Computing with the Square Root of NOT

To the two classical reversible 1-bit logic gates, i.e. the identity gate (a.k.a. the follower) and the NOT gate (a.k.a. the inverter), we add an extra gate, the square root of NOT. Similarly, we add to the 24 classical reversible 2-bit circuits, both the square root of NOT and the controlled square root of NOT. This leads to a new kind of calculus, situated between classical reversible computing and quantum computing.

Two-Language, Two-Paradigm Introductory Computing Curriculum Model and its Implementation

This paper analyzes difficulties with the introduction of object-oriented concepts in introductory computing education and then proposes a two-language, two-paradigm curriculum model that alleviates such difficulties. Our two-language, two-paradigm curriculum model begins with teaching imperative programming using Python programming language, continues with teaching object-oriented computing using Java, and concludes with teaching object-oriented data structures with Java.

A Linear Time Algorithm for Computing Longest Paths in Cactus Graphs

ACM Computing Classification System (1998): G.2.2.

A New Method for Computing the Eccentric Connectivity Index of Fullerenes

ACM Computing Classification System (1998): G.2.2, G.2.3.

Content-Based Image Retrieval for Computer Tomography Images Using Wavelet Descriptors

An approach to building a CBIR-system for searching computer tomography images using the methods of wavelet-analysis is presented in this work. The index vectors are constructed on the basis of the local features of the image and on their positions. The purpose of the proposed system is to extract visually similar data from the individual personal records and from analogous analysis of other patients.

Changes and Shifts in Computing Curricula

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

The Application of Cloud Computing in Education

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

VisibleZ: A Mainframe Architecture Emulator for Computing Education

This paper describes a PC-based mainframe computer emulator called VisibleZ and its use in teaching mainframe Computer Organization and Assembly Programming classes. VisibleZ models IBM’s z/Architecture and allows direct interpretation of mainframe assembly language object code in a graphical user interface environment that was developed in Java. The VisibleZ emulator acts as an interactive visualization tool to simulate enterprise computer architecture. The provided architectural components include main storage, CPU, registers, Program Status Word (PSW), and I/O Channels. Particular attention is given to providing visual clues to the user by color-coding screen components, machine instruction execution, and animation of the machine architecture components. Students interact with VisibleZ by executing machine instructions in a step-by-step mode, simultaneously observing the contents of memory, registers, and changes in the PSW during the fetch-decode-execute machine instruction cycle. The object-oriented design and implementation of VisibleZ allows students to develop their own instruction semantics by coding Java for existing specific z/Architecture machine instructions or design and implement new machine instructions. The use of VisibleZ in lectures, labs, and assignments is described in the paper and supported by a website that hosts an extensive collection of related materials. VisibleZ has been proven a useful tool in mainframe Assembly Language Programming and Computer Organization classes. Using VisibleZ, students develop a better understanding of mainframe concepts, components, and how the mainframe computer works. ACM Computing Classification System (1998): C.0, K.3.2.

Three New Methods for Computing Subresultant Polynomial Remainder Sequences (PRS’S)

Given the polynomials f, g ∈ Z[x] of degrees n, m, respectively, with n > m, three new, and easy to understand methods — along with the more efficient variants of the last two of them — are presented for the computation of their subresultant polynomial remainder sequence (prs). All three methods evaluate a single determinant (subresultant) of an appropriate sub-matrix of sylvester1, Sylvester’s widely known and used matrix of 1840 of dimension (m + n) × (m + n), in order to compute the correct sign of each polynomial in the sequence and — except for the second method — to force its coefficients to become subresultants. Of interest is the fact that only the first method uses pseudo remainders. The second method uses regular remainders and performs operations in Q[x], whereas the third one triangularizes sylvester2, Sylvester’s little known and hardly ever used matrix of 1853 of dimension 2n × 2n. All methods mentioned in this paper (along with their supporting functions) have been implemented in Sympy and can be downloaded from the link http://inf-server.inf.uth.gr/~akritas/publications/subresultants.py

Context -aware data caching for mobile computing environments

The deployment of wireless communications coupled with the popularity of portable devices has led to significant research in the area of mobile data caching. Prior research has focused on the development of solutions that allow applications to run in wireless environments using proxy based techniques. Most of these approaches are semantic based and do not provide adequate support for representing the context of a user (i.e., the interpreted human intention.). Although the context may be treated implicitly it is still crucial to data management. In order to address this challenge this dissertation focuses on two characteristics: how to predict (i) the future location of the user and (ii) locations of the fetched data where the queried data item has valid answers. Using this approach, more complete information about the dynamics of an application environment is maintained. ^ The contribution of this dissertation is a novel data caching mechanism for pervasive computing environments that can adapt dynamically to a mobile user's context. In this dissertation, we design and develop a conceptual model and context aware protocols for wireless data caching management. Our replacement policy uses the validity of the data fetched from the server and the neighboring locations to decide which of the cache entries is less likely to be needed in the future, and therefore a good candidate for eviction when cache space is needed. The context aware driven prefetching algorithm exploits the query context to effectively guide the prefetching process. The query context is defined using a mobile user's movement pattern and requested information context. Numerical results and simulations show that the proposed prefetching and replacement policies significantly outperform conventional ones. ^ Anticipated applications of these solutions include biomedical engineering, tele-health, medical information systems and business. ^

How does the healthcare industry involve users in medical device development? Pointers for UbiHealth

This paper introduces the Multidisciplinary Assessment of Technology Centre for Healthcare (MATCH) and outlines the problem of integrating a user-centred approach for development of medical devices together with the information and communication technology environments in which they are increasingly required to operate. We highlight some of the regulatory requirements that are relevant to user needs consideration in medical device development. Finally, we reveal a range of limitations in the current practice of the medical device industry in the area of user needs capture, based on responses from interviews with MATCH’s industry partners.

Educated to Learn : How to enhance the education of computer science and informatics

The very nature of computer science with its constant changes forces those who wish to follow to adapt and react quickly. Large companies invest in being up to date in order to generate revenue and stay active on the market. Universities, on the other hand, need to imply same practices of staying up to date with industry needs in order to produce industry ready engineers. By interviewing former students, now engineers in the industry, and current university staff this thesis aims to learn if there is space for enhancing the education through different lecturing approaches and/or curriculum adaptation and development. In order to address these concerns a qualitative research has been conducted, focusing on data collection obtained through semi-structured live world interviews. The method used follows the seven stages of research interviewing introduced by Kvale and focuses on collecting and preparing relevant data for analysis. The collected data is transcribed, refined, and further on analyzed in the “Findings and analysis” chapter. The focus of analyzing was answering the three research questions; learning how higher education impacts a Computer Science and Informatics Engineers’ job, how to better undergo the transition from studies to working in the industry and how to develop a curriculum that helps support the previous two. Unaltered quoted extracts are presented and individually analyzed. To paint a better picture a theme-wise analysis is presented summing valuable themes that were repeated throughout the interviewing phase. The findings obtained imply that there are several factors directly influencing the quality of education. From the student side, it mostly concerns expectation and dedication involving studies, and from the university side it is commitment to the curriculum development process. Due to the time and resource limitations this research provides findings conducted on a narrowed scope, although it can serve as a great foundation for further development; possibly as a PhD research.

An Integrated Soft Computing Approach to Hughes Syndrome Risk Assessment

The AntiPhospholipid Syndrome (APS) is an acquired autoimmune disorder induced by high levels of antiphospholipid antibodies that cause arterial and veins thrombosis, as well as pregnancy-related complications and morbidity, as clinical manifestations. This autoimmune hypercoagulable state, usually known as Hughes syndrome, has severe consequences for the patients, being one of the main causes of thrombotic disorders and death. Therefore, it is required to be preventive; being aware of how probable is to have that kind of syndrome. Despite the updated of antiphospholipid syndrome classification, the diagnosis remains difficult to establish. Additional research on clinically relevant antibodies and standardization of their quantification are required in order to improve the antiphospholipid syndrome risk assessment. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model allows for improving the diagnosis, classifying properly the patients that really presented this pathology (sensitivity higher than 85%), as well as classifying the absence of APS (specificity close to 95%).

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.