The use of analytical hierarchy process in spatial decision support system for land use management

Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

Learning domain-specific sentiment lexicons with applications to recommender systems

Search is now going beyond looking for factual information, and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present dissertation addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. For this research objective we propose to capture sentiment words that are derived from online users’ reviews. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. To this aim we present a fully generative method that automatically learns a domain-specific lexicon and is fully independent of external sources. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. Therefore, we present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm. Furthermore, entities’ reputation is intrinsically associated with sentiment words that have a positive or negative relation with those entities. Hence, is provided a study that observes the viability of using a domain-specific lexicon to compute entities reputation. Finally, a recommendation system algorithm is improved with the use of sentiment-based ratings and entities reputation.

Cost evaluation and comparison of three decision strategies for cardiac revascularization : results of the suspected CAD protocol of the European CMR registry

Background: The public health burden of coronary artery disease (CAD) is important. Perfusion cardiac magnetic resonance (CMR) is generally accepted to detect and monitor CAD. Few studies have so far addressed its costs and costeffectiveness. Objectives: To compare in a large CMR registry the costs of a CMR-guided strategy vs two hypothetical invasive strategies for the diagnosis and the treatment of patients with suspected CAD. Methods: In 3'647 patients with suspected CAD included prospectively in the EuroCMR Registry (59 centers; 18 countries) costs were calculated for diagnostic examinations, revascularizations as well as for complication management over a 1-year follow-up. Patients with ischemia-positive CMR underwent an invasive X-ray coronary angiography (CXA) and revascularization at the discretion of the treating physician (=CMR+CXA strategy). Ischemia was found in 20.9% of patients and 17.4% of them were revascularized. In ischemia-negative patients by CMR, cardiac death and non-fatal myocardial infarctions occurred in 0.38%/y. In a hypothetical invasive arm the costs were calculated for an initial CXA followed by FFR testing in vessels with ≥50% diameter stenoses (=CXA+FFR strategy). To model this hypothetical arm, the same proportion of ischemic patients and outcome was assumed as for the CMR+CXA strategy. The coronary stenosis - FFR relationship reported in the literature was used to derive the proportion of patients with ≥50% diameter stenoses (Psten) in the study cohort. The costs of a CXA-only strategy were also calculated. Calculations were performed from a third payer perspective for the German, UK, Swiss, and US healthcare systems.

Corporate Social Responsibility in the Oil and Gas Industry: Environmental Management Systems as a Source of Sustainable Development

The environmental aspect of corporate social responsibility (CSR) expressed through the process of the EMS implementation in the oil and gas companies is identified as the main subject of this research. In the theoretical part, the basic attention is paid to justification of a link between CSR and environmental management. The achievement of sustainable competitive advantage as a result of environmental capital growth and inclusion of the socially responsible activities in the corporate strategy is another issue that is of special significance here. Besides, two basic forms of environmental management systems (environmental decision support systems and environmental information management systems) are explored and their role in effective stakeholder interaction is tackled. The most crucial benefits of EMS are also analyzed to underline its importance as a source of sustainable development. Further research is based on the survey of 51 sampled oil and gas companies (both publicly owned and state owned ones) originated from different countries all over the world and providing reports on sustainability issues in the open access. To analyze their approach to sustainable development, a specifically designed evaluation matrix with 37 indicators developed in accordance with the General Reporting Initiative (GRI) guidelines for non-financial reporting was prepared. Additionally, the quality of environmental information disclosure was measured on the basis of a quality – quantity matrix. According to results of research, oil and gas companies prefer implementing reactive measures to the costly and knowledge-intensive proactive techniques for elimination of the negative environmental impacts. Besides, it was identified that the environmental performance disclosure is mostly rather limited, so that the quality of non-financial reporting can be judged as quite insufficient. In spite of the fact that most of the oil and gas companies in the sample claim the EMS to be embedded currently in their structure, they often do not provide any details for the process of their implementation. As a potential for the further development of EMS, author mentions possible integration of their different forms in a single entity, extension of existing structure on the basis of consolidation of the structural and strategic precautions as well as development of a unified certification standard instead of several ones that exist today in order to enhance control on the EMS implementation.

Studies on Energy Requirement and Conservation in Selected Fish Harvesting Systems

Present work deals with the studies on energy requirement and convervation in selected fish harvesting systems.Modem fishing is one of the most energy intensive methods of food production. Fossil fuels used for motorised and mechanised fishing are nonrenewable and limited. Most of the environmental problems that confront mankind today are connected to the use of energy in one way or another. Code of Conduct for Responsible Fisheries (FAO, 1995) highlights the need for efficient use of energy in the fisheries sector. Information on energy requirement in different fish harvesting systems, based on the principles of energy analysis, is entirely lacking in respect of Indian fisheries. Such an analysis will provide an unbiased decision making support for maximising the yield per unit of non-renewable energy use, from different fishery resource systems, by rational deployment of harvesting systems. In the present study, results of investigations conducted during 1997-2000 on energy requirement in selected fish harvesting systems and approaches to energy conservation in fishing, are presented along with a detailed description of the fish harvesting systems and their operation. The content of the thesis is organised into 8 Chapters.

Numerical aspects in the data model of conceptual information systems

While most data analysis and decision support tools use numerical aspects of the data, Conceptual Information Systems focus on their conceptual structure. This paper discusses how both approaches can be combined.

Is export orientation a major motivator for the adoption of food safety systems in the Turkish dried fig firms?

Food safety management systems (FSMSs) and the scrutinisation of the food safety practices that are intended for adoption on the firm level both offer strategic value to the dried fig sector. This study aims to prove the hypothesis that export orientation is a major motivating force for the adoption of food safety systems in the Turkish dried fig firms. Data were obtained from 91 dried fig firms located in Aydin, Turkey. Interviews were carried out with firms’ managers/owners using a face-to-face questionnaire designed from May to August of 2010. While 36.3 percent of the interviewed firms had adopted one or more systems, the rest had no certification. A binomial logistic econometric model was employed. The parameters that influenced this decision included contractual agreements with other firms, implementation of good practices by the dried fig farmers, export orientation and cost-benefit ratio. Interestingly, the rest of the indicators employed had no statistically significant effect on adoption behaviour. This paper focusses on the export orientation parameter directly in order to test the validity of the main research hypothesis. The estimated marginal effect suggests that when dried fig firms are export-oriented, the probability that these firms will adopt food safety systems goes up by 39.5 percent. This rate was the first range observed among all the marginal probability values obtained and thus verified the hypothesis that export orientation is a major motivator for the adoption of food safety systems in the Turkish dried fig firms.

Capturing Emergent Semantics from Social Annotation Systems

The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.

Decision‐Making in Public Good Dilemmas: Theory and Agent‐Based Simulation

In many real world contexts individuals find themselves in situations where they have to decide between options of behaviour that serve a collective purpose or behaviours which satisfy one’s private interests, ignoring the collective. In some cases the underlying social dilemma (Dawes, 1980) is solved and we observe collective action (Olson, 1965). In others social mobilisation is unsuccessful. The central topic of social dilemma research is the identification and understanding of mechanisms which yield to the observed cooperation and therefore resolve the social dilemma. It is the purpose of this thesis to contribute this research field for the case of public good dilemmas. To do so, existing work that is relevant to this problem domain is reviewed and a set of mandatory requirements is derived which guide theory and method development of the thesis. In particular, the thesis focusses on dynamic processes of social mobilisation which can foster or inhibit collective action. The basic understanding is that success or failure of the required process of social mobilisation is determined by heterogeneous individual preferences of the members of a providing group, the social structure in which the acting individuals are contained, and the embedding of the individuals in economic, political, biophysical, or other external contexts. To account for these aspects and for the involved dynamics the methodical approach of the thesis is computer simulation, in particular agent-based modelling and simulation of social systems. Particularly conductive are agent models which ground the simulation of human behaviour in suitable psychological theories of action. The thesis develops the action theory HAPPenInGS (Heterogeneous Agents Providing Public Goods) and demonstrates its embedding into different agent-based simulations. The thesis substantiates the particular added value of the methodical approach: Starting out from a theory of individual behaviour, in simulations the emergence of collective patterns of behaviour becomes observable. In addition, the underlying collective dynamics may be scrutinised and assessed by scenario analysis. The results of such experiments reveal insights on processes of social mobilisation which go beyond classical empirical approaches and yield policy recommendations on promising intervention measures in particular.

Assessing the users’ need for a spatial decision support system of smallholder farming in Kenya

Accurate data of the natural conditions and agricultural systems with a good spatial resolution are a key factor to tackle food insecurity in developing countries. A broad variety of approaches exists to achieve precise data and information about agriculture. One system, especially developed for smallholder agriculture in East Africa, is the Farm Management Handbook of Kenya. It was first published in 1982/83 and fully revised in 2012, now containing 7 volumes. The handbooks contain detailed information on climate, soils, suitable crops and soil care based on scientific research results of the last 30 years. The density of facts leads to time consuming extraction of all necessary information. In this study we analyse the user needs and necessary components of a system for decision support for smallholder farming in Kenya based on a geographical information system (GIS). Required data sources were identified, as well as essential functions of the system. We analysed the results of our survey conducted in 2012 and early 2013 among agricultural officers. The monitoring of user needs and the problem of non-adaptability of an agricultural information system on the level of extension officers in Kenya are the central objectives. The outcomes of the survey suggest the establishment of a decision support tool based on already available open source GIS components. The system should include functionalities to show general information for a specific location and should provide precise recommendations about suitable crops and management options to support agricultural guidance on farm level.

Opportunities and constraints of peri-urban buffalo and dairy cattle systems in Faisalabad, Punjab, Pakistan

In the big cities of Pakistan, peri-urban dairy production plays an important role for household income generation and the supply of milk and meat to the urban population. On the other hand, milk production in general, and peri-urban dairy production in particular, faces numerous problems that have been well known for decades. Peri-urban dairy producers have been especially neglected by politicians as well as non-government-organizations (NGOs). Against this background, a study in Pakistan’s third largest city, Faisalabad (Punjab Province), was carried out with the aims of gathering basic information, determining major constraints and identifying options for improvements of the peri-urban milk production systems. For data collection, 145 peri-urban households (HH) engaged in dairy production were interviewed face to face using a structured and pretested questionnaire with an interpreter. For analyses, HH were classified into three wealth groups according to their own perception. Thus, 38 HH were poor, 95 HH well off and 12 HH rich (26.2%, 65.5% and 8.3%, respectively). The richer the respondents perceived their HH, the more frequently they were actually in possession of high value HH assets like phones, bank accounts, motorbikes, tractors and cars. Although there was no difference between the wealth groups with respect to the number of HH members (about 10, range: 1 to 23), the educational level of the HH heads differed significantly: on average, heads of poor HH had followed education for 3 years, compared to 6 years for well off HH and 8 years for rich HH. About 40% of the poor and well off HH also had off-farm incomes, while the percentage was much higher - two thirds (67%) - for the rich HH. The majority of the HH were landless (62%); the rest (55 HH) possessed agricultural land from 0.1 to 10.1 ha (average 2.8 ha), where they were growing green fodder: maize, sorghum and pearl millet in summer; berseem, sugar cane and wheat were grown in winter. Dairy animals accounted for about 60% of the herds; the number of dairy animals per HH ranged from 2 to 50 buffaloes (Nili-Ravi breed) and from 0 to 20 cows (mostly crossbred, also Sahiwal). About 37% (n=54) of the HH did not keep cattle. About three quarters of the dairy animals were lactating. The majority of the people taking care of the animals were family workers; 17.3% were hired labourers (exclusively male), employed by 11 rich and 32 well off HH; none of the poor HH employed workers, but the percentages were 33.7% for the well off and 91.7% for the rich HH. The total number of workers increased significantly with increasing wealth (poor: 2.0; well off:2.5; rich: 3.4). Overall, 69 female labourers were recorded, making up 16.8% of employed workers and one fourth of the HH’s own labourers. Apparently, their only duty was to clean the animals´ living areas; only one of them was also watering and showering the animals. Poor HH relied more on female workers than the other two groups: 27.1% of the workers of poor HH were women, but only 14.8% and 6.8% of the labour force of well off and rich HH were female. Two thirds (70%) of the HH sold milk to dhodis (middlemen) and one third (35%) to neighbours; three HH (2%) did doorstep delivery and one HH (1%) had its own shop. The 91 HH keeping both species usually sold mixed milk (97%). Clients for mixed and pure buffalo milk were dhodis (78%, respectively 59%) and neighbours (28%, respectively 47%). The highest milk prices per liter (Pakistani Rupees, 100 PKR @ 0.8 Euro) were paid by alternative clients (44 PKR; 4 HH), followed by neighbours (40 PKR, 50 HH); dhodis paid lower prices (36 PKR, 99 HH). Prices for pure buffalo and mixed milk did not differ significantly. However, HH obtaining the maximum price from the respective clients for the respective type of milk got between 20% (mixed milk, alternative clients) and 68% (mixed milk, dhodi) more than HH fetching the minimum price. Some HH (19%) reported 7% higher prices for the current summer than the preceding winter. Amount of milk sold and distance from the HH to the city center did not influence milk prices. Respondents usually named problems that directly affected their income and that were directly and constantly visible to them, such as high costs, little space and fodder shortages. Other constraints that are only influencing their income indirectly, e.g. the relatively low genetic potential of their animals due to neglected breeding as well as the short- and long-term health problems correlated with imbalanced feeding and insufficient health care, were rarely named. The same accounts for problems accompanying improper dung management (storage, disposal, burning instead of recycling) for the environment and human health. Most of the named problems are linked to each other and should be addressed within the context of the entire system. Therefore, further research should focus on systematic investigations and improvement options, taking a holistic and interdisciplinary approach instead of only working in single fields. Concerted efforts of dairy farmers, researchers, NGOs and political decision makers are necessary to create an economic, ecological and social framework that allows dairy production to serve the entire society. For this, different improvement options should be tested in terms of their impact on environment and income of the farmers, as well as feasibility and sustainability in the peri-urban zones of Faisalabad.

Embedding Emotional Context in Recommender Systems

Emotions are crucial for user's decision making in recommendation processes. We first introduce ambient recommender systems, which arise from the analysis of new trends on the exploitation of the emotional context in the next generation of recommender systems. We then explain some results of these new trends in real-world applications through the smart prediction assistant (SPA) platform in an intelligent learning guide with more than three million users. While most approaches to recommending have focused on algorithm performance. SPA makes recommendations to users on the basis of emotional information acquired in an incremental way. This article provides a cross-disciplinary perspective to achieve this goal in such recommender systems through a SPA platform. The methodology applied in SPA is the result of a bunch of technology transfer projects for large real-world rccommender systems

Studies about the atomic capabilities concept for linear control systems in physical multi-agent environments

This paper shows the impact of the atomic capabilities concept to include control-oriented knowledge of linear control systems in the decisions making structure of physical agents. These agents operate in a real environment managing physical objects (e.g. their physical bodies) in coordinated tasks. This approach is presented using an introspective reasoning approach and control theory based on the specific tasks of passing a ball and executing the offside manoeuvre between physical agents in the robotic soccer testbed. Experimental results and conclusions are presented, emphasising the advantages of our approach that improve the multi-agent performance in cooperative systems

Self-organized sociopolitical interactions as the best way to achieve organized patterns in human social systems: going beyond the top-down control of classical political regimes

La monografía presenta la auto-organización sociopolítica como la mejor manera de lograr patrones organizados en los sistemas sociales humanos, dada su naturaleza compleja y la imposibilidad de las tareas computacionales de los regímenes políticos clásico, debido a que operan con control jerárquico, el cual ha demostrado no ser óptimo en la producción de orden en los sistemas sociales humanos. En la monografía se extrapola la teoría de la auto-organización en los sistemas biológicos a las dinámicas sociopolíticas humanas, buscando maneras óptimas de organizarlas, y se afirma que redes complejas anárquicas son la estructura emergente de la auto-organización sociopolítica.

Does uncertainty cause inertia in decision making? An experimental study of the role of regret aversion and indecisiveness

Previous research has shown that often there is clear inertia in individual decision making---that is, a tendency for decision makers to choose a status quo option. I conduct a laboratory experiment to investigate two potential determinants of inertia in uncertain environments: (i) regret aversion and (ii) ambiguity-driven indecisiveness. I use a between-subjects design with varying conditions to identify the effects of these two mechanisms on choice behavior. In each condition, participants choose between two simple real gambles, one of which is the status quo option. I find that inertia is quite large and that both mechanisms are equally important.