Keystroke Biometrics for Freely Typed Text Based on CNN model

Keystroke biometrics, as an authentication method with advantages of no extra hardware cost, easy-to-integrate and high-security, has attracted much attention in user authentication. However, a mass of researches on keystroke biometrics have focused on the fixed-text analysis, while only a few took free-text analysis into consideration. And in the field of free-text analysis, most researchers usually devote their efforts to extracting the most appropriate keystroke features on their own experience. These methods were inevitably questionable due to their strong subjectivity. In this paper we proposed a multi-user keystroke authentication scheme based on CNN model, which can automatically figure out the appropriate features for the model, adjust and optimize the model constantly to further enhance the performance of model. In the experiment on a small sample set, the performance is improved more than 10% compared with the benchmark. Our model achieves an average recognition accuracy of 92.58%, with FAR of 0.24% and FRR of 7.34%

THE BATTLE FOR SINGLES’ DAY: HOW SOCIAL MEDIA MARKETING CAMPAIGNS BOOST SALES

Numerous studies have shown that social media marketing strategies have positive impacts on the long-term financial performance of firms. However, whether short-term marketing campaigns have any influence on firm revenue remains unknown. This paper examines data from Singles’ Day, the world’s largest shopping event, revealing that firms’ social media efforts have a positive impact on product sales. Furthermore, we find that the two social media effort measures generally thought to have positive impacts on a firm’s long-term financial performance, richness and intensity, have no significant influence on the success of a firm’s short-term marketing campaign. Instead, relevance shows significant and positive impacts. Moreover, we compare the effects of social media marketing yields from company-owned accounts with those of employee-owned accounts, finding that employee-owned accounts have better marketing effects than company-owned ones

I Know It\u27s You: Touch Behavioral Characteristics Recognition on Smartphone Based on Pattern Password

In recent years, pattern password has been widely used for user authentication on smartphones and other mobile devices in addition to the traditional password protection approach. However, pattern password authentication mechanism is incapable of protecting users from losses when a user\u27s login credential information is stolen. We propose an identity verification scheme based on user’s touching behaviors when inputting a pattern password on the smartphone screen. By exploiting the biometrical features, such as position, pressure, size, and time when a user inputs a pattern password to a smartphone, the proposed user verification mechanism can validate whether the user is the true owner of the smartphone. We adopted fuzzy logic, artificial neural network, and support vector machine, to build classifiers, using the behavioral data collected from 10 users. The experimental results show that all the three algorithms have significant recognition capacity, and the fuzzy logic algorithm is the best one with its false acceptance rate and false rejection rate as 4.7% and 4.468% respectively

The Value of Backers’ Word-of-Mouth in Screening Crowdfunding Projects: An Empirical Investigation

Reward-based crowdfunding is an emerging financing channel for entrepreneurs to raise money for their innovative projects. How to screen the crowdfunding projects is critical for crowdfunding platform, project founder, and potential backers. This study aims to investigate whether backers’ word-of-mouth (WOM) is a valuable input to generate collective intelligence for project screening. Specially, we answer three questions. First, is backers’ WOM an effective signal for implementation performance of crowdfunding projects? Second, how do the WOM help screen projects during the fund-raising process? Third, which kind of comments (positive or negative) is more effective in screening crowdfunding projects? Research hypotheses were developed based on theories of collective intelligence and WOM communication. Using a cross section dataset and a panel dataset, we get the following findings. First, backers’ negative WOM can effectively predict project implementation performance, however positive WOM does not have that prediction power. The prediction power of positive and negative WOM differs significantly. One possible reason is that negative WOM does contain more information of project quality. Second, project with more accumulative negative WOM tend to attract fewer subsequent backers. However, accumulative positive WOM is not helpful for attracting more potential backers. We conclude that negative WOM is useful for project screening project, because it is a signal of project quality, and meanwhile it could prevent backers make subsequent investments

CRPV Genomes with Synonymous Codon Optimizations in the CRPV E7 Gene Show Phenotypic Differences in Growth and Altered Immunity upon E7 Vaccination

Papillomaviruses use rare codons relative to their hosts. Recent studies have demonstrated that synonymous codon changes in viral genes can lead to increased protein production when the codons are matched to those of cells in which the protein is being expressed. We theorized that the immunogenicity of the virus would be enhanced by matching codons of selected viral genes to those of the host. We report here that synonymous codon changes in the E7 oncogene are tolerated in the context of the cottontail rabbit papillomavirus (CRPV) genome. Papilloma growth rates differ depending upon the changes made indicating that synonymous codons are not necessarily neutral. Immunization with wild type E7 DNA yielded significant protection from subsequent challenge by both wild type and codon-modified genomes. The reduction in growth was most dramatic with the genome containing the greatest number of synonymous codon changes

The complete mitochondrial genome of Hemathlophorus brevigenatus Wei, 2005 (Hymenoptera: Tenthredinidae) with phylogenetic analysis

The mitochondrial genome of Hemathlophorus brevigenatus Wei, 2005 collected from Huanggang Mountain of China is described using the NGS approach. The length of the sequence is 15,452 bp containing 13 protein-coding genes, 22 transfer RNA genes, two ribosomal RNA genes, and one control region. The overall A + T content is 79.5%. tRNA rearrangements occur in the MQI cluster. Phylogenetic analysis of H. brevigenatus resolved it in a clade with Allantus togatus in Allantinae which provides new evidence for the phylogeny of Tenthredinidae

TDSD: A Touch Dynamic and Sensor Data Based Approach for Continuous User Authentication

With the popularity of mobile business, it becomes essential for mobile devices to check regularly whether the current user is the same one who unlock the device. The challenge lies on how to authenticate users continuously without influence on device usability. To guarantee both security and usability of mobile devices, we propose TDSD, a touch dynamic and sensor data based approach. It depicts user behavioral features in more comprehensive aspects and identify individuals with higher certainty. We utilize six classifiers and combine them together to form a stronger model by a compound-voting mechanism. Our experiments on real world dataset show a satisfactory performance of TDSD. Based on a small sample from 30 participants, compound-voting mechanism improve the accuracy of TDSD from about 85.00% to 100.00% and drop its false accept/reject rates to 0.00%

Characterization of the mitochondrial genome of Eutomostethus vegetus Konow, 1898 (Hymenoptera: Tenthredinidae) and phylogenetic analysis

The nearly complete mitochondrial genome of Eutomostethus vegetus Konow, 1898 was high-quality assembled. Several gene rearrangement events were observed in IQM gene cluster by comparing with the inferred insect ancestral mitochondrial genome. Phylogenetic analysis demonstrated the position of Eutomostethus vegetus in the Tenthredinidae and showed that Blennocampinae is a sister group to Fenusinae

LOOKING FOR GOLD IN THE SANDS: STOCK PREDICTION USING FINANCIAL NEWS AND SOCIAL MEDIA

Abstract Both traditional finance and behavioral finance theory have reached a consensus that the news medi