Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple sequence alignment – the gateway to further analysis

Whether the ultimate aim is a phylogenetic analysis of several orthologues, the identification of a pattern for particular feature or motif, or the basis for structural modelling, multiple sequence alignments allow the researcher to gather more biological information than a single sequence can offer. Possibly the most popular method for comparing three or more sequences is the clustering algorithm used in applications such as the Clustal (ClustalW and ClustalX) series of programs. It is certainly by no means the only method of alignment, but will be used to illustrate this text. Initial clustering of sequence pairs reduces the computing time required to align multiple sequences and this can be achieved using one of two possible methods. Slow clustering is the more rigorous of the two options, but is noticeably much slower for approximately 20 or more sequences, or fewer, longer regions. It uses the dynamic programming method of Needleman–Wunsch to align each sequence with another according to a weight matrix and gap penalties. The ultimate aim of the computer program is to achieve the highest score possible, within the constraints the program has been placed under. Weight matrices have been developed using homologous sequences, and allocate a score to each residue or nucleotide base indicating the probability of it replacing a different residue or nucleotide base as a possible mutation. In the case of protein sequences, this has been done for all 20 amino acid residues, together with the three ambiguity codes (B 1⁄4 Asp and Asn, Z 1⁄4 Glu and Gln, X 1⁄4 any residue) using several different methods. Nucleotide matrices have also been developed, and in general indicate a positive score for an identical match, and no score, or a negative one for a mismatch. Because of its very nature, and the existence of only four common bases, more information for the alignment can be obtained by using protein sequences, and it often makes sense to translate regions of coding DNA into protein sequence before aligning them. Once a high score has been achieved for each of the sequence pairs in the alignment, they are clustered together in accordance with their relative scores, using the neighbour-joining method to link the closest pairings together, and less similar sequences more remotely. This information is stored as a series of numerical distances arranged by means of nested brackets in a dendrogram file. This file is in no way representative of evolutionary distances, and should not be presented as such. It merely represents the proximity of each sequence within a cluster, and each cluster to another and is used to form the final alignment. The information retained in the dendrogram file may be kept and used to align other multiple sequence sets. Larger sequence volumes may be compared using a faster method, in order to reduce computing time. This is based on the algorithm of Wilbur and Lipman and is quicker but less accurate than the dynamic programming methods of the slow comparison. It involves definition of
International Journal of Geographical Information Science

Earth science research and applications usually use Distributed Geospatial Information Processing (DGIP) services and powerful computing capabilities to extract information and knowledge from large volumes of distributed geospatial data. Conceptually, such processing can be abstracted into a logical model that utilizes geospatial domain knowledge to produce new geospatial products. Using this idea, the geo-tree concept and the proposed geospatial Abstract Information Model (AIM) have been used to develop a Grid workflow engine complying with geospatial standards and the Business Process Execution Language. Upon a user’s request, the engine generates virtual geospatial data/information/knowledge products from existing DGIP data and services. This article details how to (1) define and describe the AIM in XML format, (2) describe the process logically with an AIM, including the geospatial semantic logic, (3) conceptually describe the process of producing a particular geospatial product step by step from raw geospatial data, (4) instantiate AIM as a concrete Grid-service workflow by selecting the optimal service instances and data sets, and (5) design a Grid workflow engine to execute the concrete workflows to produce geospatial products. To verify the advantages and applicability of this Grid-enabled virtual geospatial product system, its performance is evaluated, and a sample application is provided.
KOF Working Papers

As the first to use an archival data set on historical land values of Berlin, Germany, from 1890 to 1936, we exploit exogenous variation in transport technology in order to test the validity of the monocentric city model. Endogenously determining the CBD, we conduct cross-section and timedifference analysis and model the land gradient in terms of straight-line distance and travel times. A counterfactual scenario indicates that a large proportion of urban decentralization is attributable to improvements in transport infrastructure. Controlling for spatial dependency, results suggest that the monocentric model fitted the city structure until the mid 20 century.
Distributional Clustering of Words for Text Classi cation

This paper describes the application of Dis tributional Clustering to document classi cation This approach clusters words into groups based on the distribution of class labels associated with each word Thus unlike some other unsupervised dimensionality reduction techniques such as Latent Semantic Indexing we are able to compress the feature space much more aggressively while still maintaining high document clas si cation accuracy Experimental results obtained on three real world data sets show that we can reduce the feature dimen sionality by three orders of magnitude and lose only accuracy signi cantly better than Latent Semantic In dexing class based clustering feature selection by mutual information or Markov blanket based fea ture selection We also show that less aggressive clustering sometimes results in improved classi cation accuracy over classi cation without clustering
Low-Resource Machine Transliteration Using Recurrent Neural Networks of Asian Languages

Grapheme-to-phoneme models are key components in automatic speech recognition and text-to-speech systems. With low-resource language pairs that do not have available and well-developed pronunciation lexicons, grapheme-to-phoneme models are particularly useful. These models are based on initial alignments between grapheme source and phoneme target sequences. Inspired by sequence-to-sequence recurrent neural network-based translation methods, the current research presents an approach that applies an alignment representation for input sequences and pre-trained source and target embeddings to overcome the transliteration problem for a low-resource languages pair. We participated in the NEWS 2018 shared task for the English-Vietnamese transliteration task.
An Error Handling Framework for the ORBWork Work(cid:13)ow Enactment Service of METEOR

Work(cid:13)ow Management Systems (WFMSs) can be used to re-engineer, streamline, automate, and track organizational processes involving humans and automated informationsystems. However, the state-of-the-art in work(cid:13)ow technology su(cid:11)ers from a number of limitations that prevent it from being widely used in large-scale mission critical applications. Error handling is one such issue. What makes the task of error handling challenging is the need to deal with errors that appear in various components of a complex distributed application execution environment, including various WFMS components, work(cid:13)ow application tasks of di(cid:11)erent types, and the heterogeneous computing infrastructure. In this paper, we discuss a top-down approach towards dealing with errors in the context of ORBWork, a CORBA-based fully distributed work(cid:13)ow enactment service for the METEOR2 WFMS. The paper discusses the types of errors that might occur including those involving the infrastructure of the enactment environment, system architecture of the work(cid:13)ow enactment service. In the context of the underlying work(cid:13)ow model for METEOR, we then present a three-level error model to provide a uni(cid:12)ed approach to speci(cid:12)cation, detection, and runtime recovery of errors in ORBWork. Implementationissues are also discussed. We expect the model and many of the techniques to be relevant and adaptable to other WFMS implementations.
Anchoring of rice BAC clones to the rice genetic map in silico

A wealth of molecular resources have been developed for rice genomics, including dense genetic maps, expressed sequence tags (ESTs), yeast artificial chromosome maps, bacterial artificial chromosome (BAC) libraries and BAC end sequence databases. Integration of genetic and physical maps involves labor-intensive empirical experiments. To accelerate the integration of the bacterial clone resources with the genetic map for the International Rice Genome Sequencing Project, we cleaned and filtered the available EST and BAC end sequences for repetitive sequences and then searched all available rice genetic markers with our filtered databases. We identified 418 genetic markers that aligned with at least one BAC end sequence with >95% sequence identity, providing a set of large insert clones with an average separation of 1 Mb that can serve as nucleation points for the sequencing phase of the International Rice Genome Sequencing Project.
NWU-CS-05-06 April 14 , 2005 VSched : Mixing Batch And Interactive Virtual Machines Using Periodic Real-time Scheduling

We are developing Virtuoso, a system for distributed computing using virtual machines (VMs). Virtuoso must be able to mix batch and interactive VMs on the same physical hardware, while satisfying constraints on responsiveness and compute rates for each workload. VSched is the component of Virtuoso that provides this capability. VSched is an entirely user-level tool that interacts with the stock Linux kernel running below any type-II virtual machine monitor to schedule all VMs (indeed, any process) using a periodic real-time scheduling model. This abstraction allows compute rate and responsiveness constraints to be straightforwardly described using a period and a slice within the period, and it allows for fast and simple admission control. This paper makes the case for periodic real-time scheduling for VM-based computing environments, and then describes and evaluates VSched. It also applies VSched to scheduling parallel workloads, showing that it can help a BSP application maintain a fixed stable performance despite externally caused load imbalance. Effort sponsored by the National Science Foundation under Grants ANI-0093221, ACI0112891, ANI-0301108, EIA-0130869, and EIA-0224449, and aided by support from VMware and Dell. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation (NSF), VMware, or Dell.
A computational memory and processing model for prosody

This thesis links processing in working memory to prosody in speech, and links different working memory capacities to different prosodic styles. It provides a causal account of prosodic differences and an architecture for reproducing them in synthesized speech. The implemented system mediates text-based information through a model of attention and working memory. The main simulation parameter of the memory model quantifies recall. Changing its value changes what counts as given and new information in a text, and therefore determines the intonation with which the text is uttered. Other aspects of search and storage in the memory model are mapped to the remainder of the continuous and categorical features of pitch and timing, producing prosody in three different styles: for small recall values, the exaggerated and sing-song melodies of children's speech; for mid-range values, an adult expressive style: for the largest values, the prosody of a speaker who is familiar with the text, and at times sounds bored or irritated. In addition, because the storage procedure is stochastic, the prosody from simulation to simulation varies, even for identical control parameters. As with human speech, no two renditions are alike. Informal feedback indicates that the stylistic differences are recognizable and that the prosody is improved over current offerings. A comparison with natural data shows clear and predictable trends although not at significance. However, a comparison within the natural data also did not produce results at significance. One practical contribution of this work is a text mark-up schema consisting of relational annotations to grammatical structures. Another is the product—varied and plausible prosody in synthesized speech. The main theoretical contribution is to show that resource-bound cognitive activity has prosodic correlates, thus providing a rationale for the individual and stylistic differences in melody and rhythm that are ubiquitous in human speech. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Developing Citizen Centric Application using GSM

As world development goes in increasing order, people requirement related to their lifestyle is increased. Internet of things (IOT) is a paradigm which helps in completing their requirements. In IOT, The System uses the concept smart city for enhancing the quality of life style. The System proposed to develop two models automatic street light and smart parking. These models are one of the parts in smart city development. Street light is flexible-lighting technology. The System can control the power consumptions at the streets and eliminating manpower. The System propose to implement this model using sensors, LDR and Microcontrollers. Second model The System proposed to implement is Smart parking, which aims to present an intelligent system for parking space detection based on image processing technique. This technique will detect the exact parking space in parking area without wasting any time in search of the vacant place.
Which actress played character Amy Squirrel on Bad Teacher WDT

Templates are an important asset for question answering over knowledge graphs, simplifying the semantic parsing of input utterances and generating structured queries for interpretable answers. Stateof-the-art methods rely on hand-crafted templates with limited coverage. This paper presents QUINT, a system that automatically learns utterance-query templates solely from user questions paired with their answers. Additionally, QUINT is able to harness language compositionality for answering complex questions without having any templates for the entire question. Experiments with different benchmarks demonstrate the high quality of QUINT.
Scenario-based Performance Analysis of Routing Protocols for Mobile Ad-hoc Networks

are made on a scenario where nodes moves randomly. Results are presented as a function of a novel mobility metric designed to reflect the relative speeds of the nodes in a scenario. Furthermore, three realistic scenarios are introduced to test the protocols in more specialized contexts. In most simulations the reactive protocols (AODV and DSR) performed significantly better than DSDV. At moderate traffic load DSR performed better than AODV for all tested mobility values, while AODV performed better than DSR at higher traffic loads. The latter is caused by the source routes in DSR data packets, which increase the load on the network.
GRAM++ - An indigenous GIS software suite demonstration

This article describes the development of a GIS tool GRAM++ (Geo Referenced Area management) using object oriented methodology. The package has all intrinsic functional capabilities to edit, handle and analyze spatial, nonspatial and remote sensing data and works on Windows95 , 98 and NT platforms. Taking advantage of the modular nature of the package, different functions of GRAM++ have been bundled with customized features to develop separate tools for meeting specific end-user needs. GRAM++ Suite comprises of GRAM++ package, Data Preparation Tool, Raster Analysis Kit, Vec-Viewer, MapEditLite and Mapping Control Tools. In addition a CD-Rom based self training generate GIS Tutor has also been developed.
In silico analysis of bacterial translation factors reveal distinct translation event speci�c pI values

Protein synthesis is a cellular process that takes place through the successive translation events within the ribosome with the help of the event-speci�c protein factors, namely, initiation, elongation, release, and recycling factors. The translation process is fundamental to all organisms living in the wide variety of environments. In this regard, we asked the questions about how similar are those translation factors to each other from a wide variety of bacteria? Hence, we did a thorough in silico study of the translation factors from 495 bacterial sp. , and 4262 amino acid sequences, wherein we theoretically measured their pI and MW values that are the two determining factors for distinguishing individual proteins in 2D gel electrophoresis. Then we analyzed the output from various angles. the pI of translation are translation event We found that the translation initiation factors are mainly basic, whereas, elongation and release factors that interact with the inter-subunit space of the intact 70S ribosome during translation are strictly acidic. Further analysis revealed that the acidic property of those factors is due to the higher frequencies of glutamic acids. However, two translation factors, the translation initiation factor 2 (IF2) and the ribosome recycling factor (RRF) showed variable pI values. Remarkably, the variability of the pI values of these two factors showed distinct lineage with the order of phylogeny.
Project-Team icare Instrumentation, Commande et Architecture des Robots Évolués

to generalize the study to trains of more than two vehicles, with extensions to vehicles mechanically hooked together (trucks with trailers, for instance). The second subject addresses autonomous and semi-autonomous navigation (assistance to driving) of the CyCab by using information data provided by visual or telemetric sensors. This is closely related to the problem of a vehicle moving in an urban environment with its speciﬁc aspects of localization, path planning and following, subjected to stringent safety constraints (detection of pedestrians and obstacles) within large and evolutive structured environments.
Register-sensitive Translation : A Case Study of Mandarin and Cantonese Tak sumWong

This paper describes an approach for translation between Chinese dialects that can produce target sentences at different registers. We focus on Mandarin as the source language, and Cantonese as the target. Mutually unintelligible, these two varieties of Chinese exhibit differences at both the lexical and syntactic levels, and the extent of the difference can vary considerably depending on the register of Cantonese. Since only a modest amount of parallel data is available, we adopt a knowledge-based approach and exploit lexical mappings and syntactic transformations from linguistics research. Our system parses a source sentence, uses register-annotated lexical mappings to translate words, and then performs word reordering through syntactic transformations. Evaluation shows that translation models that match the required register of the target sentences yield better translation quality.
Simulated Water Well Performance on Mars

This paper describes improvements in our understanding of the nature and location of massive ice sheets on the surface of Mars as well as refinements made to a technical approach for extracting significant quantities of water from these ice sheets using a technique known as a Rodriguez Well. Recently published discoveries on Mars have reinforced the evidence for the existence and structure of these massive buried ice sheets. Using this improved understanding of the feedstock material, this paper describes estimates made regarding basic characteristics – mass, power, configuration, etc. – of a system that can access and extract water from these ice sheets. This paper then summarizes the basic operation of a Rodriguez Well and describes a computer simulation used to estimate the performance characteristics of this type of well. This simulation was built and used to predict the performance of similar wells operated in the Earth’s Arctic and Antarctic regions. However, physical parameters (e.g., specific heat and gas constant for air, heat transfer between water and air and between ice and air, etc.) used in the simulation represent a terrestrial environment and must be adjusted for a Martian environment. A pair of experiments designed to determine the appropriate values for these parameters under Martian conditions are described. Until results from these experiments are available, published results from other sources are used in the simulation to gain an understanding of the effect that could be seen. These provisional results are discussed.
Applied Computer Science, vol

In order to reduce costs of experimental research, new methods of forecasting material properties are being developed. The current intensive increase in computing power motivates to develop the computer simulations for material properties prediction. This is due to the possibility of using analytical and numerical methods of homogenization. In this work calculations for predicting the properties of WPC composites using analytical homogenization methods, i.e. Mori-Tanaka (first and second order) models, Nemat-Nasser and Hori models and numerical homogenization methods were performed.
High‐tech valuation: should artificial neural networks bypass the human valuer?

Compares the predictive performance of artificial neural networks to hedonic pricing models, a more traditional valuation tool. The results document similar predictive performance evidenced from both techniques, which contradicts some of the earlier studies which support a position of artificial neural network superiority. Demonstrates that at least 18 per cent of the “normal” property predictions and over 70 per cent of the “outlier” property predictions contained valuation errors greater than 15 per cent of the actual sales price. The combination of these substantial errors and the model‐optimization costs incurred motivate a message of caution before artificial neural networks are adopted by the real estate valuation and/or lending industries.
Themis: Ambiguity-Aware Network Intrusion Detection based on Symbolic Model Comparison

ACM Reference Format: Zhongjie Wang∗, Shitong Zhu§, Keyu Man§, Pengxiong Zhu§, Yu Hao§, Zhiyun Qian§ and Srikanth V. Krishnamurthy§, Tom La Porta†, and Michael J. De Lucia‡. 2021. Themis: Ambiguity-Aware Network Intrusion Detection based on Symbolic Model Comparison. In Proceedings of the 8th ACM Workshop on Moving Target Defense (MTD ’21), November 15, 2021, Virtual Event, Republic of Korea. ACM, New York, NY, USA, 2 pages. https: //doi.org/10.1145/3474370.3485669