Miracle-dz/UniFAR-FTUs huggingface dataset:
Harnessing Unlabeled Examples through Iterative Application of Dynamic Markov Modeling

We describe the application of dynamic Markov modeling - a sequential bit-wise prediction technique - to labeling email cor- pora for the 2006 ECML/PKDD Discovery Challenge. Our technique involves: (1) converting the corpora's bag-of-words representation to a sequence of bits; (2) using logistic regression on the training data to induce an initial maximum likelihood classifier; (2) combining all test sets into one; (3) ordering the combined set by decreasing magnitude of the log-likelihood ratio; (4) iteratively applying dynamic Markov model- ing (DMC) to compute successive log-likelihood estimates; (5) averaging successive estimates to form an overall estimate; (6) partitioning the combined estimates into separate results for each test set. Post-hoc ex- periments showed that: (a) the iterative process improved on the initial classifier in almost all cases; (b) treating each test set separately yielded nearly indistinguishable results.
Shaping up the protein folding funnel by local interaction: lesson from a structure prediction study.

Predicting protein tertiary structure by folding-like simulations is one of the most stringent tests of how much we understand the principle of protein folding. Currently, the most successful method for folding-based structure prediction is the fragment assembly (FA) method. Here, we address why the FA method is so successful and its lesson for the folding problem. To do so, using the FA method, we designed a structure prediction test of "chimera proteins. " In the chimera proteins, local structural preference is specific to the target sequences, whereas nonlocal interactions are only sequence-independent compaction forces. We find that these chimera proteins can find the native folds of the intact sequences with high probability indicating dominant roles of the local interactions. We further explore roles of local structural preference by exact calculation of the HP lattice model of proteins. From these results, we suggest principles of protein folding: For small proteins, compact structures that are fully compatible with local structural preference are few, one of which is the native fold. These local biases shape up the funnel-like energy landscape.
Urban Multi-Layered Chord for P2P over vehicular network

Vehicular network is different from wired network due to its network environment changes rapidly. The connection lifetime between vehicles is usually short because vehicles move in high speeds. Hence, deploy peer-to-peer (p2p) applications over vehicular network is a challenging research issue. There are many problems confronted in p2p file sharing, e.g. how to search files effectively, how to share files with distant vehicles, how to fully utilize the limited bandwidth, etc. In this paper, we propose an infrastructure-based Urban Multi-Layered Chord (UML-Chord) architecture for p2p file sharing over an urban vehicular network. In this architecture, vehicles are grouped into clusters. A multi-layer chord is employed to manage both files information and clustered vehicles locations. Connection lifetime between vehicles is estimated on a traffic aware basis. Target vehicle selection considers connection lifetime, bandwidth, and vehicle transmission status. Simulations results show that UML-Chord outperforms Chord, clustered organization and overlay based approaches in terms of number of hops (per query), control message overhead, query delay time, average download time, and file complete ratio.
Application of Edge Detection on Large Lump Detection

Detecting large lumps of oil sand is a critical step which protects exploitation facilities from jamming. This report presents a method that detects large lumps with edge detection and edge classification. The approach applies Gaussian based local scale control algorithm to detect edges in oil sands, then extracts intensity features as well as geometry features for edge classification. Trained with manually selected ground truth, the k nearest neighbour classifier will distinguish edges of large lumps out of edges of fine fragments. Finally, large lumps of oil sands can be located with classified edges. Since large lumps are often merged in a pile of fine fragments, it is quite difficult to get the complete shape of this kind of oil sands. The main contribution of this approach is detecting large lumps only with edge information, which is much easier to get.
TRANSITIVITY AND IDEOLOGY IN DONALD TRUMP CAMPAIGN SPEECH

Political speech is often being a topic of research in linguistic. Some of interdisciplinary studies appeared while the role of the language has developed. They are pragmatics, critical discourse analysis, phsycholingustics, neurolinguistics and sociolinguistics. This research focused on the transitivity system and ideology in Donald Trump Speech Campaign. Transitivity System that stated by Halliday become a tool to analyze the linguistic data which this theory has been used by Fairchlough in his critical discourse analysis. Based on the aims of this research that described transitivity system and ideology of Donald Trump speech campaign, therefore this research called descriptive research. Method of collecting data is method of seeing and noted technique. Technique purposive sampling is used in this research. The result showed that there are six types of process is used by Donald Trump to represent his experience, those are material process, relational process, mental process, verbal process, behavioral process, existential process. Material process is mostly used by Donald Trump followed by relational process and then mental process. To show his ideas, Donald Trump used material process mostly and showed his principal that better do action than only talk. To draw attention of US society and influenced their thought, Donald Trump is often used rasism issue in his speech campaign such as limit the access of immigrant in working and list the muslims US in separated database. Beside that, some of his statements showed that he is a narsistic. He showed his love and proud of himself mostly and he has protectionism in economy.
Constraint logic programming and mu-calculus

A wide range of problems such as static program analysis and symbolic verii-cation induces the need for an evaluation mechanism of xed point, and thus, a certain form of quantiication over relations. Many specialized tools (MVL 7], MEC 1], . .) exist, mainly based upon the mu-calculus formalism 9]. On the one hand, while generally ooering good performances, these tools use their own syntaxes, and are restricted to particular applications. On the other hand, Constraint Logic Programming languages are easy to use, give compact source code, provide friendly development platforms with lots of useful libraries, but often suuer from poor performances and lack of features such as second order quantiication and explicit manipulation of relations. The purpose of the work described in this paper is to take the best of the two approaches, more precisely, to integrate a solver of xed point equations, based on the-calculus, into a well known and open Prolog environment : SICStus Prolog. This work originate in the Toupie 10] project. Toupie is a constraint language designed on an extension of-calculus over symbolic nite domain, which provide full universal and existential quantiication and allow the deenition of relations as xed point of equations. We will rst describe the module which has been implemented, then give some results obtained for groundness analysis of logic programs and nally propose promising extensions to this work. 2 The module We chose to implement this solver of xed point equations as a SICStus Prolog module. The SICStus Prolog environment provides a lot of libraries (terms, AVL trees,. .). Especially, it has a boolean constraints solver 4], coded as a module, and using the ordered binary decision diagram (OBBD) 2, 3] data structure. Techniques of representation of boolean relations and formulas of-calculus using BDDs (and their extensions) have proved to be eecient 6, 10]. It was thus convenient for us to use the BDD primitive of the boolean constraint solver in order to represent our formulas.
Design of Reconfigurable and Adjustable Wireless CORDIC Single Core Rake Receiver

In wireless communication system transmitted signals are subjected to multiple reflections, diffractions and attenuation caused by obstacles such as buildings and hills, etc. At the receiver end, multiple copies of the transmitted signal are received that arrive at clearly distinguishable time instants and are faded by signal cancellation. Rake receiver is a technique to combine these so called multi-paths [2] by utilizing multiple correlation receivers allocated to those delay positions on which the significant energy arrives which achieves a significant improvement in the SNR of the output signal. This paper shows how the rake, including dispreading and descrambling could be replaced by a receiver that can be implemented on a CORDIC based hardware architecture. The performance in conjunction with the computational requirements of the receiver is widely adjustable which is significantly better than that of the conventional rake receiver.
Reduced-rank filtering on L1-norm subspaces

Recent studies in signal processing have unveiled the remarkable outlier-resistance properties of L1-norm subspaces, calculated by means of L1-norm principal component analysis (L1-PCA). In this work, we present for the first time reduced-rank interference-suppressive filtering on L1-norm subspaces of the received signal vectors. Our simulation studies illustrate that the proposed filtering framework allows for successful suppression of coherent interference while, at the same time, it offers sturdy protection against outliers that appear among the training samples.
Three- and Four-repeat Tau Regulate the Dynamic Instability of Two Distinct Microtubule Subpopulations in Qualitatively Different Manners

The microtubule-associated protein tau is implicated in the pathogenesis of many neurodegenerative diseases, including fronto-temporal dementia and parkinsonism linked to chromosome 17 (FTDP-17), in which both RNA splicing and amino acid substitution mutations in tau cause dominantly inherited early onset dementia. RNA-splicing FTDP-17 mutations alter the wild-type ∼50:50 3-repeat (3R) to 4-repeat (4R) tau isoform ratio, usually resulting in an excess of 4R tau. To examine further how splicing mutations might cause dysfunction by misregulation of microtubule dynamics, we used video microscopy to determine the in vitro behavior of individual microtubules stabilized by varying amounts of human 4R and 3R tau. At low tau:tubulin ratios (1:55 and 1:45), all 3R isoforms reduced microtubule growth rates relative to the no-tau control, whereas all 4R isoforms increased them; however, at a high tau:tubulin ratio (1:20), both 4R and 3R tau increased the growth rates. Further analysis revealed two distinct subpopulations of growing microtubules in the absence of tau. Increasing concentrations of both 4R and 3R tau resulted in an increase in the size of the faster growing subpopulation of microtubules; however, 4R tau caused a redistribution to the faster growing subpopulation at lower tau:tubulin ratios than 3R tau. This modulation of discrete growth rate subpopulations by tau suggests that tau causes a conformational shift in the microtubule resulting in altered dynamics. Quantitative and qualitative differences observed between 4R and 3R tau are consistent with a “microtubule misregulation” model in which abnormal tau isoform expression results in the inability to properly regulate microtubule dynamics, leading to neuronal death and dementia.
A Cartesian Grid Method for Solving the Two-Dimensional Streamfunction-Vorticity Equations in Irregular Regions

We describe a method for solving the two-dimensional Navier? Stokes equations in irregular physical domains. Our method is based on an underlying uniform Cartesian grid and second-order finite-difference/finite-volume discretizations of the streamfunction-vorticity equations. Geometry representing stationary solid obstacles in the flow domain is embedded in the Cartesian grid and special discretizations near the embedded boundary ensure the accuracy of the solution in the cut cells. Along the embedded boundary, we determine a distribution of vorticity sources needed to impose the no-slip flow conditions. This distribution appears as a right-hand-side term in the discretized fluid equations, and so we can use fast solvers to solve the linear systems that arise. To handle the advective terms, we use the high-resolution algorithms in CLAWPACK. We show that our Stokes solver is second-order accurate for steady state solutions and that our full Navier? Stokes solver is between first- and second-order accurate and reproduces results from well-studied benchmark problems in viscous fluid flow. Finally, we demonstrate the robustness of our code on flow in a complex domain.
CHEMP receiver for large-scale multiuser MIMO systems using spatial modulation

In spatial modulation (SM), information bits are conveyed through the index of the active transmit antenna in addition to the information bits conveyed through conventional modulation symbols. In this paper, we propose a receiver for large-scale multiuser spatial modulation MIMO (SM-MIMO) systems. The proposed receiver exploits the channel hardening phenomenon observed in large-dimensional MIMO channels. It works with a matched filtered system model. On this system model, it obtains an estimate of the matched filtered channel matrix (rather than the channel matrix itself) and uses this estimate for detecting the data. The data detection is done using an approximate message passing algorithm. The proposed receiver, referred to as the channel hardening-exploiting message passing receiver for SM(CHEMP-SM), is shown to achieve very good performance at low complexity.
Design and development of a humanoid with Soft 3D-deformable sensor flesh and automatic recoverable mechanical overload protection mechanism

In order for robots to be able to assist humans at a very close distance, robots should allow contacts occurred at many places and deal with them. For realizing such functions, robots should have whole-body soft sensor exterior for preparing contacts against almost every body parts since it is difficult to limit where to be touched from humans.
Advanced remote sensing techniques for forestry applications: an application case in Sarawak, Malaysia

12 This paper reports the operational implementation of new techniques for the exploitation of remote sensing data (SAR and optical) in the framework of forestry applications. In particular, we present a new technique for standing timber volume estimation. This technique is based on remote sensing knowledge (SAR and optical synergy) and forestry knowledge (forest structure models), proved fairly accurate. To illustrate the application of these techniques, an operational commercial case study regarding forest concessions in Sarawak is presented. Validation of this technique by comparison of the remote sensing results and the database of the customer has shown that this technique is fairly accurate.
A Comparison of Teacher’s and Senior Students’ Feedback : Student Attitudes and Their Writing Improvement

Based on the concepts of Zone of Proximal Development (ZPD), this study compared the effects of feedback given from teacher and senior students on Thai EFL (English as a Foreign Language) students’ writing. The research participants were 33 students majoring in English who were undertaking an English Essay Writing Course and 22 senior students who have already passed the course. The data were collected from a questionnaire, semi-structured interviews, a group discussion, and the students’ writing drafts. The results showed that students found the senior feedback helpful to improve their writing drafts, and they felt comfortable to receive feedback from senior students; however, they had low confidence towards the comments. With regards to teacher comments, students found them helpful to raise their awareness in terms of tenses, grammar, and structure. However, the limitations of teacher feedback were pointed out in terms of confusing comments, stress, and timing. Finally, the analysis of the effects of feedback types on students’ improvements showed that metalinguistic corrective feedback (CF) made by both teacher and senior students led to most of the effective corrections. Based on the findings, the implications and directions for future research will be discussed
Quantitative Analysis of the Internet Topology Model

The article presents analysis of the Internet topology graph model. We use usual methods to analyse properties of the model but also propose some new characteristics. Our experimental data set comprises long-term traceroute records for several thousands of target hosts, repeatedly executed from a fixed source. We processed particular routes by merging them all together thus creating a single connected graph, which represents a sample of Internet-like network. We evaluate several network characteristics, notably node degree distribution, k-core decomposition, clustering coefficients, etc. Comparison shows good correspondence with other known results. Furthermore, we examine new metrics, particularly the count and length of linear subgraphs and the number of connections between vertices with maximum and minimum degree. These characteristics help to distinguish between network types. The latter one appears to be useful also in the context of finding a dominating vertex set problem.
How cultural confidence affects local residents’ wellbeing

ABSTRACT This study provides and tests an integrated model that explores the effect of cultural confidence on residents’ spiritual wellbeing and the impacts of spiritual, social and psychological wellbeing on subjective wellbeing. Using Xinjiang Uygur Autonomous Region of China as the research site, 356 responses are collected via a field survey. A mixed-method approach is used to conceptualize and develop measures of cultural confidence. PLS-SEM results indicate significant positive relationships between cultural confidence and three dimensions of spiritual wellbeing (such as personal, environmental and communal). Spiritual wellbeing has a strong influence on social, psychological, and subjective wellbeing. Social wellbeing is positively related to psychological wellbeing, which in turn leads to subjective wellbeing. This research proposes and validates an integral framework that explains the development of residents’ subjective wellbeing. Findings have significant implications to destination policy decision-making in support of tourism development.
Temporalized Dempster-Shafer belief structure in discrimination analysis

The analysis of Dempster-Shafer temporalized structure is performed for the construction of more precise decisions based on the expert knowledge valuations. The relation of information precision is defined on the bodies of evidence. Negative inaccuracy is defined as the stream of rational expert knowledge in Dempster-Shafer temporalized structure. The principle of negative inaccuracy is developed, as the maximum principle of non-specificity measure and/or Shapley information entropy of a body of evidence. Corresponding mathematical programming problem is constructed. The possibilities of modeling more precise decisions are illustrated using Discrimination Analysis.
Fast Regularized Least Squares and k-means Clustering Method for Intrusion Detection Systems

Intrusion detection systems are intended for reliable, accurate and efficient detection of attacks in a large networked system. Machine learning methods have shown promising results in terms of accuracy but one disadvantage they share is the high computational cost of training and prediction phase when applied to intrusion detection. Recently some methods have been introduced to increase this efficiency. Kernel based methods are one of the most popular methods in the literature, and extending them with approximation techniques we describe in this paper has a huge impact on minimizing the computational time of the Intrusion Detection System (IDS). This paper proposes using optimized Regularized Least Square (RLS) classification combined with k-means clustering. Standard techniques are used in choosing the optimal RLS predictor parameters. The optimization leads to fewer basis vectors which improves the prediction speed of the IDS. Our algorithm evaluated on the KDD99 benchmark IDS dataset demonstrates considerable improvements in the training and prediction times of the intrusion detection while maintaining the accuracy.
Minimized conical spiral antenna for GNSS

In this paper, a tw o-arm conical spiral antenna (CSA) fed by 50 ohm coaxial-cable for Global Satellite Navigation System(GNSS) is designed and simulated, while the traditional CSA has great dimension, in the paper, minimization is achieved with the help of simulation software. To match the balance structure and the wideband character of the antenna, matched balun is inevitable In order to hence the performance of lower frequency, resistors are sealed to the bottom of the arm, simulation results show that the minimized CSA antenna with microstrip balun presenting good performance over the whole frequency range.
Comparing Redundancy Removal Techniques for Multi–Document Summarisation

We describe an experiment to determine the quality of different similarity metrics, with regard to redundancy removal. The three metrics under examination are WordNet distance, Cosine Similarity (Vector-space model) and Latent Semantic Indexing. Our experiment was performed on a corpus drawn from the 2003 Document Understanding Conference (DUC)[1].
Conditioned Belief Propagation revisited (extended version)

Belief Propagation (BP) applied to cyclic problems is a well known approximate inference scheme for probabilistic graphical models. To improve its accuracy , Conditioned Belief Propagation (CBP) has been proposed, which splits a problem into subproblems by conditioning on variables, applies BP to sub-problems, and merges the results to produce an answer to the original problem. In this work, we propose a reformulated version of CBP that exhibits anytime behavior and allows for more specific tuning by formalizing a further aspect of the algorithm through the use of a leaf selection heuristic. We propose several simple and easy to compute heuristics and demonstrate their performance using an empirical evaluation on randomly generated problems.
Using Clausal Graphs to Determine the Computational Complexity of k-Bounded Positive 1-in-3 SAT

The 1-in-3 SAT problem is known to be NP-complete even in the absence of negated variables [1], a variant known as Positive (or Monotone) 1-in-3 SAT. In this note, we use clausal graphs to investigate a further restriction: kBounded-Positive 1-in-3 SAT (kBP 1-in-3 SAT), in which each variable occurs in no more than k clauses. We show that for k = 2, kBP 1-in-3 SAT is in the polynomial complexity class P, while for all k>2, it is NP-complete, providing another way of exploring the boundary between classes P and NP.