nils-herrmann/clean_scirepeval huggingface dataset:
Behavior Analysis based DNS Tunneling Detection and Classification with Big Data Technologies

Domain Name System (DNS) is ubiquitous in any network. DNS tunnelling is a technique to transfer data, convey messages or conduct TCP activities over DNS protocol that is typically not blocked or watched by security enforcement such as firewalls. As a technique, it can be utilized in many malicious ways which can compromise the security of a network by the activities of data exfiltration, cyber-espionage, and command and control. On the other side, it can also be used by legitimate users. The traditional methods may not be able to distinguish between legitimate and malicious uses even if they can detect the DNS tunnelling activities. We propose a behaviour analysis based method that can not only detect the DNS tunnelling, but also classify the activities in order to catch and block the malicious tunnelling traffic. The proposed method can achieve the scale of real-time detection on fast and large DNS data with the use of big data technologies in offline training and online detection systems.
SAP HANA distributed in-memory database system: Transaction, session, and metadata management

One of the core principles of the SAP HANA database system is the comprehensive support of distributed query facility. Supporting scale-out scenarios was one of the major design principles of the system from the very beginning. Within this paper, we first give an overview of the overall functionality with respect to data allocation, metadata caching and query routing. We then dive into some level of detail for specific topics and explain features and methods not common in traditional disk-based database systems. In summary, the paper provides a comprehensive overview of distributed query processing in SAP HANA database to achieve scalability to handle large databases and heterogeneous types of workloads.
Debbie, the Debate Bot of the Future

Chatbots are a rapidly expanding application of dialogue systems with companies switching to bot services for customer support, and new applications for users interested in casual conversation. One style of casual conversation is argument; many people love nothing more than a good argument. Moreover, there are a number of existing corpora of argumentative dialogues, annotated for agreement and disagreement, stance, sarcasm and argument quality. This paper introduces Debbie, a novel arguing bot, that selects arguments from conversational corpora, and aims to use them appropriately in context. We present an initial working prototype of Debbie, with some preliminary evaluation and describe future work.
Intelligent weather monitoring systems using connectionist models

This paper presents a comparative study of different neural network models for forecasting the weather of Vancouver, British Columbia, Canada. For developing the models, we used one year’s data comprising of daily maximum and minimum temperature, and wind-speed. We used Multi-Layered Perceptron (MLP) and an Elman Recurrent Neural Network (ERNN), which were trained using the one-step-secant and LevenbergMarquardt algorithms. To ensure the effectiveness of neurocomputing techniques, we also tested the different connectionist models using a different training and test data set. Our goal is to develop an accurate and reliable predictive model for weather analysis. Radial Basis Function Network (RBFN) exhibits a good universal approximation capability and high learning convergence rate of weights in the hidden and output layers. Experimental results obtained have shown RBFN produced the most accurate forecast model as compared to ERNN and MLP networks.
Altered Resting Brain Function and Structure in Professional Badminton Players

Neuroimaging studies of professional athletic or musical training have demonstrated considerable practice-dependent plasticity in various brain structures, which may reflect distinct training demands. In the present study, structural and functional brain alterations were examined in professional badminton players and compared with healthy controls using magnetic resonance imaging (MRI) and resting-state functional MRI. Gray matter concentration (GMC) was assessed using voxel-based morphometry (VBM), and resting-brain functions were measured by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity. Results showed that the athlete group had greater GMC and ALFF in the right and medial cerebellar regions, respectively. The athlete group also demonstrated smaller ALFF in the left superior parietal lobule and altered functional connectivity between the left superior parietal and frontal regions. These findings indicate that badminton expertise is associated with not only plastic structural changes in terms of enlarged gray matter density in the cerebellum, but also functional alterations in fronto-parietal connectivity. Such structural and functional alterations may reflect specific experiences of badminton training and practice, including high-capacity visuo-spatial processing and hand-eye coordination in addition to refined motor skills.
Regular Property Guided Dynamic Symbolic Execution

A challenging problem in software engineering is to check if a program has an execution path satisfying a regular property. We propose a novel method of dynamic symbolic execution (DSE) to automatically find a path of a program satisfying a regular property. What makes our method distinct is when exploring the path space, DSE is guided by the synergy of static analysis and dynamic analysis to find a target path as soon as possible. We have implemented our guided DSE method for Java programs based on JPF and WALA, and applied it to 13 real-world open source Java programs, a total of 225K lines of code, for extensive experiments. The results show the effectiveness, efficiency, feasibility and scalability of the method. Compared with the pure DSE on the time to find the first target path, the average speedup of the guided DSE is more than 258X when analyzing the programs that have more than 100 paths.
Enhancing the Security of LTE Networks against Jamming Attacks

The long-term advancement (LTE) is the new mobile communication system, built after a redesigned physical part and predicated on an orthogonal regularity division multiple gain access to (OFDMA) modulation, features solid performance in challenging multipath surroundings and substantially boosts the performance of the cellular channel in conditions of pieces per second per Hertz (bps/Hz). Nevertheless, as all cordless systems, LTE is susceptible to radio jamming episodes. Such dangers have security implications especially regarding next-generation disaster response communication systems predicated on LTE technology. This proof concept paper overviews some new effective attacks (smart jamming) that extend the number and effectiveness of basic radio jamming. Predicated on these new hazards, some new potential security research guidelines are introduced, looking to improve the resiliency of LTE systems against such problems. A spread-spectrum modulation of the key downlink broadcast stations is coupled with a scrambling of the air tool allocation of the uplink control stations and a sophisticated system information subject matter encryption scheme.
SENSING WITH TERAHERTZ RADIATION : APPLICATIONS AND CHALLENGES

The field of Terahertz (THz) radiation, electromagnetic energy, between 0.3 to 3 THz, has seen intense interest recently, because it combines some of the best properties of IR along with those of RF. For example, THz radiation can penetrate fabrics with less attenuation than IR, while its short wavelength maintains comparable imaging capabilities. We discuss major challenges in the field: designing systems and applications which fully exploit the unique properties of THz radiation. To illustrate, we present our reflective, radar-inspired THz imaging system and results, centered on biomedical burn imaging and skin hydration, and discuss challenges and ongoing research.
A Compact Four-Element MIMO/Diversity Antenna With Enhanced Bandwidth

In this letter, a four-element wideband multiple-input–multiple-output (MIMO) configuration consisting of inverted L-monopole antenna (ILA) elements is proposed. An additional low-frequency operating mode arises in the MIMO system due to symmetric arrangement of elements with interconnected ground, apart from the resonance of the isolated ILA. Utilizing this mode, the proposed MIMO antenna operates in wide frequency range of <inline-formula> <tex-math notation="LaTeX">$\text{2.70-4.94}$</tex-math></inline-formula> GHz (impedance bandwidth <inline-formula> <tex-math notation="LaTeX">$=58.6\%$</tex-math></inline-formula>). The proposed four-element MIMO system occupies compact total area of <inline-formula><tex-math notation="LaTeX">$0.13\lambda _{0}^{2}$</tex-math></inline-formula> ( <inline-formula><tex-math notation="LaTeX">$\lambda _{0}$</tex-math></inline-formula> = highest operating wavelength) and has no complex decoupling scheme. Satisfactory interelement isolation (<inline-formula><tex-math notation="LaTeX"> $\geq $</tex-math></inline-formula>11 dB) and directional pattern with average gain <inline-formula> <tex-math notation="LaTeX">$\approx 4$</tex-math></inline-formula> dBi are achieved throughout the operating band of the proposed MIMO antenna. Furthermore, envelope correlation coefficient <inline-formula><tex-math notation="LaTeX"> $< 0.1$</tex-math></inline-formula> and mean effective gain ratio close to 1 are obtained in the working frequencies, confirming satisfactory MIMO/diversity performance.
Face and Facial Feature Detection Evaluation - Performance Evaluation of Public Domain Haar Detectors for Face and Facial Feature Detection

Fast and reliable face and facial feature detection are required abilities for any Human Computer Interaction approach based on Computer Vision. Since the publication of the Viola-Jones object detection framework and the more recent open source implementation, an increasing number of applications have appeared, particularly in the context of facial processing. In this respect, the OpenCV community shares a collection of public domain classifiers for this scenario. However, as far as we know these classifiers have never been evaluated and/or compared. In this paper we analyze the individual performance of all those public classifiers getting the best performance for each target. These results are valid to define a baseline for future approaches. Additionally we propose a simple hierarchical combination of those classifiers to increase the facial feature detection rate while reducing the face false detection rate.
Genetic algorithm implementation in Python

This paper deals with genetic algorithm implementation in Python. Genetic algorithm is a probabilistic search algorithm based on the mechanics of natural selection and natural genetics. In genetic algorithms, a solution is represented by a list or a string. List or string processing in Python is more productive than in C/C++/Java. Genetic algorithms implementation in Python is quick and easy. In this paper, we introduce genetic algorithm implementation methods in Python. And we discuss various tools for speeding up Python programs.
Chapter 1 FPGA-oriented Security

Reconfigurable hardware is by far the most dominant implementation platform in terms of the number of designs per year. During the past decade, security has emerged as a premier design metrics with an ever increasing scope. Our objective is to identify and survey the most important issues related to FPGA security. Instead of insisting on comprehensiveness, we focus on a number of techniques that have the highest potential for conceptual breakthroughs or for the practical widespread adoption. Our emphasis is on security primitives (PUFs and TRNGs), analysis of potential vulnerabilities of FPGA synthesis flow, digital rights management, and FPGA-based applied algorithmic cryptography. We also discuss the most popular and a selection of recent research directions related to FPGA-based security platforms. Specifically, we identify and discuss a number of classical and emerging exciting FPGA-based security research and development directions.
REAL TIME WIRELESS AIR POLLUTION MONITORING SYSTEM

Air pollution has significant influence on the concentration of constituents in the atmosphere leading to effects like global warming and acid rains. To avoid such adverse imbalances in the nature, an air pollution monitoring system is utmost important. This paper attempts to develop an effective solution for pollution monitoring using wireless sensor networks (WSN) on a real time basis namely real time wireless air pollution monitoring system. Commercially available discrete gas sensors for sensing concentration of gases like CO2, NO2, CO and O2 are calibrated using appropriate calibration technologies. These pre-calibrated gas sensors are then integrated with the wireless sensor motes for field deployment at the campus and the Hyderabad city using multi hop data aggregation algorithm. A light weight middleware and a web interface to view the live pollution data in the form of numbers and charts from the test beds was developed and made available from anywhere on the internet. Other parameters like temperature and humidity were also sensed along with gas concentrations to enable data analysis through data fusion techniques. Experimentation carried out using the developed wireless air pollution monitoring system under different physical conditions show that the system collects reliable source of real time fine-grain pollution data.
Life "modes" in social media

Current social media products such as Facebook and Twitter have not sufficiently addressed how to help users organize people and content streams across different areas of their lives. We conducted a qualitative design research study to explore how we might best leverage natural models of social organization to improve experiences of social media. We found that participants organize their social worlds based on life 'modes', i.e., family, work and social. They strategically use communication technologies to manage intimacy levels within these modes, and levels of permeability through the boundaries between these modes. Mobile communication in particular enabled participants to aggregate and share content dynamically across life modes. While exploring problems with managing their social media streams, people showed a strong need for focused sharing - the ability to share content only with appropriate audiences within certain areas of life.
Elasticity in cloud computing: a survey

Cloud computing is now a well-consolidated paradigm for on-demand services provisioning on a pay-as-you-go model. Elasticity, one of the major benefits required for this computing model, is the ability to add and remove resources “on the fly” to handle the load variation. Although many works in literature have surveyed cloud computing and its features, there is a lack of a detailed analysis about elasticity for the cloud. As an attempt to fill this gap, we propose this survey on cloud computing elasticity based on an adaptation of a classic systematic review. We address different aspects of elasticity, such as definitions, metrics and tools for measuring, evaluation of the elasticity, and existing solutions. Finally, we present some open issues and future direcEmanuel Ferreira Coutinho Master and Doctorate in Computer Science (MDCC) Virtual UFC Institute Federal University of Ceara (UFC) Brazil Tel.: +55-85-8875-1977 E-mail: emanuel@virtual.ufc.br Flávio R. C. Sousa Teleinformatics Engineering Department (DETI) Federal University of Ceara (UFC) Brazil E-mail: flaviosousa@ufc.br Paulo A. L. Rego Master and Doctorate in Computer Science (MDCC) Federal University of Ceara (UFC) Brazil E-mail: pauloalr@ufc.br Danielo G. Gomes Teleinformatics Engineering Department (DETI) Federal University of Ceara (UFC) Brazil E-mail: danielo@ufc.br José N. de Souza Master and Doctorate in Computer Science (MDCC) Federal University of Ceara (UFC) Brazil E-mail: neuman@ufc.br 2 Emanuel Ferreira Coutinho et al. tions. To the best of our knowledge, this is the first study on cloud computing elasticity using a systematic review approach.
Architectural layout design optimization

This article presents an optimization model of the quantifiable aspects of architectural floorplan layout design, and a companion article presents a method for integrating mathematical optimization and subjective decision making during conceptual design. The model presented here offers a new approach to floorplan layout optimization that takes advantage of the efficiency of gradient-based algorithms, where appropriate, and uses evolutionary algorithms to make discrete decisions and do global search. Automated optimization results are comparable to other methods in this research area, and the new formulation makes it possible to integrate the power of human decision-making into the process.
CalFuzzer: An Extensible Active Testing Framework for Concurrent Programs

Active testing has recently been introduced to effectively test concurrent programs. Active testing works in two phases. It first uses predictive off-the-shelf static or dynamic program analyses to identify potential concurrency bugs, such as data races, deadlocks, and atomicity violations. In the second phase, active testing uses the reports from these predictive analyses to explicitly control the underlying scheduler of the concurrent program to accurately and quickly discover real concurrency bugs, if any, with very high probability and little overhead. In this paper, we present an extensible framework for active testing of Java programs. The framework currently implements three active testers based on data races, atomic blocks, and deadlocks.
A 110 nA Voltage Regulator System With Dynamic Bandwidth Boosting for RFID Systems

This paper describes a voltage regulator system for ultra-low-power RFID tags (also called passive tags) in a 0.15 mum analog CMOS technology. These tags derive their power supply from the incoming RF energy through rectification instead of from a battery. The regulator is functional with just 110 nA current. Owing to the huge variation of the rectified voltage (by as much as tens of volts), voltage limiters and clamps are employed at various points along the regulation path. A limiter at the rectifier output clamps the rectifier voltage to a narrower range of 1.4 V. A fine-regulator, then, regulates the supply voltage close to a bandgap reference value of 1.25 V. The key aspect of this regulator is the dynamic bandwidth boosting that takes place in the regulator by sensing the excess current that is bypassed in the limter (during periods of excess energy) and increasing its bias current and hence bandwidth, accordingly. A higher bandwidth is necessary for quick recovery from line transients due to the burst nature of RF transmission, with a larger energy burst requiring a higher bandwidth to settle quickly without large line transients. The challenge of compensating such a regulator across various load currents and RF energy levels is described in this paper
Points-to analysis for JavaScript

JavaScript is widely used by web developers and the complexity of JavaScript programs has increased over the last year. Therefore, the need for program analysis for JavaScript is evident. Points-to analysis for JavaScript is to determine the set of objects to which a reference variable or an object property may point. Points-to analysis for JavaScript is a basis for further program analyses for JavaScript. It has a wide range of applications in code optimization and software engineering tools. However, points-to analysis for JavaScript has not yet been developed.
 JavaScript has dynamic features such as the runtime modification of objects through addition of properties or updating of methods. We propose a points-to analysis for JavaScript which precisely handles the dynamic features of JavaScript. Our work is the first attempt to analyze the points-to behavior of JavaScript. We evaluate the analysis on a set of JavaScript programs. We also apply the analysis to a code optimization technique to show that the analysis can be practically useful.
Cyber-physical security of Wide-Area Monitoring, Protection and Control in a smart grid environment

Smart grid initiatives will produce a grid that is increasingly dependent on its cyber infrastructure in order to support the numerous power applications necessary to provide improved grid monitoring and control capabilities. However, recent findings documented in government reports and other literature, indicate the growing threat of cyber-based attacks in numbers and sophistication targeting the nation's electric grid and other critical infrastructures. Specifically, this paper discusses cyber-physical security of Wide-Area Monitoring, Protection and Control (WAMPAC) from a coordinated cyber attack perspective and introduces a game-theoretic approach to address the issue. Finally, the paper briefly describes how cyber-physical testbeds can be used to evaluate the security research and perform realistic attack-defense studies for smart grid type environments.
PHASE SHIFTED , ZERO VOLTAGE TRANSITION DESIGN CONSIDERATIONS and the UC 3875 PWM CONTROLLER BILL ANDREYCAK

This Application Note will highlight the design considerations incurred in a high frequency power supply using the Phase Shifted Resonant PWM control technique. An overview of this switching technique including comparisons to existing fixed frequency non-resonant and variable frequency Zero Voltage Switching is included. Numerous design equations and associated voltage, current and timing waveforms supporting this technique will be highlighted. A general purpose Phase Shifted converter design guide and procedure will be introduced to assist in weighing the various design tradeoffs. An experimental 500 Watt, 48 volt at 10.5 amp power supply design operating from a preregulated 400 volt DC input will be presented as an example. Considerations will be given to the details of the magnetic, power switching and control circuitry areas. A summary of comparative advantages, differences and tradeoffs to other conversion alternatives is included. UC3875 CONTROL CIRCUIT SCHEMATIC
Analysis and Design of Mixed-Mode Operation for Noninverting Buck–Boost DC–DC Converters

A noninverting buck-boost dc-dc converter can work in the buck, boost, or buck-boost mode, but it has been analyzed that operating in the buck-boost mode has the lowest efficiency. However, if the buck-boost mode is excluded, the converter may jump between the buck and boost modes when the input voltage approaches the output voltage. This transition region is called the mixed mode, and larger output voltage ripples are expectable. In this brief, the conditions for the converter to operate in the mixed mode are analyzed, including the impact of mismatches between ramp signals, and a ramp generator is designed accordingly. Moreover, a full-cycle current-sensing circuit is proposed, and it can effectively inhibit the switching noise on the sensed current signal. The proposed chip was fabricated by the 0.35-μm 2P4M 3.3-V/5-V mixed-signal polycide process. The maximal measured efficiency is 93.5%.