AUC of mining

1.

mining chip has gone from CPU mining to GPU mining to FPGA mining, and now it has entered the era of ASIC mining. However, the way of mining has also experienced from one or two mining machines to small mining machine workshops, and now it has entered the era of large-scale mining

(1) mining mode: from one miner to large-scale mine

if you start to try mining, you need to prepare a miner, a computer with internet connection, an AUC, a raspberry pie, power supply and various connecting cables. The connection order of various devices is network cable - & gt; Raspberry pie - & gt; Microusb cable - & gt; AUC-> 4Pin cable - & gt; Mining machine and power supply

2. AUC in machine learning refers to random sampling from a pile of samples. The probability of positive samples is higher than that of negative samples
the detailed explanation is as follows: a sample is randomly selected, and each potential value x corresponds to a probability P
in descending order from high probability to low probability, rank is the highest probability in positive samples_ The probability is smaller than M-1 positive samples (M is the number of positive samples), (rank_ 1 - M) negative samples
the second highest positive sample probability is rank_ 2. The probability smaller than that is m-2 positive samples_ 2 - M + 1) negative samples
and so on
rank is the lowest probability in positive samples_ M. What's less likely than that is 0 positive samples, rank_ M - 1 negative sample
there are mxn positive and negative sample pairs in total (n is the number of negative samples). The formula (rank) is obtained by calculating all the cases in which the probability of positive sample is greater than that of negative sample_ 1 - M + rank_ 2 - M + 1 .... + rank_ M - 1) / (mxn) is the probability that the positive sample probability is greater than the negative sample probability.

3.

1. AUC is the area under the drug time curve, which represents the bioavailability of the drug (the degree of absorption and utilization of the drug in the human body). If AUC is large, the bioavailability is high, otherwise it is low

Cmax was the peak concentration of the drug. The maximum plasma drug concentration on the time curve is the highest plasma drug concentration that can be achieved after treatment

Tmax was the peak time of drug action. It refers to the time required to reach the highest concentration (drug peak concentration) on the human plasma drug concentration curve after administration

extended data

related characteristics:

bioavailability (EBA) refers to the ratio of the total amount of drugs absorbed by the test preparation and the reference preparation, which is used to measure the degree of drug absorption. It can be calculated by the ratio of the area under the blood concentration time curve (AUC)

The drug peak concentration is closely related to the clinical application of drugs. Only when the peak concentration reaches the effective concentration can the effect be obvious, and if it is higher than the safe range, it can show the toxic reaction. In addition, the peak concentration is an important index to measure the absorption and safety of the preparation

the time of drug peak was short, which indicated that the drug absorbed quickly and took effect quickly, but also eliminated quickly; The long peak time of the drug indicates that the absorption and onset of the drug are slow, and the ration of the drug action is often prolonged

4. select t.*,sum(t.AAA) over (partition by tt.mon order by t.年,t.月,t.日) as sum_dayfrom table_name t;

5. Unknown_Error

6. Reference can be made to the following literature

7.

The authentication center (AUC) consists of three groups: rand (random number), SREs (sign response) and KC (ciphering key)

authentication center (AUC) is a function used to verify each SIM card when it attempts to connect to the GSM core network (usually a mobile phone driver). Once the authentication is successful, HLR allows the management of the above SIM and services. An encryption key is also generated, which is then used to encrypt all wireless communications (voice, SMS, etc.) between the mobile phone and the GSM core network

extended data:

the characteristics of AUC

AUC does not directly participate in the authentication process, but is used in the process of generating MSc called data triplets. The security of the process depends on the shared key and sim between AUCs, which is called "ki."

ki can run safely until SIM is manufactured and also copied safely to AUC. This ki. Is never propagated between AUC and SIM card, but combined with IMSI proction response, and identifies tasks and an encryption key named KC that can be used for communication

if the authentication fails, then from the SIM card and mobile phone operator who cannot provide the service. An additional form is proposed to identify and check the serial number of mobile phone for eir section description, but it has nothing to do with AUC processing

8.

AUC is the abbreviation of area under curve, which is defined as the area under the ROC curve and surrounded by the coordinate axis. Obviously, the value of this area will not be greater than 1. Because the ROC curve is generally above the line y = x, the AUC is between 0.5 and 1

The closer the AUC is to 1.0, the higher the authenticity of the detection method; When it is equal to 0.5, the authenticity is the lowest and has no application value

extended data:

AUC is defined as the area under the ROC curve. We often use AUC value as the evaluation standard of the model, because often the ROC curve can not clearly indicate which classifier is better, but as a value, the classifier with larger AUC is better

among them, receiver operating characteristic curve (ROC) is a curve drawn according to a series of different boundary values or decision thresholds of dichotomy, with sensitivity of true positive rate as ordinate and 1-specificity of false positive rate as abscissa

AUC is a performance index to measure the advantages and disadvantages of learners. From the definition, AUC can be obtained by summing the areas of the parts under the ROC curve

The

ROC curve can easily find out the influence of any threshold on the generalization performance of the learner

9. Test variables are equivalent to independent variables, state variables are equivalent to dependent variables

10. Unknown_Error