Simultaneous mobile sink allocation in home environments with applications in mobile consumer robotics

This paper presents a novel mobile sink area allocation scheme for consumer based mobile robotic devices with a proven application to robotic vacuum cleaners. In the home or office environment, rooms are physically separated by walls and an automated robotic cleaner cannot make a decision about which room to move to and perform the cleaning task. Likewise, state of the art cleaning robots do not move to other rooms without direct human interference. In a smart home monitoring system, sensor nodes may be deployed to monitor each separate room. In this work, a quad tree based data gathering scheme is proposed whereby the mobile sink physically moves through every room and logically links all separated sub-networks together. The proposed scheme sequentially collects data from the monitoring environment and transmits the information back to a base station. According to the sensor nodes information, the base station can command a cleaning robot to move to a specific location in the home environment. The quad tree based data gathering scheme minimizes the data gathering tour length and time through the efficient allocation of data gathering areas. A calculated shortest path data gathering tour can efficiently be allocated to the robotic cleaner to complete the cleaning task within a minimum time period. Simulation results show that the proposed scheme can effectively allocate and control the cleaning area to the robot vacuum cleaner without any direct interference from the consumer. The performance of the proposed scheme is then validated with a set of practical sequential data gathering tours in a typical office/home environment.

Micro-abrasion of flint artefacts by mobile sediments: a taphonomic approach

Fluvial redeposition of stone artifacts is a major complicating factor in the interpretation of Lower Palaeolithic open-air archaeological sites. However, the microscopic examination of lithic surfaces may provide valuable background information on the transport history of artifacts, particularly in low energy settings. Replica flint artifacts were therefore abraded in an annular flume and examined with a scanning electron microscope. Results showed that abrasion time, sediment size, and artifact transport mode were very sensitive predictors of microscopic surface abrasion, ridge width, and edge damage (p < 0.000). These results suggest that patterns of micro-abrasion of stone artifacts may enhance understanding of archaeological assemblage formation in fluvial contexts

Mobile phones and radios: effects on transactions costs and market participation for households in Northern Ghana

The literature on agricultural markets suggests that transactions costs are the main obstacles preventing households from participating in agricultural markets. We examine the impact of the recent massive penetration of information communication technologies (ICTs), particularly mobile phones and radios, in developing countries to investigate the role of information in economic transactions and participation in food crop markets. To fully capture market participation behaviours, the current theoretical framework on market participation and transactions costs is extended to include those households that sell and buy in the same time period. We correct for endogeneity and selectivity throughout our models. We used a novel dataset of 393 households in northern Ghana with detailed information on market transactions and ICTs usage. Results show that receiving market information via mobile phones has a positive and significant impact on market participation, with a greater impact for households with a surplus of food crops. We find that radios have a larger impact on the quantity traded. This may reflect the nature of mobile phones in reducing searching costs, whereas radios provide an updated and regular flow of information which affects the pattern of crops consumed and sold. We also emphasise that the most significant factor is how ICTs are used, rather than their ownership.

Student perceptions of iPads as mobile learning devices for fieldwork

This paper reports findings from six field courses about student’s perceptions of iPads as mobile learning devices for fieldwork. Data were collected through surveys and focus groups. The key findings suggest that the multi-tool nature of the iPads and their portability were the main strengths. Students had some concerns over the safety of the iPads in adverse weather and rugged environments, though most of these concerns were eliminated after using the devices with protective cases. Reduced connectivity was found to be one of the main challenges for mobile learning. Finally, students and practitioners views of why they used the mobile devices for fieldwork did not align.

Using mobile devices to enhance undergraduate field research

Mobile devices can enhance undergraduate research projects and students’ research capabilities. The use of mobile devices such as tablet computers will not automatically make undergraduates better researchers, but their use should make investigations, writing, and publishing more effective and may even save students time. We have explored some of the possibilities of using “tablets” and “smartphones” to aid the research and inquiry process in geography and bioscience fieldwork. We provide two case studies as illustration of how students working in small research groups use mobile devices to gather and analyze primary data in field-based inquiry. Since April 2010, Apple’s iPad has changed the way people behave in the digital world and how they access their music, watch videos, or read their email much as the entrepreneurs Steve Jobs and Jonathan Ive intended. Now with “apps” and “the cloud” and the ubiquitous references to them appearing in the press and on TV, academics’ use of tablets is also having an impact on education and research. In our discussion we will refer to use of smartphones such as the iPhone, iPod, and Android devices under the term “tablet”. Android and Microsoft devices may not offer the same facilities as the iPad/iphone, but many app producers now provide versions for several operating systems. Smartphones are becoming more affordable and ubiquitous (Melhuish and Falloon 2010), but a recent study of undergraduate students (Woodcock et al. 2012, 1) found that many students who own smartphones are “largely unaware of their potential to support learning”. Importantly, however, students were found to be “interested in and open to the potential as they become familiar with the possibilities” (Woodcock et al. 2012). Smartphones and iPads could be better utilized than laptops when conducting research in the field because of their portability (Welsh and France 2012). It is imperative for faculty to provide their students with opportunities to discover and employ the potential uses of mobile devices in their learning. However, it is not only the convenience of the iPad or tablet devices or smartphones we wish to promote, but also a way of thinking and behaving digitally. We essentially suggest that making a tablet the center of research increases the connections between related research activities.

Bio-inspired ant colony optimization based clustering algorithm with mobile sinks for applications in consumer home automation networks

With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.

Ability of students to recognize the relationship between using mobile apps for learning during fieldwork and the development of graduate attributes

The increasing importance of employability in Higher Education curricula and the prevalence of using mobile devices for fieldbased learning prompted an investigation into student awareness of the relationship between the use of mobile apps for learning and the development of graduate attributes (GAs) (and the link to employability). The results from post-fieldwork focus groups from four field courses indicated that students could make clear links between the use of a variety of mobile apps and graduate attribute development. The study suggests a number of mobile apps can align simultaneously with more than one graduate attribute. Furthermore, prior experience and the context of use can influence students’ perceptions of an app and its link with different GAs.

Effectiveness of mobile apps in teaching field-based identification skills

It has been suggested that few students graduate with the skills required for many ecological careers, as field-based learning is said to be in decline in academic institutions. Here, we asked if mobile technology could improve field-based learning, using ability to identify birds as the study metric. We divided a class of ninety-one undergraduate students into two groups for field-based sessions where they were taught bird identification skills. The first group has access to a traditional identification book and the second group were provided with an identification app. We found no difference between the groups in the ability of students to identify birds after three field sessions. Furthermore, we found that students using the traditional book were significantly more likely to identify novel species. Therefore, we find no evidence that mobile technology improved students’ ability to retain what they experienced in the field; indeed, there is evidence that traditional field guides were more useful to students as they attempted to identify new species. Nevertheless, students felt positively about using their own smartphone devices for learning, highlighting that while apps did not lead to an improvement in bird identification ability, they gave greater accessibility to relevant information outside allocated teaching times.

Moving on in Neolithic studies: understanding mobile lives

Mobility is a fundamental facet of being human and should be central to archaeology. Yet mobility itself and the role it plays in the production of social life, is rarely considered as a subject in its own right. This is particularly so with discussions of the Neolithic people where mobility is often framed as being somewhere between a sedentary existence and nomadic movements. This volume examines the importance and complexities of movement and mobility, whether on land or water, in the Neolithic period. It uses movement in its widest sense, ranging from everyday mobilities – the routines and rhythms of daily life – to proscribed mobility, such as movement in and around monuments, and occasional and large-scale movements and migrations around the continent and across seas. Papers are roughly grouped and focus on ‘mobility and the landscape’, ‘monuments and mobility’, ‘travelling by water’, and ‘materials and mobility’. Through these themes the volume considers the movement of people, ideas, animals, objects, and information, and uses a wide range of archaeological evidence from isotope analysis; artefact studies; lithic scatters and assemblage diversity.

Mobile sink based fault diagnosis scheme for wireless sensor networks

Network diagnosis in Wireless Sensor Networks (WSNs) is a difficult task due to their improvisational nature, invisibility of internal running status, and particularly since the network structure can frequently change due to link failure. To solve this problem, we propose a Mobile Sink (MS) based distributed fault diagnosis algorithm for WSNs. An MS, or mobile fault detector is usually a mobile robot or vehicle equipped with a wireless transceiver that performs the task of a mobile base station while also diagnosing the hardware and software status of deployed network sensors. Our MS mobile fault detector moves through the network area polling each static sensor node to diagnose the hardware and software status of nearby sensor nodes using only single hop communication. Therefore, the fault detection accuracy and functionality of the network is significantly increased. In order to maintain an excellent Quality of Service (QoS), we employ an optimal fault diagnosis tour planning algorithm. In addition to saving energy and time, the tour planning algorithm excludes faulty sensor nodes from the next diagnosis tour. We demonstrate the effectiveness of the proposed algorithms through simulation and real life experimental results.

The R2 mobile element of Rhynchosciara americana: Molecular, cytological and dynamic aspects

Ribosomal RNA genes are encoded by large units clustered (18S, 5S, and 28S) in the nucleolar organizer region in several organisms. Sometimes additional insertions are present in the coding region for the 28S rDNA. These insertions are specific non-long terminal repeat retrotransposons that have very restricted integration targets within the genome. The retrotransposon present in the genome of Rhynchosciara americana, RaR2, was isolated by the screening of a genomic library. Sequence analysis showed the presence of conserved regions, such as a reverse transcriptase domain and a zinc finger motif in the amino terminal region. The insertion site was highly conserved in R. americana and a phylogenetic analysis showed that this element belongs to the R2 clade. The chromosomal localization confirmed that the RaR2 mobile element was inserted into a specific site in the rDNA gene. The expression level of RaR2 in salivary glands during larval development was determined by quantitative RT-PCR, and the increase of relative expression in the 3P of the fourth instar larval could be related to intense gene activity characteristic of this stage. 5`-Truncated elements were identified in different DNA samples. Additionally, in three other Rhynchosciara species, the R2 element was present as a full-length element.

A Floating-point Extended Kalman Filter Implementation for Autonomous Mobile Robots

Localization and Mapping are two of the most important capabilities for autonomous mobile robots and have been receiving considerable attention from the scientific computing community over the last 10 years. One of the most efficient methods to address these problems is based on the use of the Extended Kalman Filter (EKF). The EKF simultaneously estimates a model of the environment (map) and the position of the robot based on odometric and exteroceptive sensor information. As this algorithm demands a considerable amount of computation, it is usually executed on high end PCs coupled to the robot. In this work we present an FPGA-based architecture for the EKF algorithm that is capable of processing two-dimensional maps containing up to 1.8 k features at real time (14 Hz), a three-fold improvement over a Pentium M 1.6 GHz, and a 13-fold improvement over an ARM920T 200 MHz. The proposed architecture also consumes only 1.3% of the Pentium and 12.3% of the ARM energy per feature.

Semantic mapping using mobile robots

Robotic mapping is the process of automatically constructing an environment representation using mobile robots. We address the problem of semantic mapping, which consists of using mobile robots to create maps that represent not only metric occupancy but also other properties of the environment. Specifically, we develop techniques to build maps that represent activity and navigability of the environment. Our approach to semantic mapping is to combine machine learning techniques with standard mapping algorithms. Supervised learning methods are used to automatically associate properties of space to the desired classification patterns. We present two methods, the first based on hidden Markov models and the second on support vector machines. Both approaches have been tested and experimentally validated in two problem domains: terrain mapping and activity-based mapping.