Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Lightweight Main Memory Database for Telecom Network Performance Management System

Today telecom network are growing complex. Although the amount of network performance data increased dramatically, telecom network operators require better performance on network performance data collection and analysis. Database is the important component in modern network management model. Since main memory database (MMDB) store data in main physical memory and provide very high-speed access, MMDB can suffice the requirements on data intensive and real time response in network performance management system. This paper presents a novel lightweight design on MMDB for network performance data persistence. This design improves data access performance in following aspects. The data persistence mechanism employs user mode memory map provided by UNIX OS. To reduce the cost of data copy and data interpretation, the data storage format is designed as consistent with binary format in application memory. The database is provided as program library and the application can access data in shared memory to avoid the cost on inter-process communication. Once data is updated in memory, query application can get updated data without disk I/O cost. The data access methods adopt multi-level RB-Tree structure. In best case, the algorithm complexity is O(N). In worst case, the algorithm complexity is O(N*lgN). In real performance data distribution scenarios, the complexity is nearly O(N). The system approach has been tested in laboratory using benchmark data. The result shows the performances of the application fully meet the requirements of the product index. The CPU and memory consumption are also lower than network management system requirements.
An iterative screening strategy based on detection performance for multi-channel cooperative spectrum sensing

Cooperative spectrum sensing's false alarm probability and detection probability can be affected seriously when certain SUs with poor detection performance or some malicious SUs exist. To solve this problem, an iterative screening strategy based on detection performance (ISDP) strategy is proposed for multi-channel cooperative spectrum sensing in distributed CR networks. We divide time into fixed-length slots, during each slot, SU first senses channels by energy detection, and then broadcasts its local binary results to others using the common control channel (CCC). Once having received all of the other SU's binary sensing results, SU immediately executes the SU Adjust strategy to make its own decision on whether to continue sensing in next time slot or not. Finally, a two-slot forgetting function is executed to improve SU's local detection performance. In this manner, these SUs with poor detection performance can be screened out quickly one by one as time going on. Performance analysis and simulation results demonstrate that under a very easy condition, the ISDP strategy can effectively eliminate these sensing users with poor detection performance, decrease the number of cooperative users, and greatly improve the CR system's detection performance.
Calibration and imaging challenges at low radio frequencies: An overview of the state of the art

Many scientific deliverables of the next generation low frequency radio telescopes require high dynamic range imaging. Next generation telescopes under construction indeed promise at least a ten-fold increase in the sensitivity compared with existing telescopes. The projected achievable RMS noise in the images from these telescopes is in the range of 1--10$\mu$Jy/beam corresponding to typical imaging dynamic ranges of $10^{6-7}$. High imaging dynamic range require removal of systematic errors to high accuracy and for long integration intervals. In general, many source of errors are directionally dependent and unless corrected for, will be a limiting factor for the imaging dynamic range of these next generation telescopes. This requires development of new algorithms and software for calibration and imaging which can correct for such direction and time dependent errors. In this paper, I discuss the resulting algorithmic and computing challenges and the recent progress made towards addressing these challenges.
INFLUENCE OF PROJECT PLANNING ON THE PERFORMANCE OF COMMUNITY BASED HIV PROJECTS IN KIAMBU, KENYA

Purpose: The purpose of this study was to determine the influence of project planning on the performance of Community based HIV projects in Kiambu, Kenya. Methodology: The study used descriptive survey research method and adopted stratified random sampling to identify a sample size of 151 respondents out of the target population of 249 NPOs implementing HIV projects in the 12 sub-counties in Kiambu. A structured questionnaire with closed and open-ended questions collected primary data. A pilot study to test the validity and reliability of the research instrument using Cronbach’s alpha was undertaken. The collected data was edited, cleaned and analyzed using descriptive statistics with the aid of the Statistical Package for Social Science (SPSS 21.0). Correlation and regression were used to determine the relationship between critical success factors and project performance of Community based HIV projects. Data was presented in tables, charts and figures. Results: The study found that project planning had a significant and positive relationship with the performance of Community based HIV projects in Kiambu, Kenya. Unique contribution to theory, practice and policy: Project objectives should be aligned to the organization's strategic plan, with top management allocating sufficient resources for the project and giving the project manager room to run the project. Keywords: Project planning, performance, Community based HIV projects.
Distributed Cooperative Regulation for Multiagent Systems and Its Applications to Power Systems: A Survey

Cooperative regulation of multiagent systems has become an active research area in the past decade. This paper reviews some recent progress in distributed coordination control for leader-following multiagent systems and its applications in power system and mainly focuses on the cooperative tracking control in terms of consensus tracking control and containment tracking control. Next, methods on how to rank the network nodes are summarized for undirected/directed network, based on which one can determine which follower should be connected to leaders such that partial followers can perceive leaders' information. Furthermore, we present a survey of the most relevant scientific studies investigating the regulation and optimization problems in power systems based on distributed strategies. Finally, some potential applications in the frequency tracking regulation of smart grids are discussed at the end of the paper.
Multikernel Adaptive Filtering

This paper exemplifies that the use of multiple kernels leads to efficient adaptive filtering for nonlinear systems. Two types of multikernel adaptive filtering algorithms are proposed. One is a simple generalization of the kernel normalized least mean square (KNLMS) algorithm [2], adopting a coherence criterion for dictionary designing. The other is derived by applying the adaptive proximal forward-backward splitting method to a certain squared distance function plus a weighted block l1 norm penalty, encouraging the sparsity of an adaptive filter at the block level for efficiency. The proposed multikernel approach enjoys a higher degree of freedom than those approaches which design a kernel as a convex combination of multiple kernels. Numerical examples show that the proposed approach achieves significant gains particularly for nonstationary data as well as insensitivity to the choice of some design-parameters.
A Robust Technique of Anti Key-Logging using Key-Logging Mechanism

System security and privacy always have to face new confronts. Continuous updates in the operating systems and anti-virus applications strive to amplify the system security level. In recent years 'key-loggers' have proved to be one of the prevalent intimidations to security and privacy. Key-logger is a surreptitious surveillance application, which is used to keep record of user's activities on the computer in various ways like keyboard logging, screen logging, mouse logging and voice logging, completely in imperceptible mode. Although key-loggers can also be used for prolific purposes but due to the tremendous increase in the Internet usage, the caustic use of key-loggers simply surmounts its advantages. Key-loggers have gained so much supremacy in their execution that they have become a serious intimidation to the privacy and security of a computer. The fact which makes the key-loggers more perilous is their undetectable nature against anti-virus and spy-where applications. This paper discusses some existing techniques of fortification against key-loggers and also exemplifies a new technique along with its proved advantages.
Efficacy and safety of recombinant human follicle stimulating hormone (Gonal-F) with urinary human chorionic gonadotrophin for induction of spermatogenesis and fertility in gonadotrophin-deficient men.

In order to evaluate the efficacy and safety of recombinant human follicle stimulating hormone (r-hFSH) in combination with urinary human chorionic gonadotrophin (HCG) to induce spermatogenesis and fertility in gonadotrophin-deficient men, we conducted a prospective, open, non-comparative multicentre study in two Australian academic medical centres. Ten men with gonadotrophin deficiency requiring induction of spermatogenesis and fertility were treated with HCG for 3-6 months followed by the s.c. self-administration of injections of r-hFSH in combination with HCG for 18 months. Among the eight men who commenced r-hFSH treatment, seven demonstrated sperm output at a median of 6 months and five achieved the target sperm output of 1. 5x10(6) per ml at a median of 9 months of FSH treatment. Mean testicular volume increased by 4.2 ml during FSH treatment. Three men produced pregnancies in their partners, two of which resulted in the birth of healthy babies and a third patient's partner had a miscarriage. We conclude that r-hFSH is well tolerated and effective in inducing testis growth, spermatogenesis and fertility in gonadotrophin-deficient men. The efficacy of r-hFSH seems comparable with urinary FSH at restoring normal fertility in gonadotrophin-deficient men.
Assessing mitochondrial dysfunction in primary cardiomyocytes Mitochondrial reserve capacity is a sensitive measure of cellular stress

This Application Note describes a method for pro ling mitochondrial function in cells responding to stress. The mitochondrial pro le generated in this way provides four parameters of mitochondrial function that can be measured in one experiment: basal respiration rate, ATP-linked respiration, proton leak, and reserve capacity. The results described here suggest that the development of cardiomyocyte injury, in this case caused by an oxidized lipid, increases ATP-linked oxygen consumption, diminishes respiratory ef ciency, and depletes the bioenergetic reserve capacity.
A Preliminary Study of Statistically Predictive Syntactic Complexity Features and Manual Simplifications in Basque

In this paper, we present a comparative analysis of statistically predictive syntactic features of complexity and the treatment of these features by humans when simplifying texts. To that end, we have used a list of the most five statistically predictive features obtained automatically and the Corpus of Basque Simplified Texts (CBST) to analyse how the syntactic phenomena in these features have been manually simplified. Our aim is to go beyond the descriptions of operations found in the corpus and relate the multidisciplinary findings to understand text complexity from different points of view. We also present some issues that can be important when analysing linguistic complexity.
Rapid Relationality: How Peripheral Experts Build a Foundation for Influence with Line Managers

This paper develops grounded theory to understand how and when experts in lower-power peripheral roles can develop influential relationships with higher-power line managers in core functions to regularly elicit their cooperation. I use data from an ethnographic study of experts in peripheral roles—mental health professionals hired by the U.S. Army to provide rehabilitative services to active-duty soldiers suffering from conditions such as post-traumatic stress disorder (PTSD)—and the line managers in core functions they depended on for their soldier-care recommendations to be followed—their soldiers’ direct commanders. I analyze relational histories of 56 commander–provider dyads and detail a three-phase process model I refer to as “rapid relationality. ” Through the process of rapid relationality, mental health professionals capitalized on short windows of opportunity to quickly develop influential relationships with commanders, despite lacking formal authority over them, before a series of minor conflicts or a major conflict threatened their burgeoning influence. My analysis suggests it is not only what peripheral experts do that allows them to elicit cooperation from line managers but also when and how quickly they do it that matters. Speed and taking early action are important because experts cannot predict when conflict will occur and hence may have short initial windows of opportunity for establishing an influential relationship. I further find that some experts have fewer tactics available to them or must use more time-consuming and energy-intensive tactics than others to achieve the same relational influence based on their personal characteristics (e.g., gender). As a result, it may be harder for some experts to achieve relational influence before their window of opportunity closes.
Interactive Rule Interestingness Learning

Data mining is the efficient discovery of patterns in large databases, and classification rules are perhaps the most important type of patterns in data mining applications. However, the number of such classification rules is generally too huge that selection of interesting ones among all discovered rules becomes an important task. In this paper, factors related to the interestingness of a rule are investigated and some new factors are proposed. Following this, an interactive rule interestingness-learning algorithm (IRIL) is developed to automatically label the classification rules either as “interesting” or “uninteresting” with limited user participation. In our study, VFPI (Voting Feature Point Intervals), a feature projection based concept description learning and classification algorithm, is also developed in the framework of IRIL. Being specific to our concerns, VFPI takes the rule interestingness factors as features and is used to learn the rule interestingness concept and to classify the unlabeled classification rules. The success of the previously developed feature projection based learning and classification techniques encouraged us to develop VFPI. The empirical results based on TCMB (Central Bank of Turkish Republic) data set give promising results.
A non-parametric method based on NBNN for automatic detection of liver lesion in CT images

An automatic liver lesion detection method for CT images is presented, which need not learn the model parameters and segment liver region. The lesion detection problem is formulated as finding a region with maximal score. The developed method employs an over-segmentation algorithm to generate the superpixels (small regions) and adapts the Naive Bayes Nearest Neighbor (NBNN) classifier to score the superpixels. Then, the connected superpixels with positive scores are aggregated as the detected regions. The performance of the method is evaluated on a data set consisting of 442 CT slices of 129 patients acquired in portal venous phase of contrast enhancement. The pixel-wise accuracy for classification and recall for detection can achieve 93% and 62%, respectively. The method can work well for hyperdense, hypodense, and heterogeneous liver lesions.
Internationalization at home: the case of Business Week Entrepreneurship

Globalization and changes in market labour demand for higher education institutions concerning new commitments in the process of students training. The internationalization and entrepreneurship are strategic factors that promote the differentiation of students skills profile at the end of each cycle of education. This study analyzed the contribution of International Project Business Week Entrepreneurship Setubal to the internationalization of the campus, also considering the purchase of a set of skills essential to a manager in the twenty-first century. This study uses a case study methodology supported in two sources of data collection - questionnaire surveys applied to all students and interviews applied to Portuguese students. The results allowed to confirm the propositions and assess the relevance of this kind of projects and teaching methodologies for the development of important skills to nowadays managers.
Level set trees with enhanced marginal density visualization

We study level set tree methods to analyze and visualize multivariate data. The probability density function of the underlying distribution is estimated using a kernel density estimator, and the density estimate is visualized using level set trees. These trees can be used to analyze the mode structure of a function. We show how level set trees can be used to enhance more traditional density function visualization tools, like marginal densities and slices of the density. The method is applied to flow cytometry data.
Design Evolution of Low-Cost Humanoid Robot CALUMA

In this paper the design evolution of CALUMA (CAssino Low-cost hUMAnoid) robot has been illustrat ed. CALUMA robot is composed by sub-systems of prototype s that have been designed and built at LARM in the recent pas . These sub-systems have been modified suitably in order to achieve a whole assembly of the proposed humanoid robot. Probl ems and solutions of sub-system designs have been considere d for suitable operation and design of CALUMA. Mechanical modifications of components in terms of shapes, mec hanism configuration and structures have been developed fo r a final design of CALUMA. Preliminary solutions of the robot are reported to show and discuss problems during the evo lution of its design. By using dynamic simulations, the opera tion of CALUMA has been checked in order to study mechanical feasibility and efficiency.
Rough Set Theory for Topological Spaces in Information Systems

In this paper, we present an alternative way for constructing a topological space in information systems. We use the theory of rough set and show that the topology is a quasi discrete-topology. We apply this topology to characterize the roughness property of a set involving dependency of attributes and apply the notions of base and sub-base to attribute reduction and rough membership function.
An Examination of Domestic Migration from California Counties

California has experienced a net loss of domestic migrants within the United States every year since 1990. This reversal from Californiaâ€™s traditional attraction to migrants has been attributed to numerous causes including the high cost of housing, the cyclical downturn in business activity, and a decline in the level of amenities and quality of life that drew thou-sands of migrants to California each year over several decades. This paper uses Internal Rev-enue Service county migration data to examine outmigration flows and assesses the influences of proximity and urban classification on migration flows. Simple and augmented gravity models investigate distance and population effects, finding surprisingly little effect of economic variables but significant differences among counties in the roles of distance and population.
Theoretical analysis on reconstruction-based super-resolution for an arbitrary PSF

This study presents and proves a condition number theorem for super-resolution (SR). The SR condition number theorem provides the condition number for an arbitrary space-invariant point spread function (PSF) when using an infinite number of low resolution images. A gradient restriction is also derived for maximum likelihood (ML) method. The gradient restriction is presented as an inequality which shows that the power spectrum of the PSF suppresses the spatial frequency component of the gradient of ML cost function. A Box PSF and a Gaussian PSF are analyzed with the SR condition number theorem. Effects of the gradient restriction on super-resolution results are shown using synthetic images.
In vivo magnetic resonance imaging tracking of transplanted superparamagnetic iron oxide-labeled bone marrow mesenchymal stem cells in rats with myocardial infarction

Superparamagnetic iron oxide (SPIO) nanoparticles generate superparamagnetism, thereby resulting in an inhomogeneous local magnetic field, which shortens the T2 value on magnetic resonance imaging (MRI). The purpose of the present study was to use MRI to track bone marrow mesenchymal stem cells (BMSCs) labeled with SPIO in a rat model of myocardial infarction. The BMSCs were isolated from rats and labeled with SPIO. The anterior descending branch of the coronary artery was ligated under anesthesia. Two weeks later, the rats received, at random, 5×107 SPIO-labeled BMSCs, 5×107 unlabeled BMSCs or a vehicle (100 μl phosphate-buffered saline) via direct injection into the ischemic area (20 animals/group). MRI was used to track the SPIO-labeled BMSCs and the rats were then sacrificed to verify the presence of BMSCs using immunohistochemistry with an anti-CD90 antibody. The procedure labeled 99% of the BMSCs with SPIO, which exhibited low-intensity signals on T2 and T2* MRI imaging. At 24 h post-BMSC transplantation, low-intensity MRI signals were detected on the T2 and T2* sequences at the infarction margins. After 3 weeks following transplantation, low-intensity signals started to appear within the infarcted area; however, the signal intensity subsequently decreased and became indistinct. Immunohistochemistry revealed that the SPIO-labeled BMSCs migrated from the margin into the infarcted region. In conclusion, the BMSCs were readily labeled with SPIO and in vivo and MRI tracking demonstrated that the SPIO-labeled BMSCs established and grew in the infarcted myocardium.
What is Being Black and High Achieving Going to Cost me in your School? Students Speak Out About their Educational Experiences Through a Racial Opportunity Cost Lens

Abstract:Researchers have documented how schools perpetuate an unequal opportunity structure for low- income students of color. However, most of the attention has focused on low academic performers. We contribute to a growing body of research that shows how the educational needs of high-achieving, low-income students of color are not being met. Using the concept of racial opportunity cost, we share the perspectives of five African American high achieving, low- income students as they explain the high premium they pay to achieve academic success. We utilized a qualitative, phenomenological research design to understand the lived experiences of the five participants. Data were collected through focus groups and individual semi-structured interviews. Through our findings, we provide an explanation of what it means to be labeled at-risk versus being placed at-risk.
Evaluation of resilience in self-adaptive systems using probabilistic model-checking

The provision of assurances for self-adaptive systems presents its challenges since uncertainties associated with its operating environment often hamper the provision of absolute guarantees that system properties can be satisfied. In this paper, we define an approach for the verification of self-adaptive systems that relies on stimulation and probabilistic model-checking to provide levels of confidence regarding service delivery. In particular, we focus on resilience properties that enable us to assess whether the system is able to maintain trustworthy service delivery in spite of changes in its environment. The feasibility of our proposed approach for the provision of assurances is evaluated in the context of the Znn.com case study.