Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on Security and Privacy Protocols for Cognitive Wireless Sensor Networks

Wireless sensor networks have emerged as an important and new area in wireless and mobile computing research because of their numerous potential applications that range from indoor deployment scenarios in home and office to outdoor deployment in adversary's territory in tactical battleground. Since in many WSN applications, lives and livelihoods may depend on the timeliness and correctness of sensor data obtained from dispersed sensor nodes, these networks must be secured to prevent any possible attacks that may be launched on them. Security is, therefore, an important issue in WSNs. However, this issue becomes even more critical in cognitive wireless sensor networks, a type of WSN in which the sensor nodes have the capabilities of changing their transmission and reception parameters according to the radio environment under which they operate in order to achieve reliable and efficient communication and optimum utilization of the network resources. This survey paper presents a comprehensive discussion on various security issues in CWSNs by identifying numerous security threats in these networks and defense mechanisms to counter these vulnerabilities. Various types of attacks on CWSNs are categorized under different classes based on their natures and tragets, and corresponding to each attack class, appropriate security mechanisms are presented. The paper also identifies some open problems in this emerging area of wireless networking.
Robust Estimation of Message Importance Using Inferred Inter-recipient Trust for Supporting Email Triage

In recent years, the number of emails received by an individual has been increasing, and the time required for email triage (i.e., the process of going through unhandled emails and deciding what to do with them) has therefore been increasing. Golbeck et al. proposed TrustMail, which is a prototype email client that prioritizes emails in user’s mailbox utilizing a trust network (i.e., a social network representing trust relationships among users). In this paper, we extend the notion of TrustMail to allow robust message-based prioritization using inter-recipient trusts, which are (inferred) trust scores from the recipient to other recipients. We propose a method called EMIRT (Estimating Message Importance from inter-Recipient Trust) for enabling robust message prioritization. We also evaluate the effectiveness of our proposed EMIRT for estimating importance of emails through experiments utilizing a large email corpus called Enron Email Dataset. Consequently, we show that EMIRT realizes robust email prioritization.
The Masked Code Book ( MCB )

In this paper, we present a new narrow block mode of operation, the Masked Code Book (MCB), that can be efficiently deployed in disk encryption applications. MCB is characterized by its high-speed in comparison to current state of the art narrow block modes of operation. It is about 25% faster than XTS (when AES is the underlying cipher). Furthermore, MCB does not face the limitations of XTS.
SCIX PROJECT : DEMONSTRATING A MORE EFFICIENT WAY OF KNOWLEDGE TRANSFER WITHIN THE ITC COMMUNITY

ABSTRACT:The SciX (Open, self organising repository for scientific information exchange) project is a project funded by the European Commission in order to demonstrate the feasibility of new alternative models of scientific publishing made possible by the Internet. The project builds upon the previous experience of some of the partners in running an electronic peer reviewed journal and in setting up an e-prints archive. The project includes both theoretical work in making a formal model of the scientific publishing process, to be used as a basis for studying the life-cycle costs of alternative business models, and a demonstrator of a functioning e-prints archive.
Parallel Computations Reveal Hidden Errors of Commonly Used Random Number Generators

This paper reports that in parallel Monte-Carlo simulations of the 2D Ising-Model, commonly used pseudo-random number generators (PRNG) lead to manifestly erroneous results. When parallel random number sequences for a parallel simulation are generated by a same PRNG with diffrent initial seeds, the sequences can be strongly correlated with each other if the seeds are selected
INSECT-PLANT RELATIONSHIP - CHANCE AND NECESSITY

From the early 1920s, Europe was furiously struggling with the invasion of the Colorado potato beetle and then soon took cognisance of its inevitable triumph with resignation. All over Europe, laboratories were established and talented entomologists attempted to discover the “Achilles-heel” of the new pest devastating potato fields and threatening the potato industry. In 1947, the first scouts of the species were noticed in Western Hungary too. Authorities quickly established a temporary laboratory in the local mansion house at Hedervar and measures were taken to eliminate spots of infestation. The first elementary studies with the species were made by two entomologists who worked while being closely watched by officials of the Hungarian KGB! One of them was TIBOR JERMY. In spite of the atmosphere of paranoia of those years (the communist authorities insisted that the turn up of the Colorado potato beetle in Hungary was the result of the cover action of the American “war-mongers”), the first connection with the Colorado potato beetle resulted in a lifetime bond and stimulated a research rich in ideas and results. TIBOR JERMY’s special and most important scientific field was born then and there. Although he was a tremendously busy writer on very varied topics at that time (see his complete publication list at the end of this volume), important experimental and theoretical achievements were frequently connected with this particular species. The most important results concerning how insects use host plants, including behavioural and developmental observations, were born by studying the Colorado potato beetle. One cannot also dismiss the idea that the conceptual flourishing of later years must have been rooted in those times. Based on TIBOR JERMY’s suggestions and plans, a permanent laboratory was opened in Keszthely (West Hungary) in 1958 where quieter atmosphere and fine colleagues helped him to further deepen knowledge about the Colorado potato beetle, as well as basic biology and autecology of several other insect species. Other entomologists, as well as the papers published from this period, univocally prove that he was full of clever ideas, which then were manifested in very simple experiments. His proverbial patience, and endurance under harsh conditions, led to the production of heaps of notebooks full of results, but these were never published; once knowing the outcome of an experiment he was too eager to carry on with the next, instead of writing yet another paper.
The Effects of Loneliness and Internalized Stigma on Perceived Social Support in People with AIDS: A Cross-Sectional Study

A cross-sectional study examined social support, loneliness, internalized stigma, the effects of loneliness and internalized stigma on perceived social support in 140 Greek adults with AIDS. The Medical Outcomes Study Social Support Scale, UCLA Loneliness Scale, and Internalized AIDS-Related Stigma were administered. Significant associations: between social support, social loneliness, psychological loneliness, isolation, and Aids Related Stigma. Psychological loneliness and isolation had the strongest effect on social support. Efforts reducing them may positively affect social support.
Variations in KIR Genes: A Study in HIV-1 Serodiscordant Couples

Background. NK cells have anti-HIV activity mediated through killer cell immunoglobulin-like receptors (KIRs). The current prospective cohort study evaluated whether variation in KIR genes is associated with HIV infection in discordant couples (DCs), where one spouse remains seronegative (HSN) despite repeated exposure to the HIV. Methods. KIR was genotyped using PCR SSP. Viral load and CD4 counts were estimated using commercially available reagents. Data were analyzed using SPSS software. Results. Among the 47 DCs, HSN spouses had significantly (P = 0.006) higher frequencies of KIR3DS1. Regression analysis revealed significant (P = 0.009) association of KIR2DS1 with low viral load. KIR2DS4 variant was associated (P = 0.032) with high viral load. Three pairs of KIR genes were in strong LD in HSNs and two pairs in HSPs. There were 60 KIR genotypes, and 16 are reported the first time in the Indian population. Exclusive genotypes were present either in HSPs (N = 22, 11 unique genotypes) or in HSNs (n = 27, 9 unique genotypes). Conclusions. This study highlights for the first time in the Indian population an association of KIR genes in HIV infection where presence of exclusive and unique genotypes indicates possible association with either HIV infection or with protection.
Digitally Assisted Dual-Switch High-Efficiency Envelope Amplifier for Envelope-Tracking Base-Station Power Amplifiers

This paper presents a novel digitally assisted dual-switch envelope amplifier used for wideband high-efficiency envelope-tracking (ET) base-station power amplifiers (PAs). The proposed envelope amplifier comprises two switching buck converters to provide the high-power ET signal to the RF stage and a wideband linear stage to maintain the envelope signal accuracy. The control technique utilizes digital signal processing in conjunction with analog hysteretic feedback to separately control two high-efficiency switchers and thus successfully reduces power consumption of the linear stage, especially for applications requiring high peak-to-average ratio (PAPR) signals. The overall ET system was demonstrated using GaAs high-voltage HBT PAs. For a variety of signals ranging from 6.6- to 9.6-dB PAPR and up to 10-MHz RF bandwidth, the overall system power-added efficiency reached 50%-60%, with a normalized root-mean-square error below 1% and the first adjacent channel leakage power ratio of -55 dBc after digital predistortion with memory mitigation, at an average output power above 20 W and 10-dB gain.
Mining Specification of Insecure Browser Extension Behavior

In this paper, a method about how to identify insecure behaviors of browser extensions is proposed. Typically, the identification of insecure extension behaviors is based on knowledge which is got by investigating known malicious or vulnerable extensions. We present an automatic technique that can ease the laborious manual investigating process. Our technique mines the difference between the behavior graphs of insecure and secure extensions based on graph mining algorithm. The difference between them is the specification of insecure extension behaviors which can be further analyzed manually or automatically to help people make a better decision about whether an extension is secure or not. We developed a prototype and the experimental results show that this kind of technique can effectively extract insecure extension behaviors.
EFFECT OF DIVERSITY COMBINING IN MOBILE TERRESTRIAL ENVIRONMENT

Mobile communications have experienced massive growth in recent years. It is also in high demand nowadays. However, these systems suffer from much impairment such as multipath propagation effects and thermal noise. The study investigates the effect of using Binary Phase Shift Keying (BPSK) and Binary Differential Phase Shift Keying (BDPSK) with Maximal Ratio Combiner (MRC) which will improve the overall system performance better in mobile environment so that the transmitted signal can be retrieved at the receiver with minimum error. The effects of the mobile communication environment which hindered the transmitted signals were first studied. The system model for processing the received signal at mobile speed of 30 km/h in two different channels; Additive White Gaussian Noise (AWGN) and mobile terrestrial channels was developed and simulated. Randomly produced data and water lilies image were used as source data which were gray encoded, processed by BPSK and BDPSK schemes, properly filtered by square root raised cosine filter. These signals were then passed through the mobile multipath Rayleigh environment and AWGN. Then at the receiver, MRC combined two strong paths to evaluate the performances which were measured in term of Average Bit Error Rate (BER) and image quality. The simulation was carried out using MATLAB 7.4 application package. The results show that the performance of BDPSK signaling scheme was found to be better than BPSK scheme giving lower Average BER indicating lower erroneous bits at the same point when transmitting the same number of bits. Moreover, the received image quality was also in agreement with the performance when randomly produced source data was used. In mobile communication, good quality of service is the major concern, because it changes business more than anything else and the system suffers from impairment. Adoption of fade margin or continue increasing the transmitted power is also inefficient. Hence modulation with diversity is essential. In line with this, the results indicate that modulation schemes are quite effective in combating channel impairment and can be used as references for the design of new reduced error system.
Comparative study of Kernel based classification and feature selection methods with gene expression data

Gene expression profiles obtained by high-throughput techniques such as microarray provide a snapshot of expression values of up to ten thousands genes in a particular tissue sample. Analyzing such gene expression data can be quite cumbersome as the sample size is small, the dimensionality is high, and the data are occasionally noisy. Kernel methods such as Support Vector Machines (SVMs) [5, 45] have been extensively applied within the field of gene expression analysis, and particularly to the problems of gene classification and selection. In general, kernel methods outperform other approaches due to their ability to handle high dimensionality easily. In this thesis, we perform a comparative study of various state-of-the-art kernel based classification and feature selection methods with gene expression data. It is our aim to have all the results together in one place so that people can easily see their similarities and differences both theoretically and empirically. In the literature, a feature selection method is evaluated by the classification accuracies using the features selected by the method. This evaluation criterion measures the classification capabilities of the data after the elimination of irrelevant features. We propose another criterion, called stability, to evaluate the feature selection methods in addition to classification accuracies. The feature set selected by a stable feature selection algorithm should not change significantly when some small changes are made to the training data. In this thesis, we use both of two evaluation criteria to compare feature selection methods. It has been showed that cross validation technique can be used to improve feature selection methods in terms of classification accuracies [8]. In this thesis, we extend one existing feature selection method which utilizes Gaussian Processes (GP) [47] with Automatic Relevance Determination (ARD) [28, 34], and cross validation, and propose a new feature selection method. Experiments on real gene expression data sets show that our method outperforms all other feature selection methods in terms of classification accuracies, and achieves comparable stability as Sparse Multinomial Logistic Regression (SMLR) [23], the most stable feature selection method in the literature.
Growth of Structure Seeded by Primordial Black Holes

We discuss the possibilities for the growth of primordial black holes (PBHs) via the accretion of dark matter. In agreement with previous works, we find that accretion during the radiation-dominated era does not lead to a significant mass increase. However, during matter domination, PBHs may grow by up to 2 orders of magnitude in mass through the acquisition of large dark matter halos. We discuss the possibility of PBHs being an important component in dark matter halos of galaxies, as well as their potential to explain the ultraluminous X-ray sources (ULXs) observed in nearby galactic disks. We point out that although PBHs are ruled out as the dominant component of dark matter, there is still a great deal of parameter space that is open to their playing a role in the modern-day universe. For example, a primordial halo population of PBHs each at 102.5 M☉, making up 0.1% of the dark matter, grows to 104.5 M☉ via the accumulation of dark matter halos and accounts for ~10% of the dark matter mass by a redshift of z ≈ 30. These intermediate-mass black holes may then "light up" when passing through molecular clouds, becoming visible as ULXs at the present day, or they may form the seeds for supermassive black holes at the centers of galaxies.
MOGA-Net: A MultiObjective Genetic Algorithm-Net to Find Communities in Complex Networks

The problem of community detection in complex networks as a MultiObjective clustering problem, and presented an evolutionary MultiObjective approach to uncover community structure. The algorithm optimizes two objective functions able to identify densely connected groups of nodes having sparse inter connections. The method generates a set of network divisions at different hierarchical levels in which solutions at deeper levels, consisting of a higher number of modules, are contained in solutions having a lower number of communities. The cluster's should tune the size of the communities, has been considering as same group because, the partitioning found for this value are relevant. The number of modules is automatically determined by the better tradeoff values of the objective functions. Optimization methodology define an Objective function that allows the division of a graph in sub graphs, and try to maximize this objective in order to obtain the best partitioning of the network.
Interleukin 1β-converting Enzyme Related Proteases/Caspases Are Involved in TRAIL-induced Apoptosis of Myeloma and Leukemia Cells

The Fas/APO-1/CD95 ligand (CD95L) and the recently cloned TRAIL ligand belong to the TNFfamily and share the ability to induce apoptosis in sensitive target cells. Little information is available on the degree of functional redundancy between these two ligands in terms of target selectivity and intracellular signalling pathway(s). To address these issues, we have expressed and characterized recombinant mouse TRAIL. Specific detection with newly developed rabbit anti-TRAIL antibodies showed that the functional TRAIL molecule released into the supernatant of recombinant baculovirus-infected Sf9 cells is very similar to that associated with the membrane fraction of Sf9 cells. CD95L resistant myeloma cells were found to be sensitive to TRAIL, displaying apoptotic features similar to those of the CD95L- and TRAIL-sensitive T leukemia cells Jurkat. To assess if IL-1β-converting enzyme (ICE) and/or ICE-related proteases (IRPs) (caspases) are involved in TRAIL-induced apoptosis of both cell types, peptide inhibition experiments were performed. The irreversible IRP/caspase-inhibitor AcYVAD-cmk and the reversible IRP/caspase-inhibitor Ac-DEVD-CHO blocked the morphological changes, disorganization of plasma membrane phospholipids, DNA fragmentation, and loss of cell viability associated with TRAIL-induced apoptosis. In addition, cells undergoing TRAIL-mediated apoptosis displayed cleavage of poly(ADP)-ribose polymerase (PARP) that was completely blocked by Ac-DEVD-CHO. These results indicate that TRAIL seems to complement the activity of the CD95 system as it allows cells, otherwise resistant, to undergo apoptosis triggered by specific extracellular ligands. Conversely, however, induction of apoptosis in sensitive cells by TRAIL involves IRPs/caspases in a fashion similar to CD95L. Thus, differential sensitivity to CD95L and TRAIL seems to map to the proximal signaling events associated with receptor triggering.
On the Effectiveness of Prioritized User-Profile and Detecting Active Users in Collaborative Filtering Recommender Systems

Recommender systems intend to help users find their interested items from among a large number of items. These systems especially those based on collaborative filtering methods have shown success on the Web. This paper emphasizes on the effectiveness of the prioritized user-profile and detecting active users as two basic approaches that could improve the quality of collaborative filtering recommenders. The first approach is based on [1] and tries to implement more personalized recommendation by assigning different priority importance to each of the features of the user-profile for different users. The second approach tries to reduce the effort needed to find similar users and at the same time increase the quality of recommendations by using the opinions of active users in the system. These two techniques are compared with the standard user-based Pearson algorithm (Breese et al., 1998) on book and movie datasets.
Application of active contour models in medical image segmentation

Recent developments on medical imaging techniques have brought a completely new research field on image processing. The principal aim is to improve medical diagnosis through segmented images. Techniques have been developed to help for identifying specific structures within a magnetic resonance image: MRI. The active contour methods, these methods are adaptable to the desired features in the image. In our work, we describe two classes of active contour models and discussing application aspects in medical imaging area.
Dual‐optimisation of power sources including plug‐in electric vehicles and renewable energy resources at transmission‐level system

With the growing trend of plug-in electric vehicles (PEVs), the charging load of PEVs can have a huge impact on current transmission-level system. In the meantime, there also comes a great potential in the optimisation aspect for both power generation economic and power transmission safety concerns. Here, a dual-optimisation algorithm is developed to minimise the total production cost of power sources including renewable energy resources (RER) and PEV cluster. In the meantime, the overloading in transmission lines and transformers is avoided. Linear programming and DC optimal power flow (DCOPF) are separately applied to step one and step two optimisation. The simulation result from a modified IEEE 9-bus system reveals that dual-optimisation method successfully reduced the production cost based on a hybrid model of power grid in step one optimisation. In step two optimisation, the overloaded transmission line is detected and held at capacity limit to prevent overheating. In conclusion, in dual-optimisation algorithm, PEVs can serve as both the energy storage device and the energy supply device. Consequently, the total production cost can be reduced, and the optimal power flow can be obtained.