Miracle-dz/UniFAR-FTUs huggingface dataset:
Indexing and searching strategies for the Russian language

This paper describes and evaluates various stemming and indexing strategies for the Russian language. We design and evaluate two stemming approaches, a light and a more aggressive one, and compare these stem-mers to the Snowball stemmer, to no stemming, and also to a language-independent approach ( n -gram). To evaluate the suggested stemming strategies we apply various probabilistic information retrieval (IR) models, including the Okapi, the Divergence from Randomness (DFR), a statistical language model (LM), as well as two vector-space approaches, namely, the classical tf idf scheme and the dtu-dtn model. We ﬁnd that the vector-space dtu-dtn and the DFR models tend to result in better retrieval effectiveness than the Okapi, LM, or tf idf models, while only the latter two IR approaches result in statistically signiﬁcant performance differences. Ignoring stemming generally reduces the MAP by more than 50%, and these differences are always signiﬁcant. When applying an n -gram approach, performance differences are usually lower than an approach involving stemming. Finally,our light stemmer tends to perform best,although performance differences between the light, aggressive, and Snowball stemmers are not statistically signiﬁcant.
The Technology Structure and Appropriation of Server-Based Computing: A Case Study of a Taiwanese High Tech Firm

IT usage is key issue in MIS research. However, a variety of models such as Technology Acceptance Model (TAM) have neglected the role of technology structure in studying IT usage. Alternatively, IT appropriation considers how IT is called into use in terms of IT technology structures. However, the practices of IT appropriation have not yet been convincingly demonstrated. This paper explores the issues of IT appropriation. Specifically, we conduct our study in the context of Server-Based Computing (SBC), due to its unique technology structures, where the issues of appropriation process of SBC becomes relevant and important. In this paper, the Adaptive Structuration Theory (AST) provides a conceptual framework that helps to capture the appropriation process. Drawing on a Taiwanese case study, three perspectives of SBC appropriation process are examined including the faithfulness of appropriation, the attitudes toward use, and the consensus on appropriation. The case findings suggest that incremental change, identity development and interaction are of critical importance in the SBC appropriation process. Our findings contribute to the literature on IT infrastructure deployment, innovation and cooperative behavior, and the social perspective of information management. The implications and future research directions are also discussed.
RISE: Receipt-Free Cooperation Incentive Scheme for Multihop Wireless Networks

In this paper, we propose a receipt-free cooperation incentive scheme for multihop wireless networks. The nodes submit lightweight payment reports containing their alleged charges and rewards, and store undeniable security evidences. The fair reports can be cleared with almost no processing overhead. For the cheating reports, the evidences are requested to identify and evict the cheating nodes. Since cheating actions are exceptional, our scheme can significantly reduce the overhead of submitting and processing the payment data. Extensive analysis and simulations demonstrate that the proposed scheme can clear the payment with almost no processing overhead while achieving the same security strength as the receipt-based schemes.
Parallax angle parametrization in incremental SLAM

The lack of depth information in camera images has triggered much work on their use for localization and mapping in robotics. In particular, specific landmark parametrizations that isolate the unknown depth in one variable, and that allows to handle the associated large uncertainties have been proposed. Recently, an innovative parametrization (Parallax Angle) has shown to outperform the others in the context of a Bundle Adjustment approach. This paper investigates the way to exploit this parametrization in an incremental graph-based SLAM approach, in a robotics context in which motions measures can be incorporated in the overall estimation. It presents the factors required to initialize landmarks and manage their observations. Simulation results show that the proposed algorithms are able to incrementally incorporate observations, and a discussion analyzes how the incremental updates on ISAM2 are affected by these new factors.
The predictability of the extratropical stratosphere on monthly time‐scales and its impact on the skill of tropospheric forecasts

Extreme variability of the winter‐ and spring‐time stratospheric polar vortex has been shown to affect extratropical tropospheric weather. Therefore, reducing stratospheric forecast error may be one way to improve the skill of tropospheric weather forecasts. In this review, the basis for this idea is examined. A range of studies of different stratospheric extreme vortex events shows that they can be skilfully forecasted beyond 5 days and into the sub‐seasonal range (0–30 days) in some cases. Separate studies show that typical errors in forecasting a stratospheric extreme vortex event can alter tropospheric forecast skill by 5–7% in the extratropics on sub‐seasonal time‐scales. Thus understanding what limits stratospheric predictability is of significant interest to operational forecasting centres. Both limitations in forecasting tropospheric planetary waves and stratospheric model biases have been shown to be important in this context.
American Journal of Epidemiology Original Contribution Age at Menarche and Risk of Type 2 Diabetes: Results from 2 Large Prospective Cohort Studies

The authors investigated the association between age at menarche and risk of type 2 diabetes mellitus (T2DM)years of follow-up, respectively, 7,963 and 2,739 incident cases of T2DM were documented. Young age at menarche was associated with increased risk of T2DM after adjustment for potential confounders, including body figure at age 10 years and body mass index (BMI; weight (kg)/height (m) 2) at age 18 years. Associations were substantially attenuated after additional control for updated time-varying BMI. These data suggest that early menarche is associated with increased risk of T2DM in adulthood. The association may be largely mediated through excessive adult adiposity. The association was stronger among younger women, supporting a role for sex hormones in younger onset of T2DM, in addition to BMI. The prevalence of type 2 diabetes mellitus in the United States has increased rapidly during the last several decades, in parallel with the obesity epidemic (1–3). By the time type 2 diabetes is diagnosed, some individuals have already developed serious complications (2). Therefore, it has become increasingly important to identify persons at risk in early life so they may benefit from early interventions. Early menarche has been associated with risk factors for diabetes, such as excessive adiposity in childhood (4–6) and adulthood (7–10), as well as elevated blood glucose levels (11–14) and insulin resistance (15–17), independently of adiposity. Moreover, coincidental with the increasing prevalence of obesity and type 2 diabetes, age at menarche in US girls has been declining over the past 30 years (18, 19). Few studies have been conducted to examine the association between age at menarche and risk of type 2 diabetes. Findings from existing studies have been inconclusive because of small samples and lack of information on childhood or adulthood characteristics that could confound the association (14, 20, 21). Notably, one important characteristic of the escalating type 2 diabetes epidemic is a shift toward a younger age of onset. The association of age at menarche with type 2 diabetes among younger, middle-aged women was not addressed in previous studies, in which study populations were predominantly postmenopausal women (ages 40–92 years; average age, >57 years) (14, 20, 21). Therefore, we conducted prospective analyses in 2 large, independent cohorts including both old and young
Tradeoffs in Parallelism for Point Quadtree Nearest K Neighbors Problem

The period during which Moore’s Law governed the increase in processor speed is over. In an effort to push higher and higher performance out of a series of chips with constant clock rate, the major manufacturers have stated to move towards multiple cores per chip. In order to achieve greater algorithm speeds from this newer general purpose hardware, geometric database operations will need to exploit multi-core parallelism. However spatial database algorithms must be rewritten in a parallel way before they can exploit this new technology. Furthermore these parallel algorithms have to balance their runtime with the total work done on all processors. In this paper I analyze one such problem, the k nearest neighbors problem over point quadtrees, and present simulation results comparing the single processor version to several parallel variants. All simulations are performed on the XMT architecture [2] [3] developed at UMD to closely resemble PRAM.
Responses to Dynamic Head-and-Body Tilts are Enhanced in Parkinson's Disease

ABSTRACT: Background: Previous studies demonstrated that destabilizing responses to slow perturbations were enhanced in patients with Parkinson's disease (PD). Our objectives were to investigate the influence of PD on responses to faster whole head-and-body tilts in the standing position, and to establish whether any modification of tilt-evoked responses in PD patients was related to possible changes in the modulation of soleus (SO) H-reflex. Methods: Ten PD patients and 10 age-matched normal subjects assumed a standing position on an L-shaped tilting apparatus. Their head and shoulders were firmly attached to the back support of the apparatus, while their feet were fixated to the standing platform. With their vision occluded, the subject's whole head-and-body was suddenly tilted forward to 20°, at a peak head acceleration of 0.7g ± 0.lg. Tilt-evoked responses were recorded from the lower limb muscles bilaterally. In addition, 40 H-reflexes were elicited in the SO muscle at 30-190 ms intervals after the onset of head acceleration. The M response amplitude was kept within ±15% of its control value. Results: PD patients demonstrated an abnormally high responsiveness to whole head-and-body tilts in comparison with age-matched normal subjects. This was shown by the significantly larger proportion of PD patients manifesting responses in the SO, biceps femoris and vastus lateralis muscles (p<0.05), as well as their significantly larger SO response area (413%; p<0.01). In contrast, the amplitude of the SO H-reflex was significantly increased by only 14% (p<0.05) in these patients, and only at 30-70 ms after head acceleration onset. Conclusion: The overexcitable tilt-evoked responses of PD patients could originate from a reduced ability to suppress responses when the body is supported. This enhanced excitability of tilt-evoked responses was probably not due to motoneuronal hyperexcitability or decreased presynaptic inhibition of the group la terminals involved in the mainly monosynaptic H-reflex pathway. Thus, we hypothesize that the control of spinal interneurons involved in the tilt-evoked responses may be defective in PD.
Efficiency Measurement of Kenyan Commercial Banks

The idea of development is considered a vital strategy to the growth of any national economy. The banking system has been considered as the main sector that contributes significantly to the development of economy and hence the efficiency of commercial banks, gains significance. This study proposes to examine the efficiency of Private and Public Sector Banks in Kenya. It was found that the sample Kenyan commercial banks recorded volatility of variables during the study period. But the Public Sector Banks displayed better efficiency scores than the Private Sector Banks during the study period. DOI: 10.5901/mjss.2015. v6n4s2p621
Occlusion-Resistant Camera Design for Acquisition of Active Environments

We propose a family of Occlusion-Resistant Camera (ORC) designs for acquiring active environments despite the presence of moving interfering occluders. Being able to capture images in an in-use environment increases acquisition efficiency and quality without having to close-off the targeted site. Our cameras explicitly remove interfering dynamic occluders from acquired data in real-time and during live capture. Our key idea is to capture the scene at least twice from each viewpoint as the camera moves continually to sweep the scene and sample all surfaces. Our approach creates a single portable device combining the benefits of a stationary camera, which detects moving interfering occluders by image differencing, with those of a dynamic camera, which achieves scene coverage for inside-looking-out modeling. We describe our family of designs that progressively trades complexity for stricter camera orientation constraints, analyze their performance, and present a first ORC implementation.
On modeling of linear-assisted DC-DC voltage regulators

This paper presents the modeling of linear-assisted DC-DC regulators. This kind of voltage regulators consists of a switching converter together with a classic or LDO (low dropout) linear voltage regulator. While the linear regulator provides the constant output voltage, the switching converter conducts nearly all the current provided in the output load, and keeping the regulator current close to zero where the higher efficiency is achieved. However, the circuit could be unstable due to some critical parameters such as parasitic output capacitance; as a consequence, the mathematical modeling is obtained to study and corroborate the stability of the whole system.
Gamma-filter self-organising neural networks for unsupervised sequence processing

Adding γ-filters to self-organising neural networks for unsupervised sequence processing is proposed. The proposed γ-context model is applied to self-organising maps and neural gas networks. The γ-context model is a generalisation that includes as a particular example the previously published merge-context model. The results show that the γ-context model outperforms the merge-context model in terms of temporal quantisation error and state-space representation.
Marginal Gains: Monetary Transactions in Atlantic Africa

In America, almost all the money in circulation passes through financial institutions every day. But in Nigeria's "cash and carry" system, 90 percent of the currency never comes back to a bank after it's issued. What happens when two such radically different economies meet and mingle, as they have for centuries in Atlantic Africa? The answer is a rich diversity of economic practices responsive to both local and global circumstances. In "Marginal Gains," Jane I. Guyer explores and explains these often bewildering practices, including trade with coastal capitalism and across indigenous currency zones, and within the modern popular economy. Drawing on a wide range of evidence, Guyer demonstrates that the region shares a coherent, if loosely knit, commercial culture. She shows how that culture actually works in daily practice, addressing both its differing scales of value and the many settings in which it operates, from crisis conditions to ordinary household budgets. The result is a landmark study that reveals not just how popular economic systems work in Africa, but possibly elsewhere in the Third World.
' s personal copy Radiation characteristics of Chlamydomonas reinhardtii CC 125 and its truncated chlorophyll antenna transformants tla 1 , tlaX and tla 1-CW D

This experimental study reports, for the first time, the radiation characteristics of the unicellular green algae Chlamydomonas reinhardtii strain CC125 and its truncated chlorophyll antenna transformants tla1, tlaX and tla1-CWþ. Photobiological hydrogen production is a sustainable alternative to thermo-chemical and electrolytic technologies with the possible advantage of carbon dioxide mitigation. However, scale-up of photobioreactors from bench top to industrial scale is made difficult by excessive absorption and waste of light energy as heat and fluorescence. This results in limited light penetration into the photobioreactor and low solar to hydrogen energy conversion efficiency. To overcome these challenges, the algae C. reinhardtii have been genetically engineered with reduced pigment concentrations in their photosystems. This can improve the performance of photobioreactors by increasing the saturation irradiance of algae and quantum efficiency of photobiological hydrogen production. The extinction and absorption coefficients of all strains studied are obtained from normal– normal and normal–hemispherical transmittance measurements over the spectral range from 300 to 1300 nm. Moreover, a polar nephelometer is used to measure the scattering phase function of the microorganisms at 632.8 nm. It is established that the wild strain C. reinhardtii CC125 has major absorption peaks at 435 and 676 nm, corresponding to the in vivo absorption peaks of chlorophyll a, and at 475 and 650 nm corresponding to those of chlorophyll b. The genetically engineered strains have less chlorophyll pigments than the wild strain and thus have smaller absorption cross-sections. In particular, the mutant tlaX features a significant reduction in chlorophyll b concentration. For all mutants, however, the reduction in the absorption cross-section is accompanied by an increase in scattering cross-section. Although scattering becomes the dominant phenomenon contributing to the overall extinction of light, it is mainly in the forward direction. Thus, to fully assess the effect of genetic engineering on light transport in the photobioreactor requires careful radiation transfer analysis using the radiation characteristics reported in this study. a 2008 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved. * Corresponding author. Tel. : þ1 (310) 206 5598; fax: þ1 (310) 206 4830. E-mail address: pilon@seas.ucla. edu (L. Pilon). Avai lab le a t www.sc iencedi rec t . com j ourna l homepage : www.e lsev ier . com/ loca te /he 0360-3199/$ – see front matter a 2008 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.ijhydene. 2008.07. 071 i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y 3 3 ( 2 0 0 8 ) 6 4 6 7 – 6 4 8 3 Author's personal copy
Artificial immune system-based classification in class-imbalanced problems

We investigate the effect of the Class Imbalance Problem on the performance of an Artificial Immune System(AIS)-based classification algorithm. Our motivation stems from the fact that the Adaptive Immune System constitutes one of the most sophisticated biological systems which is particularly evolved in order to continuously address an extremely unbalanced pattern classification problem. That is the “self”/“non-self” discrimination process, consisting in classifying any cell as “self” or “non-self”. Our experimentation indicates that the AIS-based classification paradigm has the intrinsic properly in dealing more efficiently with highly skewed datasets than standard pattern classification algorithms such as the Support Vector Machines (SVMs). Specifically, the experimental results presented in this paper provide justifications concerning the superiority of AISbased classification in identifying instances from the minority class.
Morphological Priming Effect: The Role of Surface Frequency

Two cross-modal experiments were conducted to investigate the format of lexical representation of suffixed derived words and their stems. The results show that only low frequency suffixed words (as opposed to high frequency suffixed words) yield a full priming effect of their stems. By contrast, a stem (e.g., travail) does not fully prime words belonging to the same morphological family (e.g., travailleur), although it primes high frequency suffixed words more than it does low frequency words. To account for these findings we propose a model in which the stem and high frequency affixed words are represented both as full forms and as decomposed morphemes while low frequency affixed words are represented only in a decomposed form.
An integrated model for learning style classification in university students using data mining techniques

Different people may have a different learning styles and it is important to provide the most suitable content and course materials for learning. However, determining the learning style may be difficult due to limited information about the learner and lack of a learner profile. The learner has to complete a questionnaire form based on educational theory in order to determine the learning style. Moreover, it is necessary to know the learner's study record related to other factors such as demographic factors. Therefore, an enhanced model to identify learning style is needed. This research aims to address the problem of identifying the learning style for a new student. A learning style classification model was proposed and ensemble classification techniques were implemented. The results showed that the proposed ensemble classification techniques performed better compared to other classification techniques used in the experiment.
The Basic-Level Convergence Effect in Memory Distortions

Whereas most previous findings suggest that memory may become more abstract over time, so that memory for gist outlasts verbatim memory, there are findings suggesting that abstract information may sometimes be instantiated in more specific terms. In this study, we examined the hypothesis that retained information tends to converge at an intermediate level of abstractness—the basic level. In two experiments, we found bidirectional, symmetrical shifts in the memory for story material: Participants presented with either subordinate terms (e.g., sports car) or superordinate terms (e.g., vehicle) tended to falsely report basic-level terms (e.g., car) instead. This pattern emerged for both recall and recognition memory tests, at both immediate and delayed testing, and under free and forced reporting. The results suggest that the basic level, which has been considered cognitively optimal for perception, categorization, and communication, is also the preferred level for retaining episodic information in memory.
Sequential Bayesian optimization as a POMDP for environment monitoring with UAVs

Bayesian Optimization has gained much popularity lately, as a global optimization technique for functions that are expensive to evaluate or unknown a priori. While classical BO focuses on where to gather an observation next, it does not take into account practical constraints for a robotic system such as where it is physically possible to gather samples from, nor the sequential nature of the problem while executing a trajectory. In field robotics and other real-life situations, physical and trajectory constraints are inherent problems. This paper addresses these issues by formulating Bayesian Optimization for continuous trajectories within a Partially observable Markov Decision Process (POMDP) framework. The resulting POMDP is solved using Monte-Carlo Tree Search (MCTS), which we adapt to using a reward function balancing exploration and exploitation. Experiments on monitoring a spatial phenomenon with a UAV illustrate how our BO-POMDP algorithm outperforms competing techniques.