Miracle-dz/UniFAR-FTUs huggingface dataset:
Semantic Chameleon Clustering Analysis Algorithm with Recommendation Rules for Efficient Web Usage Mining

World Wide Web (WWW) is having a huge volume of information and each day millions of users are accessing it. So the major problem in this scenario is to provide relevant recommendations to the users' according to their request. The web usage mining is one of the efficient approaches where the web logs are mined to generate the user search model and provide recommendations and the recommendation process provides significant search options that the user expects. So the recommended options are needed to be more meaningful and relevant to present search. In this paper, we suggest an approach for generating the frequent pattern with strong recommendations for user search with semantic relation. The semantically similar patterns are derived by applying semantic analysis on frequent search pattern. The CHAMELEON, a Two-phase Clustering Algorithm is used for the discovering the frequent search pattern. Finally the Recommendation Rules Generation component is used to find the matching web pages and links for recommendations to the users.
Cardiac Arrhythmias as Manifestations of Nanopathies: An Emerging View

A nanodomain is a collection of proteins localized within a specialized, nanoscale structural environment, which can serve as the functional unit of macroscopic physiologic processes. We are beginning to recognize the key roles of cardiomyocyte nanodomains in essential processes of cardiac physiology such as electrical impulse propagation and excitation–contraction coupling (ECC). There is growing appreciation of nanodomain dysfunction, i.e., nanopathy, as a mechanistic driver of life-threatening arrhythmias in a variety of pathologies. Here, we offer an overview of current research on the role of nanodomains in cardiac physiology with particular emphasis on: (1) sodium channel-rich nanodomains within the intercalated disk that participate in cell-to-cell electrical coupling and (2) dyadic nanodomains located along transverse tubules that participate in ECC. The beat to beat function of cardiomyocytes involves three phases: the action potential, the calcium transient, and mechanical contraction/relaxation. In all these phases, cell-wide function results from the aggregation of the stochastic function of individual proteins. While it has long been known that proteins that exist in close proximity influence each other’s function, it is increasingly appreciated that there exist nanoscale structures that act as functional units of cardiac biophysical phenomena. Termed nanodomains, these structures are collections of proteins, localized within specialized nanoscale structural environments. The nano-environments enable the generation of localized electrical and/or chemical gradients, thereby conferring unique functional properties to these units. Thus, the function of a nanodomain is determined by its protein constituents as well as their local structural environment, adding an additional layer of complexity to cardiac biology and biophysics. However, with the emergence of experimental techniques that allow direct investigation of structure and function at the nanoscale, our understanding of cardiac physiology and pathophysiology at these scales is rapidly advancing. Here, we will discuss the structure and functions of multiple cardiomyocyte nanodomains, and novel strategies that target them for the treatment of cardiac arrhythmias.
Benefits and Risks of Nonsteroidal Anti-inflammatory Drugs: Methodologic Limitations Lead to Clinical Uncertainties

Nonsteroidal anti-inflammatory drugs (NSAIDs) include traditional (tNSAIDs), such as ibuprofen, naproxen, and diclofenac, as well as selective cyclooxygenase-2 inhibitors (COXIBs), principally celecoxib. COXIBs were developed to decrease gastrointestinal side effects. Recently, the US Food and Drug Administration strengthened its warning about the risks of non-aspirin NSAIDs on myocardial infarction and stroke. The Cyclooxygenase 2 and Non-Steroidal Anti-Inflammatory Drug Trialist collaboration conducted a comprehensive worldwide meta-analysis using individual patient data exploring the risks of various COXIBs and NSAIDs on cardiovascular disease (CVD). Recently, the results of the Prospective Randomized Evaluation of Celecoxib Integrated Safety versus Ibuprofen or Naproxen (PRECISION) trial were published that tested risks of COXIBs and NSAIDs on CVD. Generally, data from meta-analyses of trials not designed a priori to test hypotheses are less reliable than large-scale randomized trials to test small to moderate benefits or harm. When the sample size is large, randomization provides control of confounding not possible to achieve in any observational study. Further, observational studies, and especially claims data, have inherent confounding by indication larger than the effects being sought. Nonetheless, trials must be of sufficient size and duration and achieve high compliance and follow-up to avoid bias and confounding. In this regard, PRECISION has high rates of nonadherence and losses to follow-up that may have introduced bias and confounding. At present, therefore, it may be most prudent for clinicians to remain uncertain about benefits and risks of these drugs and make individual clinical judgments for each of their patients.
LARGen: Automatic Signature Generation for Malwares Using Latent Dirichlet Allocation

As the quantity and complexity of network threats grow, Intrusion Detection Systems (IDSs) have become critical for securing networks. Achieving computer network intrusion detection with these IDSs requires high-level information technology and security expertise because malicious traffic has to be rigorously analyzed and the appropriate IDS rules written to effectively detect vulnerabilities that may potentially be exploited. However, incorrect IDS rules may produce numerous false positives, thereby degrading the performance of the IDS, and even worse, paralyzing the network. In this paper, we present a novel approach that exploits the Latent Dirichle Allocation (LDA) algorithm to generate IDS rules. Our proposed method, called LDA-based Automatic Rule Generation (LARGen), automatically performs an analysis of the malicious traffic and extracts the appropriate attack signatures that will be used for IDS rules. LARGen first extracts multiple signature strings embedded in network flows. Then, the flows are classified based on the extracted signature strings, and key content strings for malicious traffic are identified through the LDA inferential topic model. Those key content strings are the core of an IDS rule that can detect malicious traffic. We study the effectiveness of LDA in the context of network attack signature generation via extensive experiments with real network trace data, consisting of both benign and malicious traffic. Experimental results confirm that threat rules generated from LARGen accurately detect every cyber attack with high accuracy.
Dimension Reduction Techniques Analysis on Image Processing for Facial Emotion Recognition

As the rapid growth of technology continuously increases the accuracy, effectivity, and efficiency of human's effort, technology also requires some improvements in order to sustain its capabilities. One of the latest technologies today when it comes to biometrics is facial emotion recognition. Facial emotion recognition initially detects the face of a person before it recognizes human's emotion using image processing or video sequence method. The different algorithm was applied to related studies to increase the accuracy on recognizing the emotion. However, the efficiency of the data needed in order to identify the emotion of a person is also a big factor to reduce time on image processing part. This research analyzed three dimension reduction techniques on image processing for facial emotion recognition such as dimension reduction by forward selection, dimension reduction by decision tree, and dimension reduction by principal component analysis. The application of online recognition API and data mining tool on controlled dataset serves as the materials to generate the numerical and logical result which is used in the process of analysis.
The Epidemiology of Symptomatic Catheter-associated Urinary Tract Infections in the Intensive Care Unit: A 4-year Single Center Retrospective Study.

PURPOSE Catheter-associated urinary tract infection (CAUTI) occurs frequently in critical illness with signifi-cant morbidity, mortality, and additional hospital costs. The epidemiology of symptomatic ward-acquired CAUTI (within 48 hours of intensive care unit [ICU] admission) has not been carefully examined. The objective of our study was to identify the patient characteristics and microbiology of symptomatic CAUTI in critical illness. MATERIALS AND METHODS A 4-year retrospective observational study (2013-2016) was conducted at a single adult ICU with 30 beds in a tertiary hospital in Northeast China. The enrolled patients were over 18 years of age and had been diagnosed as having symptomatic CAUTIs in the ICU from January 2013 to December 2016. The infor-mation of clinicopathological characteristics (such as age, sex, underlying diseases, hospital admission diagnosis, ICU admission source, severity of illness, duration of urinary catheterization, use of antibiotics, duration of ICU stay, and ICU mortality) was recorded in an electronic database by senior clinicians who were blinded to the study purpose and design. Microbiological data were retrieved from the computerized hospital database. RESULTS Between January 2013 and December 2016, 4115 patients were admitted to the ICU. Ninety-eight symp-tomatic CAUTI cases were enrolled in this study, including 29 patients who had ward-acquired CAUTI and 69 pa-tients who had ICU-acquired CAUTI. Patients with ward-acquired symptomatic CAUTI had significantly shorter overall ICU length of stay and shorter urinary catheterization time, and the overall ICU mortality was significantly higher in patients who had ICU-acquired symptomatic CAUTI. More third-generation cephalosporins and carbap-enems were used prior to CAUTI in the patients with ICU-acquired symptomatic CAUTI. Escherichia coli and Acinetobacter baumannii were the most common bacteria causing ward-acquired and ICU-acquired CAUTI, re-spectively. There were a higher number of cases of non-Candida albicans infections in patients with ICU-acquired symptomatic CAUTI than in patients with ward-acquired symptomatic CAUTI. CONCLUSION Clinical characteristics, microbiological characteristics, and prognosis were different between ward-acquired and ICU-acquired symptomatic CAUTI. Patients with ICU-acquired symptomatic CAUTI had higher overall ICU mortality.
Distributed Control of Active Distribution Networks for Frequency Support

It is a new trend to utilize highly distributed energy resources (DERs) scattered in distribution networks to support power system frequency control. However, in a power system, there may be thousands or millions of DERs, and it is impractical to control these DERs directly by the control center. To solve this challenge, we regard each distribution network with DERs as a distributed energy resource cluster (DERC) which serves as the intermediary between DERs and the control center. For each DERC, the primary objective is to quickly follow the active power change command given by the control center. However, due to the high R/X ratio of lines in distribution networks, the active power changes of DERs can also lead to voltage issues such as voltage variation and violation in a distribution network. To overcome these issues, this paper develops a novel distributed control framework for DERCs to support frequency control, which consists of two modules: an active power sharing module and a voltage regulation module. The former one aims to rapidly track the active power change command from the control center by coordinating the active power of DERs in an optimal distributed manner. The latter one aims to regulate bus voltages within the acceptable limits by changing the reactive power of each DER based on local voltage information. The effectiveness of the proposed control framework has been tested through an 8-bus distribution system.
Intimate Partner Violence in the Golden Age: Systematic Review of Risk and Protective Factors

Intimate partner violence (IPV) is identifiable as a major public health concern worldwide. The international literature highlights how this phenomenon is complex and transversal to all age groups. While the global population is becoming older, the scientific research about risk and protective factors related to IPV in the golden age is diverse, and the different findings of the various studies have not been systematized so far. Thus, in this systematic review, we aim to analyze the scientific studies that investigate the risk and the protective factors of violent dynamics between elderly couples. From the perspective of the theoretical frameworks and the methodological approaches used, we present the main conceptual themes that emerge. Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, we review the articles that report the analyses of protective and risk factors of IPV perpetration. Our results indicate social support, help-seeking behavior, and the availability of community-based services addressing the issues of abuse as the main protective factors. The risk factors are related to economic conditions, belonging to an ethnic minority, cognitive or physical impairment, other conditions associated with cultural background and relational dynamics, such as intrapartner dependence and intergenerational transmission of violence and trauma, and caregiving stress. We discuss possible future directions of research to improve the understanding of IPV in the elderly population and the implications for the development of intervention policies at preventive and supportive levels.
Application of Model Predictive Control Algorithm on a Hydro Turbine Governor Control

Operation of the most turbine governors currently in use is based on Proportional-Integral-Derivative (PID) controllers. The use of PID controllers is widespread primarily because of their extensive applicability to a variety of single-input-single-output (SISO) applications. However, classical PID controllers have disadvantages, e.g. resiliency to disturbances and uncertainties, as well as integral windup. In this regard, a controller based on the Model Predictive Control (MPC) algorithm, which is known as a Generalized Predictive Control (GPC), is developed and applied to a linearized SISO model of the hydropower plant. The response of the system with constrained GPC is compared to the classical PI controller. The main conclusion is that GPC provides better performance than the classical PI regulator.
Breaking Through Opacity: A Context-Aware Data-Driven Conceptual Design for a Predictive Anti Money Laundering System

We studied the problem of money laundering. Current anti money laundering artificial systems solve this problem by tracking transactions. However, several inherent aspects impede a full uncovering of the underlying process; most arguably the abstract nature of transactions and the ‘legitimacy dilemma’. We circumvent these issues by proposing a context-aware and data-driven software/hardware system that tracks physical money rather than abstract transactions. The proposed system identifies banknotes by their unique serial numbers, allowing a meta data component that accumulates further contextual information to better detect unusual patterns of transactional behaviours. In addition, using ‘social network analysis’, the system can be used to predict future money laundering processes.
Fusion of Compound Queries with Multiple Modalities for Known Item Video Search

Multimedia collections are ubiquitous and contain hundreds of hours of video information. The retrieval of a particular scene of a video (Known Item Search (KIS)) in a large collection is a difficult problem, considering the multimodal character of all video shots and the complexity of the query, either visual or textual. We tackle these challenges by fusing, first, multiple modalities in a nonlinear graph-based way for each subtopic of the query. Then, we fuse the top retrieved video shots per sub-query to provide the final list of retrieved shots, which is re-ranked using temporal information. The framework is evaluated in popular KIS tasks in the context of video shot retrieval and provides the largest Mean Reciprocal Rank scores.
mm-Wave High Gain Cavity-Backed Aperture-Coupled Patch Antenna Array

A wideband and high gain cavity-backed $4\times 4$ patch antenna array is proposed in this paper. Each patch antenna element of the array is enclosed by a rectangular cavity and differentially-fed by the slot underneath. By optimizing the geometry of the radiating patch and the cavity, a very uniform E-field distribution at the antenna aperture is achieved, leading to the high array aperture efficiency and thus the gain. Taking advantages of the higher-order substrate integrated cavity excitation, the elements of the array are efficiently fed with the same amplitude and phase in a simplified feeding mechanism instead of the conventional bulky and lossy power-splitter-based feeding network. Measured results show the antenna bandwidth is from 56 to 63.1-GHz (16.1%) with the peak gain reaching 21.4 dBi. The radiation patterns of the array are very stable over the entire frequency band and the cross-polarizations are as low as −30 dB. These good characteristics demonstrate that the proposed array can be a good candidate for the future 60-GHz communication system applications.
A Review on the Application and Usefulness of Metal Nanosized Particles in Solid Rocket Propellants

In order to make the next leap forward from the current generation of technology, energy applications ofnanotech-nology have been developed. Nanotechnology is any technology that contains components smaller than 100 nm. Nanomaterials research takes a materials science-based approach to nanotechnology, leveraging advances in materials metrology and synthesis which have been developed in support of microfabrication research. Materials with structure at the nanoscale often have unique optical, electronic, mechanical, thermal, magnetic or catalytic properties. This research work aims to review the most relevant, recent investigations that have been made in order to clarify the importance of the application of these energetic nanomaterials, particularly for aerospace propulsion, for solid rocket propellants characteristics and performance enhancement, and this by exploring the different factors and characteristics of these materials that influence the burning rates, burning times, ignition delays and temperatures. First, we explored the addition of metals to solid propellants for different applications and the advantages that it can bring. Then, we investigated the benefits of substituting metals micron-sized particles by their nanosized counterparts. Finally, the enhancement of composite solid propellants decomposition by using nanosized particles as catalysts. The benefits of utilizing nanoparticles consist of the potential to eliminate agglomeration encountered for larger particles, earlier ignition, higher total heat release rate, and further extension of the burning rate for functionalized/catalytic particles.
YAG:Ce-Phosphor Scintillators for Optical Fiber Radiation Sensors With High Temporal Resolution

A miniature optical fiber real-time X-ray radiation sensor based on plastic optical fiber coupled with a fast decay time trivalent cerium-activated yttrium aluminum garnet Y3Al5O12 (YAG:Ce) scintillator material is reported. The YAG material was tested in powder and ceramic form. Three separate sensors were irradiated three times on a Siemens Artiste linear accelerator (linac). The measured light output of the YAG:Ce ceramic to the detector at the distal end of the fiber is 4.52 times greater than the YAG:Ce powder, and its output intensity detected by photon counter is further increased 2.52 times using a two-layer highly reflective Teflon tape. The sensor made with YAG:Ce powder shows excellent repeatability, being a maximum of 0.36 %, but the value using YAG:Ce ceramic exhibits orientation sensitivity when located in orthogonal positions relative to the X-ray beam. To the best of our knowledge, the work described in this letter is the first instance of the direct high temporal resolution detection of the individual (circa 3.9 ms) output of X-ray light pulses of clinical linacs. The experimental results of pulsewidths are in good agreement with the manufacturer’s stated value of $3.45~\pm ~0.21~\mu \text{s}$ .
Investigating the Prerequisites for a robust Neurotutor: The Detection of mixed User States containing Working Memory Load, Affective Valence and Affective Dominance

Up to now, most brain-based measures of the electroencephalogram (EEG) are used in lab environments and only focus on narrow mental states (e.g. WML). However, we assume that outside the lab complex multidimensional mental states are evoked. This could potentially create interference between EEG signatures used for identification of specific mental states. In this study, we investigated interactions between WML and affective valence to reveal potential interferences in EEG measures. To induce changes in WML and affective valence, we used a paradigm which combines an Nback task (for WML manipulation) with a standard method to induce affect (affective pictures taken from the International Affective Picture System or IAPS database). As expected, we found that behavioral performance decreased with increasing workload as well as negative valence, showing that affective valence can have an effect on The three Manuscripts describing the Studies of this Thesis Page 48 of 178 cognitive processing. These findings are supported by changes in frontal theta and parietal alpha power, parameters used for measuring of WML in the EEG. However, these EEG measures are influenced by the negative valence condition as well and thereby show interactions between WML and affective valence. Unexpectedly, we did not find any effects for EEG measures typically used for affective valence detection (frontal alpha asymmetry or FAA). Therefore we assume that the FAA measure might not be usable if cognitive workload is induced simultaneously. We conclude that future studies should account for potential context-specifity of EEG measures.
Binary "proximity patches motion" descriptor for action recognition in videos

Building action recognition systems that are simultaneously fast, robust and requiring small memory space is very challenging. Though current state-of-the-art frameworks proposed the best performance on accuracy, speed or memory, they do not offer simultaneously best performance on all three metrics. Thus, it is still possible to achieve a good trade-off among all these three metrics. Using a compact patch-based pattern, this paper introduces a novel binary motion descriptor to efficiently describe motion in video. The descriptor, namely the Proximity Patches Motion (PPM), compares in two different ways a 3 x 3 central patch centered on a detected keypoint with other 24 patches compactly positioned around it between three consecutive frames. Experimental results on the Weizmann and KTH datasets show that the proposed method not only requires a small amount of memory, but is also faster and achieves competitive accuracy when compared to the state-of-the-art spatio-temporal binary descriptors.