Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-Overhead Distributed Jamming for SIMO Secrecy Transmission with Statistical CSI

In this letter, we propose a distributed jamming strategy to maximize the achievable ergodic secrecy rate (ESR) of a single-input multi-output (SIMO) transmission with a multiple-antenna eavesdropper based on only the statistical channel state information (CSI). In the scheme, exploring the heterogeneous large-scale fading effects, multiple geographically distributed single-antenna jammers transmit independent and uncoordinated jamming signals to confound the eavesdropper. We derive a large-scale asymptotic approximation of the achievable ESR, and optimize the transmit power of each jammer for maximizing the asymptotic ESR by geometric programming (GP). The proposed scheme does not require signal coordination among jammers and greatly reduces the training/synchronization overhead, which is applicable when the receiver has a large number of antennas, i.e., massive MIMO system.
Flexible handling robot system for cloth

Flexible objects such as clothes are hard to be handled by robots. But the working conditions for laundry factories are severe because of dusts, heats and steams, and full automation systems which can handle clothes are highly required. To automate these factories, 3-D Vision systems and flexible handling mechanism are dispensable to handle flexible clothes. There are three steps to handle clothes by robots. They are ; (1) to pick up one cloth from piled clothes, (2) to grasp one corner of a cloth, (3) to grasp one edge of a cloth. In every step, proper combination of mechanisms and vision systems are required. Here, the vision systems and flexible cloth handling mechanisms to input washing clothes to the a pressing and folding line have been introduced.
Multi-Point Ethernet over Next-Generation SONET/SDH

Advances in SONET/SDH technologies have introduced novel features for improved services mapping and provisioning, enabling many new avenues for new Carrier Ethernet support. However Ethernet-over-SONET studies have mostly focused on provisioning point-to-point Ethernet private line offerings. This paper considers the more challenging case of provisioning multi-point-to-multi-point Ethernet LAN services over advanced SONET/SDH networks and presents novel strategies based upon connection group overlays. Detailed simulation results are also presented along with directions for future work.
A Novel Approach for Handling Outliers in Imbalanced Data

Most of the traditional classification algorithms assume their training data to be well-balanced in terms of class distribution. Real-world datasets, however, are imbalanced in nature thus degrade the performance of the traditional classifiers. To solve this problem, many strategies are adopted to balance the class distribution at the data level. The data level methods balance the imbalance distribution between majority and minority classes using either oversampling or under sampling techniques. The main concern of this paper is to remove the outliers that may generate while using oversampling techniques. In this study, we proposed a novel approach for solving the class imbalance problem at data level by using modified SMOTE to remove the outliers that may exist after synthetic data generation using SMOTE oversampling technique. We extensively compare our approach with SMOTE, SMOTE+ENN, SMOTE+Tomek-Link using 9 datasets from keel repository using classification algorithms. The result reveals that our approach improves the prediction performance for most of the classification algorithms and achieves better performance compared to the existing approaches.
Mitigating Circumstances in Cybercrime: A Position Paper

This paper argues the need for considering mitigating circumstances in cybercrime. Mitigating circumstances are conditions which moderate the culpability of an offender of a committed offence. Our argument is based on several observations. The cyberspace introduces a new family of communication and interaction styles and designs which could facilitate, make available, deceive, and in some cases persuade, a user to commit an offence. User's lack of awareness could be a valid mitigation when using software features introduced without a proper management of change and enough precautionary mechanisms, e.g. warning messages. The cyber behaviour of users may not be necessarily a reflection of their real character and intention. Their irrational and unconscious actions may result from their immersed and prolonged presence in a particular cyber context. Hence, the consideration of the cyberspace design, the "cyber psychological" status of an offender and their inter-relation could form a new family of mitigating circumstances inherent and unique to cybercrime. This paper elaborates on this initial argument from different perspectives including software engineering, cyber psychology, digital forensics, social responsibility and law.
Accumulation of DNA Damage-Induced Chromatin Alterations in Tissue-Specific Stem Cells: The Driving Force of Aging?

Accumulation of DNA damage leading to stem cell exhaustion has been proposed to be a principal mechanism of aging. Using 53BP1-foci as a marker for DNA double-strand breaks (DSBs), hair follicle stem cells (HFSCs) in mouse epidermis were analyzed for age-related DNA damage response (DDR). We observed increasing amounts of 53BP1-foci during the natural aging process independent of telomere shortening and after protracted low-dose radiation, suggesting substantial accumulation of DSBs in HFSCs. Electron microscopy combined with immunogold-labeling showed multiple small 53BP1 clusters diffusely distributed throughout the highly compacted heterochromatin of aged HFSCs, but single large 53BP1 clusters in irradiated HFSCs. These remaining 53BP1 clusters did not colocalize with core components of non-homologous end-joining, but with heterochromatic histone modifications. Based on these results we hypothesize that these lesions were not persistently unrepaired DSBs, but may reflect chromatin rearrangements caused by the repair or misrepair of DSBs. Flow cytometry showed increased activation of repair proteins and damage-induced chromatin modifications, triggering apoptosis and cellular senescence in irradiated, but not in aged HFSCs. These results suggest that accumulation of DNA damage-induced chromatin alterations, whose structural dimensions reflect the complexity of the initial genotoxic insult, may lead to different DDR events, ultimately determining the biological outcome of HFSCs. Collectively, our findings support the hypothesis that aging might be largely the remit of structural changes to chromatin potentially leading to epigenetically induced transcriptional deregulation.
Diurnal patterns of productivity of arbuscular mycorrhizal fungi revealed with the Soil Ecosystem Observatory

Arbuscular mycorrhizal (AM) fungi are the most abundant plant symbiont and a major pathway of carbon sequestration in soils. However, their basic biology, including their activity throughout a 24-h day : night cycle, remains unknown. We employed the in situ Soil Ecosystem Observatory to quantify the rates of diurnal growth, dieback and net productivity of extra-radical AM fungi. AM fungal hyphae showed significantly different rates of growth and dieback over a period of 24 h and paralleled the circadian-driven photosynthetic oscillations observed in plants. The greatest rates (and incidences) of growth and dieback occurred between noon and 18:00 h. Growth and dieback events often occurred simultaneously and were tightly coupled with soil temperature and moisture, suggesting a rapid acclimation of the external phase of AM fungi to the immediate environment. Changes in the environmental conditions and variability of the mycorrhizosphere may alter the diurnal patterns of productivity of AM fungi, thereby modifying soil carbon sequestration, nutrient cycling and host plant success.
Automatic Detection of Double Meaning in Texts from the Social Networks

The paper presents a method for automatic detection of double meaning of texts in English from the social networks. For the purposes of this paper we define double meaning as one of irony, sarcasm and satire. We proposed nine rules selected from a pool of twenty. We defined six features and evaluated their predictive accuracy. Further we compared the accuracy of three different classifiers - Naive Bayes, k-Nearest Neighbours and Support Vector Machine. We also studied the predictive accuracy of all words and bi-terms. We test the algorithms above against opinions from the social network: sample opinions from the social networks Facebook, Twitter and Google+. These opinions were extracted via HTTP requests using one of the hashtags #sarcasm, #irony or #satire and we select 3000 opinions for each of the tests.
Identification of N-Acetyltransferase 2 (NAT2) Transcription Start Sites and Quantitation of NAT2-Specific mRNA in Human Tissues

Human N-acetyltransferase 2 (NAT2) genetic polymorphism is associated with drug toxicity and/or carcinogenesis in various tissues. Knowledge of NAT2 gene structure and expression is critical for understanding these associations. Previous findings suggest that human NAT2 expression is highest in liver and gut but expressed at functional levels in other tissues. A sensitive and specific TaqMan reverse transcriptase-polymerase chain reaction (RT-PCR) assay with intron-spanning primers was developed and used, together with a second TaqMan RT-PCR assay based on amplification of a NAT2 open reading frame (ORF) exon segment, to measure NAT2 mRNA in 29 different human tissues. Cap-dependent amplification of mRNA 5′ termini and review of public database information were done to more precisely define the NAT2 promoter(s) and to validate the quantitative RT-PCR assay design. The great majority (40/41) of NAT2 liver cDNAs had 5′ termini between 8682 and 8752 nucleotides upstream of the NAT2 ORF exon, and 34 of 40 5′ termini were at the –8711 and –8716 adenines. All 59 NAT2 cDNAs with 5′ termini in this vicinity, including 40 of the liver isolates and 19 cDNAs in public databases from liver and other sources, showed direct splicing to the ORF exon, with no other noncoding exon detected. NAT2 mRNA was highest in liver, small intestine, and colon and was readily detected in most other tissues, albeit at much lower levels. NAT2 expression in diverse human tissues provides further mechanistic support underlying associations between NAT2 genetic polymorphism, drug toxicity, and/or chemical carcinogenesis.
Neutrophil Depletion Inhibits Experimental Abdominal Aortic Aneurysm Formation

Background—Neutrophils may be an important source of matrix metalloproteinase-2 (MMP-2) and matrix metalloproteinase-9 (MMP-9), two matrix-degrading enzymes thought to be critical in the formation of an abdominal aortic aneurysm (AAA). The purpose of this investigation was to test the hypothesis that neutrophil depletion would limit experimental AAA formation by altering one or both of these enzymes. Methods and Results—Control, rabbit serum–treated (RS; n=27) or anti-neutrophil-antibody–treated (anti-PMN; n=25) C57BL/6 mice underwent aortic elastase perfusion to induce experimental aneurysms. Anti-PMN–treated mice became neutropenic (mean, 349 cells/&mgr;L), experiencing an 84% decrease in the circulating absolute neutrophil count (P<0.001) before elastase perfusion. Fourteen days after elastase perfusion, control mice exhibited a mean aortic diameter (AD) increase of 104±14% (P<0.0001), and 67% developed AAAs, whereas anti-PMN–treated mice exhibited a mean AD increase of 42±33%, with 8% developing AAAs. The control group also had increased tissue neutrophils (20.3 versus 8.6 cells per 5 high-powered fields [HPFs]; P=0.02) and macrophages (6.1 versus 2.1 cells per 5 HPFs, P=0.005) as compared with anti-PMN–treated mice. There were no differences in monocyte chemotactic protein-1 or macrophage inflammatory protein-1&agr; chemokine levels between groups by enzyme-linked immunosorbent assay. Neutrophil collagenase (MMP-8) expression was detected only in the 14-day control mice, with increased MMP-8 protein levels by Western blotting (P=0.017), and MMP-8–positive neutrophils were seen almost exclusively in this group. Conversely, there were no statistical differences in MMP-2 or MMP-9 mRNA expression, protein levels, enzyme activity, or immunostaining patterns between groups. When C57BL/6 wild-type (n=15) and MMP-8–deficient mice (n=17) were subjected to elastase perfusion, however, ADs at 14 days were no different in size (134±7.9% versus 154±9.9%; P=0.603), which suggests that MMP-8 serves only as a marker for the presence of neutrophils and is not critical for AAA formation. Conclusions—Circulating neutrophils are an important initial component of experimental AAA formation. Neutrophil depletion inhibits AAA development through a non–MMP-2/9–mediated mechanism associated with attenuated inflammatory cell recruitment.
Model assessment of decadal variability and trends in the tropical Pacific Ocean

Abstract In this report, global coupled ocean–atmosphere models are used to explore possible mechanisms for observed decadal variability and trends in Pacific Ocean SSTs over the past century. The leading mode of internally generated decadal (>7 yr) variability in the model resembles the observed decadal variability in terms of pattern and amplitude. In the model, the pattern and time evolution of tropical winds and oceanic heat content are similar for the decadal and ENSO timescales, suggesting that the decadal variability has a similar “delayed oscillator” mechanism to that on the ENSO timescale. The westward phase propagation of the heat content anomalies, however, is slower and centered slightly farther from the equator (∼12° vs 9°N) for the decadal variability. Cool SST anomalies in the midlatitude North Pacific during the warm tropical phase of the decadal variability are induced in the model largely by oceanic advection anomalies. An index of observed SST over a broad triangular region of the tropi.
Processing of emotional material in major depression : cognitive and neuropsychological investigations

The aim of this thesis was to expand the existing knowledge base concerning the profile of emotional processing that is associated with major depression, particularly in terms of socially important non-verbal stimuli (e.g. emotional facial expressions). Experiment one utilised a face-word variant of the emotional Stroop task and demonstrated that depressed patients (DP) did not exhibit a selective attention bias for sad faces. Conversely, the healthy controls (HC) were shown to selectively attend to happy faces. At recognition memory testing, DP did not exhibit a memory bias for depression-relevant words, but did demonstrate a tendency to falsely recognise depression-relevant words that had not been presented at encoding. Experiment two examined the pattern of autobiographical memory (ABM) retrieval exhibited by DP and HC in response to verbal (words) and non-verbal (images & faces) affective cues. DP were slower than HC to retrieve positive ABMs, but did not differ from HC in their retrieval times for negative ABMs. Overall, DP retrieved fewer specific ABMs than did the HC. Participants retrieved more specific ABMs to image cues than to words or faces, but this pattern was only demonstrated by the HC. Reduced retrieval of specific ABMs by DP was a consequence of increased retrieval of categorical ABMs; this tendency was particularly marked when the participants were cued with faces. During experiment three, DP and HC were presented with a series of faces and were asked to identify the gender of the person featured in each photograph. Overall, gender identification times were not affected by the emotion portrayed by the faces. Furthermore at subsequent recognition memory testing, DP did not exhibit MCM bias for sad faces. During experiment four, DP and HC were presented with videotaped depictions of ‘realistic’ social interactions and were asked to identify the emotion portrayed by the characters and to make inferences about the thoughts, intentions and beliefs of these individuals. Overall, DP were impaired in their recognition of happiness and in understanding social interactions involving sarcasm and deception. Correct social inference was significantly related to both executive function and depression severity. Experiment five involved assessing a group of eight patients that had undergone
A Non-Blocking Single-Phase Commit Protocol For Rigorous Participants

Differents standards transactionnels tels que le modele DTP de X/Open ou le modele OTS de l'OMG permettent a des sources de donnees heterogenes de participer a un meme protocole de validation atomique (ACP). en particulier le protocole de validation a deux phases (2PC). Bien que largement utilise, le protocole 20C est bloquant et il introduit un cout de communication et un temps de latence importants. Des variantes de ce protocole ont ete proposees et ont permis d'optimiser le protocole de base ou de le rendre non bloquant. Cependant, les optimisations du protocole 20C violent generalement l'autonomie des sites alors que les protocoles non bloquants accroissent les couts de communication et le temps de latence. Cet article propose u nouveau ACP qui: (i) est non bloquant, (ii) a le plus faible temsp de latence possible pour un ACP et (iii) preserve l'autonomie des sites, ce qui le rend compatible avec les SGBD existants. Ce protocole repose sur l'hypothese que tous les sites participants utilisent un protocole de controle de concurrence rigoureux. Nous montrons que cette hypothese peut etre relâchee afin d'accepter des participants supportant les niveaux d 'isolation standardises dans SQL2.
A Sorting Algorithm Based on Calculation

This article introduces an adaptive sorting algorithm that can relocate elements accurately by substituting their values into a function which we name it the guessing function. We focus on building this function which is the mapping relationship between record values and their corresponding sorted locations essentially. The time complexity of this algorithm O(n),when records distributed uniformly. Additionally, similar approach can be used in the searching algorithm.
A Novel Closed-Form Estimator for 3D TMA Using Heterogeneous Sensors

This paper considers the problem of three-dimensional target motion analysis using a combination of bearing, elevation, and time difference of arrival (TDOA) measurements. We propose a hybrid closed-form solution based on the weighted instrumental variables for this highly nonlinear problem. The proposed solution avoids the high computational complexity and convergence problems associated with iterative estimators. Furthermore, the simulation results suggest that the proposed estimator is nearly efficient, since its performance is very close to the best achievable performance as predicted by the Cramer-Rao lower bound.
Food Understanding from Digital Images

There is a general consensus on the fact that people love food. Due to the great diffusion of low cost image acquisition devices (e.g., smartphones and wearable cameras), the food is nowadays one of the most photographed objects. The number of food images on the web is increasing and novel social networks for food lovers (e.g., foodspotting) are more and more popular. The automatic analysis and classification of food items from images can provide a wider comprehension of the relationship between people and their meals (e.g., preferences of subjects with respect to the dishes of a fast food) and can be useful to build diet monitoring systems (e.g., to combat obesity), as well as recommendation systems for food advertising purposes. On the other hand, automatic food understanding from images is a challenging and exciting task since the high variability of the content depicted in images. In this paper, we address the problem of understanding food from images by proposing a framework for automatic food classification.
Examining Twitter Content of State Emergency Management During Hurricane Joaquin

Those tasked with disseminating life-protecting messages during crises have many factors to consider. Social media sites have become an information source for individuals during these times, and more research is needed examining the use of specific message strategies by emergency management agencies that may elicit attention and retransmission. This study examines Twitter content concerning Hurricane Joaquin. Content analysis of tweets from state emergency management accounts was performed to provide an overview of the content and stylistic elements used in tweets associated with the event. The findings are discussed in the context of both past research on the matter and implications for emergency management agencies responding to high-consequence events.
On Learning How to Learn Learning Strategies Technical Report Fki-198-94 (revised)

This paper introduces the \incremental self-improvement paradigm". Unlike previous methods, incremental self-improvement encourages a reinforcement learning system to improve the way it learns, and to improve the way it improves the way it learns . , without signiicant theoretical limitations | the system is able to \shift its inductive bias" in a universal way. Its major features are: (1) There is no explicit diierence between \learning", \meta-learning", and other kinds of information processing. Using a Turing machine equivalent programming language, the system itself occasionally executes self-delimiting, initially highly random \self-modiication programs" which modify the context-dependent probabilities of future action sequences (including future self-modiication programs). (2) The system keeps only those probability modiications computed by \useful" self-modiication programs: those which bring about more payoo (reward, reinforcement) per time than all previous self-modiication programs. (3) The computation of payoo per time takes into account all the computation time required for learning | the entire system life is considered: boundaries between learning trials are ignored (if there are any). A particular implementation based on the novel paradigm is presented. It is designed to exploit what conventional digital machines are good at: fast storage addressing, arithmetic operations etc. Experiments illustrate the system's mode of operation.
Design of Post-Mapping Fusion Classifiers for Voice-Based Access Control System

This paper introduced voice-based biometric system for access control. The ability to verify the identity of a person by analyzing his/her speech, or speaker verification, is an attractive and relatively unobtrusive means of providing security for admission into an important or secured place. In the field of speaker verification, the main objective is to achieve the highest possible classification accuracy. The proposed system focused on combining the classification scores. Features are extracted from raw data and can be diverse. Therefore, in post-mapping fusion, each feature set is modeled separately, and the output score of the classifiers are combined to give the overall match score. Furthermore, for each classifier score, an a priori weight is set based on the level of confidence of the feature set and the classifier. Three different feature extractions involved in this work are Liner Prediction Cepstral Coefficients (LPCCs), Mel Frequency Cepstral Coefficients (MFCCs) and Perceptual Linear Prediction (PLP) coefficients. While the classifier used in this study is Support Vector Machines (SVMs). Experimental result confirms that in terms of false acceptance rate (FAR) and false rejection rate (FRR), the Post-Mapping Fusion Classifiers is effective to use in the proposed system.