nils-herrmann/clean_scirepeval huggingface dataset:
A survey of power and energy efficient techniques for high performance numerical linear algebra operations

Power and energy Performance Power management Supercomputers Numerical linear algebra DVFS a b s t r a c t Extreme scale supercomputers available before the end of this decade are expected to have 100 million to 1 billion computing cores. The power and energy efficiency issue has become one of the primary concerns of extreme scale high performance scientific computing. This paper surveys the research on saving power and energy for numerical linear algebra algorithms in high performance scientific computing on supercomputers around the world. We first stress the significance of numerical linear algebra algorithms in high performance scientific computing nowadays, followed by a background introduction on widely used numerical linear algebra algorithms and software libraries and benchmarks. We summarize commonly deployed power management techniques for reducing power and energy consumption in high performance computing systems by presenting power and energy models and two fundamental types of power management techniques: static and dynamic. Further, we review the research on saving power and energy for high performance numerical linear algebra algorithms from four aspects: profiling, trading off performance , static saving, and dynamic saving, and summarize state-of-the-art techniques for achieving power and energy efficiency in each category individually. Finally, we discuss potential directions of future work and summarize the paper.
Accelerating MapReduce on a coupled CPU-GPU architecture

The work presented here is driven by two observations. First, heterogeneous architectures that integrate a CPU and a GPU on the same chip are emerging, and hold much promise for supporting power-efficient and scalable high performance computing. Second, MapReduce has emerged as a suitable framework for simplified parallel application development for many classes of applications, including data mining and machine learning applications that benefit from accelerators.
 This paper focuses on the challenge of scaling a MapReduce application using the CPU and GPU together in an integrated architecture. We develop different methods for dividing the work, which are the map-dividing scheme, where map tasks are divided between both devices, and the pipelining scheme, which pipelines the map and the reduce stages on different devices. We develop dynamic work distribution schemes for both the approaches. To achieve high load balance while keeping scheduling costs low, we use a runtime tuning method to adjust task block sizes for the map-dividing scheme. Our implementation of MapReduce is based on a continuous reduction method, which avoids the memory overheads of storing key-value pairs.
 We have evaluated the different design decisions using 5 popular MapReduce applications. For 4 of the applications, our system achieves 1.21 to 2.1 speedup over the better of the CPU-only and GPU-only versions. The speedups over a single CPU core execution range from 3.25 to 28.68. The runtime tuning method we have developed achieves very low load imbalance, while keeping scheduling overheads low. Though our current work is specific to MapReduce, many underlying ideas are also applicable towards intra-node acceleration of other applications on integrated CPU-GPU nodes.
Priors for people tracking from small training sets

We advocate the use of scaled Gaussian process latent variable models (SGPLVM) to learn prior models of 3D human pose for 3D people tracking. The SGPLVM simultaneously optimizes a low-dimensional embedding of the high-dimensional pose data and a density function that both gives higher probability to points close to training data and provides a nonlinear probabilistic mapping from the low-dimensional latent space to the full-dimensional pose space. The SGPLVM is a natural choice when only small amounts of training data are available. We demonstrate our approach with two distinct motions, golfing and walking. We show that the SGPLVM sufficiently constrains the problem such that tracking can be accomplished with straightforward deterministic optimization.
Watch What You Wear: Preliminary Forensic Analysis of Smart Watches

This work presents preliminary forensic analysis of two popular smart watches, the Samsung Gear 2 Neo and LG G. These wearable computing devices have the form factor of watches and sync with smart phones to display notifications, track footsteps and record voice messages. We posit that as smart watches are adopted by more users, the potential for them becoming a haven for digital evidence will increase thus providing utility for this preliminary work. In our work, we examined the forensic artifacts that are left on a Samsung Galaxy S4 Active phone that was used to sync with the Samsung Gear 2 Neo watch and the LG G watch. We further outline a methodology for physically acquiring data from the watches after gaining root access to them. Our results show that we can recover a swath of digital evidence directly form the watches when compared to the data on the phone that is synced with the watches. Furthermore, to root the LG G watch, the watch has to be reset to its factory settings which is alarming because the process may delete data of forensic relevance. Although this method is forensically intrusive, it may be used for acquiring data from already rooted LG watches. It is our observation that the data at the core of the functionality of at least the two tested smart watches, messages, health and fitness data, e-mails, contacts, events and notifications are accessible directly from the acquired images of the watches, which affirms our claim that the forensic value of evidence from smart watches is worthy of further study and should be investigated both at a high level and with greater specificity and granularity.
Web application security assessment by fault injection and behavior monitoring

As a large and complex application platform, the World Wide Web is capable of delivering a broad range of sophisticated applications. However, many Web applications go through rapid development phases with extremely short turnaround time, making it difficult to eliminate vulnerabilities. Here we analyze the design of Web application security assessment mechanisms in order to identify poor coding practices that render Web applications vulnerable to attacks such as SQL injection and cross-site scripting. We describe the use of a number of software-testing techniques (including dynamic analysis, black-box testing, fault injection, and behavior monitoring), and suggest mechanisms for applying these techniques to Web applications. Real-world situations are used to test a tool we named the Web Application Vulnerability and Error Scanner (WAVES, an open-source project available at http://waves.sourceforge.net) and to compare it with other tools. Our results show that WAVES is a feasible platform for assessing Web application security.
A New Approach to Design Circularly Polarized Beam-Steering Antenna Arrays Without Phase Shift Circuits

A new approach to generate beam steering for the circularly polarized (CP) antenna array without phase shift circuits is proposed. The proposed approach is a low cost one compared with those with phase shifters. It is found that in spherical coordinate system (<inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\theta $ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$\varphi $ </tex-math></inline-formula>), for any constant <inline-formula> <tex-math notation="LaTeX">$r$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\theta $ </tex-math></inline-formula>, as <inline-formula> <tex-math notation="LaTeX">$\varphi $ </tex-math></inline-formula> varies from 0 to <inline-formula> <tex-math notation="LaTeX">$2\pi $ </tex-math></inline-formula>, the phase of the CP antenna’s copolarized far field will progress linearly by <inline-formula> <tex-math notation="LaTeX">$2\pi $ </tex-math></inline-formula>, and the magnitude is constant. If a CP antenna is rotated around its own phase center by certain degrees, there is a phase difference between the copolarized electric far fields generated by the antenna before and after rotation. An <inline-formula> <tex-math notation="LaTeX">$N \times N$ </tex-math></inline-formula> array with such CP antennas elements is analyzed. The array can generate beam steering with different rotation angles of adjacent elements. The beam-steering mechanism is discussed from the orthogonal electric current elements and array perspective. Then, a <inline-formula> <tex-math notation="LaTeX">$4 \times 4$ </tex-math></inline-formula> planar spiral array is designed to verify the mechanism. The array has a good beam-steering characteristic within <inline-formula> <tex-math notation="LaTeX">$X$ </tex-math></inline-formula>-band. At the planes of <inline-formula> <tex-math notation="LaTeX">$\varphi = 0^{\circ }$ </tex-math></inline-formula>, 45°, and 90°, the mainlobe can be scanned from −25° to +24°, −36° to +35°, and −24° to +25°, respectively.
Stimuli-responsive nanocarriers for drug delivery.

Spurred by recent progress in materials chemistry and drug delivery, stimuli-responsive devices that deliver a drug in spatial-, temporal- and dosage-controlled fashions have become possible. Implementation of such devices requires the use of biocompatible materials that are susceptible to a specific physical incitement or that, in response to a specific stimulus, undergo a protonation, a hydrolytic cleavage or a (supra)molecular conformational change. In this Review, we discuss recent advances in the design of nanoscale stimuli-responsive systems that are able to control drug biodistribution in response to specific stimuli, either exogenous (variations in temperature, magnetic field, ultrasound intensity, light or electric pulses) or endogenous (changes in pH, enzyme concentration or redox gradients).
Deep learning for object identification in ROS-based mobile robots

In this paper, an open source robotic middleware ROS is applied to identify objects with a Raspberry Pi based mobile robot. Faster R-CNN algorithm is considered for enhanced deep learning. The capabilities of robot control and object detection are verified through experimental validations. Based on a low-cost Raspberry Pi control kernel, an easy-to-use interface is developed to integrate front-end and back-end applications. Firstly some ROS packages for the mobile robot are needed to be designed. Then the captured environment information will be provided for objective detection using GPU-accelerated computing. In this paper, Kinect sensor is used to capture images and the deep learning algorithm is implemented based on ROS middleware. All previous mentioned function modules are contained in a cloud service.
Intrusion Detection System using K-means , PSO with SVM Classifier : A Survey

Intrusion detection is a process of identifying the Attacks. The main aim of IDS is to identify the Normal and Intrusive activities. In recent years, many researchers are using data mining techniques for building IDS. Here we propose a new approach using data mining technique such as SVM and Particle swarm optimization for attaining higher detection rate. The propose technique has major steps: Preprocessing, Training using PSO, clustering using K-means to generate different training subsets. Then based on the subsequent training subsets a vector for SVM classification is formed and in the end, classification using PSO is performed to detect Intrusion has happened or not. This paper contains summarization study and identification of the drawbacks of formerly surveyed works. Intrusion detection system; Neuro-fuzzy; Support Vector Machine (SVM); PSO; K-means
Reprint of: Pyrolysis technologies for municipal solid waste: a review.

Pyrolysis has been examined as an attractive alternative to incineration for municipal solid waste (MSW) disposal that allows energy and resource recovery; however, it has seldom been applied independently with the output of pyrolysis products as end products. This review addresses the state-of-the-art of MSW pyrolysis in regards to its technologies and reactors, products and environmental impacts. In this review, first, the influence of important operating parameters such as final temperature, heating rate (HR) and residence time in the reaction zone on the pyrolysis behaviours and products is reviewed; then the pyrolysis technologies and reactors adopted in literatures and scale-up plants are evaluated. Third, the yields and main properties of the pyrolytic products from individual MSW components, refuse-derived fuel (RDF) made from MSW, and MSW are summarised. In the fourth section, in addition to emissions from pyrolysis processes, such as HCl, SO2 and NH3, contaminants in the products, including PCDD/F and heavy metals, are also reviewed, and available measures for improving the environmental impacts of pyrolysis are surveyed. It can be concluded that the single pyrolysis process is an effective waste-to-energy convertor but is not a guaranteed clean solution for MSW disposal. Based on this information, the prospects of applying pyrolysis technologies to dealing with MSW are evaluated and suggested.
On the Definition of Cyber-Physical Resilience in Power Systems

Modern society relies heavily upon complex and widespread electric grids. In recent years, advanced sensors, intelligent automation, communication networks, and information technologies (IT) have been integrated into the electric grid to enhance its performance and efficiency. Integrating these new technologies has resulted in more interconnections and interdependencies between the physical and cyber components of the grid. Natural disasters and man-made perturbations have begun to threaten grid integrity more often. Urban infrastructure networks are highly reliant on the electric grid and consequently, the vulnerability of infrastructure networks to electric grid outages is becoming a major global concern. In order to minimize the economic, social, and political impacts of large-scale power system outages, the grid must be resilient in addition of being robust and reliable. The concept of a power system’s cyber-physical resilience centers around maintaining critical functionality of the system backbone in the presence of unexpected extreme disturbances. Resilience is a multidimensional property of the electric grid; it requires managing disturbances originating from physical component failures, cyber component malfunctions, and human attacks. In the electric grid community, there is not a clear and universally accepted definition of cyber-physical resilience. This paper focuses on the definition of resilience for the electric grid and reviews key concepts related to system resilience. This paper aims to advance the field not only by adding cyber-physical resilience concepts to power systems vocabulary, but also by proposing a new way of thinking about grid operation with unexpected extreme disturbances and hazards and leveraging distributed energy resources. The concepts of service availability and quality are not new, but many recognize the need of resilience in maintaining essential services to critical loads, for example to allow home refrigerators to operate for food conservation in the aftermath of a hurricane landfall. By providing a comprehensive definition of power system resilience, this paper paves the way for creating appropriate and effective resilience standards and metrics. & 2015
Equivalent circuit modeling of electro-magnetic pulse generator for typical immunity simulation

The equivalent circuits modeling method is developed for the EMP(Electromagnetic pulse) generators of the equipment-level immunity test. On the double-exponential function of EMP waveform, the corresponding circuit structure is introduced, and the calculation method is given to obtain the circuit RLC parameters. For the generators of EFT(Electrical Fast Transient/Burst), surge combination wave, and ESD(Electro-Static Discharge), the equivalent circuits and components parameters are proposed. Finally, simulation results validate the proposed method and circuit models.
How Maps Work - Representation, Visualization, and Design

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Indoor Navigation Validation Framework for Visually Impaired Users

In this paper, we introduce the first validation framework of an indoor navigation system for blind and visually impaired (BVI) users, which is a significant step toward the development of cost effective indoor way-finding solutions for BVI users. The BVI users require detailed landmark-based navigation instructions that will help them arrive at the chosen destination independently. These users will interact with the navigation instructions on a smartphone using an accessible user interface. The validation framework includes the following three main components: 1) virtual reality-based simulation that simulates a BVI user traversing and interacting with the physical environment, developed using Unity game engine; 2) generation of action codes that emulate the avatar movement in the virtual environment, developed using a natural language processing parser of the navigation instructions; and 3) accessible user interface, which enables the user to access the navigation instructions, developed using Sikuli script library. We introduce a case study that illustrates the use of the validation tool using PERCEPT system. It is our strong belief that the validation framework we provide in this paper will encourage other developers to invent indoor navigation systems for BVI users. In addition, we would like to mention that this tool is the first step of validating an indoor navigation system and should be followed by trials with human subjects.
Locating faults through automated predicate switching

Typically debugging begins when during a program execution a point is reached at which an obviously incorrect value is observed. A general and powerful approach to automated debugging can be based upon identifying modifications to the program state that will bring the execution to a successful conclusion. However, searching for arbitrary changes to the program state is difficult due to the extremely large search space. In this paper we demonstrate that by forcibly switching a predicate's outcome at runtime and altering the control flow, the program state can not only be inexpensively modified, but in addition it is often possible to bring the program execution to a successful completion (i.e., program produces the desired output). By examining the switched predicate, also called the critical predicate, the cause of the bug can then be identified. Since the outcome of a branch can only be either true or false, the number of modified states resulting by predicate switching is far less than those possible through arbitrary state changes. Thus, it is possible to automatically search through modified states to find one that leads to the correct output. We have developed an implementation based upon dynamic instrumentation to perform this search through program re-execution -- the program is executed from the beginning and a predicate's outcome is switched to produce the desired change in control flow. To evaluate our approach, we tried our technique on several reported bugs for a number of UNIX utility programs. Our technique was found to be practical (i.e., acceptable in time taken) and effective (i.e., we were able to automatically identify critical predicates). Moreover we show that bidirectional dynamic slices of critical predicates capture the faulty code.
Somatization vs . Psychologization of Emotional Distress : A Paradigmatic Example for Cultural Psychopathology

This paper describes the developing area of cultural psychopathology, an interdisciplinary field of study focusing on the ways in which cultural factors contribute to the experience and expression of psychological distress. We begin by outlining two approaches, often competing, in order to provide a background to some of the issues that complicate the field. The main section of the paper is devoted to a discussion of depression in Chinese culture as an example of the types of questions that can be studied. Here, we start with a review of the epidemiological literature, suggesting low rates of depression in China, and move to the most commonly cited explanation, namely that Chinese individuals with depression present this distress in a physical way. Different explanations of this phenomenon, known as somatization, are explored and reconceptualized according to an increasingly important model for cross-cultural psychologists: the cultural constitution of the self. We close by discussing some of the contributions, both theoretical and methodological, that can be made by cross-cultural psychologists to researchers in cultural psychopathology.  https://scholarworks.gvsu.edu/orpc/vol10/iss2/3
DeepMag: Sniffing Mobile Apps in Magnetic Field through Deep Convolutional Neural Networks

In this paper, we report a newfound vulnerability on smartphones due to the malicious use of unsupervised sensor data. We demonstrate that an attacker can train deep Convolutional Neural Networks (CNN) by using magnetometer or orientation data to effectively infer the Apps and their usage information on a smartphone with an accuracy of over 80%. Furthermore, we show that such attacks can become even worse if sophisticated attackers exploit motion sensors to cluster the magnetometer or orientation data, improving the accuracy to as high as 98%. To mitigate such attacks, we propose a noise injection scheme that can effectively reduce the App sniffing accuracy to only 15% and at the same time has negligible effect on benign Apps.
Decentralized Control for Parallel Operation of Distributed Generation Inverters Using Resistive Output Impedance

In this paper, a novel wireless load-sharing controller for islanding parallel inverters in an ac-distributed system is proposed. This paper explores the resistive output impedance of the parallel-connected inverters in an island microgrid. The control loops are devised and analyzed, taking into account the special nature of a low-voltage microgrid, in which the line impedance is mainly resistive and the distance between the inverters makes the control intercommunication between them difficult. In contrast with the conventional droop-control method, the proposed controller uses resistive output impedance, and as a result, a different control law is obtained. The controller is implemented by using a digital signal processor board, which only uses local measurements of the unit, thus increasing the modularity, reliability, and flexibility of the distributed system. Experimental results are provided from two 6-kVA inverters connected in parallel, showing the features of the proposed wireless control