Manajemen Sistem Pengambilan Keputusan (Gagasan Mengilmiahkan Proses Pengambilan Keputusan)

The fifth generation management emerged and developed in tune with the emergence of high-tech technology, information superhighway, and digitec economy so that the concept of the importance of building competitiveness through knowledge emerged. Within this framework, the teachings of fifth generation management should be applied in the lives of both profit and non-profit organizations including education. Decision making as one of the elements of the organizational sub-system, needs to adjust to the concept in question. Therefore, decision making must also be related to how decision making within the organization - including education - must also be scientifically accountable as the rules of the fifth generation management teachings

Defending Tor from Network Adversaries: A Case Study of Network Path Prediction

The Tor anonymity network has been shown vulnerable to traffic analysis attacks by autonomous systems and Internet exchanges, which can observe different overlay hops belonging to the same circuit. We aim to determine whether network path prediction techniques provide an accurate picture of the threat from such adversaries, and whether they can be used to avoid this threat. We perform a measurement study by running traceroutes from Tor relays to destinations around the Internet. We use the data to evaluate the accuracy of the autonomous systems and Internet exchanges that are predicted to appear on the path using state-of-the-art path inference techniques; we also consider the impact that prediction errors have on Tor security, and whether it is possible to produce a useful overestimate that does not miss important threats. Finally, we evaluate the possibility of using these predictions to actively avoid AS and IX adversaries and the challenges this creates for the design of Tor

Personalized Medicine: Studies of Pharmacogenomics in Yeast and Cancer

Advances in microarray and sequencing technology enable the era of personalized medicine. With increasing availability of genomic assays, clinicians have started to utilize genetics and gene expression of patients to guide clinical care. Signatures of gene expression and genetic variation in genes have been associated with disease risks and response to clinical treatment. It is therefore not difficult to envision a future where each patient will have clinical care that is optimized based on his or her genetic background and genomic profiles. However, many challenges exist towards the full realization of the potential personalized medicine. The human genome is complex and we have yet to gain a better understanding of how to associate genomic data with phenotype. First, the human genome is very complex: more than 50 million sequence variants and more than 20,000 genes have been reported. Many efforts have been devoted to genome-wide association studies (GWAS) in the last decade, associating common genetic variants with common complex traits and diseases. While many associations have been identified by genome-wide association studies, most of our phenotypic variation remains unexplained, both at the level of the variants involved and the underlying mechanism. Finally, interaction between genetics and environment presents additional layer of complexity governing phenotypic variation. Currently, there is much research developing computational methods to help associate genomic features with phenotypic variation. Modeling techniques such as machine learning have been very useful in uncovering the intricate relationships between genomics and phenotype. Despite some early successes, the performance of most models is disappointing. Many models lack robustness and predictions do not replicate. In addition, many successful models work as a black box, giving good predictions of phenotypic variation but unable to reveal the underlying mechanism. In this thesis I propose two methods addressing this challenge. First, I describe an algorithm that focuses on identifying causal genomic features of phenotype. My approach assumes genomic features predictive of phenotype are more likely to be causal. The algorithm builds models that not only accurately predict the traits, but also uncover molecular mechanisms that are responsible for these traits. . The algorithm gains its power by combining regularized linear regression, causality testing and Bayesian statistics. I demonstrate the application of the algorithm on a yeast dataset, where genotype and gene expression are used to predict drug sensitivity and elucidate the underlying mechanisms. The accuracy and robustness of the algorithm are both evaluated statistically and experimentally validated. The second part of the thesis takes on a much more complicated system: cancer. The availability of genomic and drug sensitivity data of cancer cell lines has recently been made available. The challenge here is not only the increasing complexity of the system (e.g. size of genome), but also the fundamental differences between cancers and tissues. Different cancers or tissues provide different contexts influencing regulatory networks and signaling pathways. In order to account for this, I propose a method to associate contextual genomic features with drug sensitivity. The algorithm is based on information theory, Bayesian statistics, and transfer learning. The algorithm demonstrates the importance of context specificity in predictive modeling of cancer pharmacogenomics. The two complementary algorithms highlight the challenges faced in personalized medicine and the potential solutions. This thesis detailed the results and analysis that demonstrate the importance of causality and context specificity in predictive modeling of drug response, which will be crucial for us towards bringing personalized medicine in practice

Is there any effect of accounting information on Stock prices? evidence from top 20 firms listed in Fbm KLCI

Tujuan utama kajian ini adalah untuk memeriksa hubungan antara harga saham dan nilai ekuiti, keuntungan dan dividen secara empirik, dengan menggunakan rangka kerja Model Ohlson. The main purpose of this study is to empirically examine the relationship between share price and the net book value, earnings per share and dividends per share, based on the framework of Ohlson mode

Organoleptic Test of Eco-enzyme : Fermentation of Banana Peel Waste

Prevention of environmental damage can be done by recycling household waste both organic and inorganic. One of them is by making eco-enzymes made from banana peel waste which is found in the environment. This study aims to determine the level of respondents' liking based on organoleptic test variables. This research method is an experiment that includes making eco-enzymes, and organoleptic tests consisting of aroma, color and texture variables. Data analysis was carried out in a qualitative descriptive way by looking at the level of respondents' liking. The results showed that the average respondent chose a brown color with a percentage of 90%, yellow 7%, and colorless 3%. The scent variable respondents chose sour odor by 70% and other aromas 30%. While the texture of all respondents chose the composition of liquid eco-enzyme. This is due to the metabolic activity of microorganisms that result in the breakdown of substrates by bacteria resulting in changes in the aroma, color and texture of banana peels. The conclusion of this study is that the use of banana peel as the basic ingredient for making eco-enzyme affects the respondents' level of liking. Eco-enzyme can be used as a natural fertilizer for plant growth and can reduce household waste

Development Of Dried Black Grass Jelly (Mesona Chinensis) Containing Different Tapioca And Sago Starch Ratio

Black grass jelly is a herbal dessert made from dried leaves extracts of Mesona chinensis plant. Commercial black grass jelly exhibits a short shelf life when stored at room temperature due to the usage of tapioca starch which results in a higher syneresis rate and unstable texture. Hence, the objective of this research is to develop dried black grass jelly with different tapioca and sago starch ratio for increasing the shelf life of the black grass jelly. The black grass jelly was formulated with different sago and tapioca starch ratio (0:100, 25:75, 50:50, 75:25, 100:0), thereafter dried at different drying time (0, 3, 6, 9, 12, 24, 30 hr) and rehydrated at 90 ℃ for 15 min. The development of dried black grass jelly containing different tapioca and sago starch ratio was successful. The effects of different sago and tapioca starch ratio and drying time on the physical properties of black grass jelly were determined. Hence, analyses on the moisture content, colour, texture, syneresis, drying kinetics (moisture content against drying time) and rehydration capacity were conducted. The increase in sago starch ratio significantly decreased (p<0.05) the moisture content of fresh black grass jelly consisting of both starches. The values of all the colour parameters and textural parameters except springiness, of the fresh black grass jelly increased significantly (p<0.05) in comparison with control sample when the sago starch ratio was increased to more than 75%. Different sago and tapioca starch ratio did not significantly affect (p>0.05) the syneresis of black grass jelly after storage for 24 hr, however the syneresis of fresh black grass jelly significantly (p<0.05) increased with the increase in storage time. A non-linear relationship was observed on the drying curve of black grass jelly

Predicting Changes of Body Weight, Body Fat, Energy Expenditure and Metabolic Fuel Selection in C57BL/6 Mice

The mouse is an important model organism for investigating the molecular mechanisms of body weight regulation, but a quantitative understanding of mouse energy metabolism remains lacking. Therefore, we created a mathematical model of mouse energy metabolism to predict dynamic changes of body weight, body fat, energy expenditure, and metabolic fuel selection. Based on the principle of energy balance, we constructed ordinary differential equations representing the dynamics of body fat mass (FM) and fat-free mass (FFM) as a function of dietary intake and energy expenditure (EE). The EE model included the cost of tissue deposition, physical activity, diet-induced thermogenesis, and the influence of FM and FFM on metabolic rate. The model was calibrated using previously published data and validated by comparing its predictions to measurements in five groups of male C57/BL6 mice (N = 30) provided ad libitum access to either chow or high fat diets for varying time periods. The mathematical model accurately predicted the observed body weight and FM changes. Physical activity was predicted to decrease immediately upon switching from the chow to the high fat diet and the model coefficients relating EE to FM and FFM agreed with previous independent estimates. Metabolic fuel selection was predicted to depend on a complex interplay between diet composition, the degree of energy imbalance, and body composition. This is the first validated mathematical model of mouse energy metabolism and it provides a quantitative framework for investigating energy balance relationships in mouse models of obesity and diabetes

An institution-based enquiry into concepts of proficiency, automaticity and second-language learning among dyslexic students

It is, for some, 'common knowledge' that dyslexic students cannot master a foreign language 'because' they cannot master their own. This study enquires into the assumption, and the 'because', above, and seeks other explanatory routes for dyslexic university students' difficulties with foreign language learning. Building on earlier work concerned with notions of 'automaticity' in relation to concepts of 'proficiency' in proficiency and dyslexia literatures, it relates these directly to second language teaching/learning concepts and discusses this in relation to 'phronetic', 'professional' and tacit' views of knowledge. The empirical part of the study comprises cross-comparison of four narrative sources: the narratives of a dozen dyslexic students engaged in a semi-structured, in-depth interview concerning their language difficulty and how they view it; a second narrative relating the voices of the advisors most directly linked to dyslexic language learners in the institution, also including past and future difficulties of some dyslexic students who may face a study year abroad, e.g. on Erasmus and similar schemes; a third interview with the then current head of the unit dealing with both English as a Foreign Language, and Modern Foreign Languages; and the over-arching narrative of the researcher – his story in conducting this study. Within this framework, the research uncovers how, at a practical level as well as theoretically, phronetic, teaching-learning and exceptional language-acquisition 'knowledge' may be open to subversion from several quarters: the pragmatics and economics of 3rd-level EFL and MFL1 language teaching; transposing child language acquisition concepts onto adult language learning ones; the cross- and/or mismatching of these with dyslexia ones; and the possible collision between some areas of professional knowledge – tacit or otherwise. The research shows how for the 'institutional dyslexics' concerned, and sometimes despite their advisors, the unit's academic director and the institution, automaticity is anterior to proficiency and agency is anterior to automaticity. Moreover reversing this, discovering or rediscovering their sense of agency allows certain of the dyslexic participants to attain a qualified measure of automaticity in their language studies and hence, of proficiency. These findings have important implications for those engaged in second language teaching and learning. The organisation of the thesis is as follows: in a first chapter which the researcher introduces with a short autobiography and an account of how the research came about, a broadly descriptive and factual introduction to the piece then summarises previous work in the doctoral degree particularly the critical analytical study, focusing the research questions, and discussing the relationship between methodology and methods, and begins a consideration of what a 'case' is, and what is the case here. Chapter 2 expands the theoretical focus with a discussion of the notion of coherentism and the notion of 'fit', and introduces issues in narrativity and in phronesis. Chapter 3 addresses understandings and terminologies in 'communicative' language teaching, cross-mapping these to both dyslexia and 'proficiency' issues previously discussed. Chapter 4 explores the data, and begins an assessment of the 'fit' between the respondents. Finally, Chapter 5 summarises and discusses the 'findings' of the research – what emerges from the research questions and what from their interpretation; how theoretical understandings now 'fit', or not; what else emerged during the study; what constitutes a finding; and returning to Chapter 1, asks to what extent the study is a foundationalist 'case' which can or should be 'generalisable'. A short discussion of further research avenues is presented

Fast and efficient optical phase conjunction using a degenerate Raman System in rubidium

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1997.Includes bibliographical references (p. 69).by Darren S. Hsiung.M.Eng