nils-herrmann/clean_scirepeval huggingface dataset:
Emotional Branding and the Strategic Value of the Doppelgänger Brand Image

Emotional branding is widely heralded as a key to marketing success. However, little attention has been given to the risks posed by this strategy. This article argues that emotional-branding strategies are conducive to the emergence of a doppelgänger brand image, which is defined as a family of disparaging images and meanings about a brand that circulate throughout popular culture. This article’s thesis is that a doppelgänger brand image can undermine the perceived authenticity of an emotional-branding story and, thus, the identity value that the brand provides to consumers. The authors discuss how the tenets of emotional branding paradoxically encourage the formation and propagation of doppelgänger brand imagery. This article develops the counterintuitive proposition that rather than merely being a threat to be managed, a doppelgänger brand image can actually benefit a brand by providing early warning signs that an emotional-branding story is beginning to lose its cultural resonance. This article demonstrates these ideas through an analysis of the doppelgänger brand image that is beginning to haunt a paragon of emotional branding—Starbucks. The authors conclude with a discussion of how marketing managers can proactively use the insights gained by analyzing a doppelgänger brand image.
Modeling of Planar Spiral Inductors Between Two Multilayer Media for Induction Heating Applications

We present an analytical model of the equivalent impedance of an n-turn planar winding sandwiched between top and bottom multilayer media. Although the model's general and compact notation is valid for all systems involving magnetic dipoles and stratified media, perhaps its main application is domestic induction heating systems. The proposed model is based on the vector potential solution of a single-turn coil located between two multilayer media, and this result is extended to n-turn coils. We demonstrate the applicability of the model by a variety of examples. We present experimental results to justify the theoretical model
An Analysis on a Dynamic Amplifier and Calibration Methods for a Pseudo-Differential Dynamic Comparator

This paper analyzes a pseudo-differential dynamic comparator with a dynamic pre-amplifier. The transient gain of a dynamic preamplifier is derived and applied to equations of the thermal noise and the regeneration time of a comparator. This analysis enhances understanding of the roles of transistor’s parameters in pre-amplifier’s gain. Based on the calculated gain, two calibration methods are also analyzed. One is calibration of a load capacitance and the other is calibration of a bypass current. The analysis helps designers’ estimation for the accuracy of calibration, dead-zone of a comparator with a calibration circuit, and the influence of PVT variation. The analyzed comparator uses 90-nm CMOS technology as an example and each estimation is compared with simulation results. key words: dynamic amplifier, dynamic comparator, load capacitance, bypass current, calibration, and PVT variation
Single or Multiple? Combining Word Representations Independently Learned from Text and WordNet

Text and Knowledge Bases are complementary sources of information. Given the success of distributed word representations learned from text, several techniques to infuse additional information from sources like WordNet into word representations have been proposed. In this paper, we follow an alternative route. We learn word representations from text and WordNet independently, and then explore simple and sophisticated methods to combine them. The combined representations are applied to an extensive set of datasets on word similarity and relatedness. Simple combination methods happen to perform better that more complex methods like CCA or retrofitting, showing that, in the case of WordNet, learning word representations separately is preferable to learning one single representation space or adding WordNet information directly. A key factor, which we illustrate with examples, is that the WordNet-based representations captures similarity relations encoded in WordNet better than retrofitting. In addition, we show that the average of the similarities from six word representations yields results beyond the state-ofthe-art in several datasets, reinforcing the opportunities to explore further combination techniques.
Software Re-Modularization Based on Structural and Semantic Metrics

The structure of a software system has a major impact on its maintainability. To improve maintainability, software systems are usually organized into subsystems using the constructs of packages or modules. However, during software evolution the structure of the system undergoes continuous modifications, drifting away from its original design, often reducing its quality. In this paper we propose an approach for helping maintainers to improve the quality of software modularization. The proposed approach analyzes the (structural and semantic) relationships between classes in a package identifying chains of strongly related classes. The identified chains are used to define new packages with higher cohesion than the original package. The proposed approach has been empirical evaluated through a case study. The context of the study is represented by an open source system, JHotDraw, and two software systems developed by teams of students at the University of Salerno. The analysis of the results reveals that the proposed approach generates meaningful re-modularization of the studied systems, which can lead to higher quality.
Designing and Implementing a Lightweight WSN MAC Protocol for Smart Home Networking Applications

Wireless sensor networks (WSNs) represent a promising solution in the ̄elds of the Internet of Things (IoT) and machine-to-machine networks for smart home applications. However, to feasibly deploy wireless sensor devices in a smart home environment, four key requirements must be satis ̄ed: stability, compatibility, reliability routing, and performance and power balance. In this study, we focus on the unreliability problem of the IEEE 802.15.4 WSN medium access control (MAC), which is caused by the contention-based MAC protocol used for channel access. This problem results in a low packet delivery ratio, particularly in a smart home network with only a few sensor nodes. In this paper, we ̄rst propose a lightweight WSN protocol for a smart home or an intelligent building, thus replacing the IEEE 802.15.4 protocol, which is highly complex and has a low packet delivery ratio. Subsequently, we describe the development of a discrete event systemmodel for theWSN by using a GRAFCET and propose a development platform based on a recon ̄gurable FPGA for reducing fabrication cost and time. Finally, a prototype WSN controller ASIC chip without an extra CPU and with our proposed lightweight MAC was developed and tested. It enhanced the packet delivery ratio by up to 100%.
An Operator Interaction Framework for Visualization Systems

Information visualization encounters a wide variety of different data domains. The visualization community has developed representation methods and interactive techniques. As a community, we have realized that the requirements in each domain are often dramatically different. In order to easily apply existing methods, researchers have developed a semiology of graphic representations. We have extended this research into a framework that includes operators and interactions in visualization systems, such as a visualization spreadsheet. We discuss properties of this framework and use it to characterize operations spanning a variety of different visualization techniques. The framework developed in this paper enables a new way of exploring and evaluating the design space of visualization operators, and helps end–users in their analysis tasks.
Framing: Toward Clarification of a Fractured Paradigm

In response to the proposition that communication lacks disciplinary status because of deficient core knowledge, I propose that we turn an ostensible weakness into a strength. We should identify our mission as bringing together insights and theories that would otherwise remain scattered in other disciplines. Because of the lack of interchange among the disciplines, hypotheses thoroughly discredited in one field may receive wide acceptance in another. Potential research paradigms remain fractured, with pieces here and there but no comprehensive statement to guide research. By bringing ideas together in one location, communication can aspire to become a master discipline that synthesizes related theories and concepts and exposes them to the most rigorous, comprehensive statement and exploration. Reaching this goal would require a more self-conscious determination by communication scholars to plumb other fields and feed back their studies to outside researchers. At the same time, such an enterprise would enhance the theoretical rigor of communication scholarship proper. The idea of “framing” offers a case study of just the kind of scattered conceptualization I have identified. Despite its omnipresence across the social sciences and humanities, nowhere is there a general statement of framing theory that shows exactly how frames become embedded within and make themselves manifest in a text, or how framing influences thinking. Analysis o f this concept suggests how the discipline of communication might contribute something unique: synthesizing a key concept’s disparate uses, showing how they invariably involve communication, and constructing a coherent theory from them. Whatever its specific use, the concept of framing consistently offers a way to describe the power of a communicating text. Analysis of frames illuminates the precise way in which influence over a human consciousness is exerted by the transfer (or communication) of information from
A Mobile Application Offloading Algorithm for Mobile Cloud Computing

In mobile cloud computing, offloading mobile applications to close remote servers appears as a straightforward solution to overcome mobile terminals processor and battery limitations. Remote execution leverages the high computation capacity of the server to enrich user experience and extend battery autonomy through energy savings. However, application offloading is energy efficient only under various conditions. For that purpose, we propose an original algorithm called MAO(Mobile Application's Offloading) triggered by two conditions: The current CPU load and State of Charge (SoC) of the battery.On the basis of various traffic scenarios mixing interactive and delay tolerant mobile applications, we study through numerical simulations the efficiency of the MAO algorithm and assess its performance in terms of rejected jobs and the amount of energy savings achieved. Rejected jobs are those unable to meet user quality of experience (QoE) and/or energy efficiency requirements. Evaluations on simulated workloads show that both traffic loads and user's radio mobile environment have direct impact on the efficiency of the MAO algorithm.
Speed control of buck converter fed DC motor drives

This research paper presents a new speed control method for DC motor through differential flatness control. The desired angular velocity trajectory is well tracked and the performance of the controller is healthy in all dynamic operating circumstances. The actual value follows the trajectory with time delay and reduced magnitude in simulation. So controller gains are introduced to overcome these issues. Along with that, hardware is to be implemented for the simulation model of overall system. It is significant that these kinds of sudden deviations do not occur in repetition at the similar time, or through such huge deviations about their nominal values.
ERP evidence for conceptual mappings and comparison processes during the comprehension of conventional and novel metaphors

Cognitive linguists suggest that understanding metaphors requires activation of conceptual mappings between the involved concepts. We tested whether mappings are indeed in use during metaphor comprehension, and what mapping means as a cognitive process with Event-Related Potentials. Participants read literal, conventional metaphorical, novel metaphorical, and anomalous target sentences preceded by primes with related or unrelated mappings. Experiment 1 used sentence-primes to activate related mappings, and Experiment 2 used simile-primes to induce comparison thinking. In the unprimed conditions of both experiments, metaphors elicited N400s more negative than the literals. In Experiment 1, related sentence-primes reduced the metaphor-literal N400 difference in conventional, but not in novel metaphors. In Experiment 2, related simile-primes reduced the metaphor-literal N400 difference in novel, but not clearly in conventional metaphors. We suggest that mapping as a process occurs in metaphors, and the ways in which it can be facilitated by comparison differ between conventional and novel metaphors.
An application of neural net chips: handwritten digit recognition

A general-purpose, fully interconnected neural-net chip was used to perform computationally intensive tasks for handwritten digit recognition. The chip has nearly 3000 programmable connections, which can be set for template matching. The templates can be reprogrammed as needed during the recognition sequence. The recognition process proceeds in four major steps. First, the image is captured using a TV camera and a digital framegrab. This image is converted, using a digital computer, to either black or white pixels and scaled to fill a 16*16-pixel frame. Next, using the neural-net chip, the image is skeletonized, i.e. the image is thinned to a backbone one pixel wide. Then, the chip is programmed, and a feature map is created by template-matching stored primitive patterns on the chip with regions on the skeletonized image. Finally, recognition, based on the feature map, is achieved using any one of a variety of statistical and heuristic techniques on a digital computer. Best scores range between 90% and 99% correct classification, depending on the quality of the original handwritten digits.<<ETX>>
Tuning in to RF MEMS

RF MEMS technology was initially developed as a replacement for GaAs HEMT switches and p-i-n diodes for low-loss switching networks and X-band to mm-wave phase shifters. However, we have found that its very low loss properties (high device Q), its simple microwave circuit model and zero power consumption, its high power (voltage/current) handling capabilities, and its very low distortion properties, all make it the ideal tuning device for reconfigurable filters, antennas and impedance matching networks. In fact, reconfigurable networks are currently being funded at the same level-if not higher-than RF MEMS phase shifters, and in our opinion, are much more challenging for high-Q designs.
Maximum power point tracking using a fuzzy logic control scheme

This paper proposes an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and insolation conditions. This method uses a fuzzy logic controller applied to a DC-DC converter device. The different steps of the design of this controller are presented together with its simulation. Results of this simulation are compared to those obtained by the perturbation and observation controller. They show that the fuzzy logic controller exhibits a much better behaviour. Résumé – Cet article propose une méthode de contrôle intelligent pour la recherche du point de puissance maximum (MPPT) d’un système photovoltaïque dans des conditions variables de la température et d’insolation. Cette méthode emploie un contrôleur de logique floue appliqué à un dispositif de convertisseur de DC-DC. Les différentes étapes de la conception de ce contrôleur sont présentées, ainsi que sa simulation. Des résultats de cette simulation sont comparés à ceux obtenus par le contrôleur de perturbation et d’observation. Ils prouvent que le contrôleur de logique floue montre un comportement bien meilleur.
Web Mining for Information Retrieval

The present era is engulfed in data and it is quite difficult to churn the emergence of unstructured data in order to mine relevant information. In this paper we present a basic outline of web mining techniques which changed the scenario of today world and help in retrieval of information. Web Mining actually referred as mining of interesting pattern by using set of tools and techniques from the vast pool of web. It focuses on different aspects of web mining referred as Web Content Mining, Web Structure Mining and Web Usage Mining. The overview of these mining techniques which help in retrieving desired information are covered along with the approaches used and algorithm employed.
A study of SSL Proxy attacks on Android and iOS mobile applications

According to recent articles in popular technology websites, some mobile applications function in an insecure manner when presented with untrusted SSL certificates. These non-browser based applications seem to, in the absence of a standard way of alerting a user of an SSL error, accept any certificate presented to it. This paper intends to research these claims and show whether or not an invisible proxy based SSL attack can indeed steal user's credentials from mobile applications, and which types applications are most likely to be vulnerable to this attack vector. To ensure coverage of the most popular platforms, applications on both Android 4.2 and iOS 6 are tested. The results of our study showed that stealing credentials is indeed possible using invisible proxy man in the middle attacks.
Evaluation of Precise Point Positioning Using MADOCA-LEX via Quasi-Zenith Satellite System

This paper describes the evaluation of precise point positioning (PPP) using the Quasi-Zenith Satellite System (QZSS) L-band Experiment (LEX) signal. The first QZSS, the Japanese regional satellite navigation system, was launched from Japan in September 2010. QZSS transmits augmentation signals to enhance the global navigation satellite system (GNSS) positioning accuracy. One of the QZSS augmentation signals is the LEX signal, the objective of which to realize centimeter-class positioning with its broadcasting data. The Japan Aerospace Exploration Agency began a test transmission of a MADOCA-LEX message, a new type of LEX message, in April 2013. MADOCA-LEX provides the satellite orbit and clock correction data of multi-GNSS using a statespace representation (SSR) format for real-time PPP. Unfortunately, the LEX signal cannot be received using the currently available commercial GNSS receivers. Moreover, for real-time applications, the LEX message contained in the LEX signal is required to be extracted for computing the user positions in real time. In this study, we have developed a novel technique for receiving and decoding the MADOCA-LEX message using a software GNSS receiver. We have developed a technique to decode the LEX messages without the use of an LEX signal tracking loop for estimating the code phase and the Doppler frequency of the LEX signal, however, with the aid of the conventional L1CA signal broadcasted simultaneously from the QZSS. We have confirmed the effectiveness of the proposed method through static and kinematic tests. We have determined the receiver positions with a distance rootmean-square error of within 10 cm, by using PPP with the MADOCA-LEX message in the real-time static test. We have also found that the proposed localization technique is effective for position estimation with the decimeterlevel accuracy through a kinematic test in the open-sky environment.
PROPOSED METHODOLOGY FOR EARTHQUAKE-INDUCED LOSS ASSESSMENT OF INSTRUMENTED STEEL FRAME BUILDINGS : BUILDING-SPECIFIC AND CITY-SCALE APPROACHES

The performance-based earthquake engineering framework utilizes probabilistic seismic demand models to obtain accurate estimates of building engineering demand parameters. These parameters are utilized to estimate earthquake-induced losses in terms of probabilistic repair costs, life-safety impact, and loss of function due to damage to a wide variety of building structural and non-structural components and content. Although nonlinear response history analysis is a reliable tool to develop probabilistic seismic demand models, it typically requires a considerable time investment in developing detailed building numerical model representations. In that respect, the challenge of city-scale damage assessment still remains. This paper proposes a simplified methodology that rapidly assesses the story-based engineering demand parameters (e.g., peak story drift ratios, residual story drift ratios, peak absolute floor accelerations) along the height of a steel frame building in the aftermath of an earthquake. The proposed methodology can be employed at a city-scale in order to facilitate rapid earthquake-induced loss assessment of steel frame buildings in terms of structural damage and monetary losses within a region. Therefore, buildings within an urban area that are potentially damaged after an earthquake event or scenario can be easily identified without a detailed engineering inspection. To illustrate the methodology for rapid earthquake-induced loss assessment at the city-scale we employ data from instrumented steel frame buildings in urban California that experienced the 1994 Northridge earthquake. Maps that highlight the expected structural and nonstructural damage as well as the expected earthquake-induced monetary losses are developed. The maps are developed with the geographical information system for steel frame buildings located in Los Angeles. Seong-Hoon Hwang and Dimitrios G. Lignos
A hybrid factor analysis and probabilistic PCA-based system for dictionary learning and encoding for robust speaker recognition

Probabilistic Principal Component Analysis (PPCA) based low dimensional representation of speech utterances is found to be useful for speaker recognition. Although, performance of the FA (Factor Analysis)-based total variability space model is found to be superior, hyperparameter estimation procedure in PPCA is computationally efficient. In this work, recent insight on the FA-based approach as a combination of dictionary learning and encoding is explored to use its encoding procedure in the PPCA framework. With the use of an alternate encoding technique on dictionaries learnt using PPCA, performance of state-of-the-art FA-based i-vector approach is matched by using the proposed procedure. A speed up of 4x is obtained while estimating the hyperparameter at the cost of 0.51% deterioration in performance in terms of the Equal Error Rate (EER) in the worst case. Compared to the conventional PPCA model, absolute improvements of 2.1% and 2.8% are observed on two telephone conditions of NIST 2008 SRE database. Using Canonical Correlational Analysis, it is shown that the i-vectors extracted from the conventional FA model and the proposed approach are highly correlated.
Road traffic sign detection and classification

A vision-based vehicle guidance system for road vehicles can have three main roles: 1) road detection; 2) obstacle detection; and 3) sign recognition. The first two have been studied for many years and with many good results, but traffi c sign recognition is a less-studied field. Traffi c signs provide drivers with very valuable informatio n about the road, in order to make drivin g safer and easier. We think that traffi c signs must play the same role for autonomous vehicles. They are designed to be easily recognized by human driver s mainly because their color and shapes are very different from natural environments. The algorithm described in this paper takes advantage of these features. I t has two main parts. The first one, for the detection, uses color thresholding to segment the image and shape analysis to detect the signs. The second one, for the classification, uses a neural network. Some results from natural scenes are shown. On the other hand, the algorithm is valid to detect other kinds of marks that would tell the mobile robot to perform some task at that place.