Miracle-dz/UniFAR-FTUs huggingface dataset:
Behaviour Analysis Voting Model Using Social Media Data

: Nowadays, Social Media has become an important communication tool. Behavior could be measured using machine learning or deep learning techniques. This study represents a proposed model that shows how classification techniques can be used to recognize the personality according to the individuals' tweets using voting technique. The individual behavior is classified according to Eysenck's Three Factor personality model. A comparison was conducted between various machine learning and deep learning approaches as an input to a voting algorithm; which gave us more accurate results in the classifying task. The test results were 84.208% accurate. The study's main target is to make a new hybrid model for Twitter behavior analysis to enhance the accuracy of every approach individually on the dataset. Introducing the deep learning algorithm was to overcome the complexity and the time consuming obstacles. So this study can be used to predict future customers' behavior in order to increase satisfaction.
Use of biclustering for missing value imputation in gene expression data

DNA microarray data always contains missing values. As subsequent analysis such as biclustering can only be applied on complete data, these missing values have to be imputed before any biclusters can be detected. Existing imputation methods exploit coherence among expression values in the microarray data. In view that biclustering attempts to find correlated expression values within the data, we propose to combine the missing value imputation and biclustering into a single framework in which the two processes are performed iteratively. In this way, the missing value imputation can improve bicluster analysis and the coherence in detected biclusters can be exploited for better missing value estimation. Experiments have been conducted on artificial datasets and real datasets to verify the effectiveness of the proposed algorithm in reducing estimation errors of missing values.
Document Flattening through Grid Modeling and Regularization

For document images captured by a digital camera, perspective and geometric distortions make it hard to recognize the document content properly. In this paper, we propose an integrated document restoration technique, which is capable of removing perspective and geometric distortions, and producing a flattened and fronto-parallel text image that is friendly to the generic OCR systems. The proposed document restoration is accomplished through grid modeling, which divides camera images into multiple quadrilateral grids using vertical text directions and the x lines and base lines. The global distortions are then removed through grid regularization that transforms the quadrilateral grids together with the pixel contents to the regular square grids. Experimental results show the proposed method is fast and easy for implementation
On the Security of Mexican Digital Fiscal Documents

In January 2005, the Mexican Tributary Administration System (SAT) introduced an official norm that stipulates how to generate electronic invoices that were termed by SAT, Comprobante Fiscal Digital (CFD). Supporting the CFD service implies the exchange of confidential information over Internet and other communication channels that are intrinsically highly vulnerable. Therefore, it becomes indispensable to incorporate to this service reliable and sound information security mechanisms. In the case of SAT’s CFD, its security guarantees depend on customary cryptographic mechanisms such as, digital signatures, hash functions, etc. In this paper we point out several security flaws in the procedure specified by SAT for generating such electronic invoices. Furthermore, we provide recommendations for avoiding the security problems detected, which include the usage of more robust cryptographic mechanisms, alternative authentication protocols, time stamps authorities and a safe storage system.
Population growth makes waves in the distribution of pairwise genetic differences.

Episodes of population growth and decline leave characteristic signatures in the distribution of nucleotide (or restriction) site differences between pairs of individuals. These signatures appear in histograms showing the relative frequencies of pairs of individuals who differ by i sites, where i = 0, 1, . In this distribution an episode of growth generates a wave that travels to the right, traversing 1 unit of the horizontal axis in each 1/2u generations, where u is the mutation rate. The smaller the initial population, the steeper will be the leading face of the wave. The larger the increase in population size, the smaller will be the distribution's vertical intercept. The implications of continued exponential growth are indistinguishable from those of a sudden burst of population growth Bottlenecks in population size also generate waves similar to those produced by a sudden expansion, but with elevated uppertail probabilities. Reductions in population size initially generate L-shaped distributions with high probability of identity, but these converge rapidly to a new equilibrium. In equilibrium populations the theoretical curves are free of waves. However, computer simulations of such populations generate empirical distributions with many peaks and little resemblance to the theory. On the other hand, agreement is better in the transient (nonequilibrium) case, where simulated empirical distributions typically exhibit waves very similar to those predicted by theory. Thus, waves in empirical distributions may be rich in information about the history of population dynamics.
A model-driven approach to non-functional analysis of software architectures

We present an approach to managing formal models using model driven architecture (MDA) technologies that deliver analysis techniques through integration with the design tools and repositories that practitioners use. Expert modeling knowledge is captured in domain-specific languages and meta-model constraints. These are represented using UML (Unified Modeling Language) and collocated with designs and analysis models, providing a flexible and visible approach to managing semantic associations. The approach relies on standards to permit deployment in multiple tools. We demonstrate our approach with an example in which queuing-network models are associated with UML design models to predict average case performance.
A novel approach for droplet position sensing in electrowetting devices

A droplet position sensing scheme for monitoring multiple droplets has been proposed, which gives a direct voltage output linearly proportional to droplet position in electrowetting-on-dielectric (EWOD) based devices. An extra dielectric and metal layers are required in the bottom substrate for physical realization of the scheme which provides better isolation between actuation and sensing line. The capacitors formed due to the extra dielectric and metal layers facilitate direct voltage output proportional to droplet position during transport. Energy-based model has been used for analysis purpose. Results show that the additional dielectric and metal layer in the bottom substrate does not significantly change the driving electrostatic force profile. This makes the proposed scheme compatible for digital microfluidic operations.
Catecholamine Stimulation, Substrate Competition, and Myocardial Glucose Uptake in Conscious Dogs Assessed with Positron Emission Tomography

Uptake of radiolabelled deoxyglucose out of proportion to reduced coronary flow demonstrated by positron emission tomography has been used to identify reversibly ischemic, viable myocardium. For this concept to be applied reliably in the clinical setting, factors that may depress glucose availability independent of tissue viability, such as adrenergic stimulation and substrate competition, must be examined. Accordingly, we studied the effect of catecholamine stimulation by dopamine on myocardial glucose uptake in vivo using chronically instrumented, intact dogs and positron emission tomography. We measured myocardial activity of [2-18F]-2-deoxyglucose (FDG) and 82Rb in glucose-loaded animals randomly studied during dopamine infusion, during insulin infusion, and then during their combined infusion. Myocardial FDG uptake was significantly decreased when animals were treated with dopamine, compared with treatment in the same animals with insulin. When insulin was added to the dopamine infusion, myocardial FDG uptake was restored. In contrast, myocardial activity of 82Rb, which is taken up in proportion to coronary flow, was similar under all three experimental conditions. Plasma glucose, free fatty acid, and lactate concentrations were determined before and during each infusion. The depression of myocardial FDG activity seen during dopamlne infusion and its reversal with addition of insulin can be explained on the basis of effects of these hormones on substrate availability and competition. (Circulation Research 1987;61(suppl II):II-124-II-129)
Analysis of tag within online social networks

In recent years, tagging systems have been paid increasing attentions from both research communities and system designers. Most popular online social networking sites harness tag for managing and locating contents, for organizing and connecting users, and for recommending and sharing resources. We believe that tag acts like bridge between people and resources. Research on tag and tagging behavior will provide us insight about resource space and user activities on the Internet. In this paper, we present a two-level analysis of the tagging system of Del.icio. us. The results from both two levels confirm each other. In network level, we connect tags by users collaborative tagging to form a social network of tags. By investigating its network feature, we find phenomena of small world and scale-free network. We also discover that the links within this network have relatively strong semantic relatedness. In individual level, users' tagging behaviors and patterns are observed by visualizing their bookmarking history on Del.icio. us. Besides, we study the linked users by their tags and find that users within a subscription network share more common interests than random pairs of users. During the analysis, we also discuss the implications of the findings for the design of tag-based system.
Fecal Contamination of Drinking-Water in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis

Robert Bain and colleagues conduct a systematic review and meta-analysis to assess whether water from “improved” sources is less likely to contain fecal contamination than “unimproved” sources and find that access to an “improved source” provides a measure of sanitary protection but does not ensure water is free of fecal contamination. Please see later in the article for the Editors' Summary
Detecting Network Compression : A Case Study

Internet middleboxes such as VPNs, firewalls, and proxies can significantly change handling of traffic streams. They play an increasingly important role in various types of IP networks. If end hosts can detect them, these hosts can make beneficial, and in some cases, crucial improvements in security and performance But because middleboxes have widely varying behavior and effects on the traffic they handle, no single technique has been discovered that can detect all of them. Devising a detection mechanism to detect any particular type of middlebox interference involves many design decisions and has numerous dimensions. One approach to assist with the complexity of this process is to provide a set of systematic guidelines. This paper is the first attempt for introducing a set of general guidelines (as well as the rationale behind them) to assist researchers with devising detection methodologies to detect middleboxes by the end-hosts. The presented guidelines take some inspiration from previous work of other researchers using various and often ad hoc approaches. These guidelines, however, are mainly based on our experience from conducting research in this area to detect such middleboxes. To assist researchers for using these guidelines we also provide an example of how to bring them into play for detection of network compression.
Traffic Simulation for Packet Telephony in Mobile Ad-hoc Networks

Realization of cost effective packet telephony solutions over mobile ad-hoc networks is one of the attended area by the computer science research fraternity. As with other ideas it is difficult to test new proposals on mobile ad-hoc networks using a real time environment. So researchers need to resort to simulation based environment. To model packet telephony over mobile ad-hoc network generation of relevant traffic is central to the success. Authors in this work are proposing an algorithm to model the application layer of a mobile ad-hoc network carrying packet telephony, thereby generation of relevant telephony data to be transported over the network. Packet Telephony (1) represents implementation of conventional telephony using IP packets. This essentially represents computer network carrying voice conversations. Packet telephony is also sometimes termed as Voice over Internet Protocol. This technique has the potential of being highly useful for offering services like video conferencing, fax, SMS over the internet. Traditionally all of these services have been offered using circuit switched network which require dedicated copper path. The technique of Packet Telephony does not require any copper path reservation and hence can help achieve a number of parallel voice conversations through same media. These days a number of companies are offering VoIP service where call rates are much cheaper as compared to traditional telephonic calls. VoIP offers a number of advantages over the traditional circuit switched telephony technique like simultaneous calling, data service in parallel with voice services, less operational cost and flexibility etc. Packet Telephone over wireless networks can be used to extend the reach of fixed telephony over an area, termed as fixed-to-mobile convergence (FMC) (2). VoIP as a technique do have some limitations also like security and legal issues. The successful implementation of packet telephony is constrained by a number of Quality of Service, QoS, parameters (3). These parameters include end to end delay, jitter, throughput, packet delivery rate, call drop rate etc Implementation of Quality of Service based Packet Telephony is a challenge.
Consumer demand for food diversity : evidence for Germany

Whereas a large number of empirical studies have been devoted to analysing consumer demand for specific products, much less attention has been paid to the household’s demand for product variety (the number of different products consumed in a specific time period). This paper analyses consumer demand for food variety in Germany. The econometric analysis of 4632 households suggests that variety significantly increases with income and the number of children aged between 7 and 17 years and is significantly higher if the family lives in larger cities in East Germany, and the housekeeping person is not additionally working full-time. A single male household consumes a significantly smaller number of different food products. The significant (and positive) impact of household income on food variety is in line with the hypothesis that consumption evolves along a hierarchical order as income increases.  2003 Elsevier Science Ltd. All rights reserved.
Topic graph based transfer learning via generalized KL divergence based NMF

We propose a topic graph based transfer learning method based on Non-negative Matrix Factorization (NMF) with generalized Kullback-Leibler (KL) divergence. Based on the Frobenius norm based NMF, a transfer learning method was proposed based on the similarity of feature spaces. We extend the previous method by utilizing generalized KL divergence based NMF so that better probabilistic interpretation can be obtained with the divergence. The proposed method is formalized as the minimization of an objective function under the divergence, and an auxiliary function for the objective function is defined. From the auxiliary function, we derive a learning algorithm with multiplicative update rules, which are guaranteed to converge. The proposed method is evaluated in terms of document clustering over several well-known benchmark datasets. Extensive experiments have been conducted on the datasets, and comparison with other transfer learning methods as well as state-of-the-art NMF methods is reported.
The FedEx Problem

Consider the pricing problem faced by FedEx. Each customer has a package to ship, a deadline $d$ by which he needs his package to arrive, and a value $v$ for a guarantee that the package will arrive by his deadline. FedEx can (and does) offer a number of different shipping options in order to extract more revenue from their customers. In this paper, we solve the optimal (revenue-maximizing) auction problem for the single-agent version of this problem. Our paper adds to the relatively short list of multi-parameter settings for which a closed-form solution is known.
AGENT PLATFORM FOR ROBOT CONTROL IN REAL-TIME DYNAMIC ENVIRONMENTS

This paper describes a platform that enables a real robot control through a software Agent capable of learning, planning and navigating in a dynamic realtime environment. The Agent can be adapted to any mobile robot and creates a two-dimensional representation of the world that is used for navigation and path planning. Current implementation supports two environments: a simulated robot environment and a real world environment with a four legged walking robot. Our main contributions include: adapting BDI agents to real-time requirements and an algorithm to build a two-dimensional representation of that environment.
A Cutoff in the X-Ray Fluctuation Power Density Spectrum of the Seyfert 1 Galaxy NGC 3516

During 1997 March-July, the Rossi X-Ray Timing Explorer observed the bright, strongly variable Seyfert 1 galaxy NGC 3516 once every ~12.8 hours for 4.5 months and nearly continuously (with interruptions due to South Atlantic Anomaly passage but not Earth occultation) for a 4.2 day period in the middle. These were followed by ongoing monitoring once every ~4.3 days. These data are used to construct the first well-determined X-ray fluctuation power density spectrum (PDS) of an active galaxy to span more than four decades of usable temporal frequency. The PDS shows no signs of any strict or quasi-periodicity but does show a progressive flattening of the power-law slope from -1.74 at short timescales to -0.73 at longer timescales. This is the clearest observation to date of the long predicted cutoff in the PDS. The characteristic variability timescale corresponding to this cutoff temporal frequency is ~1 month. Although it is unclear how this timescale may be interpreted in terms of a physical size or process, there are several promising candidate models. The PDS appears similar to those seen for Galactic black hole candidates such as Cyg X-1, suggesting that these two classes of objects with very different luminosities and putative black hole masses (differing by more than a factor of 105) may have similar X-ray generation processes and structures.
Galaxy Number Counts in the Hubble Deep Field as a Strong Constraint on a Hierarchical Galaxy Formation Model

Number counts of galaxies are reanalyzed using a semianalytic model (SAM) of galaxy formation based on the hierarchical clustering scenario. We have determined the astrophysical parameters in the SAM that reproduce observations of nearby galaxies and used them to predict the number counts and redshifts of faint galaxies for three cosmological models: (1) the standard cold dark matter (CDM) universe, (2) a low-density flat universe with nonzero cosmological constant, and (3) a low-density open universe with zero cosmological constant. The novelty of our SAM analysis is the inclusion of selection effects arising from the cosmological dimming of the surface brightness of high-redshift galaxies and also from the absorption of visible light by internal dust and intergalactic H I clouds. Contrary to previous SAM analyses that do not take into account such selection effects, we find from comparison with observed counts and redshifts of faint galaxies in the Hubble Deep Field (HDF) that the standard CDM universe is not preferred, and a low-density universe either with or without a cosmological constant is favorable, as suggested by other recent studies. Moreover, we find that a simple prescription for the timescale of star formation (SF), being proportional to the dynamical timescale of the formation of the galactic disk, is unable to reproduce the observed number-redshift relation for HDF galaxies, and that the SF timescale should be nearly independent of redshift, as suggested by other SAM analyses for the formation of quasars and the evolution of damped Lyα systems.
On the Role of PDZ Domain-Encoding Genes in Drosophila Border Cell Migration

Cells often move as collective groups during normal embryonic development and wound healing, although the mechanisms governing this type of migration are poorly understood. The Drosophila melanogaster border cells migrate as a cluster during late oogenesis and serve as a powerful in vivo genetic model for collective cell migration. To discover new genes that participate in border cell migration, 64 out of 66 genes that encode PDZ domain-containing proteins were systematically targeted by in vivo RNAi knockdown. The PDZ domain is one of the largest families of protein-protein interaction domains found in eukaryotes. Proteins that contain PDZ domains participate in a variety of biological processes, including signal transduction and establishment of epithelial apical-basal polarity. Targeting PDZ proteins effectively assesses a larger number of genes via the protein complexes and pathways through which these proteins function. par-6, a known regulator of border cell migration, was a positive hit and thus validated the approach. Knockdown of 14 PDZ domain genes disrupted migration with multiple RNAi lines. The candidate genes have diverse predicted cellular functions and are anticipated to provide new insights into the mechanisms that control border cell movement. As a test of this concept, two genes that disrupted migration were characterized in more detail: big bang and the Dlg5 homolog CG6509. We present evidence that Big bang regulates JAK/STAT signaling, whereas Dlg5/CG6509 maintains cluster cohesion. Moreover, these results demonstrate that targeting a selected class of genes by RNAi can uncover novel regulators of collective cell migration.
The Effect of Fishbone Diagram on Students’ Writing of Analytical Exposition Text

As writing in English is seemed to be highly demanded in schools, this study was conducted to obtain the empirical evidence of the effect of Fishbone Diagram on students’ writing of Analytical Exposition Text. The research design in this study was quasi-experimental design with 64 samples of the eleventh-grade students of SMAN 4 Tangerang Selatan. The samples were taken through purposive sampling technique and classified into two classes; experimental and controlled classes. The controlled class was treated with conventional teaching method without using Fishbone Diagram while the experimental class was treated by using Fishbone Diagram as the tool to enhance their writing. The instrument of the data collection was writing tests which were given as pretests and post-tests. The data collected from this study were analysed using t-test in order to identify the significance level of the results. This study resulted that both classes gained their scores in post-test. However, the experimental class has performed more significant improvement than the controlled class. Thus, it can be concluded that Fishbone Diagram had significant effect on students’ writing of Analytical Exposition Text at the eleventhgrade of SMA Negeri 4 Tangerang Selatan in Academic Year 2018/2019.