More than 500 healthy, quick, easy, and delicious recipes with limited sodium, sugar, and fat—perfect for busy families! What’s for dinner? With The Super Big Book of Easy, Delicious, and Healthy Recipes the Whole Family Will Love, the answer to that eternal question has never been easier. In this comprehensive cookbook, you’ll find more than 500 recipes that are quick, easy, healthy and, most importantly, delicious. Each recipe limits sodium, sugar, and fat without sacrificing any flavor, so you can feel good about feeding your family meals they’ll love. Find detailed nutritional statistics along with each recipe, as well as plenty of wholesome meals with minimal prep work, including recipes for slow cookers, casseroles, and one-pot meals that are perfect for your busy schedule. The best part? All meals included are ready in 30 minutes or less! From quick and satisfying breakfasts to fast, flavorful dinners to savory snacks, with The Super Big Book of Easy, Delicious, and Healthy Recipes the Whole Family Will Love, it’s easy to keep your family happy, as well as healthy.

The three-volume set LNCS 5101-5103 constitutes the refereed proceedings of the 8th International Conference on Computational Science, ICCS 2008, held in Krakow, Poland in June 2008. The 167 revised papers of the main conference track presented together with the abstracts of 7 keynote talks and the 100 revised papers from 14 workshops were carefully reviewed and selected for inclusion in the three volumes. The main conference track was divided into approximately 20 parallel sessions addressing topics such as e-science applications and systems, scheduling and load balancing, software services and tools, new hardware and its applications, computer networks, simulation of complex systems, image processing and visualization, optimization techniques, numerical linear algebra, and numerical algorithms. The second volume contains workshop papers related to various computational research areas, e.g.: computer graphics and geometric modeling, simulation of multiphysics multiscale systems, computational chemistry and its applications, computational finance and business intelligence, physical, biological and social networks, geocomputation, and teaching computational science. The third volume is mostly related to computer science topics such as bioinformatics' challenges to computer science, tools for program development and analysis in computational science, software engineering for large-scale computing, collaborative and cooperative environments, applications of workflows in computational science, as well as intelligent agents and evolvable systems.

Low-Cost Airline Carriers in Emerging Countries traces the development of low-cost carriers (LCCs) in Asia, Latin America, the Middle East and Africa, examining airlines that have become significant players in their home markets but little known at a global scale. The book maps the geography of the LCC phenomenon, explaining the starkly varying success of budget airlines, and assessing their current social, economic and environmental impacts. The book concludes with insights into the future potential of the LCC phenomenon along with its global ramifications. Beginning with Southwest Airlines in the 1970s, low-cost carriers (LCCs) have democratized air travel around the world, fostering huge increases in airline traffic and transforming the airline industry. At the same time however, the ascent of these budget airlines has exacerbated aviation-related problems such as aircraft noise, airport congestion, greenhouse gas emissions and more. LCCs have been extensively studied in the US and Europe but not in emerging regions of the globe. Yet the impact of such airlines is greatest in low- and middle-income economies where only a small fraction of the population has ever flown, and where competition from alternative modes (road, rail) is weak. - Examines the evolution of low cost carriers around the world, how established airlines react to their entry and the wide-ranging societal implications for individual countries and the world - Places emerging countries' LCCs into a global context, comparing them to their US and European counterparts - Offers original quantitative analysis of LCC networks at several spatial scales (global, regional, national, airport vs. airport) using global schedule data from OAG - Includes professionally produced maps of representative airlines networks

The last few years have witnessed fast development on dictionary learning approaches for a set of visual computing tasks, largely due to their utilization in developing new techniques based on sparse representation. Compared with conventional techniques employing manually defined dictionaries, such as Fourier Transform and Wavelet Transform, dictionary learning aims at obtaining a dictionary adaptively from the data so as to support optimal sparse representation of the data. In contrast to conventional clustering algorithms like K-means, where a data point is associated with only one cluster center, in a dictionary-based representation, a data point can be associated with a small set of dictionary atoms. Thus, dictionary learning provides a more flexible representation of data and may have the potential to capture more relevant features from the original feature space of the data. One of the early algorithms for dictionary learning is K-SVD. In recent years, many variations/extensions of K-SVD and other new algorithms have been proposed, with some aiming at adding discriminative capability to the dictionary, and some attempting to model the relationship of multiple dictionaries. One prominent application of dictionary learning is in the general field of visual computing, where long-standing challenges have seen promising new solutions based on sparse representation with learned dictionaries. With a timely review of recent advances of dictionary learning in visual computing, covering the most recent literature with an emphasis on papers after 2008, this book provides a systematic presentation of the general methodologies, specific algorithms, and examples of applications for those who wish to have a quick start on this subject.

The two-volume set LNAI 10191 and 10192 constitutes the refereed proceedings of the 9th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2017, held in Kanazawa, Japan, in April 2017. The total of 152 full papers accepted for publication in these proceedings was carefully reviewed and selected from 420 submissions. They were organized in topical sections named: Knowledge Engineering and Semantic Web; Social Networks and Recommender Systems; Text Processing and Information Retrieval; Intelligent Database Systems; Intelligent Information Systems; Decision Support and Control Systems; Machine Learning and Data Mining; Computer Vision Techniques; Advanced Data Mining Techniques and Applications; Intelligent and Context Systems; Multiple Model Approach to Machine Learning; Applications of Data Science; Artificial Intelligence Applications for E-services; Automated Reasoning and Proving Techniques with Applications in Intelligent Systems; Collective Intelligence for Service Innovation, Technology Opportunity, E-Learning and Fuzzy Intelligent Systems; Intelligent Computer Vision Systems and Applications; Intelligent Data Analysis, Applications and Technologies for Internet of Things; Intelligent Algorithms and Brain Functions; Intelligent Systems and Algorithms in Information Sciences; IT in Biomedicine; Intelligent Technologies in the Smart Cities in the 21st Century; Analysis of Image, Video and Motion Data in Life Sciences; Modern Applications of Machine Learning for Actionable Knowledge Extraction; Mathematics of Decision Sciences and Information Science; Scalable Data Analysis in Bioinformatics and Biomedical Informatics; and Technological Perspective of Agile Transformation in IT organizations.

The assembly of this study started in 2013 during the preparation of the foundation of the Flexible Electrical Networks (FEN) Research Campus, an institution supported by the German Federal Ministry of Education and Science, concentrating on DC technology in power grids as an enabler for the energy transition. It reflects the state-of-the-art and research needs of DC technology against the background of application in public grids up until the year 2015. Topics as components, control, management and automation, high-, medium, and low-voltage grid concepts as well as social dimensions, economics, and impact on living beings are considered. After substantial editorial effort, its first public edition has become ready now. The aim of FEN is to investigate and to develop flexible power grids. Such grid will safeguard the future energy supply with a high share of fluctuating and decentralized renewable energy sources. At the same time, these grids will enable a reliable and affordable energy supply in the future. The objective is to provide new technologies and concepts for the security and quality of the energy supply in the transmission and distribution grids. To pursue this goal, the use of direct-current (DC) technology, based on power electronics, automation and communication technologies, plays an important role. Although DC technology is not yet established as a standard technology in the public electrical power supply system, its high potential has been widely recognized. The use of DC is an enabler to make the future energy supply system more economical than a system based on alternating-current (AC), because of its superior properties in handling distributed and fluctuation power generation. Indeed, DC connections are already the most cost-efficient solution in cases of very high-power long-distance point-to-point transmission of electricity or via submarine cables. The objective of the FEN Research Campus is now to achieve and demonstrate feasibility of DC as a standard solution for future electrical grids, as described in this study.