Professional Liability of the Construction Professional as an Expert Witness in the Spanish Legal Framework

Inside COBRA 2011 RICS International Research Conference, the present paper is linked to analyze the liability of the construction professional in his practice as a expert witness in the Spanish legal framework. In a large number of legal procedures related to the building it is necessary the intervention of the expert witness to report on the subject of litigation, and to give an opinion about possible causes and solutions. This field is increasingly importantly for the practice of construction professional that requires an important specialization. The expert provides his knowledge to the judge in the matter he is dealing with (construction, planning, assessment, legal, ...), providing arguments or reasons as the base for his case and acting as part of the evidence. Although the importance of expert intervention in the judicial process, the responsibilities arising from their activity is a slightly studied field. Therefore, the study has as purpose to think about the regulation of professional activities raising different aims. The first is to define the action of the construction professional-expert witness and the need for expert evidence, establishing the legal implications of this professional activity. The different types of responsibilities (the civil, criminal and administrative) have been established as well as the economic, penal or disciplinary damages that can be derived from the expert report

Hybrid Approach Combining Machine Learning and a Rule-Based Expert System for Text Categorization

This paper discusses a novel hybrid approach for text categorization that combines a machine learning algorithm, which provides a base model trained with a labeled corpus, with a rule-based expert system, which is used to improve the results provided by the previous classifier, by filtering false positives and dealing with false negatives. The main advantage is that the system can be easily fine-tuned by adding specific rules for those noisy or conflicting categories that have not been successfully trained. We also describe an implementation based on k-Nearest Neighbor and a simple rule language to express lists of positive, negative and relevant (multiword) terms appearing in the input text. The system is evaluated in several scenarios, including the popular Reuters-21578 news corpus for comparison to other approaches, and categorization using IPTC metadata, EUROVOC thesaurus and others. Results show that this approach achieves a precision that is comparable to top ranked methods, with the added value that it does not require a demanding human expert workload to train

QL-CONST1: an expert system for quality level prediction in concrete structures

Current trends in the fields of artifical intelligence and expert systems are moving towards the exciting possibility of reproducing and simulating human expertise and expert behaviour into a knowledge base, coupled with an appropriate, partially ‘intelligent’, computer code. This paper deals with the quality level prediction in concrete structures using the helpful assistance of an expert system, QL-CONST1, which is able to reason about this specific field of structural engineering. Evidence, hypotheses and factors related to this human knowledge field have been codified into a knowledge base. This knowledge base has been prepared in terms of probabilities of the presence of either hypotheses or evidence and the conditional presence of both. Human experts in the fields of structural engineering and the safety of structures gave their invaluable knowledge and assistance to the construction of the knowledge base. Some illustrative examples for, the validation of the expert system behaviour are included.

Cooperation between expert knowledge and data mining discovered knowledge: Lessons learned

Expert systems are built from knowledge traditionally elicited from the human expert. It is precisely knowledge elicitation from the expert that is the bottleneck in expert system construction. On the other hand, a data mining system, which automatically extracts knowledge, needs expert guidance on the successive decisions to be made in each of the system phases. In this context, expert knowledge and data mining discovered knowledge can cooperate, maximizing their individual capabilities: data mining discovered knowledge can be used as a complementary source of knowledge for the expert system, whereas expert knowledge can be used to guide the data mining process. This article summarizes different examples of systems where there is cooperation between expert knowledge and data mining discovered knowledge and reports our experience of such cooperation gathered from a medical diagnosis project called Intelligent Interpretation of Isokinetics Data, which we developed. From that experience, a series of lessons were learned throughout project development. Some of these lessons are generally applicable and others pertain exclusively to certain project types.

Expert systems for quality prediction in structural engineering

This work deals with quality level prediction in concrete structures through the helpful assistance of an expert system wich is able to apply reasoning to this field of structural engineering. Evidences, hypotheses and factors related to this human knowledge field have been codified into a Knowledge Base in terms of probabilities for the presence of either hypotheses or evidences,and conditional presence of both. Human experts in structural engineering and safety of structures gave their invaluable knowledge and assistance necessary when constructing the "computer knowledge body".

Computational Fluid Dynamics Expert System using Artificial Neural Networks

The design of a modern aircraft is based on three pillars: theoretical results, experimental test and computational simulations. As a results of this, Computational Fluid Dynamic (CFD) solvers are widely used in the aeronautical field. These solvers require the correct selection of many parameters in order to obtain successful results. Besides, the computational time spent in the simulation depends on the proper choice of these parameters. In this paper we create an expert system capable of making an accurate prediction of the number of iterations and time required for the convergence of a computational fluid dynamic (CFD) solver. Artificial neural network (ANN) has been used to design the expert system. It is shown that the developed expert system is capable of making an accurate prediction the number of iterations and time required for the convergence of a CFD solver.

Los agentes de la edificación desde el punto de vista de la Gestión Integral de Proyectos: diferencias y semejanzas entre la Legislación Española y los Estándares Internacionales = Expert agents in the Global Development of a building project: differences and similarities between Spanish and International contexts.

Desde los años 60, crece en Europa y Estados Unidos la preocupación y la necesidad de mejorar los procesos de gerencia de los proyectos de construcción al volverse estos más complejos. Esto ha llevado a la continua aparición de nuevos profesionales desde la fecha citada hasta nuestros días. De ahí la complejidad de conocer las cualidades de cada uno de ellos, así como las funciones a realizar o la formación que deben tener para poder desarrollar el puesto de trabajo según el papel que desempeñan para cada actividad. Muchos agentes son los que pueden intervenir en la edificación, muchas son las funciones que llevan a cabo estos agentes, muchas son las habilidades que se necesitan para realizar estas misiones, y una buena gestión de la edificación es la que hay que desarrollar para lograr el gran éxito. El presente trabajo fin de máster, dirigido a arquitectos, arquitectos técnicos, ingenieros, abogados, economistas y todos los profesionales del sector inmobiliario y de la construcción, trata de resolver todas aquellas dudas sobre los diferentes sujetos que estarán presentes desde la definición del proyecto en la fase inicial hasta el final de la obra, pasando por las fases de pre-construcción, construcción y post-construcción. (ENGLISH VERSION) Since the 1960s, most construction projects have become more and more complex, and new concerns and necessities related to the management of a project have been on the rise in Europe and in the United States. Thence, the need for more specialized professionals in the field has become a common fact, as well as the inclusion of new curricular subjects in most building engineering studies. There are different agents that play a relevant role in a building project; some of them are expected to perform a highly specialized set of functions that require specific management skills for the work to be successful. This research work—aimed mainly at engineers, quantity surveyors, lawyers, economists, real estate and construction professionals—shows the major implications of the building construction process including both pre-tender/construction and post-tender/construction stages as far as the main expert agents are involved.

Automatic expert system based on images for accuracy crop row detection in maize fields

This paper proposes an automatic expert system for accuracy crop row detection in maize fields based on images acquired from a vision system. Different applications in maize, particularly those based on site specific treatments, require the identification of the crop rows. The vision system is designed with a defined geometry and installed onboard a mobile agricultural vehicle, i.e. submitted to vibrations, gyros or uncontrolled movements. Crop rows can be estimated by applying geometrical parameters under image perspective projection. Because of the above undesired effects, most often, the estimation results inaccurate as compared to the real crop rows. The proposed expert system exploits the human knowledge which is mapped into two modules based on image processing techniques. The first one is intended for separating green plants (crops and weeds) from the rest (soil, stones and others). The second one is based on the system geometry where the expected crop lines are mapped onto the image and then a correction is applied through the well-tested and robust Theil–Sen estimator in order to adjust them to the real ones. Its performance is favorably compared against the classical Pearson product–moment correlation coefficient.

Exploring the economic value of personal information from firms' financial statements

Currently personal data gathering in online markets is done on a far larger scale and much cheaper and faster than ever before. Within this scenario, a number of highly relevant companies for whom personal data is the key factor of production have emerged. However, up to now, the corresponding economic analysis has been restricted primarily to a qualitative perspective linked to privacy issues. Precisely, this paper seeks to shed light on the quantitative perspective, approximating the value of personal information for those companies that base their business model on this new type of asset. In the absence of any systematic research or methodology on the subject, an ad hoc procedure is developed in this paper. It starts with the examination of the accounts of a number of key players in online markets. This inspection first aims to determine whether the value of personal information databases is somehow reflected in the firms’ books, and second to define performance measures able to capture this value. After discussing the strengths and weaknesses of possible approaches, the method that performs best under several criteria (revenue per data record) is selected. From here, an estimation of the net present value of personal data is derived, as well as a slight digression into regional differences in the economic value of personal information.

Low-Cost Radar-Based Target Identification Prototype using an Expert System

Smart and green cities are hot topics in current research because people are becoming more conscious about their impact on the environment and the sustainability of their cities as the population increases. Many researchers are searching for mechanisms that can reduce power consumption and pollution in the city environment. This paper addresses the issue of public lighting and how it can be improved in order to achieve a more energy efficient city. This work is focused on making the process of turning the streetlights on and off more intelligent so that they consume less power and cause less light pollution. The proposed solution is comprised of a radar device and an expert system implemented on a low-cost platform based on a DSP. By analyzing the radar echo in both the frequency and time domains, the system is able to detect and identify objects moving in front of it. This information is used to decide whether or not the streetlight should be turned on. Experimental results show that the proposed system can provide hit rates over 80%, promising a good performance. In addition, the proposed solution could be useful in kind of other applications such as intelligent security and surveillance systems and home automation.