The study of genetic diversity and population structure of the Korean fleshy shrimp, Fenneropenaeus chinensis, using newly developed microsatellite markers

The fleshy shrimp, Fenneropenaeus chinensis, is the family of Penaeidae and one of the most economically important marine culture species in Korea. However, its genetic characteristics have never been studied. In this study, a total of 240 wild F. chinensis individuals were collected from four locations as follows: Narodo (NRD, n = 60), Beopseongpo (BSP, n = 60), Chaesukpo (CSP, n = 60), and Cheonsuman (CSM, n = 60). Genetic variability and the relationships among four wild F. chinensis populations were analyzed using 13 newly developed microsatellite loci. Relatively high levels of genetic variability (mean allelic richness = 16.87; mean heterozygosity = 0.845) were found among localities. Among the 52 population loci, 13 showed significant deviation from the Hardy–Weinberg equilibrium. Neighbor-joining, principal coordinate, and molecular variance analyses revealed the presence of three subpopulations (NRD, CSM, BSP and CSP), which was consistent with clustering based on genetic distance. The mean observed heterozygosity values of the NRD, CSM, BSP, and CSP populations were 0.724, 0.821, 0.814, and 0.785 over all loci, respectively. These genetic variability and differentiation results of the four wild populations can be applied for future genetic improvement using selective breeding and to design suitable management guidelines for Korean F. chinensis culture.

Social organization of household finance: Understanding artful financial systems in the home

In this paper we discuss results of a field study focused on understanding the ways money and financial issues are handled within family settings. Families develop ‘systems’ or methods through which they coordinate and manage their everyday financial activities. Through an analysis of our fieldwork data collected from fifteen families, we provide several examples of such systems, highlighting their qualities and illustrating how such systems come to support the handling of financial activities in the home. Our results show that these systems are developed with a careful consideration of familial values, relationships and routines; and incorporate the use of physical and digital tools. Consequently, we suggest that design should consider the use and non-use of technology when supporting household financial management, taking into account the richness of families’ existing organically formed practices surrounding financial systems. Finally, our findings point to the fact that financial management in the domestic setting is socially organized and is closely connected to supporting everyday household activities.

R1SVM: A randomised nonlinear approach to large-scale anomaly detection

The problem of unsupervised anomaly detection arises in a wide variety of practical applications. While one-class support vector machines have demonstrated their effectiveness as an anomaly detection technique, their ability to model large datasets is limited due to their memory and time complexity for training. To address this issue for supervised learning of kernel machines, there has been growing interest in random projection methods as an alternative to the computationally expensive problems of kernel matrix construction and sup-port vector optimisation. In this paper we leverage the theory of nonlinear random projections and propose the Randomised One-class SVM (R1SVM), which is an efficient and scalable anomaly detection technique that can be trained on large-scale datasets. Our empirical analysis on several real-life and synthetic datasets shows that our randomised 1SVM algorithm achieves comparable or better accuracy to deep auto encoder and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

R1STM: One-class support tensor machine with randomised kernel

Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

Real-time kinematic positioning over long baselines using triple-frequency BeiDou signals

The BeiDou system is the first global navigation satellite system in which all satellites transmit triple-frequency signals that can provide the positioning, navigation, and timing independently. A benefit of triple-frequency signals is that more useful combinations can be formed, including some extrawide-lane combinations whose ambiguities can generally be instantaneously fixed without distance restriction, although the narrow-lane ambiguity resolution (NL AR) still depends on the interreceiver distance or requires a long time to achieve. In this paper, we synthetically study decimeter and centimeter kinematic positioning using BeiDou triple-frequency signals. It starts with AR of two extrawide-lane signals based on the ionosphere-free or ionosphere-reduced geometry-free model. For decimeter positioning, one can immediately use two ambiguity-fixed extrawide-lane observations without pursuing NL AR. To achieve higher accuracy, NL AR is the necessary next step. Despite the fact that long-baseline NL AR is still challenging, some NL ambiguities can indeed be fixed with high reliability. Partial AR for NL signals is acceptable, because as long as some ambiguities for NL signals are fixed, positioning accuracy will be certainly improved.With accumulation of observations, more and more NL ambiguities are fixed and the positioning accuracy continues to improve. An efficient Kalman-filtering system is established to implement the whole process. The formulated system is flexible, since the additional constraints can be easily applied to enhance the model's strength. Numerical results from a set of real triple-frequency BeiDou data on a 50 km baseline show that decimeter positioning is achievable instantaneously.With only five data epochs, 84% of NL ambiguities can be fixed so that the real-time kinematic accuracies are 4.5, 2.5, and 16 cm for north, east, and height components (respectively), while with 10 data epochs more than 90% of NL ambiguities are fixed, and the rea- -time kinematic solutions are improved to centimeter level for all three coordinate components.

Towards an analysis framework of technology habituation by older users

Smart everyday objects could support the wellbeing, independent living and social connectedness of ageing people, but their successful adoption depends upon them fitting with their skills, values and goals. Many technologies fail in this respect. Our work is aimed at designs that engage older people by building on their individual affective attachment to habituated objects and leveraging, from a participatory design perspective, the creative process through which people continuously adapt their homes and tools to their own lifestyle. We contribute a novel analytic framework based on an analysis of related research on appropriation and habituated objects. It identifies steps in appropriation from inspection to performance and habituation. We test this framework with the preliminary testing of an augmented habituated object, a messaging kettle. While only used in one home so far, its daily use has provoked many thoughts, scenarios and projections about use by friends, both practical, utopian and dystopian.

The enhanced Russell-based directional distance measure with undesirable outputs: Numerical example considering CO2 emissions

Following the spirit of the enhanced Russell graph measure, this paper proposes an enhanced Russell-based directional distance measure (ERBDDM) model for dealing with desirable and undesirable outputs in data envelopment analysis (DEA) and allowing some inputs and outputs to be zero. The proposed method is analogous to the output oriented slacks-based measure (OSBM) and directional output distance function approach because it allows the expansion of desirable outputs and the contraction of undesirable outputs. The ERBDDM is superior to the OSBM model and traditional approach since it is not only able to identify all the inefficiency slacks just as the latter, but also avoids the misperception and misspecification of the former, which fails to identify null-jointness production of goods and bads. The paper also imposes a strong complementary slackness condition on the ERBDDM model to deal with the occurrence of multiple projections. Furthermore, we use the Penn Table data to help us explore our new approach in the context of environmental policy evaluations and guidance for performance improvements in 111 countries.

Vendors' perspectives of coordination in the information technology offshore outsourcing industry : An exploratory study from the Philippines

This study investigates how offshore information technology (IT) service providers (vendors) coordinate work with their clients (employers) in order to succeed in the global IT offshore outsourcing industry. We reviewed literature on coordination studies, interviewed offshore service providers in the Philippines, and used thematic analysis to analyse coordination practices from the point of view of these individual vendors in a newly industrialized country. We used Olson and Olson's framework on 'collaboration at a distance' as a lens to structure the results. The study provides an understanding of vendors' individual attitudes towards the coordination of distributed work and draws attention to how differences in power affect the work situation of vendors, and by implication all stakeholders. We offer this insight as a way to enhance existing CSCW frameworks, by imbuing them with the perspective of non-equal relationships. The study found that vendors were generally able to produce outputs that satisfy their clients, however these results were only achieved because individuals were willing to take risks and make sacrifices in their personal lives. The relationship was further characterised by a complex interplay between the client's control of the overall work arrangements and the vendors' ability to establish a level of autonomy in their work practices and their flexible use of coordination tools.