Sabah tercümanı

Mahmut Sadık'ın Sabah'ta tefrika edilen Sabah Tercümanı adlı romanıTefrikanın devamına rastlanmamış, tefrika yarım kalmıştır

Nickel-Catalyzed Enantioselective Reductive Arylation of Common Ketones

A nickel complex of chiral bisoxazolines catalyzed the stereoselective reductive arylation of ketones in high enantioselectivity. A range of common acyclic and cyclic ketones reacted without the aid of directing groups. Mechanistic studies using isolated complex of a chiral bis(oxazoline) (L)Ni(Ar)Br revealed that Mn reduction was not needed, while Lewis acidic titanium alkoxides were critical to ketone insertion

Nickel-Catalyzed Enantioselective Reductive Arylation of Common Ketones

A nickel complex of chiral bisoxazolines catalyzed the stereoselective reductive arylation of ketones in high enantioselectivity. A range of common acyclic and cyclic ketones reacted without the aid of directing groups. Mechanistic studies using isolated complex of a chiral bis(oxazoline) (L)Ni(Ar)Br revealed that Mn reduction was not needed, while Lewis acidic titanium alkoxides were critical to ketone insertion

Selective sensing of a heterogeneous population of units with dynamic health conditions

<p>Monitoring a large number of units whose health conditions follow complex dynamic evolution is a challenging problem in many healthcare and engineering applications. For instance, a unit may represent a patient in a healthcare application or a machine in a manufacturing process. Challenges mainly arise from: (i) insufficient data collection that results in limited measurements for each unit to build an accurate personalized model in the prognostic modeling stage; and (ii) limited capacity to further collect surveillance measurement of the units in the monitoring stage. In this study, we develop a selective sensing method that integrates prognostic models, collaborative learning, and sensing resource allocation to efficiently and economically monitor a large number of units by exploiting the similarity between them. We showcased the effectiveness of the proposed method using two real-world applications; one on depression monitoring and another with cognitive degradation monitoring for Alzheimer’s disease. Comparing with existing benchmark methods such as the ranking-and-selection method, our fully integrated prognosis-driven selective sensing method enables more accurate and faster identification of high-risk individuals.</p

Statistical patterns of human mobility in emerging Bicycle Sharing Systems

<div><p>The emerging Bicycle Sharing System (BSS) provides a new social microscope that allows us to “photograph” the main aspects of the society and to create a comprehensive picture of human mobility behavior in this new medium. BSS has been deployed in many major cities around the world as a short-distance trip supplement for public transportations and private vehicles. A unique value of the bike flow data generated by these BSSs is to understand the human mobility in a short-distance trip. This understanding of the population on short-distance trip is lacking, limiting our capacity in management and operation of BSSs. Many existing operations research and management methods for BSS impose assumptions that emphasize statistical simplicity and homogeneity. Therefore, a deep understanding of the statistical patterns embedded in the bike flow data is an urgent and overriding issue to inform decision-makings for a variety of problems including traffic prediction, station placement, bike reallocation, and anomaly detection. In this paper, we aim to conduct a comprehensive analysis of the bike flow data using two large datasets collected in Chicago and Hangzhou over months. Our analysis reveals intrinsic structures of the bike flow data and regularities in both spatial and temporal scales such as a community structure and a taxonomy of the eigen-bike-flows.</p></div

Diagnostic monitoring of high-dimensional networked systems via a LASSO-BN formulation

<p>Quality control of multivariate processes has been extensively studied in the past decades; however, fundamental challenges still remain due to the complexity and the decision-making challenges that require not only sensitive fault detection but also identification of the truly out-of-control variables. In existing approaches, fault detection and diagnosis are considered as two separate tasks. Recent developments have revealed that selective monitoring of the potentially out-of-control variables, identified by a variable selection procedure combined with the process monitoring method, could lead to promising performances. Following this line, we propose the diagnostic monitoring that takes an additional step on from the selective monitoring idea and directs the monitoring effort on the potentially out-of-control variables. The identification of the truly out-of-control variables can be achieved by integrating the process monitoring formulation with process cascade knowledge represented by a Bayesian Network. Computationally efficient algorithms are developed for solving the optimization formulation with connection to the Least Absolute Shrinkage and Selection Operator (LASSO) problem being identified. Both theoretical analysis and extensive experiments on a simulated data set and real-world applications are conducted that show the superior performance.</p

Statistical patterns of human mobility in emerging Bicycle Sharing Systems - Fig 1

<p>(a) Location information of the BSS stations; (b) number of trips per days; (c) average number of trips on hourly basis; and (d) average number of trips of each day in a week.</p

Community structures detected in both Chicago and Hanzhou bike flow data.

<p>Community structures detected in both Chicago and Hanzhou bike flow data.</p

Number of eigen-bike-flows that constitute each ABF.

<p>Number of eigen-bike-flows that constitute each ABF.</p

Indices of the eigen-bike-flows constituting each ABF.

<p>Note that the x-axis is the eigen-bike-flow index that are organized by convention in decreasing order of the singular values, and y-axis is ordered according to the decreasing ABF rate as well.</p