nils-herrmann/clean_scirepeval huggingface dataset:
The MAIN Model : A Heuristic Approach to Understanding Technology Effects on Credibility

The media world of today's youth is almost completely digital. With newspapers going online and television becoming increasingly digital, the current generation of youth has little reason to consume analog media. Music, movies, and all other forms of mass-mediated content can be obtained via a wide array of digital devices, ranging from CDs to DVDs, from iPods to PDAs. Even their nonmedia experiences are often characterized by a reliance on digital devices. Most young people communicate with most of their acquaintances through cell phones and computer-mediated communication tools such as instant messengers and e-mail systems. 1 And, with the arrival of personal broadcasting technologies such as blogs and social networking sites, many youngsters experience the world through their own self-expression and the expressions of their peers. This serves to blur the traditional boundary between interpersonal and mass communication, leading to an idiosyncratic construction of one's media world. Customization in the digital age—be it in the form of Web sites such as cus-tomizable portals that allow users to shape content or devices such as iPods that allow for customized playlists—enables the user to serve as the gatekeeper of content. As media get highly interactive, multimodal, and navigable, the receiver tends to become the source of communication. 2 While this leads naturally to egocentric construals of one's information environment, it also raises questions about the veracity of all the material that is consumed. The ease of digital publishing has made authors out of us all, leading to a dramatic profusion of information available for personal as well as public consumption. Much of this information, however, is free-floating and does not follow any universally accepted gatekeeping standards, let alone a professional process of writing and editing. Therefore, the veridicality of information accessed on the Web and other digital media is often suspect. 3 This makes credibility a supremely key concern in the new media environment, necessitating the constant need to critically assess information while consuming it. Credibility is classically ascertained by considering the source of information. If the attributed source of a piece of information is a credible person or organization, then, according to conventional wisdom, that information is probably reliable. However, in Internet-based media, source is a murky entity because there are often multiple layers of sources in online transmission of information (e.g., e-mail from a friend giving you a piece of information that he or she found on a newsgroup, posted …
The SPEC cloud group's research vision on FaaS and serverless architectures

Cloud computing enables an entire ecosystem of developing, composing, and providing IT services. An emerging class of cloud-based software architectures, serverless, focuses on providing software architects the ability to execute arbitrary functions with small overhead in server management, as Function-as-a-service (FaaS). However useful, serverless and FaaS suffer from a community problem that faces every emerging technology, which has indeed also hampered cloud computing a decade ago: lack of clear terminology, and scattered vision about the field. In this work, we address this community problem. We clarify the term serverless, by reducing it to cloud functions as programming units, and a model of executing simple and complex (e.g., workflows of) functions with operations managed primarily by the cloud provider. We propose a research vision, where 4 key directions (perspectives) present 17 technical opportunities and challenges.
Effective Inhibition of Mannitol Crystallization in Frozen Solutions by Sodium Chloride

The purpose of this work was to study the possibility of preventing mannitol crystallization in frozen solutions by using pharmaceutically acceptable additives.  Differential scanning calorimetry (DSC) and low-temperature X-ray diffractometry (LTXRD) were used to characterize the effect of additives on mannitol crystallization.  DSC screening revealed that salts (sodium chloride, sodium citrate, and sodium acetate) inhibited mannitol crystallization in frozen solutions more effectively than selected surfactants, α-cyclodextrin, polymers, and alditols. This finding prompted further studies of the crystallization in the mannitol-NaCl-water system. Isothermal DSC results indicated that mannitol crystallization in frozen solutions was significantly retarded in the presence of NaCl and that NaCl did not crystallize until mannitol crystallization completed. Low-temperature X-ray diffractometry data showed that when a 10% w/v mannitol solution without additive was cooled at 1°C/min, the crystalline phases emerging after ice crystallization were those of a mannitol hydrate as well as the anhydrous polymorphs. In the presence of NaCl (5% w/v), mannitol crystallization was suppressed during both cooling and warming and occurred only after annealing and rewarming. In the latter case however, mannitol did not crystallize as the hydrate, but as the anhydrous δ polymorph. At a lower NaCl concentration of 1% w/v, the inhibitory effect of NaCl on mannitol crystallization was evident even during annealing at temperatures close to the Tg′ (−40°C). A preliminary lyophilization cycle with polyvinyl pyrrolidone and NaCl as additives rendered mannitol amorphous.  The effectiveness of additives in inhibiting mannitol crystallization in frozen solutions follows the general order: salts > alditols > polyvinyl pyrrolidone > α-cyclodextrin > polysorbate 80 ∼ polyethylene glycol ∼ poloxamer. The judicious use of additives can retain mannitol amorphous during all the stages of the freeze-drying cycle.
Photonic Demodulator With Sensitivity Control

A current assisted photonic demodulator for use as a pixel in a 3-D time-of-flight imager shows nearly 100% static demodulator contrast and is operable beyond 30 MHz. An integrated tunable sensitivity control is also presented for increasing the distance measurement range and avoiding unwanted saturation during integration periods. This is achieved by application of a voltage on a dedicated drain tap showing a quenching of sensor sensitivity to below 1%
Broadband Frequency-Selective Spoof Surface Plasmon Polaritons on Ultrathin Metallic Structure

We propose an ultrathin metallic structure to produce frequency-selective spoof surface plasmon polaritons (SPPs) in the microwave and terahertz frequencies. Designed on a thin dielectric substrate, the ultrathin metallic structure is composed of two oppositely oriented single-side corrugated strips, which are coupled to two double-side corrugated strips. The structure is fed by a traditional coplanar waveguide (CPW). To make a smooth conversion between the spatial modes in CPW and SPP modes, two transition sections are also designed. We fabricate and measure the frequency-selective spoof SPP structure in microwave frequencies. The measurement results show that the reflection coefficient is less than -10 dB with the transmission loss around 1.5 dB in the selective frequency band from 7 to 10 GHz, which are in good agreements with numerical simulations. The proposed structure can be used as an SPP filter with good performance of low loss, high transmission, and wide bandwidth in the selective frequency band.
Sparse logistic regression with supervised selectivity for predictors selection in credit scoring

Credit scoring is a fundamental and one of the most complex tasks that financial institutions have to deal with. Commonly this problem is considered as default probability prediction for the lenders counterparts. Knowing predictors that significantly contribute to default prediction has recently emerged as a crucial issue of credit risk analysis. Default prediction and default predictor selection are two related issues, but many existing approaches address them separately. In this paper a unified procedure is proposed that is based on the regularization approach with logistic regression as an underlying model, which simultaneously selects the default predictors and optimizes all the parameters within the model. We give the strong probabilistic statement of shrinkage criterion for features selection.
 The proposed regularization do not corrupt the relevant predictors, can select correlated predictors into model, gives stable subset of relevant features. Experimental results show that the proposed framework is competitive on both artificial data and publicly available data sets.
MUSIC AND NATIONAL CULTURE: POP MUSIC AND RESISTANCE IN BRAZIL

In the late 1960s Brazil was experiencing a boom in its television and record industries, as part of the so-called “Economic Miracle” (1968 74) brought about by the military dictatorship’s opening up of the market to international capital. Censorship was introduced more or less simultaneously and responded in part to the military’s recognition of the potential power of the audio-visual media in a country in which over half of the population was illiterate or semi-literate. After the 1964 coup and until the infamous 5 Institutional Act (AI-5), introduced in 1968 to silence opposition to the regime, the left wing cultural production that had characterised the period under the government of the deposed populist president, João Goulart, had continued to flourish. Until 1968, the military had largely left the cultural scene alone to face up to the failure of its revolutionary political and cultural projects. Instead the generals focused on the brutal repression of student, trade union and grassroots activists who had collaborated with the cultural left, thus effectively depriving these artists of their public. Chico Buarque, one of the most censored performers of the period, maintains that at this moment he was saved from retreating into an introspective formalism in his songs and musical dramas by the emergence in 1965 of the televised music festivals, which became one of the most talked about events in the country (Buarque, 1979, 48). Sponsored by the television stations, which were themselves closely monitored and regulated by the government, the festivals still provided oppositional songwriters with an opportunity to re-
Identifying Difference in Perceptions of Academic Stress and Reaction to Stressors Based on Gender among First Year University Students

This study identifies the difference in the perceptions of academic stress and reaction to stressors based on gender among first year university students in Nigeria. Student Academic Stress Scale (SASS) was the instrument used to collect data from 2,520 first year university students chosen through systematic random sampling from Universities in the six geo-political zones of Nigeria. To determine gender differences among the respondents, independent samples t-test was used via SPSS version 15.0. The results of research showed that male and female respondents differed significantly in their perceptions of frustrations, financials, conflicts and selfexpectations stressors but did not significantly differ in their perceptions of pressures and changesrelated stressors. Generally, no significant difference was found between male and female respondents in their perceptions of academic stressors, however using the mean scores as basis, female respondents scored higher compared to male respondents. Regarding reaction to stressors, male and female respondents differ significantly in their perceptions of emotional and cognitive reactions but did not differ significantly in their perceptions of physiological and behavioural reaction to stressors.
FOR LEARNING-BASED PRESENTATION SLIDES GENERATION AND IEEE FORMAT CREATION FOR ACADEMIC PAPERS Miss

We uses the backslide procedure to determine the Noteworthiness Score of the sentences in a paper and then uses the Integer Linear Programming Algorithms system to create well-organized slides by selecting and adjusting key expressions and sentences. Evaluated result based on a certain set of 200 arrangements of papers and slide assemble on the web displays in our proposed structure of PPSGen can create slides with better quality and quick. Paper talks about a technique for consequently getting outline slides from a content, contemplating the programmed era of presentation slides from a specialized paper and also examines the challenging task of continuous creating presentation slides from academic paper. The created slide can be used as a draft to help moderator setup their systematic slides in a quick manners. This paper introduces novel systems called PPSGen to help moderators create such slide. A customer study also exhibits that PPSGen has obvious advantage over baseline method and speed is fast for creations. .  Regression (SVR), Integer Linear Programming (ILP), Abstract methods, texts mining, Classification etc....
Privacy challenges in proximity based social networking: Techniques & solutions

The development of the Proximity based Mobile Social Networking (PMSN) has been growing exponentially with the adoption of smartphones and introduction of Wi-Fi hotspots in public and remote areas. Users present in the vicinity can interact with each other using the embedded technologies in their mobile devices such as GPS, Wi-Fi and Bluetooth. Due to its growing momentum, this new social networking has also aroused the interest of business people and advertisers. However, due to a lack of security in these networks, several privacy concerns were reported. Users are more reluctant to share their locations and to address this issue, some initial solutions to preserve location privacy were implemented. The aim of this paper is to present a clear categorization of the different privacy threats in PMSN. Moreover, the location privacy enforcement policies and techniques used to ensure privacy are outlined and some solutions employed in existent systems are presented and discussed. To the best of our knowledge, this is the first study done outlining several categories of PMSN privacy challenges and their solutions in this new type of social networking services. Finally, some privacy research challenges and future perspectives are proposed.
` p-Norm Multiple Kernel Learning

Learning linear combinations of multiple kernels is an appealing strategy when the right choice of features is unknown. Previous approaches to multiple kernel learning (MKL) promote sparse kernel combinations to support interpretability and scalability. Unfortunately, this `1-norm MKL is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we extend MKL to arbitrary norms. We devise new insights on the connection between several existing MKL formulations and develop two efficient interleaved optimization strategies for arbitrary norms, that is `p-norms with p ≥ 1. This interleaved optimization is much faster than the commonly used wrapper approaches, as demonstrated on several data sets. A theoretical analysis and an experiment on controlled artificial data shed light on the appropriateness of sparse, non-sparse and `∞-norm MKL in various scenarios. Importantly, empirical applications of `p-norm MKL to three real-world problems from computational biology show that non-sparse MKL achieves accuracies that surpass the state-of-the-art. Data sets, source code to reproduce the experiments, implementations of the algorithms, and further information are available at
Understanding user goals in web search

Previous work on understanding user web search behavior has focused on how people search and what they are searching for, but not why they are searching. In this paper, we describe a framework for understanding the underlying goals of user searches, and our experience in using the framework to manually classify queries from a web search engine. Our analysis suggests that so-called navigational" searches are less prevalent than generally believed while a previously unexplored "resource-seeking" goal may account for a large fraction of web searches. We also illustrate how this knowledge of user search goals might be used to improve future web search engines.
A review on different methods of paraphrasing

This paper is survey of computational approaches for paraphrasing. Paraphrasing methods such as generation, identification and acquisition of phrases or sentences is a process that conveys same information. Paraphrasing is a process of expressing semantic content of source using different words to achieve the greater clarity. The task of generating or identifying the semantic equivalence for different elements of language such as words sentences; is an essential part of the natural language processing. Paraphrasing is being used for various natural language applications. This paper discuses paraphrase impact on few applications and also various paraphrasing methods.
Sampling Big Trajectory Data

The increasing prevalence of sensors and mobile devices has led to an explosive increase of the scale of spatio-temporal data in the form of trajectories. A trajectory aggregate query, as a fundamental functionality for measuring trajectory data, aims to retrieve the statistics of trajectories passing a user-specified spatio-temporal region. A large-scale spatio-temporal database with big disk-resident data takes very long time to produce exact answers to such queries. Hence, approximate query processing with a guaranteed error bound is a promising solution in many scenarios with stringent response-time requirements. In this paper, we study the problem of approximate query processing for trajectory aggregate queries. We show that it boils down to the distinct value estimation problem, which has been proven to be very hard with powerful negative results given that no index is built. By utilizing the well-established spatio-temporal index and introducing an inverted index to trajectory data, we are able to design random index sampling (RIS) algorithm to estimate the answers with a guaranteed error bound. To further improve system scalability, we extend RIS algorithm to concurrent random index sampling (CRIS) algorithm to process a number of trajectory aggregate queries arriving concurrently with overlapping spatio-temporal query regions. To demonstrate the efficacy and efficiency of our sampling and estimation methods, we applied them in a real large-scale user trajectory database collected from a cellular service provider in China. Our extensive evaluation results indicate that both RIS and CRIS outperform exhaustive search for single and concurrent trajectory aggregate queries by two orders of magnitude in terms of the query processing time, while preserving a relative error ratio lower than 10\%, with only 1% search cost of the exhaustive search method.
Strategic IS alignment: the necessity for a hybrid framework linking shared vision, leadership, change management and diffusion theory

The rapid pace of business process change, partially fueled by information technology, is placing increasingly difficult demands on the organization. In many industries, organizations are required to evaluate and assess new information technologies and their organization-specific strategic potential, in order to remain competitive. The scanning, adoption and diffusion of this information technology must be carefully guided by strong strategic and technological leadership in order to infuse the organization and its members with strategic and technological visions, and to coordinate their diverse and decentralized expertise. This view of technological diffusion requires us to look beyond individuals and individual adoption, toward other levels of analysis and social theoretical viewpoints to promote the appropriate and heedful diffusion of often organization-wide information technologies. Particularly important is an examination of the diffusion champions and how a feasible and shared vision of the business and information technology can be created and communicated across organizational communities in order to unify, motivate and mobilize technology change process. The feasibility of this shared vision depends on its strategic fit and whether the shared vision is properly aligned with organizational objectives in order to filter and shape technological choice and diffusion. Shared vision is viewed as an organizational barometer for assessing the appropriateness of future technologies amidst a sea of overwhelming possibilities. We present a theoretical model to address an extended program of research focusing on important phases during diffusion, shared vision, change management and social alignment. We also make a call for further research into these theoretical linkages and into the development of feasible shared visions.
Partially materialized views

We propose a new type of materialized view called a partially materialized view. A partially materialized view only materializes some of the rows, for example, the most frequently accessed rows, which reduces storage space and view maintenance effort. One or more control tables are associated with the view and define which rows are currently materialized. As a result, one can easily change which rows of the view are stored and maintained. We show how to extend view matching and maintenance algorithms to partially materialized views and outline several potential applications of the new view type. Experimental results in Microsoft SQL Server show that compared with fully materialized views, partially materialized views have lower storage requirements, better buffer pool efficiency, better query performance, and significantly lower maintenance costs.
Dynamics Transfer GAN: Generating Video by Transferring Arbitrary Temporal Dynamics from a Source Video to a Single Target Image

In this paper, we propose Dynamics Transfer GAN; a new method for generating video sequences based on generative adversarial learning. The spatial constructs of a generated video sequence are acquired from the target image. The dynamics of the generated video sequence are imported from a source video sequence, with arbitrary motion, and imposed onto the target image. To preserve the spatial construct of the target image, the appearance of the source video sequence is suppressed and only the dynamics are obtained before being imposed onto the target image. That is achieved using the proposed appearance suppressed dynamics feature. Moreover, the spatial and temporal consistencies of the generated video sequence are verified via two discriminator networks. One discriminator validates the fidelity of the generated frames appearance, while the other validates the dynamic consistency of the generated video sequence. Experiments have been conducted to verify the quality of the video sequences generated by the proposed method. The results verified that Dynamics Transfer GAN successfully transferred arbitrary dynamics of the source video sequence onto a target image when generating the output video sequence. The experimental results also showed that Dynamics Transfer GAN maintained the spatial constructs (appearance) of the target image while generating spatially and temporally consistent video sequences.
Segment-based injection attacks against collaborative filtering recommender systems

Significant vulnerabilities have recently been identified in collaborative filtering recommender systems. Researchers have shown that attackers can manipulate a system's recommendations by injecting biased profiles into it. In this paper, we examine attacks that concentrate on a targeted set of users with similar tastes, biasing the system's responses to these users. We show that such attacks are both pragmatically reasonable and also highly effective against both user-based and item-based algorithms. As a result, an attacker can mount such a "segmented" attack with little knowledge of the specific system being targeted and with strong likelihood of success.