Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Denial of Service detection using hybrid machine learning technique

Distributed Denial of Service (DDoS) is a major threat among many security issues. To overcome this problem, many studies have been carried out by researchers, however due to inefficiency of their techniques in terms of accuracy and computational cost, proposing an efficient method to detect DDoS attack is still a hot topic in research. Current paper proposes architecture of a detection system for DDoS attack. Genetic Algorithm (GA) and Artificial Neural Network (ANN) are deployed for feature selection and attack detection respectively in our hybrid method. Wrapper method using GA is deployed to select the most efficient features and then DDoS attack detection rate is improved by applying Multi-Layer Perceptron (MLP) of ANN. Results demonstrate that the proposed method is able to detect DDoS attack with high accuracy and deniable False Alarm.
A Multiview Multimodal System for Monitoring Patient Sleep

Clinical observations indicate that during critical care at the hospitals, a patient's sleep positioning and motion have a significant effect on recovery rate. Unfortunately, there is no formal medical protocol to record, quantify, and analyze motion of patients. There are very few clinical studies that use manual analysis of sleep poses and motion recordings to support medical benefits of patient positioning and motion monitoring. Manual processes do not scale, are prone to human errors, and put strain on an already taxed healthcare workforce. This study introduces multimodal, multiview motion analysis and summarization for healthcare (MASH). MASH is an autonomous system, which addresses these issues by monitoring healthcare environments and enabling the recording and analysis of patient sleep-pose patterns. MASH uses three RGB-D cameras to monitor patients in a medical intensive care unit (ICU) room. The proposed algorithms estimate pose direction at different temporal resolutions and use keyframes to efficiently represent pose transition dynamics. MASH combines deep features computed from the data with a modified version of hidden Markov model (HMM) to flexibly model pose duration and summarize patient motion. The performance is evaluated in ideal (BC: bright and clear/occlusion-free) and natural (DO: dark and occluded) scenarios at two motion resolutions and in two environments: a mock-up and a medical ICU. The usage of deep features is evaluated and their performance compared with engineered features. Experimental results using deep features in DO scenes increase performance from $\text{86.7}\%$ to $\text{93.6}\%$, while matching the classification performance of engineered features in BC scenes. The performance of MASH is compared with HMM and C3D. The overall overtime tracing and summarization error rate across all methods increased when transitioning from the mock-up to the the medical ICU data. The proposed keyframe estimation helps achieve a $\text{78}\%$ transition classification accuracy.
Sound localization and occupational noise

OBJECTIVE: The aim of this study was to determine the effects of occupational noise on sound localization in different spatial planes and frequencies among normal hearing firefighters. METHOD: A total of 29 adults with pure-tone hearing thresholds below 25 dB took part in the study. The participants were divided into a group of 19 firefighters exposed to occupational noise and a control group of 10 adults who were not exposed to such noise. All subjects were assigned a sound localization task involving 117 stimuli from 13 sound sources that were spatially distributed in horizontal, vertical, midsagittal and transverse planes. The three stimuli, which were square waves with fundamental frequencies of 500, 2,000 and 4,000 Hz, were presented at a sound level of 70 dB and were randomly repeated three times from each sound source. The angle between the speaker's axis in the same plane was 45°, and the distance to the subject was 1 m. RESULT: The results demonstrate that the sound localization ability of the firefighters was significantly lower (p<0.01) than that of the control group. CONCLUSION: Exposure to occupational noise, even when not resulting in hearing loss, may lead to a diminished ability to locate a sound source.
Towards a multilevel cognitive probabilistic representation of space

This paper addresses the problem of perception and representation of space for a mobile agent. A probabilistic hierarchical framework is suggested as a solution to this problem. The method proposed is a combination of probabilistic belief with “Object Graph Models” (OGM). The world is viewed from a topological optic, in terms of objects and relationships between them. The hierarchical representation that we propose permits an efficient and reliable modeling of the information that the mobile agent would perceive from its environment. The integration of both navigational and interactional capabilities through efficient representation is also addressed. Experiments on a set of images taken from the real world that validate the approach are reported. This framework draws on the general understanding of human cognition and perception and contributes towards the overall efforts to build cognitive robot companions.
Intrauterine ozone administration for improving fertility rate in Simmental cattle.

1Sisak-Moslavina County, Department of Agriculture and Forestry, Sisak, Croatia 2Veterinary practice Bosgen d.o. o. , Zagreb Croatia 3Veterinary practice Daruvar, Daruvar, Croatia 4Veterinary practice Jastrebarsko, Jastrebarsko, Croatia 5Veterinary practice Grubisno Polje, Grubisno Polje, Croatia 6Veterinary practice Duga Resa, Duga Resa, Croatia 7Geo Agro Farm, Novi Grabovac, Croatia 8Veterinary practice Gejzir, Dubrava, Croatia 9Clinic for Surgery, Orthopaedics and Ophthalmology, Faculty of Veterinary Medicine, University of Zagreb, Zagreb, Croatia ________________________________________________________________________________________ ZOBEL, R. , R. MARTINEC, D. IVANOVIC, N. ROSIC, Z. STANCIC, I. ŽERJAVIC, B. FLAJSIG, H. PLAVEC, O. SMOLEC: Intrauterine ozone administration for improving fertility rate in Simmental cattle. Vet. arhiv 84, 1-8, 2014. ABSTRACT The objective of the study was to determine whether fertility in cows can be improved by postpartal intrauterine ozone administration. The cows were divided into two groups treatment (T) and control (C). The treatment group received 20 mL of ozonated foam into the uterus within 6 hours after calving and 24 hours later. Control group received no treatment. The outcome measurements were the number of days open and the number of artifi cial inseminations until pregnancy. The ozone was found to be effective treatment modality, resulting in a shorter period of days open (75.47 vs. 98.03, P<0.05), and fewer inseminations until pregnancy (1.68 vs. 2.42, P<0.05) in treated cows compared to the control group. Postpartal intrauterine ozone fl ush, coupled with intracornual insemination represents an effective treatment option that could lead to an improved fertility rate in Simmental cows.
A New Family of Software Anti-patterns: Linguistic Anti-patterns

Recent and past studies have shown that poor source code lexicon negatively affects software understand ability, maintainability, and, overall, quality. Besides a poor usage of lexicon and documentation, sometimes a software artifact description is misleading with respect to its implementation. Consequently, developers will spend more time and effort when understanding these software artifacts, or even make wrong assumptions when they use them. This paper introduces the definition of software linguistic antipatterns, and defines a family of them, i.e., those related to inconsistencies (i) between method signatures, documentation, and behavior and (ii) between attribute names, types, and comments. Whereas "design" antipatterns represent recurring, poor design choices, linguistic antipatterns represent recurring, poor naming and commenting choices. The paper provides a first catalogue of one family of linguistic antipatterns, showing real examples of such antipatterns and explaining what kind of misunderstanding they can cause. Also, the paper proposes a detector prototype for Java programs called LAPD (Linguistic Anti-Pattern Detector), and reports a study investigating the presence of linguistic antipatterns in four Java software projects.
Maturity level of knowledge management in Thailand: the practical

Knowledge is a valuable for any organization. The way that the organization creates, identifies, stores, and uses knowledge is important. Data are sources of knowledge. The analytical methods are used to transform data to be information and knowledge. As knowledge can be used to increase organization performance, the quality of data and its management, analytical skills and tools, collaboration skills, interpretation ability to identify knowledge, and knowledge management should be evaluated. Leading knowledge management organizations in Thailand were interviewed to identify the maturity level of knowledge management. The results show that data quality should be improved along with the analytical skills. The problem definitions are not stated clearly and represented the real business problems. The collaboration level among organizations are low, including the collaboration within the organization. Knowledge are kept in form of report mostly and not practical used efficiently overall the organization. To increase the maturity level of knowledge management, the organization should concern more about the quality of data, the ability to understand the business environment, and the ability of performing data analysis.
Fast Algorithms for Resource Allocation in Wireless Cellular Networks

We consider a scheduled orthogonal frequency division multiplexed (OFDM) wireless cellular network where the channels from the base-station to the n mobile users undergo flat fading. Spectral resources are to be divided among the users in order to maximize total user utility. We show that this problem can be cast as a nonlinear convex optimization problem, and describe an O(n) algorithm to solve it. Computational experiments show that the algorithm typically converges in around 25 iterations, where each iteration has a cost that is O(n), with a modest constant. When the algorithm starts from an initial resource allocation that is close to optimal, convergence typically takes even fewer iterations. Thus, the algorithm can efficiently track the optimal resource allocation as the channel conditions change due to fading. We also show how our techniques can be extended to solve resource allocation problems that arise in wideband networks with frequency selective fading and when the utility of a user is also a function of the resource allocations in the past.
The rigidity of choice: lifetime savings under information-processing constraints

This paper studies the implications of information-processing limits on the consumption and savings behavior of households through time. It presents a dynamic model in which consumers rationally choose the size and scope of the information they want to process about their fi�nancial possibilities, constrained by a Shannon channel. The model predicts that people with higher degrees of risk aversion rationally choose higher information. This happens for precautionary reasons since, with fi�nite processing rate, risk averse consumers prefer to be well informed about their fi�nancial possibilities before implementing consumption plan. Moreover, numerical results show that consumers with processing capacity constraints have asymmetric responses to shocks, with negative shocks producing more persistent effects than positive ones. This asymmetry results into more savings. I show that the predictions of the model can be effectively used to study the impact of tax reforms on consumers spending. The results are qualitatively consistent with the evidence on tax rebates (2001, 2008).
Content Based Copy Detection

1. Briefly, what approach or combination of approaches did you test in each of your submitted runs? • VIVAlab-uOttawa.v The video search approach is based on a method that finds keypoints in each video frame, and then uses a descriptor of keypoint counts in 16 (4 by 4) equally sized regions of the images. • VIVAlab-uOttawa.a The audio-only copy detection search scheme was based on the computation of a coherence function, using intermediate features in the ITU-R BS.1387 Perceptual Evaluation of Audio Quality (PEAQ) standard. • VIVAlab-uOttawa.m The combined audio-video used the fact that audio was detected in a database segment simply to boost the video scores. 2. What if any significant differences (in terms of what measures) did you find among the runs? The video only approach performs well in terms of the mean F1 measure, which is a consequence of the construction of the algorithm. Indeed, because a frame is represented with only 16 bytes, it was possible to compare each frame of the query with each frame of the video database. As a result, our algorithm is one of the best in terms of accuracy. The balanced profile performs at almost exactly the median in terms of NDCR, while the NOFA profile is slightly worse than the median performance. The audio only approach is slightly worse than the median in terms of NDCR. The F1 results are not significant in this case because of the very low number of positive detection that were submitted. The audio detection method has a very low false positive detection rate but, unfortunately a very high false negative too. The combined results were lower than what we expected; we still have to analyze the root cause of this performance. 3. Based on the results, can you estimate the relative contribution of each component of your system/approach to its effectiveness? Currently the video analysis seems to be doing most of the work, but we do not believe that our combination of the audio and video search methods is optimal. 4. Overall, what did you learn about runs/approaches and the research question(s) that motivated them? With so many different possible solutions to copy detection deciding which is the best is a function of the goals. Our goal is to have an approach that provides good performance, is easy to parallelize, works quickly in search mode, and has low storage requirements per video frame of the database. We believe that we have achieved this goals, but we have not yet found a satisfactory way of combining the audio video results.
Performance study of the index structures in audited environment

Development in information systems has brought the need for universal access to data stored in computer systems using database approach. It should ensure quality, reliability, performance with emphasis on rising data amount. The first part of the paper deals with the index structure definition, index access methods, which delimit access type. However, another significant factor is the data security. The second part of the paper deals with the audit as one element of complex activities. Standard database auditing does not influence defined index, but can generate too much data regardless the query type. Fine-grained auditing is new opportunity based on attribute granularity. Experiment section highlights limitations of index access methods, when adding new audit policy. As we can see, new audit characteristic definition can significantly degrade performance due to adding new conditions to the query consequencing sequential table data processing.
Model-Based Fault Detection and Identification for Switching Power Converters

We present the analysis, design, and experimental validation of a model-based fault detection and identification (FDI) method for switching power converters using a model-based state estimator approach. The proposed FDI approach is general in that it can be used to detect and identify arbitrary faults in components and sensors in a broad class of switching power converters. The FDI approach is experimentally demonstrated on a nanogrid prototype with a 380-V dc distribution bus. The nanogrid consists of four different switching power converters, including a buck converter, an interleaved boost converter, a single-phase rectifier, and a three-phase inverter. We construct a library of fault signatures for possible component and sensor faults in all four converters. The FDI algorithm successfully achieves fault detection in under 400 $\mu$s and fault identification in under 10 ms for faults in each converter. The proposed FDI approach enables a flexible and scalable solution for improving fault tolerance and awareness in power electronics systems.
A novel caveolin-1/p85α/Rab5/Tiam1/Rac1 signaling axis in tumor cell migration and invasion

The small GTPase Rab5 has been frequently studied in the context of intracellular trafficking, but evidence obtained more recently has implicated Rab5 as a critical regulator of cell adhesion, migration and invasion in both normal and tumor cells. These recent findings showing that Rab5 promotes Rac1 activation and focal adhesion dynamics have highlighted the question as to what the upstream regulators of Rab5 activity might be and how these are connected to cell migration. The efforts to shed light on this issue identified in metastatic cancer cells a novel Caveolin‑1/p85α/Rab5/Tiam1/Rac1 signaling axis relevant to cancer cell migration and invasion. In this addendum, we highlight aspects concerning Rab5 regulation in this context.
A Fast Extension for Sparse Representation on Robust Face Recognition

We extend a recent Sparse Representation-based Classification (SRC) algorithm for face recognition to work on 2D images directly, aiming to reduce the computational complexity whilst still maintaining performance. Our contributions include: (1) a new 2D extension of SRC algorithm; (2) an incremental computing procedure which can reduce the eigen decomposition expense of each 2D-SRC for sequential input data; and (3) extensive numerical studies to validate the proposed methods.
Association Between Hearing Aid Use and Health Care Use and Cost Among Older Adults With Hearing Loss

Importance Hearing loss (HL) is common among older adults and is associated with poorer health and impeded communication. Hearing aids (HAs), while helpful in addressing some of the outcomes of HL, are not covered by Medicare. Objective To determine whether HA use is associated with health care costs and utilization in older adults. Design, Setting, and Participants This retrospective cohort study used nationally representative 2013-2014 Medical Expenditure Panel Survey data to evaluate the use of HAs among 1336 adults aged 65 years or older with HL. An inverse propensity score weighting was applied to adjust for potential selection bias between older adults with and without HAs, all of whom reported having HL. The mean treatment outcomes of HA use on health care utilization and costs were estimated. Exposures Encounter with the US health care system. Main Outcomes and Measures (1) Total health care, Medicare, and out-of-pocket spending; (2) any emergency department (ED), inpatient, and office visit; and (3) number of ED visits, nights in hospital, and office visits. Results Of the 1336 individuals included in the study, 574 (43.0%) were women; mean (SD) age was 77 (7) years. Adults without HAs (n = 734) were less educated, had lower income, and were more likely to be from minority subpopulations. The mean treatment outcomes of using HAs per participant were (1) higher total annual health care spending by $1125 (95% CI, $1114 to $1137) and higher out-of-pocket spending by $325 (95% CI, $322 to $326) but lower Medicare spending by $71 (95% CI, −$81 to −$62); (2) lower probability of any ED visit by 2 percentage points (PPs) (24% vs 26%; 95% CI, −2% to −2%) and lower probability of any hospitalization by 2 PPs (20% vs 22%; 95% CI, −3% to −1%) but higher probability of any office visit by 4 PPs (96% vs 92%; 95% CI, 4% to 4%); and (3) 1.40 more office visits (95% CI, 1.39 to 1.41) but 0.46 (5%) fewer number of hospital nights (95% CI, −0.47 to −0.44), with no association with the number of ED visits, if any (95% CI, 0.01 to 0). Conclusions and Relevance This study demonstrates the beneficial outcomes of use of HAs in reducing the probability of any ED visits and any hospitalizations and in reducing the number of nights in the hospital. Although use of HAs reduced total Medicare costs, it significantly increased total and out-of-pocket health care spending. This information may have implications for Medicare regarding covering HAs for patients with HL.
Efficacy of Propolis on the Denture Stomatitis Treatment in Older Adults: A Multicentric Randomized Trial

Our hypothesis tested the efficacy and safety of a mucoadhesive oral gel formulation of Brazilian propolis extract compared to miconazole oral gel for the treatment of denture stomatitis due to Candida spp. infection in older adults. Forty patients were randomly allocated in a noninferiority clinical trial into two groups. The control group (MIC) received 20 mg/g miconazole oral gel and the study group (PROP) received mucoadhesive formulation containing standardized extract of 2% (20 mg/g) propolis (EPP-AF®) during 14 days. Patients were examined on days 1, 7, and 14. The Newton's score was used to classify the severity of denture stomatitis. The colony forming unity count (CFU/mL) was quantified and identified (CHROMagar Candida®) before and after the treatment. Baseline characteristics did not differ between groups. Both treatments reduced Newton's score (P < 0.0001), indicating a clinical improvement of the symptoms of candidiasis with a clinical cure rate of 70%. The microbiological cure with significant reduction in fungal burden on T14 was 70% in the miconazole group and 25% in the EPP-AF group. The EPP-AF appears to be noninferior to miconazole considering the clinical cure rate and could be recommended as an alternative treatment in older patients.
Estimation of Nonlinear Functionals of Densities With Confidence

This paper introduces a class of k-nearest neighbor (k-NN) estimators called bipartite plug-in (BPI) estimators for estimating integrals of nonlinear functions of a probability density, such as Shannon entropy and Rényi entropy. The density is assumed to be smooth, have bounded support, and be uniformly bounded from below on this set. Unlike previous k-NN estimators of nonlinear density functionals, the proposed estimator uses data-splitting and boundary correction to achieve lower mean square error. Specifically, we assume that T i.i. d. samples Xi ϵ Rd from the density are split into two pieces of cardinality M and N, respectively, with M samples used for computing a k-NN density estimate and the remaining N samples used for empirical estimation of the integral of the density functional. By studying the statistical properties of k-NN balls, explicit rates for the bias and variance of the BPI estimator are derived in terms of the sample size, the dimension of the samples, and the underlying probability distribution. Based on these results, it is possible to specify optimal choice of tuning parameters M/T, k for maximizing the rate of decrease of the mean square error. The resultant optimized BPI estimator converges faster and achieves lower mean squared error than previous k-NN entropy estimators. In addition, a central limit theorem is established for the BPI estimator that allows us to specify tight asymptotic confidence intervals.