Baseline Evaluation of Potential to Use Solar Radiation in Air Conditioning Applications

AbstractThe study presents a global evaluation of the potential to use solar radiation in the air conditioning with application to an office building located in Cluj-Napoca, Romania. The study was realized for a one year period, based on multiannual average values for solar radiation and ambient temperature. It were compared the performances of two types of solar cooling systems, one based on absorption chiller and one of photovoltaic type. It is presented the methodology for calculation of the efficiency of the solar thermal field and of the equivalent photovoltaic field, placed on the terrace roof of the building, considered completely filled with evacuated tubes solar collectors tilted at 45° and facing south was taken into account or with photovoltaic field of collectors oriented in the same position. The solar collectors were arranged to completely avoid each other shading, for any solar altitude angles higher than 30°. The one year variation of several calculated parameters is presented together with the corresponding variation in the period of (10-20) June. The one year thermal solar cooling fraction was found to be of 24.5% and the one year photovoltaic cooling fraction was found to be of 36.6%

Precision medicine and artificial intelligence : a pilot study on deep learning for hypoglycemic events detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal

Precision medicine and artificial intelligence : a pilot study on deep learning for hypoglycemic events detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal

VIEWS ON THE OFFENCE OF HUMAN TRAFFICKING

In the international background of the current period, Romania is included in the "Balkan Route" of illegal migration, which influences all the main areas of society, including the security of the state and that of its citizens.One of the main issues in the last decade, at national and international level, is the human trafficking, linked to the illegal migration, which is constantly increasing.Human trafficking is an offense which affects human rights, with profound economic and social interference, due to the mobility and perceivable advantages of the phenomenon.Until 2014, human trafficking was provided for by law 678/2001 regarding the prevention and control of human trafficking, but with the entry into force of the New Criminal Code this offense was covered by the same code, provided by art. 210.

A Multi-Attribute Sales Comparison Method for Real Estate Valuation

The theory and practice of real-estate valuation has attracted immense interest over the past decades. This paper is concerned with the sales comparison approach. First, a brief survey of some procedures used worldwide, the sales comparison by adjustments, the hedonic regression and the hedonic price index method, is presented. To improve the versatility of property appraisals a new valuation method, as a combination of multi-objective optimization (MOO) and multi-criteria decision analysis (MCDA) is developed. A unique feature of this model is that it enables the appraiser to evaluate the characteristics of a property on those scales of measurement to which they belong de facto. To comply with this objective, distinct metric distance functions on each scale of measurement, including the two qualitative scales (nominal and ordinal), are employed. After that, the physical worth of a property is derived as a weighted sum of the composite scores. This can be measured on an interval scale. To predict the monetary worth of a property, a simple linear regression model is developed. The benefits of the use of this multi-attribute valuation method is also discussed. A comprehensive real-world study showing the application of the procedure is included

Integration of Advanced Technologies for Efficient Operation of Smart Grids

The current transition of electrical power systems toward smart grids is encompassing a fundamental change in their structure, as well as operation. This is setting the path to be followed by the hardware and software embedded in electrical power systems, as well as technology adaptation to the “open-source” customers’ needs and consumption patterns. This chapter is following the evolution of energy sector, accompanied by constant improvements of technology, which is providing increasingly complex hardware, which embeds power quality improvement devices, for an efficient operation of electrical power assets. This chapter presents a comprehensive survey of continuous advances of renewable energy sources and storage technology which have started the transformation of end users into energy-efficient and clean prosumers, underlining the subsequent energy markets support of peer-to-peer energy trading through novel technologies as blockchain

Study of the Behavior of Some Spring Barley Lines with Two Rows Created at A.R.D.S Turda Regarding Production Capacity and Quality

The spring barley is a variety of a superior quality for brewing compared with the feed barley due to several reasons. Research was conducted in the field of breeding of spring barley with two rows, within ARDS Turda, during 2013-2015. The trials were comparatively developed, and included 25 variants. The biological material was represented by four  autochthonous genotypes: Turdeana, Daciana Romaniţa (A.R.D.S. Turda), and Adina (A.R.D.S. Suceava). The spring barley lines created by the S.C.D.A. Turda, meet the requirements of the beer industry in terms of protein content, starch, M.M.B. and germination energy

Drug Use - Attitudinal Dimensions within the Student Population

AbstractDrug use has become a serious social problem that crosses continents and most countries. Surprisingly, studies on the prevalence and genesis of drug use in the academic environment are extremely rare.The study in question represents a sequence within a broader research devoted to drug use and analysis of predictive factors of consumer behavior in the student environment. Are identified four categories of predictive factors in the ensemble which attitudes occupy a distinct position. The results highlight the importance of attitudes for understanding motivation for drug use and for the construction of prevention programs

Blended Learning Concept and its Applications to Engineering Education

Abstract. The technical educational act means theory and practice, individual study, group-based projects or experimental work that involves equipment, simulation/emulation software packages and laboratory applications. In order to develop advanced e-learning tools and integrate them within online platforms for higher and postgraduate engineering education, new methodologies should be taken into consideration: project-and problem based learning, virtual laboratory (remote access to laboratory infrastructure and task evaluation) or remote assistance for diploma projects and mobility grants. This paper presents new blended learning concepts and approaches and the manner they can be adopted in engineering education, by using the symbiotic computing paradigms adapted to blended learning, especially blended learning gap and blended learning bridge