nils-herrmann/clean_scirepeval huggingface dataset:
All-SiC 9.5 kW/dm3 On-Board Power Electronics for 50 kW/85 kHz Automotive IPT System

Inductive power transfer (IPT) is widely discussed for the automated opportunity charging of plug-in hybrid and electric public transport buses without moving mechanical components and reduced maintenance requirements. In this paper, the design of an on-board active rectifier and dc–dc converter for interfacing the receiver coil of a 50 kW/85 kHz IPT system is designed. Both conversion stages employ 1.2 kV SiC MOSFET devices for their low switching losses. For the dc–dc conversion, a modular, nonisolated buck+boost-type topology with coupled magnetic devices is used for increasing the power density. For the presented hardware prototype, a power density of 9.5 kW/dm3 (or 156 W/in3) is achieved, while the ac–dc efficiency from the IPT receiver coil to the vehicle battery is 98.6%. Comprehensive experimental results are presented throughout this paper to support the theoretical analysis.
ZINC: A Free Tool to Discover
Chemistry for Biology

ZINC is a free public resource for ligand discovery. The database contains over twenty million commercially available molecules in biologically relevant representations that may be downloaded in popular ready-to-dock formats and subsets. The Web site also enables searches by structure, biological activity, physical property, vendor, catalog number, name, and CAS number. Small custom subsets may be created, edited, shared, docked, downloaded, and conveyed to a vendor for purchase. The database is maintained and curated for a high purchasing success rate and is freely available at zinc.docking.org.
A fully homomorphic encryption scheme with better key size

Fully homomorphic encryption is faced with two problems now. One is candidate fully homomorphic encryption schemes are few. Another is that the efficiency of fully homomorphic encryption is a big question. In this paper, we propose a fully homomorphic encryption scheme based on LWE, which has better key size. Our main contributions are: (1) According to the binary-LWE recently, we choose secret key from binary set and modify the basic encryption scheme proposed in Linder and Peikert in 2010. We propose a fully homomorphic encryption scheme based on the new basic encryption scheme. We analyze the correctness and give the proof of the security of our scheme. The public key, evaluation keys and tensored ciphertext have better size in our scheme. (2) Estimating parameters for fully homomorphic encryption scheme is an important work. We estimate the concert parameters for our scheme. We compare these parameters between our scheme and Bra12 scheme. Our scheme have public key and private key that smaller by a factor of about logq than in Bra12 scheme. Tensored ciphertext in our scheme is smaller by a factor of about log2q than in Bra12 scheme. Key switching matrix in our scheme is smaller by a factor of about log3q than in Bra12 scheme.
Supply chain management : theory , practice and future challenges

The purpose of this paper is to critically assess current developments in the theory and practice of supply management and through such an assessment to identify barriers, possibilities and key trends.  The paper is based on a three-year detailed study of six supply chains which encompassed 72 companies in Europe. The focal firms in each instance were sophisticated, blue-chip corporations operating on an international scale. Managers across at least four echelons of the supply chain were interviewed and the supply chains were traced and observed.  The paper reveals that supply management is, at best, still emergent in terms of both theory and practice. Few practitioners were able – or even seriously aspired – to extend their reach across the supply chain in the manner prescribed in much modern theory. The paper identifies the range of key barriers and enablers to supply management and it concludes with an assessment of the main trends.  The research presents a number of challenges to existing thinking about supply strategy and supply chain management. It reveals the substantial gaps between theory and practice. A number of trends are identified which it is argued may work in favour of better prospects for SCM in the future and for the future of supply management as a discipline.  A central challenge concerns who could or should manage the supply chain. Barriers to effective supply management are identified and some practical steps to surmount them are suggested.  The paper is original in the way in which it draws on an extensive systematic study to critically assess current theory and current developments. The paper points the way for theorists and practitioners to meet future challenges.
A Simple and Faster Branch-and-Bound Algorithm for Finding a Maximum Clique with Computational Experiments

This paper proposes new approximate coloring and other related techniques which markedly improve the run time of the branchand-bound algorithm MCR ( 2007), previously shown to be the fastest maximum-clique-finding algorithm for a large number of graphs. The algorithm obtained by introducing these new techniques in MCR is named MCS. It is shown that MCS is successful in reducing the search space quite efficiently with low overhead. Consequently, it is shown by extensive computational experiments that MCS is remarkably faster than MCR and other existing algorithms. It is faster than the other algorithms by an order of magnitude for several graphs. In particular, it is faster than MCR for difficult graphs of very high density and for very large and sparse graphs, even though MCS is not designed for any particular type of graphs. MCS can be faster than MCR by a factor of more than 100,000 for some extremely dense random graphs.
Attentive Recurrent Social Recommendation

Collaborative filtering(CF) is one of the most popular techniques for building recommender systems. To alleviate the data sparsity issue in CF, social recommendation has emerged by leveraging social influence among users for better recommendation performance. In these systems, users' preferences over time are determined by their temporal dynamic interests as well as the general static interests. In the meantime, the complex interplay between users' internal interests and the social influence from the social network drives the evolution of users' preferences over time. Nevertheless, traditional approaches either neglected the social network structure for temporal recommendation or assumed a static social influence strength for static social recommendation. Thus, the problem of how to leverage social influence to enhance temporal social recommendation performance remains pretty much open. To this end, in this paper, we present an attentive recurrent network based approach for temporal social recommendation. In the proposed approach, we model users' complex dynamic and general static preferences over time by fusing social influence among users with two attention networks. Specifically, in the dynamic preference modeling process, we design a dynamic social aware recurrent neural network to capture users' complex latent interests over time, where a temporal attention network is proposed to learn the temporal social influence over time. In the general static preference modeling process, we characterize each user's static interest by introducing a static social attention network to model the stationary social influence among users. The output of the dynamic preferences and the static preferences are combined together in a unified end-to-end framework for the temporal social recommendation task. Finally, experimental results on two real-world datasets clearly show the superiority of our proposed model compared to the baselines.
Virtual Babyz : Believable Agents with Narrative Intelligence

This paper describes the interactive narrative experiences in Babyz, an interactive entertainment product for the PC currently in development at PF Magic / Mindscape in San Francisco, to be released in October 1999. Babyz are believable agents designed and implemented in the tradition of Dogz and Catz, Your Virtual Petz. As virtual human characters, Babyz are more intelligent, expressive and communicative than their Petz predecessors, allowing for both broader and deeper narrative possibilities. Babyz are designed with behaviors to support entertaining short-term narrative experiences, as well as long-term emotional relationships and narratives.
Efficient integrity checking of untrusted network storage

Outsourced storage has become more and more practical in recent years. Users can now store large amounts of data in multiple servers at a relatively low price. An important issue for outsourced storage systems is to design an efficient scheme to assure users that their data stored at remote servers has not been tampered with. This paper presents a general method and a practical prototype application for verifying the integrity of files in an untrusted network storage service. The verification process is managed by an application running in a trusted environment (typically on the client) that stores just one cryptographic hash value of constant size, corresponding to the "digest" of an authenticated data structure. The proposed integrity verification service can work with any storage service since it is transparent to the storage technology used. Experimental results show that our integrity verification method is efficient and practical for network storage systems.
Smart Car Parking Management System Using IoT

Proliferation in the number of vehicles is leading to problems of vehicles parking at an appropriate place especially the car parking. This indirectly leads to traffic congestion. This is because of the fact that current transportation infrastructure and car park facility are unable to cope with the arrival of large number of vehicles on the road. To alleviate the aforementioned problem, authors proposed a Smart Parking Management System that helps users to automatically find a free parking space with a smaller amount. Smart Parking involves use of Ultrasonic sensor, Arduino Uno, ESP8266-01 Wi-Fi Module, Cloud server. IOT based new parking platform enable to connect, analyze and automate data gathered from devices and execute smart parking possible. Smart parking would enable vehicle occupancy, monitoring and managing of available parking space in real-time that reducing the environmental pollution. Proposed system provides optimize usage of parking space and get considerable revenue generation.
Using LLL-Reduction for Solving RSA and Factorization Problems

25 years ago, Lenstra, Lenstra and Lovász presented their c el brated LLL lattice reduction algorithm. Among the various applicatio ns of the LLL algorithm is a method due to Coppersmith for finding small roots of polyn mial equations. We give a survey of the applications of this root finding metho d t the problem of inverting the RSA function and the factorization problem. A s we will see, most of the results are of a dual nature, they can either be interpret ed as cryptanalytic results or as hardness/security results.
Behavior Matching in Multimodal Communication Is Synchronized

A variety of theoretical frameworks predict the resemblance of behaviors between two people engaged in communication, in the form of coordination, mimicry, or alignment. However, little is known about the time course of the behavior matching, even though there is evidence that dyads synchronize oscillatory motions (e.g., postural sway). This study examined the temporal structure of nonoscillatory actions-language, facial, and gestural behaviors-produced during a route communication task. The focus was the temporal relationship between matching behaviors in the interlocutors (e.g., facial behavior in one interlocutor vs. the same facial behavior in the other interlocutor). Cross-recurrence analysis revealed that within each category tested (language, facial, gestural), interlocutors synchronized matching behaviors, at temporal lags short enough to provide imitation of one interlocutor by the other, from one conversational turn to the next. Both social and cognitive variables predicted the degree of temporal organization. These findings suggest that the temporal structure of matching behaviors provides low-level and low-cost resources for human interaction.
Fault Detection and Isolation in Low-Voltage DC-Bus Microgrid System

A fault detection and isolation scheme for low-voltage dc-bus microgrid systems is presented in this paper. Unlike traditional ac distribution systems, protection has been challenging for dc systems. The goals of the proposed scheme are to detect the fault in the bus between devices and to isolate the faulted section so that the system keeps operating without disabling the entire system. To achieve these goals, a loop-type dc-bus-based microgrid system, which has a segment controller between connected components, is proposed. The segment controller consists of master and slave controllers that monitor currents and control the segment separation, which include solid-state bidirectional switches and snubber circuits. The proposed system can detect faults on the bus regardless of fault current amplitude or the power supply's feeding capacity. The proposed concepts have been verified by OrCAD/PSpice simulations and experiments on hardware test bed.
The Continuous Interaction Space: Interaction Techniques Unifying Touch and Gesture on and above a Digital Surface

The rising popularity of digital table surfaces has spawned considerable interest in new interaction techniques. Most interactions fall into one of two modalities: 1) direct touch and multi-touch (by hand and by tangibles) directly on the surface, and 2) hand gestures above the surface. The limitation is that these two modalities ignore the rich interaction space between them. To move beyond this limitation, we first contribute a unification of these discrete interaction modalities called the continuous interaction space. The idea is that many interaction techniques can be developed that go beyond these two modalities, where they can leverage the space between them. That is, we believe that the underlying system should treat the space on and above the surface as a continuum, where a person can use touch, gestures, and tangibles anywhere in the space and naturally move between them. Our second contribution illustrates this, where we introduce a variety of interaction categories that exploit the space between these modalities. For example, with our Extended Continuous Gestures category, a person can start an interaction with a direct touch and drag, then naturally lift off the surface and continue their drag with a hand gesture over the surface. For each interaction category, we implement an example (or use prior work) that illustrates how that technique can be applied. In summary, our primary contribution is to broaden the design space of interaction techniques for digital surfaces, where we populate the continuous interaction space both with concepts and examples that emerge from considering this space as a continuum.
Congenitally Missing Lateral Incisor with Orthodontics, Bone Grafting and Single-Tooth Implant: A Case Report

Congenitally missing teeth are frequently presented to the dentist. Interdisciplinary approach may be needed for the proper treatment plan. The available treatment modalities to replace congenitally missing teeth include prosthodontic fixed and removable prostheses, resin bonded retainers, orthodontic movement of maxillary canine to the lateral incisor site and single tooth implants. Dental implants offer a promising treatment option for placement of congenitally missing teeth. Interdisciplinary approach may be needed in these cases. This article aims to present a case report of replacement of unilaterally congenitally missing maxillary lateral incisors with dental implants.
Extended subdivision surfaces: Building a bridge between NURBS and Catmull-Clark surfaces

An extended subdivision surface (ESub) is a generalization of Catmull Clark and NURBS surfaces. Depending on the knot intervals and valences of the vertices and faces, Catmull Clark as well as NURBS patches can be generated using the extended subdivision rules. Moreover, an arbitrary choice of the knot intervals and the topology is possible. Special features like sharp edges and corners are consistently supported by setting selected knot intervals to zero or by applying special rules. Compared to the prior nonuniform rational subdivision surfaces (NURSS), the ESubs offer limit-point rules which are indispensable in many applications, for example, for computer-aided design or in adaptive visualization. The refinement and limit-point rules for our nonuniform, nonstationary scheme are obtained via a new method using local Bézier control points. With our new surface, it is possible to start with existing Catmull Clark as well as NURBS models and to continue the modeling process using the extended subdivision options.
Detecting stress and depression in adults with aphasia through speech analysis

Aphasia is an acquired communication disorder often resulting from stroke that can impact quality of life and may lead to high levels of stress and depression. Depression diagnosis in this population is often completed through subjective caregiver questionnaires. Stress diagnostic tests have not been modified for language difficulties. This work proposes to use speech analysis as an objective measure of stress and depression in patients with aphasia. Preliminary analysis used linear support vector regression models to predict depression scores and stress scores for a total of 19 and 18 participants respectively. Teager Energy Operator-Amplitude Modulation features performed the best in predicting the Perceived Stress Scale score based on various measures. The complications of speech in people with aphasia are examined and indicate the need for future work on this understudied population.
CBC: An associative classifier with a small number of rules

Associative classifiers have been proposed to achieve an accurate model with each individual rule being interpretable. However, existing associative classifiers often consist of a large number of rules and, thus, can be difficult to interpret. We show that associative classifiers consisting of an ordered rule set can be represented as a tree model. From this view, it is clear that these classifiers are restricted in that at least one child node of a non-leaf node is never split. We propose a new tree model, i.e., condition-based tree (CBT), to relax the restriction. Furthermore, we also propose an algorithm to transform a CBT to an ordered rule set with concise rule conditions. This ordered rule set is referred to as a condition-based classifier (CBC). Thus, the interpretability of an associative classifier is maintained, but more expressive models are possible. The rule transformation algorithm can be also applied to regular binary decision trees to extract an ordered set of rules with simple This research was partially supported by ONR grant N00014-09-1-0656. Email addresses: hdeng3@asu.com (Houtao Deng), george.runger@asu.edu (George Runger), eugene.tuv@intel.com (Eugene Tuv), wade.bannister@ingenixconsulting.com (Wade Bannister)  2013 rule conditions. Feature selection is applied to a binary representation of conditions to simplify/improve the models further. Experimental studies show that CBC has competitive accuracy performance, and has a significantly smaller number of rules (median of 10 rules per data set) than well-known associative classifiers such as CBA (median of 47) and GARC (median of 21). CBC with feature selection has even a smaller number of rules.
Automatic paraphrase acquisition from news articles

Paraphrases play an important role in the variety and complexity of natural language documents. However they adds to the difficulty of natural language processing. Here we describe a procedure for obtaining paraphrases from news article. A set of paraphrases can be useful for various kinds of applications. Articles derived from different newspapers can contain paraphrases if they report the same event of the same day. We exploit this feature by using Named Entity recognition. Our basic approach is based on the assumption that Named Entities are preserved across paraphrases. We applied our method to articles of two domains and obtained notable examples. Although this is our initial attempt to automatically extracting paraphrases from a corpus, the results are promising.
Control-flow integrity principles, implementations, and applications

Current software attacks often build on exploits that subvert machine-code execution. The enforcement of a basic safety property, control-flow integrity (CFI), can prevent such attacks from arbitrarily controlling program behavior. CFI enforcement is simple and its guarantees can be established formally, even with respect to powerful adversaries. Moreover, CFI enforcement is practical: It is compatible with existing software and can be done efficiently using software rewriting in commodity systems. Finally, CFI provides a useful foundation for enforcing further security policies, as we demonstrate with efficient software implementations of a protected shadow call stack and of access control for memory regions.
SEPP-ZVS high frequency inverter for induction heating using newly developed SiC-SIT

SiC-SIT power semiconductor switching devices has an advantage that its switching time is high speed compared to those of other power semiconductor switching devices. We adopt newly developed SiC-SITs which have the maximum ratings 800V/4A and prepare a breadboard of a conventional single-ended push-pull(SEPP) high frequency inverter. This paper describes the characteristics of SiC-SIT on the basis of the experimental results of the breadboard. Its operational frequencies are varied at from 100 kHz to 250kHz with PWM control technique for output power regulation. Its load is induction fluid heating systems for super-heated-steam production.
Wisteria: Nurturing Scalable Data Cleaning Infrastructure

Analysts report spending upwards of 80% of their time on problems in data cleaning. The data cleaning process is inherently iterative, with evolving cleaning workflows that start with basic exploratory data analysis on small samples of dirty data, then refine analysis with more sophisticated/expensive cleaning operators (i.e., crowdsourcing), and finally apply the insights to a full dataset. While an analyst often knows at a logical level what operations need to be done, they often have to manage a large search space of physical operators and parameters. We present Wisteria, a system designed to support the iterative development and optimization of data cleaning workflows, especially ones that utilize the crowd. Wisteria separates logical operations from physical implementations, and driven by analyst feedback, suggests optimizations and/or replacements to the analyst’s choice of physical implementation. We highlight research challenges in sampling, in-flight operator replacement, and crowdsourcing. We overview the system architecture and these techniques, then propose a demonstration designed to showcase how Wisteria can improve iterative data analysis and cleaning. The code is available at: http://www.sampleclean.org.
A Comparative Study of Classification Techniques in Data Mining Algorithms

Classification is used to find out in which group each data instance is related within a given dataset. It is used for classifying data into different classes according to some constrains. Several major kinds of classification algorithms including C4.5, ID3, k-nearest neighbor classifier, Naive Bayes, SVM, and ANN are used for classification. Generally a classification technique follows three approaches Statistical, Machine Learning and Neural Network for classification. While considering these approaches this paper provides an inclusive survey of different classification algorithms and their features and limitations. key words: C4.5, ID3, ANN, Naive Bayes, SVM, k-nearest neighbour.