Artificial-Intelligence-Based Optimization of the Management of Snow Removal Assets and Resources Final Report, October 2002

Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent snow removal asset management system (SRAMS). The system has been evaluated through a case study examining snow removal from the roads in Black Hawk County, Iowa, for which the Iowa Department of Transportation (Iowa DOT) is responsible. The SRAMS is comprised of an expert system that contains the logical rules and expertise of the Iowa DOT’s snow removal experts in Black Hawk County, and a geographic information system to access and manage road data. The system is implemented on a mid-range PC by integrating MapObjects 2.1 (a GIS package), Visual Rule Studio 2.2 (an AI shell), and Visual Basic 6.0 (a programming tool). The system could efficiently be used to generate prioritized snowplowing routes in visual format, to optimize the allocation of assets for plowing, and to track materials (e.g., salt and sand). A test of the system reveals an improvement in snowplowing time by 1.9 percent for moderate snowfall and 9.7 percent for snowstorm conditions over the current manual system.

Multidimensional Adaptations for Open Learning Management Systems

Our work is focused on alleviating the workload for designers of adaptive courses on the complexity task of authoring adaptive learning designs adjusted to specific user characteristics and the user context. We propose an adaptation platform that consists in a set of intelligent agents where each agent carries out an independent adaptation task. The agents apply machine learning techniques to support the user modelling for the adaptation process

Development of LRFD Procedures for Bridge Pile Foundations in Iowa, Volume I: An Electronic Database for PIle LOad Tests (PILOT), TR-573, 2011

For well over 100 years, the Working Stress Design (WSD) approach has been the traditional basis for geotechnical design with regard to settlements or failure conditions. However, considerable effort has been put forth over the past couple of decades in relation to the adoption of the Load and Resistance Factor Design (LRFD) approach into geotechnical design. With the goal of producing engineered designs with consistent levels of reliability, the Federal Highway Administration (FHWA) issued a policy memorandum on June 28, 2000, requiring all new bridges initiated after October 1, 2007, to be designed according to the LRFD approach. Likewise, regionally calibrated LRFD resistance factors were permitted by the American Association of State Highway and Transportation Officials (AASHTO) to improve the economy of bridge foundation elements. Thus, projects TR-573, TR-583 and TR-584 were undertaken by a research team at Iowa State University’s Bridge Engineering Center with the goal of developing resistance factors for pile design using available pile static load test data. To accomplish this goal, the available data were first analyzed for reliability and then placed in a newly designed relational database management system termed PIle LOad Tests (PILOT), to which this first volume of the final report for project TR-573 is dedicated. PILOT is an amalgamated, electronic source of information consisting of both static and dynamic data for pile load tests conducted in the State of Iowa. The database, which includes historical data on pile load tests dating back to 1966, is intended for use in the establishment of LRFD resistance factors for design and construction control of driven pile foundations in Iowa. Although a considerable amount of geotechnical and pile load test data is available in literature as well as in various State Department of Transportation files, PILOT is one of the first regional databases to be exclusively used in the development of LRFD resistance factors for the design and construction control of driven pile foundations. Currently providing an electronically organized assimilation of geotechnical and pile load test data for 274 piles of various types (e.g., steel H-shaped, timber, pipe, Monotube, and concrete), PILOT (http://srg.cce.iastate.edu/lrfd/) is on par with such familiar national databases used in the calibration of LRFD resistance factors for pile foundations as the FHWA’s Deep Foundation Load Test Database. By narrowing geographical boundaries while maintaining a high number of pile load tests, PILOT exemplifies a model for effective regional LRFD calibration procedures.

Modeling and Simulation ofReal-Time System as a Tool to Improve Capacity Management - Case Fenix

Tämän tutkimustyön kohteena on TietoEnator Oy:n kehittämän Fenix-tietojärjestelmän kapasiteettitarpeen ennustaminen. Työn tavoitteena on tutustua Fenix-järjestelmän eri osa-alueisiin, löytää tapa eritellä ja mallintaa eri osa-alueiden vaikutus järjestelmän kuormitukseen ja selvittää alustavasti mitkä parametrit vaikuttavat kyseisten osa-alueiden luomaan kuormitukseen. Osa tätä työtä on tutkia eri vaihtoehtoja simuloinnille ja selvittää eri vaihtoehtojen soveltuvuus monimutkaisten järjestelmien mallintamiseen. Kerätyn tiedon pohjaltaluodaan järjestelmäntietovaraston kuormitusta kuvaava simulaatiomalli. Hyödyntämällä mallista saatua tietoa ja tuotantojärjestelmästä mitattua tietoa mallia kehitetään vastaamaan yhä lähemmin todellisen järjestelmän toimintaa. Mallista tarkastellaan esimerkiksi simuloitua järjestelmäkuormaa ja jonojen käyttäytymistä. Tuotantojärjestelmästä mitataan eri kuormalähteiden käytösmuutoksia esimerkiksi käyttäjämäärän ja kellonajan suhteessa. Tämän työn tulosten on tarkoitus toimia pohjana myöhemmin tehtävälle jatkotutkimukselle, jossa osa-alueiden parametrisointia tarkennetaan lisää, mallin kykyä kuvata todellista järjestelmää tehostetaanja mallin laajuutta kasvatetaan.

Analysis of vineyard differential management zones and relation to vine development, grape maturity and quality

The objective of research was to analyse the potential of Normalized Difference Vegetation Index (NDVI) maps from satellite images, yield maps and grapevine fertility and load variables to delineate zones with different wine grape properties for selective harvesting. Two vineyard blocks located in NE Spain (Cabernet Sauvignon and Syrah) were analysed. The NDVI was computed from a Quickbird-2 multi-spectral image at veraison (July 2005). Yield data was acquired by means of a yield monitor during September 2005. Other variables, such as the number of buds, number of shoots, number of wine grape clusters and weight of 100 berries were sampled in a 10 rows × 5 vines pattern and used as input variables, in combination with the NDVI, to define the clusters as alternative to yield maps. Two days prior to the harvesting, grape samples were taken. The analysed variables were probable alcoholic degree, pH of the juice, total acidity, total phenolics, colour, anthocyanins and tannins. The input variables, alone or in combination, were clustered (2 and 3 Clusters) by using the ISODATA algorithm, and an analysis of variance and a multiple rang test were performed. The results show that the zones derived from the NDVI maps are more effective to differentiate grape maturity and quality variables than the zones derived from the yield maps. The inclusion of other grapevine fertility and load variables did not improve the results.

Keeping the balance? Management of oxidative stress, body mass and reproduction under energetic constraints by dispersing and philopatric collared flycatchers.

Dispersal, i.e. individual movement between breeding sites, is a key process for metapopulation dynamics and gene flow. Its success can be modulated by phenotypic differences between dispersing and philopatric individuals, or dispersal syndromes. However, the environmental (external) and physiological (internal) constraints underlying such syndromes remain poorly known. This project aimed at clarifying the impact of environmental variation and oxidative constraints, linked to the reactive oxygen species produced during respiration, on phenotypes associated to dispersal in a passerine bird, the collared flycatcher Ficedula albicollis. Energetic demand was experimentally (i) increased through a wing load manipulation or (ii) relieved through food supplementation. The oxidative balance of breeding flycatchers was influenced by complex interactions of dispersal status and extrinsic factors (breeding density, year, experimental treatments). Interestingly, antioxidant capacity was influenced both by permanent individual differences and by food availability, whereas measures of pro-oxidants were highly variables within individuals. Environmental variation and energetic constraints also modulated the differences in reproduction associated with dispersal: dispersing and philopatric birds differ in their management of the oxidative balance when it is competing with reproductive investment. This thesis highlights that reaction norms, rather than fixed differences, often shape traits associated to dispersal. ----- Le déplacement d'un individu entre sites de reproduction, ou dispersion, est un processus clé pour la dynamique des métapopulations et les flux de gènes. Son succès peut être modulé par des différences de phénotype, ou syndromes de dispersion. Cependant, les contraintes environnementales et physiologiques qui sous-tendent ces syndromes restent mal connues. Ce projet vise à clarifier l'impact des variations environnementales et des contraintes oxydatives (liées aux espèces réactives de l'oxygène produites durant la respiration) sur les phénotypes associés à la dispersion chez un passereau, le gobemouche à collier Ficedula albicollis. La demande énergétique a été expérimentalement (i) augmentée en manipulant la surface alaire ou (ii) diminuée par une supplémentation en nourriture. L'équilibre oxydo-réducteur des gobemouches en reproduction est influencé par des interactions complexes entre statut de dispersion et facteurs extrinsèques (densité de couples reproducteurs, année, traitement expérimental). La capacité antioxydante dépend principalement de différences permanentes entre individus, alors que les pro-oxydants présentent de grandes variations intra-individu. Environnement et contraintes énergétiques modulent aussi les différences de reproduction liées à la dispersion : les oiseaux dispersants et philopatriques diffèrent dans leur gestion de l'équilibre oxydo-réducteur lorsqu'il est en compétition avec l'investissement reproducteur. Ce travail souligne que les traits associés à la dispersion sont souvent déterminés par des normes de réaction à l'environnement et non des différences fixées entre individus.

E-PORT. Improving efficiency of Finnish port community by intelligent systems Final report of the Mobile Port project

The management of port-related supply chains is challenging due to the complex and heterogeneous operations of the ports with several actors and processes. That is why the importance of information sharing is emphasised in the ports. However, the information exchange between different port-related actors is often cumbersome and it still involves a lot of manual work and paper. Major ports and port-related actors usually have advanced information systems in daily use but these systems are seldom interoperable with each other, which prevents economies of scale to be reached. Smaller ports and companies might not be equipped with electronic data transmission at all. This is the final report of the Mobile port (MOPO) project, which has sought ways to improve the management and control of port-related sea and inland traffic with the aid of ICT technologies. The project has studied port community systems (PCS) used worldwide, evaluated the suitability of a PCS for the Finnish port operating environment and created a pilot solution of a Finnish PCS in the port of HaminaKotka. Further, the dry port concept and its influences on the transportation system have been explored. The Mobile Port project comprised of several literature reviews, interviews of over 50 port-related logistics and/or ICT professionals, two different kinds of simulation models as well as designing and implementing of the pilot solution of the Finnish PCS. The results of these multiple studies are summarised in this report. Furthermore, recommendations for future actions and the topics for further studies are addressed in the report. The study revealed that the information sharing in a typical Finnish port-related supply chain contains several bottlenecks that cause delays in shipments and waste resources. The study showed that many of these bottlenecks could be solved by building a port community system for the Finnish port community. Almost 30 different kinds of potential services or service entities of a Finnish PCS were found out during the study. The basic requirements, structure, interfaces and operation model of the Finnish PCS were also defined in the study. On the basis of the results of the study, a pilot solution of the Finnish PCS was implemented in the port of HaminaKotka. The pilot solution includes a Portconnect portal for the Finnish port community system (available at https://www.portconnect.fi) and two pilot applications, which are a service for handling the information flows concerning the movements of railway wagons and a service for handling the information flows between Finnish ports and Finland-Russian border. The study also showed that port community systems can be used to improve the environmental aspects of logistics in two different ways: 1) PCSs can bring direct environmental benefits and 2) PCSs can be used as an environmental tool in a port community. On the basis of the study, the development of the Finnish port community system should be continued by surveying other potential applications for the Finnish PCS. It is also important to study if there is need and resources to extend the Finnish PCS to operate in several ports or even on a national level. In the long run, it could be reasonable to clarify whether there would be possibilities to connect the Finnish PCS as a part of Baltic Sea wide, European-wide or even worldwide maritime and port-related network in order to get the best benefit from the system

Data management as a part of performance management: Case study about production reporting development project

Because of the increased availability of different kind of business intelligence technologies and tools it can be easy to fall in illusion that new technologies will automatically solve the problems of data management and reporting of the company. The management is not only about management of technology but also the management of processes and people. This thesis is focusing more into traditional data management and performance management of production processes which both can be seen as a requirement for long lasting development. Also some of the operative BI solutions are considered in the ideal state of reporting system. The objectives of this study are to examine what requirements effective performance management of production processes have for data management and reporting of the company and to see how they are effecting on the efficiency of it. The research is executed as a theoretical literary research about the subjects and as a qualitative case study about reporting development project of Finnsugar Ltd. The case study is examined through theoretical frameworks and by the active participant observation. To get a better picture about the ideal state of reporting system simple investment calculations are performed. According to the results of the research, requirements for effective performance management of production processes are automation in the collection of data, integration of operative databases, usage of efficient data management technologies like ETL (Extract, Transform, Load) processes, data warehouse (DW) and Online Analytical Processing (OLAP) and efficient management of processes, data and roles.

Cost-efficient virtual machine management : provisioning, admission control, and consolidation

One of the main challenges in Software Engineering is to cope with the transition from an industry based on software as a product to software as a service. The field of Software Engineering should provide the necessary methods and tools to develop and deploy new cost-efficient and scalable digital services. In this thesis, we focus on deployment platforms to ensure cost-efficient scalability of multi-tier web applications and on-demand video transcoding service for different types of load conditions. Infrastructure as a Service (IaaS) clouds provide Virtual Machines (VMs) under the pay-per-use business model. Dynamically provisioning VMs on demand allows service providers to cope with fluctuations on the number of service users. However, VM provisioning must be done carefully, because over-provisioning results in an increased operational cost, while underprovisioning leads to a subpar service. Therefore, our main focus in this thesis is on cost-efficient VM provisioning for multi-tier web applications and on-demand video transcoding. Moreover, to prevent provisioned VMs from becoming overloaded, we augment VM provisioning with an admission control mechanism. Similarly, to ensure efficient use of provisioned VMs, web applications on the under-utilized VMs are consolidated periodically. Thus, the main problem that we address is cost-efficient VM provisioning augmented with server consolidation and admission control on the provisioned VMs. We seek solutions for two types of applications: multi-tier web applications that follow the request-response paradigm and on-demand video transcoding that is based on video streams with soft realtime constraints. Our first contribution is a cost-efficient VM provisioning approach for multi-tier web applications. The proposed approach comprises two subapproaches: a reactive VM provisioning approach called ARVUE and a hybrid reactive-proactive VM provisioning approach called Cost-efficient Resource Allocation for Multiple web applications with Proactive scaling. Our second contribution is a prediction-based VM provisioning approach for on-demand video transcoding in the cloud. Moreover, to prevent virtualized servers from becoming overloaded, the proposed VM provisioning approaches are augmented with admission control approaches. Therefore, our third contribution is a session-based admission control approach for multi-tier web applications called adaptive Admission Control for Virtualized Application Servers. Similarly, the fourth contribution in this thesis is a stream-based admission control and scheduling approach for on-demand video transcoding called Stream-Based Admission Control and Scheduling. Our fifth contribution is a computation and storage trade-o strategy for cost-efficient video transcoding in cloud computing. Finally, the sixth and the last contribution is a web application consolidation approach, which uses Ant Colony System to minimize the under-utilization of the virtualized application servers.

Energy Management System for LVDC Island Networks

Recent developments in power electronics technology have made it possible to develop competitive and reliable low-voltage DC (LVDC) distribution networks. Further, islanded microgrids—isolated small-scale localized distribution networks— have been proposed to reliably supply power using distributed generations. However, islanded operations face many issues such as power quality, voltage regulation, network stability, and protection. In this thesis, an energy management system (EMS) that ensures efficient energy and power balancing and voltage regulation has been proposed for an LVDC island network utilizing solar panels for electricity production and lead-acid batteries for energy storage. The EMS uses the master/slave method with robust communication infrastructure to control the production, storage, and loads. The logical basis for the EMS operations has been established by proposing functionalities of the network components as well as by defining appropriate operation modes that encompass all situations. During loss-of-powersupply periods, load prioritizations and disconnections are employed to maintain the power supply to at least some loads. The proposed EMS ensures optimal energy balance in the network. A sizing method based on discrete-event simulations has also been proposed to obtain reliable capacities of the photovoltaic array and battery. In addition, an algorithm to determine the number of hours of electric power supply that can be guaranteed to the customers at any given location has been developed. The successful performances of all the proposed algorithms have been demonstrated by simulations.

Intelligent Use of Emotions in Personal Selling: A Study into the Effect of Emotional Intelligence on the Performance of Sales Executives

School of Management Studies, Cochin University of Science and Technology

Channel Adaptive MAC Protocol with Traffic-Aware Distributed Power Management in Wireless Sensor Networks-Some Performance Issues

In Wireless Sensor Networks (WSN), neglecting the effects of varying channel quality can lead to an unnecessary wastage of precious battery resources and in turn can result in the rapid depletion of sensor energy and the partitioning of the network. Fairness is a critical issue when accessing a shared wireless channel and fair scheduling must be employed to provide the proper flow of information in a WSN. In this paper, we develop a channel adaptive MAC protocol with a traffic-aware dynamic power management algorithm for efficient packet scheduling and queuing in a sensor network, with time varying characteristics of the wireless channel also taken into consideration. The proposed protocol calculates a combined weight value based on the channel state and link quality. Then transmission is allowed only for those nodes with weights greater than a minimum quality threshold and nodes attempting to access the wireless medium with a low weight will be allowed to transmit only when their weight becomes high. This results in many poor quality nodes being deprived of transmission for a considerable amount of time. To avoid the buffer overflow and to achieve fairness for the poor quality nodes, we design a Load prediction algorithm. We also design a traffic aware dynamic power management scheme to minimize the energy consumption by continuously turning off the radio interface of all the unnecessary nodes that are not included in the routing path. By Simulation results, we show that our proposed protocol achieves a higher throughput and fairness besides reducing the delay

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year

Sustainable Solid Waste Management Through Ecological Footprint Analysis – A Solution To Kochi City, India

Kochi, the commercial capital of Kerala, South India and second most important city next to Mumbai on the Western coast is a land having a wide variety of residential environments. Due to rapid population growth, changing lifestyles, food habits and living standards, institutional weaknesses, improper choice of technology and public apathy, the present pattern of the city can be classified as that of haphazard growth with typical problems characteristics of unplanned urban development especially in the case of solid waste management. To have a better living condition for us and our future generations, we must know where we are now and how far we need to go. We, each individual must calculate how much nature we use and compare it to how much nature we have available. This can be achieved by applying the concept of ecological footprint. Ecological footprint analysis (EFA) is a quantitative tool that represents the ecological load imposed on earth by humans in spatial terms. The aim of applying EFA to Kochi city is to quantify the consumption and waste generation of a population and to compare it with the existing biocapacity. By quantifying the ecological footprint we can formulate strategies to reduce the footprint and there by having a sustainable living. The paper discusses the various footprint components of Kochi city and in detail analyses the waste footprint of the residential areas using waste footprint analyzer. An attempt is also made to suggest some waste foot print reduction strategies thereby making the city sustainable as far as solid waste management is concerned.