nils-herrmann/clean_scirepeval huggingface dataset:
SAIL: single access point-based indoor localization

SAIL, a Single Access Point Based Indoor Localization system. Although there have been advances in WiFi-based positioning techniques, we find that existing solutions either require a dense deployment of access points (APs), manual fingerprinting, energy hungry WiFi scanning, or sophisticated AP hardware.  SAIL using a single commodity WiFi AP to avoid these restrictions. SAIL computes the distance between the client and an AP using the propagation delay of the signal traversing between the two, combines the distance with smartphone dead-reckoning techniques, and employs geometric methods to ultimately yield the client's location using a single AP. SAIL combines physical layer (PHY) information and human motion to compute the propagation delay of the direct path by itself, eliminating the adverse effect of multipath and yielding sub-meter distance estimation accuracy. Furthermore, SAIL systematically addresses some of the common challenges towards dead-reckoning using smartphone sensors and achieves 2-5x accuracy improvements over existing techniques. We have implemented SAIL on commodity wireless APs and smartphones. Evaluation in a large-scale enterprise environment with 10 mobile users demonstrates that SAIL can capture the user's location with a mean error of 2.3m using just a single AP.
New cubic reference table based image steganography

Tradition reference table based (RTB) methods employ two pixels to conceal a secret digit according to a two-dimensional reference table. In this paper, x-dimensional reference table framework is defined, which can be regarded as generalization of the prior works. The available pixels to be embedded are limited in two-dimensional space, so the proposed methods extend the dimensional space of reference table. Theoretical analyses are given to justify the effectiveness of the proposed construction. Two novel RTB methods named CRT (cubic reference table) and CRT-PVD (cubic reference table and pixel value differencing) are presented. The former is independent of image contents while embedding, and the latter is depended on the discriminated image smoothness. Experimental results show that two proposed methods can achieve better performance compared with the prior works.
Security Issues in NoSQL Databases

applications has created the need to store large amount of data in distributed databases that provide high availability and scalability. In recent years, a growing number of companies have adopted various types of non-relational databases, commonly referred to as NoSQL databases, and as the applications they serve emerge, they gain extensive market interest. These new database systems are not relational by definition and therefore they do not support full SQL functionality. Moreover, as opposed to relational databases they trade consistency and security for performance and scalability. As increasingly sensitive data is being stored in NoSQL databases, security issues become growing concerns. This paper reviews two of the most popular NoSQL databases (Cassandra and MongoDB) and outlines their main security features and problems.
Discriminative Color Descriptors

Color description is a challenging task because of large variations in RGB values which occur due to scene accidental events, such as shadows, shading, specularities, illuminant color changes, and changes in viewing geometry. Traditionally, this challenge has been addressed by capturing the variations in physics-based models, and deriving invariants for the undesired variations. The drawback of this approach is that sets of distinguishable colors in the original color space are mapped to the same value in the photometric invariant space. This results in a drop of discriminative power of the color description. In this paper we take an information theoretic approach to color description. We cluster color values together based on their discriminative power in a classification problem. The clustering has the explicit objective to minimize the drop of mutual information of the final representation. We show that such a color description automatically learns a certain degree of photometric invariance. We also show that a universal color representation, which is based on other data sets than the one at hand, can obtain competing performance. Experiments show that the proposed descriptor outperforms existing photometric invariants. Furthermore, we show that combined with shape description these color descriptors obtain excellent results on four challenging datasets, namely, PASCAL VOC 2007, Flowers-102, Stanford dogs-120 and Birds-200.
Raziel: Private and Verifiable Smart Contracts on Blockchains

Raziel combines secure multi-party computation and proof-carrying code to provide privacy, correctness and verifiability guarantees for smart contracts on blockchains. Effectively solving DAO and Gyges attacks, this paper describes an implementation and presents examples to demonstrate its practical viability (e.g., private and verifiable crowdfundings and investment funds, double auctions for decentralized exchanges). Additionally, we show how to use Zero-Knowledge Proofs of Proofs (i.e., Proof-Carrying Code certificates) to prove the validity of smart contracts to third parties before their execution without revealing anything else. Finally, we show how miners could get rewarded for generating pre-processing data for secure multi-party computation. ∗Corresponding author
Achieving Secure, Universal, and Fine-Grained Query Results Verification for Secure Search Scheme over Encrypted Cloud Data

Secure search techniques over encrypted cloud data allow an authorized user to query data files of interest by submitting encrypted query keywords to the cloud server in a privacy-preserving manner. However, in practice, the returned query results may be incorrect or incomplete in the dishonest cloud environment. For example, the cloud server may intentionally omit some qualified results to save computational resources and communication overhead. Thus, a well-functioning secure query system should provide a query results verification mechanism that allows the data user to verify results. In this paper, we design a secure, easily integrated, and fine-grained query results verification mechanism, by which, given an encrypted query results set, the query user not only can verify the correctness of each data file in the set but also can further check how many or which qualified data files are not returned if the set is incomplete before decryption. The verification scheme is loose-coupling to concrete secure search techniques and can be very easily integrated into any secure query scheme. We achieve the goal by constructing secure verification object for encrypted cloud data. Furthermore, a short signature technique with extremely small storage cost is proposed to guarantee the authenticity of verification object and a verification object request technique is presented to allow the query user to securely obtain the desired verification object. Performance evaluation shows that the proposed schemes are practical and efficient.
Comparative Metagenomics Reveals Host Specific Metavirulomes and Horizontal Gene Transfer Elements in the Chicken Cecum Microbiome

The complex microbiome of the ceca of chickens plays an important role in nutrient utilization, growth and well-being of these animals. Since we have a very limited understanding of the capabilities of most species present in the cecum, we investigated the role of the microbiome by comparative analyses of both the microbial community structure and functional gene content using random sample pyrosequencing. The overall goal of this study was to characterize the chicken cecal microbiome using a pathogen-free chicken and one that had been challenged with Campylobacter jejuni.



Comparative metagenomic pyrosequencing was used to generate 55,364,266 bases of random sampled pyrosequence data from two chicken cecal samples. SSU rDNA gene tags and environmental gene tags (EGTs) were identified using SEED subsystems-based annotations. The distribution of phylotypes and EGTs detected within each cecal sample were primarily from the Firmicutes, Bacteroidetes and Proteobacteria, consistent with previous SSU rDNA libraries of the chicken cecum. Carbohydrate metabolism and virulence genes are major components of the EGT content of both of these microbiomes. A comparison of the twelve major pathways in the SEED Virulence Subsystem (metavirulome) represented in the chicken cecum, mouse cecum and human fecal microbiomes showed that the metavirulomes differed between these microbiomes and the metavirulomes clustered by host environment. The chicken cecum microbiomes had the broadest range of EGTs within the SEED Conjugative Transposon Subsystem, however the mouse cecum microbiomes showed a greater abundance of EGTs in this subsystem. Gene assemblies (32 contigs) from one microbiome sample were predominately from the Bacteroidetes, and seven of these showed sequence similarity to transposases, whereas the remaining sequences were most similar to those from catabolic gene families.



This analysis has demonstrated that mobile DNA elements are a major functional component of cecal microbiomes, thus contributing to horizontal gene transfer and functional microbiome evolution. Moreover, the metavirulomes of these microbiomes appear to associate by host environment. These data have implications for defining core and variable microbiome content in a host species. Furthermore, this suggests that the evolution of host specific metavirulomes is a contributing factor in disease resistance to zoonotic pathogens.
Multi-Modal Fusion for Moment in Time Video Classification

Action recognition in videos remains a challenging problem in the machine learning community. Particularly challenging is the differing degree of intra-class variation between actions: While background information is enough to distinguish certain classes, many others are abstract and require fine-grained knowledge for discrimination. To approach this problem, in this work we evaluate different modalities on the recently published Moments in Time dataset, a collection of one million videos of short length.
Sufficient Sample Sizes for Multilevel Modeling

An important problem in multilevel modeling is what constitutes a sufficient sample size for accurate estimation. In multilevel analysis, the major restriction is often the higher-level sample size. In this paper, a simulation study is used to determine the influence of different sample sizes at the group level on the accuracy of the estimates (regression coefficients and variances) and their standard errors. In addition, the influence of other factors, such as the lowest-level sample size and different variance distributions between the levels (different intraclass correlations), is examined. The results show that only a small sample size at level two (meaning a sample of 50 or less) leads to biased estimates of the second-level standard errors. In all of the other simulated conditions the estimates of the regression coefficients, the variance components, and the standard errors are unbiased and accurate.
STRATEGIC MAP FOR HOSPITAL MANAGEMENT: PERSPECTIVES AND PRIORITIES

The aim of this article is to present the application of a strategic map for hospital management. The main hypothesis is, that strategic map for a hospital should differ from the classical one by Kaplan & Norton due to different priorities hospital work specificity as such. The main finding is that financial perspective is fundamental, basic for hospital activity. In hospital “X” strategic map, finance are the resource, not the result.  December, 2015 1st  March, 2016  June, 2016 DOI: 10.14254/2071789X.2016/9-3/6 JEL Classification: I11, M41, M21
Predicting at-risk novice Java programmers through the analysis of online protocols

In this study, we attempted to quantify indicators of novice programmer progress in the task of writing programs, and we evaluated the use of these indicators for identifying academically at-risk students. Over the course of nine weeks, students completed five different graded programming exercises in a computer lab. Using an instrumented version of BlueJ, an integrated development environment for Java, we collected novice compilations and explored the errors novices encountered, the locations of these errors, and the frequency with which novices compiled their programs. We identified which frequently encountered errors and which compilation behaviors were characteristic of at-risk students. Based on these findings, we developed linear regression models that allowed prediction of students' scores on a midterm exam. However, the models derived could not accurately predict the at-risk students. Although our goal of identifying at-risk students was not attained, we have gained insights regarding the compilation behavior of our students, which may help us identify students who are in need of intervention.
A comparative study of vein pattern recognition for biometrie authentication

In informational age there are many information crucial to a individual. To protect the data from the unwanted use we proposed the biometric system of vein recognition as today's world demand for a easy and accurate biometric system to protect our data. The biometric system is accurate and easy to use as every individual has a unique vein pattern. In this paper we have studied various method used by different people to achieve the goal to secure world and give the reader a brief prospective of this technology.
Area-efficient high-speed hybrid 1-bit full adder circuit using modified XNOR gate

A hybrid 1-bit full adder design is presented here using modified 3T-XNOR gate to improve the area and speed performance. The design is implemented for 1-bit full adder and then is scaled to 32-bit adder. Combination of CMOS and transmission gate logic is used to enhance the performance in terms of area, delay and power. The performance of the proposed design is evaluated through the simulation analysis in 90-nm technology with 1.2v supply voltage. The effect of scaling on the overall performance is also analyzed through the performance evaluation of 1-bit and 32-bit adder. The performance of proposed design is also compared with conventional design to verify the effectiveness in terms of area, power, delay.
A Mapping Study on Requirements Engineering in Agile Software Development

Agile software development (ASD) methods have gained popularity in the industry and been the subject of an increasing amount of academic research. Although requirements engineering (RE) in ASD has been studied, the overall understanding of RE in ASD as a phenomenon is still weak. We conducted a mapping study of RE in ASD to review the scientific literature. 28 articles on the topic were identified and analyzed. The results indicate that the definition of agile RE is vague. The proposed benefits from agile RE included lower process overheads, a better requirements understanding, a reduced tendency to over allocate development resources, responsiveness to change, rapid delivery of value, and improved customer relationships. The problematic areas of agile RE were the use of customer representatives, the user story requirements format, the prioritization of requirements, growing technical debt, tacit requirements knowledge, and imprecise effort estimation. We also report proposed solutions to the identified problems.
Inverse kinematics of a two-wheeled differential drive an autonomous mobile robot

In this research, an inverse kinematic model for automatic mobile robot has been experimental designed by direct controlling of two-wheeled differential drive method. An orientation of the robot toward lined track is observed to evaluate the right position by controlling the speed differences between the rears two-wheeled separately. The angular speed of the rear wheels calculated according to the desired linear speed of the robot and an error occurs to the angle of the robot orientation affected by of radius of the rear wheel, distance between the two driven rear wheels, and the curvature of turn movement the mobile robot. Two font-wheels were designed flexible as a free wheel mechanism to follow the lined track. A system performance was analyzed to obtain the robot characteristic response.
The Double Dance of Agency : a socio-theoretic account of how machines and humans interact

The nature of the relationship between information technology (IT) and organizations has been a long-standing debate in the Information Systems literature. Does IT shape organizations, or do people in organisations control how IT is used? To formulate the question a little differently: does agency (the capacity to make a difference) lie predominantly with machines (computer systems) or humans (organisational actors)? Many proposals for a middle way between the extremes of technological and social determinism have been put advanced; in recent years researchers oriented towards social theories have focused on structuration theory and (lately) actor network theory. These two theories, however, adopt different and incompatible views of agency. Thus, structuration theory sees agency as exclusively a property of humans, whereas the principle of general symmetry in actor network theory implies that machines may also be agents. Drawing on critiques of both structuration theory and actor network theory, this paper develops a theoretical account of the interaction between human and machine agency: the double dance of agency. The account seeks to contribute to theorisation of the relationship between technology and organisation by recognizing both the different character of human and machine agency, and the emergent properties of their interplay.
IGCTs vs. IGBTs for circuit breakers in advanced ship electrical systems

Solid-State Circuit Breakers (SSCBs) are being considered for several of the new Navy ships' power distribution platforms. This is because SSCBs offer many advantages to electrical systems that conventional Electro-Mechanical Circuit Breakers (EMCBs) cannot. These advantages include much faster interruption of overcurrents, based on lower current thresholds and/or di/dt rate of current rise; reduced energy flowing into the electrical system during faults; and reduced system ringing during fault interruptions. Additional advantages of SSCBs are the elimination of electrical arcing, which is particularly useful for DC and higher voltage distribution systems and systems in environments with volatile gases or explosives; reduced acoustic noise and Electro-Magnetic Interference (EMI) levels during circuit breaker switching; and reduced maintenance and lifecycle costs during the typical 40-year lifetime of the ship. This paper describes the advantages and disadvantages of SSCBs using IGCTs, SSCBs using IGBTs and conventional EMCBs. It will also describe the differences between IGCTs and IGBTs and will consider the design of the bus voltage snubber. This paper will also show how redesigning the ship's electrical system, while considering these important issues, can result in a more reliable, cost-effective power distribution system for the ship.
The Epi.q-1 Hybrid Mobile Robot

In this paper we propose an innovative solution for a small size hybrid mobile robot called Epi.q-1. Overall dimensions are about 160 mm 360 mm 280 mm (height length width). The Epi.q-1 robot moves on flat, steep or uneven ground. It can climb over obstacles or steps, even if they are non-uniform in size. Its operating mode adapts to ground conditions and changes accordingly: from rolling (on wheels) to stepping (on legs) thanks to its great mobility it can follow complex routes. It is easy to control with just a few actuators. Robot locomotion drive-generating units employ an original driving mechanism, where degrees of freedom (DOFs) can be limited to some extent according to the operating conditions or thanks to a switching device. Locomotion units consist of a motor linked to a gear (double epicyclical chain) and an axial device (mini-motor and lead screw system) able to lock or unlock some DOFs of the kinematic chain. Moreover, the robot locomotion unit can change its size, from small to large and vice versa, in order to be able to reach restricted spaces and to overcome even quite tall obstacles. It was experimentally tested on flat ground and slopes. It can overcome 90 mm obstacles, that are 72% of the height of the locomotion unit, and climb stairs. KEY WORDS—mobile robot, hybrid robot, wheel-legged locomotion, stair climbing, triple wheels The International    http://www.sagepub.co.uk/journalsPermissions.nav Figures 1–3, 6–12 appear in color online: http://ijr.sagepub.com
Harnessing Context Incongruity for Sarcasm Detection

The relationship between context incongruity and sarcasm has been studied in linguistics. We present a computational system that harnesses context incongruity as a basis for sarcasm detection. Our statistical sarcasm classifiers incorporate two kinds of incongruity features: explicit and implicit. We show the benefit of our incongruity features for two text forms tweets and discussion forum posts. Our system also outperforms two past works (with Fscore improvement of 10-20%). We also show how our features can capture intersentential incongruity.
A survey of variability modeling in industrial practice

Over more than two decades, numerous variability modeling techniques have been introduced in academia and industry. However, little is known about the actual use of these techniques. While dozens of experience reports on software product line engineering exist, only very few focus on variability modeling. This lack of empirical data threatens the validity of existing techniques, and hinders their improvement. As part of our effort to improve empirical understanding of variability modeling, we present the results of a survey questionnaire distributed to industrial practitioners. These results provide insights into application scenarios and perceived benefits of variability modeling, the notations and tools used, the scale of industrial models, and experienced challenges and mitigation strategies.
Data-Oriented Programming: On the Expressiveness of Non-control Data Attacks

As control-flow hijacking defenses gain adoption, it is important to understand the remaining capabilities of adversaries via memory exploits. Non-control data exploits are used to mount information leakage attacks or privilege escalation attacks program memory. Compared to control-flow hijacking attacks, such non-control data exploits have limited expressiveness, however, the question is: what is the real expressive power of non-control data attacks? In this paper we show that such attacks are Turing-complete. We present a systematic technique called data-oriented programming (DOP) to construct expressive non-control data exploits for arbitrary x86 programs. In the experimental evaluation using 9 programs, we identified 7518 data-oriented x86 gadgets and 5052 gadget dispatchers, which are the building blocks for DOP. 8 out of 9 real-world programs have gadgets to simulate arbitrary computations and 2 of them are confirmed to be able to build Turing-complete attacks. We build 3 end-to-end attacks to bypass randomization defenses without leaking addresses, to run a network bot which takes commands from the attacker, and to alter the memory permissions. All the attacks work in the presence of ASLR and DEP, demonstrating how the expressiveness offered by DOP significantly empowers the attacker.