Programazioaren oinarriak: C-ko eta Java-ko praktikak

Helburuak: Ikasmaterial honen helburu nagusia ikasleek C-ko eta Java-ko klase teorikoetan lantzen dituzten ezagutzak sendotzea da. Norentzat: Programazioari buruzko lehen ezagutzak sendotu nahi dituen edozein ikasleei zuzenduta, baina bereziki telekomunikazio ikasketak egiten ari diren ikasleei.Liburu hau atal nagusi bitaz osatuta dago: C programazio lengoaiari zuzendurik dago lehen atala, teoriako oinarrizko kontzeptuak erabiliz programa erraz eta labur batetik abiaturik, kode zailago bateraino iristeko aukera emango duten praktikez osaturik dago. Bigarrena, Java programazio lengoaiari zuzenduta dago, lehen atalaren egitura bardina jarraituaz

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Millimetre wave communications in 5G networks under latency constraints: machine intelligence, application scenarios and perspectives.

222 p.Nowadays there is little doubt that wireless communications have been a pivotal player in the irruption and maturity of digital technologies in almost all sectors of activity. Over the years, the society has witnessed how wireless networking has become an essential element of its evolution and prosperity. However, the ever-growing requirements of applications and services in terms of rate, reliability and latency have steered the interest of regulatory bodies towards emergent radio access interfaces capable of efficiently coping with such requisites. In this context, millimeter-wave (mmWave) communications have been widely acknowledged as a technology enabler for ultra-reliable, low-latency applications in forthcoming standards, such as 5G. Unfortunately, the unprecedented data rates delivered by mmWave communications come along with new paradigms in regards to radio resource allocation, user scheduling, and other issues all across the protocol stack, mainly due to the directivity of antennas andsensitiveness to blockage of communications held in this spectrum band. Consequently, the provision of machine intelligence to systems and processes relying on mmWave radio interfaces is a must for efficiently handling the aforementioned challenges.This Thesis contributes to the above research niche by exploring the use of elements and tools from Computational Intelligence, Matching Theory and Stochastic Optimization for the management of radio and network resources in mmWave communications. To this end, two different application scenarios are targeted: 1) Vehicular communications, where the high degree of mobility and the recurrent inter-vehicular blockage give rise to complex channel conditions for channel allocation and beam alignment; and 2) mobile virtual reality (VR), where the motion-to-photon latency limit raises the hurdle for scheduling the delivery of multimedia content over mmWave. A diversity of intelligent methods for clustering, predictive modeling, matching and optimization for dynamical systems are studied, adapted and applied to the aforementioned scenarios, giving evidences of the profitable advantages and performance gains yielded by these methods. The Thesis complements its technical contribution with a thorough overview of the recent literature of mmWave communications, leading to the main conclusion stemming from the findings of the Thesis: machine intelligence, provided by any technological means, is a driver to realize the enormous potential of mmWave for applications with unprecedented latency constraints