Negotiation Support for Co-design of Business Services

Part 3: Product-Service Systems

A Collaborative Mobile Crowdsensing System for Smart Cities

Nowadays words like Smart City, Internet of Things, Environmental Awareness surround us with the growing interest of Computer Science and Engineering communities. Services supporting these paradigms are definitely based on large amounts of sensed data, which, once obtained and gathered, need to be analyzed in order to build maps, infer patterns, extract useful information. Everything is done in order to achieve a better quality of life. Traditional sensing techniques, like Wired or Wireless Sensor Network, need an intensive usage of distributed sensors to acquire real-world conditions. We propose SenSquare, a Crowdsensing approach based on smartphones and a central coordination server for time-and-space homogeneous data collecting. SenSquare relies on technologies such as CoAP lightweight protocol, Geofencing and the Military Grid Reference System.

Hybrid power system intelligent operation and protection involving plug-in electric vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. ^ The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. ^ The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.^

Mixed Spatial and Nonspatial Problems in Location Based Services

With hundreds of millions of users reporting locations and embracing mobile technologies, Location Based Services (LBSs) are raising new challenges. In this dissertation, we address three emerging problems in location services, where geolocation data plays a central role. First, to handle the unprecedented growth of generated geolocation data, existing location services rely on geospatial database systems. However, their inability to leverage combined geographical and textual information in analytical queries (e.g. spatial similarity joins) remains an open problem. To address this, we introduce SpsJoin, a framework for computing spatial set-similarity joins. SpsJoin handles combined similarity queries that involve textual and spatial constraints simultaneously. LBSs use this system to tackle different types of problems, such as deduplication, geolocation enhancement and record linkage. We define the spatial set-similarity join problem in a general case and propose an algorithm for its efficient computation. Our solution utilizes parallel computing with MapReduce to handle scalability issues in large geospatial databases. Second, applications that use geolocation data are seldom concerned with ensuring the privacy of participating users. To motivate participation and address privacy concerns, we propose iSafe, a privacy preserving algorithm for computing safety snapshots of co-located mobile devices as well as geosocial network users. iSafe combines geolocation data extracted from crime datasets and geosocial networks such as Yelp. In order to enhance iSafe's ability to compute safety recommendations, even when crime information is incomplete or sparse, we need to identify relationships between Yelp venues and crime indices at their locations. To achieve this, we use SpsJoin on two datasets (Yelp venues and geolocated businesses) to find venues that have not been reviewed and to further compute the crime indices of their locations. Our results show a statistically significant dependence between location crime indices and Yelp features. Third, review centered LBSs (e.g., Yelp) are increasingly becoming targets of malicious campaigns that aim to bias the public image of represented businesses. Although Yelp actively attempts to detect and filter fraudulent reviews, our experiments showed that Yelp is still vulnerable. Fraudulent LBS information also impacts the ability of iSafe to provide correct safety values. We take steps toward addressing this problem by proposing SpiDeR, an algorithm that takes advantage of the richness of information available in Yelp to detect abnormal review patterns. We propose a fake venue detection solution that applies SpsJoin on Yelp and U.S. housing datasets. We validate the proposed solutions using ground truth data extracted by our experiments and reviews filtered by Yelp.

Geospatial Data Indexing Analysis and Visualization via Web Services with Autonomic Resource Management

With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.

A DEA-based incentives system for centrally managed multi-unit organisations

In multi-unit organisations such as a bank and its branches or a national body delivering publicly funded health or education services through local operating units, the need arises to incentivize the units to operate efficiently. In such instances, it is generally accepted that units found to be inefficient can be encouraged to make efficiency savings. However, units which are found to be efficient need to be incentivized in a different manner. It has been suggested that efficient units could be incentivized by some reward compatible with the level to which their attainment exceeds that of the best of the rest, normally referred to as “super-efficiency”. A recent approach to this issue (Varmaz et. al. 2013) has used Data Envelopment Analysis (DEA) models to measure the super-efficiency of the whole system of operating units with and without the involvement of each unit in turn in order to provide incentives. We identify shortcomings in this approach and use it as a starting point to develop a new DEA-based system for incentivizing operating units to operate efficiently for the benefit of the aggregate system of units. Data from a small German retail bank is used to illustrate our method.

Collaborative filtering and deep learning based recommendation system for cold start items

Recommender system is a specific type of intelligent systems, which exploits historical user ratings on items and/or auxiliary information to make recommendations on items to the users. It plays a critical role in a wide range of online shopping, e-commercial services and social networking applications. Collaborative filtering (CF) is the most popular approaches used for recommender systems, but it suffers from complete cold start (CCS) problem where no rating record are available and incomplete cold start (ICS) problem where only a small number of rating records are available for some new items or users in the system. In this paper, we propose two recommendation models to solve the CCS and ICS problems for new items, which are based on a framework of tightly coupled CF approach and deep learning neural network. A specific deep neural network SADE is used to extract the content features of the items. The state of the art CF model, timeSVD++, which models and utilizes temporal dynamics of user preferences and item features, is modified to take the content features into prediction of ratings for cold start items. Extensive experiments on a large Netflix rating dataset of movies are performed, which show that our proposed recommendation models largely outperform the baseline models for rating prediction of cold start items. The two proposed recommendation models are also evaluated and compared on ICS items, and a flexible scheme of model retraining and switching is proposed to deal with the transition of items from cold start to non-cold start status. The experiment results on Netflix movie recommendation show the tight coupling of CF approach and deep learning neural network is feasible and very effective for cold start item recommendation. The design is general and can be applied to many other recommender systems for online shopping and social networking applications. The solution of cold start item problem can largely improve user experience and trust of recommender systems, and effectively promote cold start items.

A novel latent factor model for recommender system

Matrix factorization (MF) has evolved as one of the better practice to handle sparse data in field of recommender systems. Funk singular value decomposition (SVD) is a variant of MF that exists as state-of-the-art method that enabled winning the Netflix prize competition. The method is widely used with modifications in present day research in field of recommender systems. With the potential of data points to grow at very high velocity, it is prudent to devise newer methods that can handle such data accurately as well as efficiently than Funk-SVD in the context of recommender system. In view of the growing data points, I propose a latent factor model that caters to both accuracy and efficiency by reducing the number of latent features of either users or items making it less complex than Funk-SVD, where latent features of both users and items are equal and often larger. A comprehensive empirical evaluation of accuracy on two publicly available, amazon and ml-100 k datasets reveals the comparable accuracy and lesser complexity of proposed methods than Funk-SVD.

Enhancing legume ecosystem services through an understanding of plant–pollinator interplay

Legumes are bee-pollinated, but to a different extent. The importance of the plant– pollinator interplay (PPI), in flowering crops such as legumes lies in a combination of the importance of pollination for the production service and breeding strategies, plus the increasing urgency in mitigating the decline of pollinators through the development and implementation of conservation measures. To realize the full potential of the PPI, a multidisciplinary approach is required. This article assembles an international team of genebank managers, geneticists, plant breeders, experts on environmental governance and agro-ecology, and comprises several sections. The contributions in these sections outline both the state of the art of knowledge in the field and the novel aspects under development, and encompass a range of reviews, opinions and perspectives. The first three sections explore the role of PPI in legume breeding strategies. PPI based approaches to crop improvement can make it possible to adapt and re-design breeding strategies to meet both goals of: (1) optimal productivity, based on an efficient use of pollinators, and (2) biodiversity conservation. The next section deals with entomological aspects and focuses on the protection of the “pest control service” and pollinators in legume crops. The final section addresses general approaches to encourage the synergybetweenfoodproductionandpollinationservicesatfarmerfieldlevel.Twobasic approaches are proposed: (a) Farming with Alternative Pollinators and (b) Crop Design System.

Economic evaluations of clinical pharmacy services in Ireland, 2007-2015

Introduction The concept of this thesis was driven by stagnation within the Irish healthcare system. Multiple reports from pharmacy organisations had outlined possible future directions for the profession but progress was minimal, especially in comparison with other countries. The author’s directive was to evaluate the economic impact of a series of clinical pharmacy services (CPS) in hospital and community settings. Methods A systematic review of economic evaluations of clinical pharmacy services in hospital patients was undertaken to gain insight into recent research in the field. Eligible studies were evaluated using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS), to establish the quality, consistency and transparency of relevant research. A retrospective analysis of an internal hospital pharmacy interventions database was conducted. A method first described by Nesbit et al. was implemented to estimate the level of cost avoidance achieved. A cost-effectiveness analysis based on data from a randomised controlled trial of a pharmacist-supervised patient self-testing (PST) of warfarin therapy is presented. Outcome measure was the incremental cost associated with six months of intervention management. A similar cost-effectiveness analysis based on previously published RCT data was used to evaluate a novel structured pharmacist review of medication in older hospitalised patients. Cost-effectiveness analysis was presented in the form of an incremental cost-effectiveness ratio (ICER). An ICER is an additional cost per unit effect, in the case of this study, the cost of preventing an additional non-trivial ADR in hospital. A method described by Preaud et al. was adapted to estimate the clinical and economic benefit gained from vaccination of patients by a community pharmacist in Ireland in 2013/14. Sample demographic data was obtained from a national chain of community pharmacies and applied to overall national vaccination data. Results Systematic review identified twenty studies which were eligible for inclusion. Overall, pharmacist interventions had a positive impact on hospital budgets. Only three studies (15%) were deemed to be “good-quality” studies. No ‘novel’ clinical pharmacist intervention was identified during the course of this review. Analysis of internal hospital database identified 4,257 interventions documented on 2,147 individual patients over a 12 month period. Substantial cost avoidance of €710,000 was generated over a 1 year period from the perspective of the health care provider. Mean cost avoidance of €166 per intervention was generated. The cost of providing these interventions was €82,000. Substantial net cost-benefits of €626,279 and a cost-benefit ratio of 8.64 : 1 were generated based on this evaluation of pharmacist interventions. Results from an evaluation of a novel pharmacist-led form of warfarin management indicated indicated that on a per patient basis, PST was slightly more expensive than established anticoagulant management. On a per patient basis over a six month period, PST resulted in an incremental cost of €59.08 in comparison with routine care. Overall cost of managing a patient through pharmacist-supervised PST for a six month period is €226.45. However, for this increase in cost a clinically significant improvement in care was provided. Patients achieved a significantly higher time in therapeutic range during the PST arm in comparison with routine care, (72 ± 19.7% vs 59 ± 13.5%). Difference in overall cost was minimal and PST was the dominant strategy in some scenarios examined during sensitivity analysis. Structured pharmacist review of medication was determined to be dominant in comparison to usual pharmaceutical care. Even if the healthcare payer was unwilling to pay any money for the prevention of an ADR, the intervention strategy is still likely to be cost-effective (probability of being determined cost-effective = 0.707). Implementation of pharmacist-led influenza vaccination has resulted in substantial clinical and economic benefits to the healthcare system. The majority of patients (64.9%) who availed of this service had identifiable influenza-related risk factors. Of patients with influenza-related risk factors, age ≥65 year was the most commonly cited risk factor. Pharmacist vaccination services averted a total of 848 influenza cases across all age groups during the 2013/2014 influenza season. Due to receipt of vaccination in a pharmacy setting, 444 influenza-related GP visits were prevented. In terms of more serious influenza-associated events, 11 hospitalisations and five influenza-related deaths were averted. Costs averted were approximately €305,000. These were principally wider societal-related costs associated with lost productivity. Conclusion Overall, clinical pharmacy services are adding value to the Irish healthcare system in both hospital and community settings, but provision of additional funding for new services would enable them to offer a great deal more.

Evaluation of Iowa's public mental health system : task two report, 1998

The purpose of this evaluation is to assess the performance of Iowa's mental health system in relation to current standards, benchmarks and best practices found in public health systems in the United States.

A regulation-based classification system for marine protected areas (MPAs)

Marine protected areas (MPAs) are a global conservation and management tool to enhance the resilience of linked social-ecological systems with the aim of conserving biodiversity and providing ecosystem services for sustainable use. However, MPAs implemented worldwide include a large variety of zoning and management schemes from single to multiple-zoning and from no-take to multiple-use areas. The current IUCN categorisation of MPAs is based on management objectives which many times have a significant mismatch to regulations causing a strong uncertainty when evaluating global MPAs effectiveness. A novel global classification system for MPAs based on regulations of uses as an alternative or complementing, the current IUCN system of categories is presented. Scores for uses weighted by their potential impact on biodiversity were built. Each zone within a MPA was scored and an MPA index integrates the zone scores. This system classifies MPAs as well as each MPA zone individually, is globally applicable and unambiguously discriminates the impacts of uses. (C) 2016 The Authors. Published by Elsevier Ltd.

Enhancing legume ecosystem services through an understanding of plant–pollinator interplay

Legumes are bee-pollinated, but to a different extent. The importance of the plant– pollinator interplay (PPI), in flowering crops such as legumes lies in a combination of the importance of pollination for the production service and breeding strategies, plus the increasing urgency in mitigating the decline of pollinators through the development and implementation of conservation measures. To realize the full potential of the PPI, a multidisciplinary approach is required. This article assembles an international team of genebank managers, geneticists, plant breeders, experts on environmental governance and agro-ecology, and comprises several sections. The contributions in these sections outline both the state of the art of knowledge in the field and the novel aspects under development, and encompass a range of reviews, opinions and perspectives. The first three sections explore the role of PPI in legume breeding strategies. PPI based approaches to crop improvement can make it possible to adapt and re-design breeding strategies to meet both goals of: (1) optimal productivity, based on an efficient use of pollinators, and (2) biodiversity conservation. The next section deals with entomological aspects and focuses on the protection of the “pest control service” and pollinators in legume crops. The final section addresses general approaches to encourage the synergybetweenfoodproductionandpollinationservicesatfarmerfieldlevel.Twobasic approaches are proposed: (a) Farming with Alternative Pollinators and (b) Crop Design System.

Gradual correction of phosphorus availability in the no-tillage system.

2016

Double Dyke System - Natural engineering solutions

According to various studies, the effects of climate change will be a danger to ecosystems and the population, especially in coastal areas, increasing the risk of floods. Authorities are taking action to prevent future disasters using traditional engineering solutions. These solutions can have high environmental and economic costs, fixing the coastline, increasing the salinization of aquifers, and can be subject to failure mechanisms. For this reason, studies were made to use natural engineering solutions for coastal protection, instead of traditional solutions, to achieve the UN SDGs. Coastal ecosystems have the natural ability to repair and restore themselves, increasing soil elevation, and attenuating waves. One of these solutions is the Double Dyke System, consisting of creating a salt marsh between the first dyke and a second inland. The goal is to protect the coasts and to restore ecosystems. The purpose of this study is to compare the costs of natural engineering solutions with traditional ones. It is assumed that these solutions may be more effective and less expensive in the long run. For this evaluation, a suitability analysis of the polders in the Dutch Zeeland region to assess the costs and benefits under different SLR scenarios was made. A saline intrusion model was also created to analyze the effects of a salt marsh on the aquifers. From the analyzes conducted, the implementation of the DDS turns out to be the cheapest coastal defense system in all SLR scenarios. The presence of a salt marsh could also have a positive impact on the prevention of saline intrusion in the various scenarios considered. The DDS could have a positive economic and environmental impact in the long term, reducing the investment costs for coastal defense and bringing important benefits for the protection of man and nature. Despite the results, more studies are needed on the efficiency of this defense system and on the economic evaluation of non-marketable ecosystem services.