Sensor Search Techniques for Sensing as a Service Architecture for The Internet of Things

The Internet of Things (IoT) is part of the Internet of the future and will comprise billions of intelligent communicating "things" or Internet Connected Objects (ICO) which will have sensing, actuating, and data processing capabilities. Each ICO will have one or more embedded sensors that will capture potentially enormous amounts of data. The sensors and related data streams can be clustered physically or virtually, which raises the challenge of searching and selecting the right sensors for a query in an efficient and effective way. This paper proposes a context-aware sensor search, selection and ranking model, called CASSARAM, to address the challenge of efficiently selecting a subset of relevant sensors out of a large set of sensors with similar functionality and capabilities. CASSARAM takes into account user preferences and considers a broad range of sensor characteristics, such as reliability, accuracy, location, battery life, and many more. The paper highlights the importance of sensor search, selection and ranking for the IoT, identifies important characteristics of both sensors and data capture processes, and discusses how semantic and quantitative reasoning can be combined together. This work also addresses challenges such as efficient distributed sensor search and relational-expression based filtering. CASSARAM testing and performance evaluation results are presented and discussed.Comment: IEEE sensors Journal, 2013. arXiv admin note: text overlap with arXiv:1303.244

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Microservices and Machine Learning Algorithms for Adaptive Green Buildings

In recent years, the use of services for Open Systems development has consolidated and strengthened. Advances in the Service Science and Engineering (SSE) community, promoted by the reinforcement of Web Services and Semantic Web technologies and the presence of new Cloud computing techniques, such as the proliferation of microservices solutions, have allowed software architects to experiment and develop new ways of building open and adaptable computer systems at runtime. Home automation, intelligent buildings, robotics, graphical user interfaces are some of the social atmosphere environments suitable in which to apply certain innovative trends. This paper presents a schema for the adaptation of Dynamic Computer Systems (DCS) using interdisciplinary techniques on model-driven engineering, service engineering and soft computing. The proposal manages an orchestrated microservices schema for adapting component-based software architectural systems at runtime. This schema has been developed as a three-layer adaptive transformation process that is supported on a rule-based decision-making service implemented by means of Machine Learning (ML) algorithms. The experimental development was implemented in the Solar Energy Research Center (CIESOL) applying the proposed microservices schema for adapting home architectural atmosphere systems on Green Buildings

Choice of Law: A Well-Watered Plateau

De flesta stora företag använder idag ett affärssystem, för att exempelvis integrera olikafunktioner i verksamheten och automatisera affärsprocesser, vilket har bidragit till attmånga leverantörer har ökat försäljningsfokus mot mindre företag. Små företag inserockså behovet av affärssystem (Iskanius et al., 2009) och statistik visar även attanvändandet ökar i mindre företag (SCB, 2013). Små företag kan inte ses som mindreversioner av stora företag (Malhotra och Temponi, 2010; Welsh och White, 1981), dådessa skiljer sig i exempelvis striktare resursbegränsningar, vilket innebär attaffärssystemsprojekt också skiljer sig från de i stora företag. Av denna anledning är detviktigt för leverantörer att förstå vad som påverkar små företag underinförskaffningsprocessen av ett affärssystem. Denna rapport syftar till att, för småsvenska företag, identifiera faktorer som är avgörande för valet att införskaffa ettaffärssystem och undersöka hur dessa påverkar viktiga faktorer senare i processen.Utifrån en litteraturstudie och en inledande empirisk datainsamling ställdes en teori uppi form av hypoteser om hur avgörande faktorer i införskaffandeprocessens initieringsfaspåverkar viktiga faktorer under anskaffnings- och implementeringsfasen. Genom enfallstudiemetod, där sex företag som införskaffat ett affärssystem under de senaste årenundersöktes, analyserades och testades den framtagna teorin.Studiens resultat belyser vikten av inblandade personers befintliga kunskap, en faktorsom påverkar bland annat möjligheten att ta fram en genomtänkt kravspecifikation ochprojektets struktur. Vidare identifierades stora skillnader i inställningen till att förändraoch effektivisera verksamheten och en syn på resursbegränsningar som leder till attexempelvis otillräcklig tid avvaras för projektet. Trots att affärssystem i små företag oftaanvänds endast för ekonomi och ibland även logistik tyder undersökningen också på attinförskaffandet kan medföra ett stort värde genom ett effektivare arbetssätt.Most large companies today use an ERP system, for example to integrate differentfunctional areas of the organization and automate business processes. This has mademany suppliers increase their sales focus on smaller companies. These companiesrealize the need for ERP systems (Iskanius et al., 2009) and statistics also show that theusage is increasing in smaller companies (SCB, 2013). However, small enterprisescannot be seen as smaller versions of large companies (Malhotra and Temponi, 2010;Welsh and White, 1981) as these differ, for example in more stringent resourceconstraints, which means that ERP projects also differ from those of large companies.For this reason, it is important for suppliers and consultants to understand what affectssmall companies during the process of acquiring an ERP system. This report aims to, insmall Swedish companies, identify factors that affect the decision to acquire an ERPsystem and examine how these affect important factors later in the process.Based on a literature review and an initial empirical data collection, a theory wascreated in the form of hypotheses about how the determinants of the aquiring processinitialization phase affects important factors during the acquisition and implementationphases. Through a case study method, in which six companies that has acquired an ERPsystem in recent years were studied, the developed theory was analyzed and tested.Our results highlight the importance of the existing knowledge of involved persons, afactor that influences, for example, the ability to develop a good requirementsspecification and the project structure. Furthermore, we identified significantdifferences in the openness to changing and improving the work flow of the companyand a view of resource constraints that often leads to insufficient time being spared forthe project. Although ERP system in small enterprises often are used only for financialmanagement and sometimes logistics the study shows that the acquisition can add largevalue to the organization through more efficient work processes

Citizen science as a new tool in dog cognition research

The work of Á.M. was supported by the Hungarian Academy of Sciences (MTA 01 031).Family dogs and dog owners offer a potentially powerful way to conduct citizen science to answer questions about animal behavior that are difficult to answer with more conventional approaches. Here we evaluate the quality of the first data on dog cognition collected by citizen scientists using the Dognition. com website. We conducted analyses to understand if data generated by over 500 citizen scientists replicates internally and in comparison to previously published findings. Half of participants participated for free while the other half paid for access. The website provided each participant a temperament questionnaire and instructions on how to conduct a series of ten cognitive tests. Participation required internet access, a dog and some common household items. Participants could record their responses on any PC, tablet or smartphone from anywhere in the world and data were retained on servers. Results from citizen scientists and their dogs replicated a number of previously described phenomena from conventional lab-based research. There was little evidence that citizen scientists manipulated their results. To illustrate the potential uses of relatively large samples of citizen science data, we then used factor analysis to examine individual differences across the cognitive tasks. The data were best explained by multiple factors in support of the hypothesis that nonhumans, including dogs, can evolve multiple cognitive domains that vary independently. This analysis suggests that in the future, citizen scientists will generate useful datasets that test hypotheses and answer questions as a complement to conventional laboratory techniques used to study dog psychology.Publisher PDFPeer reviewe

Book Review: Teaching Interreligious Encounters

Book review of Teaching Interreligious Encounters. Edited by Marc A. Pugliese and Alexander Y. Hwang. Oxford: Oxford University Press, 2017, 368 pages

Determining the essential characetristics of Six Sigma Black Belts

A Six Sigma Black Belt (SSBB) plays the role of a full-time team leader responsible for implementing process improvement projects using the Six Sigma methodology (Define-Measure-Analyse-Improve-Control) within the business to drive up customer satisfaction levels and business productivity. Black Belt projects are typically defined so that they can be completed in less than 6 months, and are generally focused on high-priority business issues and are targeted to add $175,000 to$250,000 to the bottom-line of organisations (Snee, 2004). A fully trained BB will be expected to deliver a minimum of $500,000 to well over$1,000,000 in direct cost savings to the bottom-line of an organisation per year (Harry and Schroeder, 2000). Moreover, a BB is expected to complete between 4 to 6 projects per annum depending on the scope of the project, complexity of the project and availability of data. The BB program of study focuses on an understanding of the Six Sigma philosophy, key principles and concepts, tactics, application of tools and techniques, project management skills, etc. So,why the martial arts terminology? The sole function of a BB is to focus on disciplined problem solving using the DMAIC (Define-Measure-Analyse-Improve-Control) methodology and a specific set of tools and techniques with speed (i.e. project completion in a short period of time). The purpose here is to defeat the enemy – variation in processes which lead to customer dissatisfaction (Brue and Howes, 2006)