Analysis of competitiveness level in an industrial company using a continuous improvement based approach

International audience

A MARKET-BASED APPROACH TO 3D PRINTING FOR ECONOMIC DEVELOPMENT IN GHANA

The purpose of this report is to create the foundation for further study of a market-based approach to 3D printing as an instrument for economic development in Ghana. The delivery of improved products and services to the most underserved markets is needed to spur economic activity and improve standards of living. The relationship between economic development and the advancement of technology is considered within the context of Ghana. An opportunity for market entry exists within both the bottom of the economic pyramid and the mid-segment market. 3D printing (additive manufacturing) has proven to be a disruptive technology that has demonstrated an ability to expedite the speed of innovations and create products that were previously not possible. An investigation of how 3D printers can be used to create improved products for the most underserved markets within Ghana is presented. Questions are asked to elucidate how and when adoption of 3D printers and 3D printed products may occur in the future. Based upon the existing barriers to adoption, 3D printing technology must improve before widespread adoption will occur in Ghana.

Health profile of centenarians in Portugal: a census-based approach

Background: The number of centenarians is rapidly increasing in Europe. In Portugal, it has almost tripled over the last 10 years and constitutes one of the fastest-growing segments of the population. This paper aims to describe the health and sociodemographic characteristics of Portuguese centenarians as given in the 2011 census and to identify sex differences. Methods: All persons living in Portugal mainland and Madeira and Azores islands aged 100 years old at the time of the 2011 census (N = 1,526) were considered. Measures include sociodemographic characteristics and perceived difficulties in six functional domains of basic actions (seeing, hearing, walking, cognition, self-care, and communication) as assessed by the Portuguese census official questionnaires. Results: Most centenarians are women (82.1 %), widowed (82 %), never attended school (51 %), and live in private households (71 %). The majority show major constraints in seeing (67.4 %), hearing (72.3 %), and particularly in their mobility (83.7 % cannot/have great difficulties in walking/climbing stairs and 80.7 % in bathing/dressing). In general, a better outcome was found for reported memory/concentration and understanding, with 39.1 % and 42.5 % presenting no or mild difficulty, respectively. Top-level functioning (no/mild difficulties in all dimensions concurrently) was observed in a minority of cases (5.96 %). Women outnumber men by a ratio of 4.6, and statistically significant differences were found between men and women for all health-related variables, with women presenting a higher percentage of difficulties. Conclusion: Portuguese centenarians experience great difficulties in sensory domains and basic daily living activities, and to a lesser extent in cognition and communication. The obtained profile, though self-reported, is important in considering the potential of social and family participation of this population regardless of their functional and sensory limitations. Based on the observed differences between men and women, gender-specific and gender-sensitive interventions are recommended in order to acknowledge women’s worse overall condition.

The value of peer support and a strengths-based approach in a groupwork programme for fathers in a family support setting

This paper seeks to share and critically explore the learning gained through the genesis, realisation, and facilitation process of Just for Dads, a groupwork programme for fathers, run in a family support setting. It highlights the importance of and challenges involved in engaging men in practice, and in groupwork aimed at fathers in particular. It recounts the significance of using a strengths perspective as a framework for engaging fathers in groupwork and highlights its value as experienced by participants and facilitators. The dynamic of peer learning which developed as a key part of the groupwork process is discussed, both in relation to how it was experienced by participants and also the degree to which the facilitators were part of that dynamic. Overall the paper aims to document and air key issues arising in this relatively unexplored arena of groupwork and family support practice.

Integration of process planning and scheduling using mobile-agent based approach in a networked manufacturing environment

Effective and efficient implementation of intelligent and/or recently emerged networked manufacturing systems require an enterprise level integration. The networked manufacturing offers several advantages in the current competitive atmosphere by way to reduce, by shortening manufacturing cycle time and maintaining the production flexibility thereby achieving several feasible process plans. The first step in this direction is to integrate manufacturing functions such as process planning and scheduling for multi-jobs in a network based manufacturing system. It is difficult to determine a proper plan that meets conflicting objectives simultaneously. This paper describes a mobile-agent based negotiation approach to integrate manufacturing functions in a distributed manner; and its fundamental framework and functions are presented. Moreover, ontology has been constructed by using the Protégé software which possesses the flexibility to convert knowledge into Extensible Markup Language (XML) schema of Web Ontology Language (OWL) documents. The generated XML schemas have been used to transfer information throughout the manufacturing network for the intelligent interoperable integration of product data models and manufacturing resources. To validate the feasibility of the proposed approach, an illustrative example along with varied production environments that includes production demand fluctuations is presented and compared the proposed approach performance and its effectiveness with evolutionary algorithm based Hybrid Dynamic-DNA (HD-DNA) algorithm. The results show that the proposed scheme is very effective and reasonably acceptable for integration of manufacturing functions.

A Case-Based Approach to Nosocomial Infection Detection

The nosocomial infections are a growing concern because they affect a large number of people and they increase the admission time in healthcare facilities. Additionally, its diagnosis is very tricky, requiring multiple medical exams. So, this work is focused on the development of a clinical decision support system to prevent these events from happening. The proposed solution is unique once it caters for the explicit treatment of incomplete, unknown, or even contradictory information under a logic programming basis, that to our knowledge is something that happens for the first time.

A Case Based approach to assess Waiting Time Prediction at an Intensive Care Unity

Waiting time at an intensive care unity stands for a key feature in the assessment of healthcare quality. Nevertheless, its estimation is a difficult task, not only due to the different factors with intricate relations among them, but also with respect to the available data, which may be incomplete, self-contradictory or even unknown. However, its prediction not only improves the patients’ satisfaction but also enhance the quality of the healthcare being provided. To fulfill this goal, this work aims at the development of a decision support system that allows one to predict how long a patient should remain at an emergency unit, having into consideration all the remarks that were just stated above. It is built on top of a Logic Programming approach to knowledge representation and reasoning, complemented with a Case Base approach to computing.

Age Prediction through Pelvis X-Ray Images - A Case Based approach to Problem Solving

It is well known that the dimensions of the pelvic bones depend on the gender and vary with the age of the individual. Indeed, and as a matter of fact, this work will focus on the development of an intelligent decision support system to predict individual’s age based on pelvis’ dimensions criteria. On the one hand, some basic image processing technics were applied in order to extract the relevant features from pelvic X-rays. On the other hand, the computational framework presented here was built on top of a Logic Programming approach to knowledge representation and reasoning, that caters for the handling of incomplete, unknown, or even self-contradictory information, complemented with a Case Base approach to computing.

Assessing the role of Mediterranean evergreen oaks canopy cover in land surface albedo and temperature using a remote sensing-based approach

Modifications in vegetation cover can have an impact on the climate through changes in biogeochemical and biogeophysical processes. In this paper, the tree canopy cover percentage of a savannah-like ecosystem (montado/dehesa) was estimated at Landsat pixel level for 2011, and the role of different canopy cover percentages on land surface albedo (LSA) and land surface temperature (LST) were analysed. A modelling procedure using a SGB machine-learning algorithm and Landsat 5-TM spectral bands and derived vegetation indices as explanatory variables, showed that the estimation of montado canopy cover was obtained with good agreement (R2 = 78.4%). Overall, montado canopy cover estimations showed that low canopy cover class (MT_1) is the most representative with 50.63% of total montado area. MODIS LSA and LST products were used to investigate the magnitude of differences in mean annual LSA and LST values between contrasting montado canopy cover percentages. As a result, it was found a significant statistical relationship between montado canopy cover percentage and mean annual surface albedo (R2 = 0.866, p < 0.001) and surface temperature (R2 = 0.942, p < 0.001). The comparisons between the four contrasting montado canopy cover classes showed marked differences in LSA (χ2 = 192.17, df = 3, p < 0.001) and LST (χ2 = 318.18, df = 3, p < 0.001). The highest montado canopy cover percentage (MT_4) generally had lower albedo than lowest canopy cover class, presenting a difference of −11.2% in mean annual albedo values. It was also showed that MT_4 and MT_3 are the cooler canopy cover classes, and MT_2 and MT_1 the warmer, where MT_1 class had a difference of 3.42 °C compared with MT_4 class. Overall, this research highlighted the role that potential changes in montado canopy cover may play in local land surface albedo and temperature variations, as an increase in these two biogeophysical parameters may potentially bring about, in the long term, local/regional climatic changes moving towards greater aridity.

Semi-automatic keyword based approach for FIRE 2016 Microblog Track

This paper describes our semi-automatic keyword based approach for the four topics of Information Extraction from Microblogs Posted during Disasters task at Forum for Information Retrieval Evaluation (FIRE) 2016. The approach consists three phases.

From Traditional Assessment to the New Competency-Based Assessment

The evaluation of school students has always attempted to estimate the effort, abilities and learning of students. However, at the beginning, evaluation consisted in measuring the progress of the student’s behavior compared to a desirable behavior. Later on, different changes in evaluation benefited the processes addressed to assessing the academic achievement of students and learning itself. Today, the demands of the contemporary society are vast and numerous: students not only require knowledge, they need to develop skills, values and postures. Postmodern education requires individuals to develop different talents and competencies to grow in every way. Therefore, evaluation should respond to such needs promoting an ethical, technical, reliable assessment of the student’s competencies, thus providing more fair and objective, qualitative and quantitative judgments. This dissertation project is the result of a literature review of several authors and the daily work of teachers in the Centros de Educación Media Superior a Distancia [High School Distance Centers] of Morelos, Mexico.

Detecting social patterns within 20th century documentary photos: a deep learning based approach

The job of a historian is to understand what happened in the past, resorting in many cases to written documents as a firsthand source of information. Text, however, does not amount to the only source of knowledge. Pictorial representations, in fact, have also accompanied the main events of the historical timeline. In particular, the opportunity of visually representing circumstances has bloomed since the invention of photography, with the possibility of capturing in real-time the occurrence of a specific events. Thanks to the widespread use of digital technologies (e.g. smartphones and digital cameras), networking capabilities and consequent availability of multimedia content, the academic and industrial research communities have developed artificial intelligence (AI) paradigms with the aim of inferring, transferring and creating new layers of information from images, videos, etc. Now, while AI communities are devoting much of their attention to analyze digital images, from an historical research standpoint more interesting results may be obtained analyzing analog images representing the pre-digital era. Within the aforementioned scenario, the aim of this work is to analyze a collection of analog documentary photographs, building upon state-of-the-art deep learning techniques. In particular, the analysis carried out in this thesis aims at producing two following results: (a) produce the date of an image, and, (b) recognizing its background socio-cultural context,as defined by a group of historical-sociological researchers. Given these premises, the contribution of this work amounts to: (i) the introduction of an historical dataset including images of “Family Album” among all the twentieth century, (ii) the introduction of a new classification task regarding the identification of the socio-cultural context of an image, (iii) the exploitation of different deep learning architectures to perform the image dating and the image socio-cultural context classification.

Spatial based approach to fisheries management. An application to bottom trawling in the strait of Sicily

At the beginning of my thesis project, considering that some stocks are in overfishing status due to both high fishing effort and high level of juveniles in the catch, my main purpose was to understand how to contribute to improving the state of the fishery resources of the Mediterranean Sea. To mitigate the overfishing, the General Fisheries Commission for the Mediterranean (GFCM) adopted several Fishery Restricted Areas, which are geographically defined areas where some specific fishing activities are temporarily or permanently banned or restricted in order to reduce the exploitation patterns and conservation of specific stocks as well as of habitats and deep-sea ecosystems, including the Essential Fish Habitats (EFH) and the Vulnerable Marine Ecosystems (VME). Considering that GFCM established 3 Fisheries Restricted Areas (FRAs) in the Strait of Sicily (SoS) in 2016 aimed at protecting the nursery areas of the deep-water rose shrimp (DPS, Parapenaeus longirostris – Lucas, 1846) and the European hake (HKE, Merluccius merluccius – Linnaeus, 1758) to reduce the exploitation pattern of undersized species, in my thesis project I devoted myself to evaluate the effect of the FRAs on the status stock and the fishery performance using a spatial bio-economic model.

Computer vision in aseptic pharmaceutical manufacturing: a deep learning-based approach to vial inspection and pack formation during a lyophilizer loading cycle

Vision systems are powerful tools playing an increasingly important role in modern industry, to detect errors and maintain product standards. With the enlarged availability of affordable industrial cameras, computer vision algorithms have been increasingly applied in industrial manufacturing processes monitoring. Until a few years ago, industrial computer vision applications relied only on ad-hoc algorithms designed for the specific object and acquisition setup being monitored, with a strong focus on co-designing the acquisition and processing pipeline. Deep learning has overcome these limits providing greater flexibility and faster re-configuration. In this work, the process to be inspected consists in vials’ pack formation entering a freeze-dryer, which is a common scenario in pharmaceutical active ingredient packaging lines. To ensure that the machine produces proper packs, a vision system is installed at the entrance of the freeze-dryer to detect eventual anomalies with execution times compatible with the production specifications. Other constraints come from sterility and safety standards required in pharmaceutical manufacturing. This work presents an overview about the production line, with particular focus on the vision system designed, and about all trials conducted to obtain the final performance. Transfer learning, alleviating the requirement for a large number of training data, combined with data augmentation methods, consisting in the generation of synthetic images, were used to effectively increase the performances while reducing the cost of data acquisition and annotation. The proposed vision algorithm is composed by two main subtasks, designed respectively to vials counting and discrepancy detection. The first one was trained on more than 23k vials (about 300 images) and tested on 5k more (about 75 images), whereas 60 training images and 52 testing images were used for the second one.

A medical imaging-based approach for total shoulder replacement

Ogni anno in Italia, migliaia di protesi convenzionali vengono impiantate con successo in pazienti affetti da artrosi alla spalla, tuttavia è stato dimostrato che questa tipologia di protesi non funziona in quei pazienti che soffrono contemporaneamente anche di grandi lesioni alla cuffia dei rotatori, ricorrendo successivamente a un impianto di protesi di spalla inversa. La scelta sul miglior tipo di protesi da parte del chirurgo è quindi fondamentale e necessaria per evitare futuri stress e operazioni al paziente. Nel corso degli anni si è fatto affidamento a protocolli che non considerano in maniera specifica la componente tissutale ossea. In questa tesi si cerca di dimostrare che attraverso l’utilizzo delle immagini mediche è possibile ricavare dati e grafici specifici sulla componente ossea del paziente per ottimizzare poi la scelta della protesi da parte del chirurgo e la fase pre/intra operatoria.