IEEE STUDENT BRANCH: CONSTITUTION

The purpose of this seminar is to present the characteristics of the student branch of IEEE. The student branch is a student group belonging to an university but has constant contact with the largest community of engineers in the world. The purpose of this seminar is to show the benefits of membership in this prestigious community of engineers and has the aims to show benefits for students in terms of, knowledge, opportunities and careers. IEEE world wide is divided into regions and Italy belongs to the region 8. Within the region there are the sections, one for each nation. The Italian section is very vital, in fact it has 33 technical chapter, 3 affinity groups and 22 student branch (then 22 universities have their student Branch). The goal therefore is to form the student branch of Federico II

Implications of learning environments on the Information Systems of educational institutions

Since the early years where they started to enter the market, Learning Management Systems (LMS) have reached a very high level of maturity, providing professional solutions to mostly any educational need referring to distance learning. In this paper, an analysis of how LMSs should evolve in the future is presented, according to authors’ experience, in terms of functionalities and services provided to users. Behind these new functionalities and services, we foresee research fields that could provide interesting and fruitful stimulus to the market and to these platforms. The foreseen direction is the one that goes towards an expansion of the collaboration services, where virtual learning environments should be mixed with typical Computer Supported Collaborative Work (CSCW) tools and approaches that put collaboration at the heart of the system. Nevertheless, also traditional e-learning services should be improved with additions coming exactly from this integration with cooperative / collaborative services. The reference point is a virtual community platform created and developed along the years, used in the authors’ institutions and in several public and private organizations. The platform is oriented towards the support of collaborative processes, where of course e-learning is one of the most important, but not the only one, and where new services supporting collaboration in different ways are constantly added

ADOPTING COGNITIVE COMPUTING SOLUTIONS IN HEALTHCARE

This paper discusses possible motivations to adopt cognitive computing- based solutions in the field of healthcare and surveys some recent experiences. From a very practical point of view, the use of cognitive computing techniques can provide machines with human-like reasoning capabilities, thus allowing them to face heavy uncertainties and to cope with problems whose solution may require computing intensive tasks. Moreover, empowered by reliable networking infrastructures and cloud environments, cognitive computing enables effective machine-learning techniques, resulting in the ability to find solutions on the basis of past experience, taking advantage from both errors and successful ndings. Owing to these special features, it is perceptible that healthcare can greatly bene t from such a powerful technology. In fact, clinical diagnoses are frequently based on statistics and signi cant research advancements were accomplished through the recursive analysis of huge quantity of unstructured data such as in the case of X-ray images or computerized axial tomography scans. As another example, let us consider the problem of DNA sequence classi cation with the uncountable combinations that derive from such a complex structure

COGNITIVE COMPUTING & HEALTHCARE

The training for the acquisition of manual skills and expertise of da Vinci is complex. It is believed that Watson may be useful as tutoring to the formation of these abilities and skills, mainly because the robot versions change very frequently and surgical specialties increase with continuity (urology, cardiology, neonatology, neuro surgery, etc). Watson will be a useful training ground for engineers and doctors and an experience in the field of cognitive computing applied to customized training

IBM Faculty Award to Enforcing Team Cooperation (ETC) using Rational Software Tools: consegna del riconoscimentoal prof. Paolo Maresca

La disponibilità di architetture mutuate dall’esperienza Internet per il mondo dello sviluppo software, veicolate in particolare dall’architettura Jazz, ha fatto nascere l’idea di un progetto sperimentale di utilizzo delle discipline dell’ingegneria del software e della conduzione di laboratorio di sviluppo software in un ambito collaborativo universitario che consenta agli studenti e ai docenti la migliore fruizione delle modalità di insegnamento nelle università, coniugata alle nuove possibilità di collaborazione e condivisione intrauniversitaria. Il seminario, cogliendo l’occasione del conferimento del prestigioso IBM Faculty Award al prof. Paolo Maresca discute le idee, la vision i risultati ottenuti e gli sviluppi futuri del progetto denominato Enforcing Team Cooperation using Rational software tools (ETC) e descrive la collaborazione tra il mondo universitario italiano e IBM, nell’ambito delle attività dell’ Academic Initiative.. Nella prima relazione la dr.ssa Milani di IBM illustrerà l’academic initiative di IBM e i rapporti con le università, nella seconda relazione il prof. Paolo Maresca discuterà lo stato del progetto ETC, i risultati raggiunti e gli sviluppi futuri, nella terza relazione il dr. Ferdinando Gorga di IBM illustrerà il trend dell’ingegneria del software. La quarta sarà dedicata alla esperienza degli studenti. L’evento si concluderà con il saluto del direttore del DIS prof. Antonino Mazzeo. Il progetto è supportato da IBM Academic Initiative, IBM Rational ed è in cooperazione con la comunità Eclipse Italiana

Increasing Consonance and Resonance in Agile Teaching Methodologies

In a cooperative environment technicalexcellence and high quality students’ artifacts is whatteachers strive to achieve while educating computerscience students and facing the challenges of this newcentury. When agile techniques and accelerators andinjected in the process in a cooperative environment theconsonance and resonance in groups increases. Thisspeeds up the learning process and the quality of thematerial produced by the students improves. Twoobservational studies at Kent State University at Starkand Ohio University are described in this paper. Thestudies observe the usefulness of using agile teachingtechniques and analyze the quality of deliverablesproduced. A post questionnaire gathered students’feedback. The observation shows that cooperativelearning produces better results than individuallearning however consonance and resonance must bereached before the speed is achieved

Adopting cognitive computing solutions in healthcare

This paper discusses possible motivations to adopt cognitive computing-based solutions in the field of healthcare and surveys some recent experiences. From a very practical point of view, the use of cognitive computing techniques can provide machines with human-like reasoning capabilities, thus allowing them to face heavy uncertainties and to cope with problems whose solution may require computing intensive tasks. Moreover, empowered by reliable networking infrastructures and cloud environments, cognitive computing enables effective machine-learning techniques, resulting in the ability to find solutions on the basis of past experience, taking advantage from both errors and successful findings. Owing to these special features, it is perceptible that healthcare can greatly benefit from such a powerful technology. In fact, clinical diagnoses are frequently based on statistics and significant research advancements were accomplished through the recursive analysis of huge quantity of unstructured data such as in the case of X-ray images or computerized axial tomography scans. As another example, let us consider the problem of DNA sequence classification with the uncountable combinations that derive from such a complex structure

Focus on: New trends, challenges and perspectives on healthcare cognitive computing: from information extraction to healthcare analytics

The focus of this special issue is cognitive computing in healthcare, due to the ever-increasing interest it is gaining for both research purposes and clinical applications. Indeed, cognitive computing is a challenging technology in many fields of application (Banavar, 2016) such as, e.g., medicine, education or eco- nomics (Coccoli et al., 2016) especially for the management of huge quantities of information where cognitive computing techniques push applications based on the use of big data (Coccoli et al., 2017). An unprecedented amount of data is made available from a heterogeneous variety of sources and this is true also in the case of health data, which can be exploited in many ways by means of sophisticated cognitive computing solutions and related technologies, such as, e.g., information extraction, natural language processing, and analytics. Also, from the point of view of programming they set challenging issues (see, e.g., Coccoli et al., 2015). In fact, the amount of healthcare that is now available and, potentially useful to care teams, reached 150 Exabytes worldwide and about 80% of this huge volume of data is in an unstructured form, being thus somehow invisible to systems. Hence, it is clear that cognitive computing and data analytics are the two key factors we have for make use – at least partially – of such a big volume of data. This can lead to personalized health solutions and healthcare systems that are more reliable, effective and efficient also re- ducing their expenditures. Healthcare will have a big impact on industry and research. However, this field, which seems to be a new era for our society, requires many scientific endeavours. Just to name a few, you need to create a hybrid and secure cloud to guarantee the security and confidentiality of health data, especially when smartphones or similar devices are used with specific app (see, e.g., Mazurczyk & Caviglione, 2015). Beside the cloud, you also need to consider novel ar- chitectures and data platforms that shall be different from the existing ones,because 90% of health and biomedical data are images and also because 80% of health data in the world is not available on the Web. This special issue wants to review state-of-the-art of issues and solutions of cognitive computing, focusing also on the current challenges and perspecti- ves and includes a heterogeneous collection of papers covering the following topics: information extraction in healthcare applications, semantic analysis in medicine, data analytics in healthcare, machine learning and cognitive com- puting, data architecture for healthcare, data platform for healthcare, hybrid cloud for healthcare

Teaching Computer Programming Through Hands-on Labs on Cognitive Computing

In this work we report the experience of a long-lasting educational project that we have been carrying since a couple of years. In particular, we summarize the results achieved by students in the last year, when they were put to work on the collaborative development of small, yet full featured, software projects. At the same time, based on more recent findings, we seek to lay the foundations to build a pragmatic model to teach cognitive computing programming. The experience was carried on in a Programming course at the Universities of Naples “Federico II” and Genoa, in Italy, and fostered the use of a PaaS (Platform as a Service) environment for a cooperative learning activity, used to disseminate theoretical concepts acquired within the course, also by means of cognitive computing tools. The project, from its inception, has involved a relevant number of students. Initially, the experiment had to be concluded in one year but, instead, has continued evolving with new projects, as new tools and services were made available, carrying new opportunities. The evolution has led, in the most recent release, to using the IBM Bluemix platform with its wide range of components, including Watson. This work goes in the direction of developing the smart university model, by using innovative and intelligent services to help develop a new generation of applications, but also to promote and disseminate a new way for designing and building them