Project management: evaluation of the problems in the portuguese construction industry

During recent decades it has been possible to identify several problems in construction industry project management, related with to systematic failures in terms of fulfilling its schedule, cost and quality targets, which highlight a need for an evaluation of the factors that may cause these failures. Therefore, it is important to understand how project managers plan the projects, so that the performance and the results can be improved. However, it is important to understand if other areas beyond cost and time management that are mentioned on several studies as the most critical areas, receive the necessary attention from construction project managers. Despite the cost and time are the most sensitive areas/fields, there are several other factors that may lead to project failure. This study aims at understand the reasons that may cause the deviation in terms of cost, time and quality, from the project management point of view, looking at the knowledge areas mentioned by PMI (Project Management Institute).

A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Evaluating ubiquitous computing environments using 3D simulation

Human activity is very dynamic and subtle, and most physical environments are also highly dynamic and support a vast range of social practices that do not map directly into any immediate ubiquitous computing functionally. Identifying what is valuable to people is very hard and obviously leads to great uncertainty regarding the type of support needed and the type of resources needed to create such support. We have addressed the issues of system development through the adoption of a Crowdsourced software development model [13]. We have designed and developed Anywhere places, an open and flexible system support infrastructure for Ubiquitous Computing that is based on a balanced combination between global services and applications and situated devices. Evaluation, however, is still an open problem. The characteristics of ubiquitous computing environments make their evaluation very complex: there are no globally accepted metrics and it is very difficult to evaluate large-scale and long-term environments in real contexts. In this paper, we describe a first proposal of an hybrid 3D simulated prototype of Anywhere places that combines simulated and real components to generate a mixed reality which can be used to assess the envisaged ubiquitous computing environments [17].

A trust model for cloud computing environment

This paper presents a proposal for a management model based on reliability requirements concerning Cloud Computing (CC). The proposal was based on a literature review focused on the problems, challenges and underway studies related to the safety and reliability of Information Systems (IS) in this technological environment. This literature review examined the existing obstacles and challenges from the point of view of respected authors on the subject. The main issues are addressed and structured as a model, called "Trust Model for Cloud Computing environment". This is a proactive proposal that purposes to organize and discuss management solutions for the CC environment, aiming improved reliability of the IS applications operation, for both providers and their customers. On the other hand and central to trust, one of the CC challenges is the development of models for mutual audit management agreements, so that a formal relationship can be established involving the relevant legal responsibilities. To establish and control the appropriate contractual requirements, it is necessary to adopt technologies that can collect the data needed to inform risk decisions, such as access usage, security controls, location and other references related to the use of the service. In this process, the cloud service providers and consumers themselves must have metrics and controls to support cloud-use management in compliance with the SLAs agreed between the parties. The organization of these studies and its dissemination in the market as a conceptual model that is able to establish parameters to regulate a reliable relation between provider and user of IT services in CC environment is an interesting instrument to guide providers, developers and users in order to provide services and secure and reliable applications.

Step towards of a homemade business intelligence solution: A case study in textile industry

Nowadays, organizations are increasingly looking to invest in business intelligence solutions, mainly private companies in order to get advantage over its competitors, however they do not know what is necessary. Business intelligence allows an analysis of consolidated information in order to obtain more specific outlets and certain indications in order to support the decision making process. You can take the right decision based on the data collected from different information systems present in the organization and outside of them. The textile sector is a sector where concept of Business Intelligence it is not many explored yet. Actually there are few textile companies that have a BI platform. Thus, the article objective is present an architecture and show all the steps by which companies need to spend to implement a successful free homemade Business Intelligence system. As result the proposed approach it was validated using real data aiming assess the steps defined.

Information systems assessment in pathologic anatomy service

Information technologies changed the way of how the health organizations work, contributing to their effectiveness, efficiency and sustainability. Hospital Information Systems (HIS) are emerging on all of health institutions, helping health professionals and patients. However, HIS are not always implemented and used in the best way, leading to low levels of benefits and acceptance by users of these systems. In order to mitigate this problem, it is essential to take measures able to ensure if the HIS and their interfaces are designed in a simple and interactive way. With this in mind, a study to measure the user satisfaction and their opinion was made. It was applied the Technology Acceptance Model (TAM) on a HIS implemented on various hospital centers (AIDA), being used the Pathologic Anatomy Service. The study identified weakness and strengths features of AIDA and it pointed some solutions to improve the medical record.

Pervasive business intelligence platform to improve the quality of decision process in primary and secondary education – A Portuguese case study

Business Intelligence (BI) can be seen as a method that gathers information and data from information systems in order to help companies to be more accurate in their decision-making process. Traditionally BI systems were associated with the use of Data Warehouses (DW). The prime purpose of DW is to serve as a repository that stores all the relevant information required for making the correct decision. The necessity to integrate streaming data became crucial with the need to improve the efficiency and effectiveness of the decision process. In primary and secondary education, there is a lack of BI solutions. Due to the schools reality the main purpose of this study is to provide a Pervasive BI solution able to monitoring the schools and student data anywhere and anytime in real-time as well as disseminating the information through ubiquitous devices. The first task consisted in gathering data regarding the different choices made by the student since his enrolment in a certain school year until the end of it. Thereafter a dimensional model was developed in order to be possible building a BI platform. This paper presents the dimensional model, a set of pre-defined indicators, the Pervasive Business Intelligence characteristics and the prototype designed. The main contribution of this study was to offer to the schools a tool that could help them to make accurate decisions in real-time. Data dissemination was achieved through a localized application that can be accessed anywhere and anytime.

Predicting plateau pressure in intensive medicine for ventilated patients

Barotrauma is identified as one of the leading diseases in Ventilated Patients. This type of problem is most common in the Intensive Care Units. In order to prevent this problem the use of Data Mining (DM) can be useful for predicting their occurrence. The main goal is to predict the occurence of Barotrauma in order to support the health professionals taking necessary precautions. In a first step intensivists identified the Plateau Pressure values as a possible cause of Barotrauma. Through this study DM models (classification) where induced for predicting the Plateau Pressure class (>=30 cm

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Interacting and making personalized recommendations of places of interest to tourists

Advances in Intelligent Systems and Computing, 353

Dependable decentralized storage management for cloud computing

The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto.

Development of an intelligent bio-based packaging system

[Extrat] Currently there is a growing interest in the development of eco-efficient bio-based packaging, being active, smart and intelligent packaging the most highlighted among various innovations. Intelligent packaging has the ability to detect and mark, in real time, changes that might occur within the package/in the food product. Their main purpose is to help the consumer decide whether to buy a certain food product, ensuring that when it is bought it has not suffered significant changes influencing its quality and safety. (...)

Learning Robotics for youngsters - the RoboParty experience

Series: "Advances in intelligent systems and computing , ISSN 2194-5357, vol. 417"

A soft computing approach to kidney diseases evaluation

Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

An assessment of chronic kidney diseases

Kidney renal failure means that one’s kidney have unexpectedlystoppedfunctioning,i.e.,oncechronicdiseaseis exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapiddeteriorationoftherenalfunction,butisoftenreversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis. The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow onetoconsiderincomplete,unknown,and evencontradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.