Search

A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of Master’s of Science in Mathematical and Computer Science and Engineering of the Nelson Mandela African Institution of Science and Technology

ARt Image Exploration Space (ARIES) is a free, cloud-based dynamic environment offering art historians and others an extensive array of practical tools for analysing images. It is the product of a successful collaboration between art historians, librarians, computer scientists, and engineers from the Frick Art Reference Library, New York University's Tandon School of Engineering, and Brazil's Universidade Federal Fluminense. ARIES is a powerful tool for art historians, both replicating and augmenting traditional methods they have long-used to study images.1 With the advent of the prevalent use of digital photos, art historians lacked the technology capable of replacing what they had previously been able to accomplish in the analogue world. Wood Ruby and Deutch realized that art historians needed an out-of-the-box solution that didn't require extensive knowledge of other disciplines (computer science and engineering). The result of successful collaborations and a generous donation, ARIES is now available in BETA form at www.artimageexplorationspace.com.

Шмелева Евгения Дмитриевна - научный сотрудник Центра социологии высшего образования Института образования Национального исследовательского университета «Высшая школа экономики». E-mail: eshmeleva@hse.ruФрумин Исак Давидович - научныи руководитель Института образования Национального исследовательского университета«Высшая школа экономики». E-mail: ifroumin@hse.ruАдрес: 101000, Москва, ул. Мясницкая, 20.Инженерному образованию в России сегодня уделяется особое внимание: около половины всех бюджетных мест в вузах выделяется на инженерные направления подготовки. И в то же время среди студентов этого профиля наблюдается наиболее высокий уровень выбытия. Цель данного исследования - оценить масштаб выбытия студентов инженерно-технического профиля в начале и середине обучения, а также установить факторы выбытия. Исследование опирается на данные, полученные в ходе опроса более 4 тыс. студентов инженерных направлений подготовки в 34 российских вузах, составляющих репрезентативную национальную выборку, а также на административные сведения об отчислениях студентов. При анализе факторов выбытия студентов в первые три семестра обучения авторы опираются на теоретическую рамку В. Тинто, согласно которой социальная и академическая интеграция студентов является критически важным условием успешного продолжения обучения в выбранном университете. Результаты исследования подтверждают ключевую роль академической интеграции, а именно посещения занятий и активного взаимодействия с преподавателями, в предотвращении выбытия студентов, но опровергают гипотезу о значимости социальной интеграции. Риску выбытия подвергаются студенты с низкими баллами ЕГЭ по математике, а также те, чей фактический выбор направления подготовки не соответствовал желаемому. Гипотеза о том, что уровень выбытия в высокоселективных вузах выше, чем в прочих, не нашла подтверждения. Предложены рекомендации для университетов, направленные на снижение уровня выбытия среди студентов.

We have discussed in this elucidation paper about correlation of Fibonacci sequence and golden ratio with its applications in engineering and science. One of the most recurring sequences in nature is the Fibonacci sequence. As the sequence was explored, it was found out that this sequence led to the golden ratio. This study tried to apply the concept of Fibonacci and golden ratio to maximize efficiency of our live life. We consider self-similar curve like golden spiral in whose nature their beauty is much admired. The explanations show that source of Fibonacci numbers and how to exist Fibonacci numbers in the world we live. The mathematical theories of Fibonacci numbers and golden ratio gives the source of many new ideas in Mathematics, Chemistry, Civil engineering, Architecture, Automobile engineering, Philosophy, Botanic and biology, Electrical engineering, Computer science and engineering, Mechanical engineering, Communication systems, Mathematical education as well as theoretical physics and physics of high energy particles.

Predicting the binding affinity between compounds and proteins with reasonable accuracy is crucial in drug discovery. Computational prediction of binding affinity between compounds and targets greatly enhances the probability of finding lead compounds by reducing the number of wet-lab experiments. Machine-learning and deep-learning techniques using ligand-based and target-based approaches have been used to predict binding affinities, thereby saving time and cost in drug discovery efforts. In this review, we discuss about machine-learning and deep-learning models used in virtual screening to improve drug-target interaction (DTI) prediction. We also highlight current knowledge and future directions to guide further development in this field.

Differential count of leukocytes plays a consequential role in the determination of diagnostic details of a patient. Conventionally, leukocyte identification is performed manually by skilled medica...

Significance Societal stereotypes that girls are less interested than boys in computer science and engineering are endorsed by children and adolescents in a large and socioeconomically diverse sample, across multiple racial/ethnic and gender intersections, and as early as age six (first grade). Gender-interest stereotypes may contribute to subsequent gender disparities in the pursuit of these societally important fields. Addressing interest stereotypes may help improve educational equity., Societal stereotypes depict girls as less interested than boys in computer science and engineering. We demonstrate the existence of these stereotypes among children and adolescents from first to 12th grade and their potential negative consequences for girls’ subsequent participation in these fields. Studies 1 and 2 (n = 2,277; one preregistered) reveal that children as young as age six (first grade) and adolescents across multiple racial/ethnic and gender intersections (Black, Latinx, Asian, and White girls and boys) endorse stereotypes that girls are less interested than boys in computer science and engineering. The more that individual girls endorse gender-interest stereotypes favoring boys in computer science and engineering, the lower their own interest and sense of belonging in these fields. These gender-interest stereotypes are endorsed even more strongly than gender stereotypes about computer science and engineering abilities. Studies 3 and 4 (n = 172; both preregistered) experimentally demonstrate that 8- to 9-y-old girls are significantly less interested in an activity marked with a gender stereotype (“girls are less interested in this activity than boys”) compared to an activity with no such stereotype (“girls and boys are equally interested in this activity”). Taken together, both ecologically valid real-world studies (Studies 1 and 2) and controlled preregistered laboratory experiments (Studies 3 and 4) reveal that stereotypes that girls are less interested than boys in computer science and engineering emerge early and may contribute to gender disparities.

As cybersecurity issues become ever more prevalent in today’s society, it is imperative that our computer science and engineering programs train students to work in cybersecurity fields. The University of Cincinnati’s Department Electrical Engineering and Computer Science, part of a NSA Center of Excellence, is developing a new B.S. in Cybersecurity Engineering which will be coordinated with cybersecurity programs in Information Technology and in Political Science. We describe our current cybersecurity certificate progran and our proposed new B.S. in Cybersecurity Engineering, which will meet the criteria to apply for ABET EAC accreditation.

In today's society, the popularization rate of computers in the whole country and even all over the world is increasing rapidly year by year. This makes People's Daily work closely connected with computers, information technology and the Internet. As an auxiliary tool, the computer provides great convenience for the process of teaching. Intelligent tools make the learning process more convenient, so the significance of computer science and technology to computer education is huge. In the teaching process, teachers should try their best to use the advantages of computers to assist teaching, and provide students with better network learning environment and learning conditions. Different from the traditional teaching methods, the application of computer technology to education has gradually formed a new type of computer education. This has caused a great change to the current situation of China's education development, and at the same time, China's education model is also faced with various problems.

Here we introduce a new column that explores IEEE Computer Magazine’s contribution to the computing literature and how it is laying the foundation for the future of computer science and engineering.

Nanotechnology is the science of objects

Data is the most crucial component of a successful ML system. Once a machine learning model is developed, it gets obsolete over time due to presence of new input data being generated every second. In order to keep our predictions accurate we need to find a way to keep our models up to date. Our research work involves finding a mechanism which can retrain the model with new data automatically. This research also involves exploring the possibilities of automating machine learning processes. We started this project by training and testing our model using conventional machine learning methods. The outcome was then compared with the outcome of those experiments conducted using the AutoML methods like TPOT. This helped us in finding an efficient technique to retrain our models. These techniques can be used in areas where people do not deal with the actual working of a ML model but only require the outputs of ML processes.

Decisions about participation in computer science and engineering opportunities are often made prior to high school, and these decisions are frequently mediated by prior experience, interes...

Pap smear is a microscopic screening process of cervical smear used to detect pre-cancerous and cancerous cells in the cervix region. Cell nuclei segmentation is one of the most significant task in cervical cell image analysis which aids in identifyi

Age-related Macular Degeneration (AMD) is the leading cause of legal blindness and central vision loss in the 50 above age group among both developed and developing countries. In India, the prevalence of early late ARMD is similar to that observed in

Color is considered to be a major characteristic feature that is used for distinguishing benign and malignant melanocytic lesions. Most of malignant melanomas are characterized by the presence of six suspicious colors inspired from the ABCD dermoscopic rule. The presence of these suspicious colors histopathologically indicates the presence of melanin in the deeper layers of the epidermis and dermis. The objective of the proposed work is to evaluate the role of color features, a set of fifteen color features have been extracted from the region of interest to determine the role of color in malignancy detection. Further, a set of ensemble classifiers with dynamic selection techniques are used for classification of the extracted features, yielding an average accuracy of 87.5% for classifying benign and malignant lesions.

This article explores one group’s use of action research (AR) and lesson study in three US university-level computer science courses affecting 85 undergraduate computer science and engineer...

Machine Translation Systems are part of Natural Language Processing (NLP) that makes communication possible among people using their own native language through computer and smart media devices. This paper describes recent progress in language dictionaries and machine translation commonly used for communications and social interaction among people or Internet users worldwide who speak different languages. Problems of accuracy and quality related to computer translation systems encountered in web & Apps-based translation are described and discussed. Possible programming solutions to the problems are also put forward to create software tools that are able to analyze and synthesize language intelligently based on semantic representation of sentences and phrases. Challenges and problems on Apps-based machine translation on smart devices towards AI, NLP, smart learning and understanding still remain until now, and need to be addressed and solved through collaboration between computational linguists and computer scientists.

The data management group at the Nanyang Technological University (dante) was founded in 2009 by the first author when the School of Computer Science and Engineering hired two young faculty members in this area. The group currently consists of three faculty members and more than twenty graduate students, research assistants, and postdocs. Our alumni include faculty members at the Chinese University of Hong Kong, National University of Singapore, University of New South Wales, and several researchers and engineers at Facebook, Google, eBay, Huawei, and other technology companies. The group's major funding is from the Ministry of Education in Singapore, National Research Foundation, and companies such as Huawei.

This presentation considers elements of Software Performance Engineering (SPE) and how they have evolved. It addresses both skills needed by practitioners and areas of research. Which topics should be covered? How can the education cover realistic systems and problems? What is the history of SPE and is it relevant today? Are these topics unique to SPE education? How should SPE education be integrated with other specialties in Computer Science and Engineering?

Computer animations are widely used to improve comprehension. They are used in almost all disciplines. However, a poorly designed animation may not improve learning as such animations may increase the cognitive load. As a result, quite a lot of research is being focused on design principles that would be effective with respect to the cognitive load theory and can be integrated into animations to improve comprehension. This research work found the answer through a well-designed experimental study. The present study first identified effective design principles through an extensive literature review. Thereafter, an experimental study was designed in which 50 students of fourth semester of CSE (Computer Science and Engineering) participated willingly. The participants were randomly divided into two groups of 25 students each. The Group-1 was taught using modern animations, which were designed according to the selected design principles, whereas Group-2 was taught with conventional animations with auditory explanation only. A t-test was conducted on the post-test scores and found that the variances between the groups were equal (F=1.144, Sig = 0.290). Further, the two-tailed value was observed and found to be

Research in smart homes is still quite recent; however, there is no doubt that it will become a pervasive research topic in the near future. This chapter analyzes the whole research production on smart homes indexed in the Scopus database from 1985 to 2019, yielding a total of 11,000 studies. One of the goals of this chapter is to identify the main countries and institutions that have published on this topic and what their interest has been throughout the time. Four out of 116 countries stand out in this field, namely China, USA, India, and South Korea. In terms of the main institutions, the three with the highest scientific output are Ulster University (UK), CNRS Centre National de la Recherche Scientifique (France), and Universite Grenoble Alpes (France). Another aim of the chapter is to determine the research fields and subfields investigated about smart homes. The publications are mainly focused on two scientific fields, that is, computer science and engineering, accounting for 64% of the overall scientific production. In an aggregate analysis of all publications, four main clusters have been identified, namely Internet of Things, Activity Recognition, Security, and Energy.

The past 30 years have seen increased adoption of learning management systems (LMSs) in education. Several studies have investigated the usability of LMSs for students. However, very few studies have assessed the usability from the instructors’ perspective. Usability issues can pose challenges for instructors who use LMSs to create, manage and deliver courses. These challenges require instructors to spend extra time and energy on tackling the challenges rather on teaching-related tasks, which will have negative impacts on learners’ experiences and learning outcomes. This paper aims to identify usability challenges in LMSs for instructors. We used Canvas as an example and conducted user testing with 35 university instructors in computer science and engineering disciplines. Pre- and post-interviews were transcribed and analyzed together with the observation data during their use of Canvas to carry out tasks. The results show that, although Canvas has made continuous efforts to improve its usability, instructors still face some usability challenges. Instructors are a diverse user group for LMSs. Further research should consider recruiting participants from other disciplines and investigating other LMSs to identify possibilities for improving general usability of digital tools for instructors.

The problem of simplifying a complex shape with simpler ones is an important research area in computer science and engineering. In this paper we investigate the effect of visibility properties of polygons when their boundaries are approximated to have simpler shapes. The presented algorithm is expected to have wide applications in simplifying 1.5D terrain which are restricted class of simple polygons.

The aim of this paper is to develop a web application where scholars of the Faculty of Computer Science and Engineering (FINKI) at the University of Ss. Cyril and Methodius can display and share their projects and publications. Visitors can view, search through, and filter the authors, projects and publications that can be added and edited by the administrators via the administrator panel. In this paper, we first explain the type of system we are building and go through similar existing systems explaining how they work and what they offer. Then, we go through the programming languages and technologies we decided to use to develop this web application. After that, the development phase follows, where we describe each of the features we implemented. In The Final Product section we finally show images where you can see how the web application works and what it looks like. We finish the paper with a conclusion, briefly summarizing what we have achieved.

We present a Software Quality course taught in a MSc program in Computer Science and Engineering. The course takes an overview (‘breadth’) approach, reviewing the most important topics that contribute to the quality of software. The course has been taught traditionally as well as online; we discuss the advantages and disadvantages of both styles and point out what should be kept from the online experience. We also discuss the students’ evaluation and feedback.

Fifty years after the publication of the first algorithms for the automatic detection of Atrial Fibrillation (AF), this cardiac condition is still the most studied from the computer science and engineering perspectives. Machine learning techniques are widely applied to a variety of problems, including detection, characterization, prediction and simulation, in general with promising results. In the last years, the Big Data + Deep Learning binomial is getting most of the attention in academia and industry, but on many occasions this approach fails on capitalizing all the knowledge acquired in previous decades of research. This article, written as a companion to the keynote with the same title presented in the CinC 2020 conference, tries to illustrate the importance of exploiting expert knowledge and classical approaches in synergy with the most advanced deep learning methods, which by themselves have fundamental limitations. The discussion is built around the AF detection problem and the conclusions extracted from the Physionet/CinC Challenge 2017, but the main points can be relevant in other problems for which humans have a better answer than computers, and this answer can be described.

The university has been applying a teaching methodology based on continuous assessment over the last few years. The main advantage of this methodology is that students acquire the knowledge gradually, so that they consolidate it better in their memory; however, they run the risk of forgetting what was studied in the first parts of the course when they finish it. To motivate students to review what they learnt, we have implemented an augmented reality mobile application and methodology with which students review the contents of the subject through the serious game. Moreover, the game focuses on the specific difficulties of each student by reinforcing those questions that are most difficult for them. In this paper, we also present how the game has been customized for various courses from the Degree in Computer Science and Engineering at the University of Cadiz and which results were obtained.

Association rule mining is a popular approach to find out the frequent itemset from a database and hence discover the association rules exist for those itemsets. It often turns out to be useful to explore the interestingness among the data. Student’s educational information is one such important area where mining algorithms can be applied to uncover useful hidden information for improving academics. In this regard, the association rule mining techniques have been used in the present work to study the importance of prerequisite subjects on academic results of dependent subjects. The dataset used in this study contains subject-wise semester marks collected throughout the eight semesters of 117 students of Computer Science and Engineering bachelor course of a university of West Bengal. The study reveals the significant impact of prerequisite subjects on the academic result of dependent subjects of students very clearly.

A thesis report submitted to the School of Computer Science and Engineering, Nanyang Technological University, Singapore, in partial fulfilment of the requirements for the degree of Doctor of Philosophy.

This Research Full Paper presents our experience in analyzing and selecting block-based programming environments to support the teaching of algorithms for the students starting the introductory courses of a Computer Science major. The teaching of algorithms and programming concepts to students of the first years of Computer Science and Engineering courses has been a major challenge because students often have difficulty understanding the logic and abstraction, leading to a high dropout rate. Some strategies have been conducted to further the mission of helping students understand better those basic concepts, but this topic still remains a major problem for students in the initial grades of those courses. In previous projects developed at our university, we have already proposed the use of learning objects and gamification, with very positive results. One of the questions that arise when we adopt new teaching approaches is to know how this new path will contribute to the student’s learning. In this project, we conducted a study on eight block-based programming environments and sought to identify which aspects of those environments comply with the Computer Science reference curriculum. Our work was based on the joint task force on Computing Curricula conducted by the ACM and IEEE Computer Society CS2013 curriculum guidelines for undergraduate programs in Computer Science. We studied the virtual programming environments Alice, MIT App Inventor, Blockly Games, Code.org, Gameblox, Pencil Code, Microsoft MakeCode and Scratch. Then, we crossed the characteristics of each, identified the positive and negative points of each teaching environment in relation to the topics established by the guidelines. We have classified the main characteristics of those programming environments, establishing criteria such as: prior programming knowledge requirements; ease of interaction with users; programming language code; availability of documentation for learning; programming practices addressed by the environment; and ease of learning programming. We believe that this work can contribute to the selection process of a suitable programming environment to be adopted in an introductory course of computer programming.

Mathematical subjects studied in the Faculty of Computer Science and Engineering at Burgas Free University are focused on acquiring fundamental knowledge and developing essential skills required for future engineers. This paper looks into changing the process of assessment of students’ achievements in mathematics from closed-book exams to diversification of tasks and expected outcomes. Three aspects of assessing the mathematical knowledge in engineering programs are considered: the importance of identifying the entry level, blended learning and creating students’ portfolios with MatLab. The experience of the authors in using the tools of blended learning and the use of a software environment are presented. Some emerging problems in the educational process that need to be faced are outlined.

This talk is intended to motivate diverse students in their study of computer science and engineering. Prof. Jimenez discusses the path he took to become a computer science professor. He describes his efforts promoting women and under-represented minorities in computer science and engineering. He ends with some advice to diverse students.

A powerful new idea in the computational representation of structures is that of the digital twin. The concept of the digital twin emerged and developed over the last decade, and has been identified by many industries as a highly desired technology. The current situation is that individual companies often have their own definitions of a digital twin, and no clear consensus has emerged. In particular, there is no current mathematical formulation of a digital twin. A companion paper to the current one will attempt to present the essential components of the desired formulation. One of those components is identified as a rigorous representation theory of models; most importantly, governing how they are verified and validated, and how validation information can be transferred between models. Unlike its companion, which does not attempt detailed specification of any twin components, this paper will attempt to outline a rigorous representation theory of models, based on the introduction of two new concepts: mirrors and virtualizations. The paper is not intended as a passive wish list; it is intended as a rallying call. The new theory will require the active participation of researchers across a number of domains including: pure and applied mathematics, physics, computer science, and engineering. The paper outlines the main objects of the theory and gives examples of the sort of theorems and hypotheses that might be proved in the new framework.