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J. Comput. Sci. Eng. Vol.
27 (2016) 775-786 |
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Optimized
Research of Batch Query for Detailed Call Records |
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Menglin
Liu, jianguang Liu |
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J. Comput. Sci. Eng.
27 (2016) 775-778
¡ªPublished
November 25, 2016 |
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Abstract:
For Telecom operators, the query for detailed call
records is an important window to provide services for
the outside world, which can provide the service for
users or public, inspection, law and other units. For
Shandong Unicom Corporation£¬due to the current query
system of detailed call records can only achieve the
query of a single number or batch numbers in a single
account period, but it can¡¯t achieve the query such as
batch number in a multi-account period. In order to
solve this problem, this paper proposes an optimization
plan of batch query for detailed call records and gives
the detailed implementation process, and batch inquiry
for batch numbers in the multi-billing periods is
achieved. Practice has proved that this optimization has
achieved the batch query for detailed call records
within a multi-account period ,and the implementation
process is very simple, efficient, and the query results
is fairly accurate, so it has a certain value of
application and academic. |
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Keywords:
Detailed call records; Batch query; Optimization; Stored
procedure.
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RSM-BASED
Optimization of Enzymatic Hydrolysis Conditions for Chicken
Bones |
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Shuqian
Li |
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J. Comput. Sci. Eng. 27 (2016) 779-782
¡ªPublished
November 25, 2016 |
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Abstract:
The response surface methodology was used to study the
enzymolysis technology of chicken bone and the
enzymolysis technology model was established so as to
obtain the optimum enzymatic hydrolysis technology
conditions. Five factors, namely the size of bone,
enzymolysis temperature, time of enzymolysis,
solid-liquid ratio and quantity of enzyme were
investigated using one way ANOVA. Then the model was
established via response surface optimization. The
results showed that the optimum enzymolysis conditions
were: bone size: 1.9cm, the enzymolysis time 2.5h, and
enzymolysis temperature 63¡æ£¬ the obtained chicken bone
enzymolysis production has an DEH of 0.921. |
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Keywords:
Response surface methodology; Enzyme hydrolysis; Chicken
bones.
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The Influences of
Digitalization Technology on the Essence of Photography |
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Quan
Jin |
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J. Comput. Sci. Eng. 27 (2016) 783-786
¡ªPublished
November 25, 2016 |
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Abstract:
Based on the theory and practice combination of methods,
emphatically from the relationship of photography and
technology, analyzes digital technology in the change of
the photography invent the authenticity, rich
photography creation technique of expression and fuzzy
photography creation of professional limit and so on the
impact of photography creation, from the main ideology
and cognitive aspects steering Angle analysis
photography formed social causes, this paper reveals the
development of digital technology on the contemporary
photography creation important significance to help
better understanding the photographer photography art,
understand the influence of digital technology on
photography in constructing the important role of
Chinese culture. |
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Keywords:Photography;
Digital technology; Influence.
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Study on Risk
Factors of Mild Cognitive Impairment: Based on Decision Tree
Model |
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Xiao
Wang and Zongjun Guo |
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J. Comput. Sci. Eng. 27 (2016) 787-790¡ªPublished
December 25, 2016 |
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Abstract:
Collect demographic, life and clinical factors of
patients with mild cognitive impairment(MCI), analysis
of MCI factors and set up high-risk factors model by use
the decision tree data mining methods. 380 patients were
selected from our hospital department of health and
neurology clinic or hospital treatment during October
2014 to October 2016, The demographics, living habit of
patients and Clinical factors were collected, C5.0
decision tree algorithm was adopted to establish the
mild cognitive impairment risk factor prediction model,
use the Logistic regression analysis and chi-square to
assist the decision tree model. According to the
decision tree model, the model prediction accuracy was
78.95%, age was the most important variable factors for
MCI, sleep, exercise, diabetes, education, drinking were
important variables to MCI. According to result of
Logistic regression analysis, age, drinking, sleep were
independent risk factors for MCI, the model prediction
accuracy was 66.32%, results had significant difference
(P<0.05). The decision tree model was superior to
logistic regression model in the prediction accuracy for
MCI happened, age, diabetes, drinking, insomnia were
risk factors for MCI, exercise and education were the
protective factors for the MCI. |
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Keywords:Photography;
Digital technology; Influence.
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¡ª¡ª from ACSS |