Human Mobility and Application Usage Prediction Algorithms for Mobile Devices

Mobile devices such as smartphones and smart watches are ubiquitous companions of humans’ daily life. Since 2014, there are more mobile devices on Earth than humans. Mobile applications utilize sensors and actuators of these devices to support individuals in their daily life. In particular, 24% of the Android applications leverage users’ mobility data. For instance, this data allows applications to understand which places an individual typically visits. This allows providing her with transportation information, location-based advertisements, or to enable smart home heating systems. These and similar scenarios require the possibility to access the Internet from everywhere and at any time. To realize these scenarios 83% of the applications available in the Android Play Store require the Internet to operate properly and therefore access it from everywhere and at any time. Mobile applications such as Google Now or Apple Siri utilize human mobility data to anticipate where a user will go next or which information she is likely to access en route to her destination. However, predicting human mobility is a challenging task. Existing mobility prediction solutions are typically optimized a priori for a particular application scenario and mobility prediction task. There is no approach that allows for automatically composing a mobility prediction solution depending on the underlying prediction task and other parameters. This approach is required to allow mobile devices to support a plethora of mobile applications running on them, while each of the applications support its users by leveraging mobility predictions in a distinct application scenario. Mobile applications rely strongly on the availability of the Internet to work properly. However, mobile cellular network providers are struggling to provide necessary cellular resources. Mobile applications generate a monthly average mobile traffic volume that ranged between 1 GB in Asia and 3.7 GB in North America in 2015. The Ericsson Mobility Report Q1 2016 predicts that by the end of 2021 this mobile traffic volume will experience a 12-fold increase. The consequences are higher costs for both providers and consumers and a reduced quality of service due to congested mobile cellular networks. Several countermeasures can be applied to cope with these problems. For instance, mobile applications apply caching strategies to prefetch application content by predicting which applications will be used next. However, existing solutions suffer from two major shortcomings. They either (1) do not incorporate traffic volume information into their prefetching decisions and thus generate a substantial amount of cellular traffic or (2) require a modification of mobile application code. In this thesis, we present novel human mobility and application usage prediction algorithms for mobile devices. These two major contributions address the aforementioned problems of (1) selecting a human mobility prediction model and (2) prefetching of mobile application content to reduce cellular traffic. First, we address the selection of human mobility prediction models. We report on an extensive analysis of the influence of temporal, spatial, and phone context data on the performance of mobility prediction algorithms. Building upon our analysis results, we present (1) SELECTOR – a novel algorithm for selecting individual human mobility prediction models and (2) MAJOR – an ensemble learning approach for human mobility prediction. Furthermore, we introduce population mobility models and demonstrate their practical applicability. In particular, we analyze techniques that focus on detection of wrong human mobility predictions. Among these techniques, an ensemble learning algorithm, called LOTUS, is designed and evaluated. Second, we present EBC – a novel algorithm for prefetching mobile application content. EBC’s goal is to reduce cellular traffic consumption to improve application content freshness. With respect to existing solutions, EBC presents novel techniques (1) to incorporate different strategies for prefetching mobile applications depending on the available network type and (2) to incorporate application traffic volume predictions into the prefetching decisions. EBC also achieves a reduction in application launch time to the cost of a negligible increase in energy consumption. Developing human mobility and application usage prediction algorithms requires access to human mobility and application usage data. To this end, we leverage in this thesis three publicly available data set. Furthermore, we address the shortcomings of these data sets, namely, (1) the lack of ground-truth mobility data and (2) the lack of human mobility data at short-term events like conferences. We contribute with JK2013 and UbiComp Data Collection Campaign (UbiDCC) two human mobility data sets that address these shortcomings. We also develop and make publicly available a mobile application called LOCATOR, which was used to collect our data sets. In summary, the contributions of this thesis provide a step further towards supporting mobile applications and their users. With SELECTOR, we contribute an algorithm that allows optimizing the quality of human mobility predictions by appropriately selecting parameters. To reduce the cellular traffic footprint of mobile applications, we contribute with EBC a novel approach for prefetching of mobile application content by leveraging application usage predictions. Furthermore, we provide insights about how and to what extent wrong and uncertain human mobility predictions can be detected. Lastly, with our mobile application LOCATOR and two human mobility data sets, we contribute practical tools for researchers in the human mobility prediction domain

In Search of Signature Pedagogies for Teacher Education: The Critical Case of Kodály-Inspired Music Teacher Education

The purposes of this study are to identify the features of Kodály-inspired music teacher education programs that either confirm or refute the notion that signature pedagogies (Shulman, 2005 a, b, c) are present in this form of teacher education and to identify whether and how philosophical, pedagogical, and institutional influences support such pedagogies. Signature pedagogies are shared modes of teaching that are distinct to a specific profession. These pedagogies, based in the cognitive, practical, and normative apprenticeships of professional preparation, dominate the preparation programs of a profession, both within and across institutions. This study employs a collective case study design to examine Kodály-inspired teacher education programs, specifically those endorsed by the Organization of American Kodály Educators (OAKE). This study serves as a critical test of the applicability of the construct of signature pedagogies to teacher education. Because these programs purport to hold shared philosophical and pedagogical ideals and are governed by an endorsing body (OAKE), signature pedagogies ought to be present in these programs if they are present in any teacher education programs. Embedded in this collective case are: (1) a history of Kodály-inspired pedagogy and its adoption and adaptation in the U.S., (2) case studies of two prominent and influential OAKE-endorsed Kodály-inspired teacher education programs, and (3) case studies of four to five faculty in each of these programs. Data sources include primary and secondary texts and documents, observations of the various events and activities that occur as a part of Kodály-inspired teacher education programs, and focus group and individual interviews with program faculty and students. This study finds that the two case sites possess four signature pedagogies: (1) demonstration teaching, (2) master class teaching, (3) discovery learning, and (4) the music literature collection and retrieval system. These pedagogies appear to be inextricably tethered to the contexts, professional body (OAKE), and work of Kodály-inspired music educators though multiple complex linkages. The study closes by assessing the applicability and usefulness of the construct for the discourses and study of teacher education and by offering revisions to the construct that may help to improve the construct's usefulness in future research

Organization of the mitochondrial genomes of whiteflies, aphids, and psyllids (Hemiptera, Sternorrhyncha)

BACKGROUND: With some exceptions, mitochondria within the class Insecta have the same gene content, and generally, a similar gene order allowing the proposal of an ancestral gene order. The principal exceptions are several orders within the Hemipteroid assemblage including the order Thysanoptera, a sister group of the order Hemiptera. Within the Hemiptera, there are available a number of completely sequenced mitochondrial genomes that have a gene order similar to that of the proposed ancestor. None, however, are available from the suborder Sternorryncha that includes whiteflies, psyllids and aphids. RESULTS: We have determined the complete nucleotide sequence of the mitochondrial genomes of six species of whiteflies, one psyllid and one aphid. Two species of whiteflies, one psyllid and one aphid have mitochondrial genomes with a gene order very similar to that of the proposed insect ancestor. The remaining four species of whiteflies had variations in the gene order. In all cases, there was the excision of a DNA fragment encoding for cytochrome oxidase subunit III(COIII)-tRNA(gly)-NADH dehydrogenase subunit 3(ND3)-tRNA(ala)-tRNA(arg)-tRNA(asn )from the ancestral position between genes for ATP synthase subunit 6 and NADH dehydrogenase subunit 5. Based on the position in which all or part of this fragment was inserted, the mitochondria could be subdivided into four different gene arrangement types. PCR amplification spanning from COIII to genes outside the inserted region and sequence determination of the resulting fragments, indicated that different whitefly species could be placed into one of these arrangement types. A phylogenetic analysis of 19 whitefly species based on genes for mitochondrial cytochrome b, NADH dehydrogenase subunit 1, and 16S ribosomal DNA as well as cospeciating endosymbiont 16S and 23S ribosomal DNA indicated a clustering of species that corresponded to the gene arrangement types. CONCLUSIONS: In whiteflies, the region of the mitochondrial genome consisting of genes encoding for COIII-tRNA(gly)-ND3-tRNA(ala)-tRNA(arg)-tRNA(asn )can be transposed from its ancestral position to four different locations on the mitochondrial genome. Related species within clusters established by phylogenetic analysis of host and endosymbiont genes have the same mitochondrial gene arrangement indicating a transposition in the ancestor of these clusters

RRL: A Rich Representation Language for the Description of Agent Behaviour in NECA

In this paper, we describe the Rich Representation Language (RRL) which is used in the NECA system. The NECA system generates interactions between two or more animated characters. The RRL is a formal framework for representing the information that is exchanged at the interfaces between the various NECA system modules

Gravitational Wave Spectrum Induced by Primordial Scalar Perturbations

We derive the complete spectrum of gravitational waves induced by primordial scalar perturbations ranging over all observable wavelengths. This scalar-induced contribution can be computed directly from the observed scalar perturbations and general relativity and is, in this sense, independent of the cosmological model for generating the perturbations. The spectrum is scale-invariant on small scales, but has an interesting scale-dependence on large and intermediate scales, where scalar-induced gravitational waves do not redshift and are hence enhanced relative to the background density of the Universe. This contribution to the tensor spectrum is significantly different in form from the direct model-dependent primordial tensor spectrum and, although small in magnitude, it dominates the primordial signal for some cosmological models. We confirm our analytical results by direct numerical integration of the equations of motion.Comment: 19 pages, 5 figure

Protecting the Environment Using Integrated Weed Management in Lawns

4 pp., 4 photosIntegrated Pest Management (IPM) can be used to control weeds, keep lawns healthy and protect the environment. This publication explains the steps to take in an IPM program and the importance of calibrating equipment and making proper calculations when pesticides need to be applied

Suggestions for Weed Control in Corn.

22 p

Taboo tattoos? A study of the gendered effects of body art on consumers' attitudes toward visibly tattooed front line staff

The purpose of this experiment is to examine the gendered effects of body art on consumers’ attitudes toward visibly tattooed employees. We analyse the reaction of 262 respondents with exposure to male and female front line staff in two distinct job contexts: a surgeon and an automobile mechanic. The results demonstrate differences on three dimensions: a) job context, b) sex of face and c) stimulus (i.e., tattooed or not). We demonstrate significant interaction effects on those three dimensions, and our findings point to the intersectionality of gender-based and tattoo-based discrimination. Consumers have a negative reaction to body art, but perceptions of tattoos on male and female front line staff differ significantly. A key marketing challenge is how to balance employees’ individual rights to self-expression and at the same time cater to consumers’ expectations regarding appearance of staff. Our study forms the basis for this debate that is only just emerging.PostprintPeer reviewe