from a small posterior cerebral artery aneurysm, which had not been recognized on two angiograms.



These patients elaborate on the clinical spectrum of subarachnoid hemorrhage with a perimesencephalic pattern. First, a negative exploratory craniotomy suggests that the source of nonaneurysmal perimesencephalic hemorrhage may not be arterial. Second, nonaneurysmal perimesencephalic hemorrhage may also occur in children. Finally, the index of suspicion for a posterior circulation aneurysm should remain high in patients who present with a perimesencephalic pattern of subarachnoid hemorrhage, and these aneurysms may rise from unusual locations.
Neck lift my way: an update.

The author updates prior descriptions of an approach to the surgical neck lift that aims for a maximum degree of control over the size, shape, and position of every anatomical feature of the neck that is negatively affecting its appearance.



A 38-year clinical experience guided the development of the operative tactics that define the strategy. Data collected from a records review of 522 consecutive neck lifts performed during the 10-year period 2004 through 2013 further inform the report. The approach has eight features: (1) nearly routine use of open submental access to all tissue layers of the central neck, including a regimen that curbed the problems that may attend an extensive tissue dissection; (2) management of lax neck skin by lateral excision using a specific postauricular incision, or by using the nonexcisional method of redistribution; (3) open lipectomy for precise removal of excess subcutaneous neck and jawline fat; (4) individualized modifications to subplatysmal fat, perihyoid fascia, and anterior digastric muscles; (5) treatment of large, ptotic, or malpositioned submandibular salivary glands by partial excision using a transcutaneous traction suture; (6) the current version of the corset platysmaplasty, which is used to treat static paramedian platysma muscle bands, and to avoid contour imperfections following subplatysmal maneuvers; (7) an approach that facilitates an isolated neck lift; and (8) durable results.



Case examples demonstrate outcomes.



Although the updated approach remains relatively complex and invasive, the author believes that the ends justify the means.
Detecting Online Harassment in Social Networks

Online Harassment is the process of sending messages for example in Social Networks to cause psychological harm to a victim. In this paper, we propose a pattern-based approach to detect such messages. Since user generated texts contain noisy language we perform a normalization step first to transform the words into their canonical forms. Additionally, we introduce a person identification module that marks phrases which relate to a person. Our results show that these preprocessing steps increase the classification performance. The pattern-based classifier uses the information provided by the preprocessing steps to detect patterns that connect a person to profane words. This technique achieves a substantial improvement compared to existing approaches. Finally, we discuss the portability of our approach to Social Networks and its possible contribution to tackle the abuse of such applications for the distribution of Online
Prosody contour prediction with long short-term memory, bi-directional, deep recurrent neural networks

Deep Neural Networks (DNNs) have been shown to provide state-of-the-art performance over other baseline models in the task of predicting prosodic targets from text in a speechsynthesis system. However, prosody prediction can be affected by an interaction of shortand long-term contextual factors that a static model that depends on a fixed-size context window can fail to properly capture. In this work, we look at a recurrent formulation of neural networks (RNNs) that are deep in time and can store state information from an arbitrarily large input history when making a prediction. We show that RNNs provide improved performance over DNNs of comparable size in terms of various objective metrics for a variety of prosodic streams (notably, a relative reduction of about 6% in F0 mean-square error accompanied by a relative increase of about 14% in F0 variance), as well as in terms of perceptual quality assessed through mean-opinion-score listening tests.
Minimum snap trajectory generation and control for quadrotors

We address the controller design and the trajectory generation for a quadrotor maneuvering in three dimensions in a tightly constrained setting typical of indoor environments. In such settings, it is necessary to allow for significant excursions of the attitude from the hover state and small angle approximations cannot be justified for the roll and pitch. We develop an algorithm that enables the real-time generation of optimal trajectories through a sequence of 3-D positions and yaw angles, while ensuring safe passage through specified corridors and satisfying constraints on velocities, accelerations and inputs. A nonlinear controller ensures the faithful tracking of these trajectories. Experimental results illustrate the application of the method to fast motion (5–10 body lengths/second) in three-dimensional slalom courses.
Semantic Framework for Comparison Structures in Natural Language

Comparison is one of the most important phenomena in language for expressing objective and subjective facts about various entities. Systems that can understand and reason over comparative structure can play a major role in the applications which require deeper understanding of language. In this paper we present a novel semantic framework for representing the meaning of comparative structures in natural language, which models comparisons as predicate-argument pairs interconnected with semantic roles. Our framework supports not only adjectival, but also adverbial, nominal, and verbal comparatives. With this paper, we provide a novel dataset of gold-standard comparison structures annotated according to our semantic framework.
Comparison of high resolution melting analysis, pyrosequencing, next generation sequencing and immunohistochemistry to conventional Sanger sequencing for the detection of p.V600E and non-p.V600E BRAF mutations

The approval of vemurafenib in the US 2011 and in Europe 2012 improved the therapy of not resectable or metastatic melanoma. Patients carrying a substitution of valine to glutamic acid at codon 600 (p.V600E) or a substitution of valine to leucine (p.V600K) in BRAF show complete or partial response. Therefore, the precise identification of the underlying somatic mutations is essential. Herein, we evaluate the sensitivity, specificity and feasibility of six different methods for the detection of BRAF mutations. Samples harboring p.V600E mutations as well as rare mutations in BRAF exon 15 were compared to wildtype samples. DNA was extracted from formalin-fixed paraffin-embedded tissues by manual micro-dissection and automated extraction. BRAF mutational analysis was carried out by high resolution melting (HRM) analysis, pyrosequencing, allele specific PCR, next generation sequencing (NGS) and immunohistochemistry (IHC). All mutations were independently reassessed by Sanger sequencing. Due to the limited tumor tissue available different numbers of samples were analyzed with each method (82, 72, 60, 72, 49 and 82 respectively). There was no difference in sensitivity between the HRM analysis and Sanger sequencing (98%). All mutations down to 6.6% allele frequency could be detected with 100% specificity. In contrast, pyrosequencing detected 100% of the mutations down to 5% allele frequency but exhibited only 90% specificity. The allele specific PCR failed to detect 16.3% of the mutations eligible for therapy with vemurafenib. NGS could analyze 100% of the cases with 100% specificity but exhibited 97.5% sensitivity. IHC showed once cross-reactivity with p.V600R but was a good amendment to HRM. Therefore, at present, a combination of HRM and IHC is recommended to increase sensitivity and specificity for routine diagnostic to fulfill the European requirements concerning vemurafenib therapy of melanoma patients.
Book Review

This eagerly awaited anthology, while surely not the last word on the Turing Test, equally surely deserves to become the principal source of information on the test. It includes not only Turing’s classic paper, but a fine selection of the main replies to date, all tied together by an engaging and penetrating essay by the editor. Stuart M. Shieber’s name is well known to computational linguists for his research and to computer scientists more generally for his debate on the Loebner Turing Test competition, which appeared a decade earlier in Communications of the ACM (Shieber 1994a, 1994b; Loebner 1994).1 With this collection, I expect it to become equally well known to philosophers. The collection begins with historical “precursors” to Turing’s paper: two pieces by Descartes—his Discourse on the Method, Chap. V (1637), and his “Letter to the Marquess of Newcastle”—followed by selections from La Mettrie’s Machine Man (1748). The second part contains the centerpiece: Turing’s 1950 paper from Mind, “Computing Machinery and Intelligence,” accompanied by three “ephemera”: two early (1951) and difficult-to-find articles by Turing—“Intelligent Machinery, a Heretical Theory” and “Can Digital Computers Think?”—and a transcript of a 1952 BBC radio interview with Turing, M. H. A. Newman, Sir Geoffrey Jefferson, and R. B. Braithwaite, “Can automatic Calculating Machines Be Said to Think?” Shieber’s presentation of the pièce de résistance (Turing 1950) devotes great attention to the sanctity of the text and is replete with scholarly paraphernalia comparing his carefully edited reprint with the original (which, by the way, is now available online, courtesy of JSTOR.org). The third, and final, part contains the immediate reactions to Turing’s Mind paper as they appeared in that journal, followed by now-classic responses and some more-recent, important papers, some arranged chronologically, others logically. The first published response was Leonard Pinsky’s early (1951)—and satirical—“Do Machines Think about Machines Thinking?” for which Shieber offers a brief, wry introduction. Next we have a quartet consisting of Keith Gunderson’s important “The Imitation Game” (1964), Richard Purtill’s response (“Beating the Imitation Game,” 1971), and Geoffrey Sampson’s (“In Defence of Turing”) and P. H. Millar’s (“On the Point of the Imitation Game”) 1973 replies to Purtill. Jumping ahead a couple of decades comes Robert M. French’s 1990 “Subcognition and the Limits of the Turing Test.” Next, in more of a logical than a chronological order, comes a trio consisting of John
Generalized Sampling and Infinite-Dimensional Compressed Sensing

We introduce and analyze a framework and corresponding method for compressed sensing in infinite dimensions. This extends the existing theory from finite-dimensional vector spaces to the case of separable Hilbert spaces. We explain why such a new theory is necessary by demonstrating that existing finitedimensional techniques are ill-suited for solving a number of key problems. This work stems from recent developments in generalized sampling theorems for classical (Nyquist rate) sampling that allows for reconstructions in arbitrary bases. A conclusion of this paper is that one can extend these ideas to allow for significant subsampling of sparse or compressible signals. Central to this work is the introduction of two novel concepts in sampling theory, the stable sampling rate and the balancing property, which specify how to appropriately discretize an infinite-dimensional problem.