If you conduct a scientific experiment or undertake a piece of research, you’ll usually need to write up a corresponding project or lab report, to summarize the objective of your task, the methods you followed, the results you obtained, and the conclusions you drew from your work. Here we provide a sample of great templates for producing such reports, which include layout guidelines to help guide you through the process.
Energy consumption is one of the most critical issues in the manufacturing
industry. The modeling, analysis and improvement of energy cost and consumption in multistage production system have been widely studied in many research
works. To summarize the latest development of research of energy consumption, a large amount of research work have been investigated. The review work
includes effect of design for the energy consumption and interactions between
many aspects related to industry. This research research combines energy systems from microscopic to macroscopic, which includes machine, manufacturing
line and factory level. This document begins with a review of energy consumption on machine level. Including the schema for machine states and transition of
energy, the process model for energy analysis and improvement methods. These
topics are further discussed in detail for different processes, eg. forming process, additive processes, etc. In the next part of the review the researches on
energy consumption for the multi-machine/manufacturing line level are introduced. Include the define of manufacturing line level, the logical benchmarking
of manufacturing lines, and the utilization of energy flows. At last, the detailed
way for the factory level energy management are studied. Including the factory
energy management system and the method of reduce energy consumption.
Mobile ad-hoc network (MANET) is a collection of mobile
terminals forming an infrastructure less and quick deployable network,
which can communicate to each other via multiple hops or single hop.
Such ad-hoc networks have always been important for various applications like defence applications especially for countries like India having
boundaries and regions with large geographical diversity. Mobility attribute is a notable one in MANETs, as this leads to frequent topology
changes which are the primary cause of route failure. A route is an ordered set of links, hence for predicting future availability of any particular
route, it is important to estimate the availability of its currently available constituent links. This paper explores various link availability prediction model and proposes a least square polynomial regression-based
statistical approach to predict the availability of link. Proposed approach
assumes that movement of nodes are based on column mobility model i.e
each node in the network is linearly moving with constant speed. Each
node in the network periodically broadcasts hello packets to its neighbours to inform it’s availability in the network. Neighbour node receives
hello packet and uses its signal strength to estimate distance between
sender and receiver of hello packet. A monotonically decreasing signal
strength of hello packets at receiver node indicates that nodes are moving away from each other and link between them may break in future so
it starts link residual time prediction algorithm to predict the time when
the distance between them will exceed the pre-defined threshold value.
The proposed algorithm is simulated using NS 2.35. The performance
of the algorithm has been analyzed for identified parameters. The results are also been compared by simulating other existing link prediction
approaches based on interpolation.
We compare major factor models and find that the Stambaugh and Yuan (2016) four-factor model is the overall winner in the time-series domain. The Hou, Xue, and Zhang (2015) q-factor model takes second place and the Fama and French (2015) five-factor model and the Barillas and Shanken (2018) six-factor model jointly take third place. But the pairwise cross-sectional R2 and the multiple model comparison tests show that the Hou, Xue, and Zhang (2015) q-factor model, the Fama and French (2015) five-factor and four-factor models, and the Barillas and Shanken (2018) six-factor model take equal first place in the horse race.
Com a evolução constante da eletrônica, a necessidade de produzir protótipos em placa de circuito impresso é cada vez mais
cobrada e importante para se elaborar tecnologia de forma rápida, mas sem deixar a qualidade de produção baixa. Pensando
nisso, este artigo propõe o desenvolvimento de uma fresadora CNC com base no comando numérico computadorizado para a
confecção de trilhas na placa de circuito impresso de forma otimizada. Deste modo, são mostrados passo a passo os pilares
teóricos que compõem a base de conhecimento para que se possa entender e desenvolver a ferramenta que irá usinar e por
sua vez produzir o protótipo de forma eficaz. Os resultados obtidos em relação à montagem da ferramenta e o material
usinado foi classificado com satisfatório, já que a máquina CNC conseguiu atingir seus objetivos, perfurando, cortando a
placa e isolando as trilhas formando assim o circuito.
José Gleury Galvino Pereira e Adriana Maria Rebouças do Nascimento
Gesture controlled robot is a robot which can be controlled by simple gesture. The
user just needs to wear a gesture device which include a sensor. The sensor will record
the movement of hand in a specific direction which will result in the movement of the
robot in the respective direction. The robot and the gesture device are connected
wirelessly via radio waves. The wireless communication enables the user to interact
with the robot in a more friendly way.
In the last few years the resolution of NLP tasks with architectures composed of neural models has taken vogue. There are many advantages to using these approaches especially because there is no need to do features engineering. In this paper, we make a survey of a Deep Learning architecture that propose a resolutive approach to some classical tasks of the NLP. The Deep Learning architecture is based on a cutting-edge model that exploits both word-level and character-level representations through the combination of bidirectional LSTM, CNN and CRF. This architecture has provided cutting-edge performance in several sequential labeling activities for the English language. The architecture that will be treated uses the same approach for the Italian language. The same guideline is extended to perform a multi-task learning involving PoS labeling and sentiment analysis. The results show that the system performs well and achieves good results in all activities. In some cases it exceeds the best systems previously developed for Italian.
O conceito de automação residencial é definido como o conjunto de serviços proporcionados por sistemas tecnológicos
integrados, sendo a melhor maneira de satisfazer as necessidades básicas de segurança, comunicação, gestão energética
e conforto de uma habitação. Seguindo essa concepção, surgiu-se a ideia da criação de um Kit automatizado para
janelas utilizando a plataforma Arduíno, visando a solução de problemas do dia a dia como o transtorno causado pela
chuva e principalmente, gerando praticidade e comodidade para os cidadãos.