PERFORMANCE ENGINEERING OF BUSINESS INFORMATION SYSTEMSFilling the Gap between High-level Business Services and Low-level Performance Models

Author(s):  
Samuel Kounev
VLSI Design ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-17
Author(s):  
Soumya Pandit ◽  
Chittaranjan Mandal ◽  
Amit Patra

This paper presents a systematic methodology for the generation of high-level performance models for analog component blocks. The transistor sizes of the circuit-level implementations of the component blocks along with a set of geometry constraints applied over them define the sample space. A Halton sequence generator is used as a sampling algorithm. Performance data are generated by simulating each sampled circuit configuration through SPICE. Least squares support vector machine (LS-SVM) is used as a regression function. Optimal values of the model hyper parameters are determined through a grid search-based technique and a genetic algorithm- (GA-) based technique. The high-level models of the individual component blocks are combined analytically to construct the high-level model of a complete system. The constructed performance models have been used to implement a GA-based high-level topology sizing process. The advantages of the present methodology are that the constructed models are accurate with respect to real circuit-level simulation results, fast to evaluate, and have a good generalization ability. In addition, the model construction time is low and the construction process does not require any detailed knowledge of circuit design. The entire methodology has been demonstrated with a set of numerical results.


2011 ◽  
Vol 217-218 ◽  
pp. 1-4 ◽  
Author(s):  
Bao Liang Hu

This paper identifies structural element differences between the business model(BM) with relatively high-level performance and BM with relatively low-level performance through comparison of two cases of the BM with relatively high-level performance and two cases of the BM with relatively low-level performance in terms of ten aspects such as cost structure, revenue mechanism, value proposition, target market, competitive strategy, value configuration, value network, entrepreneur team, capital structure and core competence.


2019 ◽  
Vol 1 (1) ◽  
pp. 31-39
Author(s):  
Ilham Safitra Damanik ◽  
Sundari Retno Andani ◽  
Dedi Sehendro

Milk is an important intake to meet nutritional needs. Both consumed by children, and adults. Indonesia has many producers of fresh milk, but it is not sufficient for national milk needs. Data mining is a science in the field of computers that is widely used in research. one of the data mining techniques is Clustering. Clustering is a method by grouping data. The Clustering method will be more optimal if you use a lot of data. Data to be used are provincial data in Indonesia from 2000 to 2017 obtained from the Central Statistics Agency. The results of this study are in Clusters based on 2 milk-producing groups, namely high-dairy producers and low-milk producing regions. From 27 data on fresh milk production in Indonesia, two high-level provinces can be obtained, namely: West Java and East Java. And 25 others were added in 7 provinces which did not follow the calculation of the K-Means Clustering Algorithm, including in the low level cluster.


Author(s):  
Margarita Khomyakova

The author analyzes definitions of the concepts of determinants of crime given by various scientists and offers her definition. In this study, determinants of crime are understood as a set of its causes, the circumstances that contribute committing them, as well as the dynamics of crime. It is noted that the Russian legislator in Article 244 of the Criminal Code defines the object of this criminal assault as public morality. Despite the use of evaluative concepts both in the disposition of this norm and in determining the specific object of a given crime, the position of criminologists is unequivocal: crimes of this kind are immoral and are in irreconcilable conflict with generally accepted moral and legal norms. In the paper, some views are considered with regard to making value judgments which could hardly apply to legal norms. According to the author, the reasons for abuse of the bodies of the dead include economic problems of the subject of a crime, a low level of culture and legal awareness; this list is not exhaustive. The main circumstances that contribute committing abuse of the bodies of the dead and their burial places are the following: low income and unemployment, low level of criminological prevention, poor maintenance and protection of medical institutions and cemeteries due to underperformance of state and municipal bodies. The list of circumstances is also open-ended. Due to some factors, including a high level of latency, it is not possible to reflect the dynamics of such crimes objectively. At the same time, identification of the determinants of abuse of the bodies of the dead will reduce the number of such crimes.


2021 ◽  
pp. 002224372199837
Author(s):  
Walter Herzog ◽  
Johannes D. Hattula ◽  
Darren W. Dahl

This research explores how marketing managers can avoid the so-called false consensus effect—the egocentric tendency to project personal preferences onto consumers. Two pilot studies were conducted to provide evidence for the managerial importance of this research question and to explore how marketing managers attempt to avoid false consensus effects in practice. The results suggest that the debiasing tactic most frequently used by marketers is to suppress their personal preferences when predicting consumer preferences. Four subsequent studies show that, ironically, this debiasing tactic can backfire and increase managers’ susceptibility to the false consensus effect. Specifically, the results suggest that these backfire effects are most likely to occur for managers with a low level of preference certainty. In contrast, the results imply that preference suppression does not backfire but instead decreases false consensus effects for managers with a high level of preference certainty. Finally, the studies explore the mechanism behind these results and show how managers can ultimately avoid false consensus effects—regardless of their level of preference certainty and without risking backfire effects.


Author(s):  
Richard Stone ◽  
Minglu Wang ◽  
Thomas Schnieders ◽  
Esraa Abdelall

Human-robotic interaction system are increasingly becoming integrated into industrial, commercial and emergency service agencies. It is critical that human operators understand and trust automation when these systems support and even make important decisions. The following study focused on human-in-loop telerobotic system performing a reconnaissance operation. Twenty-four subjects were divided into groups based on level of automation (Low-Level Automation (LLA), and High-Level Automation (HLA)). Results indicated a significant difference between low and high word level of control in hit rate when permanent error occurred. In the LLA group, the type of error had a significant effect on the hit rate. In general, the high level of automation was better than the low level of automation, especially if it was more reliable, suggesting that subjects in the HLA group could rely on the automatic implementation to perform the task more effectively and more accurately.


2020 ◽  
Vol 4 (POPL) ◽  
pp. 1-32 ◽  
Author(s):  
Michael Sammler ◽  
Deepak Garg ◽  
Derek Dreyer ◽  
Tadeusz Litak
Keyword(s):  

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