nils-herrmann/clean_scirepeval huggingface dataset:
Energy-Efficient Transmission for Beamforming in Wireless Sensor Networks

Energy conservation is essential in wireless sensor networks (WSNs) because of limited energy in batteries. Collaborative beamforming uses multiple transmitters to form antenna arrays; the electromagnetic waves from these antenna arrays can create constructive interferences at the receiver and increase the transmission distance. Each transmitter can use lower power and save energy, since the energy consumption is spread over multiple transmitters. However, if the same nodes are always used for collaborative beamforming, these nodes would deplete their energy much sooner and this sensing area will no longer be monitored. To avoid this situation, energy consumption for collaborative beamforming needs to be balanced over the whole network by assigning the transmitters in turns. The transmitters in each round are selected by a scheduler and the energy carried in each node is balanced to increase the number of transmissions. We define the lifetime of a network as the number of transmissions until a certain percentage of the nodes depletes their energy. This paper proposes an algorithm to calculate energy-efficient schedules based on the remaining energy and the phase differences of their signals arriving at the receiver. Compared with an existing algorithm, our algorithm can extend the network lifetime by more than 60%.
Voxel-based global illumination

Computing a global illumination solution in real-time is still an open problem. We introduce Voxel-based Global Illumination (VGI), a scalable technique that ranges from real-time near-field illumination to interactive global illumination solutions. To obtain a voxelized scene representation, we introduce a new atlas-based boundary voxelization algorithm and an extension to a fast ray-voxel intersection test. Similar to screen-space illumination methods, VGI is independent of the scene complexity. Using voxels for indirect visibility enables real-time near-field illumination without the screen-space artifacts of alternative methods. Furthermore, VGI can be extended to interactive, multi-bounce global illumination solutions like path tracing and instant radiosity.
A new evolutionary system for evolving artificial neural networks

This paper presents a new evolutionary system, i.e., EPNet, for evolving artificial neural networks (ANNs). The evolutionary algorithm used in EPNet is based on Fogel's evolutionary programming (EP). Unlike most previous studies on evolving ANN's, this paper puts its emphasis on evolving ANN's behaviors. Five mutation operators proposed in EPNet reflect such an emphasis on evolving behaviors. Close behavioral links between parents and their offspring are maintained by various mutations, such as partial training and node splitting. EPNet evolves ANN's architectures and connection weights (including biases) simultaneously in order to reduce the noise in fitness evaluation. The parsimony of evolved ANN's is encouraged by preferring node/connection deletion to addition. EPNet has been tested on a number of benchmark problems in machine learning and ANNs, such as the parity problem, the medical diagnosis problems, the Australian credit card assessment problem, and the Mackey-Glass time series prediction problem. The experimental results show that EPNet can produce very compact ANNs with good generalization ability in comparison with other algorithms.
A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data

One of the most important issues in machine learning is whether one can improve the performance of a supervised learning algorithm by including unlabeled data. Methods that use both labeled and unlabeled data are generally referred to as semi-supervised learning. Although a number of such methods are proposed, at the current stage, we still don’t have a complete understanding of their effectiveness. This paper investigates a closely related problem, which leads to a novel approach to semi-supervised learning. Specifically we consider learning predictive structures on hypothesis spaces (that is, what kind of classifiers have good predictive power) from multiple learning tasks. We present a general framework in which the structural learning problem can be formulated and analyzed theoretically, and relate it to learning with unlabeled data. Under this framework, algorithms for structural learning will be proposed, and computational issues will be investigated. Experiments will be given to demonstrate the effectiveness of the proposed algorithms in the semi-supervised learning setting.
The Blurring Boundaries Of Work-Related And Personal Media Use: A Grounded Theory Study On The Employee's Perspective

The ongoing consumerization of information technology (IT) demands to rethink the traditional paradigms of media use at the workplace. Past research has focused on the use of company IT resources for personal purposes (e.g., ‘cyberloafing’) and primarily emphasized the adverse effects. This study takes a wider perspective and includes the use of personal IT resources for company purposes as well as other mixed forms of personal and work-related media use. We conducted interviews with 14 employees in 5 different firms and used a grounded theory approach to explore the blurring of boundaries between work and private life discussed in the wider social science literature. Our study demonstrates different attitudes of employees towards work-life blurring and suggests that social and mobile IT has a catalyst role in this process. We contribute to the past literature by providing a conceptual model for the context, the conditions and the consequences of this phenomenon. Practical implications are discussed.
Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.
Modeling Propagation Dynamics and Developing Optimized Countermeasures for Rumor Spreading in Online Social Networks

The spread of rumors in Online Social Networks (OSNs) poses great challenges to the social peace and public order. It is imperative to model propagation dynamics of rumors and develop corresponding countermeasures. Most of the existing works either overlook the heterogeneity of social networks or do not consider the cost of countermeasures. Motivated by these issues, this paper proposes a heterogeneous network based epidemic model that incorporates both the network heterogeneity and various countermeasures. Through analyzing the existence and stability of equilibrium solutions of the proposed ODE (Ordinary Differential Equation) system, the critical conditions that determine whether a rumor continuously propagates or becomes extinct are derived. Moreover, we concern about the cost of the main two types of countermeasures, i.e., Blocking rumors at influential users and spreading truth to clarify rumors. Employing the Pontryagin's maximum principle, we obtain the optimized countermeasures that ensures a rumor can become extinct at the end of an expected time period with lowest cost. Both the critical conditions and the optimized countermeasures provide a real-time decision reference to restrain the rumor spreading. Experiments based on Digg2009 dataset are conducted to evaluate the effectiveness of the proposed dynamic model and the efficiency of the optimized countermeasures.
Risk Aversion and Expected-Utility Theory : A Calibration Theorem

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A Trainable Document Summarizer

s by the selection of sentences. American Documentation, 12(2):139–143, April 1961.  U. Reimer and U. Hahn. Text condensationas knowledge base abstraction. In   G. Salton, J. Alan, and C. Buckley. Approaches to passage retrieval in full text information systems. In Proceedings of SIGIR’93, pages 49–58, June 1993.  G. Salton, J. Allan, C. Buckley, and A. Singhal. Automatic analysis, theme generation, and summarization of machinereadable texts. Science, 264(3):1421–1426, June 1994.  C. Schwarz. Content based text handling. Information Processing & Management, 26(2):219–226, 1990.  E. F. Skorokhod’ko. Adaptive method of automatic abstracting and indexing. In IFIP Congress,Ljubljana, Yugoslavia 71, pages 1179–1182. North Holland, 1972.  J. I. Tait. Generating summaries using a script-based language analyzer. In L. Steels and J.A. Campbell, editors, Progress in Artificial Intelligence, pages 312–318. Ellis Horwood, 1985.  L. C. Tong and S. L. Tan. A statistical approach to automatic text extraction. Asian  Direct Match If a summary sentence is identical to a sentence in the original, or has essentially the same content, the match is defined as a direct match. An example match that is not exact but considered to convey the same content is shown below: Manual: This paper identifies the desirable features of an ideal multisensor gas monitor and lists the different models currently available.  The present part lists the desirable features and the different models of portable, multisensor gas monitors currently available. 9.0.2 Direct Join If the content of the manual sentence is represented by two or more sentences in the original, the latter sentences are noted as joins. For example: Manual: In California, Caltrans has a rolling pavement management program, with continuouscollection of data with the aim of identifying roads that require more monitoring and repair. Original (1): Rather than conducting biennial surveys, Caltrans now has a rolling pavement-management program, with data collected continuously. Original (2): The idea is to pinpoint the roads that may need more or less monitoring and repair. 9.0.3 Incomplete Matches A sentence in the original document is labelled as an incomplete match if it only partially covers the content of a manual summary sentence, or if a direct match is not clear. It can occur in the context of a single sentence or a join. The following exemplifies an incomplete single sentence match: Manual: Intergranular fracture of polycrystalline Ni3Alwas studied at 77K. Original: Before discussing the observeddeformation and fracture behavior of polycrystalline Ni3Al at 77K in terms of the kinetics of the proposed environmental embrittlement mechanism, we should ask whether the low temperature by itself significantly affects the brittleness of Ni3Al.
An Autonomous Multi-UAV System for Search and Rescue

This paper proposes and evaluates a modular architecture of an autonomous unmanned aerial vehicle (UAV) system for search and rescue missions. Multiple multicopters are coordinated using a distributed control system. The system is implemented in the Robot Operating System (ROS) and is capable of providing a real-time video stream from a UAV to one or more base stations using a wireless communications infrastructure. The system supports a heterogeneous set of UAVs and camera sensors. If necessary, an operator can interfere and reduce the autonomy. The system has been tested in an outdoor mission serving as a proof of concept. Some insights from these tests are described in the paper.
Consumers ’ Perceptions , Attitudes and Purchase Intention towards Private Label Food Products in Malaysia

The onset of inflation drives the rising of living cost. The rise of private label market provides an alternative selection for consumers during purchasing. There is very limited research regarding private label food product in Malaysia. This research focused on factors that may influence consumers’ intention to purchase private label food product in a state in Malaysia. Factors examined are extrinsic factors which include ‘perceived price’, ‘packaging’, ‘advertisement’ and ‘store image’; intrinsic factors (i.e. ‘perceived quality’, ‘perceived risk’ and ‘perceived value’) and consumers’ attitudes (in terms of trust, familiarity and perceived economic situation). All responses were collected by using questionnaire through convenience sampling (n=100). Data was analyzed to obtain descriptive statistics, comparing mean analysis (i.e. independent t-test and ANOVA) and other analyses (i.e. correlation analysis and multiple linear regressions). Result shows that ‘perceived value’ becomes prominent in consumers’ purchasing of private label brand food product, followed by other factors. Almost all independent variables are associated with purchase intention towards private label brand food products. The most significant factor that influencing consumers’ purchase intention towards private label food products are ‘consumers’ attitude’ and ‘perceived price’. Consumers’ past purchasing experience with the private label food products may also influence their perception towards price, packaging, store image and trust of those products. This study adds new knowledge regarding public purchasing behavior towards private label product. Retailers are anticipated to better understand the factors influencing the purchase and re-purchase intention of private label food products which could better improve the standard of private label food products in the local market.
Correlation mapping method for generating microcirculation morphology from optical coherence tomography (OCT) intensity images.

Standard optical coherence tomography (OCT) in combination with software tools can be harnessed to generate vascular maps in vivo. In this study we have successfully combined a software algorithm based on correlation statistic to reveal microcirculation morphology on OCT intensity images of a mouse brain in vivo captured trans-cranially and through a cranial window. We were able to estimate vessel geometry at bifurcation as well as along vessel segments down-to mean diameters of about 24 μm. Our technique has potential applications in cardiovascular-related parameter measurements such as volumetric flow as well as in assessing vascular density of normal and diseased tissue.
Harnessing the power of FPGAs using altera's OpenCL compiler

In recent years, Field-Programmable Gate Arrays have become extremely powerful computational platforms that can efficiently solve many complex problems. The most modern FPGAs comprise effectively millions of programmable elements, signal processing elements and high-speed interfaces, all of which are necessary to deliver a complete solution. The power of FPGAs is unlocked via low-level programming languages such as VHDL and Verilog, which allow designers to explicitly specify the behavior of each programmable element. While these languages provide a means to create highly efficient logic circuits, they are akin to "assembly language" programming for modern processors. This is a serious limiting factor for both productivity and the adoption of FPGAs on a wider scale. In this talk, we use the OpenCL language to explore techniques that allow us to program FPGAs at a level of abstraction closer to traditional software-centric approaches. OpenCL is an industry standard parallel language based on 'C' that offers numerous advantages that enable designers to take full advantage of the capabilities offered by FPGAs, while providing a high-level design entry language that is familiar to a wide range of programmers.
 To demonstrate the advantages a high-level programming language can offer, we demonstrate how to use Altera's OpenCL Compiler on a set of case studies. The first application is single-precision general-element matrix multiplication (SGEMM). It is an example of a highly-parallel algorithm for which an efficient circuit structures are well known. We show how this application can be implemented in OpenCL and how the high-level description can be optimized to generate the most efficient circuit in hardware. The second application is a Fast Fourier Transform (FFT), which is a classical FPGA benchmark that is known to have a good implementation on FPGAs. We show how we can implement the FFT algorithm, while exploring the many different possible architectural choices that lead to an optimized implementation for a given FPGA. Finally, we discuss a Monte-Carlo Black-Scholes simulation, which demonstrates the computational power of FPGAs. We describe how a random number generator in conjunction with computationally intensive operations can be harnessed on an FPGA to generate a high-speed benchmark, which also consumes far less power than the same benchmark running on a comparable GPU. We conclude the tutorial with a set of live demonstrations.
 Through this tutorial we show the benefits high-level languages offer for system-level design and productivity. In particular, Altera's OpenCL compiler is shown to enable high-performance application design that fully utilizes capabilities of modern FPGAs.
Acceptance of homegrown enterprise resource planning (ERP) systems in Ethiopia

In the current competitive global market, organizations are implementing information and communication technology (ICT) that could add value to their products, processes, and satisfaction of their users. The adoption, implementation and use of homegrown enterprise resource planning (ERP) systems is one of these mechanisms being globally used for recording, processing, storing, and exchanging organizational information anytime anywhere. Although organizations have been utilizing ERP systems, the acceptance of homegrown ERP systems is given less attention as compared to commercial off-the shelf (COTS) software. Hence, this research studied factors that determine acceptance of homegrown ERP through the extension of unified theory of acceptance and use of technology (UTAUT) model. The finding revealed that performance expectancy, effort expectancy, social influence, competitive advantage, cost effectiveness, and facilitations functions are determinants of homegrown ERP system acceptance in Ethiopia. Moreover, experience and voluntariness are found to be significant moderators of the study.
Automatic detection of phone-level mispronunciation for language learning

We are interested in automatically detecting specific phone segments that have been mispronounced by a nonnative student of a foreign language. The phone-level information allows a language instruction system to provide the student with feedback about specific pronunciation mistakes. Two approaches were evaluated; in the first approach, log-posterior probability-based scores  are computed for each phone segment. These probabilities are based on acoustic models of native speech. The second approach uses a phonetically labeled nonnative speech database to train two different acoustic models for each phone: one model is trained with the acceptable, or correct native-like pronunciations, while the other model is trained with the incorrect, strongly nonnative pronunciations. For each phone segment, a log-likelihood ratio score is computed using the incorrect and correct pronunciation models. Either type of score is compared with a phone dependent threshold to detect a mispronunciation. Performance of both approaches was evaluated in a phonetically transcribed database of 130,000 phones uttered in continuous speech sentences by 206 nonnative speakers.
ZIGZAG: An Efficient Peer-to-Peer Scheme for Media Streaming

We design a peer-to-peer technique called ZIGZAG for single-source media streaming. ZIGZAG allows the media server to distribute content to many clients by organizing them into an appropriate tree rooted at the server. This applicationlayer multicast tree has a height logarithmic with the number of clients and a node degree bounded by a constant. This helps reduce the number of processing hops on the delivery path to a client while avoiding network bottleneck. Consequently, the end-to-end delay is kept small. Although one could build a tree satisfying such properties easily, an efficient control protocol between the nodes must be in place to maintain the tree under the effects of network dynamics and unpredictable client behaviors. ZIGZAG handles such situations gracefully requiring a constant amortized control overhead. Especially, failure recovery can be done regionally with little impact on the existing clients and mostly no burden on the server.
Evaluation of supply chain structures through modularization and postponement

This paper introduces a conceptual framework for evaluating dierent supply chain structures in the context of modularization and postponement. In our analysis, modularization is linked to inbound logistics as the combination of dierent components (or modules) allow for the assembly of the ®nal product. Postponement, however, corresponds with the outbound logistics since it is through the distribution function that customers' speci®c demand is satis®ed. Given this perspective, we introduce a taxonomy and develop a corresponding framework for the characterization of four supply chain structures, de®ned according to the combined levels of modularization and postponement: Rigid, Postponed, Modularized and Flexible. We also illustrate the applicability of the resulting framework through quantifying the total cost dierential for utilizing a particular supply chain structure. By quantifying the total cost for employing a particular supply chain structure we can numerically illustrate structural results that allow for an objective comparison among them. As such, our ®ndings substantiate the empirical evidence that vertical integration along the supply chain is not always desirable. A point of emphasis in this paper is the notion that ®rms may be better o making combined modularization (outsourcing) and postponement decisions as opposed to separate ones (as they currently do). This also suggests that modularization and postponement decisions need not be independent and that their joint consideration extends operational advantages worthy of contemplation. Ó 2000 Elsevier Science B.V. All rights reserved.