管理干部胜任特征评价方法的初步研究

Competency Assessment Method (CAM) is an important technique of Human Resource Management and Development in theory and practice, especially in personnel selection and training. Based on literatures of related fields, the thesis explored the feasibility of CAM in China. The main results found in this study are as follows: 1. Competencies scored in Behavioral Event Interviews (BEI) are not influenced by length of protocol, by performance in the preceding year. Average level and maximal level of complexity correlate significantly with length of protocol. Total competency frequency of outstanding executives is not significantly different from that of typical executives. These results support McCleland's view. But there is significant correlation between length of protocol and competency frequencies, which which is not agreed by McCleland. We found that competency scores using coding standard of average level and maximal level of complexity show more reliability than that using coding standard of competency frequencies. But this isn't confirmed by McCleland. 2. Inter-rater reliability was studied. The results indicated: total Category Agreement (CA) is 55.45%, over 70 percent of 20 competencies of the inter-rater reliability coefficients based on the classical test theory are significantly correlated. G coefficient based on the generalization theory is 0.85697. 3. Study of criterion sample shows that manager's competencies of China's communication enterprise are as follows: Impact and Influence, Organization Commitment, Information Seeking, Achievement Orientation, Team Leadership, Interpersonal Understanding, Initiative, Market Awareness, Self-confidence, Developing Others. This result in similar to the generic competency model of managers presented in Spencer's book. 4. CAM showed more advantages than the method of experts panel judgement.

The Effect of Indexing on the Complexity of Object Recognition

Many current recognition systems use constrained search to locate objects in cluttered environments. Previous formal analysis has shown that the expected amount of search is quadratic in the number of model and data features, if all the data is known to come from a sinlge object, but is exponential when spurious data is included. If one can group the data into subsets likely to have come from a single object, then terminating the search once a "good enough" interpretation is found reduces the expected search to cubic. Without successful grouping, terminated search is still exponential. These results apply to finding instances of a known object in the data. In this paper, we turn to the problem of selecting models from a library, and examine the combinatorics of determining that a candidate object is not present in the data. We show that the expected search is again exponential, implying that naﶥ approaches to indexing are likely to carry an expensive overhead, since an exponential amount of work is needed to week out each of the incorrect models. The analytic results are shown to be in agreement with empirical data for cluttered object recognition.

Determination of heavy metal ions by capillary electrophoresis with contactless conductivity detection after field-amplified sample injection

A method has been developed for determining of heavy metal ions by field-amplified sample injection capillary electrophoresis with contactless conductivity detection. The effects of the 2-N-morpholinoethanesulfonic acid/histidine (MES/His) concentration in the sample matrix, the injection time and organic additives on the enrichment factor were studied. The results showed that MES/His with a low concentration in the sample matrix, an increase of the injection time and the addition of acetonitrile improved the enrichment factor. Four heavy metal ions (Zn2+, Co2+, Cu2+ and Ni2+) were dissolved in deionized water, separated in a 10 mM MES/His running buffer at pH 4.9 and detected by contactless conductivity detection. The detection sensitivity was enhanced by about three orders of magnitude with respect to the non-stacking injection mode. The limits of detection were in the range from 5 nM (Zn2+) to 30 nM (Cu2+). The method has been used to determine heavy metal ions in tap water.

Influence of depression in a sample of people with hallux valgus

Hallux valgus (HV) is a highly-prevalent forefoot deformity associated with progressive subluxation and osteoarthritis of the first metatarsophalangeal joint; it is believed to be associated with depression. The aim of the present study was to determine the association of patients with varying degrees of HV involvement to depression using the Beck Depression Inventory (BDI). The sample consisted of 102 participants (mean age: 45.1±1.6), who attended an outpatient centre where self-report data were recorded. The degree of HV deformity was determined in both feet, and the scores on the BDI were compared. A total of 38.24% of the sample had depression, with an average BDI score of 10.55±12.36 points. There was a statistically-significant association between the degree and presence of HV in both feet (P=0.0001). People with a greater degree of HV deformity in any foot also have a significant increase in depression based on BDI scores, regardless of sex.

Audiences and Receptions of Sexual Violence in Contemporary Cinema

Barkre, M.; Mathijs, E.; Sexton, J.; Egan, K.; Hunter, R. and Selfe, M. (2007). Audiences and Receptions of Sexual Violence in Contemporary Cinema. London: British Board of Film Classification. RAE2008

Appreciating ecological complexity: Habitat contours as a conceptual landscape model

Joern Fischer, David B. Lindermayer, and Ioan Fazey (2004). Appreciating Ecological Complexity: Habitat Contours as a Conceptual Landscape Model. Conservation Biology, 18 (5)pp.1245-1253 RAE2008

A Short History of Computational Complexity

National Science Foundation (CCR-998310); Army Research Office (DAAD19-02-1-0058)

Learning a Family of Detectors

Object detection and recognition are important problems in computer vision. The challenges of these problems come from the presence of noise, background clutter, large within class variations of the object class and limited training data. In addition, the computational complexity in the recognition process is also a concern in practice. In this thesis, we propose one approach to handle the problem of detecting an object class that exhibits large within-class variations, and a second approach to speed up the classification processes. In the first approach, we show that foreground-background classification (detection) and within-class classification of the foreground class (pose estimation) can be jointly solved with using a multiplicative form of two kernel functions. One kernel measures similarity for foreground-background classification. The other kernel accounts for latent factors that control within-class variation and implicitly enables feature sharing among foreground training samples. For applications where explicit parameterization of the within-class states is unavailable, a nonparametric formulation of the kernel can be constructed with a proper foreground distance/similarity measure. Detector training is accomplished via standard Support Vector Machine learning. The resulting detectors are tuned to specific variations in the foreground class. They also serve to evaluate hypotheses of the foreground state. When the image masks for foreground objects are provided in training, the detectors can also produce object segmentation. Methods for generating a representative sample set of detectors are proposed that can enable efficient detection and tracking. In addition, because individual detectors verify hypotheses of foreground state, they can also be incorporated in a tracking-by-detection frame work to recover foreground state in image sequences. To run the detectors efficiently at the online stage, an input-sensitive speedup strategy is proposed to select the most relevant detectors quickly. The proposed approach is tested on data sets of human hands, vehicles and human faces. On all data sets, the proposed approach achieves improved detection accuracy over the best competing approaches. In the second part of the thesis, we formulate a filter-and-refine scheme to speed up recognition processes. The binary outputs of the weak classifiers in a boosted detector are used to identify a small number of candidate foreground state hypotheses quickly via Hamming distance or weighted Hamming distance. The approach is evaluated in three applications: face recognition on the face recognition grand challenge version 2 data set, hand shape detection and parameter estimation on a hand data set, and vehicle detection and estimation of the view angle on a multi-pose vehicle data set. On all data sets, our approach is at least five times faster than simply evaluating all foreground state hypotheses with virtually no loss in classification accuracy.

On the Complexity of Quantum ACC

For any q > 1, let MOD_q be a quantum gate that determines if the number of 1's in the input is divisible by q. We show that for any q,t > 1, MOD_q is equivalent to MOD_t (up to constant depth). Based on the case q=2, Moore has shown that quantum analogs of AC^(0), ACC[q], and ACC, denoted QAC^(0)_wf, QACC[2], QACC respectively, define the same class of operators, leaving q > 2 as an open question. Our result resolves this question, implying that QAC^(0)_wf = QACC[q] = QACC for all q. We also prove the first upper bounds for QACC in terms of related language classes. We define classes of languages EQACC, NQACC (both for arbitrary complex amplitudes) and BQACC (for rational number amplitudes) and show that they are all contained in TC^(0). To do this, we show that a TC^(0) circuit can keep track of the amplitudes of the state resulting from the application of a QACC operator using a constant width polynomial size tensor sum. In order to accomplish this, we also show that TC^(0) can perform iterated addition and multiplication in certain field extensions.

A smart wireless inertial measurement unit system: simplifying & encouraging usage of WIMU technology

Wireless Inertial Measurement Units (WIMUs) combine motion sensing, processing & communications functionsin a single device. Data gathered using these sensors has the potential to be converted into high quality motion data. By outfitting a subject with multiple WIMUs full motion data can begathered. With a potential cost of ownership several orders of magnitude less than traditional camera based motion capture, WIMU systems have potential to be crucially important in supplementing or replacing traditional motion capture and opening up entirely new application areas and potential markets particularly in the rehabilitative, sports & at-home healthcarespaces. Currently WIMUs are underutilized in these areas. A major barrier to adoption is perceived complexity. Sample rates, sensor types & dynamic sensor ranges may need to be adjusted on multiple axes for each device depending on the scenario. As such we present an advanced WIMU in conjunction with a Smart WIMU system to simplify this aspect with 3 usage modes: Manual, Intelligent and Autonomous. Attendees will be able to compare the 3 different modes and see the effects of good andbad set-ups on the quality of data gathered in real time.

Women's help seeking behaviour and the associated influencing factors on self discovery of a breast symptom

To investigate women’s help seeking behavior (HSB) following self discovery of a breast symptom and determine the associated influencing factors. A descriptive correlation design was used to ascertain the help seeking behavior (HSB) and the associated influencing factors of a sample of women (n = 449) with self discovered breast symptoms. The study was guided by the ‘Help Seeking Behaviour and Influencing Factors” conceptual framework (Facione et al., 2002; Meechan et al., 2003, 2002; Leventhal, Brissette and Leventhal, 2003 and O’Mahony and Hegarty, 2009b). Data was collected using a researcher developed multi-scale questionnaire package to ascertain women’s help seeking behavior on self discovery of a breast symptom and determine the factors most associated with HSB. Factors examined include: socio-demographics, knowledge and beliefs (regarding breast symptom; breast changes associated with breast cancer; use of alternative help seeking behaviours and presence or absence of a family history of breast cancer),emotional responses, social factors, health seeking habits and health service system utilization and help seeking behavior. A convenience sample (n = 449 was obtained by the researcher from amongst women attending the breast clinics of two large urban hospitals within the Republic of Ireland. All participants had self-discovered breast symptoms and no previous history of breast cancer. The study identified that while the majority of women (69.9%; n=314) sought help within one month, 30.1% (n=135) delayed help seeking for more than one month following self discovery of their breast symptom. The factors most significantly associated with HSB were the presenting symptom of ‘nipple indrawn/changes’ (p = 0.005), ‘ignoring the symptom and hoping it would go away’ (p < 0.001), the emotional response of being ‘afraid@ on symptom discovery (p = 0.005) and the perception/belief in longer symptom duration (p = 0.023). It was found that women who presented with an indrawn/changed nipple were more likely to delay (OR = 4.81) as were women who ‘ignored the symptoms and hoped it would go away’ (OR = 10.717). Additionally, the longer women perceived that their symptom would last, they more likely they were to delay (OR = 1.18). Conversely, being afraid following symptom discovery was associated with less delay (OR = 0.37; p=0.005). This study provides further insight into the HSB of women who self discovered breast symptoms. It highlights the complexity of the help seeking process, indicating that is not a linear event but is influenced by multiple factors which can have a significant impact on the outcomes in terms of whether women delay or seek help promptly. The study further demonstrates that delayed HSB persists amongst women with self discovered breast symptoms. This has important implications for continued emphasis on the promotion of breast awareness, prompt help seeking for self discovered breast symptoms and early detection and treatment of breast cancer, amongst women of all ages.

Investigation of stress and burnout in Irish second-level teachers: A mixed-methods approach.

This study explores the experiences of stress and burnout in Irish second level teachers and examines the contribution of a number of individual, environmental and health factors in burnout development. As no such study has previously been carried out with this sample, a mixed-methods approach was adopted in order to comprehensively investigate the subject matter. Teaching has consistently been identified as a particularly stressful occupation and research investigating its development is of great importance in developing measures to address the problem. The first phase of study involved the use of focus groups conducted with a total of 20 second-level teachers from 11 different schools in the greater Cork city area. Findings suggest that teachers experience a variety of stressors – in class, in the staff room and outside of school. The second phase of study employed a survey to examine the factors associated with burnout. Analysis of 192 responses suggested that burnout results from a combination of demographic, personality, environmental and coping factors. Burnout was also found to be associated with a number of physical symptoms, particularly trouble sleeping and fatigue. Findings suggest that interventions designed to reduce burnout must reflect the complexity of the problem and its development. Based on the research findings, interventions that combine individual and organisational approaches should provide the optimal chance of effectively tackling burnout.

The use of different blood sample preparations in the development of biomarkers for the environmental monitoring of domestic farm animals

The application of biological effect monitoring for the detection of environmental chemical exposure in domestic animals is still in its infancy. This study investigated blood sample preparations in vitro for their use in biological effect monitoring. When peripheral blood mononuclear cells (PBMCs), isolated following the collection of multiple blood samples from sheep in the field, were cryopreserved and subsequently cultured for 24 hours a reduction in cell viability (<80%) was attributed to delays in the processing following collection. Alternative blood sample preparations using rat and sheep blood demonstrated that 3 to 5 hour incubations can be undertaken without significant alterations in the viability of the lymphocytes; however, a substantial reduction in viability was observed after 24 hours in frozen blood. Detectable levels of early and late apoptosis as well as increased levels of ROS were detectable in frozen sheep blood samples. The addition of ascorbic acid partly reversed this effect and reduced the loss in cell viability. The response of the rat and sheep blood sample preparations to genotoxic compounds ex vivo showed that EMS caused comparable dose-dependent genotoxic effects in all sample preparations (fresh and frozen) as detected by the Comet assay. In contrast, the effects of CdCl2 were dependent on the duration of exposure as well as the sample preparation. The analysis of leukocyte subsets in frozen sheep blood showed no alterations in the percentages of T and B lymphocytes but led to a major decrease in the percentage of granulocytes compared to those in the fresh samples. The percentages of IFN-γ and IL-4 but not IL-6 positive cells were comparable between fresh and frozen sheep blood after 4 hour stimulation with phorbol 12-myrisate 13-acetate and ionomycin (PMA+I). These results show that frozen blood gives comparable responses to fresh blood samples in the toxicological and immune assays used.