Miracle-dz/UniFAR-FTUs huggingface dataset:
Mathematisches Forschungsinstitut Oberwolfach Report No . 8 / 2005 Mini-Workshop : Interface Problems in Computational Fluid Dynamics Organised

Multiple difficulties are encountered when designing algorithms to simulate flows having free surfaces, embedded particles, or elastic containers. One difficulty common to all of these problems is that the associated interfaces are Lagrangian in character, while the fluid equations are naturally posed in the Eulerian frame. This workshop explores different approaches and algorithms developed to resolve these issues. Mathematics Subject Classification (2000): 65M, 65N, 76. Introduction by the Organisers This workshop was concurrent with the workshop on Analytical and Numerical Methods in Image and Surface Processing (see: Report No. 10/2005), and since the participants interests overlapped several combined talks were organized. In particular, we thank P. Schroder, U. Reif, G. Dziuk, C. Elliot, and F. Cirak, for their contributions. Currently there are three major techniques for tracking or characterizing interfaces present in a CFD computation: (i) The level set method, (ii) Phase field approximations, and (iii) Explicit parameterization using Lagrangian variables. Each of these techniques, and various hybrids, were presented by the participants to solve a variety of challenging CFD problems involving interfaces. Several trends emerged during the workshop. (1) The analysis of phase field algorithms is much more advanced than that of the level set method (Elliot and Walkington). (2) If the topology of the surface doesn’t change, Lagrangian methods provide very accurate descriptions of the complex motions and physics of 466 Oberwolfach Report 8/2005 the interfaces (see for example the Willmore flow by Dzuik). Many hybrid Eulerian/Lagrangian schemes were presented such as the immersed interface method (Gastaldi), volume of fluid method (Picasso), ALE and deforming mesh methods (Behr, Krahl, Mehnert, Ganesan). The most detailed simulations presented at the workshop modeled hundreds of interacting rigid particles (Turek). The pistons and orientations of the particles were explicitly computed. Progress has been made in the analysis of Lagrangian schemes to model interfacial motion (Dzuik, Mehnert, Nobile) for problems where the interface remains regular. (3) Practical application of the level set technique appears to require frequent reparameterization of the level set function, and in order to obtain a sharp interface it is necessary to evaluate the Heavyside function of the level set function. These modifications to the basic algorithm represent a significant complication to the analysis of this class of methods. These complications also appear to extend to the practical implementation; for example, both Burman and Reusken evolve their interfaces using level sets, but explicitly construct a parametrization of the interface at each time step. Mini-Workshop: Interface Problems in Computational Fluid Dynamics 467 Mini-Workshop: Interface Problems in Computational Fluid Dynamics
Two Tiered Distributed Training Algorithm for Acoustic Modeling

We present a hybrid approach for scaling distributed training of neural networks by combining Gradient Threshold Compression (GTC) algorithm - a variant of stochastic gradient descent (SGD) - which compresses gradients with thresholding and quantization techniques and Blockwise Model Update Filtering (BMUF) algorithm - a variant of model averaging (MA). In this proposed method we divide total number of workers into smaller subgroups in a hierarchical manner and limits frequent communication within each subgroup. We update local model using GTC within a subgroup and global model using BMUF across different subgroups. We evaluated this approached by training deep long short-term memory (LSTM) recurrent neural network for automatic speech recognition (ASR) problem on a 2000 hour audio dataset, and comparing to BMUF training with 128 GPUs, the proposed approach delivers 1.25x relative speed up (~100x speed up comparing to single GPU) and reduces relative WER degradation by 100%.
TESTING THE FACTUALITY OF THE CONQUEST OF AI NARRATIVE IN THE BOOK OF JOSHUA

Summary of the problem. The gamut of views concerning the conquest of Ai narrative in the 7 and 8 chapters of the Book of Joshua can be summarized as follows: the narrative is factual, having the weight of eye witness testimony; or, it is an aetiological legend, compiled long after the fact, either just before or during the Babylonian exile for the purpose of justifying Israel’s presence in the land of Canaan; or, it is a pernicious myth, deceptively and skillfully fabricated to correspond with the material time-space context in which it is alleged to have occurred. Is there a method that is capable of objectively arbitrating among these three views? Summary of the method. The theory of True Narrative Representations propounded by John W. Oller provides the basis for an analytical test of the factuality of the narrative in question, and thereby an arbitration among the three views summarized above. The analytical process begins with the derivation of a fourteen-parameter criterial screen from careful exegesis of the biblical text in the Book of Joshua. The criterial screen is the analytical tool whereby the correspondence of the biblical narrative to its material time-space context can be empirically assessed. The first three parameters of the screen form a predicate criterial screen, which is applied to the three candidate sites for Joshua’s Ai that emerge from past research; namely, et-Tell, Kh. Nisya, and Kh. el-Maqatir. Even this very limited three-parameter screen is sufficiently explicit that only one of the candidate sites, Kh. elMaqatir, meets all of its requirements. The remaining eleven parameters of the more elaborate and still more demanding criterial screen are then applied to that one surviving site, which entails a careful and detailed correlation of the text of Joshua 7 and 8 with the archaeological, geographical, and topographical context of the site. By this means, the conformity of the narrative in question with the determinacy, connectedness, and generalizability properties of true narratives is empirically tested. Included in the analytical process is the postulation of viable engagement scenarios for the two battles of Ai. Summary of the conclusion. The result of the analytical process is that, of the three candidate sites for Joshua’s Ai, only Kh. el-Maqatir satisfies all fourteen parameters of the criterial screen, thus providing conclusive evidence that the conquest of Ai narrative is a True Narrative Representation and that Kh. el-Maqatir is the site of the fortress of Ai conquered by Joshua. Key aspects of the evidence include the geographical/topographical context of Kh. el-Maqatir, the configuration of its defensive system, its size, its archaeology, and its total conformity with the requirements of the text in Joshua 7
Online Linear Programming with Uncertain Constraints

There are many applications scenarios in different disciplines where the critical knowledge of decision making arrives in a sequential manner, so the optimization must be done in an online fashion. An important class of online optimization problems that have been extensively studied in the past is online linear programs. This paper tackles a general class of online linear programs that take into account the online arrival of the constraint entries related to the available budget and demand for packing and covering problems. This generalization is motivated by many recent applications on revenue management or resource allocation problems with the unknown and timevarying budget. As the main contribution of this paper, we propose a decoupling strategy that can be used to reduce the general problem into a series of subproblems with constant constraint entries. Using the proposed strategy, one can decouple the general problem, leverage the state-of-the-art algorithms for the online subproblems with fixed constraint entries, and achieve the same performance for the general problem. As for a case study, we apply the strategy to an extension of the one-way trading problem with the dynamic budget.
Protected Geographical Rules to Set Different Path Routing In Manets

Portability and convenient nature of Mobile Ad hoc Networks (MANET) has expanded its prominence by two overlap. MANETs have turned into a usually utilized system for different applications. However, this favorable position endures with genuine security concerns, fundamentally a remote transmission medium viewpoint where such systems might be liable to parcel dropping. Portability and versatile nature of Mobile Ad hoc Network may likewise prompt connection disappointment. Impromptu on interest separate vector (AODV) is a mainstream directing convention however is presented to understood parcel dropping assault. Proposed framework presents another convention named Secured Geographic Routing (SGR), which can honestly identify parcel dropping assault in MANET. SGR can distinguish noxious hubs by recognizing dropping of directing and information bundle. Bundle dropping because of both connection mistake and nearness of malignant hubs can recognize. It additionally gives significance to protect security of information.
Measurement of sportsman ‘ s jump psychomotoric reaction

For representatives of sport games are very important components of physical abilities – spring and rate of psychomotoric reaction. For the following sportsman’s especially important is the rate of psychomotoric reaction, which defines reaction to the constantly changing ambience, similar to the sport action. Testing system, which simulates the situation of sports game, was created in the department of Informatics and biomechanics of LKKA. This system allows estimating the physical capabilities of player – spring and the speed of psychomotoric reaction. The speed of psychomotoric reaction is evaluated by making the jump-up. The influence of the height of jump-up on the spring and speed of reaction of sportsman is investigated. Considering the results of experiments and statistical analysis some recommendations are given and conclusions withdrawn.
Managing Counterparty Risk in OTC Markets

We study how banks manage their default risk to optimally negotiate quantities and prices of contracts in over-the-counter markets. We show that costly actions exerted by banks to reduce their default probabilities are inefficient. Negative externalities due to counterparty concentration may lead banks to reduce their default probabilities even below the social optimum. The model provides new implications which are supported by empirical evidence: (i) intermediation is done by low-risk banks with medium initial exposure; (ii) the risk-sharing capacity of the market is impaired, even when the trade size limit is not binding; and (iii) intermediaries play the fundamental role of diversifying the idiosyncratic risk in CDS contracts, besides increasing the risk-sharing capacity of the market.
Optimized Mapreduce Using Cache for Big Data Analytics

Big data is the ocean of information we swim everyday-zeta bytes of unstructured data and updates are constantly arriving, that cannot be mined efficiently by the traditional tools and methods. To our knowledge MapReduce is the first MapReduce-based solution that efficiently supports incremental iterative computation, which is widely used in data mining applications. It utilizes key-value pair incremental processing rather than task level re-computation. In this paper, we propose an extension to MapReduce using in-memory for mining big data. Compared with the work of MapReduce, MapReduce using in-memory (i) performs key-value pair level processing in map phase based on the mining results of iterative algorithms, (ii)cache the mapped data in the buffer that reduces the i/o workload of the reducer phase. We evaluate the MapReduce task for the mobile datasets of GSMArena websites using the iterative algorithms and cache memory for fast retrieval of data in time.
Momentum pricing and trading , and economic uncertainty regimes

The effects of momentum on excess equity returns are not constant across different regimes of economic uncertainty. They tend to decrease in high uncertainty regimes for portfolios that do not depend significantly on prior returns, and to increase for portfolios that do depend, either negatively or positively. We used a smooth-transition regression framework that allows us to explore the evolving nature of momentum pricing in the context of two beta representations of the equity premium: Fama-French three and five-factor models. Here, economic uncertainty is incorporated as an economic regime that impacts the probability distribution of momentum. Our model considers two extreme states: one of low uncertainty and one of high uncertainty. We also calculate pricing errors of each model under the two regimes. We analyzed 25 value-weighted portfolios sorted according to momentum and size, 100 portfolios sorted according to size and book to market (B/M), and four univariate portfolios according to size, B/M, profitability and investment. In general, the models perform better during regimes of relatively high uncertainty, and those that incorporate momentum perform the best. Nevertheless, this superior performance comes at a cost. The abnormal returns produced by momentum disappear during high uncertainty regimes in the market, its Sharpe ratio goes to zero, the kurtosis of the momentum strategy doubles, and its skewness becomes negative. Our simple recommendation is not to trade momentum when you expect high economic uncertainty. JEL: G12, G14, G02, D81.
Dynamics on Hybrid Complex Network : Botnet Modeling and Analysis of Medical

With the rapid development of Internet of things technology, the application of intelligent devices in themedical industry has become ubiquitous. Connected devices have revolutionized clinicians and patient care but also made modern hospitals vulnerable to cyber attacks. Among the security risks, botnets are of particular concern, which can be used to control thousands of devices for remote data theft and equipment destruction. In this paper, we propose a non-Markovian spread dynamics model to understand the eects of botnet propagation, which can characterize the hybrid contagion situation in reality. Based on the Susceptible-Adopted-Recovered model, we introduce nonredundantmemory spreadmechanism for global propagation, as a tuner to adjust spreading rate dierence. For describing the proposed model, we extend a heterogeneous edge-based compartmental theory. ­rough extensive numerical simulations, we reveal that the growth pattern of the nal adoption size versus the information transmission probability is discontinuous and how the nal adoption size is aected by hybrid ratio α, global scope control factor ε, accumulated received information thresholdT, and other parameters on ER network. Furthermore, we give the theory and simulation result on BAnetwork and also compare the two hybrid methods—single infection in one time slice and double infections in one time slice—to evaluate the inuence on nal adoption size. We found in SIOT hybrid contagion scenario the nal adoption size shows the phenomenon of a decline followed by an increase versus dierent hybrid ratio, and it is both veried in theory and numerical simulation. ­rough validation by thousands of experiments, our developed theory agrees well with the numerical simulations.
CHALLENGES IN APPLICATION OF ICT IN TELEVISION BROADCASTING

This paper examines the application of ICT by broadcast professionals of Nigerian Television Authority, NTA Channel 10, Port Harcourt. The study was carried out to gauge the response of professionals of NTA to the use of ICTs; to ascertain various ways ICT enhances the broadcast process and to find out factors that militate against the use of ICTs by broadcasters of NTA. The survey research design was used for the research employing personal interview and observation technique to collect data qualitatively. The study population consisted of the staff of the engineering department; programmes department; and, news and current affairs department respectively at NTA. Nine staffs of NTA were selected purposively with three from each of the departments as sample. Findings from the research showed that the staffs have responded positively to ICT in the work place although the younger professionals have shown more enthusiasm towards using ICT compared to the older staff. Power failure and high cost of ICT tools and high cost of training are part of the factors militating against the use of ICT by broadcast professionals. The recommendations for this study include making funds available to upgrade ICT facilities, training and retraining broadcast professionals on the ethics and use of ICT resources and providing an effective and efficient power supply system in order to harness the unlimited potentials of ICT in broadcasting today.
WSS 03 Applications , Products and Services of Web-based Support Systems 111

This paper describes an approach to the topic distillation task of TREC-2002 for finding key resources in a 1.25-million-page collection of . gov domain. Content weighting of page body, anchor texts and IR techniques were employed as a primary step. Additionally, page outlinked content and in-link counts were investigated for their ability to improve key resource detection. Output from distillation is a rank list that may come from very few hosts. Users on the other hand might prefer answers that come from diverse sources that would provide a more balanced-view of a topic. We propose host diversification processes to adjust the answer list based on a host-repeat factor and host weights.
Fusion of Various Band Selection Methods for Hyperspectral Imagery

This paper presents an approach to band selection fusion (BSF) which fuses bands produced by a set of different band selection (BS) methods for a given number of bands to be selected, nBS. Since each BS method has its own merit in finding the desired bands, various BS methods produce different band subsets with the same nBS. In order to take advantage of these different band subsets, the proposed BSF is performed by first finding the union of all band subsets produced by a set of BS methods as a joint band subset (JBS). Due to the fact that a band selected by one BS method in JBS may be also selected by other BS methods, in this case each band in JBS is prioritized by the frequency of the band appearing in the band subsets to be fused. Such frequency is then used to calculate the priority probability of this particular band in the JBS. Because the JBS is obtained by taking the union of all band subsets, the number of bands in the JBS is at least equal to or greater than nBS. So, there may be more than nBS bands, in which case, BSF uses the frequency-calculated priority probabilities to select nBS bands from JBS. Two versions of BSF, called progressive BSF and simultaneous BSF, are developed for this purpose. Of particular interest is that BSF can prioritize bands without band de-correlation, which has been a major issue in many BS methods using band prioritization as a criterion to select bands.
Experimental study of the moisture removal capacity of a desiccant wheel activated at low and high temperature

Desiccant dehumidifiers can be combined with refrigeration vapour compression systems to reduce and control the humidity ratio in buildings and certain industrial processes. These combined systems are referred to as hybrid systems. Many studies about hybrid systems with desiccant wheels, DW, have been carried out. In these hybrid systems, a significant energy consumption is required for thermally activate the DW. The objectives of this piece of work are to determine empirically the main variables which influence the moisture removal capacity, MRC, of a DW activated at low and high temperature, and analyse the variability of these on MRC. In order to compare the results obtained for a DW activated at low and high temperature, a secondary objective is to obtain the theoretical cooling energy needed to achieve the supply air set conditions. In this paper, values below 60°C were considered as low regeneration temperatures for a DW and values above 60oC were considered as high regeneration temperatures. The methodology used was based on the statistical technique of design of experiments, DOE, which allows to study the behaviour of DW with a reduced number of experimental tests. The results showed a significant influence of the inlet humidity ratio of the air process and the air regeneration on MRC. Using high regeneration temperatures, the MRC values were found 61% higher than using low regeneration temperatures. However, high regeneration temperatures led to higher process air temperatures and thus more cooling energy was required to achieve the supply air set conditions.
Effective Use of Transformer Networks for Entity Tracking

Tracking entities in procedural language requires understanding the transformations arising from actions on entities as well as those entities’ interactions. While self-attention-based pre-trained language encoders like GPT and BERT have been successfully applied across a range of natural language understanding tasks, their ability to handle the nuances of procedural texts is still untested. In this paper, we explore the use of pre-trained transformer networks for entity tracking tasks in procedural text. First, we test standard lightweight approaches for prediction with pre-trained transformers, and find that these approaches underperform even simple baselines. We show that much stronger results can be attained by restructuring the input to guide the transformer model to focus on a particular entity. Second, we assess the degree to which transformer networks capture the process dynamics, investigating such factors as merged entities and oblique entity references. On two different tasks, ingredient detection in recipes and QA over scientific processes, we achieve state-ofthe-art results, but our models still largely attend to shallow context clues and do not form complex representations of intermediate entity or process state.
Effect on Reducing Untranslated Content by Neural Machine Translation with a Large Vocabulary of Technical Terms

Neural machine translation (NMT), a new approach to machine translation, has achieved promising results comparable to those of traditional approaches such as statistical machine translation (SMT). Despite its recent success, NMT cannot handle a larger vocabulary because the training complexity and decoding complexity proportionally increase with the number of target words. This problem becomes even more serious when translating patent documents, which contain many technical terms that are observed infrequently. Long et al. (2016) proposed a method that enables NMT to translate patent sentences comprising a large vocabulary of technical terms. The proposed NMT system is trained on bilingual data wherein technical terms are replaced with technical term tokens; this allows it to translate most of the source sentences except technical terms. The selected phrases are then replaced with tokens during training and post-translated by the phrase translation table of SMT. Based on the discussion as well as experimental evaluation results reported in Long et al. (2016), this paper further studies the effect of the proposed NMT model with phrase translation by the SMT model with respect to reducing untranslated content. The issue of untranslated content is among those most important problems of NMT. This paper employs the back translation probability which is proposed by Goto and Tanaka (2017) to apply to the task of detecting untranslated content in NMT. Then, we show the evaluation results of both predicting untranslated contents and of manually counting the numbers of words in the input Japanese sentences untranslated into English in the task of Japanese to English NMT, where the proposed NMT model with phrase translation by the SMT model outperforms the baseline NMT model.