Adaptive Nonparametric Image Parsing

In this paper, we present an adaptive nonparametric solution to the image parsing task, namely annotating each image pixel with its corresponding category label. For a given test image, first, a locality-aware retrieval set is extracted from the training data based on super-pixel matching similarities, which are augmented with feature extraction for better differentiation of local super-pixels. Then, the category of each super-pixel is initialized by the majority vote of the $k$-nearest-neighbor super-pixels in the retrieval set. Instead of fixing $k$ as in traditional non-parametric approaches, here we propose a novel adaptive nonparametric approach which determines the sample-specific k for each test image. In particular, $k$ is adaptively set to be the number of the fewest nearest super-pixels which the images in the retrieval set can use to get the best category prediction. Finally, the initial super-pixel labels are further refined by contextual smoothing. Extensive experiments on challenging datasets demonstrate the superiority of the new solution over other state-of-the-art nonparametric solutions.Comment: 11 page

Synthesis and reactions of β-diketiminato heavy group 14 metal alkoxides and phosphanides

Some low-valent, three-coordinated β-diketiminato heavy group 14 metal complexes have been synthesised and their reactions examined. Initially, our attention is focused on several β-diketiminatolead(II) alkoxides. The lead(II) alkoxides show different basic and nucleophilic reactivities from transition metal analogues. For example, the reaction between the lead(II) tert-butoxide and methyl iodide proceeds only under forcing conditions to give the lead(II) iodide and methyl tert-butyl ether. However, facile reversible carbon dioxide insertion into the lead-oxygen bond is observed. To investigate the steric effect of the bulky β-diketiminato ligand, compounds with various aromatic groups attached to nitrogen have been made. When either [(BDIPh)PbCl] (BDIPh = [HC{C(Me)N(C6H5)}2]−) or [(BDIIPP)PbCl] (BDIIPP = [HC{C(Me)N(4-iPrC6H4)}2]−) was treated with potassium tert-butoxide, the reactions gave the unexpected bis[β-diketiminato]lead(II) complexes. However, treatment of [(BDIDMP)PbCl] (BDIDMP = [HC{C(Me)N(2,6-Me2C6H3)}2]−) with AgOTf led to the expected β-diketiminatolead(II) triflate. These results suggest that the ortho-substituent on the N-aryl groups in the β-diketiminato ligand plays an important role in influencing the formation of bis[β-diketiminato]lead(II) complexes. A series of β-diketiminato heavy group 14 metal phosphanides was synthesised. The phosphorus is pyramidally coordinated in the compounds containing diphenyl- or dicyclohexylphosphanido ligands. In contrast, the geometry at phosphorus is planar in the germanium(II) and tin(II) bis(trimethylsilyl)phosphanides. The phosphorus in the lead(II) bis(trimethylsilyl)phosphanide is pyramidally coordinated. The observed conformations may be explained by the steric congestion from the β-diketiminato ligand and electronic effects in the phosphanido ligand. Reactions of the phosphanido complexes with one equivalent of elemental chalcogen give phosphinochalcogenoito complexes. Further reaction with elemental chalcogen gives phosphinodichalcogenoato complexes. In contrast, treatment of the germanium(II) dicyclohexylphosphanide with elemental chalcogen leads to the formation of germanium(IV) chalcogenide. The presence of NMR-active nuclei in these complexes makes possible detailed spectroscopic analysis

Gain and Loss in System Switching: A Behavioral Economics View to Understand the Joint Effects of System Usage Performance on User Satisfaction

Information systems acceptance has long been an interesting topic for both researchers and managers. It is necessary to understand user’s attitudes and behaviors toward an information system so as to evaluate the consequence of system implementation. Different from previous research, this study investigates user acceptance toward a newly introduced system from a behavioural economics perspective. Specifically, the study targets the effects of system usage outcomes on user satisfaction in a mandatory context where an old system is replaced by a new one. Based on the Prospect Theory, we argue that users evaluate the new system according to their perceptions from a value function, comparing their current system usage status with a reference point in terms of gain and loss. By describing a three-stage system switching process, this study unpacks how the usage outcomes of both the old and the new system and their contrasts affect perceived value toward the new system, which positively predicts user satisfaction. The system usage performances related to both the old and the new system are incorporated in the research model. Their joint effects, the main and the interacting effects, on user satisfaction with the new system are explicitly explored and explained. Findings of the study enable firms to better understand a system switching process and to design more effective managerial interventions for improving new system acceptance

Personalization: Is It Effective on New and Repeat Users?

This work studies personalization from the perspective of human computer interaction. The objectives are to examine the effects of various personalization strategies on users’ information processing and decision-making. We commence by reviewing the literature on personalization in the five research domains defined by Banker and Kauffman (2004), and then highlight the debates regarding the effectiveness of personalization in influencing users’ decision-making. To bridge the gap between the proliferation of personalization technologies and the uncertainty of their effectiveness, this work addresses the following research question: What are the effects of different personalization strategies on users’ information processing? We examine two common personalization strategies: preference matching and set size of personalized content. We explore how these strategies affect users’ decision-making. An information processing model rooted in the Heuristic-Systematic Model is developed. We formulate 10 hypotheses on the relationship between personalization strategies and users’ information processing. Data collected from two online field studies are used to assess the validity of the proposed hypotheses. The results of the studies indicate that personalization can capture users’ attention, and, personalization is also associated with an increase in users’ exploration of other content. This effect becomes less salient when the amount of non-personalized content increases

Technology Features, Empowering Perceptions, and Voicing Behavior on Microblog

Recently, we have observed rapid growth of individual daily technologies such as microblogs, and the technology’s influence on people’s social life. To investigate such self-determined technology usage, we choose an empowerment perspective as our theoretical lens, because the empowerment concept highlights human beings’ proactive nature. We investigate a specific microblog usage, i.e. publicly voicing personal views on social affairs, which is an initial yet fundamental step in citizen participation. The study reveals that microblog features have transformed the way social news disseminate, and hence influence information quality and users’ social network building. These changes further influence users’ empowerment perceptions through raising users’ perceptions of internal political self-efficacy, autonomy, meaning, and impact. The more empowered users are, the more likely users will voice on microblog. We integrate context into our theorizing, and the empowerment framework allow us to uncover the psychological mechanism through which microblog technology features enable voicing, a specific technology usage

Seeing Human Weight from a Single RGB-D Image

Human weight estimation is useful in a variety of potential applications, e.g., targeted advertisement, entertainment scenarios and forensic science. However, estimating weight only from color cues is particularly challenging since these cues are quite sensitive to lighting and imaging conditions. In this article, we propose a novel weight estimator based on a single RGB-D image, which utilizes the visual color cues and depth information. Our main contributions are three-fold. First, we construct the W8-RGBD dataset including RGB-D images of different people with ground truth weight. Second, the novel sideview shape feature and the feature fusion model are proposed to facilitate weight estimation. Additionally, we consider gender as another important factor for human weight estimation. Third, we conduct comprehensive experiments using various regression models and feature fusion models on the new weight dataset, and encouraging results are obtained based on the proposed features and models

An Affective Model for Unauthorized Sharing of Software

Software piracy has been studied by academics, software firms, law enforcement agents and policy makers for many years. Previous research in software piracy either did not differentiate between unauthorized copying and unauthorized sharing, or focused only on unauthorized copying. We believe the motivating factors behind the two behaviors are quite different because beneficiaries of the behaviors are different. In this paper, we consider unauthorized sharing as a kind of helping behavior and draw on relevant literature to see if the motivations behind unauthorized sharing can be better appreciated from an affective perspective. We tested the affective model of unauthorized sharing based on empirical data obtained from a large-scale survey. We found from the survey that both perceived affordability and perceived convenience could arouse sympathy or annoyance with the unauthorized copier, and their effects were mediated by perceived controllability of the need of unauthorized copying. Our results support the strong effects of affective factors on the moral obligation of unauthorized sharing

Online Community Citizenship Behaviors (OCCB) and Community Sustainability: An Examination of Benefit Creating Behaviors in Online Communities

Online communities now reach various aspects of people’s work and life; and both practitioners and researchers have recognized their importance. However, among the tens of thousands of online communities, a considerable portion of them gradually become lifeless, with little ongoing conversation and few active members. Since online communities largely rely on members’ participations to generate benefits, it is important to identify the behaviors that contribute to community sustainability. Specifically, the research questions are: 1) Besides knowledge contribution, what are the behaviors contributing to online community sustainability? 2) What is the nature of these behaviors? How do they benefit communities? Comparing online communities with organizations and referring to Organization Citizenship Behaviors (OCB), we conceptualize the benefiting creation behaviors as Online Community Citizenship Behaviors (OCCB), which have the following characteristics: 3) Discretionary 4) Beyond personal needs gratification 5) Promote the effective functioning of the online community We then identify the dimensions of OCCB, viewing online communities as complicated social entities which people go to with various needs to be fulfilled. Previous IS research mainly focuses on people’s information needs and examine knowledge sharing. Referring to social psychology studies on human needs and small group interaction analysis, we highlight that people also have social emotional needs, and argue for the importance of social emotional support on community sustainability. Behaviors offering social emotional support contribute to community relationship building, help to attract new members, and attract posts asking for social emotional support. We also examine behaviors related with community norm development and maintenance, such as recognizing other’s contribution, discouraging inappropriate behaviors. These behaviors cultivate community reciprocity norm and a friendly social atmosphere. They create strong bonding among members, retain members, and encourage members to contribute. We also note community participants may leverage other Internet platforms, such as personal blogs, to promote the community. Specifically, members’ recommendations on other platforms may generate publicity for the community and help the community to attract new users, hence we include cross platform community promotion in OCCB. Overall speaking, how to make online community sustainable is a question of both practical and theoretical interest. We address this question through investigating the benefit creating behaviors, i.e. OCCB. The study goes beyond knowledge contribution, and highlights behaviors related with social emotional needs gratifying, group norms forming, and group publicity. We propose that OCCB have positive influence on membership size, attracting posts seeking knowledge and social support, and hence make the community more influential and sustainable in the topical area; and we suggest ways to help community develop sustainably

Using Genetic Programming as a Learning Tool in Discovering Financial Trading Rules

The growth of database systems has called for more advanced information retrieval and knowledge discovery tools. Genetic programming is proposed as one such tool and its characteristics and strengths are discussed in this paper. The application of genetic programming in learning security trading rules is also discussed

Optimum nonuniform transmultiplexer design

This paper considers an optimum nonuniform FIR transmultiplexer design subject to specifications in the frequency domain. Our objective is to minimize the sum of the ripple energy for all the individual filters, subject to the specifications on amplitude and aliasing distortions, and to the passband and stopband specifications for the individual filters. This optimum nonuniform transmultiplexer design problem can be formulated as a quadratic semi-infinite programming problem. The dual parametrization algorithm is extended to the design of this nonuniform transmultiplexer problem. If the lengths of the filters are sufficiently long and the set of decimation integers is compatible, then our algorithm guarantees that the solution obtained will give rise to the global minimum, and the required specifications are satisfied