Kajian keberkesanan olahan larut lesapan menggunakan elektrod aluminum dan ferum dalam sistem elektro-penggumpalan

Elektro-pengumpalan merupakan satu kaedah alternatif yang kompetatif selain daripada kaedah konvesional bagi merawat air sisa terutamanya larut lesapan yang mempunyai struktur bahan pencemar yang kompleks dan tinggi. Kajian keberkesanan elekto-penggumpalan telahpun dijalankan bagi menentukan keberkesanan sistem ini beroperasi. Objektif utama kajian ini adalah bagi mengkaji keberkesanan dan potensi sistem beroperasi dengan menggunakan empat jenis susunan elektrod, Fe-Fe, Al-Al, Fe dan aluminum sulfat di samping penentuan nilai optimum ketumpatan arus elektrik, jarak antara elektrod, masa tindakbalas, pH, masa enapan dan aluminum sulfat. Penggunaan CILAS Analyzer digunakan bagi menentukan saiz flok di setiap penentuan optimum yang diperolehi. Sebanyak 750 liter sampel larut lesapan diambil pada awal bulan Disember 2010 - Januari 2011. Pengujian awalan BOD, COD, pepejal terampai, nitrogen ammonia, warna dan kekeruhan turut diuji terhadap sampel mentah yang diperolehi. Reaktor kaca bersaiz 300mm x 80mm x 200mm (4 L sampel) dengan luas berkesan elektrod penggumpal, 60 sm + - + - -Al , Al -Fe 2 digunakan di samping ujian penyingkiran parameter seperti COD, pepejal terampai, nitrogen ammonia warna dan kekeruhan turut diuji di dalam kajian ini. Hasil keseluruhan kajian mendapati bahawa penggunaan elektrod Al-Al memberikan peratus penyingkiran tertinggi di mana penentuan optimum yang diperolehi bagi ketumpatan arus elektrik adalah 0.025 amp/sm , jarak antara elektrod, 10 cm, masa tindakbalas, 60 minit, pH 5 dan masa enapan, 30 minit. Peratus penyingkiran yang diperolehi bagi COD, pepejal terampai, nitrogen ammonia, warna dan kekeruhan adalah 82.5%, 94.7%, 65.6%, 91% and 90.6%. Percampuran aluminum sulfat terhadap penggunaan elektrod Al-Al memberikan dos optimum sebanyak 1500 mg/l di mana penyingkiran tertinggi yang diperolehi bagi COD, pepejal terampai, nitrogen ammonia, warna dan kekeruhan adalah 84.2%, 81%, 80.3%, 75% and 81.1%. Kesimpulanya, penggunaan elektrod Al-Al dicadangkan, di mana sedikit pra olahan perlu dilakukan bagi menepati piawaian yang dibenarkan oleh Standard Malaysia bagi tahap lepasan larut lesapan. Katakunci: air sisa domestik; Elektro-pengumpalan; larut lesapa

Adapting hybrid approaches for electronic medical record management and sharing using blockchain sharding

In the past few years, it is noticed that management and sharing medical records is a key step towards increasing healthcare provider connectivity and making the healthcare system more efficient. The scalability and sustainability issues confer to mismanagement of patient is record and also raised several issues in privacy and security. The study aims to suggest more efficient alternatives for Electronic Healthcare System. Scalability and privacy are the major limitations that existing systems contain so the goal of this study is to define alternatives about how parameters like scalability, usability and data protection could be achieved in an efficient manner for healthcare system. In the healthcare industry, providing accurate, thorough, and up-to-date information on patients is critical. Another feature that allows researchers to consider efficient EHR systems is rapid access to patient records for boosting efficiency and coordination. Blockchain sharding technique is utilized along with hyper-ledger protocols and Proof-of-Authority to carry out our model implementation

Redução do custo de manutenção e aumento da eficiência na secção de estampagem a quente

This work was developed as part of a curricular internship at Gestamp Aveiro, to reduce maintenance costs associated to the hot stamping production line. For the development of this report, an in-depth study of the entire production line was carried out (from the entry of raw material in the process to the exit of the final part), to identify the possible existing problems. These problems were related to early wear or repetitive equipment failures. The causes and consequences of these failures were investigated. The impact of each of the problems was studied to access which of those were to be worked on. The selected criteria were the percentage of the maintenance budget each represented. Research to implement new solutions and improvements carried out by the company were also analysed. The areas identified as most relevant were the wear of ceramic rollers in the kiln/furnace and its implications, the excessive wear of the blank referencing presses and the excessive contamination of the shop floor by metallic dust from the laser cutting process, with special impact on the laser tool head’s components. Then, a research was conducted to discover and propose improvements, to eliminate or minimize the problems identified and to implement those proposals. Criteria were sought for the evaluation of these proposals and the results were analysed. Due to external factors, not all proposals or solutions were applied. Therefore, a plan was developed for their implementation and subsequent analysis and evaluation of their results. Revisions to preventive maintenance plans were made and an internal procedure was developed as part of the improvement propositions. In conclusion, the main objectives of this work were achieved and considering all proposed solutions, significant costs reduction was achieved. Future research and work were proposed to proceed and improve some of the problems identified in this thesis.O presente trabalho foi desenvolvido no âmbito de um estágio curricular na Gestamp Aveiro, com o principal objetivo de reduzir os custos de manutenção associados à linha de produção de estampagem a quente. Para a execução deste relatório foi feito um estudo profundo de toda a linha (desde a entrada da matéria-prima no processo até ao término da peça final), com o objetivo de identificar o maior número possível de problemas existentes, relacionados com desgaste precoce ou falha repetitiva dos equipamentos. Investigaram-se as causas e consequências dessas falhas. De seguida, foi avaliado o impacto de cada um dos problemas identificados, sendo o critério a percentagem do orçamento de manutenção que representavam. Também foram analisadas tentativas de melhoria e outras investigações realizadas pela própria empresa. As áreas de atuação catalogadas como mais relevantes foram o desgaste dos rolos cerâmicos no forno e as suas implicações, o desgaste excessivo das prensas de referenciação dos formatos e a contaminação excessiva do chão de fábrica por pó metálico, proveniente do corte laser, com especial impacto no desgaste dos componentes da cabeça de corte laser. Após a análise e avaliação preliminar, foram propostas e implementadas melhorias para eliminar ou minimizar os problemas identificados. Procuraram-se critérios para avaliar estas propostas e analisaram-se os resultados obtidos. Devido a fatores externos, nem todas as propostas foram aplicadas, sendo que se concebeu um plano de implementação para posterior análise e avaliação dos seus resultados. Foram feitas propostas de revisão dos planos de manutenção preventiva e desenvolveu-se um procedimento interno, como parte das propostas de melhorias. Em conclusão, os objetivos principais propostos neste trabalho foram concluídos com sucesso, resultando poupanças significativas nos custos de operação da empresa. Foram identificados e propostos trabalhos futuros que procedem a este trabalho desenvolvido.Mestrado em Engenharia Mecânic

Multi Sensor Data Fusion Architectures for Air Traffic Control Applications

Nowadays, the radar is no longer the sole technology which is able to ensure the surveillance of air traffic. The extensive deployment of satellite systems and air-to-ground data links leads to the emergence of complementary means and techniques on which a great deal of research and experiments have been carried out over the past ten years. In such an environment, the sensor data processing, which is a key element in any Air Traffic Control (ATC) centre, has been continuously upgraded so as to follow the sensor technology evolution and in the meantime improves the quality in term of continuity, integrity and accuracy criteria. This book chapter proposes a comprehensive description of the state of art and the roadmap for the future of the multi sensor data fusion architectures and techniques in use in ATC centres. The first part of the chapter describes the background of ATC centres, while the second part of the chapter points out various data fusion techniques. Multi radar data processing architecture is analysed and a brief definition of internal core tracking algorithms is given as well as a comparative benchmark based on their respective advantages and drawbacks. The third part of the chapter focuses on the most recent evolution that leads from a Multi Radar Tracking System to a Multi Sensor Tracking System. The last part of the chapter deals with the sensor data processing that will be put in operation in the next ten years. The main challenge will be to provide the same level of services in both surface and air surveillance areas in order to offer: ⢠highly accurate air and surface situation awareness to air traffic controllers, ⢠situational awareness via Traffic Information System â Broadcast (TIS-B) services to pilots and vehicle drivers, and ⢠new air and surface safety, capacity and efficiency applications to airports and airlines

Industry/University Collaboration at the University of Michigan-Dearborn: A Focus on Relevant Technology

https://deepblue.lib.umich.edu/bitstream/2027.42/154105/1/kampfner1997.pd

Intelligent and predictive maintenance in manufacturing systems

In recent years manufacturing companies have been facing a major shift in the manufacturing requirements, for example the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production of standardized products. As a consequence of the change, the enterprises are facing the need to adapt, forcing all sectors of the manufacturing activity to move accordingly. Maintenance is one of the major activities in manufacturing as it highly influences production productivity and quality, and has a direct impact on production cost and customer satisfaction. Nowadays, corrective and scheduled maintenance are widely implemented. However, the manufacturing world need to adapt to this new reality by implementing new, intelligent and innovative maintenance systems capable of predicting in advance possible failures. Lately, predictive maintenance systems and tools have been developed and continue to be studied and improved. However, companies do not have enough trust on these systems to fully rely on them. Considering all these aspects, the work developed on this thesis introduces a system architecture for an intelligent predictive maintenance system based on the Condition-Based Maintenance (CBM) to be used in the Catraport case study, focusing particularly on the development of the monitoring module of the system architecture. This module comprises a tool developed by using Node-RED that displays the collected data alongside with the warnings triggered by cross-checking the incoming data with implemented decision rules, through the use of graphics and text. Additionally, an Android mobile application was also developed to allow consulting remotely the operating state of the assets.Nos últimos anos, as empresas de manufatura têm enfrentado uma grande mudança nos requisitos de fabrico, nomeadamente, na procura por produtos altamente personalizados, resultando num ciclo de vida do produto mais curto, contrariamente à tradicional produção em massa de produtos padronizados. Como consequência desta mudança, as empresas, bem como todos os setores da atividade de manufatura, enfrentam a necessidade de se adaptar. A manutenção é uma das principais atividades de fabrico, visto que influência fortemente a produtividade e a qualidade da produção, e tem um impacto direto no custo do produto e na satisfação do cliente. Atualmente, as estratégias de manutenção corretiva e programada são amplamente implementadas. No entanto, o mundo da manufatura precisa de se adaptar à nova realidade, implementando sistemas de manutenção novos, inteligentes e inovadores, capazes de prever possíveis falhas. Ultimamente, os sistemas e ferramentas de manutenção preditiva têm sido desenvolvidos e continuam a ser estudados e melhorados. No entanto, as empresas não possuem confiança suficiente nesses sistemas para os implementar nas suas instalações. Considerando todos esses aspetos, o trabalho desenvolvido nesta dissertação introduz uma arquitetura para um sistema inteligente de manutenção preditiva baseado na técnica Condition- Based Maintenance (CBM) a ser usado no estudo de caso da Catraport, focando-se particularmente no desenvolvimento do módulo de monitorização da arquitetura. Este módulo compreende uma ferramenta desenvolvida com recurso ao Node-RED que exibe os dados colecionados. Adicionalmente são apresentados avisos originados pelo cruzamento dos dados recebidos com as regras de decisão implementadas. Além disso, uma aplicação móvel Android também foi desenvolvida para permitir a consulta remota o estado operacional dos equipamentos

A New 76Ge Double Beta Decay Experiment at LNGS

This Letter of Intent has been submitted to the Scientific Committee of the INFN Laboratori Nazionali del Gran Sasso (LNGS) in March 2004. It describes a novel facility at the LNGS to study the double beta decay of 76Ge using an (optionally active) cryogenic fluid shield. The setup will allow to scrutinize with high significance on a short time scale the current evidence for neutrinoless double beta decay of 76Ge using the existing 76Ge diodes from the previous Heidelberg-Moscow and IGEX experiments. An increase in the lifetime limit can be achieved by adding more enriched detectors, remaining thereby background-free up to a few 100 kg-years of exposure.Comment: 67 pages, 19 eps figures, 17 tables, gzipped tar fil

The camera of the fifth H.E.S.S. telescope. Part I: System description

In July 2012, as the four ground-based gamma-ray telescopes of the H.E.S.S. (High Energy Stereoscopic System) array reached their tenth year of operation in Khomas Highlands, Namibia, a fifth telescope took its first data as part of the system. This new Cherenkov detector, comprising a 614.5 m^2 reflector with a highly pixelized camera in its focal plane, improves the sensitivity of the current array by a factor two and extends its energy domain down to a few tens of GeV. The present part I of the paper gives a detailed description of the fifth H.E.S.S. telescope's camera, presenting the details of both the hardware and the software, emphasizing the main improvements as compared to previous H.E.S.S. camera technology.Comment: 16 pages, 13 figures, accepted for publication in NIM

Diagnosis and Prognosis of Occupational disorders based on Machine Learn- ing Techniques applied to Occupational Profiles

Work-related disorders have a global influence on people’s well-being and quality of life and are a financial burden for organizations because they reduce productivity, increase absenteeism, and promote early retirement. Work-related musculoskeletal disorders, in particular, represent a significant fraction of the total in all occupational contexts. In automotive and industrial settings where workers are exposed to work-related muscu- loskeletal disorders risk factors, occupational physicians are responsible for monitoring workers’ health protection profiles. Occupational technicians report in the Occupational Health Protection Profiles database to understand which exposure to occupational work- related musculoskeletal disorder risk factors should be ensured for a given worker. Occu- pational Health Protection Profiles databases describe the occupational physician states, and which exposure the physicians considers necessary to ensure the worker’s health protection in terms of their functional work ability. The application of Human-Centered explainable artificial intelligence can support the decision making to go from worker’s Functional Work Ability to explanations by integrating explainability into medical (re- striction) and supporting in two decision contexts: prognosis and diagnosis of individual, work related and organizational risk condition. Although previous machine learning ap- proaches provided good predictions, their application in an actual occupational setting is limited because their predictions are difficult to interpret and hence, not actionable. In this thesis, injured body parts in which the ability changed in a worker’s functional work ability status are targeted. On the one hand, artificial intelligence algorithms can help technical teams, occupational physicians, and ergonomists determine a worker’s workplace risk via the diagnosis and prognosis of body part(s) injuries; on the other hand, these approaches can help prevent work-related musculoskeletal disorders by identifying which processes are lacking in working condition improvement and which workplaces have a better match between the remaining functional work abilities. A sample of 2025 for the prognosis part (from the years of 2019 to 2020) and 7857 for the prognosis part of Occupational Health Protection Profiles based on Functional Work Ability textual re- ports in the Portuguese language in automotive industry factory. Machine learning-based Natural Language Processing methods were implemented to extract standardized infor- mation. The prognosis and diagnosis of Occupational Health Protection Profiles factors were developed in reliable Human-Centered explainable artificial intelligence system to promote a trustworthy Human-Centered explainable artificial intelligence system (enti- tled Industrial microErgo application). The most suitable regression models to predict the next medical appointment for the injured body regions were the models based on CatBoost regression, with R square and an RMSLE of 0.84 and 1.23 weeks, respectively. In parallel, CatBoost’s best regression model for most body parts is the prediction of the next injured body parts based on these two errors. This information can help tech- nical industrial teams understand potential risk factors for Occupational Health Protec- tion Profiles and identify warning signs of the early stages of musculoskeletal disorders.Os transtornos relacionados ao trabalho têm influência global no bem-estar e na quali- dade de vida das pessoas e são um ônus financeiro para as organizações, pois reduzem a produtividade, aumentam o absenteísmo e promovem a aposentadoria precoce. Os distúr- bios osteomusculares relacionados ao trabalho, em particular, representam uma fração significativa do total em todos os contextos ocupacionais. Em ambientes automotivos e industriais onde os trabalhadores estão expostos a fatores de risco de distúrbios osteomus- culares relacionados ao trabalho, os médicos do trabalho são responsáveis por monitorar os perfis de proteção à saúde dos trabalhadores. Os técnicos do trabalho reportam-se à base de dados dos Perfis de Proteção da Saúde Ocupacional para compreender quais os fatores de risco de exposição a perturbações músculo-esqueléticas relacionadas com o tra- balho que devem ser assegurados para um determinado trabalhador. As bases de dados de Perfis de Proteção à Saúde Ocupacional descrevem os estados do médico do trabalho e quais exposições os médicos consideram necessária para garantir a proteção da saúde do trabalhador em termos de sua capacidade funcional para o trabalho. A aplicação da inteligência artificial explicável centrada no ser humano pode apoiar a tomada de decisão para ir da capacidade funcional de trabalho do trabalhador às explicações, integrando a explicabilidade à médica (restrição) e apoiando em dois contextos de decisão: prognóstico e diagnóstico da condição de risco individual, relacionado ao trabalho e organizacional . Embora as abordagens anteriores de aprendizado de máquina tenham fornecido boas pre- visões, sua aplicação em um ambiente ocupacional real é limitada porque suas previsões são difíceis de interpretar e portanto, não acionável. Nesta tese, as partes do corpo lesiona- das nas quais a habilidade mudou no estado de capacidade funcional para o trabalho do trabalhador são visadas. Por um lado, os algoritmos de inteligência artificial podem aju- dar as equipes técnicas, médicos do trabalho e ergonomistas a determinar o risco no local de trabalho de um trabalhador por meio do diagnóstico e prognóstico de lesões em partes do corpo; por outro lado, essas abordagens podem ajudar a prevenir distúrbios muscu- loesqueléticos relacionados ao trabalho, identificando quais processos estão faltando na melhoria das condições de trabalho e quais locais de trabalho têm uma melhor correspon- dência entre as habilidades funcionais restantes do trabalho. Para esta tese, foi utilizada uma base de dados com Perfis de Proteção à Saúde Ocupacional, que se baseiam em relató- rios textuais de Aptidão para o Trabalho em língua portuguesa, de uma fábrica da indús- tria automóvel (Auto Europa). Uma amostra de 2025 ficheiros foi utilizada para a parte de prognóstico (de 2019 a 2020) e uma amostra de 7857 ficheiros foi utilizada para a parte de diagnóstico. . Aprendizado de máquina- métodos baseados em Processamento de Lingua- gem Natural foram implementados para extrair informações padronizadas. O prognóstico e diagnóstico dos fatores de Perfis de Proteção à Saúde Ocupacional foram desenvolvidos em um sistema confiável de inteligência artificial explicável centrado no ser humano (inti- tulado Industrial microErgo application). Os modelos de regressão mais adequados para prever a próxima consulta médica para as regiões do corpo lesionadas foram os modelos baseados na regressão CatBoost, com R quadrado e RMSLE de 0,84 e 1,23 semanas, res- pectivamente. Em paralelo, a previsão das próximas partes do corpo lesionadas com base nesses dois erros relatados pelo CatBoost como o melhor modelo de regressão para a mai- oria das partes do corpo. Essas informações podem ajudar as equipes técnicas industriais a entender os possíveis fatores de risco para os Perfis de Proteção à Saúde Ocupacio- nal e identificar sinais de alerta dos estágios iniciais de distúrbios musculoesqueléticos