pathetic wet man

truly truly truly love this part near the end of m:pn asndkjflsankf

An Analyses of the Effects of An Absence of Governance & Community Solutions in Combating Environmental Degradation - Òlúségùn Èhínfún (MBA, PhD. Candidate), Paul R. Sachs (MBA, PhD.)

Abstract Effective environmental management requires a coordinated effort between corporations, national stakeholders, and local communities. Such coordination can consider the different information that each party brings, structured in a manner that facilitates clear and complete communication. Using the examples of the Lake Chad and Niger Delta areas, this “model” of coordination is discussed.…

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Hey. Why'd you tag that sex post madcom

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Korenna had covered about a third of the debris field when her communicator rang. She pressed the button on her arm and an image of a sanfy-haired man appeared in the corner of her vision.

He gave her a little wave. "Hey! How's my favorite space captain doing?"

"Cone on, Louis," she chuckled. "I'm flying a glorified escape pod, that hardly makes me a captain."

"It flies and you're in charge of it, that makes you a captain in my book."

"So I suppose that makes you a hardened space criminal, then?"

"Fair enough!"

Korenna pushed off a chunk of hull, floating over towards a promising cluster of rubble. "So, did you have a reason for calling, or did you just get bored?"

"Nothing specific, just wanted to check in on you. Can get pretty lonely out there on your own."

Korenna fired her boosters, slowing herself down enough to catch one of the pieces of debris. "Appreciate it, but I'm doing a-okay. Feels nice, actually getting to do something instead of listening to Halon drone on all day." She examined the piece of metal she was clingning to. It looked like this may have been part of Venture's drive core- not what she was looking for, but might fetch a little something from the right buyer. She tagged it for pickup and moved on to the next cluster.

"Alright, as long as you're sure." A crashing noise came from off camera and Louis glaned to the side for a moment. "What did they get into this time? I swear, you leave that kid alone for five seconds... Looks like I gotta get going. Don't do anything too crazy now, Gorst and I made a bet whether you'd make it back in one piece, and I could really use the extra credits."

"Glad to see your heart's in the right place. Catch you later!"

Louis gave another little wave as his image blipped out. Korenna smiled. She'd head back before too much longer. Just a few more minutes of searching- the data had to be around here somewhere.

Bồn cầu két liền Sanfi S303

Thông tin chi tiết sản phẩm Bệt két liền Sanfi S303 : 

Mã sản phẩm:  S303 Kích thước (cm):  như bản vẽ Hệ thống xả :  Xả Siphon Jet 3L/6L Loại men:  Men Nano Titan chống bám dính, kháng khuẩn Màu sắc : Trắng Tính năng : 2 chế độ xả nhấn, nắp rơi êm. Công nghệ xả đẩy - hút: Xả nhanh, mạnh và không gây tiếng ồn. Bảo hành : phần sứ 20 năm, phụ kiện 3 năm. Read the full article

If you did not already know

EnsembleNet Ensembling is a universally useful approach to boost the performance of machine learning models. However, individual models in an ensemble are typically trained independently in separate stages, without information access about the overall ensemble. In this paper, model ensembles are treated as first-class citizens, and their performance is optimized end-to-end with parameter sharing and a novel loss structure that improves generalization. On large-scale datasets including ImageNet, Youtube-8M, and Kinetics, we demonstrate a procedure that starts from a strongly performing single deep neural network, and constructs an EnsembleNet that has both a smaller size and better performance. Moreover, an EnsembleNet can be trained in one stage just like a single model without manual intervention. … COMpact Image Captioning (COMIC) Recent works in image captioning have shown very promising raw performance. However, we realize that most of these encoder-decoder style networks with attention do not scale naturally to large vocabulary size, making them difficult to be deployed on embedded system with limited hardware resources. This is because the size of word and output embedding matrices grow proportionally with the size of vocabulary, adversely affecting the compactness of these networks. To address this limitation, this paper introduces a brand new idea in the domain of image captioning. That is, we tackle the problem of compactness of image captioning models which is hitherto unexplored. We showed that, our proposed model, named COMIC for COMpact Image Captioning, achieves comparable results in five common evaluation metrics with state-of-the-art approaches on both MS-COCO and InstaPIC-1.1M datasets despite having an embedding vocabulary size that is 39x – 99x smaller. … Self-Adaptive Neuro-Fuzzy Inference System (SANFIS) This paper presents a self-adaptive neuro-fuzzy inference system (SANFIS) that is capable of self-adapting and self-organizing its internal structure to acquire a parsimonious rule-base for interpreting the embedded knowledge of a system from the given training data set. A connectionist topology of fuzzy basis functions with their universal approximation capability is served as a fundamental SANFIS architecture that provides an elasticity to be extended to all existing fuzzy models whose consequent could be fuzzy term sets, fuzzy singletons, or functions of linear combination of input variables. Without a priori knowledge of the distribution of the training data set, a novel mapping-constrained agglomerative clustering algorithm is devised to reveal the true cluster configuration in a single pass for an initial SANFIS construction, estimating the location and variance of each cluster. Subsequently, a fast recursive linear/nonlinear least-squares algorithm is performed to further accelerate the learning convergence and improve the system performance. Good generalization capability, fast learning convergence and compact comprehensible knowledge representation summarize the strength of SANFIS. Computer simulations for the Iris, Wisconsin breast cancer, and wine classifications show that SANFIS achieves significant improvements in terms of learning convergence, higher accuracy in recognition, and a parsimonious architecture. … Statistical Matching Problem The statistical matching problem is a data integration problem with structured missing data. The general form involves the analysis of multiple datasets that only have a strict subset of variables jointly observed across all datasets. The simplest version involves two datasets, labelled A and B, with three variables of interest $X, Y$ and $Z$. Variables $X$ and $Y$ are observed in dataset A and variables $X$ and $Z$ are observed in dataset $B$. Statistical inference is complicated by the absence of joint $(Y, Z)$ observations. Parametric modelling can be challenging due to identifiability issues and the difficulty of parameter estimation. … https://analytixon.com/2022/10/02/if-you-did-not-already-know-1843/?utm_source=dlvr.it&utm_medium=tumblr

If you did not already know

EnsembleNet Ensembling is a universally useful approach to boost the performance of machine learning models. However, individual models in an ensemble are typically trained independently in separate stages, without information access about the overall ensemble. In this paper, model ensembles are treated as first-class citizens, and their performance is optimized end-to-end with parameter sharing and a novel loss structure that improves generalization. On large-scale datasets including ImageNet, Youtube-8M, and Kinetics, we demonstrate a procedure that starts from a strongly performing single deep neural network, and constructs an EnsembleNet that has both a smaller size and better performance. Moreover, an EnsembleNet can be trained in one stage just like a single model without manual intervention. … COMpact Image Captioning (COMIC) Recent works in image captioning have shown very promising raw performance. However, we realize that most of these encoder-decoder style networks with attention do not scale naturally to large vocabulary size, making them difficult to be deployed on embedded system with limited hardware resources. This is because the size of word and output embedding matrices grow proportionally with the size of vocabulary, adversely affecting the compactness of these networks. To address this limitation, this paper introduces a brand new idea in the domain of image captioning. That is, we tackle the problem of compactness of image captioning models which is hitherto unexplored. We showed that, our proposed model, named COMIC for COMpact Image Captioning, achieves comparable results in five common evaluation metrics with state-of-the-art approaches on both MS-COCO and InstaPIC-1.1M datasets despite having an embedding vocabulary size that is 39x – 99x smaller. … Self-Adaptive Neuro-Fuzzy Inference System (SANFIS) This paper presents a self-adaptive neuro-fuzzy inference system (SANFIS) that is capable of self-adapting and self-organizing its internal structure to acquire a parsimonious rule-base for interpreting the embedded knowledge of a system from the given training data set. A connectionist topology of fuzzy basis functions with their universal approximation capability is served as a fundamental SANFIS architecture that provides an elasticity to be extended to all existing fuzzy models whose consequent could be fuzzy term sets, fuzzy singletons, or functions of linear combination of input variables. Without a priori knowledge of the distribution of the training data set, a novel mapping-constrained agglomerative clustering algorithm is devised to reveal the true cluster configuration in a single pass for an initial SANFIS construction, estimating the location and variance of each cluster. Subsequently, a fast recursive linear/nonlinear least-squares algorithm is performed to further accelerate the learning convergence and improve the system performance. Good generalization capability, fast learning convergence and compact comprehensible knowledge representation summarize the strength of SANFIS. Computer simulations for the Iris, Wisconsin breast cancer, and wine classifications show that SANFIS achieves significant improvements in terms of learning convergence, higher accuracy in recognition, and a parsimonious architecture. … Statistical Matching Problem The statistical matching problem is a data integration problem with structured missing data. The general form involves the analysis of multiple datasets that only have a strict subset of variables jointly observed across all datasets. The simplest version involves two datasets, labelled A and B, with three variables of interest $X, Y$ and $Z$. Variables $X$ and $Y$ are observed in dataset A and variables $X$ and $Z$ are observed in dataset $B$. Statistical inference is complicated by the absence of joint $(Y, Z)$ observations. Parametric modelling can be challenging due to identifiability issues and the difficulty of parameter estimation. … https://analytixon.com/2022/10/02/if-you-did-not-already-know-1843/?utm_source=dlvr.it&utm_medium=tumblr

Becas para cursar el Máster en Banca y Mercados Financieros de la Fundación UCEIF 2022

Se ofrecen un total de 8 (OCHO) becas para la realización de estudios propios del Máster en Banca y Mercados Financieros, distribuidas en 3 convocatorias:

Convocatoria 1: Becas Santander Financial Institute (SANFI) Máster en Banca y Mercados Financieros México Plazo de solicitud: hasta el 20 de septiembre de 2022. Nº de Plazas convocadas: 2 becas para el Máster impartido en la Universidad Anáhuac (México) Dirigido a: solicitantes procedentes de universidades asociadas a la AUIP.

Convocatoria 2: Becas Santander Financial Institute (SANFI) Máster en Banca y Mercados Financieros España Plazo de solicitud: hasta el 1 de junio de 2022. Nº de Plazas convocadas: 2 becas para el máster impartido en la Universidad de Cantabria (España) Dirigido a: solicitantes latinoamericanos procedentes de universidades asociadas a la AUIP.

Convocatoria 3: Becas Santander Financial Institute (SANFI) Máster en Banca y Mercados Financieros España Plazo de solicitud: hasta el 30 de junio de 2022. Nº de Plazas convocadas: 4 becas para el master impartido en la Universidad de Cantabria (España) Dirigido a: solicitantes españoles, preferentemente procedentes de universidades asociadas a la AUIP.

Las becas consisten en una ayuda para la matrícula o colegiaturas del Máster, y, en algunos casos (ver bases de las convocatorias), un apoyo o complementario específico para el desplazamiento y la estancia de los becados a la universidad donde se imparte.

Más información: https://auip.org/es/becas-auip/2434

It's a shame that i'm deeply allergic to writing any words ever, cause I just have this growing list of prompts my brain feverishly spits up

sanfie and his little ones

SANFI incorpora la tecnología Blockchain en la emisión de sus títulos propios Los diplomas de Santander Financial Institute (SANFI) contarán con doble seguridad al beneficiarse de la tecnología Blockchain…

guys dont tell my twitter audience. but. sanfy charm.

Sanfie

sanfy.

Bồn cầu liền Sanfi S301

Thông tin chi tiết sản phẩm Bệt két liền Sanfi S301 : 

Mã sản phẩm:  S301 Kích thước (cm):  như bản vẽ Hệ thống xả :  Xả Siphon Jet 3L/6L Loại men:  Men Nano Titan chống bám dính, kháng khuẩn Màu sắc : Trắng Tính năng : 2 chế độ xả nhấn, nắp rơi êm. Công nghệ xả đẩy - hút: Xả nhanh, mạnh và không gây tiếng ồn. Bảo hành : phần sứ 20 năm, phụ kiện 3 năm. Read the full article