Evaluating the conservation of graffiti based on cultural significance.

Purpose – Graffiti, both ancient and contemporary, could be argued to be significant and therefore worthy of protection. Attaching value is, however, subjective with no specific method being solely utilised for evaluating these items. The purpose of this paper to help those who are attempting to evaluate the merit of graffiti to do so, by determining “cultural significance”, which is a widely adopted concept for attaching value to the historic built environment. The current Scottish system utilised to assess “cultural significance” is the Scottish Historic Environment Policy (SHEP) which shares many common features with other determinants of cultural significance in different countries. The SHEP document, as with other systems, could however be criticised for being insufficiently sensitive to enable the evaluation of historic graffiti due, in part, to the subjective nature of determination of aesthetic value. Design/methodology/approach – A review of literature is followed by consideration of case studies taken from a variety of historical and geographical contexts. The majority of examples of graffiti included in this paper have been selected for their relative high profile, previous academic study, and breadth of geographic spread. This selection will hopefully enable a relatively comprehensive, rational assessment to be undertaken. That being said, one example has been integrated to reflect commonly occurring graffiti that is typical to all of the built environment. Findings – The determination of aesthetic value is particularly problematic for the evaluator and the use of additional art‐based mechanisms such as “significant form”, “self expression” and “meaning” may aid this process. Regrettably, these determinants are also in themselves subjective, enhancing complexity of evaluation. Almost all graffiti could be said to have artistic merit, using the aforementioned determinants. However, whether it is “good” art is an all together different question. The evaluation of “good” art and graffiti would have traditionally been evaluated by experts. Today, determination of graffiti should be evaluated and value attached by broader society, community groups, and experts alike. Originality/value – This research will assist those responsible for historic building conservation with the evaluation of whether graffiti is worthy of conservation.

A Stationless Bikeshare Proof of Concept for College Campuses

Bikeshares promote healthy lifestyles and sustainability among commuters, casual riders, and tourists. However, the central pillar of modern systems, the bike station, cannot be easily integrated into a compact college campus. Fixed stations lack the flexibility to meet the needs of college students who make quick, short-distance trips. Additionally, the necessary cost of implementing and maintaining each station prohibits increasing the number of stations for user convenience. Therefore, the team developed a stationless bikeshare based on a smartlock permanently attached to bicycles in the system. The smartlock system design incorporates several innovative approaches to provide usability, security, and reliability that overcome the limitations of a station centered design. A focus group discussion allowed the team to receive feedback on the early lock, system, and website designs, identify improvements and craft a pleasant user experience. The team designed a unique, two-step lock system that is intuitive to operate while mitigating user error. To ensure security, user access is limited through near field ii communications (NFC) technology connected to a mechatronic release system. The said system relied on a NFC module and a servo working through an Arduino microcontroller coded in the Arduino IDE. To track rentals and maintain the system, each bike is fitted with an XBee module to communicate with a scalable ZigBee mesh network. The network allows for bidirectional, real-time communication with a Meteor.js web application, which enables user and administrator functions through an intuitive user interface available on mobile and desktop. The development of an independent smartlock to replace bike stations is essential to meet the needs of the modern college student. With the goal of creating a bikeshare that better serves college students, Team BIKES has laid the framework for a system that is affordable, easily adaptable, and implementable on any university expressing an interest in bringing a bikeshare to its campus.

Enhancing business English terminology through concept mapping

Given the need of a growing internationalization of business, to have a good command of English is, most of the times important for the development of technical (specific) competences. It is, thus, critical that professionals use accurate terminology to set grounds for a well-succeeded communication. Furthermore, business communication is increasingly moving to ICT-mediated sets and professionals have to be able to promptly adjust to these needs, resorting to trustworthy online information sources, but also using technologies that better serve their business purposes. In this scenario, the main objective of this study is to find evidence as to the utility of concept mapping as a teaching and learning strategy for the appropriation of business English terminology, enabling students to use English more efficiently as language of communication in business context. This study was based on a case study methodology, mainly of exploratory nature. Participants were students (n= 30) enrolled in the subject English Applied to Management II at Águeda School of Technology and Management – University of Aveiro (2013/14 edition). They were asked to create and peer review two concept maps (cmaps), one individually and another in pairs. The data gathered were treated and analysed resorting qualitative (content analysis) and to quantitative (descriptive statistical analysis) techniques. Results of the data analysis unveil that the use of a collaborative concept mapping tool promotes the development of linguistic competences as to the use of business terminology, but also of communication and collaboration competences. Besides, it was also a very important motivation element in the students’ engagement with the subject content.

Proactive Marketing – Concept Development and Empirical Analysis

In this thesis, proactive marketing is suggested to be a broader concept than existing research assumes. Although the concept has been mentioned in the context of competitive advantage in previous research, it has not been comprehensively described. This thesis shows that proactive marketing is more than investing in marketing communications of a company. Proactive marketing is described as a three-phased process that contains different customer value identification, creation, and delivery activities. The purpose of proactive marketing is essentially to anticipate and pursue market opportunities that bring value to the company’s stakeholders. Ultimately, proactive marketing aims at acting first on the market, shaping the markets, and thus reaching competitive advantage. The proactive marketing process is supported by the structures of an organization. Suitable structures for proactive marketing are identified in the thesis based on existing research and through an empirical analysis. Moreover, proactive marketing is related to two management theories: the dynamic capabilities framework and the empowerment of employees. A dynamic environment requires companies that pursue proactive marketing to change continuously. Dynamic capabilities are considered as tools of the management, which enable companies to create suitable conditions for the constant change. Empowerment of employees is a management practice that creates proactive behaviors in individuals. The empirical analysis is conducted in an online company operating in the rapidly changing marketplace of the Internet. Through the empirical analysis, the thesis identifies in practice how proactiveness manifests in the marketing process of a company, how organizational structures facilitate proactive marketing, and how proactive marketing is managed. The theoretical contribution of this thesis consist of defining the proactive marketing concept comprehensively and providing further research suggestions related to proactive marketing.

Leveraging Multiple Features for Image Retrieval and Matching

The goal of image retrieval and matching is to find and locate object instances in images from a large-scale image database. While visual features are abundant, how to combine them to improve performance by individual features remains a challenging task. In this work, we focus on leveraging multiple features for accurate and efficient image retrieval and matching. We first propose two graph-based approaches to rerank initially retrieved images for generic image retrieval. In the graph, vertices are images while edges are similarities between image pairs. Our first approach employs a mixture Markov model based on a random walk model on multiple graphs to fuse graphs. We introduce a probabilistic model to compute the importance of each feature for graph fusion under a naive Bayesian formulation, which requires statistics of similarities from a manually labeled dataset containing irrelevant images. To reduce human labeling, we further propose a fully unsupervised reranking algorithm based on a submodular objective function that can be efficiently optimized by greedy algorithm. By maximizing an information gain term over the graph, our submodular function favors a subset of database images that are similar to query images and resemble each other. The function also exploits the rank relationships of images from multiple ranked lists obtained by different features. We then study a more well-defined application, person re-identification, where the database contains labeled images of human bodies captured by multiple cameras. Re-identifications from multiple cameras are regarded as related tasks to exploit shared information. We apply a novel multi-task learning algorithm using both low level features and attributes. A low rank attribute embedding is joint learned within the multi-task learning formulation to embed original binary attributes to a continuous attribute space, where incorrect and incomplete attributes are rectified and recovered. To locate objects in images, we design an object detector based on object proposals and deep convolutional neural networks (CNN) in view of the emergence of deep networks. We improve a Fast RCNN framework and investigate two new strategies to detect objects accurately and efficiently: scale-dependent pooling (SDP) and cascaded rejection classifiers (CRC). The SDP improves detection accuracy by exploiting appropriate convolutional features depending on the scale of input object proposals. The CRC effectively utilizes convolutional features and greatly eliminates negative proposals in a cascaded manner, while maintaining a high recall for true objects. The two strategies together improve the detection accuracy and reduce the computational cost.

A Mismatch-Based Model for Memory Reconsolidation and Extinction in Attractor Networks

OSAN, R. , TORT, A. B. L. , AMARAL, O. B. . A mismatch-based model for memory reconsolidation and extinction in attractor networks. Plos One, v. 6, p. e23113, 2011.

Structured cases in case-based reasoning: re-using and adapting cases for time-tabling problems

In this paper, we present a case-based reasoning (CBR) approach solving educational time-tabling problems. Following the basic idea behind CBR, the solutions of previously solved problems are employed to aid finding the solutions for new problems. A list of feature-value pairs is insufficient to represent all the necessary information. We show that attribute graphs can represent more information and thus can help to retrieve re-usable cases that have similar structures to the new problems. The case base is organised as a decision tree to store the attribute graphs of solved problems hierarchically. An example is given to illustrate the retrieval, re-use and adaptation of structured cases. The results from our experiments show the effectiveness of the retrieval and adaptation in the proposed method.

Case-based reasoning in course timetabling: an attribute graph approach

An earlier Case-based Reasoning (CBR) approach developed by the authors for educational course timetabling problems employed structured cases to represent the complex relationships between courses. Previous solved cases represented by attribute graphs were organized hierarchically into a decision tree. The retrieval searches for graph isomorphism among these attribute graphs. In this paper, the approach is further developed to solve a wider range of problems. We also attempt to retrieve those graphs that have common similar structures but also have some differences. Costs that are assigned to these differences have an input upon the similarity measure. A large number of experiments are performed consisting of different randomly produced timetabling problems and the results presented here strongly indicate that a CBR approach could provide a significant step forward in the development of automated system to solve difficult timetabling problems. They show that using relatively little effort, we can retrieve these structurally similar cases to provide high quality timetables for new timetabling problems.

Development of paper-based color test-strip for drug detection in aquatic environment: Application to oxytetracycline

The wide use of antibiotics in aquaculture has led to the emergence of resistant microbial species. It should be avoided/minimized by controlling the amount of drug employed in fish farming. For this purpose, the present work proposes test-strip papers aiming at the detection/semi-quantitative determination of organic drugs by visual comparison of color changes, in a similar analytical procedure to that of pH monitoring by universal pH paper. This is done by establishing suitable chemical changes upon cellulose, attributing the paper the ability to react with the organic drug and to produce a color change. Quantitative data is also enabled by taking a picture and applying a suitable mathematical treatment to the color coordinates given by the HSL system used by windows. As proof of concept, this approach was applied to oxytetracycline (OXY), one of the antibiotics frequently used in aquaculture. A bottom-up modification of paper was established, starting by the reaction of the glucose moieties on the paper with 3-triethoxysilylpropylamine (APTES). The so-formed amine layer allowed binding to a metal ion by coordination chemistry, while the metal ion reacted after with the drug to produce a colored compound. The most suitable metals to carry out such modification were selected by bulk studies, and the several stages of the paper modification were optimized to produce an intense color change against the concentration of the drug. The paper strips were applied to the analysis of spiked environmental water, allowing a quantitative determination for OXY concentrations as low as 30 ng/mL. In general, this work provided a simple, method to screen and discriminate tetracycline drugs, in aquaculture, being a promising tool for local, quick and cheap monitoring of drugs.

Is there a health risk concerning the children´s consumption of cereal-based products? A cumulative mycotoxin risk assessment approach

Historically, the health risk of mycotoxins had been evaluated on the basis of single-chemical and single-exposure pathway scenarios. However, the co-contamination of foodstuffs with these compounds is being reported at an increasing rate and a multiple-exposure scenario for humans and vulnerable population groups as children is urgently needed. Cereals are among the first solid foods eaten by child and thus constitute an important food group of their diet. Few data are available relatively to early stages child´s exposure to mycotoxins through consumption of cereal-based foods. The present study aims to perform the cumulative risk assessment of mycotoxins present in a set of cereal-based foods including breakfast cereals (BC), processed cereal-based foods (PCBF) and biscuits (BT), consumed by children (1 to 3 years old, n=75) from Lisbon region, Portugal. Children food consumption and occurrence of 12 mycotoxins (aflatoxins, ochratoxin A, fumonisins and trichothecenes) in cereal-based foods were combined to estimate the mycotoxin daily intake, using deterministic and probabilistic approaches. Different strategies were used to treat the left censored data. For aflatoxins, as carcinogenic compounds, the margin of exposure (MoE) was calculated as a ratio of BMDL (benchmark dose lower confidence limit) and aflatoxin daily exposure. For the remaining mycotoxins, the output of exposure was compared to the dose reference values (TDI) in order to calculate the hazard quotients (HQ, ratio between exposure and a reference dose). The concentration addition (CA) concept was used for the cumulative risk assessment of multiple mycotoxins. The combined margin of exposure (MoET) and the hazard index (HI) were calculated for aflatoxins and the remaining mycotoxins, respectively. Main results revealed a significant health concern related to aflatoxins and especially aflatoxin M1 exposure according to the MoET and MoE values (below 10000), respectively. HQ and HI values for the remaining mycotoxins were below 1, revealing a low concern from a public health point of view. These are the first results on cumulative risk assessment of multiple mycotoxins present in cereal-based foods consumed by children. Considering the present results, more research studies are needed to provide the governmental regulatory bodies with data to develop an approach that contemplate the human exposure and, particularly, children, to multiple mycotoxins in food. The last issue is particularly important considering the potential synergistic effects that could occur between mycotoxins and its potential impact on human and, mainly, children health.

Application of mathematical models to mycotoxins children risk assessment: a case study of Portuguese children exposure to co-occurring mycotoxins in processed cereal-based foods

People, animals and the environment can be exposed to multiple chemicals at once from a variety of sources, but current risk assessment is usually carried out based on one chemical substance at a time. In human health risk assessment, ingestion of food is considered a major route of exposure to many contaminants, namely mycotoxins, a wide group of fungal secondary metabolites that are known to potentially cause toxicity and carcinogenic outcomes. Mycotoxins are commonly found in a variety of foods including those intended for consumption by infants and young children and have been found in processed cereal-based foods available in the Portuguese market. The use of mathematical models, including probabilistic approaches using Monte Carlo simulations, constitutes a prominent issue in human health risk assessment in general and in mycotoxins exposure assessment in particular. The present study aims to characterize, for the first time, the risk associated with the exposure of Portuguese children to single and multiple mycotoxins present in processed cereal-based foods (CBF). Portuguese children (0-3 years old) food consumption data (n=103) were collected using a 3 days food diary. Contamination data concerned the quantification of 12 mycotoxins (aflatoxins, ochratoxin A, fumonisins and trichothecenes) were evaluated in 20 CBF samples marketed in 2014 and 2015 in Lisbon; samples were analyzed by HPLC-FLD, LC-MS/MS and GC-MS. Daily exposure of children to mycotoxins was performed using deterministic and probabilistic approaches. Different strategies were used to treat the left censored data. For aflatoxins, as carcinogenic compounds, the margin of exposure (MoE) was calculated as a ratio of BMDL (benchmark dose lower confidence limit) to the aflatoxin exposure. The magnitude of the MoE gives an indication of the risk level. For the remaining mycotoxins, the output of exposure was compared to the dose reference values (TDI) in order to calculate the hazard quotients (ratio between exposure and a reference dose, HQ). For the cumulative risk assessment of multiple mycotoxins, the concentration addition (CA) concept was used. The combined margin of exposure (MoET) and the hazard index (HI) were calculated for aflatoxins and the remaining mycotoxins, respectively. 71% of CBF analyzed samples were contaminated with mycotoxins (with values below the legal limits) and approximately 56% of the studied children consumed CBF at least once in these 3 days. Preliminary results showed that children exposure to single mycotoxins present in CBF were below the TDI. Aflatoxins MoE and MoET revealed a reduced potential risk by exposure through consumption of CBF (with values around 10000 or more). HQ and HI values for the remaining mycotoxins were below 1. Children are a particularly vulnerable population group to food contaminants and the present results point out an urgent need to establish legal limits and control strategies regarding the presence of multiple mycotoxins in children foods in order to protect their health. The development of packaging materials with antifungal properties is a possible solution to control the growth of moulds and consequently to reduce mycotoxin production, contributing to guarantee the quality and safety of foods intended for children consumption.

A path-based framework for analyzing large markov models

Reliability and dependability modeling can be employed during many stages of analysis of a computing system to gain insights into its critical behaviors. To provide useful results, realistic models of systems are often necessarily large and complex. Numerical analysis of these models presents a formidable challenge because the sizes of their state-space descriptions grow exponentially in proportion to the sizes of the models. On the other hand, simulation of the models requires analysis of many trajectories in order to compute statistically correct solutions. This dissertation presents a novel framework for performing both numerical analysis and simulation. The new numerical approach computes bounds on the solutions of transient measures in large continuous-time Markov chains (CTMCs). It extends existing path-based and uniformization-based methods by identifying sets of paths that are equivalent with respect to a reward measure and related to one another via a simple structural relationship. This relationship makes it possible for the approach to explore multiple paths at the same time,· thus significantly increasing the number of paths that can be explored in a given amount of time. Furthermore, the use of a structured representation for the state space and the direct computation of the desired reward measure (without ever storing the solution vector) allow it to analyze very large models using a very small amount of storage. Often, path-based techniques must compute many paths to obtain tight bounds. In addition to presenting the basic path-based approach, we also present algorithms for computing more paths and tighter bounds quickly. One resulting approach is based on the concept of path composition whereby precomputed subpaths are composed to compute the whole paths efficiently. Another approach is based on selecting important paths (among a set of many paths) for evaluation. Many path-based techniques suffer from having to evaluate many (unimportant) paths. Evaluating the important ones helps to compute tight bounds efficiently and quickly.

From the human rights-based approach to an ecological approach on how to achieve successful inclusion in international disability education

The barriers that people with disabilities face around the world are not only inherent to the limitations resulting from the disability itself, but, more importantly, these barriers rest with the societal technologies of exclusion. Using a mixed methodology approach, I conduct a quest to revealing several societal factors that limit full participation of people with disabilities in their communities, which will contribute to understanding and developing a more comprehensive framework for full inclusion of people with disabilities into the society. First, I conduct a multiple regression analysis to seek whether there is a statistical relationship between the national level of development, the level of democratization, and the level of education within a country’s population on one hand, and expressed concern for and preparedness to improve the quality of life for people of disabilities on another hand. The results from the quantitative methodology reveal that people without disabilities are more prepared to take care of people with disabilities when the level of development of the country is higher, when the people have more freedom of expression and hold the government accountable for its actions, and when the level of corruption is under control. However, a greater concern for the well-being of people with disabilities is correlated with a high level of country development, a decreased value of political stability and absence of violence, a decreased level of government effectiveness, and a greater level of law enforcement. None of the dependent variables are significantly correlated with the level of education from a given country. Then, I delve into an interpretive analysis to understand multiple factors that contribute to the construction of attitudes and practices towards people with disabilities. In doing this, I build upon the four main principles outlined by the United Nations as strongly recommended to be embedded in all international programmes: (1) identification of claims of human rights and the corresponding obligations of governments, hence, I assess and analyze disability rights in education, looking at United Nation, United States, and European Union Perspectives Educational Rights Provisions for People with Disabilities (Ch. 3); (2) estimated capacity of individuals to claim their rights and of governments to fulfill their obligations, hence, I look at the people with disabilities as rights-holders and duty-bearers and discuss the importance of investing in special capital in the context of global development (Ch. 4); (3) programmes monitor and evaluate the outcomes and the processes under the auspices of human rights standards, hence, I look at the importance of evaluating the UN World Programme of Action Concerning People with Disabilities from multiple perspectives, as an example of why and how to monitor and evaluate educational human rights outcomes and processes (Ch. 5); and (4) programming should reflect the recommendations of international human rights bodies and mechanisms, hence, I focus on programming that fosters development of the capacity of people with disabilities, that is, planning for an ecology of disabilities and ecoducation for people with disabilities (Ch. 6). Results from both methodologies converge to a certain point, and they further complement each other. One common result for the two methodologies employed is that disability is an evolving concept when viewed in a broader context, which integrates the four spaces that the ecological framework incorporates. Another common result is that factors such as economic, social, legal, political, and natural resources and contexts contribute to the health, education and employment opportunities, and to the overall well-being of people with disabilities. The ecological framework sees all these factors from a meta-systemic perspective, where bi-directional interactions are expected and desired, and also from a human rights point of view, where the inherent value of people is upheld at its highest standard.

Protecting databases from schema disclosure: a CRUD-based protection model

Database schemas, in many organizations, are considered one of the critical assets to be protected. From database schemas, it is not only possible to infer the information being collected but also the way organizations manage their businesses and/or activities. One of the ways to disclose database schemas is through the Create, Read, Update and Delete (CRUD) expressions. In fact, their use can follow strict security rules or be unregulated by malicious users. In the first case, users are required to master database schemas. This can be critical when applications that access the database directly, which we call database interface applications (DIA), are developed by third party organizations via outsourcing. In the second case, users can disclose partially or totally database schemas following malicious algorithms based on CRUD expressions. To overcome this vulnerability, we propose a new technique where CRUD expressions cannot be directly manipulated by DIAs any more. Whenever a DIA starts-up, the associated database server generates a random codified token for each CRUD expression and sends it to the DIA that the database servers can use to execute the correspondent CRUD expression. In order to validate our proposal, we present a conceptual architectural model and a proof of concept.

Learning Binary Code Representations for Effective and Efficient Image Retrieval

The size of online image datasets is constantly increasing. Considering an image dataset with millions of images, image retrieval becomes a seemingly intractable problem for exhaustive similarity search algorithms. Hashing methods, which encodes high-dimensional descriptors into compact binary strings, have become very popular because of their high efficiency in search and storage capacity. In the first part, we propose a multimodal retrieval method based on latent feature models. The procedure consists of a nonparametric Bayesian framework for learning underlying semantically meaningful abstract features in a multimodal dataset, a probabilistic retrieval model that allows cross-modal queries and an extension model for relevance feedback. In the second part, we focus on supervised hashing with kernels. We describe a flexible hashing procedure that treats binary codes and pairwise semantic similarity as latent and observed variables, respectively, in a probabilistic model based on Gaussian processes for binary classification. We present a scalable inference algorithm with the sparse pseudo-input Gaussian process (SPGP) model and distributed computing. In the last part, we define an incremental hashing strategy for dynamic databases where new images are added to the databases frequently. The method is based on a two-stage classification framework using binary and multi-class SVMs. The proposed method also enforces balance in binary codes by an imbalance penalty to obtain higher quality binary codes. We learn hash functions by an efficient algorithm where the NP-hard problem of finding optimal binary codes is solved via cyclic coordinate descent and SVMs are trained in a parallelized incremental manner. For modifications like adding images from an unseen class, we propose an incremental procedure for effective and efficient updates to the previous hash functions. Experiments on three large-scale image datasets demonstrate that the incremental strategy is capable of efficiently updating hash functions to the same retrieval performance as hashing from scratch.