Tópicos Sugeridos dentro de su búsqueda.
Tópicos Sugeridos dentro de su búsqueda.
Buscar alternativas:
identification process » identification processes (Expander búsqueda), certification process (Expander búsqueda), identification systems (Expander búsqueda)
data identification » party identification (Expander búsqueda), datos identificacion (Expander búsqueda), latex identification (Expander búsqueda)
identification process » identification processes (Expander búsqueda), certification process (Expander búsqueda), identification systems (Expander búsqueda)
data identification » party identification (Expander búsqueda), datos identificacion (Expander búsqueda), latex identification (Expander búsqueda)
1
objeto de conferencia
Language identification is an elemental task in natural language processing, where corpus-based methods reign the state-of-the-art results in multi-lingual setups. However, there is a need to extend this application to other scenarios with scarce data and multiple classes to face, analyzing which of the most well-known methods is the best fit. In this way, Peru offers a great challenge as a multi-cultural and linguistic country. Therefore, this study focuses in three steps: (1) to build from scratch a digital annotated corpus for 49 Peruvian indigenous languages and dialects, (2) to fit both standard and deep learning approaches for language identification, and (3) to statistically compare the results obtained. The standard model outperforms the deep learning one as it was expected, with 95.9% in average precision, and both corpus and model will be advantageous inputs for more complex ta...
2
artículo
Publicado 2022
Enlace
Enlace
This article presents a proposal for the interpretation and organization of the phonetic characteristics of indubitable and dubitative samples using SplitsTree4 software, with the purpose of clarifying an alleged crime of bribery in the exercise of police functions to the detriment of the State. The dubitted samples were provided by the Public Prosecutor's Office and the indubitable samples were obtained by means of voice sampling; likewise, data anonymity was chosen. First, the relevant phonetic features of the samples were categorized; then, they were assigned a binary value of existence and non-existence; then, the binary information was processed by SplitsTree4 software to regroup the features according to the universe of speakers and show the compatibility between the indicated samples. Finally, the results indicate that the SplitsTree4 software complies with the ordering of phoneti...
3
artículo
Publicado 2024
Enlace
Enlace
Spectral signatures are graphical representations that relate the electromagnetic spectrum to the wave response or amplitude, resulting from the interaction of objects and light. Each soil cover, due to the different composition of materials, generates a particular spectral response. Therefore, the automated classification of coverages, whether object-oriented or pixel-oriented, is based on the spectral response of the different segments or pixels, respectively. Spectral libraries are databases where these spectral responses are stored so that researchers or organizations involved in the collection, processing and analysis of these samples can work collaboratively, avoiding redundancy in the investigations and optimizing time in the development of the same. However, there is currently no defined metadata model to ensure interoperability between researchers or organisations that generate...
4
tesis doctoral
Publicado 2022
Enlace
Enlace
Se obtuvieron diecinueve VHHs (dominios variables únicos de los anticuerpos de cadena pesada) que unen a CD105 (endoglina) humano, un co-receptor endotelial de TFG-β implicado en la regulación de la angiogénesis y el desarrollo de tumores, mediante screening por phage display de una biblioteca de ADNc de VHH obtenida de alpacas inmunizadas con un lisado de una línea celular de cáncer de vejiga que sobreexpresa CD105 (T24). Las secuencias de los VHH se analizaron con ExPASY, GeneDoc y BLAST y mostraron las características estructurales típicas de los VHHs. Ellas se clonaron y expresaron en pET22b(+)/E.coli y los VHHs recombinantes se purificaron por cromatografía de afinidad. Trece VHHs anti-CD105 fueron microarreglados en biochips para determinar la especificidad y afinidad a CD105 unido a membrana celular por SPRi, Los datos de SPRi mostraron que los VHHs unen a las células SC...
5
artículo
Publicado 2012
Enlace
Enlace
It is about a process to identify the gender violence of girls/boys victims and the treatment guidelines as a theoretical view that examine the problem from conscious and unconscious aspects; there are two clinical examples and that are showed in recent researches that the matter gives us relevant data. The objectives are centered in to know the preventive aspects and the most effective intervention to contributethrough the diffusion of that knowledge and the healthy development of gender violence in minor victims.
6
artículo
Publicado 2012
Enlace
Enlace
It is about a process to identify the gender violence of girls/boys victims and the treatment guidelines as a theoretical view that examine the problem from conscious and unconscious aspects; there are two clinical examples and that are showed in recent researches that the matter gives us relevant data. The objectives are centered in to know the preventive aspects and the most effective intervention to contributethrough the diffusion of that knowledge and the healthy development of gender violence in minor victims.
7
artículo
The promotion of organic and ecological production seeks the sustainable and competitive growth of organic crops in countries like Peru. In this context, agro-exportation is characterized by-products such as fruit and vegetables where they need to comply with organic certification regulations to enter products into countries like the US, where it is necessary to certify that weed control is carried out using biodegradable materials, flames, heat, media electric or manual weeding, this being a problem for some productive organizations. The problem is related to the need to differentiate between the crop and the weed as described above, by having image recognition technology tools with Deep Learning. Therefore, the objective of this article is to demonstrate how an artificial intelligence model based on computer vision can contribute to the identification of weeds in basil plots. An iterat...
8
artículo
Publicado 2017
Enlace
Enlace
Advance spaceborne thermal emission and reflection radiometer (aster) is the first sensor with multi band observation in thermal infrared region (8-12 micrometers) with 90 meters of spatial resolution and 5 spectral bands specially designed to discriminate rocks from earth crust. Different process were applied in order to discriminate alteration minerals and rock groups by using not only the thermal infrared band but also the visible and near infrared bands.The area of study is located is situated in the Department of Cuzco in the southern portion of the Peru Tertiary Volcanic Belt and located 170 kilometres northwest of Arequipa. The area lies within the Peruvian altiplano at an altitude of 4,470 to 5,370 metres. The availability of multispectral data from the satellite- borne ASTER (advance Spaceborne Thermal emission Reflection Radiometer) instrument has provided and increased potenti...
9
artículo
Publicado 2019
Enlace
Enlace
This pest identification project using remote sensing with an unmanned aerial vehicle will show the scope that can be achieved in the field of agriculture and that are being used. The project has as its first stage the custom conditioning of the unmanned aerial vehicle composed of a flight structure and a camera system which will allow us to acquire data, in this case aerial images. Once the air vehicle is conditioned, the flight plans for the acquisition of images are established. This stage is delimited by the olive cultivation area that we want to evaluate. Once the conditioning has been completed and after executing the flight plans, the images are processed under two algorithm models, the results of which will eventually be interpreted in search of the identification of pests in the cultivation of the olive tree.
10
artículo
Publicado 2007
Enlace
Enlace
The objective of this work is the re-identification of the process model that is used in existing predictive controllers (MPC) using closed-loop operation data. The controller is assumed to have a two-layer structure, where in the upper layer a simple economic optimization algorithm determines a set of optimal steady-state values ("targets"), which are passed to the MPC for implementation. This is the case for several commercial MPC packages applied in the industry. This paper focuses on the case where the model represents significant benefits in the MPC re-commissioning procedure. A new methodology is proposed to excite the system in closed loop, introducing persistent excitation signals in the objective function of the upper layer of the MPC. This strategy allows the continuous operation of the system, respecting the constraints of the process and meeting the specifications of th...
11
artículo
Nowadays, an engineer’s work consists more and more of obtaining mathematical models of the studied processes. Great part of the literature referring to system identification deals with how to find polynomial models as Prediction Error Methods (PEM) and Instrumental Variable Methods (IVM). In case of complex systems, the state space model appears as an alternative to PEM and IVM models. For multivariable systems, these methods provide reliable state space models directly from input and output data. As systems of large dimensions are usually found in industry, the application of subspace identification algorithms in this field is very promising. Currently the subspaceidentification models Multivariable Output Error State sPace (MOESP) and Numerical algorithms for Subspace State Space System IDentification (N4SID), are topic of study. The objective of this work is to implement th...
12
artículo
Nowadays, an engineer’s work consists more and more of obtaining mathematical models of the studied processes. Great part of the literature referring to system identification deals with how to find polynomial models as Prediction Error Methods (PEM) and Instrumental Variable Methods (IVM). In case of complex systems, the state space model appears as an alternative to PEM and IVM models. For multivariable systems, these methods provide reliable state space models directly from input and output data. As systems of large dimensions are usually found in industry, the application of subspace identification algorithms in this field is very promising. Currently the subspaceidentification models Multivariable Output Error State sPace (MOESP) and Numerical algorithms for Subspace State Space System IDentification (N4SID), are topic of study. The objective of this work is to implement th...
13
artículo
Publicado 2011
Enlace
Enlace
In this article, a method is presented based on artificial intelligence to control a plant DC motor for a personal microcomputer (PC), that interacted hardware and software achieves the control of the speed of the DC motor in real time using the control algorithm Fuzzy-PD+I. The acquisition of data and identification of the parameters of the DC motor have been necessary for the control of the speed of the motor DC, by means of the card of acquisition of data PCI NIDAQ 6024E whose interface runs in the real time that the Workshop Real-Time uses (RTW), the file of data is processed with the tool of identification of the program called IDENT of Matlab. The prototype of the system computer-controller is designed using the graphic programming of LabVIEW, in this case use of the tools Fuzzy Logic Control and Simulation Module. The control in real time of the system is carried out in the labora...
14
artículo
Publicado 2022
Enlace
Enlace
so, machine learning techniques are being developed to improve performance and maintenance prediction. Increasing our knowledge of the relationship between humans and algorithms, Because data is so valuable, improving strategies for intelligently having to manage the now-ubiquitous content infrastructures is a necessary part of the process toward completely autonomous agents. Numerous researchers recently developed numerous computer-aided diagnostic algorithms employing various supervised learning approaches. Early identification of sickness may help to reduce the number of people who die as a result of these illnesses. Using machine learning techniques, this research creates an efficient automated illness diagnostic algorithm. We chose three key disorders in this paper: coronavirus, cardiovascular diseases, and diabetes. The data are inputted into a mobile application in the suggested m...
15
artículo
Publicado 2020
Enlace
Enlace
El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
16
artículo
“The identification, classification and treatment of crop plant diseases are essential for agricultural production. Some of the most common diseases include root rot, powdery mildew, mosaic, leaf spot and fruit rot. Machine learning (ML) technology and convolutional neural networks (CNN) have proven to be very useful in this field. This work aims to identify and classify diseases in crop plants, from the data set obtained from Plant Village, with images of diseased plant leaves and their corresponding Tags, using CNN with transfer learning. For processing, the dataset composing of more than 87 thousand images, divided into 38 classes and 26 disease types, was used. Three CNN models (DenseNet-201, ResNet-50 and Inception-v3) were used to identify and classify the images. The results showed that the DenseNet-201 and Inception-v3 models achieved an accuracy of 98% in plant disease identif...
17
artículo
“The identification, classification and treatment of crop plant diseases are essential for agricultural production. Some of the most common diseases include root rot, powdery mildew, mosaic, leaf spot and fruit rot. Machine learning (ML) technology and convolutional neural networks (CNN) have proven to be very useful in this field. This work aims to identify and classify diseases in crop plants, from the data set obtained from Plant Village, with images of diseased plant leaves and their corresponding Tags, using CNN with transfer learning. For processing, the dataset composing of more than 87 thousand images, divided into 38 classes and 26 disease types, was used. Three CNN models (DenseNet-201, ResNet-50 and Inception-v3) were used to identify and classify the images. The results showed that the DenseNet-201 and Inception-v3 models achieved an accuracy of 98% in plant disease identif...
18
artículo
The identification, classification and treatment of crop plant diseases are essential for agricultural production. Some of the most common diseases include root rot, powdery mildew, mosaic, leaf spot and fruit rot. Machine learning (ML) technology and convolutional neural networks (CNN) have proven to be very useful in this field. This work aims to identify and classify diseases in crop plants, from the data set obtained from Plant Village, with images of diseased plant leaves and their corresponding Tags, using CNN with transfer learning. For processing, the dataset composing of more than 87 thousand images, divided into 38 classes and 26 disease types, was used. Three CNN models (DenseNet-201, ResNet-50 and Inception-v3) were used to identify and classify the images. The results showed that the DenseNet-201 and Inception-v3 models achieved an accuracy of 98% in plant disease identifica...
19
artículo
This article proposes a system that allows monitoring car accidents with the use of NFC technology. The solution is comprised of low-cost Radio Frequency Identification (RFID) tools integrated into a mobile and web application that interact with the Google Maps API for efficient monitoring. The car accident reporting process collects and sends data manually through different service channels, which generates delays and, in some cases, the receipt of erroneous data. The proposed solution automates the accident reporting process by storing data from the users involved in the RFID tags and displaying them in the mobile and web applications, when generating a new report. Also, our application interacts with the Google Maps API to show the exact location from where accidents are reported, in order to speed up the process of attention by the PNP. The validation was carried out in the city of L...
20
artículo
Efficient Search Method to Solve the Fingerprint Identification Problem by Applying Machine Learning
Publicado 2022
Enlace
Enlace
In biometrics technology, the fingerprint identification problem has been widely studied over the last decades due to its applicability in person identification cases. In casualty cases, recognition of the victim is required, which should be done unequivocally using fingerprint identification. The aim of this research is to innovate the fingerprint identification process, developing an efficient search method in a large database that allows finding a fingerprint in less time by classifying fingerprints into segments, according to their closest characteristics, using machine learning. Then, in a given segment, a discrete linear search algorithm is applied, with which the required fingerprint is located.
