Miracle-dz/UniFAR-FTUs huggingface dataset:
Recurrent Attentive Neural Process for Sequential Data

Neural processes (NPs) learn stochastic processes and predict the distribution of target output adaptively conditioned on a context set of observed input-output pairs. Furthermore, Attentive Neural Process (ANP) improved the prediction accuracy of NPs by incorporating attention mechanism among contexts and targets. In a number of real-world applications such as robotics, finance, speech, and biology, it is critical to learn the temporal order and recurrent structure from sequential data. However, the capability of NPs capturing these properties is limited due to its permutation invariance instinct. In this paper, we proposed the Recurrent Attentive Neural Process (RANP), or alternatively, Attentive Neural Process-RecurrentNeural Network(ANP-RNN), in which the ANP is incorporated into a recurrent neural network. The proposed model encapsulates both the inductive biases of recurrent neural networks and also the strength of NPs for modelling uncertainty. We demonstrate that RANP can effectively model sequential data and outperforms NPs and LSTMs remarkably in a 1D regression toy example as well as autonomous-driving applications.
Cascaded Generation of High-quality Color Visible Face Images from Thermal Captures

Generating visible-like face images from thermal images is essential to perform manual and automatic cross-spectrum face recognition. We successfully propose a solution based on cascaded refinement network that, unlike previous works, produces high quality generated color images without the need for face alignment, large databases, data augmentation, polarimetric sensors, computationally-intense training, or unrealistic restriction on the generated resolution. The training of our solution is based on the contextual loss, making it inherently scale (face area) and rotation invariant. We present generated image samples of unknown individuals under different poses and occlusion conditions.We also prove the high similarity in image quality between ground-truth images and generated ones by comparing seven quality metrics. We compare our results with two state-of-the-art approaches proving the superiority of our proposed approach.
The performance of the KIBB-g1 tabletop Kibble balance at NIST

A tabletop-sized Kibble balance (KIBB-g1) designed to directly realize mass at the gram-level range with uncertainties on the order of parts in 106 has been developed at the National Institute of Standards and Technology (NIST). The masses of a nominally 5 g and 1 g weight were determined with standard uncertainties of 9.0 g and 6.7 g, respectively. The corresponding relative uncertainties are and . The construction of the instrument, capabilities, and full uncertainty budgets are presented in this manuscript.
Policy Learning for Malaria Control

Sequential decision making is a typical problem in reinforcement learning with plenty of algorithms to solve it. However, only a few of them can work effectively with a very small number of observations. In this report, we introduce the progress to learn the policy for Malaria Control as a Reinforcement Learning problem in the KDD Cup Challenge 2019 and propose diverse solutions to deal with the limited observations problem. We apply the Genetic Algorithm, Bayesian Optimization, Q-learning with sequence breaking to find the optimal policy for five years in a row with only 20 episodes/100 evaluations. We evaluate those algorithms and compare their performance with Random Search as a baseline. Among these algorithms, Q-Learning with sequence breaking has been submitted to the challenge and got ranked 7th in KDD Cup.
Formal groups and quantum cohomology

We use chain level genus zero Gromov-Witten theory to associate to any closed monotone symplectic manifold a formal group (loosely interpreted), whose Lie algebra is the odd degree cohomology of the manifold (with vanishing bracket). When taken with coefficients mod p, the p-th power map of the formal group is related to quantum Steenrod operations. The motivation for this construction comes from derived Picard groups of Fukaya categories, and from arithmetic aspects of mirror symmetry.
The Analgesic Profiles of Opioids in Human Experimental Pain Models

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Modeling the Conditional Dependence between Stock Market Returns with a Copula-GARCH Approach

Riassunto: Recenti ricerche si sono indirizzate verso lo studio delle dinamiche che caratterizzano i legami tra i mercati azionari. Nell’ambito di tali analisi, emerge che la correlazione presentata dai rendimenti dei maggiori indici di mercato azionario non è costante nel tempo e risulta condizionata alle informazioni passate. Il presente lavoro indaga tali dinamiche mediante un approccio Copula-GARCH. I vantaggi dell’adozione di tale approccio risiedono nell’utilizzo di strumenti flessibili di analisi della distribuzione congiunta dei rendimenti (funzioni copula) caratterizzati da un parametro time-varying condizionatamente al passato, con una separata specificazione della forma delle marginali mediante l’applicazione di modelli T-GARCH.
Visual Localization with Google Earth Images for Robust Global Pose Estimation of UAVs

We estimate the global pose of a multirotor UAV by visually localizing images captured during a flight with Google Earth images pre-rendered from known poses. We metrically localize real images with georeferenced rendered images using a dense mutual information technique to allow accurate global pose estimation in outdoor GPS-denied environments. We show the ability to consistently localize throughout a sunny summer day despite major lighting changes while demonstrating that a typical feature-based localizer struggles under the same conditions. Successful image registrations are used as measurements in a filtering framework to apply corrections to the pose estimated by a gimballed visual odometry pipeline. We achieve less than 1 m and 1◦ RMSE on a 303 m flight and less than 3 m and 3◦ RMSE on six 1132 m flights as low as 36 m above ground level conducted at different times of the day from sunrise to sunset.
Image Compression for Wireless Sensor Networks

Wireless Sensor Network (WSN) are large networks made of a numerous number of sensor nodes with sensing, computation, and wireless communications capabilities. It is one of the promising platforms for a variety of applications such as military based applications to health-oriented applications. The transmission of image content through WSN has several bottlenecks including limited bandwidth, low power and less memory space. To overcome these drawbacks, the field of image processing introduced many image compression algorithms. Image compression is the technology that has been used in WSN domains and then developed to reduce image size and used by WSN applications. Absolute Moment Block Truncation Coding (AMBTC) is one of the image compression algorithm used to increase the life-time of the sensor node by reducing the computational time, better image quality and high compression ratio when compared to the existing compression techniques. In this paper has been attempt made to realize the use of AMBTC image compression algorithms over Wireless Sensor Networks in order to decrease the energy consumption of sensors and thus to maintain a long network lifetime. And also realize the effectiveness of the AMBTC by determine the performance metrics such as quality of the image, computational Time (T), Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR) by using AMBTC. Keywords—Wireless Sensor Networks, AMBTC, Image, Compression Techniques, BTC, Performance Metrics, PSNR, CR
Evaluating phosphorus losses in surface and subsurface runoff from two agricultural fields in Quebec

Phosphorous concentrations exceed water quality guidelines in most of the major rivers in southern Quebec. The problem is particularly acute in the Pike River, which drains into the Missisquoi Bay of Lake Champlain, in southeastem Quehec. Elevated phosphorus concentrations can lead to a reduction in the palatability of drinking water, a decrease in diversity of aquatic life and loss of recreational opportunities. AlI of these problems have been observed in the Bay. Two agricultural fields (the Marchand .and Gagnon .• sites) located on the Pike River watershed, in southeastem Quebec were selected and equipped with instrumentation to measure and evaluate the partitioning of phosphorus between surface runoff and subsurface drainage, on a year round basis. The snowmelt event was the dominant surface and subsurface event for the 2000/2001 hydrological year. On the Marchand site surface flow data was incomplete as a result of a failure of the surface runoff flume. On both sites the IF 200 subsurface flowmeters failed, which resulted in missing subsurface flow data during certain runoff events. Therefore, the majority of the comparisonsmade relate to the Gagnon site. The 2000/2001 hydrological year was unusually dry, which resulted in a limited number of surface and subsurface.runoff events. The annual depth of surface mnoff for the Gagnon site was 87.5 mm/ha, of which only O.2mm occurred outside the snowmelt event. The estimated depth of subsurface runoff of the snowmelt event at the Gagnon site basedupon a water balance equation.was 93.7 mm/ha, or 51.7% of the total volume that occurred on the Gagnon field during the snowmelt event. The total phosphorus load in surface runoff for the spring snowmelt at the Gagnon site was 166.4 glha, whereas the estimated total phosphorus load in subsurface drainage was 98.2 g/ha, or 37.1% of the totalload. Subsurface drains can therefore he a significant pathway for phosphorus losses.
PT PUPUK KALIMANTAN TIMUR ) APPLICATION OF RELIABILITY-CENTERED MAINTENANCE AND RISK-BASED MAINTENANCE METHODS FOR MAINTENANCE POLICY PROPOSAL CRITICAL COMPONENTS OF REFORMER SYSTEM ( CASE STUDY : PT PUPUK KALIMANTAN TIMUR )

PT Pupuk Kalimantan Timur is the largest ammonia and urea producer in Indonesia, with a production capacity of 2,76 million tons of ammonia and 3,43 million tons of urea. PT Pupuk Kalimantan Timur operates 5 units of plants for the production of ammonia and urea, and there are 4 units of utility plants that provide electricity, steam and water. Each plant is divided into 5 zones (K-1A, K-2, K-3, K-4, K-5) according to their respective location. In the last two years, the ammonia plant in the K-4 zone has the lowest average ammonia production rate due to the high corrective maintenance level at the plant. The most crucial system in the process of ammonia production is the reformer system, the system which is responsible in reacting the sulfurized natural gas with steam and air which then produces hydrogen gas as an ammonia making composition. Therefore, an appropriate maintenance policy is required in the reformer system. By using the risk matrix, AT-2002, PDT-2014, and PV-2001 are obtained as the selected critical components. Then the maintenance policy, total maintenance costs, and risks are determined using the method of reliability-centered maintenance and risk-based maintenance. Based on the results of collecting and processing the data, there are 6 scheduled on-condition tasks, and 4 scheduled restoration tasks with maintenance time interval in accordance to their task category, a total maintenance cost of Rp 159.702. 111 with the risk as much as Rp 82.754. 935.
One minute is enough : Early Prediction of Student Success and Event-level Difficulty during a Novice Programming Task

Early prediction of student difficulty during long-duration learning activities allows a tutoring system to intervene by providing needed support, such as a hint, or by alerting an instructor. To be effective, these predictions must come early and be highly accurate, but such predictions are difficult for open-ended programming problems. In this work, Recent Temporal Patterns (RTPs) are used in conjunction with Support Vector Machine and Logistic Regression to build robust yet interpretable models for early predictions. We performed two tasks: to predict student success and difficulty during one, open-ended novice programming task of drawing a square-shaped spiral. We compared RTP against several machine learning models ranging from the classic to the more recent deep learning models such as Long Short Term Memory to predict whether students would be able to complete the programming task. Our results show that RTP-based models outperformed all others, and could successfully classify students after just one minute of a 20minute exercise (students can spend more than 1 hour on it). To determine when a system might intervene to prevent incompleteness or eventual dropout, we applied RTP at regular intervals to predict whether a student would make progress within the next five minutes, reflecting that they may be having difficulty. RTP successfully classified these students needing interventions over 85% of the time, with increased accuracy using data-driven program features. These results contribute significantly to the potential to build a fully data-driven tutoring system for novice programming.
How the Enga Cope with Frost : Responses to Climatic Perturbations in the Central Highlands of New Guinea

The adaptive strategy o f a population o f New Guinea highland subsistence farmers is considered in the light o f events surrounding a series o f severe frosts experienced in 19 72. Coping with frost is seen to be a critical preoccupation for all Enga, and agricultural mounding a universal response, adequate to deal with the mild frosts o f Central Enga country below 2250 m but insufficient above. There, among the Fringe Enga, a sequence o f responses at three different levels may be identified. These may be called the local, intraregional, and extraregional levels because o f their progressively wider geographical spread in agricultural activity and attendant increased population mobility. A correspondence is indicated between response level and frost intensity. This response, while effective, is being modified through cropping innovations and disrupted by a colonial situation. Further, at higher levels, it is incompatible with the prescribed course of political and economic development.
DYNAMICS OF THE PLAGUE TRANSMISSION CYCLE IN CENTRAL JAVA ( Ecology of mammalian hosts with special reference to Rattus exulans )

Rodents are the most widespread, most abundant (both in number of species and in number of individuals) and most readility adaptable of all konwn groups of mammals. They are worldwide in distribution and occupy virtually every subteiranean, terrestrial and arboreal habitat capable of supporting mammalian life, some species even being semi-aquatic in habit. The role of wild and domestic rodents in the transmission of certain infections diseases. such as plague, is well established. Within a zoonotic cycle, rodents may serve either as primary or secondary hosts for vectors of the pathogenic agent and, depending on their resistance-susceptibility status, may function either as reservoirs or amplifying agents for the pathogen. The distributions zoonotic pathogens, and of potential vectors of these pathogens, are determined to a large extent by the respective distributions of suitable vertehrate hosts.
SUMO User Conference 2019 Remarks on Traffic Signal Coordination

The co-ordination between traffic signals is assumed to be important for the good organization of a transport system. By using an artificial approach to create and analyze a multitude of transportation systems, a few different simple traffic signals programs has been put to the test and compared to each other. The result is that a well co-ordinated system can be outperformed by a non-coordinated signal set-up, where all signals controlers run in (single intersection) actuated mode. Clearly, these results are preliminary and require more investigation.
Robust virtual sensing of the exterior noise radiation from a complex structure in different acoustic environments

By using a numerical model of a vibro-acoustic system in combination with a small set of measurements in a Kalman filter, it is possible to estimate the sound pressure at locations where no microphones are present. This can be achieved with increased accuracy as compared to using only the numerical model due to the inclusion of the expected process and measurement noise. This procedure is also known as virtual sensing. In this paper, a model-based virtual sensor is built for a complex, deep drawn structure that radiates sound into the free field. A finite element model is used that is extended with infinite elements to approximate the Sommerfeld radiation condition. Since the original model is too large to be used in a Kalman filter, it is reduced by a stable Krylov based model order reduction technique. The performance of this virtual sensor is tested in a semi-anechoic chamber, and additionally in several acoustical environments that do not conform to the Sommerfeld condition in order to validate whether the Kalman filter can handle the additional uncertainties. The obtained results show that the filter performs well, which means that the required modeling effort can be reduced significantly by assuming free-field conditions.
Magnetic resonance arthrography of femoroacetabular impingement: a case report

iagnostic radiographers in clinical practice undertake radiological investigations for patients who present with hip pains and diverse pelvic pathologies. This case report provides an insight into one of the clinical indications for undertaking such procedures. It discusses femoral acetabular impingement (FAI) which is a clinical indication for plain-film radiography and magnetic resonance imaging (MRI) of the hip bone. FAI is a concept where there is a structural or spatial abnormality of the femur (cam) or acetabulum (pincer) with damages to the chondrolabral structures during normal joint movement. It could occur either singularly as a cam, pincer or a mixed-cam-pincer pathology along the anterior femoral neck and the anterior-superior acetabular rim of the hip bone.
Neuropsychological correlates of the P 300 in patients with Alzheimer ' s disease

Abbreviations: AD, Alzheimer’s disease; NC, normal version of the Consortium to Establish a Registry for the Korean version of the Mini-Mental State Examinatio State Examination in the CERAD-K; TMT-A, Trail Making ing Test part B; ERP, Even-Related Potentials; MCI, m CASI, the Cognitive Abilities Screening Instrument te NINCDS-ADRDA, the National Institute of Neurological and the Stroke-Alzheimer’s Disease and Related Disord Dementia Rating scale; EEG, electroencephalogram; SB Short Blessed Test; K-BNT, the Korean version of the Bos oculogram; ANOVA, analyses of variance; ADAS-c Assessment-Cognitive subscale; FAB, the Frontal Assess ⁎ Corresponding author at: Department of Psychiatry, In 2240 Daehwa-dong, Ilsan-seo-gu, Goyang-si, Kyunggi-d Tel. : +82 31 910 7262; fax: +82 31 910 7268. E-mail addresses: lshpss@ilsanpaik.ac. kr, lshpss@han
TURKISH ECO OMIC ASSOCIATIO DISCUSSION PAPER 2008/12 http ://www.tek. org.tr I TERMEDIATIO COST and FI A CIAL FRAGILITY

This paper studies implications of intermediation costs in credit markets. The presence of intermediation costs increases the amount of risky projects therefore results in financial fragility. Moreover, for an open economy that has a perfectly liberal capital account, prudent firms finance their projects from foreign markets therefore shrinking the domestic credit markets. The theoretical predictions of our model gains support by Turkish data for the 1991 – 2004 period. Data suggests that an increase in intermediation costs results in an increase in non-performing loans, and an increase in foreign financing (shrinking of domestic credit markets). We argue that minimization of these costs improves financial soundness. 1 Opinions expressed in this study are Authors’ and do not represent the views of the Central Bank of Turkey. We thank Şeref Saygılı, Mesut Saygılı, seminar participants at the Central Bank and an anonymous referee for helpful comments. 2 Corresponding Author: The Central Bank of the Republic of Turkey, Research and Monetary Policy Department, International Economic Analysis Division, Istiklal Cad. No: 10, Ulus 06100 Ankara, Tel: (+90 312) 310 9341, ferhan.salman@tcmb.gov. tr
Capital Flows and Spillovers

Do gross capital flows import global shocks to emerging markets? If so, what are the output spillovers from such shocks to emerging markets and what tools should emerging market central bankers use to deal with them? Academics and policy makers have fiercely debated these central policy questions. The textbook open economy model states that countries with open capital markets must choose between monetary autonomy and exchange rate management. In order to be able to deal with global shocks imported by capital flows, countries must use a floating exchange rate as the shock absorber, leaving monetary policy to be the tool for other domestic policy considerations. Hélène Rey (2013) recently challenged this centrepiece of international macroeconomics. Her argument is that widespread co-movement in capital flows, asset prices and credit growth across countries — a global financial cycle — makes the trilemma irrelevant: independent monetary policies are possible if, and only if, the capital account is managed. To put it differently, flexible exchange rates will not absorb CHAPTER 2
COMPARISON FOR UNDERWATER ARCHAEOLOGICAL PHOTOGRAMMETRIC APPLICATIONS

This paper presents an investigation as to whether and how the selection of the SfM-MVS software affects the 3D reconstruction of submerged archaeological sites. Specifically, Agisoft Photoscan, VisualSFM, SURE, 3D Zephyr and Reality Capture software were used and evaluated according to their performance in 3D reconstruction using specific metrics over the reconstructed underwater scenes. It must be clarified that the scope of this study is not to evaluate specific algorithms or steps that the various software use, but to evaluate the final results and specifically the generated 3D point clouds. To address the above research issues, a dataset from the ancient shipwreck, laying at 45 meters below sea level, is used. The dataset is composed of 19 images having very small camera to object distance (1 meter), and 42 images with higher camera to object distance (3 meters) images. Using a common bundle adjustment for all 61 images, a reference point cloud resulted from the lower dataset is used to compare it with the point clouds of the higher dataset generated using the different photogrammetric packages. Following that, a comparison regarding the number of total points, cloud to cloud distances, surface roughness, surface density and a combined 3D metric was done to evaluate and see which one performed the best.