Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-script Off-line Signature Verification: A Two Stage Approach

Signature identification and verification are of great importance in authentication systems. The purpose of this paper is to introduce an experimental contribution in the direction of multi-script off-line signature identification and verification using a novel technique involving off-line English, Hindi (Devnagari) and Bangla (Bengali) signatures. In the first evaluation stage of the proposed signature verification technique, the performance of a multi-script off-line signature verification system, considering a joint dataset of English, Hindi and Bangla signatures, was investigated. In the second stage of experimentation, multi-script signatures were identified based on the script type, and subsequently the verification task was explored separately for English, Hindi and Bangla signatures based on the identified script result. The gradient and chain code features were employed, and Support Vector Machines (SVMs) along with the Modified Quadratic Discriminate Function (MQDF) were considered in this scheme. From the experimental results achieved, it is noted that the verification accuracy obtained in the second stage of experiments (where a signature script identification method was introduced) is better than the verification accuracy produced following the first stage of experiments. Experimental results indicated that an average error rate of 20.80% and 16.40% were obtained for two different types of verification experiments.
Algorithms for the synchrophasor measurement in steady-state and dynamic conditions

Phasor measurement units (PMUs) are becoming one of the key issues of power network monitoring. They have to be able to perform accurate estimations of current and voltage signals either under steady-state or dynamic conditions. The first part of this PhD thesis analyses the impact of the phasor models on the estimation accuracy, focuses on algorithms proposed in the literature for the estimation of phasors and studies their performance under several different conditions. On the basis of the results of this analysis, in the second part of this thesis an innovative approach to improve the performance of synchrophasor estimation is presented. The method proposes a modified version of the synchrophasor estimation algorithm which uses the non-orthogonal transform defined as Taylor-Fourier Transform (TFT) and which is based on a Weighted Least Squares (WLS) estimation of the parameters of a second order Taylor model of the phasor. The aim of the proposed enhancements is to improve the performance of the algorithm in presence of fast transient events and to achieve a Phasor Measurement Unit that is simultaneously compliant with both M and P compliance classes, suggested by the synchrophasor standard IEEE C37.118. 1. In particular, while the TFT based adaptive algorithm is used for synchrophasor estimation, frequency and Rate of Change of Frequency (ROCOF) are estimated using the higher derivatives outputs of the adaptive TFT. Frequency estimation feedback is used to tune the algorithm and achieve better performance in off-nominal conditions. The proposed approaches are validated by means of simulations in all the static and dynamic conditions defined in the standard. In the last chapter, the algorithm proposed above is used in a novel architecture, compliant to IEC 61850, for a distributed IED-based PMU, to be used in electrical substations. In particular, a measurement architecture based on process bus and sampled values synchronized with IEEE 1588-2008 is proposed, so that voltage and current signals are acquired by a Merging Unit device, while the PMU signal processing is performed on a IED (Intelligent Electronic Device), in compliance with IEEE C37.118. 1-2011.
Complete Convergence and Weak Law of Large Numbers for ρ -Mixing Sequences of Random Variables

In this paper, the complete convergence and weak law of large numbers are established for ρ-mixing sequences of random variables. Our results extend and improve the Baum and Katz complete convergence theorem and the classical weak law of large numbers, etc. from independent sequences of random variables to ρ-mixing sequences of random variables without necessarily adding any extra conditions.
AAM fitting using shape parameter distribution

A novel constraint using shape parameter distribution into the AAM fitting method is proposed. Active appearance models (AAMs) are some of the most popular facial models. AAM-based face tracking delivers accurate alignment results. However, non-face-like shapes can also be estimated by AAMs, unlike by the conventional AAM fitting method, which only minimizes the matching error of the image. This is one of the causes for face tracking performance degradation in AAMs. A constraint using the shape parameter distribution is added in order to solve this problem.
Mining Social Interaction - Ubiquitous Sensors and Social Media

Ubiquitous social media has woven itself into the very fabric of everyday life. This results in a dramatic increase of social data. Essentially, various links between the users and their associated artifacts capture different facets of interactions and relationships. The emergence of ubiquitous and mobile devices enables the capture of such interactions also in offline contexts, and the generation of according interactions networks. This paper focuses on the analysis and mining of such interaction networks, specifically focussing on data collected using ubiquitous RFID sensors as well as complementing social media. We discuss analysis results in the context of real-world systems.
Solo Mother's Challenges and Coping Strategies: A Phenomenological Study in City of Manila

Background: Filipino society's normative definition of a 'family' is one that is composed of a married heterosexual couple and their children. In such cultural set-up, both the mothers and fathers are expected to share the responsibility in raising their child or children. However, for solo mother households, this scenario is farfetched wherein solo mothers serve as the primary economic provider and caregiver. Objectives: The study aims to chart the challenges faced by solo mothers and to identify the coping strategies they employed through understanding their lived experiences. Methodology: The study used a phenomenological approach to magnify a better understanding of the phenomenon as experienced by solo mothers. The researcher conducted personal in-depth interviews to thirteen (13) solo mothers from the city of Manila. The inclusion criteria for the participants were: (a) solo mothers who raised their child alone, (b) at least 25 years of age, and (c) has at least one biological child who is 20 years old and below. The participants were recruited through purposive and snowball sampling. The interviews were carefully recorded, transcribed and critically analyzed. After careful thematic analysis of the data and with quantitative methods used, seven themes answering the study's objectives emerged. Results and Conclusions: The seven major themes recorded were: Absence of A Partner, Conflicting Responsibilities, Child Care, Social Support, Willing Endurance, Spiritual Guidance, and Self-Care. These themes were gathered from the respondents who on the averaged have been solo mothers for 10 years already. Solo mothers used both problem-focused and emotion-focused coping strategies, but the nature of the problem dictates the strategy to be employed. Solo mothers make sure to look after themselves to be able to take care of their children in the future. Given the reality of struggles of solo parenting, solo mothers as a sector must be provided with support programs and policies by the government to strengthen their stand to raise their children well.
Low-voltage and low-power CMOS current-mode divider and 1/x circuit

A new low-voltage and low-power CMOS current-mode circuit that can perform divide and 1/x functions is presented. It consists of four MOSFETs biased in weak inversion. HSPICE simulation is used to confirm the functionality of the circuit. This circuit will be a useful sub-circuit for analog current mode signal processing specially medical applications.
Multiscale adjoint waveform tomography for surface and body waves

ABSTRACTWe have developed a wavelet-multiscale adjoint scheme for the elastic full-waveform inversion of seismic data, including body waves (BWs) and surface waves (SWs). We start the inversion on the SW portion of the seismograms. To avoid cycle skipping and reduce the dependence on the initial model of these dispersive waves, we commence by minimizing an envelope-based misfit function. Subsequently, we proceed to the minimization of a waveform-difference (WD) metric applied to the SWs only. After that, we fit BWs and SWs indiscriminately using a WD misfit metric. In each of these three steps, we guide the iterative inversion through a sequence of nested subspace projections in a wavelet basis. SW analysis preserves a wealth of near-surface features that would be lost in conventional BW tomography. We used a toy model to illustrate the dispersive and cycle-skipping behavior of the SWs, and to introduce the two ways by which we combat the nonlinearity of waveform inversions involving SWs. The first is the.
Rab1 and Ca2+ are required for the fusion of carrier vesicles mediating endoplasmic reticulum to Golgi transport

Members of the rab/YPT1/SEC4 gene family of small molecular weight GTPases play key roles in the regulation of vesicular traffic between compartments of the exocytic pathway. Using immunoelectron microscopy, we demonstrate that a dominant negative rab1a mutant, rab1a(N124I), defective for guanine nucleotide binding in vitro, leads to the accumulation of vesicular stomatitis virus glycoprotein (VSV-G) in numerous pre-cis-Golgi vesicles and vesicular-tubular clusters containing rab1 and beta-COP, a subunit of the coatomer complex. Similar to previous observations (Balch et al. 1994. Cell. 76:841-852), VSV-G was concentrated nearly 5-10-fold in vesicular carriers that accumulate in the presence of the rab1a(N124I) mutant. VSV-G containing vesicles and vesicular-tubular clusters were also found to accumulate in the presence of a rab1a effector domain peptide mimetic that inhibits endoplasmic reticulum to Golgi transport, as well as in the absence of Ca2+. These results suggest that the combined action of a Ca(2+)-dependent protein and conformational changes associated with the GTPase cycle of rab1 are essential for a late targeting/fusion step controlling the delivery of vesicles to Golgi compartments.
Calibration of a network of Kinect sensors for robotic inspection over a large workspace

This paper presents an approach for calibrating a network of Kinect devices used to guide robotic arms with rapidly acquired 3D models. The method takes advantage of the rapid 3D measurement technology embedded in the Kinect sensor and provides registration accuracy within the range of the depth measurements accuracy provided by this technology. The internal calibration of the sensor in between the color and depth measurement is also presented. The resulting system is developed to inspect large objects, such as vehicles, positioned within an enlarged field of view created by the network of RGB-D sensors.
An Application Domain Speci c Languagefor Describing Board Games

Multigame is an implicitly-parallel, domain-speciic language for describing board games. The Multigame system automatically exploits parallelism (by searching game trees in parallel), without any involvement from the programmer. The paper describes the language and its implementation on a Myrinet-based distributed system. It also gives performance results for Multigame applications .
Policymaking Gone Awry: The Labor Market Regulations of the Doing Business Indicators

This article addresses conceptual and methodological issues as well as the policy implications of the "employing workers" component of the World Bank's Doing Business Indicators. It begins with a critical review of the "employing workers" indicators and their policy implication that no regulation is best for business (or the lowest the regulation, the better the business outcomes). This is followed by a methodological critique of the indicators that addresses problems of selection, coding, weighting, and ranking. The article argues that despite their role in influencing labor market reforms and policies, the "employing workers" indicators are not satisfactory indicators for formulating policy recommendations.
A Vision-Based Approach for Controlling User Interfaces of Mobile Devices

We introduce a novel user interface solution for mobile devices which enables the display to be controlled by the motion of the user’s hand. A feature-based approach is proposed for dominant global motion estimation that exploits gradient measures for both feature selection and motion uncertainty analysis. We also present a voting-based scheme for outlier removal. A Kalman filter is utilized for smoothing motion trajectories. A fixed-point implementation of the method was made on a mobile device platform that sets computational restrictions for the algorithms used. Experiments with synthetic and real image sequences show the effectiveness of the method and demonstrate the practicality of the approach in a smartphone.
Macroeconomic Monitoring and Visualizing News

This article presents the first open source IT solution for nowcasting and reading news with dynamic factor models. As illustrated in our workhorse example, the software allows us to extend the limits of currently established practices. The nowcasting model proposed for the US economy is, to the best of our knowledge, the first one that accounts for the joint behavior of quantities and prices. The model also provides a join interpretation of the forecast revisions for multiple horizons in terms of the unexpected part of both new data releases and revisions to past data, which become available in real time. For instance, a worse than expected inflation release will have an impact on the forecasting updates for GDP, but the sign of that impact will depend on the remaining news too. The reason is that we can have both positive supply and negative demand disturbances underlying the bad surprise in inflation data.
Stabilization for the compliant humanoid robot COMAN exploiting intrinsic and controlled compliance

The work presents the standing stabilization of a compliant humanoid robot against external force disturbances and variations of the terrain inclination. The novel contribution is the proposed control scheme which consists of three strategies named compliance control in the transversal plane, body attitude control, and potential energy control, all combined with the intrinsic passive compliance in the robot. The physical compliant elements of the robot are exploited to react at the first instance of the impact while the active compliance control is applied to further absorb the impact and dissipate the elastic energy stored in springs preventing the high rate of spring recoil. The body attitude controller meanwhile regulates the spin angular momentum to provide more agile reactions by changing body inclination. The potential energy control module constrains the robot center of mass (COM) in a virtual slope to convert the excessive kinetic energy into potential energy to prevent falling. Experiments were carried out with the proposed balance stabilization control demonstrating superior balance performance. The compliant humanoid was capable of recovering from external force disturbances and moderate or even abrupt variations of the terrain inclination. Experimental data such as the impulse forces, real COM, center of pressure (COP) and the spring elastic energy are presented and analyzed.
Parallelization of association rule mining: Survey

In todays big data era, all modern applications are generating and collecting large amount of data. As a result, data mining is encountering new challenges and opportunities to make algorithms such that, this voluminous data can be effectively and efficiently transformed into actionable knowledge . Traditional algorithms were designed to run sequentially over a single machine. But, as the volume of data increases computational cost associated with its processing also increases. This causes problems in analysing data on a single sequential machine and instead of assisting in data analysis, the processor serve more like a bottleneck. Parallel and distributed approaches improve the performance in terms of computational cost as well as scalability but experience some limitations during load balancing, data partitioning, job assignment, monitoring etc. MapReduce, a parallel programming model is a new concept which provides seemingly unlimited computing power, cheap storage as well as, can overcome above limitations. This makes it a topic of upcoming research interest. A detailed literature review of some existing methods is given along with their pros and cons.
Leptogenesis scenarios via non-thermally produced right-handed neutrino and sneutrino in supersymmetric seesaw model

We reconsidered leptogenesis scenario from right-handed (s)neutrino produced by the decay of inflaton. Besides the well-investigated case that the neutrino decays instantaneously after the production, leptogenesis is possible if neutrino decays after it dominates the universe. In the latter case, right-handed (s)neutrino can decay either while it is relativistic or after it becomes non-relativistic. Especially, the first case has not been discussed seriously in literatures. Resultant lepton asymmetry and constraints from the gravitino problem are studied in broad parameter region, including all cases of this scenario. It is also shown how this leptogenesis scenario depends on the parameters, the inflaton decay rate (the reheating temperature), the right-handed neutrino mass, the washout parameter, and the constraint from the gravitino problem. Leptogenesis from relativistic neutrino decay is interesting because both thermal and non-thermal gravitino problems can be relaxed.
Weekly paclitaxel combining with gemcitabine is an effective and safe treatment for advanced breast cancer patients.

OBJECTIVE Patients with metastatic breast cancer usually accept several lines of chemotherapy. This retrospective study is to analyze the therapeutic effect and tolerance of weekly paclitaxel/gemcitabine combination on patients with metastatic breast cancer. METHODS Paclitaxel 80 mg/m(2) and gemcitabine 800 mg/m(2) were administered sequentially on days 1, 8 and 15 every 28 days. Patients with measurable metastatic breast cancer or locally advanced breast cancer were included. RESULTS From March 2005 to December 2006, 50 patients received this treatment at Chang Gung Memorial Hospital, Kaohsiung Medical Center. Thirteen (26%) patients accepted this regimen as their first-line treatment for metastatic breast cancer and 25 (50%) patients accepted this regimen after at least three lines of therapies for metastatic breast cancer. The overall response rate was 56% (95% confidence interval: 42.2-69.8%), 2 patients achieved complete response and 26 patients (52, 95% confidence interval: 38.2-65.9%) achieved partial response. The median progression free survival was 7.4 months (95% confidence interval: 5.5-9.3 months), and the median overall survival was 19.0 months (95% confidence interval: 9.7-28.3 months). Except alopecia, the most common Grade 3/4 toxicities were anemia and leucopenia; the incidences of both were fewer than 10%. CONCLUSIONS The combination of weekly gemcitabine and paclitaxel in patients with advanced breast cancer showed acceptable outcome and excellent toxic profiles. This therapeutic benefit could be achieved in any linage of patients with good performance status; earlier usage of this regimen can provide better result.
Fair Intelligent Feedback Mechanism on TCP Based Network

∗ Corresponding author. Abstract Network performance degradation due to congestion is a major problem in the Internet. This performance degradation is mainly due to the uncoordinated interaction of congestion control mechanism of the TCP and that of the underlying network. Another challenging problem in the Internet is that TCP can’t achieve fair bandwidth allocation among competing TCP traffics [1 4]. In this paper, we propose Fair Intelligent Congestion Control Resource Discovery (FICCRD) mechanism to improve end-to-end TCP performance by controlling the congestion and allocating fair share of bandwidth to competing TCP traffics. The key idea is to create feedback control loop between edge routers on the network layer, a special Resource Discovery (RD) packet is introduced to collect and convey en route router state information. We apply Fair Intelligent Congestion Control (FICC) scheme [8, 9] in core routers to estimate fair share of bandwidth for competing TCP connections and feedback relevant information concerning the network conditions to the edge router. Fair Intelligent Explicit Window Adaptation (FIEWA) scheme [10] is employed at edge router to coordinate with the TCP congestion window. Simulation results show that our mechanism can significantly improve in throughput, fairness, and packet loss rate for TCP connections. Importantly, our scheme is transparent to TCP and requires no modifications to current TCP implementations.
Attenuated Circadian Rhythms in Mice Lacking the Prokineticin 2 Gene

Circadian clocks drive daily rhythms in virtually all organisms. In mammals, the suprachiasmatic nucleus (SCN) is recognized as the master clock that synchronizes central and peripheral oscillators to evoke circadian rhythms of diverse physiology and behavior. How the timing information is transmitted from the SCN clock to generate overt circadian rhythms is essentially unknown. Prokineticin 2 (PK2), a clock-controlled gene that encodes a secreted protein, has been indicated as a candidate SCN clock output signal that regulates circadian locomotor rhythm. Here we report the generation and analysis of PK2-null mice. The reduction of locomotor rhythms in PK2-null mice was apparent in both hybrid and inbred genetic backgrounds. PK2-null mice also displayed significantly reduced rhythmicity for a variety of other physiological and behavioral parameters, including sleep–wake cycle, body temperature, circulating glucocorticoid and glucose levels, as well as the expression of peripheral clock genes. In addition, PK2-null mice showed accelerated acquisition of food anticipatory activity during a daytime food restriction. We conclude that PK2, acting as a SCN output factor, is important for the maintenance of robust circadian rhythms.
Research on wireless sensor node for measurement of vegetation structure parameters

Based on WSN(Wireless Sensor Network)technology, this article designed a wireless sensor network node for vegetation parameter's measurement, which can be used at large space scale and in long temporal series measurement activity. Preliminary validation of the wireless sensor network node's algorithm and performance are presented in this article. The results indicated that the algorithm can estimate the vegetation parameters accurately from the measurement of transmittance of radiance through the canopy. The relative error of estimated LAI(Leaf Area Index) is 5%, and the LIDF(Leaf Inclination Distribution Function) agree with that of real vegetation structure basically. The sensitivity of designed wireless sensor network node is tested by measuring transmitted light intensity of projected direct LED light to leaves which have been punched with different density hole. The results indicted that the measured transmittance of leaves has high correlation with the holes density though it was also found that value of the former was slightly lower than that of the latter.