Miracle-dz/UniFAR-FTUs huggingface dataset:
Some Aspects of Personality of Individual in International Law (Rights of Individual in the International Criminal Court, Rights of Migrants, Refugees, Rights of Women and Children in International Humanitarian Law, Rights of Investors)

The article investigates the controversial issue of international legal personality interpretation. The disparities in understanding the concept of international law subject explain the lack of international legal instruments that could ascertain the exact legal positions of natural persons in question. By a thorough analysis of legal sources, the authors aimed at identifying both general legal parameters of legal personality representation in international law and its individual forms in particular, such as the rights of migrants, refugees, victims of armed conflicts, and investors as economic bloc representatives. The research demonstrates that as opposed to the positions maintained in foreign scientific literature, which tend to treat individuals as subjects of international law, the dominant point of view in the Russian doctrine of international law is the one suggesting that these persons are not subjects of international public law. In the submitted article, the authors entered upon formation of context perception of legal personality and believe that further research might be focused on assessing the degree of compliance of national legislations in coalitions.
USABLE TTS FOR INTERNET SPEECH ON DEMAND

“Speech on demand” applications need to communicate knowledge from a large and/or changing collection of data, and thus can’t pre-record all of the possible verbal information needed. Instead these applications must use some form of synthesis to convert data into an auditory form. Textual data can be transformed into speech through the use of Text To Speech synthesis, and there are certain factors such as bit rate, quality, expression, and delay that impact upon the usability of such speech on demand systems. This paper discusses different implementations of speech on demand systems, using Text To Speech synthesis, and assesses how usability is affected.
Scenario-Based Requirement Analysis

1. Introduction When developing software engineering, many steps are taken. One of the most critical phases is, to elicit and analyze requirements (Saiedian, Kumarakulasingam & Anan, 2005). In term of system engineering, requirements can be seen as what the system must do to achieve the goals. It is one of many important factors that can determines a success of build or improve the system. Thus, capturing, analyzing, validating, documenting requirement are a vital activities. The purpose of analyze requirement is to see whether all requirements are clear, complete and really resolve the conflict.
Improving Pipelined Soft Processors with Multithreading

Designers of FPGA-based systems are increasingly including soft processors-processors implemented in programmable logic-in their designs. Any combination of area, clock frequency, performance, and power may be of importance in the choice of a soft processor design to use, motivating area efficiency as the best metric with which to compare potential designs. In this paper we demonstrate that 3, 5, and 7-stage pipelined multithreaded soft processors are 33%, 77%, and 106% more area efficient than their single-threaded counterparts, the result of careful tuning of the architecture, ISA, and number of threads.
Establishing Nomological Networks for Behavioral Science: a Natural Language Processing Based Approach

As the accumulated research base of the behavioral sciences have grown, the amount of actual knowledge discovery has not kept pace as evidenced by an increasing number of disconnected theories and the related problem of construct proliferation. Therefore, integrating social and behavioral sciences across research areas or even disciplines in a meaningful way is imperative. Despite the information systems (IS) discipline’s leadership on creating nomological networks and inter-nomological networks for research integration, a quantitative approach to automatically establish nomological networks from large-scale data is missing. Based on the design science paradigm, we therefore propose a novel natural language processing based approach bringing together these two previous research endeavors. We used a dataset consisting of all the relevant behavioral studies from two tops journal in the IS and psychology fields to evaluate our approach in comparison to human decisions. Finally, the limitations and possible extensions of our approach are critically discussed.
Image Steganography by Variable Embedding and Multiple Edge Detection using Canny Operator

This paper proposes a method for image steganography. According to Human Visual System, any variation in the edges shown in the images has a low probability of being perceived by the human eyes, thus data can be hidden in the pixel of the cover image. These edges can be detected by using sophisticated operators like Canny edge detection operator. The gradient of the pixel of the image is determined and the image edges are detected by taking a threshold value of the gradient image. Here we go for multiple edge detection so that more number of pixels around the edge area is detected using the above method. Thus resulting in embedding of more information bits in the LSB of the image pixels further again we go for variable embedding so the combination of multiple edge detection and variable embedding improves the data hiding capacity. The multiple edge detection is limited to three times so as to reduce the distortions. To further increase the data hiding capacity and at the same time maintain a respectable PSNR variable embedding method is employed. For extraction of data the stego image is compared with the cover image, and the variation in the pixel values are detected, thus the embedded data is efficiently extracted.
Itemset Frequency Satisflability: Complexity and Axiomatization 1

Computing frequent itemsets is one of the most prominent problems in data mining. We study the following related problem, called FREQSAT, in depth: given some itemset-interval pairs, does there exist a database such that for every pair the frequency of the itemset falls into the interval? This problem is shown to be NPcomplete. The problem is then further extended to include arbitrary Boolean expressions over items and conditional frequency expressions in the form of association rules. We also show that, unless P equals NP, the related function problem|flnd the best interval for an itemset under some frequency constraints|cannot be approximated e‐ciently. Furthermore, it is shown that FREQSAT is recursively axiomatizable, but that there cannot exist an axiomatization of flnite arity.
Intravenous β-blockers in primary percutaneous coronary intervention: new hope for an old therapy.

Primary percutaneous coronary intervention (PCI) is the preferred strategy of reperfusion for patients with ST-segment–elevation myocardial infarction (STEMI). With contemporary PCI techniques and adjunctive pharmacological therapy, primary PCI restores optimal epicardial flow in as many as 95% of patients with STEMI.1 However despite remarkable improvement in the outcomes of patients with STEMI, mortality and morbidity remain significant.2 To further improve the efficacy of reperfusion, considerable efforts are being made on 2 fronts: the development of systems to provide timely access to PCI for patients with STEMI to reduce time to reperfusion3 and the investigation of therapies to minimize reperfusion injury (ie, to render myocardial cells more resistant to the detrimental effects of the ischemia/reperfusion cycle). 4 The restoration of blood flow to the ischemic myocardium is associated with reperfusion injury manifested as myocardial stunning, no reflow, arrhythmias, and myocardial hemorrhage. Experimental studies in animals suggest that reperfusion injury may account for up to 50% of the final infarct size.5 Despite decades of research, an understanding of reperfusion injury remains elusive, and remarkably little success has been achieved with translational research in cardioprotective therapeutics.6 Article see p 1495 β-Blockers have long been a component of care in patients with acute myocardial infarction because of their ability to reduce myocardial oxygen consumption by reducing heart rate and myocardial contractility. Preclinical studies showed reduced infarct size in dogs, particularly when the β-blockers are administered before coronary artery ligation.7 Several clinical studies performed in the prereperfusion era have demonstrated beneficial effects of β-blockers in acute myocardial infarction in terms of reduction of infarct size8,9 or improved survival.10,11 Conversely, in the thrombolytic era, randomized studies involving early intravenous administration of β-blockers were largely disappointing, with no improvement in left ventricular function, infarct size, …
Porto Alegre: a Brazilian city searching to be smarter

This article presents the findings from the first-round analysis of some initiatives in Porto Alegre, capital of the State of Rio Grande do Sul (Brazil), following the Smart Cities Initiatives Framework from Chourabi et al. In order to do that, secondary data from official websites and other available and reliable information sources are examined. The data collected combined with the framework factors of smart cities provide a faithful overview of the evolution of Porto Alegre as a city searching to be smarter. The objective here is not making a deep analysis of these initiatives. Instead, this paper aims at giving an overview of the several initiatives taking into account the eight factors produced by the members of the Smart Cities and Service Integration Project research team. The findings demonstrate the potential and the needs of further studies into some of these initiatives by using the interview protocol developed and already used in semi-structured interviews made by this group. This preliminary analysis may lead to the conclusion that the city has fully achieved the requirements of a smart city. However, since most of second data come from official sources that could be considered overly positive.
98 12 44 4 v 1 2 4 D ec 1 99 8 Cosmological Red Shift . An Information Mechanics Perspective

A photon’s observed wavelength tells an astronomical detector about the amount of position information obtained by observing that photon. This amount of position information appears to depend on time in a way which, to first order over distances small compared to the size of the universe, may account for the cosmological red shift. Interpretation of cosmological red shift as due to rapid recession of distant light sources has relied on a classical-mechanical picture (Hubble, 1936). Here, we ask about information received in detecting a photon emitted long ago and far away. Specifically, the photon’s observed wavelength tells the detector about the amount of position information accessed by such detection. This amount of position information appears to depend on time in a way which, to first order over distances small compared to the size of the universe, may account for the cosmological red shift. In information mechanics (IM) (Kantor, 1977; hereinafter cited as IM ), there is a longest possible length λ1 (IM , p.188); “radius” RU of universe U is defined as λ1/(2π) (IM , p.212). The amount of information indicated by a photon’s wavelength is λ1 divided by the photon’s wavelength (IM ; Kantor 1997). Quantum mechanics (QM) appears in restricted form as a special case in IM. The picture discussed here was reached via IM; it is expressed here using terms which may be more familiar from QM.
Using Data Mining Techniques in Development of MURA Geometric Prediction Module for Large Area Photomask

Data Mining is concerned with the different applications for discovery of a priori unknown relationships such as associations, groupings, and classifiers from data. The solution of MURA problems in producing to the large photomask industry is finding the association rules or the algorithms for learning classifiers from relational data. In this paper, we designed and developed a MURA related association rules which are suitable for the MURA model requirements, and we named MURA Risk rating system. Our purpose is to figure out the effective application of data mining algorithms in monitoring and control of complex Large Area Photomask systems. We combine the Data Mining into MURA risk management. It is indeed saving time from standby machine, and expectation of the photomask processing graphic of MURA problems. By our scheme and MURA risk rating system, we can shorten the time and reduce the MURA problems.
Bats of Barbados

The chiropteran fauna of Barbados includes representatives of four families — Noctilionidae, Phyllostomidae, Vespertilionidae, and Molossidae — including 1 piscivore (Noctilio leporinus), 1 omnivore (Brachyphylla cavernarum), 1 pollenivore/nectarivore (Monophyllus plethodon), 1 frugivore (Artibeus jamaicensis), and 2 insectivorous species (Myotis nyctor and Molossus molossus). Despite an early report, we believe that preponderance of the evidence available at this time is that E. fuscus is not part of the fauna of Barbados. The Barbadian chiropteran fauna of 6 species is much smaller than those on the four neighboring Lesser Antillean islands to the west and north. We believe that this is primarily the result of two factors—geological age and geographic isolation. Our work indicates that populations of the 6 species of bats on Barbados are in good condition in all cases, but only for Artibeus jamaicensis and Molossus molossus are the populations large enough to not be of ongoing concern. The maintenance of the chiropteran fauna can best be served by three management actions — preservation of caves and associated gullies, forests, and hydrological systems. Keywords: Barbados, biodiversity, Chiroptera, Myotis nyctor, systematics, zoogeography
Evaluating the usefulness of content addressable storage for high-performance data intensive applications

Content Addressable Storage (CAS) is a data representation technique that operates by partitioning a given data-set into non-intersecting units called chunks and then employing techniques to efficiently recognize chunks occurring multiple times. This allows CAS to eliminate duplicate instances of such chunks, resulting in reduced storage space compared to conventional representations of data. CAS is an attractive technique for reducing the storage and network bandwidth needs of performance-sensitive, data-intensive applications in a variety of domains. These include enterprise applications, Web-based e-commerce or entertainment services and highly parallel scientific/engineering applications and simulations, to name a few. In this paper, we conduct an empirical evaluation of the benefits offered by CAS to a variety of real-world data-intensive applications. The savings offered by CAS depend crucially on (i) the nature of the data-set itself and (ii) the chunk-size that CAS employs. We investigate the impact of both these factors on disk space savings, savings in network bandwidth, and error resilience of data. We find that a chunk-size of 1 KB can provide up to 84% savings in disk space and even higher savings in network bandwidth whilst trading off error resilience and incurring 14% CAS related overheads. Drawing upon lessons learned from our study, we provide insights on (i) the choice of the chunk-size for effective space savings and (ii) the use of selective data replication to counter the loss of error resilience caused by CAS.
On the Relationship between Attachment Styles and Attitude towards Drugs: Moderating Role of Personality Traits

Objective: The present study aimed at investigating the moderating role of personality traits in the relationship between attachment styles and attitude towards drugs. Method: To this end, 190 firstsemester students of Tehran Payam Noor University (south center) in 2013-2014 were randomly selected and requested to revised adult attachment scale, Eysenck personality questionnaire, and attitude towards drugs questionnaire. Results: The results of this study indicated that only avoidance attachment style could predict attitude towards drugs and this relationship could be significantly moderated by neuroticism. Conclusion: The results of this study can have applications and implications in the development of treatment and training programs for addiction prevention in vulnerable
Sampling in image space for vision based SLAM

Loop closing in vision based SLAM applications is a difficult task. Comparing new image data with all previous image data acquired for the map is practically impossible because of the high computational costs. This problem is part of the bigger problem to acquire local geometric constraints from sensor data for geometric map building termed data association. Commonly the computational costs are kept small by sampling the image data uniformly over time or using a position estimate from a mapping and localization algorithm. In this paper we propose a more natural sampling approach, by determining a subset that best describes the complete image data in the space of all previously seen images. The actual problem of finding such a subset is called the Connected Dominating Set problem which is well studied in field of graph theory. The proposed method is particularly beneficial for realistic mapping scenarios including moving objects and persons, motion blur and changing light conditions. Evaluation on multiple large indoor datasets show that the method performance is very close to that of an exhaustive data association scheme and outperforms other sampling approaches.
Convergence Property Analysis for PSO Based on Cluster-Degree

The concept of cluster-degree was put forward and distribute status of particle with different cluster-degree was studied. The reasonable parameters setting range based on cluster-degree was proposed. Under the direction of cluster-degree, many parameters which can get better searching results were found. So this paper is helpful for the choosing and adjustment of PSO parameters in practical application.
Bayes-Optimal Chemotaxis

Chemotaxis plays a crucial role in many biological processes, including nervous system development. However, fundamental physical constraints limit the ability of a small sensing device such as a cell or growth cone to detect an external chemical gradient. One of these is the stochastic nature of receptor binding, leading to a constantly fluctuating binding pattern across the cell's array of receptors. This is analogous to the uncertainty in sensory information often encountered by the brain at the systems level. Here we derive analytically the Bayes-optimal strategy for combining information from a spatial array of receptors in both one and two dimensions to determine gradient direction. We also show how information from more than one receptor species can be optimally integrated, derive the gradient shapes that are optimal for guiding cells or growth cones over the longest possible distances, and illustrate that polarized cell behavior might arise as an adaptation to slowly varying environments. Together our results provide closed-form predictions for variations in chemotactic performance over a wide range of gradient conditions.
Rules and construction effects in learning the argument structure of verbs.

Theorists of language acquisition have long debated the means by which children learn the argument structure of verbs (e.g. Bowerman, 1974, 1990; Pinker, 1984, 1989; Tomasello, 1992). Central to this controversy has been the possible role of verb semantics, especially in learning which verbs undergo dative-shift alternation in languages like English. The learning problem is somewhat simplified in Bantu double object constructions, where all applicative verbs show the same order of postverbal objects. However, Bantu languages differ as to what that order is, some placing the benefactive argument first, and others placing the animate argument first. Learning the language-specific word-order restrictions on Bantu double object applicative constructions is therefore more akin to setting a parameter (cf. Hyams, 1986). This study examined 100 three- to eight-year-old children's knowledge of word order restrictions in Sesotho double object applicatives. Performance on forced choice elicited production tasks found that four-year-olds showed evidence of rule learning, although eight-year-olds had not yet attained adult levels of performance. Further investigation found lexical construction effects for three-year-olds. These findings suggest that learning the argument structure of verbs, even when lexical semantics is not involved, may be more sensitive to lexical construction effects than previously thought.
Estimation of Muscle Fatigue during Cyclic Contractions Using Source Separation Techniques

Previous research studies have reported that spectral compression of the surface Electromyogram (SEMG) towards lower frequencies is associated with onset of localized muscle fatigue. One reason for this spectral compression has been attributed to motor unit synchronization in literature. According to this, motor units are pseudo randomly excited during muscle contraction, and the recruitment pattern changes during the onset of muscle fatigue, such that the firing of motor units becomes more synchronized. While this theory is widely accepted, there is little experimental proof of the phenomenon. This paper has used source dependence properties and measures developed in research related to independent component analysis (ICA) to test for synchronization. This paper has also determined that the global matrix can be used as a measure for estimating localized muscle fatigue during cyclic movements.