nils-herrmann/clean_scirepeval huggingface dataset:
DISTRIBUSI ASIMTOTIK UNTUK ESTIMATOR KOMPONEN PARAMETRIK DALAM MODEL SEMI PARAMETRIK PADA PROSES PENGOLAHAN LIMBAH PABRIK GULA ASEMBAGUS SITUBONDO
Year: 2010

Estimasi kurva regresi umumnya dilakukan dengan pendekatan parametrik dengan diasumsikan bentuk kurva regresi f diketahui. Jika asumsi terhadap bentuk kurva regresi f tidak diberikan maka pendekatan yang lebih tepat adalah pendekatan nonparametrik. Dari dua pendekatan ini jika digabungkan akan mendapatkan model semiparametrik. Gula merupakan salah satu dari sembilan bahan pokok masyarakat Indonesia. Seiring dengan semakin dekatnya era pasar bebas, diperlukan upayaupaya perbaikan dalam segala bidang termasuk proses pembuatan gula. Salah satu upaya yang dapat dilakukan adalah menggambarkan pola hubungan antara bahan masukan proses yang meliputi tebu dan bahan kimia lain yang ditambahkan yaitu kapur tohor(X\ sulfur(X2) flokulan(X3) tebu(,fosfat(X5) dengan limbah yang dihasilkan(Y) Dalam penelitian Nureholis Rudianto digunakan metode Bayes dengan algoritma iteratif Gibbs Sampler untuk pendugaan parameter serta menentukan model terbaik dan beberapamodel. Dengan metode All Possible Regression dapat dijelaskan ada dua model terbaik Y=(X I,X4) dan Y=(XI,X4,XS) Namun kontribusi X5 terhadap penambahan R2 hanya 0.01. Selain itu pengaruh variabel X2 dan X3 dalam penelitian ini keeil, dan nilai R? untuk model Y(X2,XS) terkeeil yaitu 34.1% Hal inilah yang memotovasi penggunaan spline untuk menduga kurva regresi dari proses pengolahan limbah pabrik gula Asembagus Situbondo. Selanjutnya diselidiki hubungan antara berat fosfat yang dalam hal ini merupakan variabel komponen nonparametrik dan berat sulfur yang merupakan variabel komponen parametrik dengan berat limbah gula yang dihasilkan. Estimasi huhungan tersebut dapat dinyatakan sebagai model semiparametrik berikut: A Y 15.3994 12.6788T 7.327IT2 1.3813T3 1.4899(T 1.9) 0.7239(T 5.9) 2.3702(T 7.8)3+ 5.8990 X 0.5385 X2 dengan nilai R2 71.92384% Ini menunjukkan bahwa variabel fosfat dan berat sulfur mampu menerangkan 71.92384% keragaman berat 1imbah. Komponen parametrik yaitu berat sulfur berdistribusi normal.
Completion Time and Energy Optimization in the UAV Enabled Mobile Edge Computing System
Venue: IEEE Internet of Things Journal
Year: 2020

Completion time and energy consumption of the unmanned aerial vehicle (UAV) are two important design aspects in UAV enabled applications. In this article, we consider a UAV enabled mobile edge computing (MEC) system for Internet of Things (IoT) computation offloading with limited or no common cloud/edge infrastructure. We study the joint design of computation offloading and resource allocation, as well as UAV trajectory for minimization of energy consumption and completion time of the UAV, subject to the IoT devices' task and energy budget constraints. We first consider the UAV energy minimization problem without predetermined completion time, a discretized nonconvex equivalent problem is obtained by using the path discretization technique. An efficient alternating optimization algorithm for the discretized problem is proposed by decoupling it into two subproblems and addressing the two subproblems with successive convex approximation (SCA) based algorithms iteratively. Subsequently, we focus on the completion time minimization problem, which is nonconvex and challenging to solve. By using the same path discretization approximation model to reformulate problem, a similar alternating optimization algorithm is proposed. Furthermore, we study the Pareto optimal solution that balances the tradeoff between the UAV energy and completion time. The simulation results are provided to corroborate this article and show that the proposed designs outperform the baseline schemes. Our results unveil the tradeoff between completion time and energy consumption of the UAV for the MEC system, and the proposed solution can provide the performance close to the lower bound.
Recent Advances of Efficient Design of Terahertz Quantum Cascade Lasers
Venue: Plasmonics
Year: 2020

Terahertz (THz) quantum cascade lasers (QCLs) are electrically pumped and heterostructure based semiconductor laser sources with intersubband transitions of electrons in different layers of the quantum wells and barriers. The THz QCLs have high output power in THz region which make them important from application point of view. Recently intensive research has been carried out by researchers for obtaining efficient designs of THz sources. Most of the researchers have investigated the THz frequency range between 0.1 and 3 THz; however, the output power of the THz sources in the frequency range 3 5 THz is small because of transit time and resistance capacitance effects. Nevertheless, the present review is focused for the development of efficient THz QCL sources in the frequency range from 3 to 5 THz where one of the major problem of thermal backfilling of the carriers has to be overcome by engineering the heterostructure.
Robust Morse Decompositions of Piecewise Constant Vector Fields
Venue: IEEE Transactions on Visualization and Computer Graphics
Year: 2012

In this paper, we introduce a new approach to computing a Morse decomposition of a vector field on a triangulated manifold surface. The basic idea is to convert the input vector field to a piecewise constant (PC) vector field, whose trajectories can be computed using simple geometric rules. To overcome the intrinsic difficulty in PC vector fields (in particular, discontinuity along mesh edges) we borrow results from the theory of differential inclusions. The input vector field and its PC variant have similar Morse decompositions. We introduce a robust and efficient algorithm to compute Morse decompositions of a PC vector field. Our approach provides subtriangle precision for Morse sets. In addition, we describe a Morse set classification framework which we use to color code the Morse sets in order to enhance the visualization. We demonstrate the benefits of our approach with three well known simulation data sets, for which our method has produced Morse decompositions that are similar to or finer than those obtained using existing techniques, and is over an order of magnitude faster.
Threshold voltage drift aware scheduling for belief propagation decoding of LDPC coded NAND flash memory
Venue: IET Commun.
Year: 2019

With the continual increase of storage density, NAND flash memory cells are particularly vulnerable to channel noise, which significantly degrades the storage reliability. To overcome this issue, low density parity check (LDPC) codes have been considered as a preferable choice for flash memory systems. To further improve the efficiency of the decoder, the convergence speed and the error rate performance are the key performance indicators for LDPC coded NAND flash memory. In this study, a threshold voltage drift aware scheduling for belief propagation (BP) decoding of LDPC coded NAND flash memory is introduced to improve the convergence speed and the error rate performance. The basic idea of the proposed scheduling is to find an appropriate updated order of variable nodes according to their corresponding locations of threshold voltages. Since the proposed scheduling updates less reliable variable nodes with higher priority, it can improve the efficiency of BP decoding. Simulation results show that the proposed scheduling not only significantly improves the convergence speed, but also obtains better error rate performance than the conventional serial scheduling.
TELEOLOGIA Y TEOLOGIA EN LA FENOMENOLOGIA DEL JOVEN DERRIDA
Venue: Aporia Revista Internacional de Investigaciones Filosoficas
Year: 2019

The present study attempts to expose the Phenomenology of the young Derrida (1953 1967) in relation to the problem of God as a universal telos. From the problem of the genesis, Derrida interprets the philosophical project of Husserl as a revolutionary thinking that tries to overcome the classical problems of philosophy. In this perspective, the first philosophical themes of Derridian thought emerge, such as the phenomenology of writing, traditionality, and an embryonic philosophy of document. In this itinerary, Derrida meets Husserl's proposal on the transcendental divinity that would provide unity to the telos and the arche. This will serve as an instrument to introduce a recurrent idea in the philosophy of the young Derrida: the unity between ideality and historicity
Experimental Evaluation of Local Sensitive Hashing Functions for Face Recognition
Venue: 2019 5th International Conference on Web Research (ICWR)
Year: 2019

Since the number of facial images has grown in social networks, such as Facebook and Instagram, face recognition has been recognized as one of the important branches of image processing research area, and large databases of face images have been created. As a result, the response time of the face recognition system is recognized as a challenge. Fortunately, dimension reduction techniques help to reduce the number of computations significantly, which directly effects on system response time. As many facial features do not include important information, which is required for getting a better result from the face recognition systems, these techniques are applicable for facial images, as well. Local Feature Hashing (LFH) is a hash based algorithm that has been used for face recognition. It has shown notable computational improvements over naive search and can overcome some challenges, including recognition of pose, facial expression, illumination, and partial occlusion parameters. With the aim of improving the time that it takes to run the LFH algorithm, we have tested several versions of Locality Sensitive Hashing (LSH) algorithm. The results showed that some of these algorithms improve the response time of the LFH algorithm. In comparison with the previously conducted research, the number of input images has been increased in our tests. Besides, the number of extracted key point vectors have been decreased, and the accuracy has not been decreased. In addition, our algorithm is able to overcome the challenge of the existence of foreign objects, such as glass. Among all different hash versions that for the first time used for face recognition, some of them are not recommended for these systems and several functions can provide minimum response time, rather than previous hash based algorithms.
The dynamics of place brands
Year: 2013

This article introduces a novel approach towards place branding theory, adopting a view based on the relationship between the place brand and place identity. The article first evaluates the dominant conceptualization of identity within place branding. It is argued that better understanding of the relationship between place identity and place brands might advance the theory of place branding. In its current state, place branding practice and, to a great extent, place branding literature adopt a rather static view on place identity as something that can easily be articulated and communicated for the purposes of branding the place. This approach is limited as it does not reveal the full complexity of place identity and limits the role and potential of place branding. The article, drawing on a combination of the literatures on place identity and organisational identity, proposes a more dynamic view of place identity that considers identity a constant dialogue between the internal and the external. The role of branding within the identity dialogue is then clarified leading to an appreciation of the full dynamics of place brands. The true nature of place branding is revealed as one of interaction and dialogue between stakeholders.
A Bayesian Based Controller for Snake Robot Locomotion in Unstructured Environments
Venue: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2020

This paper presents a novel Bayesian based controller for snake robots in cluttered environment. It extends the conventional shape based compliant control into statistical field providing an explicit mathematical formulation with Bayesian network. A sequential density propagation rule is derived by introducing several probability densities in a unified framework. Specifically, two input influence densities are proposed to model the cumulative effect of various external forces that the snake robot undergoes. Moreover, the measurement likelihood model is exploited to give a more robust closed loop feedback. Overall, the proposed approach provides an innovative way to handle challenging tasks of snake robot control in complicated environment. Experimental results have been demonstrated for both simulation and real world data.
Rhizoma gastrodiae roxburgh rose cake
Year: 2014

The present invention discloses a rhizoma gastrodiae roxburgh rose cake. GuiZhou rhizoma gastrodiae and roxburgh rose are taken as main raw materials. Apples are used as a main assistant material, and a food grade gelatinizing agent and seasonings are added. The formulation and ratio are as follows: 15 to 25 parts of roxburgh rose juice, 1 to 2 parts of rhizoma gastrodiae powder, 10 to 12 parts of apple juice, 7 to 9 parts of xylitol, 7 to 9 parts of white granulated sugar, 0.1 to 0.3 part of citric acid, and 1.5 to 1.8 parts of a composite gelatinizing agent, with the balance being water to form 100 parts. The preparation method of the rhizoma gastrodiae roxburgh rose cake comprises the following steps: selecting the finest roxburgh rose; cleaning the roxburgh rose; beating the roxburgh rose into pulp; mixing the rhizoma gastrodiae powder, the pulp, and the composite gelatinizing agent and then adding the water and carrying out blending; carrying out boiling; pouring the boiled mixture into a disc; cooling the mixture; drying the mixture; forming the mixture into a shape; cooling the shaped mixture; carrying out inflatable packaging; and testing and warehousing the finished product. The rhizoma gastrodiae roxburgh rose cake has characteristics of simple process and easy industrial production, and moderate sour and sweet taste. By combining the rhizoma gastrodiae with the roxburgh rose which is the king of Vitamin C, the rhizoma gastrodiae roxburgh rose cake can supply people with vitamin C. Furthermore the application of the rhizoma gastrodiae nutritional effects in the rhizoma gastrodiae roxburgh rose cake can expand the casual health food market. The rhizoma gastrodiae roxburgh rose cake has good market prospects.
Information security behavior: Recognizing the influencers
Venue: 2017 Computing Conference
Year: 2017

With the wide spread use of Internet, comes an increase in Information Security threats. To protect against these threats, technology alone have been found not enough as it can be misused by users and become vulnerable to various threats, thus, losing its usefulness. This is evident as users tend to use weak passwords, open email attachments without checking and do not set correct security settings. However, especially with the continuously evolving threat landscape, one cannot assume that users are always motivated to learn about Information Security and practice it. Actually, there are situations of an aware user who knows how to protect himself but, simply, chooses not to, because they do not care, usability problems or because they do not consider themselves as targets. Thus, understanding human security behavior is vital for ensuring an efficient Information Security environment that cannot depend on technology only. Although a number of psychological theories and models, such as Protection Motivation Theory and Technology Acceptance Model, were used in the literature to interpret these behaviors, they tend to assess users' intensions rather than actual behavior. The aim of this paper is to understand and assess these behaviors from a holistic view by finding the significant factors that influence them and how to best assist users to protect themselves. To accomplish this, a systematic literature review was conducted where relevant literature was sought in a number of academic digital databases. As a result, several key behavioral influencers were identified to be essential to consider when educating and directing users' security behavior. Further to that, a number of Information Security awareness approaches were proposed that may transform the user from being ill informed into a security minded user who is able to make an informed decision.
Experimental calibration for DCDC specimens
Year: 2019

The main advantages of DCDC specimens are their completely stable crack extension properties and very high path stability due to the strongly negative T stress term. Unfortunately, problems of DCDC tests can be identified by comparing experimental results that show for different materials (silicon nitride, glass) deviations from the results to be expected by 2 dimensional FE modelling as usual done in literature. Experimental calibrations on silicon nitrides and mixtures of silicon nitride and silicon carbide resulted in modified relations deviating from FE results in literature. As a possible source for the differences of measurements and 2 D FE results, we identified the influence of Poisson's number. This parameter obviously causes deviations between straight crack assumption in FEmodelling and observable curved crack fronts in the experiments. In order to avoid specimen buckling we also used short specimens of roughly half length. This may slightly affect the stress intensity factors.
TweetMT: A Parallel Microblog Corpus
Venue: LREC
Year: 2016

We introduce TweetMT, a parallel corpus of tweets in four language pairs that combine five languages (Spanish from/to Basque, Catalan, Galician and Portuguese) all of which have an official status in the Iberian Peninsula. The corpus has been created by combining automatic collection and crowdsourcing approaches, and it is publicly available. It is intended for the development and testing of microtext machine translation systems. In this paper we describe the methodology followed to build the corpus, and present the results of the shared task in which it was tested.
A near real time deep learning approach for detecting rice phenology based on UAV images
Year: 2020

Near real time crop phenology detection is essential for crop management, estimation of harvest time and yield estimation. Previous approaches to crop phenology detection have relied on time series (multi temporal) vegetation index (VI) data, and have included threshold based, phenometrics based and shape model fitting based (SMF) methods. However, the performance of these methods depends on the duration and temporal resolution of the time series data. In this study, we propose a new approach which identifies the principal growth stages of rice (Oryza sativa L. directly from RGB images. Only a mono temporal unmanned aerial vehicle (UAV) imagery was required for a large area phenology detection via the well trained network. An efficient convolutional neural network (CNN) architecture was designed to estimate rice phenology. The CNN incorporated spatial pyramid pooling (SPP) transfer learning and an auxiliary branch with external data. A total of 82 plots across a 160 hectare rice cultivation area of Southern China were selected to evaluate the proposed network. CNN predictions were ground truthed using rice phenology measurements taken from each plot throughout the growing season. Aerial data were collected using a fixed wing UAV equipped with multispectral and RGB cameras. The performance of traditional SMF methods deteriorated when time series VI data were of short duration. In contrast, the phenological stage estimated by the proposed network showed good agreement with ground observations, with a top 1 accuracy rate of 83.9% and mean absolute error (MAE) of 0.18. The spatial distribution of harvest dates for 627 plots in the study area were computed from the phenological stage estimates. The estimates matched well with the observed harvest dates. The results demonstrated the excellent performance of the proposed deep learning approach in near real time phenology detection and harvest time estimation.
Medida de actividades enzimaticas y poblacionesmicrobianas en suelos sometidos a remediacion porbentonita tras contaminacion por Cd y Pb
Year: 2015

El crecimiento de las areas urbanas supone un incremento de la contaminacion por metales pesados en los suelos. Los metales pesados son unos de los contaminantes mas toxicos que pueden estar presentes en los suelos, entre ellos, se encuentran el cadmio (Cd) y el plomo (Pb) El suelo es un componente esencial de la biosfera, por lo que cualquier contaminacion sobre este ha de ser controlada para poder preservarlo. Sus propiedades bioquimicas y microbiologicas son las primeras afectadas por la contaminacion, por lo que son utilizadas como indicadores de contaminacion y, tambien, la aplicacion de tecnicas enzimaticas se utiliza en la valoracion de los suelos sometidos a procesos de remediacion. Hay diversos metodos de remediacion de suelos, entre ellos, se encuentra la estabilizacion "in situ" de metales pesados. La bentonita es utilizada para la estabilizacion de metales pesados en suelos contaminados. Para evaluar la efectividad de la bentonita inmovilizando Cd y Pb en los suelos se utiliza el analisis de un conjunto de parametros como las caracteristicas bioquimicas, las fracciones de los metales, las actividades enzimaticas del suelo y la comunidad microbiana. La disminucion de la actividad catalasa y el aumento de las actividades invertasa y ureasa y de las bacterias, hongos y actinomicetos en el suelo implica la recuperacion metabolica del suelo por las adiciones de bentonita. Estos resultados indican que la bentonita tiene potencial para reducir la biodisponibilidad de los metales pesados en suelos agricolas; siendo necesaria la investigacion y remediacion de los suelos para evitar contaminaciones que pueden llegar hasta la cadena trofica.
Regulation of glycolysis by Pdk functions as a metabolic checkpoint for cell cycle quiescence in hematopoietic stem cells.
Venue: Cell stem cell
Year: 2013

Defining the metabolic programs that underlie stem cell maintenance will be essential for developing strategies to manipulate stem cell capacity. Mammalian hematopoietic stem cells (HSCs) maintain cell cycle quiescence in a hypoxic microenvironment. It has been proposed that HSCs exhibit a distinct metabolic phenotype under these conditions. Here we directly investigated this idea using metabolomic analysis and found that HSCs generate adenosine 5' triphosphate by anaerobic glycolysis through a pyruvate dehydrogenase kinase (Pdk) dependent mechanism. Elevated Pdk expression leads to active suppression of the influx of glycolytic metabolites into mitochondria. Pdk overexpression in glycolysis defective HSCs restored glycolysis, cell cycle quiescence, and stem cell capacity, while loss of both Pdk2 and Pdk4 attenuated HSC quiescence, glycolysis, and transplantation capacity. Moreover, treatment of HSCs with a Pdk mimetic promoted their survival and transplantation capacity. Thus, glycolytic metabolic status governed by Pdk acts as a cell cycle checkpoint that modulates HSC quiescence and function.
Exploring the Lived Experiences and Intersectionalities of Mexican Community College Transfer Students: Qualitative Insights Toward Expanding a Transfer Receptive Culture
Year: 2017

This qualitative study examines the experiences of six Mexican community college transfer students attending a research intensive institution in the Pacific Northwest. Using semi structured interviews, the objectives of this study were to 1) understand how Mexican students made meaning of their transfer experiences and 2) how those experiences could inform conceptual and practical thinking toward building a transfer receptive culture at the receiving institution. We use intersectionality as a site of material and discursive possibility to encourage predominantly White receiving institutions to recognize how they position Mexican community college transfer students on campus. Concluding are conceptual and practical recommendations that emphasize institutional and organizational responsibility in creating equitable environments for Mexican community college transfer students.