The work-family balance experiences of production couples operating Chinese Cut, Make and Trim factories in Newcastle, South Africa

The purpose of this study was to develop a deep understanding into the unique work family balance experiences of women in production couples in cut, make and trim factories in Newcastle, South Africa. A production couple is first and foremost a business partnership that involves joint ownership of a clothing factory, however the relationship is also a strategy the women use to satisfy their emotional needs and over time the relationship plays an important role in their return migration intention. Using a phenomenological research design, eight in depth semi-structured interviews were conducted with women in a production couple. Though the study set out to explore both the male and female partners, all the male partners eventually declined, citing Covid-19 related reasons such as having the only male in the researcher network dropping out, significantly lowering the likelihood of recruiting willing male participants. A potential reason for this is that men in Chinese culture are expected to carry the family name and with the persisting patriarchal gender roles (Sun & Chen, 2014), they are confronted with greater risk of losing face if exposed that they are in this type of relationship. Thematic analysis conducted on the data revealed three key themes: (1) Factors affecting the work-family balance of women in production couples, (2) Transnational care practices and, (3) Boundary management practices used by the women to maintain work-family balance. The findings challenged the nuclear family ideal and contributed new knowledge on how work family balance is perceived and maintained from a transnational perspective

DCT-domain spatial transcoding using generalized DCT decimation

[[abstract]]In this paper, we propose a generalized DCT-domain spatial downscaling scheme to improve the visual quality. We analyze the filtering performances and computational complexities of the proposed scheme and the pixel-domain downscaling schemes. The analyses show that the proposed scheme can reduce the aliasing artifact compared to the existing schemes, while the computational complexity may be increased. We also integrate the proposed decimation scheme into the cascaded DCT-domain transcoder for spatial downscaling of a pre-encoded video into its quarter size. Experiments show the proposed approach can achieve better visual quality than the existing schemes.[[fileno]]2030144030019[[department]]電機工程學

Shape restricted regression with random Bernstein polynomials

Shape restricted regressions, including isotonic regression and concave regression as special cases, are studied using priors on Bernstein polynomials and Markov chain Monte Carlo methods. These priors have large supports, select only smooth functions, can easily incorporate geometric information into the prior, and can be generated without computational difficulty. Algorithms generating priors and posteriors are proposed, and simulation studies are conducted to illustrate the performance of this approach. Comparisons with the density-regression method of Dette et al. (2006) are included.Comment: Published at http://dx.doi.org/10.1214/074921707000000157 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

H. 264 Error Resilience Coding Based on Multihypothesis Motion Compensated Prediction

[[abstract]]In this paper, we propose efficient schemes for enhancing the error robustness of multi-hypothesis motion-compensate predictive (MHMCP) coder without sacrificing the coding efficiency significantly. The proposed schemes utilize the concept of reference picture interleaving and data partitioning to make the MHMCP-coded video more resilient to channel errors, especially for burst channel error. Besides, we also propose a scheme of integrating adaptive intra-refresh into the proposed MHMCP coder to further improve the error recovery speed. Extensive simulation results show that the proposed methods can effectively and quickly mitigate the error propagation and the penalty on coding efficiency for clean channels due to the inserted error resilience features is rather minor[[fileno]]2030144030009[[department]]電機工程學

Implementation of connection scan algorithm in tourism intermodal transportation journey planner: a case study

Accessibility to tourist destinations is an important component in a tourism system, especially for natural tourist destinations located in suburban areas. Good linkage of travel information and physical connections with local transportation services for intercity travel can facilitate more people to travel and promote national tourism destinations. This research takes the popular national tourism destinations and their public transportation service in Taiwan as a research object due to the unavailability of integrated public transport information service. Free Independent Travelers (FIT) demand is growing. This research aims to integrate intermodal public transportation information to support FIT by proposing a seamless way journey planner. In this scenario, the journey planner requires timetable data as input. The Connection Scan Algorithm is used to find the earliest arrival time routes at their destinations. This journey planner is built in PHP language and can complement the official tourism travel information website by Tourism Bureau, MOTC. Hence, the FIT could get the quickest routes to reach the destinations without compiling the public transportation information provided independently

Using affinity set on mining the necessity of computed tomography scanning

Computed tomography (CT) is a medical imaging method of tomography. Digital geometry processing is used to generate a three-dimensional image of the inside of a patient from a large series of two-dimensional X-ray images taken around a single axis of rotation. The scanning ofCT has become an important tool in medical imaging to supplement X-rays and medical ultrasonography. Although it is expensive, it is the best tool to diagnose a large number of different disease entities; especially, for the trauma patients in emergency room. In this study, the trauma patients, who were treated by the CT scanning are collected in order to discover the critical knowledge; that is, what characteristics of trauma patients would lead to the necessity of CT scanning? The data mining model of affinity set and neural network (NN) are both used for resolution and comparison. Finally, studying results show that he affinity model performs better than the NN model, but the collected data lacks the explanatory power in practices. Thus, a further research is necessary

2-(1H-Pyrrolo­[2,3-b]pyridin-2-yl)pyridine

In the title compound, C12H9N3, the dihedral angle between the pyridine and aza­indole rings is 6.20 (2)°. In the crystal, pairs of N—H⋯N hydrogen bonds link mol­ecules into inversion dimers

Hedonic Values And Utilitarian Values As Predicators Of Social Media Participation

This research proposes a model to investigate the behavior of posting articles and the continued use of social media via Babin’s value perspective. The antecedents of values are web quality and users’ emotions. The model was tested with PLS-Graph software based on its structural equation modeling approach. Data was gained from 310 users. The results revealed that antecedents have a strong impact on user values, which in turn influences users’ intention to post articles and continue to use social media. Several implications for research and practice have been derived from these findings

The copepods in a collection from the southern coast of Oregon, 1963

Plankton samples for this present study were collected from an area off the southern Oregon coast, extending westward to about 83 kilometers offshore. Over this sampling area, 41 species of adult copepods were identified, including representatives of 26 genera and 17 families. The total abundance averaged 550/m³. Population densities of copepods as a group were found higher inshore than offshore and this distribution was largely determined by four dominant species, that is, Oithona similis, Pseudocalanus minutus, Acartia longiremis, and Acartia clausi. They accounted for approximately 81% of the total copepod abundance. Species diversity had a tendency to increase with distance from the coast. This could be due to the possibilities that the sampling depth was increased offshore, or that the living environment was more stable offshore than inshore. Rank-correlation analysis of the four dominant species, fish eggs, copepod nauplii, euphausiids, and Eucalanus bungii suggest that the positively correlated category includes several pairs, Oithona similis to Pseudocalanus minutus, O. sirnilis to Acartia clausi, A. longiremis to P. minutus, fish eggs to O. similis, A. longiremis to A. clausi, O. similis to copepod nauplii, and fish eggs to copepod nauplii. The negatively correlated category includes three pairs, euphausiids to copepod nauplii, euphausiids to fish eggs, and euphaus lids to O. similis. Results from the correlation analysis of the dominant species relative to temperature, salinity, and distance from shore show that no significant relationship was apparent except that the occurrence of P. minutus was negatively correlated to distance from shore

Missing data treatment and data fusion toward travel time estimation for ATIS

[[abstract]]This study develops a travel time estimation process by integrating a missing data treatment and data-fusion-based approaches. In missing data treatment, this study develops a grey time-series model and a grey-theory-based pseudo-nearest-neighbor method to recover, respectively, temporal and spatial missing values in traffic detector data sets. Both spatial and temporal patterns of traffic data are also considered in travel time data fusion. In travel time data fusion, this study presents a speed-based link travel time extrapolation model for analytical travel time estimation and further develops a recurrent neural network (RNN) integrated with grey models for real-time travel time estimation. In the case study, field data from the national freeway no. 1 in Taiwan is used as a case study for testing the proposed models. Study results showed that the grey-theory-based missing data treatment models were accurate for recovering missing values. The grey-based RNN models were capable of accurately predicting travel times. Consequently, the results of this study indicated that the proposed missing data treatment and data fusion approaches can ensure the accuracy of travel time estimation with incomplete data sets, and are therefore suited to implementation for ATIS.[[notice]]補正完