Miracle-dz/UniFAR-FTUs huggingface dataset:
The network comprising 61 high-frequency radar systems along the U . S . West Coast ( USWC ) provides a unique , high resolution , and broad scale view of ocean surface circulation

[1] The network comprising 61 high-frequency radar systems along the U.S. West Coast (USWC) provides a unique, high resolution, and broad scale view of ocean surface circulation. Subinertial alongshore surface currents show poleward propagating signals with phase speeds of O(10) and O(100–300) km d 1 that are consistent with historical in situ observations off the USWC and that can be possibly interpreted as coastally trapped waves (CTWs). The propagating signals in the slow mode are partly observed in southern California, which may result from scattering and reflection of higher-mode CTWs due to curvature of shoreline and bathymetry near Point Conception, California. On the other hand, considering the order of the phase speed in the slow mode, the poleward propagating signals may be attributed to alongshore advection or pressure-driven flows. A statistical regression of coastal winds at National Data Buoy Center buoys on the observed surface currents partitions locally and remotely wind-forced components, isolates footprints of the equatorward propagating storm events in winter off the USWC, and shows the poleward propagating signals year round.
Fast Processing of SPARQL Queries on RDF

In this paper, we propose a new approach for fast processing of SPARQL queries on large RDF datasets containing RDF quadruples (or quads). Our approach called RIQ employs a decrease-andconquer strategy: Rather than indexing the entire RDF dataset, RIQ identifies groups of similar RDF graphs and indexes each group separately. During query processing, RIQ uses a novel filtering index to first identify candidate groups that may contain matches for the query. On these candidates, it executes optimized queries using a conventional SPARQL processor to produce the final results. We evaluated RIQ using a synthetic and a real dataset, each containing about 1.4 billion quads, we show that RIQ can outperform RDF-3X and Jena TDB on a variety of SPARQL queries.
Lexical Substitution is Practical for Rare Word Simplification

We attempted to generate a sentence by using the concept of core vocabulary whilst preserving the original meaning of the sentence in the text simpliﬁcation subtask. The correlation between word simplicity and frequency shows that many complex words are less frequently used. Hence, accurately simplifying sentences containing rare words is important in the sim-pliﬁcation task. We explored a simpliﬁcation model that works robustly. The machine translation approach and the lexical substitution were evaluated in the dataset that includes rare words (referred to as RARE) and the dataset that does not include rare words (referred to as NORMAL). The machine translation approach exhibits the best performance in the NORMAL dataset, but it exhibits very poor performance in the RARE dataset.
FC-Perspolis 2012 Soccer 2 D Simulation Team Description Paper

FC-Perspolis is a new soccer 2D simulation team. Most of its members have been participating from 2005 in this field and participated in RoboCup since year 2008 and also achieved 3 place in last 2 years of RoboCup competitions with the name of MarliK team. At this project, we continue to research based on the previous versions of our related papers, teams and researches. This paper describes our recent ideas and main focus of our researches in soccer 2D simulation league which was using data mining methods in our defensive tactics in order to improve behavior of the existing defense system. Besides that, other skills are mainly changed and improved after recent achievements in this league at MarliK.
RAWLS ’ DIFFERENCE PRINCIPLE : EVIDENCE FROM GUATEMALA

While literature indicates that strong intellectual property (IP) protection is needed to attract foreign direct investment (FDI) in developing countries like Guatemala, the literature fails to address adequately the economic, social, and political considerations facing developing nations in the reformation of their IP laws. This article addresses those considerations by applying John Rawls’ Difference Principle. Rawls’ Difference Principle depicts justice as an issue of fairness, which focuses on the distribution of resources and permits an unequal distribution only to the extent that the weakest members of society benefit from that inequality. This article finds that Rawls would reject the findings from the literature and support a weak IP regime in Guatemala for three key reasons. First, economically, Guatemala’s weakest members would have immediate access to otherwise price-prohibitive products. Second, socially, Guatemala could reallocate resources to service Guatemala’s weakest members more pressing needs. Third, politically, Guatemala’s IP weak regime would be entirely consistent with the letter of the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS) and improve relations with its trading partners. According to Rawls, Guatemala’s approach to maintain a weak IP regime would be ethically sound.
LOCALIZATION FOR MIXED NEAR-FIELD AND FAR-FIELD SOURCES BY INTERLACED NESTED ARRAY

In this paper, a localization algorithm for mixed near-field and far-field sources by an interlaced nested array is proposed. The fourth-order cumulants (FOCs) of the received data are used to construct a FOC matrix, by which the angles of all signals can be estimated. Then, an effective method is driven to separate the directions of arrival (DOAs) of near-field and far-field sources without extreme value search. The ranges of the near-field sources can be estimated by one-dimensional (1D) search. Compared with existing nested array-based algorithms, the proposed algorithm can distinguish more sources and has higher estimation accuracy. Some simulation results are shown to certify the superiority of proposed algorithm.
Maximum Entropy Language Models for Information Retrieval

Recent advances in Information Retrieval (IR) have been based on the use of statistical language models for representing documents and viewing querying as a generative process. Documents are ranked based on the likelihood of their language model generating the user query. Significant performance improvements have been achieved over vector space and probabilistic models by using only unigram language models (based on term occurrence counts) and smoothing techniques. Experiments with additional features like bigrams have met limited success in information retrieval. However language models incorporating n-gram and word trigger features have shown improved performance in speech recognition applications. It is proposed to demonstrate and evaluate the usefulness of feature-rich language models in information retrieval. The language models proposed till date for information retrieval are based on linear interpolation or mixture models. They are in the form of corpus-smoothed unigram or smoothed bigram-unigram language models. While mixture models are easy to implement, they seem to make suboptimal use of their components. A natural method of combining information sources based on the Maximum Entropy Principle has been shown to contribute significantly to perplexity reduction and hence better language models for speech recognition. It is proposed that such a framework designed for information retrieval will provide a better mechanism for incorporating external knowledge and additional syntactic and semantic features of the language in language models for IR. Most published research on the language modeling approach to IR have been based on techniques that have been experimented with in speech recognition. However, Speech recognition and information retrieval have differing language modeling requirements. For example, in speech recognition the utterances information retrieval and retrieval of information should be distinguished; whereas they should have same representation for efficient information retrieval. This dissertation will identify IR specific features and characterize the language models designed for information retrieval.
Correlation of Cetacean Stranding Events between 2010-2014 at the Romanian Coast (

The current study presents data from research conducted at the Romanian coast, for the period May 2010 December 2014. Stranding data were obtained mainly through the national stranding network established by the “Mare Nostrum“ NGO in collaboration with the Water Administration authorities. The database of “Mare Nostrum“ NGO contains 451 records. Stranding data refer to number of animals stranded and not to multiple stranding events. It reveals an analysis of cetacean stranding along the entire shore and puts in front the correlations between natural and unnatural mortality, on gender and age stages. In the Black Sea, cetaceans are represented by three species, Phocoena phocoena relicta, Tursiops truncatus ponticus and Delphinus delphis ponticus. The main threat and cause of decline for the Black Sea dolphins are the fishing nets, the so-called by-catches. For the protection and conservation of the dolphin populations from the Romanian Black Sea area in conformity with the objectives of the “National Action Plan for Conservation of Dolphins“ and the “Agreement on the Conservation of Cetaceans of the Black Sea, Mediterranean Sea and contiguous Atlantic Area“, NGO “Mare Nostrum“ developed a Monitoring program called “Monitoring and conservation of Black Sea dolphins” in partenership with the National Institute for Marine Research and Development “Grigore Antipa“ Constanta, the Danube Delta Biosphere Reserve Authority, the National Agency for Fisheries and Aquaculture, the Natural Science Museum Complex “Dolphinarium“ Constanta, the Border Police Inspectorate of Constanta County, ACCOBAMS and international partners.
POS Tagging For Code-Mixed Indian Social Media Text : Systems from IIIT-H for ICON NLP Tools Contest

This paper describes Part-of-Speech (POS) tagging systems submission for POS Tagging For Code-mixed Indian Social Media Text contest taking place at ICON-15. Our system uses linguistically motivated language specific as well as generic features to train the CRF sequence labeling algorithm. There were three language pairs, namely Hindi-English (Hi-En), Bengali-English (Bn-En) and Tamil-English (Ta-En), for each of which two submissions, constrained and unconstrained, could be made. Our main focus was on systems for Hi-En language pair. We submitted constrained systems for all the three language pairs and unconstrained system only for Hi-En. Our constrained system for Bn-En and Ta-En preformed the best while Hi-En performed third best. Our unconstrained system for Hi-En performed the best with 80.68% accuracy while the second best performed with 77.60%. Our submission was declared overall contest winner.
Supplementary material for Learning to Adapt for Stereo

In Sec. 1 we provide additional implementation details concerning the loss used for unsupervised online adaptation, the conﬁdence network and the training procedure of the disparity estimation network. Later in Sec. 2 we give more experimental results on various components of our method that further conﬁrm the ﬁndings of the main paper
An Image Based Defogging Using Dark Channel :

Defogging is removing pollutant particles from an image, pollutant particles such as rain, fog, shadows occurred from the building. Dilapidation in visibility is introduced to images or a video captured in poor weather this causes defogging in an image. In this paper, the Gaussian-based dark channel is proposed to the hazy images. The RGB and estimated transmission is computed to the haze image further the filter called Laplacian is computed to the image, thus overall image is enhanced by formulating the proposed method.
Parameter Analysis and Optimization of Electrolytic In-Process Dressing Grinding on Ceramics

Ceramic materials have been studied and used in considerable industrial applications due to their high hardness and strength at high temperature and extreme wear resistance. However, the machining costs of these materials may reach as high as 90% of their total component costs and the grinding of these materials are much more susceptible to surface damage as compared to metals. Electrolytic InProcess Dressing (ELID) grinding can be used to machine hard and brittle materials, such as aluminum oxide (Al2O3), that are difficult to be machined by conventional grinding processes to achieve high surface quality and high material removal rate. The effect of each major machining parameter in processing Al2O3 on the surface roughness and material removal rate were analyzed and presented. Furthermore, by using the process models built with Neuro-fuzzy theory, an optimization algorithm is constructed for multiple objectives and which incorporates tournament sharing selection and G-bit local search is applied to find the machining parameters for achieving the best product quality and/or production rate.
Lossless Text Compression Technique Based on Static Dictionary for Unicode Tamil Document

Text compression is an effective technique that reduces the data storage and also increases the data transfer rate during communication. This paper explains a new method of lossless text compression technique for Tamil documents made of Unicode Tamil characters. The method of compression and decompression process using static dictionary compression scheme is presented. This compression technique reduces the Tamil document an average of 50% of its storage capacity. The original document is retained in the decompression process. Keywords-Text compression, decompression, Unicode and ASCII.
Genetic Variation amongst Four Rabbit Populations I Nigeria Using Microsatellite Marker

Seven microsatellite markers were used with 100 genomic deoxyribonucleic acid (DNA) isolated from New Zealand White, New Zealand Red, Californian White and Chinchilla rabbit breeds in Nigeria to determine genetic variation amongst the breeds. Power of microsatellite markers i.e., Combined Exclusion Probabilities (CEP) and Polymorphism Information Content (PIC) of markers; were determined to ascertain the informativeness of the markers. Equal number of samples (that is, 25 samples) was obtained from each of the rabbit population. Polymerase chain reaction (PCR) was carried out using each marker, isolated DNA, and double distilled water and PCR Master Mix. PCR products generated were subjected to polyacrylamide gel electrophoresis on an ABI 3730 DNA Sequencer. DNA bands were scored based on size of ladder with Gene Scan 3.1. 2. Bands obtained were designated as alleles and prepared into Excel Worksheet. With Microsatellite Analyser version 4.05 software and allele frequencies were generated. Mean inbreeding coefficient across loci (FIS) was -0.0201 and average genetic differentiation (FST) among breeds was 0.0479. Seventy nine alleles of which 18.98% were rare and 81.02% represent fixed alleles across the rabbit populations were observed. PIC per marker across populations ranged from 0.6800 (SAT 8) to 0.8100 (SOL 28) indicating that the markers were informative (PIC â¥ 0.50). CEP across markers and populations was 0.999999, meaning that the selected microsatellite markers were suitable for parentage verification of these four rabbit breeds.
Web Based Tool for Measuring Coupling in Object-Oriented Software Modules

: Coupling measurement in object-oriented software is becoming an important area day by day from the software quality evaluation point of view. Coupling is an interdependence relationship between classes (modules) of object-oriented software. The coupling measurement helps to maintain dependency degree between modules of object-oriented software. The moderate coupling values result in quality software. Ultimately quality software retains moderate range of values of software quality attributes such as complexity, efficiency, reusability, maintainability, understandability, flexibility, portability, interoperability, etc. This paper proposes a web based tool for measuring coupling in object-oriented Java software. The idea of a web based tool is to deploy a software coupling tool on intranet or cloud to give access to the prescribed users. The tool can be used online to compute coupling and the resulting data of the tool can be sent/received via the public network. The detailed architecture and components of the tool are described in the paper. The tool is most secured for input processing. The Java and Android projects are evaluated using the tool, the coupling values of Java and Android projects are compared in the results and discussion section of the paper. The Advantages of using the web based tool are also described in the paper. Seven coupling metrics are used from the literature to compute their values using web based tool proposed in this paper. Percentage coupling values of seven coupling metrics are computed for Java and Android projects. The percentage range of coupling values computed in the paper using web based tool is compared with standard range of coupling values described in the literature. The results obtained using web based tool gives us coupling values of Java and Android projects. The coupling values obtained using web based tool proposed in the paper are compared with standard coupling values described in the literature. It is found that the values obtained using the web based tool, are within the standard range of coupling values described in the literature. It means the web based tool proposed in this paper calculates correct coupling values of any object-oriented Java code.
A Case Study on 21st Century Skills Development Through a Computer Based Maths Game

The new technology developments that are emerging on the market demand re-skilling and updating competencies thus enabling people to adapt to new expectations in the 21st century workplace and life. Therefore, the education system should also prepare learners for lifelong learning through development of 21st century skills. Recent research on mathematics education also shows that for many students, math is not considered an easy subject and students are facing difficulties in developing logical thinking and problem solving skills. This paper introduces “Count With Me! ”, a novel educational computer based video game that teaches maths concepts. An investigation on how the game supports the development of learners’ 21st century skills such as problem solving, self-directed learning, knowledge building and digital literacy is presented. The results of a case study in a 3rd level educational institution show that the large majority of students that took part in the case study acquired 21st century skills. 96.97% of students believed that the Count With Me! game helped them to develop their problem solving skills. 82.82% of students liked self-pacing themselves through the game based educational material. 78.78% of students agreed that the maths game has improved their knowledge and 81.81% of students were satisfied with their achievements in the game.
Drone Communication Networks for Resilient Smart Cities View project

This paper studies the performance of cooperative wireless networks using incrementalrelaying and dual transmit diversity with the simple orthogonal space time block coding (OSTBC) scheme. The proposed model is studied by utilizing different relaying schemes including decode and forward (DF), amplify and forward (AF), and adaptive incrementalrelaying (i.e., best relay selection) with DF relaying. In particular, upper-bounded expressions are derived for the average bit error rate (BER), signal to noise ratio (SNR) outage probability, average achievable rate, and normalized throughput. Detailed results show that the dual transmit diversity approach outperforms the regular incremental relaying cooperative diversity scheme in terms of transmission power and channel efficiency for the same transmit power. Moreover, best relay selection with multiple relaying nodes outperforms fixed incremental DF relaying, especially for lower transmitted SNR values. © 2016 Elsevier Ltd. All rights reserved.
Massive MIMO channel modelling for 5G wireless communication systems

Massive Multiple-Input Multiple-Output (MIMO) wireless communication systems, equipped with tens or even hundreds of antennas, emerge as a promising technology for the Fifth Generation (5G) wireless communication networks. To design and evaluate the performance of massive MIMO wireless communication systems, it is essential to develop accurate, flexible, and efficient channel models which fully reflect the characteristics of massive MIMO channels. In this thesis, four massive MIMO channel models have been proposed. First, a novel non-stationary wideband multi-confocal ellipse Two-Dimensional (2-D) Geometry Based Stochastic Model (GBSM) for massive MIMO channels is proposed. Spherical wavefront is assumed in the proposed channel model, instead of the plane wavefront assumption used in conventional MIMO channel models. In addition, the Birth-Death (BD) process is incorporated into the proposed model to capture the dynamic properties of clusters on both the array and time axes. Second, we propose a novel theoretical non-stationary Three-Dimensional (3-D) wideband twin-cluster channel model for massive MIMO communication systems with carrier frequencies in the order of gigahertz (GHz). As the dimension of antenna arrays cannot be ignored for massive MIMO, nearfield effects instead of farfield effects are considered in the proposed model. These include the spherical wavefront assumption and a BD process to model non-stationary properties of clusters such as cluster appearance and disappearance on both the array and time axes. Third, a novel Kronecker Based Stochastic Model (KBSM) for massive MIMO channels is proposed. The proposed KBSM can not only capture antenna correlations but also the evolution of scatterer sets on the array axis. In addition, upper and lower bounds of KBSM channel capacities in both the high and low Signal-to-Noise Ratio (SNR) regimes are derived when the numbers of transmit and receive antennas are increasing unboundedly with a constant ratio. Finally, a novel unified framework of GBSMs for 5G wireless channels is proposed. The proposed 5G channel model framework aims at capturing key channel characteristics of certain 5G communication scenarios, such as massive MIMO systems, High Speed Train (HST) communications, Machine-to-Machine (M2M) communications, and Milli-meter Wave (mmWave) communications. To my family and colleagues
Speeding-up convolutional neural networks: A survey

Convolutional neural networks (CNN) have become ubiquitous in computer vision as well as several other domains, but the sheer size of the modern CNNs means that for the majority of practical applications, a significant speed up and compression are often required. Speeding-up CNNs therefore have become a very active area of research with multiple diverse research directions pursued by many groups in academia and industry. In this short survey, we cover several research directions for speeding up CNNs that have become popular recently. Specifically, we cover approaches based on tensor decompositions, weight quantization, weight pruning, and teacher-student approaches. We also review CNN architectures designed for optimal speed and briefly consider automatic architecture search.