Miracle-dz/UniFAR-FTUs huggingface dataset:
A method for detecting DGA botnet based on semantic and cluster analysis

Botnets play major roles in a vast number of threats to network security, such as DDoS attacks, generation of spam emails, information theft. Detecting Botnets is a difficult task in due to the complexity and performance issues when analyzing the huge amount of data from real large-scale networks. In major Botnet malware, the use of Domain Generation Algorithms allows to decrease possibility to be detected using white list - blacklist scheme and thus DGA Botnets have higher survival. This paper proposes a DGA Botnet detection scheme based on DNS traffic analysis which utilizes semantic measures such as entropy, meaning the level of the domain, frequency of n-gram appearances and Mahalanobis distance for domain classification. The proposed method is an improvement of Phoenix botnet detection mechanism, where in the classification phase, the modified Mahalanobis distance is used instead of the original for classification. The clustering phase is based on modified k-means algorithm for archiving better effectiveness. The effectiveness of the proposed method was measured and compared with Phoenix, Linguistic and SVM Light methods. The experimental results show the accuracy of proposed Botnet detection scheme ranges from 90 to 99,97% depending on Botnet type.
Fall Detection on Mobile Phones Using Features from a Five-Phase Model

The injuries caused by falls are great threats to the elderly people. With the ability of communication and motion sensing, the mobile phone is an ideal platform to detect the occurrence of fall accidents and help the injured person receive first aid. However, the missed detection and false alarm of the monitoring software will cause annoyance to the users in real use. In this paper, we present a novel fall detection technique using features from a five-phase model which describes the state change of the user's motion during the fall. Experiment results validate the effectiveness of the algorithm and show that the features derived from the model as gravity-cross rate and non-primarily maximum and minimum points of the acceleration data are useful to improve the precision of the detection. Moreover, we implement the technique as uCare, an Android application that helps elderly people in fall prevention, detection and first aid seeking.
Role of the B2 Receptor of Bradykinin in Insulin Sensitivity

The biological actions of bradykinin (BK) are attributed to its B2 type receptor (B2R), whereas the B1R is constitutively absent, inducible by inflammation and toxins. Previous studies in B2R gene knockout mice showed that the B1R is overexpressed, is further upregulated by hypertensive maneuvers, and assumes some of the hemodynamic functions of the B2R. The current experiments were designed to further clarify the metabolic function of the B2R and to explore whether the upregulated B1R can also assume the metabolic function of the missing B2R. One group of B2R−/− mice (n=9) and one of B2R+/+ controls (n=8) were treated for 3 days with captopril (which produced a similar blood pressure-lowering response in both groups) and studied with the hyperinsulinemic euglycemic clamp. The knockout mice had fasting and steady-state blood glucose levels similar to those of the wild-type mice but a had tendency to higher fasting insulin levels (at 27.8±5.2 versus 18±2.9 mU/L, respectively). However, they had significantly higher steady-state insulin levels (749±127.2 versus 429.1±31.5 mU/L, P <0.05) and a significantly lower glucose uptake rate (31±2.4 versus 41±2.3 mg/kg per minute, P <0.05) and insulin sensitivity index (4.6±0.9 versus 10±0.7 P <0.001). Analysis of B1R and B2R gene expression by reverse transcription-polymerase chain reaction in cardiac muscle, skeletal muscle, and adipose tissues revealed significantly higher B1R mRNA level in the knockouts versus wild-type (P <0.05) at baseline and a further significant upregulation in mRNA by 1.8- to 3.2-fold (P <0.05) after insulin infusion. We conclude that absence of B2R confers a state of insulin resistance because it results in impaired insulin - dependent glucose transport; this is probably a direct B2R effect because, unlike the hemodynamic autacoid-mediated effects, it cannot be assumed by the upregulated B1R.
Actors in an Ad-Hoc Wireless Network Environment

Today mobile devices can interact with their environment, because of the introduction of wireless communication. Wireless networks have two properties that distinguishes itself from the wired networks: First, wireless communication is less reliable than their wired variants because they have a limited communication range. Second, wireless communication is more dynamic as communication partners enter and leave frequently the communication range of the wireless network. These two distinct properties make the development of mobile software difficult. The actor model is a programming model that allows development of concurrent distributed software in open distributed environments. Actor models fail to handle these two distinct properties of wireless networks well. In this paper we extend the operational semantics of the actor model to capture these two properties in the actor model. We do this by adding a single new concept to the model: the mailbox. This paper provides a foundation for new implementations of the actor language and frameworks that are usable in the context of wireless network environments.
CLOLINK: An Adapted Algorithm for Mining Closed Frequent Itemsets

Mining of the complete set of frequent itemsets will lead to a huge number of itemsets. Fortunately, this problem can be reduced to the mining of closed frequent itemsets, which results in a much smaller number of itemsets. Methods for efficient mining of closed frequent itemsets have been studied extensively by many researchers using various strategies to prove their efficiencies such as Apriori-likemethods, FP growth algorithms, Tree projection and so on. However, when mining databases, these methods still encounter some performance bottlenecks like processing time, storage space and so on. This paper integrates the advantages of the strategies of H-Mine, a memory efficient algorithmfor mining frequent itemsets. The study proposes an algorithm named CLOLINK, which makes use of a compact data structure named L struct that links the items in the database dynamically during the mining process. An extensive experimental evaluation of the approach on real databases shows a better performance over the previous methods in mining closed frequent itemsets.
Optimization of weighting factors in the peak matched multiple window method

Peak matched multiple windows are found as the Karhunen-Loeve basis functions of a predefined peaked spectrum. With a penalty function, an optimization procedure can be constrained with resulting control of sidelobes. Weighting factors, included in the averaging of the periodograms, can be designed to fulfill certain constraints. Desirable properties are low variance and small bias. This paper presents a discussion of minimization of variance at the peak compared with the optimization that also include the neighbourhood of the peak.
Comparison of tactical offensive variables in different playing surfaces in sided games in soccer

In recent decades soccer has been analysed in great detail, enabling the technical and tactical aspects of the game to be improved through observation, analysis and training. However, there are not significant studies that particularly looked at the impact of the playing surfaces in depth. Thus the main aim of this study is to analyse and compare the quantitative and qualitative effect of the playing surface (grass, dirt or turf) on teams’ and players’ performances from a tactical perspective, through observing various sided games in youth soccer players. 54 games in three different formats (5v5, 7v7 and 9v9) were analysed, divided into two age groups (378 players of U-9 and U-14 categories) and filmed at three Spanish soccer clubs. This study used the observational and descriptive method and was carried out by systematic observation. This involved watching pre-recorded matches to observe and log different types of behaviour in previously defined categories. Results revealed that there were no significant differences for the different surfaces or game formats, and the study presents a description and analysis of the aspects that had considerable influence on the attacking moves for each surface and game format.
I like what I know: Is recognition a non-compensatory determiner of consumer choice?

What is the role of recognition in consumer choice? The recognition heuristic (RH) proposes that in situations where recognition is correlated with a decision criterion, recognized objects will be chosen more often than unrecognized ones, regardless of any other relevant information available about the recognized object. Past research has investigated this non-compensatory decision heuristic in inference. Here we report two experiments on preference using a naturalistic consumer choice task. Results revealed that, although recognition was a powerful driver of preferences, it was used in a compensatory rather than a non-compensatory way. Specifically, additional information learned about recognized brand objects significantly affected choices. It appears that recognition is processed in a compensatory manner and combined with other attributes in preferential choice.
A topic-based, publish-subscribe architecture for intermittently connected 802.15.4 networks

The small size and power consumption of IEEE 802.15. 4 devices allows embedding them in GSM/UMTS U-SIM cards and/or SD cards. The availability of such technology for data exchange within mobile phones is very useful to complement GSM/UMTS services, providing proximity services, such as chat and advertisements in a shopping mall, configuration data, micro-payments, access control. In addition, once that we have the availability of a free communication radio link, we can enlarge the assortment of offered services, supporting not only ”direct” data exchanges between two users within the 802.15. 4 connectivity range, but also communication among intermittently connected users. This is a typical scenario of so-called Delay Tolerant Networks (DTN) and we argue that a communication paradigm well suited to this environment is publish-subscribe. On the other hand, publish-subscribe is also well suited to satisfy the requirements of a community of users such as the one of an university campus, accompanying other services such as voice and Internet access. The aim of this paper is to present a topic-based, publish-subscribe architecture for intermittently connected networks exploiting IEEE 802.15. 4 devices, and taking into due account the severe constraints deriving from their physical characteristics. We describe the architectural model, the protocol design, the system analysis, and the implementation of our solution in a real test-bed, which we carried out in cooperation with Telecom Italia, that financed this work. We point out that our system can be easily adapted to operate in a fully distributed, infrastructure-less way, allowing free communications e.g. in disaster areas or in areas in which ”usual” communications means are either non existent or intentionally made unavailable. For instance, we could realize a server-less version of Twitter able to epidemically distribute information very quickly, provided that we have a high-enough density of devices implementing our solution.
Measurement in the social sciences: where C-OAR-SE delivers and where it does not

Purpose This paper aims to critically comment Rossiter’s “How to use C-OAR-SE to design optimal standard measures” in the current issue of EJM and provides a broader perspective on Rossiter’s C-OAR-SE framework and measurement practice in marketing in general. Design/methodology/approach The paper is conceptual, based on interpretation of measurement theory. Findings The paper shows that, at best, Rossiter’s mathematical dismissal of convergent validity applies to the completely hypothetical (and highly unlikely) situation where a perfect measure without any error would be available. Further considerations cast serious doubt on the appropriateness of Rossiter’s concrete object, dual subattribute-based single item measures. Being immunized against any piece of empirical evidence, C-OAR-SE cannot be considered a scientific theory and is bound to perpetuate, if not aggravate, the fundamental flaws in current measurement practice. While C-OAR-SE indeed helps generate more content valid instruments, the procedure offers no insights as to whether these instruments work properly to be used in research and practice. Practical implications This paper concludes that great caution needs to be exercised before adapting measurement instruments based on the C-OAR-SE procedure, and statistical evidence remains essential for validity assessment. Originality/value This paper identifies several serious conceptual and operational problems in Rossiter’s C-OAR-SE procedure and discusses how to align measurement in the social sciences to be compatible with the definition of measurement in the physical sciences.
The Story of a Hitchhiker: Population Genetic Patterns in the Invasive Barnacle Balanus(Amphibalanus) improvisus Darwin 1854

Understanding the ecological and evolutionary forces that determine the genetic structure and spread of invasive species is a key component of invasion biology. The bay barnacle, Balanus improvisus (= Amphibalanus improvisus), is one of the most successful aquatic invaders worldwide, and is characterised by broad environmental tolerance. Although the species can spread through natural larval dispersal, human-mediated transport through (primarily) shipping has almost certainly contributed to the current global distribution of this species. Despite its worldwide distribution, little is known about the phylogeography of this species. Here, we characterize the population genetic structure and model dispersal dynamics of the barnacle B. improvisus, and describe how human-mediated spreading via shipping as well as natural larval dispersal may have contributed to observed genetic variation. We used both mitochondrial DNA (cytochrome c oxidase subunit I: COI) and nuclear microsatellites to characterize the genetic structure in 14 populations of B. improvisus on a global and regional scale (Baltic Sea). Genetic diversity was high in most populations, and many haplotypes were shared among populations on a global scale, indicating that long-distance dispersal (presumably through shipping and other anthropogenic activities) has played an important role in shaping the population genetic structure of this cosmopolitan species. We could not clearly confirm prior claims that B. improvisus originates from the western margins of the Atlantic coasts; although there were indications that Argentina could be part of a native region. In addition to dispersal via shipping, we show that natural larval dispersal may play an important role for further colonisation following initial introduction.
Enhancement of Gear Fault Detection Using Narrowband Interference Cancellation

The development of enhanced fault detection ability for gearbox systems has received considerable attention in recent years. Detecting the gear fault easier is very important for maintenance action. This has driven the need in research for enhanced gear fault detection method. The goal is to extract periodic impulse signal from the very noise signal which mainly contains the narrowband signals. This can be done by enhancing the impulsive signals while suppressing the narrowband signals. This paper used a new method, Narrowband Interference Cancellation, to detect the gear fault. This method reserves the impulsive signal produced by gear fault and removes the other signals out. The methodology is demonstrated on a gearbox run-to-failure test. The results show that Narrowband Interference Cancellation can enable the gear fault detection easier.
Functional and structural genomics using PEDANT

MOTIVATION Enormous demand for fast and accurate analysis of biological sequences is fuelled by the pace of genome analysis efforts. There is also an acute need in reliable up-to-date genomic databases integrating both functional and structural information. Here we describe the current status of the PEDANT software system for high-throughput analysis of large biological sequence sets and the genome analysis server associated with it. RESULTS The principal features of PEDANT are: (i) completely automatic processing of data using a wide range of bioinformatics methods, (ii) manual refinement of annotation, (iii) automatic and manual assignment of gene products to a number of functional and structural categories, (iv) extensive hyperlinked protein reports, and (v) advanced DNA and protein viewers. The system is easily extensible and allows to include custom methods, databases, and categories with minimal or no programming effort. PEDANT is actively used as a collaborative environment to support several on-going genome sequencing projects. The main purpose of the PEDANT genome database is to quickly disseminate well-organized information on completely sequenced and unfinished genomes. It currently includes 80 genomic sequences and in many cases serves as the only source of exhaustive information on a given genome. The database also acts as a vehicle for a number of research projects in bioinformatics. Using SQL queries, it is possible to correlate a large variety of pre-computed properties of gene products encoded in complete genomes with each other and compare them with data sets of special scientific interest. In particular, the availability of structural predictions for over 300 000 genomic proteins makes PEDANT the most extensive structural genomics resource available on the web.
Integration of Steady-State and Temporal Gene Expression Data for the Inference of Gene Regulatory Networks

We develop a new regression algorithm, cMIKANA, for inference of gene regulatory networks from combinations of steady-state and time-series gene expression data. Using simulated gene expression datasets to assess the accuracy of reconstructing gene regulatory networks, we show that steady-state and time-series data sets can successfully be combined to identify gene regulatory interactions using the new algorithm. Inferring gene networks from combined data sets was found to be advantageous when using noisy measurements collected with either lower sampling rates or a limited number of experimental replicates. We illustrate our method by applying it to a microarray gene expression dataset from human umbilical vein endothelial cells (HUVECs) which combines time series data from treatment with growth factor TNF and steady state data from siRNA knockdown treatments. Our results suggest that the combination of steady-state and time-series datasets may provide better prediction of RNA-to-RNA interactions, and may also reveal biological features that cannot be identified from dynamic or steady state information alone. Finally, we consider the experimental design of genomics experiments for gene regulatory network inference and show that network inference can be improved by incorporating steady-state measurements with time-series data.
MicroRNA-7 inhibition rescues age-associated loss of epidermal growth factor receptor and hyaluronan-dependent differentiation in fibroblasts

Age‐related defects in fibroblast differentiation were previously shown to be associated with impaired hyaluronan synthase 2 (HAS2) and epidermal growth factor receptor (EGFR) function, with both required for normal fibroblast functionality. In fibroblasts, transforming growth factor‐beta 1 (TGF‐β1)‐dependent phenotypic activation uses two distinct but co‐operating pathways that involve TGF‐β receptor (TGF‐βR)/Smad2 activation and HA‐mediated CD44‐EGFR co‐localization and signalling through extracellular signal‐regulated kinase 1/2 (ERK1/2). The HA‐mediated CD44‐EGFR pathway was found to be compromised with in vitro aging, through loss of EGFR expression and a reduced movement of CD44 throughout the cellular membrane. Here, we also investigate the involvement of microRNAs (miRNAs) in age‐related loss of differentiation, through investigation of miRNA‐7 (miR‐7) regulation of the HA‐mediated EGFR‐signalling pathway. The transcription of miR‐7 was found to be upregulated in aged cells. In young cells, age‐related loss of differentiation could be mimicked through transfection of pre‐miR‐7, and in aged cells, could be reversed through transfection of locked nucleic acids (LNA) targeting miR‐7. Additionally, miR‐7 was found to be involved in the regulation of CD44 membrane motility, which was downregulated in instances of miR‐7 upregulation, and partially restorable through either miR‐7 inhibition or HAS2 overexpression. The altered dynamics of CD44 in the cell membrane demonstrated a further action of miR‐7 in regulating the HA‐dependent CD44/EGFR pathway. We explain this novel mechanism of age‐associated functional consequence due to miR‐7 upregulation and demonstrate that it is reversible; highlighting miR‐7 as a potential target for restoring the healing capabilities in chronic wounds in the elderly.
Information Protection in Dynamic Statistical Databases

A statistical database (SDB) is a database that contains sensitive records describing individuals but only statistical information is available. There are many inference control methods proposed to protect SDBs. In this article, we will briefly introduce three general approaches: conception, perturbation, and query restriction approaches. In addition, six criteria are also introduced to evaluate the features of these mechanisms. However, in practice, many SDBs are dynamically updated. This feature restricts the use of many inference control methods. Thus, in the rest of the article, we will present an efficient audit scheme, which is a query-restriction-based security-control method for protecting dynamic SDBs. This scheme guarantees the security of SDBs and needs less time and storage requirements than the traditional schemes while database systems are dynamically updated.
Architecture of Scalable Operating Systems : Multikernel

This paper gives a brief overview of the multikernel operating system model and uses Barrelfish [5] as example. The multikernel model tries to provide a solution to the problem of ever faster changing hardware and with it its scalability issues. The multikernel model addresses the scalability issue by using message passing instead of shared memory.