Trabalho temporário e qualidade dos serviços prestados: reflexão sobre a evolução recente na região de Setúbal

Os conceitos de qualidade e capital humano são amplamente conhecidos e a sua importância aceite por todos. A aplicação destes pressupostos à realidade do trabalho temporário, tomou-se um imperativo face ao contexto económico actual, repleto de rápidas mudanças organizacionais, caracterizado por colaboradores detentores de um novo leque de competências e flexibilidade profissional. Ao longo deste trabalho. procurou-se analisar a possível integração do trabalho temporário num novo modelo de relações laborais, na tentativa de distanciamento da corrente associação do trabalho temporário a uma "forma atípica de trabalho'', estabelecendo ainda uma breve evolução do trabalho temporário na Península de Setúbal. baseada na apreciação de trabalhos análogos. Em resultado da aplicação de questionário. definiu-se uma hierarquia de características individuais e organizacionais, como critério válido para um futuro processo de recrutamento e selecção, permitindo averiguar, ao nível do individuo, um aumento de competências profissionais e técnicas, acompanhado pelo incremento de formação e experiência profissional. Concluindo ao nível organizacional que qualidades como flexibilidade e dinamismo, aliado à experiência profissional, são factores críticos no processo de recrutamento e selecção, sendo imprescindíveis na procura contínua da qualidade, facilitando o alcance da excelência individual e organizacional. ABSTRACT: Quality and Human Capital are widely know concepts and their importance is accepted by all. Therefore, it has become imperative to make use of them in the contex t of temporary work given the current economic situation for they are present wherever organizational change happens rapidly and stakeholders possess a wide range of professional competencies and flexibility. The aim of this work is to study the possible integration of temporary work into a new model for labour relations, in an effort to distance temporay work from the notion of "atypical form of work" with which it is presently associated. Moreover, it presents a brief evolution of temporary work in the Peninsula of Setúbal, based on the analiysis of similar works. The findings obtained from our surveys ena bled us to define a hierarchy of individual and organizational characteristics which can serve as valid criteria in future recruitment and selection processes. With these processes it is al so possible to assess any increase of professional and technical competencies regarding the individual as well improvement as regards training and professional experience. At the organizational level, qualities such as nexibility and dynamism, together with professional experience, turned out to be critical factors in the recruitment and selection process. Not only are they indispensable in the constant pursuit of quality, but they also make it easy to achieve individual and organizational excellence.

SEQUENTIAL DECISIONS AND PREDICTIONS IN NATURAL LANGUAGE PROCESSING

Natural language processing has achieved great success in a wide range of ap- plications, producing both commercial language services and open-source language tools. However, most methods take a static or batch approach, assuming that the model has all information it needs and makes a one-time prediction. In this disser- tation, we study dynamic problems where the input comes in a sequence instead of all at once, and the output must be produced while the input is arriving. In these problems, predictions are often made based only on partial information. We see this dynamic setting in many real-time, interactive applications. These problems usually involve a trade-off between the amount of input received (cost) and the quality of the output prediction (accuracy). Therefore, the evaluation considers both objectives (e.g., plotting a Pareto curve). Our goal is to develop a formal understanding of sequential prediction and decision-making problems in natural language processing and to propose efficient solutions. Toward this end, we present meta-algorithms that take an existent batch model and produce a dynamic model to handle sequential inputs and outputs. Webuild our framework upon theories of Markov Decision Process (MDP), which allows learning to trade off competing objectives in a principled way. The main machine learning techniques we use are from imitation learning and reinforcement learning, and we advance current techniques to tackle problems arising in our settings. We evaluate our algorithm on a variety of applications, including dependency parsing, machine translation, and question answering. We show that our approach achieves a better cost-accuracy trade-off than the batch approach and heuristic-based decision- making approaches. We first propose a general framework for cost-sensitive prediction, where dif- ferent parts of the input come at different costs. We formulate a decision-making process that selects pieces of the input sequentially, and the selection is adaptive to each instance. Our approach is evaluated on both standard classification tasks and a structured prediction task (dependency parsing). We show that it achieves similar prediction quality to methods that use all input, while inducing a much smaller cost. Next, we extend the framework to problems where the input is revealed incremen- tally in a fixed order. We study two applications: simultaneous machine translation and quiz bowl (incremental text classification). We discuss challenges in this set- ting and show that adding domain knowledge eases the decision-making problem. A central theme throughout the chapters is an MDP formulation of a challenging problem with sequential input/output and trade-off decisions, accompanied by a learning algorithm that solves the MDP.

Tecnología Nanopore para la secuenciación de DNA

Nanopore-based sequencer will open the path to the fourth-generation DNA sequencing technology. The main differences between this technique and the previous ones are: DNA molecule that will be sequenced does not need a previous amplification step, is not necessary any type of specific label both molecular adaptors, and it has been abolished enzymatic process in the nucleotide sequence identification event. These differences have as result a more economic method since don’t spend the necessary reagents for the previous techniques, furthermore it lets to sequence samples with a low DNA concentration. This technique is based in the use of a membrane with a biologic nanopore inserted in it whereby the molecule to analyze (analyte) it made to pass, this membrane is placed between two reservoirs containing ions, when an external volatage is applied in both sides this lead to an ion current through the nanopore. When an analyte cross the nanopore the ion current is modified, that modification in the amplitude and duration of ion current determine the physical and chemical properties of that analyte. By means of subsequent statistical analyzes it can be determined to what sequence own this ion current blockade patterns. More used nanopores are the biologic ones, although they are working to develop synthetic nanopores. The main biologic nanopores are: α-Hemolysin from Staphylococcus aureus (α-HL), Mycobacterium smegmatis porin A (MspA) and bacteriophage phi29 pore (phi29). Α-HL and MspA have in their narrowest point a diameter similar to nucleotide size, they are functional at high temperature both wide range of pH (2-12) but MspA is able to read four nucleotide at the same time while α- HL just can read one by one. Finally, phi29 present a bigger diameter what let to get information about DNA spatial conformation and their interaction with proteins (Feng et al., 2015). Nowaday Oxford Nanopore Technologies (ONT) is the only company which has developed Nanopore technology; they have two devices available to sequencing (PromethION and MinION). The MinION is a single-use DNA sequencing device with the size of a USB memory with a total of 3000 nanopores that can sequence until 200kb. The PrometheION is big size sequencer that own 48 different cells, what let to sequence different samples at the same time, with a total of 144.000 nanopores and reading of several megabases (https://www.nanoporetech.com/). The high processivity and low cost become this technique in a great option to massive- sequencing.

Thin films of Cu, In and Sb chalcogenides as photovoltaic absorbers

Many different photovoltaic technologies are being developed for large-scale solar energy conversion such as crystalline silicon solar cells, thin film solar cells based on a-Si:H, CIGS and CdTe. As the demand for photovoltaics rapidly increases, there is a pressing need for the identification of new visible light absorbing materials for thin-film solar cells. Nowadays there are a wide range of earth-abundant absorber materials that have been studied around the world by different research groups. The current thin film photovoltaic market is dominated by technologies based on the use of CdTe and CIGS, these solar cells have been made with laboratory efficiencies up to 19.6% and 20.8% respectively. However, the scarcity and high cost of In, Ga and Te can limit in the long-term the production in large scale of photovoltaic devices. On the other hand, quaternary CZTSSe which contain abundant and inexpensive elements like Cu, Zn, Sn, S and Se has been a potential candidate for PV technology having solar cell efficiency up to 12.6%, however, there are still some challenges that must be accomplished for this material. Therefore, it is evident the need to find the alternative inexpensive and earth abundant materials for thin film solar cells. One of these alternatives is copper antimony sulfide(CuSbS2) which contains abundant and non-toxic elements which has a direct optical band gap of 1.5 eV, the optimum value for an absorber material in solar cells, suggesting this material as one among the new photovoltaic materials. This thesis work focuses on the preparation and characterization of In6Se7, CuSbS2 and CuSb(S1-xSex)2 thin films for their application as absorber material in photovoltaic structures using two stage process by the combination of chemical bath deposition and thermal evaporation.

Evaluation of the conductor-like screening model for real solvents for the prediction of the water activity coefficient at infinite dilution in ionic liquids

Ionic liquids (ILs) have attracted great attention, from both industry and academia, as alternative fluids for very different types of applications. The large number of cations and anions allow a wide range of physical and chemical characteristics to be designed. However, the exhaustive measurement of all these systems is impractical, thus requiring the use of a predictive model for their study. In this work, the predictive capability of the conductor-like screening model for real solvents (COSMO-RS), a model based on unimolecular quantum chemistry calculations, was evaluated for the prediction water activity coefficient at infinite dilution, gamma(infinity)(w), in several classes of ILs. A critical evaluation of the experimental and predicted data using COSMO-RS was carried out. The global average relative deviation was found to be 27.2%, indicating that the model presents a satisfactory prediction ability to estimate gamma(infinity)(w) in a broad range of ILs. The results also showed that the basicity of the ILs anions plays an important role in their interaction with water, and it considerably determines the enthalpic behavior of the binary mixtures composed by Its and water. Concerning the cation effect, it is possible to state that generally gamma(infinity)(w) increases with the cation size, but it is shown that the cation-anion interaction strength is also important and is strongly correlated to the anion ability to interact with water. The results here reported are relevant in the understanding of ILs-water interactions and the impact of the various structural features of its on the gamma(infinity)(w) as these allow the development of guidelines for the choice of the most suitable lLs with enhanced interaction with water.

Spotter: towards a unified search interface in IDEs

Program comprehension requires developers to reason about many kinds of highly interconnected software entities. Dealing with this reality prompts developers to continuously intertwine searching and navigation. Nevertheless, most integrated development environments (IDEs) address searching by means of many disconnected search tools, making it difficult for developers to reuse search results produced by one search tool as input for another search tool. This forces developers to spend considerable time manually linking disconnected search results. To address this issue we propose Spotter, a model for expressing and combining search tools in a unified way. The current implementation shows that Spotter can unify a wide range of search tools. More information about Spotter can be found at scg.unibe.ch/research/moldablespotter

Accelerating wide-angle converging waves in the near field

We show that a wide-angle converging wave may be transformed into a shape-preserving accelerating beam having a beam-width near the diffraction limit. For that purpose, we followed a strategy that is particularly conceived for the acceleration of nonparaxial laser beams, in contrast to the well-known method by Siviloglou et al (2007 Phys. Rev. Lett. 99 213901). The concept of optical near-field shaping is applied to the design of non-flat ultra-narrow diffractive optical elements. The engineered curvilinear caustic can be set up by the beam emerging from a dynamic assembly of elementary gratings, the latter enabling to modify the effective refractive index of the metamaterial as it is arranged in controlled orientations. This light shaping process, besides being of theoretical interest, is expected to open up a wide range of broadband application possibilities.

Less is more: development and evaluation of an interactive e-atlas to support anatomy learning

An Interactive electronic Atlas (IeA) was developed to assist first-year nursing students with interpretation of laboratory-based prosected cadaveric material. It was designed, using pedagogically sound principles, as a student-centered resource accessible to students from a wide range of learning backgrounds. It consisted of a highly simplified interactive interface limited to essential anatomical structures and was intended for use in a blended learning situation. The IeA's nine modules mirrored the body systems covered in a Nursing Biosciences course, with each module comprising a maximum of 10 pages using the same template: an image displaying a cadaveric specimen and, in most cases, a corresponding anatomical model with navigation panes (menus) on one side. Cursor movement over the image or clicking the menu highlighted the structure with a transparent overlay and revealed a succinct functional description. The atlas was complemented by a multiple-choice database of nearly 1,000 questions using IeA images. Students' perceptions of usability and utility were measured by survey (n = 115; 57% of the class) revealing mean access of 2.3 times per week during the 12-week semester and a median time of three hours of use. Ratings for usability and utility were high, with means ranging between 4.24 and 4.54 (five-point Likert scale; 5 = strongly agree). Written responses told a similar story for both usability and utility. The role of providing basic computer-assisted learning support for a large first-year class is discussed in the context of current research into student-centered resources and blended learning in human anatomy.

Novel design of a renewable energy remote laboratory

BACKGROUND OR CONTEXT: Current work in remote laboratories focuses on student interaction in a setting that can be at times disconnected from real world systems. Laboratories have been developed that show models of a working system, focusing on a single aspect, but very few laboratories allow the user to see the outputs of a working system that interacts with the real world as would be expected outside of a laboratory setting. It was aimed with this paper to show a design of a novel approach to building a remote laboratory that would be able to interact with a fully functional renewable energy system, and to show the students the outputs of such a system in real time. It allows for the user to be presented with information in a new context.
PURPOSE OR GOAL: With this research it is hoped to achieve a remote laboratory that will be able to present students with the data from a renewable energy system live, as it is generated as well as all the logged date generated. It is aimed with this novel approach to building a remote laboratory to assist the students in learning about renewable energy systems while allowing the student to access real data, instead of simulated data. Links to increased motivation due to realism in data given as well as change in student perception on learning in remote laboratories mean that a system such as this could change the way students approach learning about renewable energy generation systems. This will require further research however.
APPROACH: This remote laboratory required gathering data from an already established system. The live results were not recorded, and a log file was generated daily, however this was not fast enough to give to students as it was generated, so a system that could maintain communication between all systems, while also polling for data itself was required. In addition to this, the system had to communicate to a server that would give students access to the live data. The server was set up in such a way that students were not required to install any programs on their computer, multiple students could access the data at any given time, and a wide range of devices, including mobile devices, could all access the remote laboratory.
DISCUSSION: Key outcomes include the design of the remote laboratory, including screenshots of data acquisition from the renewable energy system from different devices. The design is split into two sections, one covering the server side architecture while another covers the data acquisition architecture. A very brief discussion on students’ initial interaction is also undertaken.
RECOMMENDATIONS/IMPLICATIONS/CONCLUSION: Research has shown that the degree of realism in remote education can have an effect on students’ behaviors/motivation in a remote laboratory. By allowing students to knowingly access a real system that is currently being used to generate power from renewable energy sources, the methods and motivations that students use when approaching renewable energy systems may change.

The effect of software engineers' personality traits on team climate and performance: a systematic literature review

Context Over the past 50 years numerous studies have investigated the possible effect that software engineers' personalities may have upon their individual tasks and teamwork. These have led to an improved understanding of that relationship; however, the analysis of personality traits and their impact on the software development process is still an area under investigation and debate. Further, other than personality traits, "team climate" is also another factor that has also been investigated given its relationship with software teams' performance. Objective The aim of this paper is to investigate how software professionals' personality is associated with team climate and team performance. Method In this paper we detail a Systematic Literature Review (SLR) of the effect of software engineers' personality traits and team climate on software team performance. Results Our main findings include 35 primary studies that have addressed the relationship between personality and team performance without considering team climate. The findings showed that team climate comprises a wide range of factors that fall within the fields of management and behavioral sciences. Most of the studies used undergraduate students as subjects and as surrogates of software professionals. Conclusions The findings from this SLR would be beneficial for understanding the personality assessment of software development team members by revealing the traits of personality taxonomy, along with the measurement of the software development team working environment. These measurements would be useful in examining the success and failure possibilities of software projects in development processes. General terms Human factors, performance.

Testing for predictability in panels with general predictors

The difficulty of predicting returns has recently motivated researchers to start looking for tests that are either more powerful or robust to more features of the data. Unfortunately, the way that these tests work typically involves trading robustness for power or vice versa. The current paper takes this as its starting point to develop a new panel-based approach to predictability that is both robust and powerful. Specifically, while the panel route to increased power is not new, the way in which the cross-section variation is exploited also to achieve robustness with respect to the predictor is. The result is two new tests that enable asymptotically standard normal and chi-squared inference across a wide range of empirically relevant scenarios in which the predictor may be stationary, moderately non-stationary, nearly non-stationary, or indeed unit root non-stationary. The type of cross-section dependence that can be permitted in the predictor is also very general, and can be weak or strong, although we do require that the cross-section dependence in the regression errors is of the strong form. What is more, this generality comes at no cost in terms of complicated test construction. The new tests are therefore very user-friendly.

The e-health literacy framework: A conceptual framework for characterizing e-health users and their interaction with e-health systems

In current e-health research and development there is a need for a broader understanding of the capabilities and resources required for individuals to use and benefit from e-health services, i.e. their e-health literacy. The aim of
this study was to develop a new conceptualisation of e-health literacy with consideration of the experiences of a wide range of stakeholders and in alignment with current technologies. Concept mapping was used to generate a comprehensive and grounded model of e-health literacy. Concept mapping workshop participants included patients, health professionals and medical informatics experts. Eight workshops, carried out in Denmark and United Kingdom, generated 450 statements, separated into 128 clusters. Through an inductive structured analysis, seven domains were identified: 1. Ability to process information, 2. Engagement in own health, 3. Ability to engage actively with digital services, 4. Feeling safe and in control, 5. Motivation to engage with digital services, 6. Having access to systems that work, and 7. Digital services that suit individual needs. These empirically derived domains form an e-health literacy framework (eHLF) and provide new insights into the user’s ability to understand, access and use e-health technologies. The eHLF offers a framework for evaluating an individual’s or a population’s capacity to understand, use and benefit from technology to promote and maintain their health. Such a framework also provides a potential checklist for the development and improvement of e-health services.

BARIUM CONCENTRATIONS IN ROCK SALT BY LASER INDUCED BREAKDOWN SPECTROSCOPY

Time-REsolved Laser Induced Breakdown Spectroscopy (TRELIBS) was used to determine the elemental concentration of barium in Texas Dome rock salt. TRELIBS allows for an efficient and in situ concentration analysis technique that detects a wide range of elements with no sample preparation. TRELIBS measurements were made in the 545nm to 594nm wavelength range. The proximity of a strong barium emission line (553.5481 nm) to the sodium doublet (588.9950 nm and 589.5924 nm) allowed for measurement within a single frame of the spectrograph. This barium emission line was compared to the sodium doublet for relative intensity. A homemade calibration sample containing known amounts of barium and sodium was used to determine the relative concentrations. By approximating the sodium content in the rock salt as 50%, we determined the absolute concentration of barium in the salt to be (0.13±0.03)%.

Adaptive Software Fault Prediction Approach Using Object-Oriented Metrics

As users continually request additional functionality, software systems will continue to grow in their complexity, as well as in their susceptibility to failures. Particularly for sensitive systems requiring higher levels of reliability, faulty system modules may increase development and maintenance cost. Hence, identifying them early would support the development of reliable systems through improved scheduling and quality control. Research effort to predict software modules likely to contain faults, as a consequence, has been substantial. Although a wide range of fault prediction models have been proposed, we remain far from having reliable tools that can be widely applied to real industrial systems. For projects with known fault histories, numerous research studies show that statistical models can provide reasonable estimates at predicting faulty modules using software metrics. However, as context-specific metrics differ from project to project, the task of predicting across projects is difficult to achieve. Prediction models obtained from one project experience are ineffective in their ability to predict fault-prone modules when applied to other projects. Hence, taking full benefit of the existing work in software development community has been substantially limited. As a step towards solving this problem, in this dissertation we propose a fault prediction approach that exploits existing prediction models, adapting them to improve their ability to predict faulty system modules across different software projects.

Learning data-driven models of non-verbal behaviors for building rapport using an intelligent virtual agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness.^ Evidence-based patient-centered Brief Motivational Interviewing (BMI) interventions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary.^ Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems.^ To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].^