Miracle-dz/UniFAR-FTUs huggingface dataset:
A fast algorithm on finding the non-dominated set in multi-objective optimization

A fast algorithm is proposed to find the nondominated set for multiobjective optimization problems in this paper. Two accelerated techniques are adopted in the algorithm. One is that the algorithm can yield an integer rank set after it indexes the search space. Based on this, the goal is changed into determination of the nondominated set of the integer rank set. The other is that the nondominated check sequence follows that the likely nondominated members are first checked, and that the check process is stopped when the remaining members in the nondominated check sequence are dominated. The computational complexity of the new algorithm is analyzed theoretically. Experimental results show that the new method performs much better than KLP (a famous effective algorithm) when the search space contains a large nondominated set. Moreover, the two new techniques introduced in this paper are very useful for multiobjective evolutionary algorithms (MOEAs) to improve the computational speed.
Investigating Open Source Project Success: A Data Mining Approach to Model Formulation, Validation and Testing

This paper demonstrates the use of Data Mining (DM) techniques in exploratory research. A robust model for identifying the factors that explain the success of Open Source Software (OSS) projects is created, validated and tested. The predictive modeling techniques of Logistic Regression (LR), Decision Trees (DT) and Neural Networks (NN) are used together in this analysis. Using Text Mining results in the predictive modeling process strengthens the model. SAS ® Enterprise Miner and SAS ® Text Miner are used in this research.
Distributed Operating Systems based on Manager Agents

In this paper we use the multi agent concept in order to present a new distributed operating system architecture, that is based on agent-like, individual servers, called manager agents, for each light weight process. Each manager agent is tailored to the needs of its corresponding process. It is responsible for the management of all resources the process needs during its whole lifetime. Combined with the cooperation among the manager agents a resource management is obtained that on the one hand adapts to individual requirements of each process and on the other achieves an optimal system wide management for all applications. We demonstrate the functionality of this architecture on the example of a distributed address space management. One of the main areas of development in computer science over the last decade was focused on parallel computers. However, a real breakthrough in establishing a wide range of parallel applications has not yet been reached. Some people even speak of a \parallel crisis", in analogy to the well known \software crises" at the end of the sixties. Compared to the high prices of parallel computers and the additional costs for reprogramming existing software to exploit the new hardware, in many cases the gains in performance are low. Using a network of computers instead of one parallel computer becomes more and more attractive. In theory, current workstation clusters reach the computation power of parallel computers, but they only cost a fraction of the price of parallel computers. Furthermore it is possible to run new parallel software on a network of computers as well as existing software. However, to exploit the potential laying within a cluster of workstation, a distributed operating system is needed that ooers all services required by existing software, new services for distributed systems (e.g. le sharing), and additional, eecient services for parallel systems (e.g. load balancing). Current distributed operating systems (e.g. 1, 2, 3, 4]) try to approach theses goals by extending existing operating systems. State of the art operating systems are build on the client-server-model 5]. Based on a micro-kernel the main functionality of the operating system is provided by a group of cooperating processes, called servers, that is used by user processes, called clients. The job of the micro-kernel is to virtualize the hardware, i.e. to hide low hardware details from the servers. Each server is responsible for one resource class, like e.g. a group of memory cells or …
A small world algorithm for high-dimensional function optimization

In this paper, we describe a new small world optimization algorithm for obtaining satisfactory solution for high-dimensional function. Based on the small world phenomenon which is revealed in Milgram's sociological experiment, some operators with decimal-coding strategy are proposed, and then an “imitated society” decimal-coding small world optimization algorithm (DSWOA) is designed to solve high-dimensional function optimization. Compared with the corresponding evolution algorithms, such as orthogonal genetic algorithm with quantization (OGA/Q), the simulation results of several benchmark functions with high dimension show that DSWOA can acquire satisfied solution, has also a better stability, and a fast convergence rate. Therefore, it is feasible to solve high-dimensional optimization problems.
Fixed-threshold SMO for Joint Constraint Learning Algorithm of Structural SVM

In this paper, we describe a fixed-threshold sequential minimal optimization (FSMO) for a joint constraint learning algorithm of structural classification SVM problems. Because FSMO uses the fact that the joint constraint formulation of structural SVM has b=0, FSMO breaks down the quadratic programming (QP) problems of structural SVM into a series of smallest QP problems, each involving only one variable. By using only one variable, FSMO is advantageous in that each QP sub-problem does not need subset selection.
One Scan Sanitization of Informative Association Rules

We propose here a one-scan sanitization algorithm to hide informative association rules. For a given predicting item, an informative association rule set by Jiuyong Li et. al, (2001) is the smallest association rule set that makes the same prediction as the entire association rule set by confidence priority. To hide association rules, previously proposed algorithms based on a priori approach require multiple scanning of database to calculate the supports of the large itemsets. In this work, we propose using a pattern-inversion tree to store related information so that only one scan of database is required. Numerical experiments show that the performance is more efficient than previous algorithms with similar side effects
Discovery of 10 pulsars in an Arecibo drift‐scan survey

We present the results of a 430-MHz survey for pulsars conducted during the upgrade to the 305-m Arecibo radio telescope. Our survey covered a total of 1147 deg 2 of sky using a drift-scan technique. We detected 33 pulsars, 10 of which were not known prior to the survey observations. The highlight of the new discoveries is PSR J0407+1607, which has a spin period of 25.7 ms, a characteristic age of 1.5 Gyr and is in a 1.8-yr orbit about a low-mass (>0.2 M ○. ) companion. The long orbital period and small eccentricity (e = 0.0009) make the binary system an important new addition to the ensemble of binary pulsars suitable to test for violations of the strong equivalence principle. We also report on our initially unsuccessful attempts to detect optically the companion to J0407+1607, which imply that its absolute visual magnitude is >12.1. If, as expected on evolutionary grounds, the companion is an He white dwarf, our non-detection implies a cooling age of least 1 Gyr.
Tenascin C in metastasis: A view from the invasive front

The extracellular matrix protein tenascin C (TNC) is a large glycoprotein expressed in connective tissues and stem cell niches. TNC over-expression is repeatedly observed in cancer, often at the invasive tumor front, and is associated with poor clinical outcome in several malignancies. The link between TNC expression and poor survival in cancer patients suggests a role for TNC in metastatic progression, which is responsible for the majority of cancer related deaths. Indeed, functional studies using mouse models are revealing new roles of TNC in cancer progression and underscore its important contribution to the development of metastasis. TNC has a pleiotropic role in advancing metastasis by promoting migratory and invasive cell behavior, angiogenesis and cancer cell viability under stress. TNC is an essential component of the metastatic niche and modulates stem cell signaling within the niche. This may be crucial for the fitness of disseminated cancer cells confronted with a foreign environment in secondary organs, that can exert a strong selective pressure on invading cells. TNC is a compelling example of how an extracellular matrix protein can provide a molecular context that is imperative to cancer cell fitness in metastasis.
Genetic Optimization Tuning of an Automatic Voltage Regulator System

In this paper, a genetic optimization with a new fitness function method is proposed to design a PID controller for the automatic voltage regulator system (AVR). The proposed fitness function is made by cost function to improve the transient response of the controlled system and optimize the gain. The proposed algorithm applied in the PID controller design for the AVR system. Based on simulation results, author observed that the proposed genetic algorithm with this new fitness function can find a PID control parameter set effectively so that controlled AVR system has a better control performance.
Statistical Failure Analysis of a Web Server System

Failure phenomena of web server systems are considered to depend on their workload characteristics. In this paper we focus on an Apache server system and analyze the real access/error logs. Based on parametric and non-parametric statistics, we characterize the web server failure from both theoretical and empirical points of view. As the result, it can be shown that the number of sessions strongly affects to the failure rate property of the Apache server.
Consumers ’ trust and high quality markets : a development perspective 1

The paper analyses the relationship between internal regulation on quality and the market for high quality products in the case of credence goods, focusing on the case in which there is no legal market for low quality and with special attention to food products. In the model expected quality is a function of consumers’ beliefs about the effectiveness of regulation. Foreign consumers, who cannot observe regulation as closely as domestic ones, may partly base their expectations on the level of development of the exporting country. Low effectiveness, negative stereotype and low consumers’ trust may cause a failure in the market for high quality, and there may be a trap of underdevelopment and no high quality exports. The main policy implications are that increasing the effectiveness of regulation improves export prospects; standard setting and enforcement by external actors, such as supermarkets or NGOs in the case of certain niche markets is likely to be beneficial. A further implication is that pursuing the harmonization of standards is a better strategy than mutual recognition, since the latter does not address the trust problem between countries with vastly different income levels. Journal of Economic Literature L15 Information and Product Quality; Standardization and Compatibility F13 Trade Policy; International Trade Organizations O12 Microeconomic Analyses of Economic Development ∗ Corresponding author. E-mail: cuffaro@unicas.it Affiliation: Faculty of Economics. University of Cassino. Italy Personal Address: Nadia Cuffaro. Via di San Francesco a Ripa, 61. 00153 Roma. Italy Telephone: 0039 06 5896487 e-mail: cuffaro@unicas.it web page: http://www.eco. unicas.it/docente/cuffaro/
Unit-Root Tests and the Burden of Proof

Simulation evidence is presented on the finite sample properties of two tests for stationarity recently proposed by Kwiatkowski, Phillips and Schmidt (1991) and Park (1990). Unlike earlier unit-root tests, these test the null of stationarity against the alternative of a unit root, thereby reversing the usual burden of proof. We also examine the consequenes of using the Kwiatkowski, Phillips and Schmidt test in conjuction with a standard unit-root test. These results suggest that the frequency of incorrect conclusions may be decreased relative to the application of only standard unit-root tests. Also, such a joint testing procedure may in some cases permit researchers to be more confident about their tests' results.
Robust Resilience and Substantial Interest: A Survey of Pharmacological Cognitive Enhancement among University Students in the UK and Ireland

Use of ‘smart drugs’ among UK students is described in frequent media reports as a rapidly increasing phenomenon. This article reports findings from the first large-scale survey of pharmacological cognitive enhancement (PCE) among students in the UK and Ireland. Conducted from February to September 2012, a survey of a convenience sample of 877 students measured PCE prevalence, attitudes, sources, purposes and ethics. Descriptive and logistic regression statistical methods were used to analyse the data. Lifetime prevalence of PCE using modafinil, methylphenidate or Adderall was under 10%, while past regular and current PCE users of these substances made up between 0.3%–4% of the survey population. A substantial majority of students was unaware of and/or uninterested in PCE; however about one third of students were interested in PCE. PCE users were more likely to be male, British and older students; predictors of PCE use included awareness of other students using PCEs, ADHD symptomatology, ethical concerns, and alcohol and cannabis use. The survey addresses the need for better evidence about PCE prevalence and practices among university students in the UK. We recommend PCE-related strategies for universities based on the survey findings.
High-throughput cognitive assessment using BrainTest.org: examining cognitive control in a family cohort

Understanding the relationship between brain and complex latent behavioral constructs like cognitive control will require an inordinate amount of data. Internet‐based methods can rapidly and efficiently refine behavioral measures in very large samples that are needed for genetics and behavioral research. Cognitive control is a multifactorial latent construct that is considered to be an endophenotype in numerous neuropsychiatric disorders, including attention deficit/hyperactivity disorder (ADHD). While previous studies have demonstrated high correlations between Web‐ and lab‐based scores, skepticism remains for its broad implementation.
INFLUENCE OF NETWORK DELAYS IN RESIDUAL COMPUTATION

Abstract A challenging problem that motivates this work is the network delay effects in residual computation. Residuals are assumed to be identically zero in fault-free situations whereas deviations from zero alert the presence of fault in the system. In practice residuals are not identically zero due to various factors (measurements noises, modelling uncertainties, delays, and so on). This work is focused on the study of the availability of data, due to delays in the communication network, to compute residuals. An optimal dynamic alignment of data in a time window (Dynamic Time Warping) is proposed and tested to reduce errors when computing residuals.
A privacy-aware communication scheme in Advanced Metering Infrastructure (AMI) systems

In smart grid, Advanced Metering Infrastructure (AMI) systems feed the metering data to Energy Supplier (ES) every 15 minutes. Using this information, ES can offer incentives to reduce the total power consumption during the peak hours through the real-time pricing mechanism. However, it also brings privacy concerns. Since the metering data is collected by the ES nearly in real-time, the customer's behavior and habits can be disclosed via the statistical patterns. The privacy problem will hamper the development and deployment of future smart grid. In this paper, we propose a novel metering data transmission scheme in wireless networks. In each Smart Meter (SM), the metering data is split into two parts randomly: Part 1 and Part 2, where the sum of two parts is equal to the original metering data. Part 1 is sent to the ES via cellular link, and Part 2 is sent to the next SM via Wireless Sensor Network (WSN) link. Then the next SM merges Part 2 of the previous SM into its original metering data, and creates the updated metering data. Using the proposed scheme, the metering data received by the ES is randomized, and the customer's privacy can be effectively protected even if some SM cooperates with the ES.
5-Hydroxy-9-methylstreptimidone, a new glutarimide from a Streptomyces sp. HIL Y-9065403.

wereport their production, isolation, structure elucidation and biological properties. Strain HIL Y-9065403 was isolated from a soil sample collected in Nainital, India. The strain was identified as belonging to the genus Streptomyces using the methods described by Shirling and Gottlieb2). A loopful of mature slant culture of Streptomyces Y-9065403 was inoculated into Erlenmeyer flasks (500ml capacity)
Tracking Interacting Objects Using Intertwined Flows

In this paper, we show that tracking different kinds of interacting objects can be formulated as a network-flow mixed integer program. This is made possible by tracking all objects simultaneously using intertwined flow variables and expressing the fact that one object can appear or disappear at locations where another is in terms of linear flow constraints. Our proposed method is able to track invisible objects whose only evidence is the presence of other objects that contain them. Furthermore, our tracklet-based implementation yields real-time tracking performance. We demonstrate the power of our approach on scenes involving cars and pedestrians, bags being carried and dropped by people, and balls being passed from one player to the next in team sports. In particular, we show that by estimating jointly and globally the trajectories of different types of objects, the presence of the ones which were not initially detected based solely on image evidence can be inferred from the detections of the others.
Enhancement of Sight Effectiveness by Dual Infrared System: Evaluation of Image Fusion Strategies

The problem of objective evaluation of multisensor image fusion strategies is analysed for the design of a dual infrared system. Such a system should be used to enhance the sight effectiveness in assisting a driver or a pilot in bad visibility conditions. Two no-reference indexes are used to quantify the performance of different image fusion methods. Numerical results are presented and discussed in terms of the quality of the fused images. Index Terms – Image/video processing. Data fusion. Image quality indexes.
THE COMPARISON OF NARCISSISM SCORES OF FEMALE ATHLETES IN DIFFERENT BRANCHES

This study aims to compare narcissism levels of female athletes in different branches. The narcissism levels of students who voluntarily agreed to participate in the study have been measured through 16-question Narcissistic Personality Inventory (NPI-16) which has been coordinated by Daniel R. Ames, Paul Rose and Cameron P. Anderson in 2005. The validity and the reliability of the Inventory have been done by Salim ATAY in 2009. For analyses of the data, Portable IBM SPSS Statistics v20 software package was used. The descriptive analysis, one-way Anova analysis which was used to determine the difference between two variances and Tukey’s test were also used in data analysis. At the end of the study, it was observed that the narcissism score of bodybuilding athletes is higher than other athletes in the scope of the study. Article visualizations:
Simulation Analysis Of Real-Time Signal Processor For Pulse Doppler Radar

With the advancements of VLSI chips and powerful computational devices, new complex algorithms and systems are being devised to tap the available computational power and to get the maximum performance. One particular system is the signal processor of Pulse Doppler Radar. This paper aims at finding the range and radial velocity of a moving target using Pulse Doppler Radar for land surveillance. Different optimization techniques have been employed to increase the accuracy of the system. The design was tested on MATLAB for software verification.
‘ UNMIXING ’ FUNCTIONAL MAGNETIC RESONANCE IMAGING WITH INDEPENDENT COMPONENT ANALYSIS

Independent component analysis (ICA) has recently demonstrated considerable promise in characterizing fMRI data, primarily due to its intuitive nature and ability for flexible characterization of the brain function. As typically applied, spatial brain networks are assumed to be systematically non-overlapping. Often temporal coherence of brain networks is also assumed, although convolutive and other models can be utilized to relax this assumption. ICA has been successfully utilized in a number of exciting fMRI applications including the identification of various signal-types such as task and transiently task-related and physiology-related signals in the spatial or temporal domain. Additional applications include the analysis of multi-subject fMRI data, the incorporation of a priori information, and the analysis of complex-valued fMRI data. In this paper, we first introduce ICA and its application to fMRI data analysis, and then review various applications of ICA to fMRI data.
Nanostructures for the Inhibition of Viral Infections

Multivalent interactions are omnipresent in biology and confer biological systems with dramatically enhanced affinities towards different receptors. Such multivalent binding interactions have lately been considered for the development of new therapeutic strategies against bacterial and viral infections. Multivalent polymers, dendrimers, and liposomes have successfully targeted pathogenic interactions. While a high synthetic effort was often needed for the development of such therapeutics, the integration of multiple ligands onto nanostructures turned to be a viable alternative. Particles modified with multiple ligands have the additional advantage of creating a high local concentration of binding molecules. This review article will summarize the different nanoparticle-based approaches currently available for the treatment of viral infections.
FPGA implementation of an optimized 8-bit AES architecture: A masked S-Box and pipelined approach

In this paper, we present a new pipelined 8-bit architecture for Advanced Encryption Standard (AES) encryption. The new architecture supports encryption with 128-bit keys with 10 rounds of Byte Substitution, Shift Rows, Mix Columns and Add Round Key operations. We emphasized on optimizing a single round by using an 8-bit architecture instead of 128-bit architecture which resulted into overall optimization and increase in bit security of the system. We have also proposed a new architecture for Key Expansion Unit and S-Box (Substitution Box) using a more secure key expansion algorithm and high order masking respectively, hence making the overall architecture of AES more secure and less prone to Differential Power Analysis (DPA) attacks. The proposed architecture was implemented on Virtex-7 working at a maximum clock frequency of 191.42 MHz with a throughput of 94.24 Mbps and a power consumption of 0.694 W.