E-mail is one of the most successful computer applications ever devised. Similarly to other Computer-Mediated Communication (CMC) systems, e-mail has been described as a communication media that may, occasionally, promote poor social interactions because of the lack of sensorial feedback. Empirical findings based on Speed Communication Analysis (Wicklund & Vandekerckhove, 2000) found e-mails in friendship communication (i.e., informal interaction) to be short and poor in content. The present article reviews recent disclosures on systems and methods that might overcome the sensorial limitations typical of e-mail communication. Among the patents discussed is a method for detecting and reconstructing the emotional state of the e-mail sender. Another system is presented that allows an e-mail sender to express emotional contents by means of musical emoticons. Last, an innovative method is also described that can lead an e-mail user to edit optimal reply messages. Potential limits on the use of these technologies are considered in the conclusions.
Nowadays, the building industry and its associated technologies are experiencing a period of rapid growth, which requires an equivalent growth regarding technologies in the field of vertical transportation. Therefore, the installation of synchronised elevator groups in modern buildings is a common practice in order to govern the dispatching, allocation and movement of the cars shaping the group. So, elevator control and management has become a major field of application for Artificial Intelligence approaches. Methodologies such as fuzzy logic, artificial neural networks, genetic algorithms, ant colonies, or multiagent systems are being successfully proposed in the scientific literature, and are being adopted by the leading elevator companies as elements that differentiate them from their competitors. In this sense, the most relevant companies are adopting strategies based on the protection of their discoveries and inventions as registered patents in different countries throughout the world. This paper presents a comprehensive state of the art of the most relevant recent patents on computer science applied to vertical transportation.
Computer graphics applications often use textures to render synthetic images. These textures can be obtained from a variety of sources such as hand-drawn pictures or scanned photographs. Texture synthesis is an alternative way to create textures. Because synthetic textures can be made any size, visual repetition is avoided. The goal of texture synthesis can be stated as follows: given a texture example, synthesize a new texture that, when perceived by a human observer, appears to be generated by the same underlying process. This paper reviews the recent patents on texture synthesis schemes. The key components in a texture synthesis algorithm, such as neighborhood matching, block sampling, anisometric synthesis, etc., are discussed. Then we discuss the applications of texture synthesis in texture magnification and image repairing. This paper also points out future works on this issue.
There are many different theoretical researches, which deal with the content and quality of teaching. Their common aim is to improve the quality of teaching both for students and pedagogues. The aim of the paper is to give the basic information about methods of the communicative approach to teaching, in teaching programming. The communicative approach to teaching (CAT) is based on the optimization of the amount and retention of knowledge, and the character of subject matter achieved by the higher motivation of students, and applying the knowledge in a real context. The communicative approach to teaching exploits a broad spectrum of methods, which support the general development of instructional ability of students, independent and cooperative solving of problems, and also object teaching. The centre of teaching is created by methods which use mutual communication, together with solving problems in pairs and in groups, and processes elaborating the independent solving of problems. The purpose of this paper is to suggest applying the CAT method with some patent description mainly used in teaching foreign languages, to teaching programming by means of the Java programming language.
Quantum algorithms have the potential to demonstrate that for some problems quantum computation is more efficient than classical computation. A goal of quantum computing is to determine for which problems quantum computers are faster than classical computers. In our survey we present recent quantum algorithms for basic problems from graph and algebra theory. The quantum algorithms for these problems use a combination of Grovers search algorithms, quantum amplitude amplification and quantum random walks. These quantum algorithms are faster than the best known classical algorithms for the corresponding problems.
A new algorithm is presented for blind identification of moving average (MA) models using the 1-D slice of its fourth-order cumulants and the autocorrelation functions. The proposed algorithm utilizes the BPSK signals as MA models input that is an independent and identically distributed (i.i.d) process. Our algorithm is compared with Giannakis algorithm. Simulations verify the good performance of the proposed algorithm.
The function to obtain associated surfaces on coordinate measuring machines (CMMs) is based on the minimization of the distance between measured points and the ideal surface. This function is non-linear for usual surfaces. In many works, to accelerate iterative calculations, the problem is linearized. The aim of this work is to reduce scraps using a transcription optimization of the fitting functionality of mechanical parts in maximum state of matter. An adaptive verification method is suggested. It takes account of the interface properties. A control by a virtual gauge and verification a process is developed to validate the tolerancing according to the previously suggested methodology.
In this paper, we describe a new polygraph system which is based on computer vision technologies. The underpinning idea is to detect pupil size variation from a sequence of images. Based on the variation of the pupil size, we can detect for truth or deception. We have experimented with our system and proved its effectiveness. Compared with traditional polygraph techniques, this is the best computer vision based system to date. It is much simpler compared to old systems and is easier to implement.