Software testing education and training in Hong Kong

While the use of computer applications is widely spread in every business and, hence, the reliability of software is critical, it is believed that many organizations involved in software development do not take software testing sufficiently seriously as an important task. It is worthwhile to find out how far organizations are carrying out software testing in a systematic and structured manner or still taking on an ad-hoc approach. A survey was conducted to understand the software testing practices and the level of related education and training in Hong Kong. It was found that most testing team members did not have formal training in software testing. University curricula generally did not prepare graduates with enough coverage in software testing. It is proposed that a review of the current software engineering curricula in the universities to examine the coverage of software testing will be useful to the development of quality software. © 2005 IEEE.published_or_final_versio

On the identification of categories and choices for specification-based test case generation

HKU CS Tech Report TR 2004-02The category-partition method and the classification-tree method help construct test cases from specifications. In both methods, an early step is to identify a set of categories (or classifications) and choices (or classes). This is often performed in an ad hoc manner due to the absence of systematic techniques. In this paper, we report and discuss three empirical studies to investigate the common mistakes made by software testers in such an ad hoc approach. The empirical studies serve three purposes: (a) to make the knowledge of common mistakes known to other testers so that they can avoid repeating the same mistakes, (b) to facilitate researchers and practitioners develop systematic identification techniques, and (c) to provide a means of measuring the effectiveness of newly developed identification techniques. Based on the results of our studies, we also formulate a checklist to help testers detect such mistakes. © 2004 Elsevier B.V. All rights reserved.postprin

A Covariate-Adjusted Homogeneity Test with Application to Facial Recognition Accuracy Assessment

Ordinal scores occur commonly in medical imaging studies and in black-box forensic studies \citep{Phillips:2018}. To assess the accuracy of raters in the studies, one needs to estimate the receiver operating characteristic (ROC) curve while accounting for covariates of raters. In this paper, we propose a covariate-adjusted homogeneity test to determine differences in accuracy among multiple rater groups. We derived the theoretical results of the proposed test and conducted extensive simulation studies to evaluate the finite sample performance of the proposed test. Our proposed test is applied to a face recognition study to identify statistically significant differences among five participant groups

A paradox theory lens on proactivity, individual ambidexterity, and creativity:An empirical look

Paradox theory suggests that contradictory demands, like applying current work methods while exploring new ones, should be viewed as dualities with competing and complementary aspects. It advocates for employee ambidexterity, where employees must manage exploitation and exploration. We know little about how personal dispositions affect ambidexterity independently or when interacting with situational factors. Based on a time-lagged survey of 364 employee–supervisor pairs from 74 R&D teams, we found that proactive disposition was positively related to ambidexterity, enhancing creativity. Guided by trait activation theory, we found further that paradoxical supervision and job autonomy enhanced the relationship between proactive disposition and employee ambidexterity and the indirect effect of proactive disposition on creativity via ambidexterity. We discuss these findings' theoretical and practical implications, extending the literature on proactivity, ambidexterity, and paradox theory

Prenatal Diagnosis of Agenesis of the Corpus Callosum and Cerebellar Vermian Hypoplasia Associated with a Microdeletion on Chromosome 1p32

We present the prenatal detection of a 1p32.1p31.3 microdeletion (3.46 Mb) by array comparative genomic hybridization (CGH) associated with fetal agenesis of the corpus callosum (ACC) and cerebellar vermian hypoplasia. Analysis of cultured amniocytes showed a normal karyotype. Our observations strengthen the association between this locus and central nervous system development. In addition, the fetus reported herein underscores the importance of array CGH analysis when ACC is detected prenatally, especially when there are additional central nervous system anomalies, to search for submicroscopic imbalances which can facilitate further management and parental counselling. Moreover, the presence of urinary tract anomalies should alert the clinician to the possibility of a 1p interstitial deletion, although the absence of such does not exclude it. Further reports will help to provide more information on the long-term outcomes of individuals with such microdeletion as there are only limited data.published_or_final_versio

Towards Multi-class Object Detection in Unconstrained Remote Sensing Imagery

Automatic multi-class object detection in remote sensing images in unconstrained scenarios is of high interest for several applications including traffic monitoring and disaster management. The huge variation in object scale, orientation, category, and complex backgrounds, as well as the different camera sensors pose great challenges for current algorithms. In this work, we propose a new method consisting of a novel joint image cascade and feature pyramid network with multi-size convolution kernels to extract multi-scale strong and weak semantic features. These features are fed into rotation-based region proposal and region of interest networks to produce object detections. Finally, rotational non-maximum suppression is applied to remove redundant detections. During training, we minimize joint horizontal and oriented bounding box loss functions, as well as a novel loss that enforces oriented boxes to be rectangular. Our method achieves 68.16% mAP on horizontal and 72.45% mAP on oriented bounding box detection tasks on the challenging DOTA dataset, outperforming all published methods by a large margin (+6% and +12% absolute improvement, respectively). Furthermore, it generalizes to two other datasets, NWPU VHR-10 and UCAS-AOD, and achieves competitive results with the baselines even when trained on DOTA. Our method can be deployed in multi-class object detection applications, regardless of the image and object scales and orientations, making it a great choice for unconstrained aerial and satellite imagery.Comment: ACCV 201

Diabetes and other vascular risk factors in association with the risk of lower extremity amputation in chronic limb-threatening ischemia: a prospective cohort study

BACKGROUND: Patients with diabetes are at increased risk of developing chronic limb-threatening ischemia (CLTI) due to peripheral arterial disease, and this often results in lower extremity amputation (LEA). Little is known of the interaction between diabetes and other vascular risk factors in affecting the risk of CLTI. METHODS: We investigated the association of diabetes, and its interaction with hypertension, body mass index (BMI) and smoking, with the risk of LEA due to CLTI in the population-based Singapore Chinese Health Study. Participants were interviewed at recruitment (1993-1998) and 656 incident LEA cases were identified via linkage with nationwide hospital database through 2017. Multivariate-adjusted Cox proportional hazards models were used to compute hazard ratios (HRs) and 95% CIs for the associations. RESULTS: The HR (95% CI) for LEA risk was 13.41 (11.38-15.79) in participants with diabetes compared to their counterparts without diabetes, and the risk increased in a stepwise manner with duration of diabetes (P for trend < 0.0001). Hypertension and increased BMI independently increased LEA risk in those without diabetes but did not increase the risk in those with diabetes (P for interaction with diabetes ≤ 0.0006). Conversely, current smoking conferred a risk increment of about 40% regardless of diabetes status. CONCLUSIONS: Although diabetes conferred more than tenfold increase in risk of LEA, hypertension and increased BMI did not further increase LEA risk among those with diabetes, suggesting a common mechanistic pathway for these risk factors. In contrast, smoking may act via an alternative pathway and thus confer additional risk regardless of diabetes status

Ribozyme activity modulates the physical properties of RNA–peptide coacervates

Condensed coacervate phases are now understood to be important features of modern cell biology, as well as valuable protocellular models in origin-of-life studies and synthetic biology. In each of these fields, the development of model systems with varied and tuneable material properties is of great importance for replicating properties of life. Here, we develop a ligase ribozyme system capable of concatenating short RNA fragments into long chains. Our results show that the formation of coacervate microdroplets with the ligase ribozyme and poly(L-lysine) enhances ribozyme rate and yield, which in turn increases the length of the anionic polymer component of the system and imparts specific physical properties to the droplets. Droplets containing active ribozyme sequences resist growth, do not wet or spread on unpassivated surfaces, and exhibit reduced transfer of RNA between droplets when compared to controls containing inactive sequences. These altered behaviours, which stem from RNA sequence and catalytic activity, constitute a specific phenotype and potential fitness advantage, opening the door to selection and evolution experiments based on a genotype–phenotype linkage

Comparison of Mutation Patterns in Full-Genome A/H3N2 Influenza Sequences Obtained Directly from Clinical Samples and the Same Samples after a Single MDCK Passage

Human influenza viruses can be isolated efficiently from clinical samples using Madin-Darby canine kidney (MDCK) cells. However, this process is known to induce mutations in the virus as it adapts to this non-human cell-line. We performed a systematic study to record the pattern of MDCK-induced mutations observed across the whole influenza A/H3N2 genome. Seventy-seven clinical samples collected from 2009-2011 were included in the study. Two full influenza genomes were obtained for each sample: one from virus obtained directly from the clinical sample and one from the matching isolate cultured in MDCK cells. Comparison of the full-genome sequences obtained from each of these sources showed that 42% of the 77 isolates had acquired at least one MDCK-induced mutation. The presence or absence of these mutations was independent of viral load or sample origin (in-patients versus out-patients). Notably, all the five hemagglutinin missense mutations were observed at the hemaggutinin 1 domain only, particularly within or proximal to the receptor binding sites and antigenic site of the virus. Furthermore, 23% of the 77 isolates had undergone a MDCK-induced missense mutation, D151G/N, in the neuraminidase segment. This mutation has been found to be associated with reduced drug sensitivity towards the neuraminidase inhibitors and increased viral receptor binding efficiency to host cells. In contrast, none of the neuraminidase sequences obtained directly from the clinical samples contained the D151G/N mutation, suggesting that this mutation may be an indicator of MDCK culture-induced changes. These D151 mutations can confound the interpretation of the hemagglutination inhibition assay and neuraminidase inhibitor resistance results when these are based on MDCK isolates. Such isolates are currently in routine use in the WHO influenza vaccine and drug-resistance surveillance programs. Potential data interpretation miscalls can therefore be avoided by careful exclusion of such D151 mutants after further sequence analysis.published_or_final_versio

Many-shot from Low-shot: Learning to Annotate using Mixed Supervision for Object Detection

Object detection has witnessed significant progress by relying on large, manually annotated datasets. Annotating such datasets is highly time consuming and expensive, which motivates the development of weakly supervised and few-shot object detection methods. However, these methods largely underperform with respect to their strongly supervised counterpart, as weak training signals \emph{often} result in partial or oversized detections. Towards solving this problem we introduce, for the first time, an online annotation module (OAM) that learns to generate a many-shot set of \emph{reliable} annotations from a larger volume of weakly labelled images. Our OAM can be jointly trained with any fully supervised two-stage object detection method, providing additional training annotations on the fly. This results in a fully end-to-end strategy that only requires a low-shot set of fully annotated images. The integration of the OAM with Fast(er) R-CNN improves their performance by $17\%$ mAP, $9\%$ AP50 on PASCAL VOC 2007 and MS-COCO benchmarks, and significantly outperforms competing methods using mixed supervision.Comment: Accepted at ECCV 2020. Camera-ready version and Appendice