Comments:

1. The meaning of "o^c" in C. CNN Classifier should be added (Is it the mean sample?)
2. Line 2 after the section title E.Linear Regression Classification Algorithm, c, M, i should be in italic style. Same for q=ab in Line 4.

No more comment.

In this paper, authors present a new semantic analysis frameworkd, MDLSA, for document semantic representation by considering both term frequencies and term associations. I

Two public data-sets are used to evaluate the performance of the Web document classification. The results show that the performance of the
MDLSA framework on web document classification is better than the other algorithms such as VSM, PCA, RAP, and MLM.

The contribution of the paper is to design an efficient dimensional reduction technique for compressing the graph in a principled manner and
modeling an accurate representation in a low dimensional space.

The sentences in this paper should be checked for grammar by English-speaking colleagues. 　

Please delete Springer-Verlag, Technical Support, Heidelberg, Germany in the affiliation field.
The paper makes a good impression with a clear structure.
There is a good introduction, extensive explanation of the algorithms and a detailed experimental result.
I think this paper is interesting and fits within the scope of the conference.
The paper is interesting and the area of research is of general importance.
This paper is well written and the structure is reasonable. Also the experiments are convincing.

This paper aims to design sliding mode control(SMC) for a magnetic levitation system with PID Tuning.
It first presents dynamic analysis of a magnetic levitation system.
Then discuss the controller architecture for PID control, SMC and PID-SMC design, respectively.
And the experimental results are shown accordingly.
It is evident that the PID-SMC does provide better control performance than pure PID control or SMC.

This paper is accepted for the conference and the minor improvements are given for the author to revise the paper:

1. I suggest the title of the paper modified as “ Sliding Mode Control of a Magnetic Levitation System with PID Tuning Technique”.
2. Page2, paragraph 4 –“PID adapt … SMC generate” should be “PID adapts … SMC generates”.
3. Page2, paragraph 5, line 3, "were designed to" should be "are designed to".
4. Equations (1) & (2) should be typed in using equation editor like equations (3), (4), etc. do.
   For example:
   F_m- mg – 〖cx ̇〗_m– F_L= m x ̈_m should be F_m- mg – 〖cx ̇〗_r– F_L= m x ̈_r
   Similarly, the parameters under those equations should be typed using equation editor. For example, x_r should be x_r. And FL should be F_L.
5. Page 3, line 4, “Method” should be “method”. The first line under (4) & (8) “Where” should be “where” and X=[X_1,X_2] should be X=[x_1,x_2]. u(t) is the control effort and X is the state vector should be U(t)=u(t) is the control effort and X is the state vector
6. Page 3, “3. Propose Control System” changes to “3. Proposed Control System”
7. Page 4, the term sgn(S(t) should be sgn(S(t)) in (12) and (15). Also all the sgn should be modified as sgn which denotes the sign function.
8. Page 5, last paragraph, “lager” should be “large”
9. Page 6, “4. Experimental Result” changes to “4. Experimental Results”
10. The description in the last section “Conclusion” should use the current tense instead of the past tense.

1. The English of the article is substandard.
2. Combining PID and sliding mode algorithm seems an interesting idea, but the theoretic contribution is hardly discussed in the paper.

This circular visual measurement system is interesting and useful. The system is confirmed with good measurement. It is worth of publication.

Recommend to accept this paper. This paaer provided a good methodology of size inspection just by capturing the workpiece image without contact measurement. It is good to industrial application.

The authors proposed weighted K-nearest neighbor classification based on the gradient of class-conditional density. I have some minor comments.

1. In the first column of page 3, Xi^Wj should be Xi^Wi. In the 5th column of the same page, k should be k_0.
2. The definition in equation (4) should be checked again. For example, authors said q is the test sample in page 2, and q is equal to 1 in equation (4). What does q mean? Moreover, the error also happened in equation (5).

The authors improved the robustness of the BDM.
The results show the improvement.I have the following comment.
In the definition of the BDM, each symbol should be explained clearly.

This paper contains some interesting results. A robust best distance measurement (RBDM) is given to improve the robustness of the BDM.
The influences of the distribution characteristics of each neighbor for the classification performance is investigated.
A new method called weighted robust best distance measurement k nearest neighbor method (WRBDMkNN) is proposed.
Experiments are conducted over constructed and real data.
Results show that the proposed method improves the classification performance and robustness of the NN-based method.

In general, This paper is technically sound and the motivation is clear.
This paper is also well written in presentation, methodology and evaluation.
Besides, the literature review is in-depth to guide readers properly. Overall, the quality of the paper is good.

This paper proposed a condition-based location authentication protocol for mobile devices to authenticate users' location claims.
This paper is well written. They design is techcically correct.

Authors consider the hexagonal finite volume methods for PDEs, and apply to the problem about the electrical activity of human ventricular tissues.
In this article, the convergence property of the proposed method is given, and some iterative methods are considered to solve algebraic system, numerical experiments agree with the result.

The manuscript requires minor revision. Suggestions for improvement are as follows.

Some notations are undefined, some missing table number, equation …
Besides, that's would be great if authors may provide the complexity analysis.