Teachers deal with plagiarism on a regular basis, so they try to prevent and detect plagiarism, a task that is complicated by the large size of some classes. Students who cheat often try to hide their plagiarism (obfuscate), and many different similarity detection engines (often called plagiarism detection tools) have been built to help teachers. This article focuses only on plagiarism detection and presents a detailed systematic review of the field of source-code plagiarism detection in academia. This review gives an overview of definitions of plagiarism, plagiarism detection tools, comparison metrics, obfuscation methods, datasets used for comparison, and algorithm types. Perspectives on the meaning of source-code plagiarism detection in academia are presented, together with categorisations of the available detection tools and analyses of their effectiveness. While writing the review, some interesting insights have been found about metrics and datasets for quantitative tool comparison and categorisation of detection algorithms. Also, existing obfuscation methods classifications have been expanded together with a new definition of “source-code plagiarism detection in academia.”

Source-code Similarity Detection and Detection Tools Used in Academia: A Systematic Review

Even though there are various security systems consuming large power are available in market nowadays, robbery rate is very high. We are proposing a novel system to prevent robbery in highly secure areas with lesser power consumption. T his system has face-recognition technology which grants access to only authorized people to enter that area. If others enter the place without access using some other means, then the system alerts the security personnel and streams the video captured by th e security camera. The facerecognition is done using PCA algorithm. The video transmitted is compressed and transmitted by ENVMT. By using this ENVMT, the video can play with lesser bandwidth consumption, latency and jitter.

/pdf/security-system-w-ith-face-recognition-sms-alert-and-2q2yoibf4n.pdf

Security system w ith face recognition , sms alert and embedded network video m onitoring terminal

The advent of massive open online courses (MOOC) poses challenges for teaching and learning programming. This paper has analyzed these challenges and thereby proposed a self-motivating learning platform for students in the introductory programming course. Novel mechanisms of online assignments and examination have been introduced. Our platform provides functions for self-motivating learning and practicing in MOOC, which makes it distinguish from the others. For example, self-paced timetable with supervision, self-motivated exercise contents, exercise market, and relative ranking. The automatic grading approach is also a highlight. Programs even with syntactic or semantic errors can be automatically graded. Our platform gains popularity among both students and teachers. The platform has been used together with a programming MOOC. This course is ranked as the third most popular courses among over 500 courses. The platform has also been used by more than 100 other universities. The application of the platform in both MOOC and the traditional classroom courses has shown that students' self-motivation in learning programming has been greatly promoted, and their practical skills have also been significantly improved.

Motivating students with new mechanisms of online assignments and examination to meet the MOOC challenges for programming

Since few years there is tremendous growth in the research of surveillance system especially in computer vision based surveillance system. This paper proposes a monitoring system which includes motion detection algorithm is implemented along with some alarming features. The system proposed in this paper is IOT based image processing unit with internet connectivity so that data can be transferred to any remote server for example Cloud. The motion detection feature of a system provides necessary isolation of most significant video clips that eliminates time consuming reviewing process required in normal video surveillance system. The main idea behind this system is to detect the presence of any moving object especially a human and then start recording a video from the motion is detected. The video clip can be stored locally as well as uploaded to cloud server so that it can be viewed from anywhere in the world and necessary alarms then generated by the system. There are several micro controllers are available that can be interfaced along with digital camera to achieve this goal.

Intelligent embedded video monitoring system for home surveillance

In recent years, lots of research have been done in computer vision domain. Video surveillance in real-time scenario, especially for humans, like tracking and behavior analysis is one of the most active research topics in computer vision and artificial intelligence in present situation. The main focus is providing the low-cost and efficient video surveillance system for home application and can have wide scope in other areas such as elevator monitoring and server room monitoring. As the traditional surveillance system requires huge storage capacity and consumes lot of network bandwidth, hence it becomes necessary to provide solution for such design issues. This paper presents the implementation of motion detection algorithm for live camera streaming and thus allows analyzing incoming image stream, and recognizing any movement occurs in the area and if so then triggers video recorder to save the information-contained video clip.

Home Surveillance System Using Internet of Things

Diggitalization of network video monitoring system, which has advantages of unlimited distance control, flexible extension and so on, is becoming a new standard of security system. Due to limitations of network bandwidth, video signals collected must be compressed to achieve real-time video transmission on the network. Therefore, how to maintain the high quality of the compressed signal, and meanwhile minimize the amount of data becomes a key technical problem To achieve this goal, an embedded network video monitoring terminal was designed and implemented by us This terminal consists of dedicated MPEG-4 compression ASIC, 32-bit embedded processor, 8-bit micro controller, 4-channel video capturing and decoding chips etc. Its corresponding software has been developed Users can not only watch the real-time monitoring images directly with the built-in embedded web server through the network,but also login central server, watch the monitoring images and control the network video terminal through dedicated software. Test results show that our terminal can better utilize TCP/IP network bandwidth Video can play without latency and fitter, as a result of real-time transmission and reception of digital video signal.

Design and implementation of embedded network video monitoring terminal

Studies have shown that many students have similar programs in programming class, most of which due to plagiarism. Students may simply modify others' programs as their own. This makes the assessment standards for students' programs with lots of ambiguity and uncertainty, limiting assessment accuracy and efficiency, and reducing the reliability of test results. To solve this problem, a student program plagiarism detection approach is proposed based on a data mining algorithm. Firstly, similar code fragments are mined by the CloSpan algorithm. Then, similarities between programs are calculated. Finally, the plagiarism list is output. Experiments showed that compared with the widely used plagiarism detection tool MOSS, our approach is can not only more accurately give statistical information of the similar program detected, but also be able to visualize the similar code fragments, which can greatly increase detection efficiency.

Detection of plagiarism in students' programs using a data mining algorithm

Sentence similarity computation is the more important research topics of domain of natural language processing, has a very wide range of applications, restricting the development of certain domain. In this paper, the characteristics and difficulties of the Chinese sentence similarity computation were introduced. we analyzed the advantages and shortcoming of the current commonly Chinese sentence similarity computation methods.

Research on Chinese Sentence Similarity Computation

Traditional teaching-learning has disadvantages such as insufficient teacher-student communication, insufficient personalized learning, serious plagiarism, and lacking of automatic grading of assignments. To solve these problems, an ecological network teaching and learning environment is proposed based on social constructivist teaching ideas. This platform consists of a teacher oriented ecological teaching platform and a student oriented online self-learning platform. We have explored and practiced various modes of teaching-learning based on this platform. Comparison with the traditional teaching-learning mode has showed that the ecological network environment can effectively improve the teaching and learning effects.

https://ieeexplore.ieee.org/iel5/6175418/6181892/06181981.pdf

Wang Zhifei

Papers

Design and implementation of embedded network video monitoring terminal

Detection of plagiarism in students' programs using a data mining algorithm

Research on Chinese Sentence Similarity Computation

An ecological network teaching-learning environment

Storage virtualization of object based system