On the Feature Discovery for App Usage Prediction in Smartphones

With the increasing number of mobile Apps developed, they are now closely integrated into daily life. In this paper, we develop a framework to predict mobile Apps that are most likely to be used regarding the current device status of a smartphone. Such an Apps usage prediction framework is a crucial prerequisite for fast App launching, intelligent user experience, and power management of smartphones. By analyzing real App usage log data, we discover two kinds of features: The Explicit Feature (EF) from sensing readings of built-in sensors, and the Implicit Feature (IF) from App usage relations. The IF feature is derived by constructing the proposed App Usage Graph (abbreviated as AUG) that models App usage transitions. In light of AUG, we are able to discover usage relations among Apps. Since users may have different usage behaviors on their smartphones, we further propose one personalized feature selection algorithm. We explore minimum description length (MDL) from the training data and select those features which need less length to describe the training data. The personalized feature selection can successfully reduce the log size and the prediction time. Finally, we adopt the kNN classification model to predict Apps usage. Note that through the features selected by the proposed personalized feature selection algorithm, we only need to keep these features, which in turn reduces the prediction time and avoids the curse of dimensionality when using the kNN classifier. We conduct a comprehensive experimental study based on a real mobile App usage dataset. The results demonstrate the effectiveness of the proposed framework and show the predictive capability for App usage prediction.Comment: 10 pages, 17 figures, ICDM 2013 short pape

A Visual Analytic Study of Articles in Entrepreneurship Research

The entrepreneurship research grows continuously in this century; this study utilized the visual analytic method to depict literature characteristics of entrepreneurship research, including publication countries, subject area, most cited references and so on. The analytical data was collected from database of Social Science Citation Index (SSCI) of ISI Web of knowledge. This study provided the several findings to describe the academic trend in entrepreneurship research

Negotiating the imagined community in national curriculum: the Taiwanese case

Due to its historical and geopolitical contestations, Taiwan is a country whose people possess divergent imaginations of the national community. Such a condition has been described as institutional liminality, which captures Taiwan’s status as not a complete nation state nor a non-nation state; not China nor non-China. Under such a condition, people recognize themselves either as Taiwanese, Chinese, or both. Through utilizing the concept of imagination, especially Anderson’s notion of “imagined communities” and Harvey’s interpretation of “geographical imagination,” this paper investigates the representation of imagined communities embedded in various revisions and makings of the national curriculum in Taiwan. A specific focus is put onto the revision of the national historical curriculum at the senior high school level and the resistance to it during 2014–2016. It is argued that through organizing protests and boycotts against the revision, students are no longer simply pure receivers of official knowledge, they actively express their imagination of the national community and participate in the negotiation of official knowledge, which gives the national curriculum a more democratic base

Microstructure and superelastic properties of FeNiCoAlTi single crystals with the <100> orientation under tension

The microstructure and superelastic response of an Fe41 Ni28 Co17 Al11.5 Ti2.5 (at.%) single crystal along the [removed] orientation was investigated under tension at room temperature after aging at 600◦ C for 24 h. From the superelastic results, the samples aged at 600◦ C for 24 h exhibited 4.5% recoverable strain at room temperature. The digital image correlation (DIC) method was used to observe the strain distribution during the 6.5% applied strain loading. The DIC results showed that the strain was uniformly distributed during the loading and unloading cycles. Only one martensite variant was observed from the DIC results. This was related to the aging heat treatment times. The martensite morphology became a single variant with a longer aging time. The thermo-magnetization results indicated that the phase transformation and temperature hysteresis was around 36◦ C. Increasing the magnetic field from 0.05 to 7 Tesla, the transformation temperatures increased. The maximum magnetization was 160 emu/g under the magnetic field of 7 Tesla. From the transmission electron microscopy results, the L12 precipitates were around 10 nm in size, and they were high in Ni content and low in Fe content

DNA Ligase I Is Not Essential for Mammalian Cell Viability

SummaryOf the three DNA ligases present in all vertebrates, DNA ligase I (Lig1) has been considered essential for ligating Okazaki fragments during DNA replication and thereby essential for cell viability. Here, we report the striking finding that a Lig1-null murine B cell line is viable. Surprisingly, the Lig1-null cells exhibit normal proliferation and normal immunoglobulin heavy chain class switch recombination and are not hypersensitive to a wide variety of DNA damaging agents. These findings demonstrate that Lig1 is not absolutely required for cellular DNA replication and repair and that either Lig3 or Lig4 can substitute for the role of Lig1 in joining Okazaki fragments. The establishment of a Lig1-null cell line will greatly facilitate the characterization of DNA ligase function in mammalian cells, but the finding alone profoundly reprioritizes the role of ligase I in DNA replication, repair, and recombination

The Management of Debris Flow in Disaster Prevention using an Ontology-based Knowledge Management System

In recently years, the government, academia and business have applied different information technologies to disaster prevention and diverse web sites have been developed. Although these web sites provide a large number of data about disaster-prevention, they are knowledge poor in nature. Furthermore, disaster-prevention is a knowledge-intensive task and a potential knowledge management system can overcome the shortcoming of knowledge poor. On the other hand, ontology design plays the key role toward designing a successful knowledge management system. In this paper, we introduce a three-stage life cycle for ontology design for supporting the service of disaster prevention of debris flow and propose a framework of an ontology-based knowledge management system with the KAON API environment. In addition, by appealing to the technology of component reuse, the system is developed at lower cost thus knowledge workers can focus on the design of ontology and knowledge objects. The objectives of the proposed system is to facilitate knowledge accumulation, knowledge reuse and dissemination for the management of disaster prevention. This work is expected to enable the promotion of the traditional disaster management of debris flow towards the so-called knowledge-driven decision support services