nils-herrmann/clean_scirepeval huggingface dataset:
Dynamic Software Product Line Engineering: A Reference Framework

Runtime adaptive systems are able to dynamically transform their internal structure, and hence their behavior, in response to internal or external changes. Such transformations provide the basis for new functionalities or improvements of the non-functional properties that match operational requirements and standards. Software Product Line Engineering (SPLE) has introduced several models and mechanisms for variability modeling and management. Dynamic software product lines (DSPL) engineering exploits the knowledge acquired in SPLE to develop systems that can be context-aware, post-deployment recon ̄gurable, or runtime adaptive. This paper focuses on DSPL engineering approaches for developing runtime adaptive systems and proposes a framework for classifying and comparing these approaches from two distinct perspectives: adaptation properties and adaptation realization. These two perspectives are linked together by a series of guidelines that help to select a suitable adaptation realization approach based on desired adaptation types.
In-Vehicle Network Attacks and Countermeasures: Challenges and Future Directions

The emergence of in-vehicle networks, which are composed of controller area network (CAN) buses and a great number of ECUs, significantly reduces the difficulty of vehicle designing, repairing and refitting. While owing to the intrinsic vulnerabilities of in-vehicle networks and the increasingly rich interfaces to connect in-vehicle networks to the outside, adversarial attacks can be easily implemented on in-vehicle networks. Such attacks cause serious threats to automobile security and drivers� privacy. In light of this, we provide in this article a detailed guidance, explain the basic concepts, introduce the vulnerabilities of in-vehicle networks, and summarize the attacking methodologies. We also provide countermeasures for in-vehicle networks and point out challenges and future directions.
DoS Attacks Analysis and Improvement in DTLS Protocol for Internet of Things

The main contribution in this paper is to improve the weakness of cookies exchange in the handshake process in order to counter DoS attacks. The enhanced protocol is performed on Cooja simulator in Contiki operating system for the Internet of Things, and compared with the original DTLS. The simulation results lead to better performance of the proposed protocol in terms of handshake time processing, and energy consumption. The proposed enhanced DTLS protocol is analyzed through the AVISPA tool. The formal modelling analysis using the AVISPA tool has validated the security of the proposed DTLS authentication model against external attacks such as DoS, and ensures the important properties related to a communication security protocol, which is the authentication integrity, confidentiality.
Verification , Validation , and Predictive Capability in Computational Engineering and Physics

Developers of computer codes, analysts who use the codes, and decision makers who rely on the results of the analyses face a critical question: How should confidence in modeling and simulation be critically assessed? Verification and validation (V&V) of computational simulations are the primary methods for building and quantifying this confidence. Briefly, verification is the assessment of the accuracy of the solution to a computational model. Validation is the assessment of the accuracy of a computational simulation by comparison with experimental data. In verification, the relationship of the simulation to the real world is not an issue. In validation, the relationship between computation and the real world, i.e., experimental data, is the issue.
An Empirical Examination of the Effects of Web Personalization at Different Stages of Decision-Making

Personalization agents are incorporated in many websites to tailor content and interfaces for individual users. But in contrast to the proliferation of personalized web services worldwide, empirical research studying the effects of web personalization is scant. How does exposure to personalized offers affect subsequent product consideration and choice outcome? Drawing on the literature in HCI and consumer behavior, this research examines the effects of web personalization on users’ information processing and expectations through different decision-making stages. A study using a personalized ring-tone download website was conducted. Our findings provide empirical evidence of the effects of web personalization. In particular, when consumers are forming their consideration sets, the agents have the capacity to help them discover new products and generate demand for unfamiliar products. Once the users have arrived at their choice, however, the persuasive effects from the personalization agent diminish. These results establish that adaptive role of personalization agents at different stages of decision-making.
Cell-level Production-Logistics Synchronization for multi-variety and small-batch Production: A step toward industry 4.0

Industry 4.0 is a strategy that has been proposed to satisfy the requirements of the individual customer, while the factory will become the Smart Factory. In Smart Factory, enterprises will use device-level flexible production system to deal with the enormous variety of customer orders. However, nowadays which called Industry 3.X stage in this paper, customer requirements are still in the order customization stage, on the other hand, enterprises have to deal with the diversified and small-batch orders with Cell-level static collaborative production systems, which is not enough. Under Industry 3.X stage, in this paper, a cell-level Production-Logistics Synchronized (PLS) management approach for multi-variety and small-batch Production putted forward to solve the problem that it is difficult to deal with the dynamic problem effectively with limited resource in the static cooperative process.
Using 4D modelling in a university-museum research partnership

In the field of virtual heritage, scientific 4D modelling brings together interdisciplinary expertise in an iterative process to create and revise digital models that also reflect the passage of time. Our work focusses on making this type of model serve the needs of museologists by linking various documentary sources (both text-based and iconographic) and testimonials to the 4D model. Our case study involves a former industrial site. Over the decades, various buildings in this old factory complex have been the subject of construction, demolition and redevelopment. Under a university-museum research partnership, our 4D model will be part of an interactive digital environment designed for a museum exhibit. Our goal is to maximize the flexibility of the model, which was based on i) research to find new documentary sources, ii) oral testimonies to complete the documentary record and iii) testing to make the user experience more cognitively enriching. This approach has strengthened the partnership between the museum and the university, made university research available to a wider audience and provided a modest museum with a new tool.
The HEXACO Honesty-Humility, Agreeableness, and Emotionality factors: a review of research and theory.

We review research and theory on the HEXACO personality dimensions of Honesty-Humility (H), Agreeableness (A), and Emotionality (E), with particular attention to the following topics: (1) the origins of the HEXACO model in lexical studies of personality structure, and the content of the H, A, and E factors in those studies; (2) the operationalization of the H, A, and E factors in the HEXACO Personality Inventory-Revised; (3) the construct validity of self-reports on scales measuring the H factor; (4) the theoretical distinction between H and A; (5) similarity and assumed similarity between social partners in personality, with a focus on H and A; (6) the extent to which H (and A and E) variance is represented in instruments assessing the "Five-Factor Model" of personality; and (7) the relative validity of scales assessing the HEXACO and Five-Factor Model dimensions in predicting criteria conceptually relevant to H, A, and E.
Non linear hybrid watermarking for High Dynamic Range images

The present work explores the use of a specific method, called non linear hybrid watermarking to watermark High Dynamic Range (HDR) images. The non linear hybrid technique combines both additive and multiplicative watermark embedding and is based on a square root embedding equation. We evaluate the robustness and objective quality of HDR tone mapped watermarked images on two different HDR databases. The experimentations show that the watermark is imperceptible and successfully survives tone mapping attack.
Home, habits, and energy: examining domestic interactions and energy consumption

This paper presents findings from a qualitative study of people's everyday interactions with energy-consuming products and systems in the home. Initial results from a large online survey are also considered. This research focuses not only on "conservation behavior" but importantly investigates interactions with technology that may be characterized as "normal consumption" or "over-consumption." A novel vocabulary for analyzing and designing energy-conserving interactions is proposed based on our findings, including: cutting, trimming, switching, upgrading, and shifting. Using the proposed vocabulary, and informed by theoretical developments from various literatures, this paper demonstrates ways in which everyday interactions with technology in the home are performed without conscious consideration of energy consumption but rather are unconscious, habitual, and irrational. Implications for the design of energy-conserving interactions with technology and broader challenges for HCI research are proposed.
Accelerating Online CP Decompositions for Higher Order Tensors

Tensors are a natural representation for multidimensional data. In recent years, CANDECOMP/PARAFAC (CP) decomposition, one of the most popular tools for analyzing multi-way data, has been extensively studied and widely applied. However, today's datasets are often dynamically changing over time. Tracking the CP decomposition for such dynamic tensors is a crucial but challenging task, due to the large scale of the tensor and the velocity of new data arriving. Traditional techniques, such as Alternating Least Squares (ALS), cannot be directly applied to this problem because of their poor scalability in terms of time and memory. Additionally, existing online approaches have only partially addressed this problem and can only be deployed on third-order tensors. To fill this gap, we propose an efficient online algorithm that can incrementally track the CP decompositions of dynamic tensors with an arbitrary number of dimensions. In terms of effectiveness, our algorithm demonstrates comparable results with the most accurate algorithm, ALS, whilst being computationally much more efficient. Specifically, on small and moderate datasets, our approach is tens to hundreds of times faster than ALS, while for large-scale datasets, the speedup can be more than 3,000 times. Compared to other state-of-the-art online approaches, our method shows not only significantly better decomposition quality, but also better performance in terms of stability, efficiency and scalability.
Efficient Fuzz Testing Leveraging Input, Code, and Execution

Any kind of smart testing technique must be very efficient to be competitive with random fuzz testing. State-of the-art test generators are largely inferior to random testing in real world applications. This work proposes to gather and evaluate lightweight analyses that can enable the creation of an efficient and sufficiently effective analysis-assisted fuzz tester. The analyses shall leverage information sources apart from the program under test itself, such as e.g. descriptions of the targeted input format in the form of extended context-free grammars, or hardware counters. As the main contributions, an efficient framework for building fuzzers around given analyses will be created, and with its help analyses will be identified and categorized according to their performance.
Principles and practice in reporting structural equation analyses.

Principles for reporting analyses using structural equation modeling are reviewed, with the goal of supplying readers with complete and accurate information. It is recommended that every report give a detailed justification of the model used, along with plausible alternatives and an account of identifiability. Nonnormality and missing data problems should also be addressed. A complete set of parameters and their standard errors is desirable, and it will often be convenient to supply the correlation matrix and discrepancies, as well as goodness-of-fit indices, so that readers can exercise independent critical judgment. A survey of fairly representative studies compares recent practice with the principles of reporting recommended here.
Machine Learning for Networking: Workflow, Advances and Opportunities

Recently, machine learning has been used in every possible field to leverage its amazing power. For a long time, the networking and distributed computing system is the key infrastructure to provide efficient computational resources for machine learning. Networking itself can also benefit from this promising technology. This article focuses on the application of MLN, which can not only help solve the intractable old network questions but also stimulate new network applications. In this article, we summarize the basic workflow to explain how to apply machine learning technology in the networking domain. Then we provide a selective survey of the latest representative advances with explanations of their design principles and benefits. These advances are divided into several network design objectives and the detailed information of how they perform in each step of MLN workflow is presented. Finally, we shed light on the new opportunities in networking design and community building of this new inter-discipline. Our goal is to provide a broad research guideline on networking with machine learning to help motivate researchers to develop innovative algorithms, standards and frameworks.
Face Recognition with Local Binary Patterns, Spatial Pyramid Histograms and Naive Bayes Nearest Neighbor Classification

Face recognition algorithms commonly assume that face images are well aligned and have a similar pose -- yet in many practical applications it is impossible to meet these conditions. Therefore extending face recognition to unconstrained face images has become an active area of research. To this end, histograms of Local Binary Patterns (LBP) have proven to be highly discriminative descriptors for face recognition. Nonetheless, most LBP-based algorithms use a rigid descriptor matching strategy that is not robust against pose variation and misalignment. We propose two algorithms for face recognition that are designed to deal with pose variations and misalignment. We also incorporate an illumination normalization step that increases robustness against lighting variations. The proposed algorithms use descriptors based on histograms of LBP and perform descriptor matching with spatial pyramid matching (SPM) and Naive Bayes Nearest Neighbor (NBNN), respectively. Our contribution is the inclusion of flexible spatial matching schemes that use an image-to-class relation to provide an improved robustness with respect to intra-class variations. We compare the accuracy of the proposed algorithms against Ahonen's original LBP-based face recognition system and two baseline holistic classifiers on four standard datasets. Our results indicate that the algorithm based on NBNN outperforms the other solutions, and does so more markedly in presence of pose variations.
From basic network principles to neural architecture: emergence of orientation-selective cells.

This is the second paper in a series of three that explores the emergence of several prominent features of the functional architecture of visual cortex, in a "modular self-adaptive network" containing several layers of cells with parallel feedforward connections whose strengths develop according to a Hebb-type correlation-rewarding rule. In the present paper I show that orientation-selective cells, similar to the "simple" cortical cells of Hubel and Wiesel [Hubel, D. H. & Wiesel, T. N. (1962) J. Physiol. 160, 106-154], emerge in such a network. No orientation preference is specified to the system at any stage, the orientation-selective cell layer emerges even in the absence of environmental input to the system, and none of the basic developmental rules is specific to visual processing.
A Glimpse Far into the Future: Understanding Long-term Crowd Worker Quality

Microtask crowdsourcing is increasingly critical to the creation of extremely large datasets. As a result, crowd workers spend weeks or months repeating the exact same tasks, making it necessary to understand their behavior over these long periods of time. We utilize three large, longitudinal datasets of nine million annotations collected from Amazon Mechanical Turk to examine claims that workers fatigue or satisfice over these long periods, producing lower quality work. We find that, contrary to these claims, workers are extremely stable in their quality over the entire period. To understand whether workers set their quality based on the task's requirements for acceptance, we then perform an experiment where we vary the required quality for a large crowdsourcing task. Workers did not adjust their quality based on the acceptance threshold: workers who were above the threshold continued working at their usual quality level, and workers below the threshold self-selected themselves out of the task. Capitalizing on this consistency, we demonstrate that it is possible to predict workers' long-term quality using just a glimpse of their quality on the first five tasks.
Removing rolling shutter wobble

We present an algorithm to remove wobble artifacts from a video captured with a rolling shutter camera undergoing large accelerations or jitter. We show how estimating the rapid motion of the camera can be posed as a temporal super-resolution problem. The low-frequency measurements are the motions of pixels from one frame to the next. These measurements are modeled as temporal integrals of the underlying high-frequency jitter of the camera. The estimated high-frequency motion of the camera is then used to re-render the sequence as though all the pixels in each frame were imaged at the same time. We also present an auto-calibration algorithm that can estimate the time between the capture of subsequent rows in the camera.
The Elaboration Likelihood Model of Persuasion

A. ArgumentIMessage Quality ........ ................................. 132 B. Peripheral Cues.. . . . . . . . . . . . . . . . . ................................. 134 C. Affecting Elaboration . . . . . . . . . . . . . ................................. 136 V. Postulate 4 Objective Elaboration.. ............................. . . . . . . . 137 A. Distraction ............................................... . . . . . . . 139 B. Repetition .............................. . . . . . . . . . . 143 C. Personal Relevance/Involvement . . . . . . . . . . . . . . . . . . . . . . 144 D. Personal Responsibility ................... E. Need for Cognition. . . .......... 150
An efficient message access quality model in vehicular communication networks

In vehicular ad hoc network (VANET), vehicles equipped with computing, sensing, and communication capabilities can exchange information within a geographical area to distribute emergency messages and achieve safety system. Then how to enforce fine grained control of these messages and ensure the receiving messages coming from the claimed source in such a highly dynamic environments remains a key challenge that affects the quality of service. In this paper, we propose a hierarchical access control with authentication scheme for transmitted messages with security assurance over VANET. By extending ciphertext-policy attribute-based encryption (CP-ABE) with a hierarchical structure of multiple authorities, the scheme not only achieves scalability due to its hierarchical structure, but also inherits fine-grained access control on the transmitted messages. Also by exploiting attribute-based signature (ABS), the scheme can authorize the vehicles that can most appropriately deal with the message efficiently. The results of efficiency analysis and comparison with the related works show that the proposed scheme is efficient and scalable in dealing with access control and message authentication for data dissemination in VANET. & 2014 Elsevier B.V. All rights reserved.
Design of a PCB Rogowski Coil based on the PEEC Method

In order to measure currents with high di/dt, Rogowski coils are usually used. This work studies the design of a PCB coil by means of electromagnetic field simulation. The PEEC method has been used to extract the parameters of the equivalent circuit of the coil geometry. Different winding arrangements were analyzed with respect to measurement signal strength and noise immunity. The magnetic coupling between the current sensor and the busbar is investigated for the used test setup. Finally, a comparison of the PEEC simulation results with measurements, applying a 400 A current pulse concludes this paper. The results show that the PEEC method allows a simulation of the coil including the setup in which it is used with a reasonable computational effort.
Light Stemming for Arabic Information Retrieval

Computational Morphology is an urgent problem for Arabic Natural Language Processing, because Arabic is a highly inflected language. We have found, however, that a full solution to this problem is not required for effective information retrieval. Light stemming allows remarkably good information retrieval without providing correct morphological analyses. We developed several light stemmers for Arabic, and assessed their effectiveness for information retrieval using standard TREC data. We have also compared light stemming with several stemmers based on morphological analysis.. The light stemmer, light10, outperformed the other approaches. It has been included in the Lemur toolkit, and is becoming widely used Arabic information retrieval.
Biological network analysis and comparison: mining new biological knowledge

The mechanisms underlying life machinery are still not completely understood. Something is known, something is “probably” known, other things are still unknown. Scientists all over the world are working very hard to clarify the processes regulating the cell life cycle and bioinformaticians try to support them by developing specialized automated tools. Within the plethora of applications devoted to the study of life mechanisms, tools for the analysis and comparison of biological networks are catching the attention of many researchers. It is interesting to investigate why.