Compactness in Spaces of Inner Regular Measures and a General Portmanteau Lemma

This paper may be understood as a continuation of Topsøe’s seminal paper ([16]) to characterize, within an abstract setting, compact subsets of finite inner regular measures w.r.t. the weak topology. The new aspect is that neither assumptions on compactness of the inner approximating lattices nor nonsequential continuity properties for the measures will be imposed. As a providing step also a generalization of the classical Portmanteau lemma will be established. The obtained characterizations of compact subsets w.r.t. the weak topology encompass several known ones from literature. The investigations rely basically on the inner extension theory for measures which has been systemized recently by König ([8], [10],[12]).Inner Premeasures, Weak Topology, Generalized Portmanteau Lemma.

Image processing as state reconstruction in optics

The image reconstruction of partially coherent light is interpreted as the quantum state reconstruction. The efficient method based on maximum-likelihood estimation is proposed to acquire information from registered intensity measurements affected by noise. The connection with totally incoherent image restoration is pointed out. The feasibility of the method is demonstrated numerically. Spatial and correlation details significantly smaller than the diffraction limit are revealed in the reconstructed pattern.Comment: 10 pages, 5 figure

Applications of fuzzy set theory and near vector spaces to functional analysis

We prove an original version of the Hahn-Banach theorem in the fuzzy setting. Convex compact sets occur naturally in set-valued analysis. A question that has not been satisfactorily dealt with in the literature is: What is the relationship between collections of such sets and vector spaces? We thoroughly clarify this situation by making use of R°adstr ¨om’s embedding theorem, leading up to the definition of a near vector space. We then go on to successfully apply these results to provide an original method of proof of Doob’s decomposition of submartingales

Characterizing joint distributions of random sets with an application to set-valued stochastic processes

Abstract By the Choquet theorem, distributions of random closed sets can be characterized by a certain class of set functions called capacity functionals. In this paper a generalization to the multivariate case is presented, that is, it is proved that the joint distribution of finitely many random sets can be characterized by a set function fulfilling certain properties. Furthermore, we use this result to formulate an existence theorem for set-valued stochastic processes

Fast Charging Technique For Lithium-Ion Cell

Climate change is a big concern among the people. Day by day people are trying to increase the use of the sustainable energy in every sector of their life. Like other sectors, transportation sector manufacturers are beginning to shifting from fossil fuels based models to electric models. Manufacturers are trying to introduce electrified models from bicycles to cars. For energy storage, these electrified models are highly dependent on the battery. Lithium-ion cells have a high energy density, no memory effect, long cycle life and low self discharge quality, and are therefor highly used from portable electronics to electric vehicles everywhere. A main concern with a rechargeable battery is that it needs to recharge in regular intervals. This charging procedure is time consuming and can have a great impact on the total capacity of the battery, cycle life, and charging efficiency (or energy efficiency). A gasoline-base vehicle takes 3-5 minutes to fill the gas tank, but, an electric vehicle may need up to 10-12 hours (depend on the battery pack capacity) to be fully charged. For that, electric vehicles can become unreliable under emergency conditions and a deterent to regular users. As a result, charging technology has become a major concern among the manufacturers of electric vehicles. Using fast charging techniques can create unwanted side effects, like, thermal runaway, capacity fade, lithium platting and other electrochemical changes. In this thesis we developed an optimal fast charging technique for lithium-ion cells, which will be able to charge the cell faster compared with present industrial charging methods and maintain the long cycle life without significant decay of the capcity. We used 18650 lithium-ion cells for testing. During testing continuous cycling test was stopped when the capacity degraded by 20% of it’s original capacity. We compared our proposed fast charging technique with an available industrial charging technique. Due to differences in the charging times, when our proposed fast charging technique goes through more than 1600 cycles, the industrial charging technique had completed only 660 cycles. For comparision purposes, we chose 600 cycles as the common comparision point. We had found that our proposed technique took an average 63.7 minutes to charge 100% of the cell after 600th cycle. At the same time, the industrial charging technique took an average of 150 minutes to charge 100% of the cell. From this comparision it was clear the our proposed method is 135% faster than the available industrial charging technique. Capacity degradation was 10.5% for the fast charging technique and 6.6% for the industrial charging. As a result, we can say our proposed fast charging technique is faster and capabale of maintaining the capacity degradation rate within reasonable limits

Identification of urban sectors prone to solid waste accumulation: A machine learning approach based on social indicators

In the last decades, the accumulation of municipal solid waste in urban areas has become a latent concern in our society due to its implications for the exposed population and the possible health and environmental issues it may cause. In this sense, this research study contributes to the timely identification of these sectors according to the anthropogenic characteristics of their residents as dictated by 10 social indicators (i.e., age, education, income, among others) sorted into three assessment categories (sociodemographic, sociocultural, and socioeconomic). Then, the data collected was processed and analyzed using two machine learning algorithms (random forest (RF) and logistic regression (LR)). The primary information that fed the machine learning model was collected through field visits and local/national reports. For this research, the Puente Piedra and Chaclacayo districts, both located in the province of Lima, Peru, were selected as case studies. Results suggest that the most relevant social indicators that help identifying these sectors are monthly income, consumption patterns, age, and household population density. The experiments showed that the RF algorithm has the best performance, since it efficiently identified 63% of the possible solid waste accumulation zones. In addition, both models were capable of determining different classes (AUC – RF = 0.65, AUC – LR = 0.71). Finally, the proposed approach is applicable and reproducible in different sectors of the national Peruvian territory.Campus Lima Centr

Weight analysis of influencing factors of dam break risk consequences

There are numerous influencing factors of the risk consequences of dam break. The scientific and reasonable index system and its weight distribution are some of the key elements for comprehensive evaluation of the dam break risk. Taking into consideration 20 factors, including hazards, exposure and vulnerability, the evaluation index system of the consequences of dam break risk is constructed. Using the Statistical Cloud Model (SCM) to improve the entropy method, we establish the weight calculation model of the influencing factors of dam break risk consequences. The results shows that the top five factors with the highest weight are risk population, flood intensity, alert time, risk understanding and distance from the dam. Compared to traditional algebraic weight calculation methods, the result is basically consistent with the algebraic weight distribution, and increases the range by 2.03 times, supporting a more scientific basis for recognizing and evaluating dam break risk consequences.</p

Proceedings of the ACEWATER2 Scientific Workshop Accra (Ghana) 31 Oct – 3 Nov 2016

The African Centers of Excellence on Water (ACEWATER2) project, in its second phase (2016/19), promoted by the African Ministers of Water and financed by DG DEVCO, aims at supporting the establishment of Human Capacity Development Programme of the AMCOW (African Ministers’ Council on Water) in the Water Sector, strengthens institutional networking and improving research support to policy making by scaling up the approach of the pilot phase (phase I). The main activities of the project consist in: • Strengthening of two existing NEPAD water Centers of Excellence networks in West and Southern Africa; • Expanding the NEPAD water Centres of Excellence network to Central and Eastern Africa; • Strengthening institutional networking and improving research support to policy making in the water sector; • Supporting the implementation of the African Water Ministers’ declaration urging AUC and NEPAD Centers of Excellence to develop a “Human Capacity Development Programme for junior professional and technician level capacity challenges in the water sector”; • Developing an Atlas on Regional Water Cooperation. The project geographical scope covers three major regions: Southern Africa (7 countries), Western Africa (4 countries) and Eastern/Central Africa. The project is implemented by DG JRC (overall project management and scientific cluster) with UNESCO (human capacity development cluster). Within this project, a Workshop has been organized in Accra (Ghana) from October 31st to November 3rd, specifically devoted to the sharing among CoEs of scientific interests, competences and methods towards the effective planning of (scientific) activities, achievement and delivery of scientific tools and products to support (science-based) decision making processes. By means of scientific as well as technical presentations, round tables and participative sessions, the participants (35 people representing more than 30 Institutions among Universities, Research Centres, River Basin Authorities, Regional Economic Communities and key stakeholders on water issues, further to European research Institutions as CIRAD and CREAF) shared valuable experiences and competences, including case studies, around key thematic pillars, such as: Climate Issues (Session 1), African Water-Energy-Food nexus (Session 2), Groundwater (Session 3) and Water Governance&Diplomacy (Session 4). Workshop Proceedings gather all relevant contributions in the form of (extended) abstracts and short papers, providing a general overview of key relevant issues and partners scientific interests, turning to be a valuable resource for effective planning of next project steps.JRC.D.2-Water and Marine Resource