Document Databases
This survey paper analyzes existing research on discomfort glare, evaluating the reliability of conventional measurements and metrics. Additionally, it suggests future directions for research in this field.
5.1 Very promising (established factors)
- Relative Pupil size: Inversely correlated with visual discomfort ratings, correlated with vertical illuminance at the eye and glare indices.
5.2 Just statistically significant (require further investigation)
- Pupillary unrest (hippus): Affected by the luminance intensity
- Eye Movements: Compared favourably with subjective assessment
- Spontaneous eye Blink Rate: Affected by glare while the subject is looking slightly upwards
- Degree of eye-opening: Applicable in the presence of direct sunlight; correlated highly with vertical eye illuminance, DGP and PGSV; exhibited better diagnostic performance than DGI, DGP, or vertical illuminance at the eye
5.3 Irrelevant
- Absolute pupil diameter: Correlated with overall background luminance.
- Gaze position/direction: Heavily depends on the cognitive demand and complexity of the task, unsuitable as a predictor for discomfort glare.
Whey my friend asked me why we could not create indexes for all the columns in our SQL database, I could not answer that question clearly. I mulled over, and here is the answer I would say now.
Although indexes can make queries faster, they also may have negative impacts on our database.
By the way, the friend dislikes dynamic typing programing languages but loves NoSQL, saying that NoSQL is easier to use.
I find it very inconsistent.
For programming languages, he seeks some sort of validation or safeguards, but he does not want it for databases. I will write more about this, but from my experience, business-related data is not (or should not) dynamic in most cases. I have suffered from how easily data in NoSQL is out of structure and malformed.
Editorial of CodeTON Round 9 (Div. 1 + Div. 2)
The editorial explains the approach in detail. I love it.
I had similar thoughts and observations, but failed to reach the answer. It is somewhat frustrating, but gaining EXP is a good thing.
THOUGHT: The condition seems hard to track. So a good way is to play around with smaller cases and see if we can make some observations.
ACTION: Let’s start with the smallest string… (len(s’) = 1)
ACTION: Let’s try the next smallest strings… (len(s’) = 2) I overlooked this part somehow!
ACTION: Let’s try the next smallest strings with adjacent different characters… (len(s’) = 3)
for _ in range(int(input())):
s: str = input()
sl: list[str] = list(s)
for i in range(len(sl) - 1):
if len(set(sl[i : i + 2])) == 1:
print(s[i : i + 2])
break
if len(set(sl[i : i + 3])) == 3:
print(s[i : i + 3])
break
else:
print(-1)Udon 700 Lean Cuisine 700 Cocoa 200 Gummies 600 Yogurt 500 Lean Cuisine 300 Protein shake 200
Total 3200 kcal (just kill me at this point)
jogging, lat pull down, dumbbell shoulder press
MUST:
TODO: