Growth and nonvanishing of restricted Siegel modular forms arising as Saito-Kurokawa lifts

We study the analytic behavior of the restriction of a Siegel modular form to $\mathbb{H} \times \mathbb{H}$ in the case that the Siegel form is a Saito-Kurokawa lift. A formula of Ichino links this behavior to a family of $GL_3 \times GL_2$ $L$-functions.Comment: 28 page

Simple zeros of primitive Dirichlet LL-functions and the asymptotic large sieve

Assuming the Generalized Riemann Hypothesis (GRH), we show using the asymptotic large sieve that 91% of the zeros of primitive Dirichlet $L$-functions are simple. This improves on earlier work of \"{O}zl\"{u}k which gives a proportion of at most 86%. We further compute an $q$-analogue of the Pair Correlation Function $F(\alpha)$ averaged over all primitive Dirichlet $L$-functions in the range $|\alpha| < 2$ . Previously such a result was available only when the average included all the characters $\chi$.Comment: This work was initiated during the Arithmetic Statistics MRC program at Snowbird, Utah. Corollary 3 and Section 7 are adde

Segmenting Taipei’s Real Estate Data – A Cluster Analysis

Data mining has been widely used for knowledge discovery from large amount of data. In this paper, clustering analysis is applied to Taiwan government open data platform (DATA.GOV.TW), segmenting the real estate data so as to understand the real estate market structure in Taiwan. This paper use design science research methodology (DSRM) as research method. The result provides valuable insights into market structures in Taipei City that has limited addressed in past research and contributes to real estate agencies and practitioners an insight-seeking approach that they can follow to generate values from data

Towards Robust GAN-generated Image Detection: a Multi-view Completion Representation

GAN-generated image detection now becomes the first line of defense against the malicious uses of machine-synthesized image manipulations such as deepfakes. Although some existing detectors work well in detecting clean, known GAN samples, their success is largely attributable to overfitting unstable features such as frequency artifacts, which will cause failures when facing unknown GANs or perturbation attacks. To overcome the issue, we propose a robust detection framework based on a novel multi-view image completion representation. The framework first learns various view-to-image tasks to model the diverse distributions of genuine images. Frequency-irrelevant features can be represented from the distributional discrepancies characterized by the completion models, which are stable, generalized, and robust for detecting unknown fake patterns. Then, a multi-view classification is devised with elaborated intra- and inter-view learning strategies to enhance view-specific feature representation and cross-view feature aggregation, respectively. We evaluated the generalization ability of our framework across six popular GANs at different resolutions and its robustness against a broad range of perturbation attacks. The results confirm our method's improved effectiveness, generalization, and robustness over various baselines.Comment: Accepted to IJCAI 202

Context-awareness for mobile sensing: a survey and future directions

The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions

Measuring fraud in insurance industry: The case of automobile insurance in Taiwan

By conducting an extensive exploration on claim data, this paper attempts to investigate the fraud problem in Taiwan automobile physical damage insurance. Based on the different claim patterns between data in calendar year and policy year, excess claims are significantly identified in the last month of policy year. Censored regression provides robust estimation concerning the sources of the fraud payment

Knowledge-based View in the Franchising Research Literature

Abstract. This study was conducted to understand the state of research on applications of Knowledge-based View in franchise systems. First, we used SALSA (Search, Appraisal, Synthesis, and Analysis), a simple systematic data search method, to obtain 61 sample papers. Second, the citations of authors and publications were analyzed using the bibliometric method to understand the authors and the publications that had the most impact as well as the trend of current studies in the field of knowledge-based theory application in franchise systems. The results showed that the journals that had the most publications on the topic were Entrepreneurship Theory and Practice and Journal of Business Research; the most cited author was S.A. Shane, who had an average rate of 1.016 citations per article, and the most cited study was a paper published by Darr, Argote, &amp; Epple (1995), which was cited by 18 of the 61 sample papers (18/61, 29.51%). Third, we categorized the topic of knowledge-based theory application in franchise systems into six categories, i.e., knowledge transfer, knowledge creation, knowledge sharing, knowledge application, organizational learning, and knowledge exchange, to provide references for future studies.Keywords. Knowledge-based view; Franchising; Bibliometrics.JEL. L10

Analyzing the influences of bicycle suspension systems on pedaling forces and human body vibration

Front and rear suspensions are commonly equipped on bicycles for the purpose of riding comfort especially for mountain bicycle. Suspension system includes damper for shock absorbing and spring for rebounding. Therefore suspension system would increase leg muscle forces for riding bicycle since damper dissipates some energy. ADAMS‎®‎/LifeMOD‎®‎ are proposed in this research to establish a bicycle-human integrated multibody dynamic model to investigate the impact of bicycle suspensions on cyclist’s leg muscle forces under various pedaling conditions and human body vibration for evaluation of riding comfort. Muscles studied include adductor magnus, rectus femoris, vastus lateralis and semitendinosus. Comfort analyses include the vibrating acceleration in vertical direction of lower torso and scapula. Pedaling conditions include riding on flat road, over a road bump, and climbing slope. The results indicate that suspension system increases the pedaling forces of vastus lateralis and semitendinosus. However suspension system decreases the pedaling forces of adductor magnus and rectus femoris. Suspension systems, especially the rear suspension, may effectively reduce human body vibrating acceleration. The integrated model built in this research may be used as reference for designing bicycle suspension systems. Also, the results of this study may be used as a basis of leg weight training to strengthen certain muscles for long-distance off-road cyclists