nils-herrmann/clean_scirepeval huggingface dataset:
Acanthosis nigricans, tripe palms, and sign of Leser-Trélat in a patient with gastric adenocarcinoma: case report and literature review in China.

Some cutaneous alterations can be important clues for diagnosis of malignancy, and early recognition of cutaneous paraneoplasia signaling is of great value for preventing disease progression. Malignant acanthosis nigricans (MAN) is a well-known paraneoplastic dermatosis with symmetric eruption characterized by hyperpigmented, hyperkeratotic, velvety plaques that typically affect body folds and creases. Tripe palms (TP), also known as acanthosis palmaris, is a rare cutaneous paraneoplastic syndrome, providing a wrinkled and grooved appearance of the palms. The Leser-Tr elat (LT) sign is characterized by acute eruptive efflorescence of multiple seborrheic keratoses; the sudden appearance and rapid progression support it as a paraneoplastic dermatosis. MAN has been known to be associated with intraabdominal malignancies, most commonly gastric adenocarcinomas. However, dermatoses of MAN along with TP and LT sign rarely coexist in a single gastric adenocarcinomas patient. In this study, a 41-year-old female Chinese patient with MAN was reported. The peculiarity of this case is simultaneous skin manifestation consistent with MAN, TP, and LT sign; these cutaneous paraneoplasias harbor gastric adenocarcinomas stage IV with multiple metastases, but the patient was asymptomatic except for mild pruritis. The main interest in acanthosis nigricans (AN) has been based on its association with malignancy; recognizing MAN earlier may improve with treatment of underlying malignancy. Although there were many cases about MAN reports in China, there was no systemic analysis about underlying malignancy of MAN. In this study, the cases of MAN in China published over 15 years were reviewed and analyzed; to the best of our knowledge this was the first article about systemic analysis of MAN in China.
Broadband characterization of SMA connectors by measurements

This paper presents the characterization of various types of SubMiniature version A (SMA) connectors. The characterization is performed by measurements in frequency and time domain. The SMA connectors are mounted on microstrip (MS) and conductor-backed coplanar waveguide (CPW-CB) manufactured on high-frequency (HF) laminates. The designed characteristic impedance of the transmission lines is 50 Ω and deviation from the designed characteristic impedance is measured. The measurement results suggest that for a given combination of the transmission line and SMA connector, the discontinuity in terms of characteristic impedance can be significantly improved by choosing the right connector type.
Weakly Supervised Multimodal Kernel for Categorizing Aerial Photographs

Accurately distinguishing aerial photographs from different categories is a promising technique in computer vision. It can facilitate a series of applications, such as video surveillance and vehicle navigation. In this paper, a new image kernel is proposed for effectively recognizing aerial photographs. The key is to encode high-level semantic cues into local image patches in a weakly supervised way, and integrate multimodal visual features using a newly developed hashing algorithm. The flowchart can be elaborated as follows. Given an aerial photo, we first extract a number of graphlets to describe its topological structure. For each graphlet, we utilize color and texture to capture its appearance, and a weakly supervised algorithm to capture its semantics. Thereafter, aerial photo categorization can be naturally formulated as graphlet-to-graphlet matching. As the number of graphlets from each aerial photo is huge, to accelerate matching, we present a hashing algorithm to seamlessly fuze the multiple visual features into binary codes. Finally, an image kernel is calculated by fast matching the binary codes corresponding to each graphlet. And a multi-class SVM is learned for aerial photo categorization. We demonstrate the advantage of our proposed model by comparing it with state-of-the-art image descriptors. Moreover, an in-depth study of the descriptiveness of the hash-based graphlet is presented.
Open Relation Extraction for Support Passage Retrieval: Merit and Open Issues

Our goal is to complement an entity ranking with human-readable explanations of how those retrieved entities are connected to the information need. Relation extraction technology should aid in finding such support passages, especially in combination with entities and query terms. This work explores how the current state of the art in unsupervised relation extraction (OpenIE) contributes to a solution for the task, assessing potential, limitations, and avenues for further investigation.
Reducing I.T. Project Management Failures: Early Empirical Results

Failures rates of Information Technology (I.T.) projects remain high, even after decades of efforts to reduce them. Most efforts to improve project success have focused on variations within the traditional project management paradigm, such as advanced by the Project Management Body Of Knowledge (PMBOK). This paper reports on early empirical results into project (management) success or failure factors stemming from the traditional paradigm as well as from Value-Driven Change Leadership (VDCL). The early results points to several success factors stemming from the traditional project management paradigm as well as from VDCL.
A Fast Analytic Simulation of Stochastic Mutation and its Application to Modeling Cancer Drug Resistance

Random mutation is pervasive in nature and has been mathematically modeled extensively. It is a primary mechanism by which cancer and pathogens resist drugs and other systemic treatments. For example, most cancers are still incurable primarily because they develop resistance to anti-cancer drugs. This resistance arises via a variety of mechanisms [1-4], and mathematical modeling over the past four decades has improved our understanding of it [517]. It is now recognized that tumors are heterogeneous, resulting from random mutation of cancer-cell DNA, both before and after treatment begins, and this is an important, if not the primary, source of resistance-generating mutations in cancer [18-25]. Some mathematical models of resistance have relied on this assumption using an analytic deterministic approach and have led to elegant insights [5,9,10] when applied to limited, simple cases. Others have employed more complex mathematical stochastic machinery to produce analytical solutions to their equations [8,11-16] leading to general treatment suggestions, but these have generally addressed somewhat idealized situations and required significant computation, limiting their usefulness in the clinical setting.
Engineering self-awareness with knowledge management in dynamic systems: a case for volunteer computing

The complexity of the modern dynamic computing systems has motivated software engineering researchers to explore new sources of inspiration for equipping such systems with autonomic behaviours. Self-awareness has recently gained considerable attention as a prominent property for enriching the self-adaptation capabilities in systems operating in dynamic, heterogeneous and open environments. This thesis investigates the role of knowledge and its dynamic management in realising various levels of self-awareness for enabling self-adaptivity with different capabilities and strengths. The thesis develops a novel multi-level dynamic knowledge management approach for managing and representing the evolving knowledge. The approach is able to acquire ‘richer’ knowledge about the system’s internal state and its environment in addition to managing the trade-offs arising from the adaptation conflicting goals. The thesis draws on a case from the volunteer computing, as an environment characterised by openness, heterogeneity, dynamism, and unpredictability to develop and evaluate the approach. This thesis takes an experimental approach to evaluate the effectiveness of the of the dynamic knowledge management approach. The results show the added value of the approach to the self-adaptivity of the system compared to classic self-adaptation capabilities. To my parents, wife, sons, brothers, sisters, parents-in-law with loyalty and love...
Incorporating depth into both CNN and CRF for indoor semantic segmentation

To improve segmentation performance, a novel neural network architecture (termed DFCN-DCRF) is proposed, which combines an RGB-D fully convolutional neural network (DFCN) with a depth-sensitive fully-connected conditional random field (DCRF). First, a DFCN architecture which fuses depth information into the early layers and applies dilated convolution for later contextual reasoning is designed. Then, a depth-sensitive fully-connected conditional random field (DCRF) is proposed and combined with the previous DFCN to refine the preliminary result. Comparative experiments show that the proposed DFCN-DCRF achieves competitive performance compared with state-of-the-art methods.
Better region proposals for pedestrian detection with R-CNN

Region-based convolutional neural networks (R-CNNs) have achieved great success in object detection recently. These deep models depend on region proposal algorithms to hypothesize object locations. In this paper, we combine a special region proposal algorithm with R-CNN, and apply it to pedestrian detection. The special algorithm is used to generate region proposals only for pedestrian class. It is different from the popular region proposal algorithm selective search that detects generic object locations. The experimental results prove that region proposals generated by our method are more applicable than selective search for pedestrian detection. Our method performs faster training and testing than the deep model based on, and it achieves competitive performance compared to the state-of-the-arts in pedestrian detection.
All Dungeons and Dragons Spells 3.5

Spell Description Schl Comp Time Range Target, Effect, Area Duration Save SR PHB £ Acid Fog Fog deals 2d6/rnd acid damage Conj V,S,M/DF 1 a Medium 20-ft radius 1 rnd/lvl-196 £ Acid Splash Acid Missile 1d3 damage Conj V,S 1 a Close Acid missile Instantaneous-196 £ Aid +1 att,+1 fear saves,1d8 +1/lvl hps Ench V,S,DF 1 a Touch One living creature 1 min/lvl-Yes 196 £ Air Walk Target treads on air as if solid Trans V,S,DF 1 a Touch One creature 10 min/lvl-Yes 196 £ Alarm Wards an area for 2 hr/lvl Abjur V,S,F/DF 1 a Close 20-ft radius 2 hr/lvl (D)-197 £ Align Weapon Adds alignment to weapon Trans V,S,DF 1 a Touch Weapon 1 min/lvl Will negs Yes 197 £ Alter Self Changes appearance Trans V,S 1 a Self Caster, +10 disguise 10 min/lvl (D)-197 £ Analyze Dweomer Reveals magical aspects of target Div V,S,F 1 a Close Item or creature/lvl 1 rnd/lvl (D) Will negs-197 £ Animal Growth Animal/2 lvls increases size category Trans V,S 1 a Medium 1 animal/2 lvls 1 min/lvl Fort negs Yes 198 £ Animal Messenger Send a tiny animal to specific place Ench V,S,M 1 a Close One tiny animal 1 day/lvl-Yes 198 £ Animal Shapes 1 ally/lvl polymorphs into animal Trans V,S,DF 1 a Close One creature/lvl 1 hr/lvl (D)-Yes 198 £ Animal Trance Fascinates 2d6 HD of animals Ench V,S 1 a Close Animals, Int 1 or 2 Conc Will negs Yes 198 £ Animate Dead Creates skeletons and zombies Necro V,S,M 1 a Touch Max 2HD/lvl Instantaneous-198 £ Animate Objects Items attack your foes Trans V,S 1 a Medium One small item/lvl 1 rnd/lvl-199 £ Animate Plants Animated plant Trans V 1 a Close 1 plant/3lvls 1 rnd/lvl-199 £ Animate Rope Rope moves at your command Trans V,S 1 a Medium 1 ropelike item 1 rnd/lvl-199 £ Antilife Shell 10-ft field excludes living creatures Abjur V,S,DF Round 10-ft 10-ft radius 10 min/lvl (D)-Yes 199 £ Antimagic Field Negates magic within 10-ft Abjur V,S,M/DF 1 a 10-ft 10-ft radius 10 min/lvl (D)-Sp 200 £ Antipathy Item or location repels creatures Ench V,S,M/DF 1 hr Close Location or item 2 hr/lvl (D) Will part Yes 200 £ Antiplant Shell Barrier protects against plants Abjur V,S,DF 1 a 10-ft 10-ft radius 10 min/lvl (D)-Yes 200 £ Arcane Eye Floating eye, moves 30ft/rnd Div V,S,M 10 min Unlimited Magical sensor 1 min/lvl (D)-200 …
Internet of things security

The consequences of security problems are increasingly serious. These problems can now lead to personal injury, prolonged downtime and irreparable damage to capital goods. To achieve this, systems require end-to-end security solutions that cover the layers of connectivity, furthermore, guarantee the privatization and protection of data circulated via networks. In this paper, we will give a definition to the Internet of things, try to dissect its architecture (protocols, layers, entities …), thus giving a state of the art of security in the field of internet of things (Faults detected in each layer …), finally, mention the solutions proposed until now to help researchers start their researches on internet of things security subject.
Frontmatter More information Ship Resistance and Propulsion PRACTICAL ESTIMATION OF SHIP PROPULSIVE POWER

Ship Resistance and Propulsion is dedicated to providing a comprehensive and modern scientific approach to evaluating ship resistance and propulsion. The study of propulsive power enables the size and mass of the propulsion engines to be established and estimates made of the fuel consumption and likely operating costs. This book, written by experts in the field, includes the latest developments from applied research, including those in experimental and CFD techniques, and provides guidance for the practical estimation of ship propulsive power for a range of ship types. This text includes sufficient published standard series data for hull resistance and propeller performance to enable practitioners to make ship power predictions based on material and data contained within the book. A large number of fully worked examples are included to illustrate applications of the data and powering methodologies; these include cargo and container ships, tankers and bulk carriers, ferries, warships, patrol craft, work boats, planing craft and yachts. The book is aimed at a broad readership including practising naval architects and marine engineers, sea-going officers, small craft designers and undergraduate and postgraduate degree students. It should also appeal to others involved in transportation, transport efficiency and eco-logistics, who need to carry out reliable estimates of ship power requirements.
A survey of mobile and wireless technologies for augmented reality systems

Recent advances in hardware and software for mobile computing have enabled a new breed of mobile AR systems and applications. A new breed of computing called “augmented ubiquitous computing” has resulted from the convergence of wearable computing, wireless networking and mobile AR interfaces. In this paper we provide a survey of different mobile and wireless technologies and how they have impact AR. Our goal is to place them into different categories so that it becomes easier to understand the state of art and to help identify new directions of research.
A General Evaluation Framework for Text Based Conversational Agent

This paper details the development of a new evaluation framework for a text based Conversational Agent (CA). A CA is an intelligent system that handle spoken or/and text based conversations between machine and human. Generally, the lack of evaluation frameworks for CAs effects its development. The idea behind any system’s evaluation is to make sure about the system’s functionalities and to continue development on it. A specific CA has been chosen to test the proposed framework on it; namely ArabChat. The ArabChat is a rule based CA and uses pattern matching technique to handle user’s Arabic text based conversations. The proposed and developed evaluation framework in this paper is natural language independent. The proposed framework is based on the exchange of specific information between ArabChat and user called “Information Requirements”. This information are tagged for each rule in the applied domain and should be exist in a user’s utterance (conversation). A real experiment has been done in Applied Science University in Jordan as an information point advisor for their native Arabic students to evaluate the ArabChat and then evaluating the proposed evaluation framework. Artificial intelligence; Conversational Agent and evaluation
Supplier evaluation using hybrid multiple criteria decision making approach

In the face of acute global competition, supplier management is rapidly emerging as a crucial issue to any companies striving for business success and sustainable development. To optimise competitive advantages, a company should incorporate ‘suppliers’ as an essential part of its core competencies. Supplier evaluation, the first step in supplier management, is a complex multiple criteria decision making (MCDM) problem, and its complexity is further aggravated if the highly important interdependence among the selection criteria is taken into consideration. The objective of this paper is to suggest a comprehensive decision method for identifying top suppliers by considering the effects of interdependence among the selection criteria. Proposed in this study is a hybrid model, which incorporates the technique of analytic network process (ANP) in which criteria weights are determined using fuzzy extent analysis, Technique for order performance by similarity to ideal solution (TOPSIS) under fuzzy environment is adopted to rank competing suppliers in terms of their overall performances. An example is solved to illustrate the effectiveness and feasibility of the suggested model.
Classification of design parameters for E-commerce websites: A novel fuzzy Kano approach

Websites have gained vital importance for organizations along with the growing competition in the world market. It is known that usability requirements heavily depend on the type, audience and purpose of websites. For the e-commerce environment, usability assessment of a website is required to figure out the impact of website design on customer purchases. Thus, usability assessment and design of online pages have become the subject of many scientific studies. However, in any of these studies, design parameters were not identified in such a detailed way, and they were not classified in line with customer expectations to assess the overall usability of an e-commerce website. This study therefore aims to analyze and classify design parameters according to customer expectations in order to evaluate the usability of e-commerce websites in a more comprehensive manner. Four websites are assessed using the proposed novel approach with respect to the identified design parameters and the usability scores of the websites are examined. It is revealed that the websites with high usability score are more preferred by customers. Therefore, it is indicated that usability of e-commerce websites affects customer purchases.
Real-Time Three-Dimensional Cell Segmentation in Large-Scale Microscopy Data of Developing Embryos.

We present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image analysis framework for automated three-dimensional cell segmentation in large-scale images. RACE is 55-330 times faster and 2-5 times more accurate than state-of-the-art methods. We demonstrate the generality of RACE by extracting cell-shape information from entire Drosophila, zebrafish, and mouse embryos imaged with confocal and light-sheet microscopes. Using RACE, we automatically reconstructed cellular-resolution tissue anisotropy maps across developing Drosophila embryos and quantified differences in cell-shape dynamics in wild-type and mutant embryos. We furthermore integrated RACE with our framework for automated cell lineaging and performed joint segmentation and cell tracking in entire Drosophila embryos. RACE processed these terabyte-sized datasets on a single computer within 1.4 days. RACE is easy to use, as it requires adjustment of only three parameters, takes full advantage of state-of-the-art multi-core processors and graphics cards, and is available as open-source software for Windows, Linux, and Mac OS.
GRfid: A Device-Free RFID-Based Gesture Recognition System

Gesture recognition has emerged recently as a promising application in our daily lives. Owing to low cost, prevalent availability, and structural simplicity, RFID shall become a popular technology for gesture recognition. However, the performance of existing RFID-based gesture recognition systems is constrained by unfavorable intrusiveness to users, requiring users to attach tags on their bodies. To overcome this, we propose GRfid, a novel device-free gesture recognition system based on phase information output by COTS RFID devices. Our work stems from the key insight that the RFID phase information is capable of capturing the spatial features of various gestures with low-cost commodity hardware. In GRfid, after data are collected by hardware, we process the data by a sequence of functional blocks, namely data preprocessing, gesture detection, profiles training, and gesture recognition, all of which are well-designed to achieve high performance in gesture recognition. We have implemented GRfid with a commercial RFID reader and multiple tags, and conducted extensive experiments in different scenarios to evaluate its performance. The results demonstrate that GRfid can achieve an average recognition accuracy of <inline-formula> <tex-math notation="LaTeX">$96.5$</tex-math><alternatives><inline-graphic xlink:href="wu-ieq1-2549518.gif"/> </alternatives></inline-formula> and <inline-formula><tex-math notation="LaTeX">$92.8$</tex-math><alternatives> <inline-graphic xlink:href="wu-ieq2-2549518.gif"/></alternatives></inline-formula> percent in the identical-position and diverse-positions scenario, respectively. Moreover, experiment results show that GRfid is robust against environmental interference and tag orientations.
A Comprehensive Look at Distance Education in the K – 12 Context

This review provides a comprehensive examination of the literature surrounding the current state of K–12 distance education. The growth in K–12 distance education follows in the footsteps of expanded learning opportunities at all levels of public education and training in corporate environments. Implementation has been accomplished with a limited research base, often drawing from studies in adult distance education and policies adapted from traditional learning environments. This review of literature provides an overview of the field of distance education with a focus on the research conducted in K–12 distance education environments.
Implications of Short Term Memory Research for the Design of Spaced Repetition Based Mobile Learning Games

Spaced repetition learning is an approach for choosing the most efficient intervals between rehearsing learning content. Typically used for tasks like learning vocabulary it also offers great potential for content selection in learning games. Learning games do, however differ from classic spaced repetition learning approaches in that content is not only accessed when indicated by a spaced repetition scheduling algorithm but also when the users simply want to play the game or when they decide to play the game multiple times in a row. In these cases, short term memory effects might mask learning effects in user performance, leading to faulty inputs to the calculation of spaced repetition interval lengths. This paper reviews current research literature on the interaction of short term and long term memory in order to determine how short term memory effects can be coped with in the context of spaced repetition based learning games.