nils-herrmann/clean_scirepeval huggingface dataset:
USB PassOn: Secure USB Thumb Drive Forensic Toolkit

The flash memory market has grown at an extremely fast rate, when compared with all other types of semiconductors. Much of this can be owed to the rabid use of flash memory in portable media players like Apple iPod, but also to the growth of the cellular phone market, where over 1.2 billion handsets are expected to be sold worldwide this year alone, as well as other electronic devices.[8] Lately, corporation insiders steal confidential information using small USB thumb drive. Therefore USB thumb drives are becoming very important evidence that must be seized in digital crime investigation. In addition, because there are many kinds of USB thumb drives, we need some techniques which can identify specific drive. In this paper, we describe methods of digital evidence analysis about USB thumb drives. We also design and implement USB thumb drive analysis tool that offers various functions on a digital forensic view.
Beyond Local Nash Equilibria for Adversarial Networks

Save for some special cases, current training methods for Generative Adversarial Networks (GANs) are at best guaranteed to converge to a ‘local Nash equilibrium’ (LNE). Such LNEs, however, can be arbitrarily far from an actual Nash equilibrium (NE), which implies that there are no guarantees on the quality of the found generator or classifier. This paper proposes to model GANs explicitly as finite games in mixed strategies, thereby ensuring that every LNE is an NE. We use the Parallel Nash Memory as a solution method, which is proven to monotonically converge to a resource-bounded Nash equilibrium. We empirically demonstrate that our method is less prone to typical GAN problems such as mode collapse and produces solutions that are less exploitable than those produced by GANs and MGANs.
Answering Natural Language Questions by Subgraph Matching over Knowledge Graphs

RDF question/answering (Q/A) allows users to ask questions in natural languages over a knowledge base represented by RDF. To answer a natural language question, the existing work takes a two-stage approach: question understanding and query evaluation. Their focus is on question understanding to deal with the disambiguation of the natural language phrases. The most common technique is the joint disambiguation, which has the exponential search space. In this paper, we propose a systematic framework to answer natural language questions over RDF repository (RDF Q/A) from a graph data-driven perspective. We propose a semantic query graph to model the query intention in the natural language question in a structural way, based on which, RDF Q/A is reduced to subgraph matching problem. More importantly, we resolve the ambiguity of natural language questions at the time when matches of query are found. The cost of disambiguation is saved if there are no matching found. More specifically, we propose two different frameworks to build the semantic query graph, one is relation (edge)-first and the other one is node-first. We compare our method with some state-of-the-art RDF Q/A systems in the benchmark dataset. Extensive experiments confirm that our method not only improves the precision but also speeds up query performance greatly.
Gm/ID based noise analysis for CMOS analog circuits

This paper proposes a technique to obtain thermal noise coefficient (γ) and corner frequency (f<inf>co</inf>) from simulation. Once determined, γ and f<inf>co</inf> can be integrated into the g<inf>m</inf>/I<inf>D</inf> design flow to simplify CMOS analog circuit design. A folded cascode operational transconductance amplifier (OTA) is designed to provide a point of comparison. A 10% error in input noise and a 25% error in output noise show that γ and f<inf>co</inf> can indeed be integrated into the g<inf>m</inf>/I<inf>D</inf> design flow.
Pharmaceutical significance of cellulose : A review

The amalgamation of polymer and pharmaceutical sciences led to the introduction of polymer in the design and development of drug delivery systems. Polymeric delivery systems are mainly intended to achieve controlled or sustained drug delivery. Polysaccharides fabricated into hydrophilic matrices remain popular biomaterials for controlled-release dosage forms and the most abundant naturally occurring biopolymer is cellulose; so hdroxypropylmethyl cellulose, hydroxypropyl cellulose, microcrystalline cellulose and hydroxyethyl cellulose can be used for production of time controlled delivery systems. Additionally microcrystalline cellulose, sodium carboxymethyl cellulose, hydroxypropylmethyl cellulose, hydroxyethyl cellulose as well as hydroxypropyl cellulose are used to coat tablets. Cellulose acetate phthalate and hydroxymethyl cellulose phthalate are also used for enteric coating of tablets. Targeting of drugs to the colon following oral administration has also been accomplished by using polysaccharides such as hdroxypropylmethyl cellulose and hydroxypropyl cellulose in hydrated form; also they act as binders that swell when hydrated by gastric media and delay absorption. This paper assembles the current knowledge on the structure and chemistry of cellulose, and in the development of innovative cellulose esters and ethers for pharmaceuticals.
STRATEGIC HUMAN RESOURCE MANAGEMENT AT SEARS

This article describes the HR Management System in place at Sears. Key emphases of Sears' HR management infrastructure include : (1) formulating and communicating a corporate mission, vision, and goals, (2) employee education and development through the Sears University, (3) performance management and incentive compensation systems linked closely to the firm's strategy, (4) validated employee selection systems, and (5) delivering the "HR Basics" very competently. Key challenges for the future include : (1) maintaining momentum in the performance improvement process, (2) identifying barriers to success, and (3) clearly articulating HR's role in the change management process .
Model-induced term-weighting schemes for text classification

The bag-of-words representation of text data is very popular for document classification. In the recent literature, it has been shown that properly weighting the term feature vector can improve the classification performance significantly beyond the original term-frequency based features. In this paper we demystify the success of the recent term-weighting strategies as well as provide possibly more reasonable modifications. We then propose novel term-weighting schemes that can be induced from the well-known document probabilistic models such as the Naive Bayes and the multinomial term model. Interestingly, some of the intuition-based term-weighting schemes coincide exactly with the proposed derivations. Our term-weighting schemes are tested on large-scale text classification problems/datasets where we demonstrate improved prediction performance over existing approaches.
Vehicular ad hoc networks (VANETS): status, results, and challenges

Recent advances in hardware, software, and communication technologies are enabling the design and implementation of a whole range of different types of networks that are being deployed in various environments. One such network that has received a lot of interest in the last couple of S. Zeadally ( ) Network Systems Laboratory, Department of Computer Science and Information Technology, University of the District of Columbia, 4200, Connecticut Avenue, N.W., Washington, DC 20008, USA e-mail: szeadally@udc.edu R. Hunt Department of Computer Science and Software Engineering, College of Engineering, University of Canterbury, Private Bag 4800, Christchurch, New Zealand e-mail: ray.hunt@canterbury.ac.nz Y.-S. Chen Department of Computer Science and Information Engineering, National Taipei University, 151, University Rd., San Shia, Taipei County, Taiwan e-mail: yschen@mail.ntpu.edu.tw Y.-S. Chen e-mail: yschen@csie.ntpu.edu.tw Y.-S. Chen e-mail: yschen.iet@gmail.com A. Irwin School of Computer and Information Science, University of South Australia, Room F2-22a, Mawson Lakes, South Australia 5095,  angela.irwin@unisa.edu.au A. Hassan School of Information Science, Computer and Electrical Engineering, Halmstad University, Kristian IV:s väg 3, 301 18 Halmstad, Sweden e-mail: aamhas06@student.hh.se years is the Vehicular Ad-Hoc Network (VANET). VANET has become an active area of research, standardization, and development because it has tremendous potential to improve vehicle and road safety, traffic efficiency, and convenience as well as comfort to both drivers and passengers. Recent research efforts have placed a strong emphasis on novel VANET design architectures and implementations. A lot of VANET research work have focused on specific areas including routing, broadcasting, Quality of Service (QoS), and security. We survey some of the recent research results in these areas. We present a review of wireless access standards for VANETs, and describe some of the recent VANET trials and deployments in the US, Japan, and the European Union. In addition, we also briefly present some of the simulators currently available to VANET researchers for VANET simulations and we assess their benefits and limitations. Finally, we outline some of the VANET research challenges that still need to be addressed to enable the ubiquitous deployment and widespead adoption of scalable, reliable, robust, and secure VANET architectures, protocols, technologies, and services.
SEISMIC LOSS ESTIMATION OF MID-RISE MASONRY INFILLED STEEL FRAME STRUCTURES THROUGH INCREMENTAL DYNAMIC ANALYSIS

The seismic loss estimation is greatly influenced by the identification of the failure mechanism and distribution of the structures. In case of infilled structures, the final failure mechanism greatly differs to that expected during the design and the analysis stages. This is mainly due to the resultant composite behaviour of the frame and the infill panel, which makes the failure assessment and consequently the loss estimation a challenge. In this study, a numerical investigation has been conducted on the influence of masonry infilled panels on physical structural damages and the associated economic losses, under seismic excitation. The selected index buildings have been simulated following real case typical mid-rise masonry infilled steel frame structures. A realistic simulation of construction details, such as variation of infill material properties, type of connections and built quality have been implemented in the models. The fragility functions have been derived for each model using the outcomes obtained from incremental dynamic analysis (IDA). Moreover, by considering different cases of building distribution, the losses have been estimated following an intensity-based assessment approach. The results indicate that the presence of infill panel have a noticeable influence on the vulnerability of the structure and should not be ignored in loss estimations.
Detecting falsified financial statements: a comparative study using multicriteria analysis and multivariate statistical techniques

Falsifying Financial Statements involves the manipulation of financial accounts by overstating assets, sales and profit, or understating liabilities, expenses, or losses. This paper explores the effectiveness of an innovative classification methodology in detecting firms that issue falsified financial statements (FFS) and the identification of the factors associated to FFS. The methodology is based on the concepts of multicriteria decision aid (MCDA) and the application of the UTADIS classification method (UTilités Additives DIScriminantes). A sample of 76 Greek firms (38 with FFS and 38 non-FFS) described over ten financial ratios is used for detecting factors associated with FFS. A Jackknife procedure approach is employed for model validation and comparison with multivariate statistical techniques, namely discriminant and logit analysis. The results indicate that the proposed MCDA methodology outperforms traditional statistical techniques which are widely used for FFS detection purposes. Furthermore, the results indicate that the investigation of financial information can be helpful towards the identification of FFS and highlight the importance of financial ratios such as the total debt to total assets ratio, the inventories to sales ratio, the net profit to sales ratio and the sales to total assets ratio.
Data Mining with Big Data

In an Information technology world, the ability to effectively process massive datasets has become integral to a broad range of scientific and other academic disciplines. We are living in an era of data deluge and as a result, the term “Big Data” is appearing in many contexts. It ranges from meteorology, genomics, complex physics simulations, biological and environmental research, finance and business to healthcare. Big Data refers to data streams of higher velocity and higher variety. The infrastructure required to support the acquisition of Big Data must deliver low, predictable latency in both capturing data and in executing short, simple queries. To be able to handle very high transaction volumes, often in a distributed environment; and support flexible, dynamic data structures. Data processing is considerably more challenging than simply locating, identifying, understanding, and citing data. For effective large-scale analysis all of this has to happen in a completely automated manner. This requires differences in data structure and semantics to be expressed in forms that are computer understandable, and then “robotically” resolvable. There is a strong body of work in data integration, mapping and transformations. However, considerable additional work is required to achieve automated error-free difference resolution. This paper proposes a framework on recent research for the Data Mining using Big Data.
Knowledge management in small and medium-sized companies: knowledge management for entrepreneurs

Society has changed drastically over the last few years. But this is nothing new, or so it appears. Societies are always changing, just as people are always changing. And seeing as it is the people who form the societies, a constantly changing society is only natural. However something more seems to have happened over the last few years. Without wanting to frighten off the reader straight away, we can point to a diversity of social developments that indicate that the changes seem to be following each other faster, especially over the last few decades. We can for instance, point to the pluralisation (or a growing versatility), differentialisation and specialisation of society as a whole. On a more personal note, we see the diversification of communities, an emphasis on emancipation, individualisation and post-materialism and an increasing wish to live one's life as one wishes, free from social, religious or ideological contexts.
A Geo-Indistinguishable Location Perturbation Mechanism for Location-Based Services Supporting Frequent Queries

As location-based services (LBSs) on smartphones become increasingly popular, such services are causing serious privacy concerns, because many users are unwilling to see their location information leaked to service providers. Recently, in order to protect users’ location privacy, researchers have introduced geo-indistinguishability, the first specialized privacy model for LBSs that can provide provable privacy guarantees. Intuitively, geo-indistinguishability means that through perturbation, any two locations within a given distance produce observations with similar distributions, and thus, attackers have no way to learn users’ real locations. However, even if geo-indistinguishability is achieved, there remains a significant threat to users’ location privacy: the privacy consumption increases with the number of queries for the existing geo-indistinguishable location perturbation mechanism, and therefore, there is a high risk of privacy violation when the number of queries is not small. In this paper, we enhance the privacy protection for LBSs by proposing an improved geo-indistinguishable mechanism. It can reduce the privacy costs to almost 0 when the user’s location satisfies a condition. We also present an improvement to further reduce the privacy costs when the above condition is not satisfied. Evaluations upon two public trace data sets show that the proposed mechanisms can dramatically save the privacy budget and thus support much more queries. The results also show that the proposed mechanisms are efficient, and their performance is controllable.
Towards a worldwide wood economics spectrum.

Wood performs several essential functions in plants, including mechanically supporting aboveground tissue, storing water and other resources, and transporting sap. Woody tissues are likely to face physiological, structural and defensive trade-offs. How a plant optimizes among these competing functions can have major ecological implications, which have been under-appreciated by ecologists compared to the focus they have given to leaf function. To draw together our current understanding of wood function, we identify and collate data on the major wood functional traits, including the largest wood density database to date (8412 taxa), mechanical strength measures and anatomical features, as well as clade-specific features such as secondary chemistry. We then show how wood traits are related to one another, highlighting functional trade-offs, and to ecological and demographic plant features (growth form, growth rate, latitude, ecological setting). We suggest that, similar to the manifold that tree species leaf traits cluster around the 'leaf economics spectrum', a similar 'wood economics spectrum' may be defined. We then discuss the biogeography, evolution and biogeochemistry of the spectrum, and conclude by pointing out the major gaps in our current knowledge of wood functional traits.
The Relative Densities of Pharmaceutical Powders , Blends , Dry Granulations , and Immediate-Release Tablets

relative densities of pharmaceutical solids play an important role in determining their performance (e.g., flow and compaction properties) in both tablet and capsule dosage forms. In this article, the authors report the densities of a wide variety of solid pharmaceutical formulations and intermediates. The variance of density with chemical structure, processing history, and dosage-form type is significant. This study shows that density can be used as an equipment-independent scaling parameter for several common drug-product manufacturing operations. any physical responses of powders, granules, and compacts such as powder flow and tensile strength are determined largely by their absolute and relative densities (1–8). Although measuring these properties is a simple task, a review of the literature reveals that a combined source of density data that formulation scientists can refer to does not exist. The purpose of this article is to provide such a reference source and to give insight about how these critical properties can be measured for common pharmaceutical solids and how they can be used for monitoring common drugproduct manufacturing operations.
International Computer and Information Literacy Study Assessment Framework

Overview 7 Purpose of the study 7 Background to the study 7 The place of CIL in relation to traditional disciplines 10 Research questions, participants, and instruments 12 Computer and information literacy framework 15 Overview 15 Defining computer and information literacy 16 Structure of the computer and information literacy construct 18 Strands and aspects 19 Contextual framework 25 Overview 25 Classification of contextual factors 25 Contextual levels and variables 27 Assessment design 35 The ICILS test design 35 The ICILS test instrument 36 Types of assessment task 36 Mapping test items to the CIL framework 43 The ICILS student questionnaire and context instruments 44 Foreword As an international, nonprofit cooperative of national research institutions and governmental research agencies, the International Association for the Evaluation of Educational Achievement (IEA) has conducted more than 30 large-scale comparative studies in countries around the world. These studies have reported on educational policies, practices, and learning outcomes on a wide range of topics and subject matters. These investigations have proven to be a key resource for monitoring educational quality and progress within individual countries and across a broad international context. The International Computer and Information Literacy Study (ICILS) follows a series of earlier IEA studies that had, as their particular focus, information and communication technologies (ICT) in education. The first of these, the Computers in Education Study (COMPED), was carried out in 1989 and again in 1992 for the purpose of reporting on the educational use of computers in the context of emerging governmental initiatives to implement ICT in schools. The next series of projects in this area was the Second These projects provided an update on the implementation of computer technology resources in schools and their utilization in the teaching process. The continuing rapid development of computer and other information technologies has transformed the environment in which young people access, create, and share information. Many countries, having recognized the imperative of digital technology in all its forms, acknowledge the need to educate their citizens in the use of these technologies so that they and their society can secure the future economic and social benefits of proficiency in the use of digital technologies. Within this context, many questions relating to the efficacy of instructional programs and how instruction is progressed in the area of digital literacy arise. ICILS represents the first international comparative study to investigate how students are developing the set of knowledge, understanding, …
Distributed Protocols for Leader Election: A Game-Theoretic Perspective

We do a game-theoretic analysis of leader election, under the assumption that each agent prefers to have some leader than to have no leader at all. We show that it is possible to obtain a fair Nash equilibrium, where each agent has an equal probability of being elected leader, in a completely connected network, in a bidirectional ring, and a unidirectional ring, in the synchronous setting. In the asynchronous setting, Nash equilibrium is not quite the right solution concept. Rather, we must consider ex post Nash equilibrium; this means that we have a Nash equilibrium no matter what a scheduling adversary does. We show that ex post Nash equilibrium is attainable in the asynchronous setting in all the networks we consider, using a protocol with bounded running time. However, in the asynchronous setting, we require that n > 2. We can get a fair -Nash equilibrium if n = 2 in the asynchronous setting, under some cryptographic assumptions (specifically, the existence of a pseudo-random number generator and polynomially-bounded agents), using ideas from bit-commitment protocols. We then generalize these results to a setting where we can have deviations by a coalition of size k. In this case, we can get what we call a fair k-resilient equilibrium if n > 2k; under the same cryptographic assumptions, we can a get a k-resilient equilibrium if n = 2k. Finally, we show that, under minimal assumptions, not only do our protocols give a Nash equilibrium, they also give a sequential equilibrium [?], so players even play optimally off the equilibrium path.