Lecture Notes in Computer Science: Teaching Quality Assessment Model for Software Engineering

2011 ◽  
pp. 637-641
Author(s):  
Qun Jiang ◽  
He Yan ◽  
Xing-Lan Zhang
Keyword(s):  
Software Engineering ◽  
Quality Assessment ◽  
Computer Science ◽  
Science Teaching ◽  
Teaching Quality ◽  
Assessment Model ◽  
Lecture Notes

scholarly journals An Internet of Things Evaluation Algorithm for Quality Assessment of Computer-Based Teaching

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jing Huang
Keyword(s):  
Internet Of Things ◽  
Quality Assessment ◽  
Teaching Quality ◽  
Assessment Model ◽  
Evaluation Index ◽  
Qualitative Assessment ◽  
Index Method ◽  
Evaluation Algorithm ◽  
Computer Based ◽  
Fuzzy Assessment

Internet of Things has the ability to revolutionize computer-based teaching and assess the quality of teaching at the same time. The assessment of teaching efficiency is hampered by two issues: the evaluation index method (EIS) is insufficient, and the assessment framework is incapable of dealing with complicated fuzzy indexes. To address these issues, the theory of fuzzy stratification from IoT perspective is presented for the first time in this paper. This theory is based on the related theory of fuzzy assessment by measuring the teaching quality evaluation index. Initially, theoretical analysis and model measurement were merged to build a better multiangle EIS for teaching quality. To manage fuzzy indexes, a teaching quality assessment model was developed using both quantitative and qualitative studies. The suggested EIS and fuzzy assessment model can effectively evaluate the standard of teaching in schools, colleges, universities, and institutes, according to implementation results. This qualitative assessment approach is empirical and rational, and it strongly promotes the quality enhancement of educational effectiveness, based on our experimental and simulation results.

ROI Based Post Image Quality Assessment Technique on Multiple Localized Filtering Method On Kinect HD Sensor Mobile Robot

2018 ◽  
Vol 3 (2) ◽  
pp. 145
Author(s):  
Kholilatul Wardani ◽  
Aditya Kurniawan
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Similarity Index ◽  
Assessment Model ◽  
Sensor Data ◽  
Edge Region ◽  
Kinect Sensor ◽  
Image Region ◽  
Filtering Technique

 The ROI (Region of Interest) Image Quality Assessment is an image quality assessment model based on the SSI (Structural Similarity Index) index used in the specific image region desired to be assessed. Output assessmen value used by this image assessment model is 1 which means identical and -1 which means not identical. Assessment model of ROI Quality Assessment in this research is used to measure image quality on Kinect sensor capture result used in Mobile HD Robot after applied Multiple Localized Filtering Technique. The filter is applied to each capture sensor depth result on Kinect, with the aim to eliminate structural noise that occurs in the Kinect sensor. Assessment is done by comparing image quality before filter and after filter applied to certain region. The kinect sensor will be conditioned to capture a square black object measuring 10cm x 10cm perpendicular to a homogeneous background (white with RGB code 255,255,255). The results of kinect sensor data will be taken through EWRF 3022 by visual basic 6.0 program periodically 10 times each session with frequency 1 time per minute. The results of this trial show the same similar index (value 1: identical) in the luminance, contrast, and structural section of the edge region or edge region of the specimen. The value indicates that the Multiple Localized Filtering Technique applied to the noise generated by the Kinect sensor, based on the ROI Image Quality Assessment model has no effect on the image quality generated by the sensor.

scholarly journals Coleman integration for even-degree models of hyperelliptic curves

2015 ◽  
Vol 18 (1) ◽  
pp. 258-265 ◽  
Author(s):  
Jennifer S. Balakrishnan
Keyword(s):  
Number Theory ◽  
Computer Science ◽  
Hyperelliptic Curves ◽  
Open Book ◽  
Line Integral ◽  
Book Series ◽  
Numerical Examples ◽  
Lecture Notes ◽  
Integration Algorithms ◽  
Mathematical Sciences

The Coleman integral is a $p$-adic line integral that encapsulates various quantities of number theoretic interest. Building on the work of Harrison [J. Symbolic Comput. 47 (2012) no. 1, 89–101], we extend the Coleman integration algorithms in Balakrishnan et al. [Algorithmic number theory, Lecture Notes in Computer Science 6197 (Springer, 2010) 16–31] and Balakrishnan [ANTS-X: Proceedings of the Tenth Algorithmic Number Theory Symposium, Open Book Series 1 (Mathematical Sciences Publishers, 2013) 41–61] to even-degree models of hyperelliptic curves. We illustrate our methods with numerical examples computed in Sage.

scholarly journals Application of Three Deep Machine-Learning Algorithms in a Construction Assessment Model of Farmland Quality at the County Scale: Case Study of Xiangzhou, Hubei Province, China

Agriculture ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 72
Author(s):  
Li Wang ◽  
Yong Zhou ◽  
Qing Li ◽  
Tao Xu ◽  
Zhengxiang Wu ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Index System ◽  
Quality Index ◽  
Hubei Province ◽  
Machine Learning Algorithms ◽  
Assessment Model ◽  
Soil Conditions ◽  
The Mean ◽  
County Scale ◽  
Assessment Results

Constructing a scientific and quantitative quality-assessment model for farmland is important for understanding farmland quality, and can provide a theoretical basis and technical support for formulating rational and effective management policies and realizing the sustainable use of farmland resources. To more accurately reflect the systematic, complex, and differential characteristics of farmland quality, this study aimed to explore an intelligent farmland quality-assessment method that avoids the subjectivity of determining indicator weights while improving assessment accuracy. Taking Xiangzhou in Hubei Province, China, as the study area, 14 indicators were selected from four dimensions—terrain, soil conditions, socioeconomics, and ecological environment—to build a comprehensive assessment index system for farmland quality applicable to the region. A total of 1590 representative samples in Xiangzhou were selected, of which 1110 were used as training samples, 320 as test samples, and 160 as validation samples. Three models of entropy weight (EW), backpropagation neural network (BPNN), and random forest (RF) were selected for training, and the assessment results of farmland quality were output through simulations to compare their assessment accuracy and analyze the distribution pattern of farmland quality grades in Xiangzhou in 2018. The results showed the following: (1) The RF model for farmland quality assessment required fewer parameters, and could simulate the complex relationships between indicators more accurately and analyze each indicator’s contribution to farmland quality scientifically. (2) In terms of the average quality index of farmland, RF > BPNN > EW. The spatial patterns of the quality index from RF and BPNN were similar, and both were significantly different from EW. (3) In terms of the assessment results and precision characterization indicators, the assessment results of RF were more in line with realities of natural and socioeconomic development, with higher applicability and reliability. (4) Compared to BPNN and EW, RF had a higher data mining ability and training accuracy, and its assessment result was the best. The coefficient of determination (R2) was 0.8145, the mean absolute error (MAE) was 0.009, and the mean squared error (MSE) was 0.012. (5) The overall quality of farmland in Xiangzhou was higher, with a larger area of second- and third-grade farmland, accounting for 54.63%, and the grade basically conformed to the trend of positive distribution, showing an obvious pattern of geographical distribution, with overall high performance in the north-central part and low in the south. The distribution of farmland quality grades also varied widely among regions. This showed that RF was more suitable for the quality assessment of farmland with complex nonlinear characteristics. This study enriches and improves the index system and methodological research of farmland quality assessment at the county scale, and provides a basis for achieving a threefold production pattern of farmland quantity, quality, and ecology in Xiangzhou, while also serving as a reference for similar regions and countries.

scholarly journals Leveraging Final Degree Projects for Open Source Software Contributions

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1181
Author(s):  
Juanan Pereira
Keyword(s):  
Graduate Students ◽  
Software Engineering ◽  
Computer Science ◽  
Open Source ◽  
Communication Skills ◽  
Open Source Software ◽  
Real World ◽  
Practical Experience ◽  
Multiple Challenges ◽  
Final Degree

(1) Background: final year students of computer science engineering degrees must carry out a final degree project (FDP) in order to graduate. Students’ contributions to improve open source software (OSS) through FDPs can offer multiple benefits and challenges, both for the students, the instructors and for the project itself. This work reports on a practical experience developed by four students contributing to mature OSS projects during their FDPs, detailing how they addressed the multiple challenges involved, both from the students and teachers perspective. (2) Methods: we followed the work of four students contributing to two established OSS projects for two academic years and analyzed their work on GitHub and their responses to a survey. (3) Results: we obtained a set of specific recommendations for future practitioners and detailed a list of benefits achieved by steering FDP towards OSS contributions, for students, teachers and the OSS projects. (4) Conclusion: we find out that FDPs oriented towards enhancing OSS projects can introduce students into real-world, practical examples of software engineering principles, give them a boost in their confidence about their technical and communication skills and help them build a portfolio of contributions to daily used worldwide open source applications.

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