Emotion and Adaptation

An Introduction to MultiAgent Systems.

A wide variety of media can be used in learning, including distance learning, such as print, lectures, conference sections, tutors, pictures, video, sound, and computers. Any one instance of distance learning will make choices among these media, perhaps using several.

Multimedia in Learning

Thank you for reading experimental and quasi experimental designs for research. Maybe you have knowledge that, people have search numerous times for their favorite readings like this experimental and quasi experimental designs for research, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they cope with some infectious virus inside their laptop.

Experimental And Quasi Experimental Designs For Research

Mobile application markets such as the Android Marketplace provide a centralized showcase of applications that end users can purchase or download for free onto their mobile phones. Despite the influx of applications to the markets, applications are cursorily reviewed by marketplace maintainers due to the vast number of submissions. User policing and reporting is the primary method to detect misbehaving applications. This reactive approach to application security, especially when programs can contain bugs, malware, or pirated (inauthentic) code, puts too much responsibility on the end users. In light of this, we propose Juxtapp, a scalable infrastructure for code similarity analysis among Android applications. Juxtapp provides a key solution to a number of problems in Android security, including determining if apps contain copies of buggy code, have significant code reuse that indicates piracy, or are instances of known malware. We evaluate our system using more than 58,000 Android applications and demonstrate that our system scales well and is effective. Our results show that Juxtapp is able to detect: 1) 463 applications with confirmed buggy code reuse that can lead to serious vulnerabilities in real-world apps, 2) 34 instances of known malware and variants (13 distinct variants of the GoldDream malware), and 3) pirated variants of a popular paid game.

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Juxtapp: a scalable system for detecting code reuse among android applications

This literature review presents the History, Technology, and Applications of Natural Dialog Systems or simply chatbots. It aims to organize critical information that is a necessary background for further research activity in the field of chatbots. More specifically, while giving the historical evolution, from the generative idea to the present day, we point out possible weaknesses of each stage. After we present a complete categorization system, we analyze the two essential implementation technologies, namely, the pattern matching approach and machine learning. Moreover, we compose a general architectural design that gathers critical details, and we highlight crucial issues to take into account before system design. Furthermore, we present chatbots applications and industrial use cases while we point out the risks of using chatbots and suggest ways to mitigate them. Finally, we conclude by stating our view regarding the direction of technology so that chatbots will become really smart.

Chatbots: History, technology, and applications

The use of chatbots evolved rapidly in numerous fields in recent years, including Marketing, Supporting Systems, Education, Health Care, Cultural Heritage, and Entertainment. In this paper, we first present a historical overview of the evolution of the international community’s interest in chatbots. Next, we discuss the motivations that drive the use of chatbots, and we clarify chatbots’ usefulness in a variety of areas. Moreover, we highlight the impact of social stereotypes on chatbots design. After clarifying necessary technological concepts, we move on to a chatbot classification based on various criteria, such as the area of knowledge they refer to, the need they serve and others. Furthermore, we present the general architecture of modern chatbots while also mentioning the main platforms for their creation. Our engagement with the subject so far, reassures us of the prospects of chatbots and encourages us to study them in greater extent and depth.

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An Overview of Chatbot Technology

Efficient detection of plagiarism in programming assignments of students is of a great importance to the educational procedure. This paper presents a clustering oriented approach for facing the problem of source code plagiarism. The implemented software, called PDetect, accepts as input a set of program sources and extracts subsets (the clusters of plagiarism) such that each program within a particular subset has been derived from the same original. PDetect proposes the use of an appropriate measure for evaluating plagiarism detection performance and supports the idea of combining different plagiarism detection schemes. Furthermore, a cluster analysis is performed in order to provide information beneficial to the plagiarism detection process. PDetect is designed such that it may be easily adapted over any keyword-based programming language and it is quite beneficial when compared with earlier (state-of-the-art) plagiarism detection approaches.

PDetect: A Clustering Approach for Detecting Plagiarism in Source Code Datasets

As the requirements for automatic speech recognition are continually increasing, the demand for accuracy and efficiency is also of particular interest. In this paper, we present most of the well-known Automated Speech Recognition systems (ASR), and we benchmark three of them, namely the IBM Watson, Google, and Wit, using the WER, Hper, and Rper error metrics. The experimental results show that Google’s automatic speech recognition performs better among the three systems. We intend to extend the benchmarking both to include most of the available Automated Speech Recognition systems and increase our test data.

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Lefteris Moussiades

Papers

Chatbots: History, technology, and applications

An Overview of Chatbot Technology

PDetect: A Clustering Approach for Detecting Plagiarism in Source Code Datasets

Α Benchmarking of IBM, Google and Wit Automatic Speech Recognition Systems

Fuzzy lattice reasoning (FLR) type neural computation for weighted graph partitioning