Miracle-dz/UniFAR-FTUs huggingface dataset:
A distributed approach to network anomaly detection based on independent component analysis

Network anomalies, circumstances in which the network behavior deviates from its normal operational baseline, can be due to various factors such as network overload conditions, malicious/hostile activities, denial of service attacks, and network intrusions. New detection schemes based on machine learning principles are therefore desirable as they can learn the nature of normal traffic behavior and autonomously adapt to variations in the structure of ‘normality’ as well as recognize the significant deviations as suspicious or anomalous events. The main advantages of these techniques are that, in principle, they are not restricted to any specific environment and that they can provide a way of detecting unknown attacks. Detection performance is directly correlated with the traffic model quality, in terms of ability of representing the traffic behavior from its most characterizing internal dynamics. Starting from these ideas, we developed a two‐stage anomaly detection strategy based on multiple distributed sensors located throughout the network. By using Independent Component Analysis, the first step, modeled as a Blind Source Separation problem, extracts the fundamental traffic components (the ‘source’ signals), corresponding to the independent traffic dynamics, from the multidimensional time series incoming from the sensors, corresponding to the perceived ‘mixed/aggregate’ effect of traffic on their interfaces. These components will be used to build the baseline traffic profiles needed in the second supervised phase, based on a binary classification scheme (detection is casted into an anomalous/normal classification problem) driven by machine learning‐inferred decision trees. Copyright © 2013 John Wiley & Sons, Ltd.
Application of Hidden Markov Model to Fault Diagnostics of Glass De-chuck System

De-chuck operation which attaches object to glues and detaches object from glues has been used in production line to convey materials in vacuum state. The de-chuck operation for glasses or wafers in production line sometimes causes damages on product in detaching it from glues. Since most of failures in de-chuck operation results from abnormal states of glues such as aged states or strong adhesive states, diagnostics of abnormal glues and a timely replacement of glues are the issues of the de-chuck system. In this study, a testbed simulated de-chuck system is devised and a hidden Markov model (HMM) is applied for diagnostics of the problematic glues in de-chuck system of a testbed. As a result, it was measured quantitatively to the rate of accuracy detecting the area of abnormal glues including aged stateglue and strong adhesive state-glue, and the maximum detection accuracy rate was approximately 82%.
Apoptotic properties of the type 1 interferon induced family of human mitochondrial membrane ISG12 proteins

Interferons are a family of cytokines with growth inhibitory and antiviral functions, which exert their biological actions through the expression of interferon‐stimulated genes (ISGs). The human ISG12 family of proteins comprises ISG12A, ISG12B, ISG12C and ISG6‐16. Due to differential splicing and a gene variation, the human ISG12A protein exists as a full‐length ISG12A form and three ISG12A variants. ISG12 genes have been found transcriptionally dysregulated in many disorders. High levels of ISG12A mRNA have been found in breast and ovarian cancers. Loss of heterozygosity at the position of the ISG12 genes often occurs in ovarian carcinomas and lymphoblastic leukemias. Both ISG12A and ISG6‐16 are up‐regulated in psoriasis.
Lixisenatide Therapy in Older Patients With Type 2 Diabetes Inadequately Controlled on Their Current Antidiabetic Treatment: The GetGoal-O Randomized Trial

OBJECTIVE To evaluate the efficacy and safety of lixisenatide versus placebo on glycemic control in older patients with type 2 diabetes uncontrolled on their current antidiabetic treatment. RESEARCH DESIGN AND METHODS In this phase III, double-blind, randomized, placebo-controlled, two-arm, parallel-group, multicenter trial, patients aged ≥70 years were randomized to receive once-daily lixisenatide 20 μg or placebo before breakfast concomitantly with their existing antidiabetic therapy (including insulin) for 24 weeks. Patients at risk for malnutrition or with moderate to severe cognitive impairment were excluded. The primary end point was absolute change in HbA1c from baseline to week 24. Secondary end points included change from baseline to week 24 in 2-h postprandial plasma glucose (PPG) and body weight. RESULTS A total of 350 patients were randomized. HbA1c decreased substantially with lixisenatide (−0.57% [6.2 mmol/mol]) compared with placebo (+0.06% [0.7 mmol/mol]) from baseline to week 24 (P < 0.0001). Mean reduction in 2-h PPG was significantly greater with lixisenatide (−5.12 mmol/L) than with placebo (−0.07 mmol/L; P < 0.0001). A greater decrease in body weight was observed with lixisenatide (−1.47 kg) versus placebo (−0.16 kg; P < 0.0001). The safety profile of lixisenatide in this older population, including rates of nausea and vomiting, was consistent with that observed in other lixisenatide studies. Hypoglycemia was reported in 17.6% of patients with lixisenatide versus 10.3% with placebo. CONCLUSIONS In nonfrail older patients uncontrolled on their current antidiabetic treatment, lixisenatide was superior to placebo in HbA1c reduction and in targeting postprandial hyperglycemia, with no unexpected safety findings.
A Spectrum- and Energy-Efficient Scheme for Improving the Utilization of MDRU-Based Disaster Resilient Networks

The movable and deployable resource unit (MDRU)-based network provides communication services in disaster-struck areas where the lack of spectrum and energy resources is intensified due to the high demand from users and the power outages after a disaster. The MDRU-based network attempts to apply spectrum- and energy-efficient methods to provide communications services to users. However, existing works in this field only consider spectrum efficiency or energy efficiency separately, in spite of the tradeoff relationship between them. Thus, we propose a scheme to improve the utilization of both spectrum and energy resources for better system performance. The considered MDRU-based network is composed of gateways deployed in the disaster area, which can replenish their energy by using solar panels. Our proposed scheme constructs a topology based on the top k spectrum-efficient paths from each sender and applies a max flow algorithm with vertex capacities, which are the number of transmissions that each gateway can send, which is referred to as transmission capability. The transmission capability of each gateway is determined by its energy resource and distances to its neighbors. Furthermore, we show that the proposal can be used for multisender-multireceiver topologies. A new metric named spectrum-energy efficiency to measure both spectrum efficiency and energy efficiency of the network is defined. Through analyses, we prove that a value of k exists such that the spectrum-energy efficiency of a given topology is maximized. Furthermore, our simulation results show that, by dynamically selecting appropriate value of k, the proposed scheme can provide better spectrum-energy efficiency than existing approaches. Moreover, our experimental results verify the findings of our analysis.
Trends in atmospheric carbon dioxide over the last ten to fifteen years

This study looks at the relative importance of the factors which control the concentration of atmospheric carbon dioxide. EOF analyses are run for both the seasonal and non-seasonal variations for the ten years from 1981 to 1990. The first seasonal EOF represents the anthropogenic component as well as the breathing of the land biosphere. Representing 85% of the variation, it has a seasonal variation of almost 6. The second shows the component of just the land biosphere and has a seasonal variation of about 4. The third seasonal EOF is thought to portray the effect of upwelling in the Eastern Pacific on the tropical strip. The first non-seasonal EOF, accounting for 97% of the total variance, shows an increase of about 11.7 for the period; that of the Northern Hemisphere is about 1.5 times that of the Southern Hemisphere. A modification was made to the original anomalies to adjust for the long term trend in the carbon dioxide data. The rest of the procedure was the same. The first seasonal EOF, contributing to 65.8% of the variance, appears to represent changes in the NH terrestrial biosphere. The second seasonal EOF shows the variance between the long-term trend and the actual data. The third seasonal EOF, with a variance of 4, again depicts the oceanic variance due to upwelling off the coast of Peru. The first non-seasonal EOF matches the activity of the El Nifio, supporting the theory that upwelling increases atmospheric CO2 concentration. It represents over 50% of the total variation. Error in this study may stem from unreliable station data due to infrequent sampling, not a long enough time period for the analysis, and not enough stations to develop a good global result. A stronger, standardized network would greatly enhance the outcome of this analysis. Thesis Supervisor: Reginald Newell Title: Professor Acknowledgments I would like to thank Professor Reginald Newell for all his help and understanding as my advisor. He always managed to find that one piece of information I was looking for, and also helped me through some difficult times. To Wenjie Hu, I am forever indebted for her help with my attempts to program in a language which I knew nothing about, not to mention teaching me everything she new about eigenvector analysis. No matter how matter how many times I asked, she patiently explained everything until I finally understood it. I also want to thank my parents, Ronald and Arlene Strader, for their help and support of me in everything, no matter how small, that I have ever tried to do. They have always been there when I needed them. To my best friends Michelle Bakkila, John Hansen, Andrea Jensen, and Theresa Hutchings, I just want to say, I don't know how I could have gotten through and remained sane without you.
Song-Level Features and Support Vector Machines for Music Classification

Searching and organizing growing digital music collections requires automatic classification of music. This paper describes a new system, tested on the task of artist identification, that uses support vector machines to classify songs based on features calculated over their entire lengths. Since support vector machines are exemplarbased classifiers, training on and classifying entire songs instead of short-time features makes intuitive sense. On a dataset of 1200 pop songs performed by 18 artists, we show that this classifier outperforms similar classifiers that use only SVMs or song-level features. We also show that the KL divergence between single Gaussians and Mahalanobis distance between MFCC statistics vectors perform comparably when classifiers are trained and tested on separate albums, but KL divergence outperforms Mahalanobis distance when trained and tested on songs from the same albums.
Molecular Dynamics Simulation of the Crystallizable Fragment of IgG1—Insights for the Design of Fcabs

An interesting format in the development of therapeutic monoclonal antibodies uses the crystallizable fragment of IgG1 as starting scaffold. Engineering of its structural loops allows generation of an antigen binding site. However, this might impair the molecule’s conformational stability, which can be overcome by introducing stabilizing point mutations in the CH3 domains. These point mutations often affect the stability and unfolding behavior of both the CH2 and CH3 domains. In order to understand this cross-talk, molecular dynamics simulations of the domains of the Fc fragment of human IgG1 are reported. The structure of human IgG1-Fc obtained from X-ray crystallography is used as a starting point for simulations of the wild-type protein at two different pH values. The stabilizing effect of a single point mutation in the CH3 domain as well as the impact of the hinge region and the glycan tree structure connected to the CH2 domains is investigated. Regions of high local flexibility were identified as potential sites for engineering antigen binding sites. Obtained data are discussed with respect to the available X-ray structure of IgG1-Fc, directed evolution approaches that screen for stability and use of the scaffold IgG1-Fc in the design of antigen binding Fc proteins.
A recursive approach for multiclass Support Vector Machine application to automatic classification of endomicroscopic videos

The two classical steps of image or video classification are: image signature extraction and assignment of a class based on this image signature. The class assignment rule can be learned from a training set composed of sample images manually classified by experts. This is known as supervised statistical learning. The well-known Support Vector Machine (SVM) learning method was designed for two classes. Among the proposed extensions to multiclass (three classes or more), the one-versus-one and one-versus-all approaches are the most popular ones. This work presents an alternative approach to extending the original SVM method to multiclass. A tree of SVMs is built using a recursive learning strategy, achieving a linear worst-case complexity in terms of number of classes for classification. During learning, at each node of the tree, a bi-partition of the current set of classes is determined to optimally separate the current classification problem into two sub-problems. Rather than relying on an exhaustive search among all possible subsets of classes, the partition is obtained by building a graph representing the current problem and looking for a minimum cut of it. The proposed method is applied to classification of endomicroscopic videos and compared to classical multiclass approaches.
FriendFinder: A Lifestyle based Friend Recommender App for Smart Phone Users

Today’s Social Networking services focuses towards suggesting you friends based on users social graph or Geo-location based, which neither take users life style into account or users liking ,disliking etc. Suggesting friends using the users’ link analysis may not be the best preference of suggestion for the users. In this paper, we present FriendFinder, a reliable user relation based friend suggesting app which recommends friend list to app users based on their analysis of life style and daily curricular activities on mobile phone instead of social graphs. FriendFinder captures users data i.e. daily activities and work done through mobile, for ex: App Usage, App Frequency, Browser Activities etc. Then we create a user profile with all gathered data and find most relevant matching profiles of existing candidate friends matching our profile for similarity and suggesting the result out of similarity test to the user as a friend.
Cardiac Autonomic Dysfunction in Type 2 Diabetes – Effect of Hyperglycemia and Disease Duration

Heart rate variability (HRV) is reduced in diabetes mellitus (DM) patients, suggesting dysfunction of cardiac autonomic regulation and an increased risk for cardiac events. The aim of this paper was to examine the associations of blood glucose level (BGL), glycated hemoglobin (HbA1c), and duration of diabetes with cardiac autonomic regulation assessed by HRV analysis. Resting electrocardiogram (ECG), recorded over 20 min in supine position, and clinical measurements of 189 healthy controls and 93 type 2 DM (T2DM) patients were analyzed. HRV was assessed using several time-domain, frequency-domain, and non-linear methods. HRV parameters showed a clear difference between healthy controls and T2DM patients. Hyperglycemia was associated with increase in mean heart rate and decrease in HRV, indicated by negative correlations of BGL and HbA1c with mean RR interval and most of the HRV parameters. Duration of diabetes was strongly associated with decrease in HRV, the most significant decrease in HRV was found within the first 5–10 years of the disease. In conclusion, elevated blood glucose levels have an unfavorable effect on cardiac autonomic function and this effect is pronounced in long-term T2DM patients. The most significant decrease in HRV related to diabetes and thus presence of autonomic neuropathy was observed within the first 5–10 years of disease progression.
Detection of Epstein-Barr virus DNA by polymerase chain reaction in blood and tissue biopsies from patients with Sjogren's syndrome

Polymerase chain reaction has been used to detect increased levels of EBV DNA in salivary gland (SG) biopsies and PBL from patients with Sjogren's syndrome (SS). These results suggest that EBV, which has a normal site of latency in a small number of SG epithelial cells, may be reactivated in SS patients and provide a target for immune attack. The great sensitivity of polymerase chain reaction (PCR) and the ability to analyze very small tissue biopsies (37) make this technique well suited for clinical diagnosis. Specific methods to prevent artefactual contamination of tissue biopsy DNA with viral DNA of other samples (i.e., lyophilization of samples before DNA extraction) and the use of an internal positive control (i.e., inclusion of primers for a single copy human gene) during PCR amplification are presented. Since EBV reactivation occurs with markedly increased frequency in patients with lymphoproliferative and immunodeficiency diseases, as well as transplant recipients receiving cyclosporin A (10), rapid methods of viral detection such as PCR may allow better monitoring of medications and early detection of EBV-related lymphomas that may arise in these patients.
Use Bit Scanning in Replacement Decisions

In paged storage systems, page replacement policies generally depend on a use bit for each page frame. The use bit is automatically turned on when the resident page is referenced. Typically, a page is considered eligible for replacement if its use bit has been scanned and found to be off on µ consecutive occasions, where µ is a parameter of the algorithm. This investigation focuses on the dependence of the number of bit-scanning operations on the value of µ and on properties of the string of page references. The number of such operations is a measure of the system overhead incurred while making replacement decisions. In particular, for several algorithms, the number of scans per reference is shown to be approximately proportional to µ However, empirical results from single-program traces show that the value of µ has little effect on the miss ratio. Although the miss ratios for the bit-scanning algorithms are close to those of least recently used (LRU), it is pointed out that increasing the value of µ need not bring the bit-scanning policies closer to LRU management.
Interactions of hyperthermia and chemotherapy in animals.

In tissue culture, the cytotoxicity of a number of commonly used chemotherapeutic drugs is greatly enhanced at elevated temperatures. However, pharmacokinetics, drug concentrations, oxygen tension, and pH in tumors in animals can all vary widely from those in cell cultures. In addition, tissue culture studies do not give vital information on the effect of combinations of drugs and hyperthermia on normal tissues or metastases. Available studies of drugs and hyperthermia in animals are reviewed, and they yield clinically useful information. One study indicated that the activity of methotrexate was not enhanced by hyperthermia in vivo . Results for alkylating agents were not conclusive. Antitumor effects of 1,3-bis(2-chloroethyl)-1-nitrosourea, bleomycin, and cis -diamminedichloroplatinum, however, were significantly potentiated by local hyperthermia. 1,3-bis(2-chloroethyl)-1-nitrosourea effects were enhanced between 41 and 42°C, and thus, it is potentially of use in the setting of systemic hyperthermia. Bleomycin, however, was enhanced significantly only near 43°, suggesting that its clinical use is more appropriate with local hyperthermia. Adriamycin and S -(2-aminoethyl)isothiouronium dihydrobromide, although potentiated in vitro , were not potentiated in vivo in doses which were clinically tolerable. Discrepancies between the in vitro and in vivo findings are likely due, at least in part, to differences in drug concentration. The combination of local primary tumor hyperthermia and chemotherapy did not adversely affect the incidence or severity of spontaneous lung metastases in KHT tumor-bearing mice. Very few studies of the pharmacology of drugs in vivo in the presence of hyperthermia have been reported. Uptake of chemotherapeutic drugs may be enhanced in hyperthermic tissue. Further in vivo studies both of effectiveness and drug pharmacology for combined hyperthermia and chemotherapy are advisable to define optimum time-dose schedules for clinical trials.
Spectrum database as a service (SDaaS) for broadband innovation and efficient spectrum utilization

Broadband innovations for future wireless networks involves rapid sharing of radio frequency (RF) spectrum resources by means of dynamic spectrum access techniques (DSA) to satisfy immediate portfolio of heterogeneous demands of wireless IP services. In this paper a cloud framework for spectrum database as a service (SDaaS) for the application layer is introduced. The SDaaS framework can provide a wide range of vital capabilities needed for unlocking the DSA-based networks: (i) SDaaS can be used as the best short-term solution for minimising any harmful interference that might be introduced to the co-channels and adjacent-channels of the incumbent users subject to a dynamic spectrum sharing policy. Examples of such network architectures are those based on the TV white spaces (TVWS) technologies. (ii) SDaaS can be used as a toolbox by regulators in the development of efficient dynamic spectrum regulations at a national level. (iii) Such regulations can be enforced and monitored through an SDaaS environment suggested in this paper. Moreover, multi-tenancy and schema-sharing techniques are utilised at the inter- regional level to allow the cross-border harmonisation of RF spectrum regulation to negate the problem of IP communication islands. Keywords-Cloud; Database-as-a-Service; DSA; Whitespaces; SDaaS; Regulators; Spectrum; TVWS
MIREX 2011 : AUTOMATIC AUDIO TAG CLASSIFICATION VIA SPARSE CODING

This extended abstract details our submission to the Music Information Retrieval Evaluation eXchange (MIREX) 2011 for the audio tag classification task. First of all, we extract a fixed-length feature vector (composed of some timbral as well as modulation spectrum features) from each song clip. Then, by using l-reconstruction to represent each test song clip as a linear combination of all training songs (also known as sparse coding), we use the label matrix of training song clips to transform the sparse reconstruction coefficients of each test song clip to the label vector space. Finally, the labels with the largest values are used as the final tags for each test song clip.