Miracle-dz/UniFAR-FTUs huggingface dataset:
BLAG: Improving the Accuracy of Blacklists

—IP address blacklists are a useful source of information about repeat attackers. Such information can be used to prioritize which trafﬁc to divert for deeper inspection (e.g., repeat offender trafﬁc), or which trafﬁc to serve ﬁrst (e.g., trafﬁc from sources that are not blacklisted). But blacklists also suffer from overspecialization – each list is geared towards a speciﬁc purpose – and they may be inaccurate due to misclassiﬁcation or stale information. We propose BLAG, a system that evaluates and aggregates multiple blacklists feeds, producing a more useful, accurate and timely master blacklist , tailored to the speciﬁc customer network. BLAG uses a sample of the legitimate sources of the customer network’s inbound trafﬁc to evaluate the accuracy of each blacklist over regions of address space. It then leverages recommendation systems to select the most accurate information to aggregate into its master blacklist. Finally, BLAG identiﬁes portions of the master blacklist that can be expanded into larger address regions (e.g. /24 preﬁxes) to uncover more malicious addresses with minimum collateral damage. Our evaluation of 157 blacklists of various attack types and three ground-truth datasets shows that BLAG achieves high speciﬁcity up to 99%, improves recall by up to 114 times compared to competing approaches, and detects attacks up to 13.7 days faster, which makes it a promising approach for blacklist generation.
PATTERN RECOGNITION METHODS IN PHYSICAL TRAINING EVALUATION AND PLANNING

The paper presents some pattern recognition methods used for the analysis of the data in the unsupervised learning context. The aim of the data processing is to assess the level of the physical condition of the sportsmen and their chances to gain future performance. These methods are based on several unsupervised algorithms, In the first part of the paper a model of an unsupervised learning system is underlined based on hierarchical classification. The definitions, axioms and theorem given in the paper provide a strong formalism that assures the reliability of this technique. The automatic decision making process based on the method of unsupervised learning in pattern space was experimented in the case of sportsmen from swimming team.
The lournal of the Association of Schools and Colleges of Optometry

Problem-based learning at The New England College of Optometry was introduced into the second year clinical -program in the fall of 1991. The primary goals were: (1) to serve as a transition phase for the second year students into patient care; (2) to provide our students the opportunity, early in their professional education, to apply existing knowledge and newly acquired knowledge in a patient care situation; and (3) to begin acquiring skills in clinical decision making. The design and implementation of this course is the subject of the following paper.
Prototype Support Vector Machines: Supervised Classification in Complex Datasets

Classifier learning generally requires model selection, which in practice is often an ad hoc and time-consuming process that depends on assumptions about the structure of data. To avoid this difficulty, especially in real-world data sets where the underlying model is both unknown and potentially complex, we introduce the ensemble of prototype support vector machines (PSVMs). This algorithm trains an ensemble of linear SVMs that are tuned to different regions of the feature space and thus are able to separate the space arbitrarily, reducing the need to decide what model to use for each dataset. We present experimental results demonstrating the efficacy of PSVMs in both noiseless and noisy datasets.
Children Need More Information for Comprehension: Limits on the Agent-First Preference in Korean

knowledge of word order in early sentence comprehension. Psychological Science, 17(8), 684–691. Goldin-Meadow, Susan, Wing Chee So, Aslı Özyürek, & Carolyn Mylander. (2008). The natural order of events: How speakers of different languages represent events nonverbally. In Rochel Gelman (Ed.), Proceedings of the National Academy of Sciences, 105(27), 9163–9168. 603
Insulin resistance in diabetes: The promise of using induced pluripotent stem cell technology

Insulin resistance (IR) is associated with several metabolic disorders, including type 2 diabetes (T2D). The development of IR in insulin target tissues involves genetic and acquired factors. Persons at genetic risk for T2D tend to develop IR several years before glucose intolerance. Several rodent models for both IR and T2D are being used to study the disease pathogenesis; however, these models cannot recapitulate all the aspects of this complex disorder as seen in each individual. Human pluripotent stem cells (hPSCs) can overcome the hurdles faced with the classical mouse models for studying IR. Human induced pluripotent stem cells (hiPSCs) can be generated from the somatic cells of the patients without the need to destroy a human embryo. Therefore, patient-specific hiPSCs can generate cells genetically identical to IR individuals, which can help in distinguishing between genetic and acquired defects in insulin sensitivity. Combining the technologies of genome editing and hiPSCs may provide important information about the genetic factors underlying the development of different forms of IR. Further studies are required to fill the gaps in understanding the pathogenesis of IR and diabetes. In this review, we summarize the factors involved in the development of IR in the insulin-target tissues leading to diabetes. Also, we highlight the use of hPSCs to understand the mechanisms underlying the development of IR.
Intraductal Papillary Mucinous Neoplasia of the Pancreas - Pathologic Features and Molecular Markers - A Review

Intraductal papillary mucinous neoplasm (IPMN) of the pancreas are pre neoplastic lesions defined by the World Health Organization as a grossly visible intraductal epithelial neoplasm that arises in the pancreatic ductal system, composed of mucin producing cells. The predisposing factor for their development as well as genetics are still largely unknown. Pathologists have a pivotal role in IPMN management since features like IPMN subtype, degree of atypia, margins status and presence or absence of an invasive component imply different patient management. In this article, we perform a review of the pathological features and molecular markers of IPMNs.
Mosaic Methods for Improving the Accuracy of Interferometric Based Digital Elevation Models

The last two decades, SAR interferometry is used in order to produce Digital Elevation Model (DEM) for wide areas. However, the DEM produced by only one interferometric pair is characterized by low accuracy, due to several parameters that affect the final result. In this study, the improvement of the DEM accuracy is attempted through the production of a mosaic DEM derived by multiple interferometric-based DEMs. Two methods are used to create the mosaic DEM. According to the first method, the entire height information included in the various interferometric-based DEMs is introduced in the procedure. In the second method only the selected areas of the interferometric-based DEMs participate in the production of the mosaic DEM. The selection is based on the comparison between interferometric-based DEMs with another ancillary DEM (e.g. ASTER GDEM). For both methods, the mosaic DEM generation is based on the precision file which provides a height accuracy map that is estimated from parameters such as coherence, baseline and wavelength. Although this file is not always reliable it can be used to define weights for the height values of the available interferometric-based DEMs during the mosaic DEM generation. The Root Mean Square Error (RMSE) is used to estimate the vertical accuracy. The validation of the DEMs is achieved by comparing them with a sufficient number of ground control points as well with an accurate reference DEM. The mosaic DEM produced by the first method does not yield improvements in accuracy, whereas the second method provides significant improvements depending on the accuracy of the reference DEM being used.
WiFi Localization Method Using a Gaussian Process Particle Filter

Indoor localization with low-cost sensors remains an open problem. At the same time, accurate knowledge about the position of a user offers the opportunity for a variety of novel services in many environments in which GPS is not available. A large number of studies have been conducted on wireless-based localization for GPS-denied environments. These methods use global systems for mobile communication (GSM), ultra wideband (UWB), worldwide interoperability for microwave access (WiMAX), Bluetooth, RFID, or WiFi. (1,2) Among these systems, WiFi is one of the most useful wireless signals for indoor global localization. WiFi antennas are available in almost all devices, and access points that are already present in the environment can be readily used. Furthermore, WiFi-based localization is resilient to ambiguities due to the unique identifier provided by the access points. The main problem in WiFi-based localization is the construction of accurate signal models. In real environments, signals are subject to reflections, diffractions, refractions, and other jamming factors. Therefore, estimating an accurate model of a sensor signal is very difficult. Another problem is that the density of preliminarily training data of WiFi affects localization accuracy. In the present paper, we address WiFi-based localization problems using the Gaussian process and a Gaussian process particle filter. Gaussian process regression takes into account the presence of training data and estimates the uncertainty of models. In addition, the Gaussian process particle filter automatically increases its uncertainty when the target enters an area in which there are insufficient training data. 2. Gaussian Process for the Wireless Signal Model
Gender Equality as an Enforcer of Individuals’ Choice between Education and Fertility: Evidence from 19th Century France

Recent theoretical developments of growth models, especially on unified theories of growth, suggest that the child quantity-quality trade-off has been a central element of the transition from Malthusian stagnation to sustained growth. Using a unique census-based dataset, this article explores the role of gender on the trade-off between education and fertility across 86 French counties during the nineteenth century, as an empirical extension of Diebolt and Perrin (2013, 2019a). We first test the existence of the child quantity-quality trade-off in 1851. Second, we explore the long-run effect of education on fertility from a gendered approach. Two important results emerge: (i) significant and negative association between education and fertility is found, and (ii) such a relationship is non-uniform over the distribution of education/fertility. While our results suggest the existence of a negative and significant effect of the female endowments in human capital on the fertility transition, the effects of negative endowment almost disappear at a low level of fertility.
Guided Search in miniKanren

Traditional relational programming languages often provide a fixed, simple search strategy: Prolog implementations natively provide depth-first search to find answers (though other strategies are often supported) while most miniKanren implementations perform search using a breadth-first approach. In the field of Artificial Intelligence, both of these strategies are often discarded for best-first strategies, including A∗ Search, Beam Search, Dijkstra’s Algorithm, and Uniform Cost Search. We focus on uniform-cost search, presenting a framework for guided search in the miniKanren relational language embedded in Scheme. This paper revises the traditional miniKanren lazy search implementation, imposing a partial ordering on the search space exploration in order to find answers in a programmer-specified order.
From Debugging Towards Live Tuning of Reactive Applications

Directly visualizing the effect of changes to applications improves developers productivity as they gain immediate insights on the resulting application behavior. Yet, immediate feedback requires a representation of the dataflow in the application to correctly propagate and apply the effect of the changes. Reactive programming is a programming paradigm which directly expresses applications dataflow in a declarative way. Recently, researchers developed dedicated debugging techniques for reactive programming that use the dataflow graph to enable inspections and visualization. In this paper, we adopt reactive debugging as a basis for live modifications and tuning of reactive applications. To this end we extend the debugger to allow live modifications to the dataflow graph in a structured manner to change the application behavior. We also suggest how developers of reactive applications can use such extension to enable flexible tuning of applications at run time. Our early experience shows that the combination of reactive programming and live programming allows modifications and tuning of applications while ensuring safety and consistency guarantees.
Ease of use and Awareness to use as a Predictor of Confidence in E-Banking Leading to Adoption of E-Banking: The Case of Islamic Banks in Pakistan

Iram Naz 1 , Mubashar Hassan Zia 2∗, Ammara Riaz Chohan 3, Masood Hassan 4, Tariq Iqbal Khan 5 1 Assistant Professor, Faculty of Management Sciences (FMS), Riphah International University, Islamabad, Pakistan 2 Sr. Lecturer, FMS, Riphah International University, Islamabad, Pakistan 3 MS Scholar, FMS, Riphah International University, Islamabad, Pakistan 4 Sr. Lecturer, Department of Business Administration, IoBM, Karachi, Pakistan 5 Assistant Professor, Department of Management Sciences, University of Haripur, Pakistan
Conjugate in Endometrial Carcinoma EphA2 Targeted Chemotherapy Using an Antibody Drug

Authors' 2Departme Non-Codin 4Departm Medicine, H Samsung M 6Departme Konkuk Un Gynecolog Pathology, Kwandong 9Departme Hospital, G Maryland Note: Supp Research O Correspo Departmen of Texas M 1352, Hou E-mail: aso
Baryons in a light-front approach

We present a model for baryons based on three constituent quarks using light-front holography together with basis light-front quantization (BLFQ). The work is generalized from the method which originally developed for meson systems using a constituent quark and an antiquark. We construct an effective 3-body Hamiltonian, which consists of a transverse confining interaction based on the Ads/QCD soft-wall model, and a longitudinal confining interaction which was first applied to mesons. We employ this model for the proton by calculating its form factor F1(q 2). The results are compared with experimental measurements and other theoretical methods. We develop generalized Jacobi coordinates, as well as a generalized longitudinal confinement, that will enable this model to be generalized to systems with more than three constituent quarks.
State-feedback Control of a Current Source Inverter-based STATCOM

The static synchronous compensator (STATCOM) is well known as a reactive power compensator with the best performance in the power system recently, which is used in power systems to regulate the line voltage, enhance the power transmission capacity and extend the transient stability margin. STATCOM is conventionally realized by a voltage-source converter; however, being a current injection device, its performance can be improved when realized by a current-source converter (CSC) that can generate a controllable current directly at its output terminals. A STATCOM based on the current-source converter topology is proposed. The nonlinear model of the current-source converter, which is the source of the difficulties in the controller design, has been modified to a linear model through a novel modeling technique. The proposed modeling technique is not based on the linearization of a set of nonlinear equations around an operating point. Instead, the power balance equation and a nonlinear input transformation are used to derive a linear model independent of the operating point. This model acts as the basis for the design of a decoupled state-feedback controller. The proposed STATCOM has been simulated using the PSCAD/EMTDC package. The simulation results show that a CSC-based STATCOM can result in excellent current and voltage waveforms as well as very short response time while operating at a low switching frequency. This makes the proposed scheme suitable for high power applications. Ill. 6, bibl. 11 (in English; summaries in English, Russian and Lithuanian).
Optimal spoiling of the transverse magnetization in the Actual Flip-angle Imaging (AFI) sequence for fast B1 field mapping

Fig. 2. Spoiling behavior of the AFI sequence in the weak (a: TR1/TR2=10/50 ms, AG1/AG2=16.7/82.6 mT*ms/m) and strong (b: TR1/TR2=15/75 ms, AG1/AG2=163/827 mT*ms/m) spoiling regimes. The independently measured actual α=58.8°. Top: Experimental signal measurements (points) are superimposed with simulations (lines). Bottom: Experimentally determined flip angles (black lines) are superimposed with simulations (red lines).
Protocols : The Good , the Bad and the Ugly

Protocolized care has been espoused by many as the answer to the problem of variability in medical treatment. The gradual movement in this country towards embracing the concept of evidence-based medicine has given further weight to the notion of rendering care more uniform. By identifying its role as “the conscientious, explicit, and judicious use of current best evidence in making decisions about the care of individual patients,” the proponents of evidence-based medicine seek to meld the competing priorities of physician autonomy and medical accountability. In this presentation, I will examine the impact of protocolized care, particularly as it applies to critical care, on our current practice, looking at the successes and failures of its application. I will then explore the relationship between physicians and protocols, not only in the trenches, but as an extension of the sociologic concept of the relationship between humans and plans in general.
GENERATIONAL PERSPECTIVE ON THE 1996-2001 INTER-METROPOLITAN MIGRATION IN CANADA

Based on the 2001 Canadian census, we characterized and explained the 1996-2001 inter-metropolitan migrations of different generations. In the descriptive analysis, we found that being consistent with the expected effects of acculturation, the overall outand in-migration rates increased monotonically from the 1 to the 3+ generation, whereas in Toronto and Vancouver where the attractiveness of well-established co-ethnic communities tended to weaken with increasing generation, the in-migration rate actually decreased monotonically from the 1 to the 3+ generation. In the multivariate analysis, we found that the migration behaviours of all generations were in general subject to the expected effects of labor market factors, attraction by co-ethnic communities, and accessibility to the rest of the system; and that with respect to the effects on out-migration propensity, increase in generation had the effects of weakening educational selectivity and strengthening age selectivity.
A Bayesian Network Classifier of Some Triatomine Vectors of Chagas Disease

Chagas disease (CD) disease is a life-threatening tropical parasitic disease caused by the flagellate protozoan Trypanosoma cruzi. T. cruzi is typically transmitted to humans and other mammals by the bite of "kissing bugs" of the subfamily Triatominae (family Reduviidae), primarily by species belonging to the Triatoma, Rhodnius, and Panstrongylus genera. Rapidly identifying CD insect vectors in the field is crucial to effective control of the disease. Here I describe a Bayesian network triatomine classifier that supports rapid identification of adults of nine CD vector species.
Research of Nanoscale MOSFET Parameters Impact on the Performance of Energy Converters for Internet of Things

Nowadays the devices with wireless supply are increasingly used in industry, commerce, logistics, construction as well as in everyday life. So Internet of Things technologies allow forming ‘intellectual’ nets of physical objects, interacting between each other through RF radiation, thanks to which the creation of diverse automated systems like smart home is possible [1-6]. By means of Wireless Sensor Networks [1, 2, 4, 6-9] one can in real-time mode monitor the state of various complex systems and objects, e.g. durability degree of a building or a bridge. In Radio-frequency Identification technology [4, 6-16] miniature devices called tags or transponders are deployed. The tags are attached to different objects in production facilities, shopping centers and warehouses for implementation the automated identification and also used in access control systems. Thus in all of the above applications wireless micro devices are used. These micro devices exchanges data with the base station interacting with computer system resulting in automated identification, surveillance and management are carried out.
Application of Diversity Indices in the Study of Trees and Shrubs of the Nun River Forest, Nigeria

Plants generally are an integral part of the ecosystem, and play several roles including protection, recreation, productivity, nutrition and medicine. Most plants, including shrubs and trees, have been reported to play essential roles in the control of soil erosion, contribute in the stabilization of climate among others. But in the recent times, the global forests have been decreasing due to several human factors including agricultural activities, urbanization, industrialization, population growth, bush burning (Izah et al., 2017, 2018, Izah and Seiyaboh, 2018a,b; Izah, 2018). During long term reversible or irreversible human activities in forest, its resources including plants and animals are affected with regard to their composition, distribution and abundance. Zhigila et al. (2015) and Fries and Herman (1990) reported that on annual basis about 294.020 square kilo metres of the world’s forests disappear. Close to 3 decades from this estimation, the global population has increased. As such, the diminishing rate of global forest could have far exceeded this approximation.
Generating random bigraphs with preferential attachment

The bigraph theory is a relatively young, yet formally rigorous, mathematical framework encompassing Robin Milner's previous work on process calculi, on the one hand, and provides a generic meta-model for complex systems such as multi-agent systems, on the other. A bigraph $F = \langle F^P, F^L\rangle$ is a superposition of two independent graph structures comprising a place graph $F^P$ (i.e., a forest) and a link graph $F^L$ (i.e., a hypergraph), sharing the same node set, to express locality and communication of processes independently from each other. In this paper, we take some preparatory steps towards an algorithm for generating random bigraphs with preferential attachment feature w.r. t. $F^P$ and assortative (disassortative) linkage pattern w.r. t. $F^L$. We employ parameters allowing one to fine-tune the characteristics of the generated bigraph structures. To study the pattern formation properties of our algorithmic model, we analyze several metrics from graph theory based on artificially created bigraphs under different configurations. Bigraphs provide a quite useful and expressive semantic for process calculi for mobile and global ubiquitous computing. So far, this subject has not received attention in the bigraph-related scientific literature. However, artificial models may be particularly useful for simulation and evaluation of real-world applications in ubiquitous systems necessitating random structures.