1,721,623 research outputs found
Employee Commitment and Employee Performance In Nay Kyel Oo Construction., LTD. (Ya Min Thu, 2019)
Get PDFThis research aims to identify the influencing Human Resource Management practices on organizational commitment and to analyze the effects of organizational commitment on employee performance in Nay Kyel Oo Construction Co., Ltd. The data are collected with structured questionnaires from 130 employees working in Nay Kyel Oo Construction Co., Ltd. Among the four HRM practices, training, and development, performance appraisal, rewards and benefits practices are found positive significant effect on affective commitment. All HRM practices have a positive impact on continuance and normative commitment. Moreover, affective commitment and continuance commitment has a strong influence on employee performance. The study recommends that in order to improve the organizational commitment and employee performance, management should create clear and realistic job descriptions, management should design rewards system linked to performance levels and the supervisors should encourage the participation of employees in training programs
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Cost-effectiveness analysis of Preventing Computer Virus Infection
No full text當電腦病毒感染正在全球盛行時，要降低流行性的傳染對電腦使用者是件刻不容緩的事情。而安裝防毒軟體和購買軟體的升級則必須考慮到所花的錢和時間。為了降低電腦中毒所得到的效益是否比購買防毒軟體所花的錢重要是件值得探討的問題。
就我們的瞭解，非常少的研究學者使用Anderson (1991) 傳染病模式的概念進行研究此項議題。為了在馬可夫的模式中使用Anderson的觀念，我們必須獲得許多參數，同時將參數經過轉換，因此做了一個小規模的問卷調查，而將調查所得的經驗值或專家意見應用在馬可夫的決策模型中，以進行兩種不同情景的成本效益分析。分別是兩種決策安裝防毒軟體與否，以及三種決策：購買防毒軟體同時定期更新、購買防毒軟體但並無更新、以及沒有安裝防毒軟體。
使用馬可夫決策分析可以得到如下的結果：
若效益訂為所獲得減少損失的時間，則每一單位效益相當於5小時。如此，安裝防毒軟體可以獲得3.37單位效益（16.85個小時），而沒有安裝只能獲得1.36單位效益（6.8個小時）。裝防毒軟體且每年更新可以獲得3.52單位效益（17.6個小時），而在裝防毒軟體不每年更新的狀態下，僅僅能獲得3.29單位效益（16.45小時）而已。
從消費者觀點來看，裝了防毒軟體，每要減少一個感染發生症狀的人要花新台幣38,228元。若從社會成本的觀點來看，有裝防毒軟體會比沒裝防毒軟體來的便宜且效果較好。從消費者觀點來看，裝防毒軟體且每年更新，每要減少一個感染發生症狀的人只要花新台幣26,222元，但在裝防毒軟體不每年更新的狀態下，卻要花新台幣108,158.33元。
從社會成本的觀點來看，沒裝防毒軟體比上裝防毒軟體不每年更新，每要減少一個感染發生症狀的人要花新台幣9,504.55元。從社會成本的觀點來看，若效益所獲得減少損失的時間，則每獲得5小時，防毒軟體需花費1,029元新台幣；且有裝防毒軟體比沒裝好。從消費者觀點來看，裝防毒軟體且每年更新，每獲得5小時，要花新台幣9,363元，但在裝防毒軟體不每年更新的狀態下，只要花674元。從社會成本的觀點來看，裝防毒軟體且每年更新，每獲得5小時，要花新台幣8,328元，且這個策略是較好的。
在這個研究中，裝防毒軟體且每年更新，是最有效益的策略。而安裝防毒軟體則是在預防電腦中毒上最具成本效益的策略。而我們終於成功的利用傳染病模式，發展出一個馬可夫決策模式來評估安裝防毒軟體（打疫苗）、 或購買更新的防毒軟體（追加劑）的效益或成本效益。這個模型對決定購買防毒軟體或更新的決策者是非常有用的。As computer virus infection prevails in the globe, to reduce pandemic transmission is of paramount importance to burden of computer users. And the installation of antivirus software (AVS) and the update of this software need considerable costs and time. Whether the benefit of reducing infection can outweigh cost incurred in purchasing AVS is worthy of being investigated.
To our knowledge, very few researches have been conducted to address this issue using the concept of infectious model as proposed by Anderson (1991). For applying the concept on Markov decision tree, we must get many parameters and do transformation, so we conducted a small questionnaire survey, then we applied Markov decision tree model to develop natural course of computer virus infection based on information obtained form empirical survey or expert opinion to perform cost-effectiveness analysis of comparing two decisions, AVS versus none, and three decisions, purchasing AVS updated at regular interval, purchasing AVS without updating, and none.
The present study used Markov decision analysis to analyze the effectiveness and cost-effectiveness analysis for prevention of computer virus infection. For effectiveness defined by reducing loss of time using 5 hr as a unit, strategy “AVS” can gain 3.37 unit utilities (16.85 hrs) in the model, but strategy “none” can only just gain 1.36 unit utilities (6.8 hrs). Strategy “Purchasing update AVS every year” can gain 3.52 unit utilities (17.6 hrs) in the model, but strategy “No purchasing update AVS every year” can merely gain 3.29 unit utilities (16.45 hrs).
For incremental cost per infected with symptoms averted, to prevent an infected with symptom, NT26,222 would be paid in strategy “purchasing update AVS every year”, but NT9504.55 would be paid in strategy “none”. If effectiveness is defined by utility gained in reducing loss of time, to gain 5 hrs, NT9,363 would be paid in strategy “Purchasing update AVS every year”, but NT8,328 would be paid in strategy “Purchasing update AVS every year”, and “none” is dominated
In this analysis, purchasing update AVS every year would be most effective strategy in preventing computer virus infection. And AVS used would be most cost-effective strategy in preventing computer virus infection. And we finally successfully developed a Markov decision model underpinning the infectious disease model to evaluate effectiveness or cost-effectiveness of installing AVS (vaccination) or purchasing the updated AVS (booster). This model is very useful for policy-maker in the determination of whether AVS or regular update is necessary.Catalog
誌謝 II
Catalog III
Tables and Figures List IV
中文摘要 1
Abstract 3
II Literature Review 8
III Methods 11
Infectious disease model 11
Markov Cohort Analysis 12
Markov cycle tree 14
Structure of Decision Tree 14
Probabilities 17
Monte Carlo Simulation 17
Utility 19
Costs 20
Assumptions in the model 20
Measurements and outcome variables 21
Data analysis 21
IV Results 22
45 informants 22
4.1 Results of Empirical Survey 22
4.2 Base-case Estimates 24
4.3 Utility and Cost Measurement 26
4.4 Effectiveness and Cost-effectiveness Analysis 26
Markov Cohort Analysis 26
Monte Carlo Simulation 28
Cohort of 100,000 people 31
Sensitivity analysis 33
V Discussion 42
Major Findings 42
Concept of Infectious Model 44
Limitations of Study 44
Further research 47
VI References 49
VII Appendix 51
Tables and Figures List
Figure3. 1 Schematic representation of infectious disease 12
Figure3. 2 Decision tree of two preventive strategies. 13
Figure3. 3 Decision tree of three preventive strategies. 14
Figure3. 4 Markov model for longitudinal sequence regarding computer virus infection. 16
Figure4.1. 1 Descriptive data about questionnaire 53
Table 4.2. 2 Figure 4.2. 1 Branches and probabilities of state susceptible 59
Table 4.2. 3 Figure 4.2. 2 Branches and probabilities of state infected with symptoms 60
Table 4.2. 4 Figure 4.2. 3 Branches and probabilities of node boot failure 61
Table 4.2. 5 Figure 4.2. 4 Branches and probabilities of node non CPU and/or MB failure 62
Table 4.2. 6 Figure 4.2. 5 Branches and probabilities of node CPU and/or MB failure 63
Table 4.2. 7 Figure 4.2. 6 Branches and probabilities of node boot successful 64
Table 4.2. 8 Figure 4.2. 7 Branches and probabilities of node OS failure 65
Table 4.2. 9 Figure 4.2. 8 Branches and probabilities of node OS normal 66
Table 4.2. 10 Figure 4.2. 9 Branches and probabilities of node none 67
Table 4.3. 1 Raw data of utility 68
Table 4.3. 2 Utility 72
Table 4.3. 3 Cost 76
Table 4.4.1 Results of effectiveness in terms of infection with symptoms prevented 77
Table 4.4.2 Incremental cost per infected with symptoms averted 78
Table 4.4.3 Incremental cost per infected with symptoms averted 79
Table 4.4.4 Cost-effectiveness analysis 80
Table 4.4.5 Cost-effectiveness analysis 81
Table 4.4.6 RR of effectiveness using Monte Carlo simulation 82
Table 4.4.7 Incremental cost-effectiveness ratio (effectiveness is defined by infection with symptoms averted) using Monte Carlo simulation 83
Table 4.4.8 Incremental cost-effectiveness ratio using Monte Carlo simulation 84
Table 4.4.9 Incremental cost-effectiveness ratio for two strategies, using Monte Carlo simulation 85
Table 4.4.10 Incremental cost-effectiveness ratio for three strategies using Monte Carlo simulation 86
Table 4.4.11 Results of total effectiveness for cohorts with the size of 100,000 people by two and three strategies 87
Table 4.4.12 Results of total effectiveness of cohort with the size of 100,000 people by two and three strategies 88
Table 4.4.13 Results of total effectiveness, total cost and average cost-effectiveness ratio for the cohort 89
Table 4.4.14 Results of total effectiveness, total cost and average cost-effectiveness ratio for the cohort 90
Table 4.4.15 Results of total effectiveness, total cost and average cost-effectiveness ratio for the cohort 91
Table 4.4.16 The results of total effectiveness, total cost and average cost-effectiveness ratio for cohort 92
Figure4.4.1 Sensitivity analysis of ICER between 2 strategies, direct cost is considered 93
Figure4.4. 2 Sensitivity analysis of incremental effectiveness between 2 strategies 94
Figure4.4. 3 Sensitivity analysis of ICER between 2 strategies, direct cost is considered 95
Figure4.4. 4 Sensitivity analysis of incremental effectiveness between 2 strategies, effectiveness is gain of loss of time 96
Figure4.4. 5 Sensitivity analysis of ICER between 2 strategies, indirect cost is considered 97
Figure4.4. 6 Sensitivity analysis of ICER between 2 strategies, indirect cost is considered 98
Figure4.4. 7 Sensitivity analysis of ICER between 3 strategies, no purchasing vs. none, direct cost is considered 99
Figure4.4. 8 Sensitivity analysis of ICER between 3 strategies, purchasing vs. none, direct cost is considered 100
Figure4.4. 9 Sensitivity analysis of incremental effectiveness between 3 strategies, no purchasing vs. none 101
Figure4.4. 10 Sensitivity analysis of incremental effectiveness between 3 strategies, purchasing vs. none 102
Figure4.4. 11 Sensitivity analysis of ICER between 3 strategies, none vs. no purchasing, indirect cost is considered 103
Figure4.4. 12 Sensitivity analysis of ICER between 3 strategies, purchasing vs. no purchasing, indirect cost is considered 104
Figure4.4. 13 Sensitivity analysis of incremental effectiveness between 3 strategies, none vs. no purchasing 105
Figure4.4. 14 Sensitivity analysis of incremental effectiveness between 3 strategies, purchasing vs. no purchasing 106
Figure4.4. 15 Sensitivity analysis of ICER between 3 strategies, no purchasing vs. none, direct cost is considered 107
Figure4.4. 16 Sensitivity analysis of ICER between 3 strategies, purchasing vs. none, direct cost is considered 108
Figure4.4. 17 Sensitivity analysis of incremental effectiveness between 3 strategies, no purchasing vs. none 109
Figure4.4. 18 Sensitivity analysis of incremental effectiveness between 3 strategies, purchasing vs. none 110
Figure4.4. 19 Sensitivity analysis of ICER between 3 strategies, none vs. no purchasing, indirect cost is considered 111
Figure4.4. 20 Sensitivity analysis of ICER between 3 strategies, purchasing vs. no purchasing, indirect cost is considered 112
Figure4.4. 21 Sensitivity analysis of incremental effectiveness between 3 strategies, none vs. no purchasing 113
Figure4.4. 22 Sensitivity analysis of incremental effectiveness between 3 strategies, purchasing vs. no purchasing 11
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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