Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Different Navigation Prediction Techniques

-Discovering web navigation patterns plays an important role in web mining which is used for prediction and management of website efficiently. As we all know that web site structure is always changed, many Navigation Prediction Techniques need not only consider the frequency of click behavior but also web site structure to mine web navigation patterns for navigation prediction, dynamic mining approach is also based on the previous mining results and formed new patterns just from the modifying some part of the web data. We had compared Different Navigation Prediction Techniques based on criteria’s like data structure used for intermediate storage and mining, original database used for mining, re-mining is done to track changes in the web structure, pattern tree construction for improving prediction phase and Technique used for navigation prediction and we found that Mining Web Navigation Patterns with Dynamic Thresholds for Navigation Prediction is the best from that technologies Keywords— Web mining, Navigation Prediction
FuzzE: Fuzzy Fairness Evaluation of Offensive Language Classifiers on African-American English

Hate speech and offensive language are rampant on social media. Machine learning has provided a way to moderate foul language at scale. However, much of the current research focuses on overall performance. Models may perform poorly on text written in a minority dialectal language. For instance, a hate speech classifier may produce more false positives on tweets written in African-American Vernacular English (AAVE). To measure these problems, we need text written in both AAVE and Standard American English (SAE). Unfortunately, it is challenging to curate data for all linguistic styles in a timely manner—especially when we are constrained to specific problems, social media platforms, or by limited resources. In this paper, we answer the question, “How can we evaluate the performance of classifiers across minority dialectal languages when they are not present within a particular dataset? ” Specifically, we propose an automated fairness fuzzing tool called FuzzE to quantify the fairness of text classifiers applied to AAVE text using a dataset that only contains text written in SAE. Overall, we find that the fairness estimates returned by our technique moderately correlates with the use of real ground-truth AAVE text. Warning: Offensive language is displayed in this manuscript.
Dynamic resource allocation and management in virtual networks and Clouds. (Gestion et allocation dynamique des ressources dans les réseaux virtuels et Clouds)

Cloud computing is a promising technology enabling IT resources reservation and utilization on a pay-as-you-go manner. In addition to the traditional computing resources, cloud tenants expect compete networking of their dedicated resources to easily deploy network functions and services. They need to manage an entire Virtual Network (VN) or infrastructure. Thus, Cloud providers should deploy dynamic and adaptive resource provisioning solutions to allocate virtual networks that reflect the time-varying needs of Cloud-hosted applications. Prior work on virtual network resource provisioning only focused on the problem of mapping the virtual nodes and links composing a virtual network request to the substrate network nodes and paths, known as the Virtual network embedding (VNE) problem. Little attention was paid to the resource management of the allocated resources to continuously meet the varying demands of embedded virtual networks and to ensure efficient substrate resource utilization. The aim of this thesis is to enable dynamic and preventive virtual network resources provisioning to deal with demand fluctuation during the virtual network lifetime, and to enhance the substrate resources usage. To reach these goals, the thesis proposes adaptive resource allocation algorithms for evolving virtual network requests. We adress the extension of an embedded virtual node requiring more resources and consider the substrate network profitability. We also deal with the bandwidth demand variation in embedded virtual links. We first provide a heuristic algorithm to deal with virtual nodes demand fluctuation. The work is extended by designing a preventive re-configuration scheme to enhance substrate network profitability. Finally, a distributed, local-view and parallel framework was devised to handle embedded virtual links bandwidth fluctuations. The approach is composed of a controller and three algorithms running in each substrate node in a distributed and parallel manner. The framework is based on the self-stabilization approach, and can manage various forms of bandwidth demand variations simultaneously
Adaptive cubic regularization methods with dynamic inexact Hessian information and applications to finite-sum minimization

We consider the adaptive regularization with cubics approach for solving nonconvex optimization problems and propose a new variant based on inexact Hessian information chosen dynamically. The theoretical analysis of the proposed procedure is given. The key property of ARC framework, constituted by optimal worst-case function/derivative evaluation bounds for first- and second-order critical point, is guaranteed. Application to large-scale finite-sum minimization based on subsampled Hessian is discussed and analyzed in both a deterministic and probabilistic manner, and equipped with numerical experiments on synthetic and real datasets.
Desirable Features of a Successful Entrepreneur: The Perspective of Family and Non-Family Firms

<span style="font-family: TimesNewRomanPSMT; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;">Pożądane cechy i umiejętności dobrego przedsiębiorcy mogą się różnić w zależności od organizacji,<span style="font-family: TimesNewRomanPSMT; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;"> w którą jest zaangażowany. W przedsiębiorstwach rodzinnych, w których spotykają się co najmniej dwa systemy: rodzina i przedsiębiorstwo – pożądane cechy przedsiębiorcy mogą być zupełnie inne niż w przypadku<span style="font-family: TimesNewRomanPSMT; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;"> pozostałych przedsiębiorstw. Głównym celem artykułu było ustalenie, które z tych cech są lepiej postrzegane<span style="font-family: TimesNewRomanPSMT; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;"> przez firmy rodzinne, a które – przez firmy nierodzinne. Wyniki pokazują, że dla przedsiębiorców rodzinnych<span style="font-family: TimesNewRomanPSMT; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;"> cechy związane z utrzymaniem długoterminowego przetrwania są ważniejsze niż dla firm nierodzinnych. <span style="font-family: TimesNewRomanPSMT; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;"> Co więcej, umiejętności, które mogą być przydatne dla rozwoju kapitału społecznego (np. umiejętności<span style="font-family: TimesNewRomanPSMT; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;"> negocjacyjne i tworzenie relacji biznesowych), są ważniejsze w firmach nierodzinnych. Ocena wyników<span style="font-family: TimesNewRomanPSMT; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;"> uzyskanych w tym badaniu wskazuje, że w celu utrzymania przewagi konkurencyjnej firmy rodzinne nie<span style="font-family: TimesNewRomanPSMT; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;"> powinny bagatelizować roli umiejętności społecznych i powinny być bardziej otwarte na podejmowanie<span style="font-family: TimesNewRomanPSMT; font-size: 9pt; color: #231f20; font-style: normal; font-variant: normal;"> ryzyka, ponieważ z czasem może się to okazać jedyną drogą do zapewnienia im przetrwania na rynku. </span></span></span></span></span></span></span></span></span></span>
Clustering-based Allocation of Virtualized Functions for Service Function Chaining

Network Function Virtualization (NFV) has been widely spread for software-level network configuration. Such functionalities interact each other to achieve data-flow processing, named as Service Function Chaining (SFC). In SFC, each execution unit, named as Virtualized Network Function (VNF), has dependencies with others. Such configuration is realized by allocating each VNF to a VM. Conventional approaches mainly focus on how to allocate each VNF to a VM, or how to select a VNF and they are resolved separately. In this paper, we propose a VNF clustering algorithm, called Clustering for Minimizing Worst Schedule Length for VNF (CMWSL-VNF) to resolve both VNF allocation and VNF selection simultaneously. CMWSL-VNF can greatly reduce the data communication latency and maintains the degree of parallelism by the clustering algorithm. Experimental results show that CMWSL-VNF can utilize vCPUs to minimize the response time.
The New View On Monetary Policy : The New Consensus And Its Post-Keynesian Critique

This paper seeks to look at the underlying framework of the New Consensus models, providing a postKeynesian critique. In the light of this critique, the model is reformulated, with its basic structure intact, but with alternate post-Keynesian specifications of the Phillips curve being considered. It is shown that such modifications, either allow a long run trade-off between the rate of inflation and the level of output, the rate of capacity utilization and, therefore, unemployment, or, in our preferred specification, changes in output and capacity have no implications for inflation over a large range of capacity utilization
A Study of Distinctive tools to hack wireless network

Wireless security is the prevention of illegal access or destruction to computer systems that are using wireless networks. The most common types of wireless network security are wired Equivalent Privacy (WEP) and Wi-Fi Protected Access (WPA). Wireless accessibility is being deployed increasingly in office and public environments. The Wireless Encryption Protocol is a process of securing IEEE 802.11 wireless internet connections. The main building blocks of WEP are present, but counteractive measures have been added to address the security problems. In this paper, I discuss the tools implied to hack a wireless network and the weakness of WEP key in the wireless network due to which these are hacked. The attacks in Wi-Fi network are passive and more critical to the end users like the Man-in-middle attack, replay attack and hello flood attack.
PaintRL: Coverage Path Planning for Industrial Spray Painting with Reinforcement Learning

We present PaintRL, a framework that enables research on optimizing industrial spray painting for arbitrary objects with reinforcement learning. PaintRL implements a toolkit to simulate and visualize spray painting based on the physics engine PyBullet. By means of this toolkit, we train neural networks to predict coverage paths and evaluate the results on two objects: a quadratic sheet and a real car door. Our initial results show that the generated coverage path of the car door performs on a par with a manually implemented zigzag baseline. To allow sim2real transfer for non-resettable tasks like spray painting, we replace paint by light using projection mapping. This approach opens up new possibilities to visualize the results from simulation, collect human demonstrations and capture real-world images. PaintRL is part of our endeavor to utilize the recent advances in deep reinforcement learning for economically important industrial tasks.
CYTOGENETIC STUDY OF CMS IN RAPESEED GENOTYPES AT THE NOVI SAD BREEDING CENTER

Given the commercial importance of developing rapeseed hybrids, we have in our breeding program began working on the detection of CMS sources and the incorporation of this trait into genotypes with desirable genes for other agronomically important traits. The expression of CMS into a new genetic environment was accompanied by visual assessment of male sterility in plants grown in the field. Further, microscopic inspection of the stamen was carried out to assess the anther development level and presence of pollen in male-fertile and male-sterile flowers. Pollen viability was assessed by the staining method, while the progression of meiosis/microsporogenesis was assessed by the acetocarmine method (a modified version used in sunflower). When assessing male sterility in plants that are potential CMS sources, it is necessary to examine the stamens microscopically, because visual assessment in the field is inaccurate. In male-sterile flowers, anthers are most often poorly developed, with no pollen, although cases have been reported in which small amounts of nonviable pollen were found. Meiosis progressed normally. The following phases were observed: pachyten, diakinesis, metaphase I, anaphase I, anaphase II, telophase II. Differences in the advancement of microsporogenesis between the male-fertile and male-sterile flowers were observed in the phases following the tetrads. In the male-sterile flowers, mononuclear microspores were of normal of shape and size, while irregularities (such as deformed microspores or nonviable pollen grains of irregular shape and size) were observed after this phase.
On instanton contributions to anomalous dimensions in N = 4 supersymmetric Yang – Mills theory

Instanton contributions to the anomalous dimensions of gauge-invariant composite operators in the N =4 supersymmetric SU(N) Yang–Mills theory are studied in the one-instanton sector. Independent sets of scalar operators of bare dimension ∆0 ≤ 5 are constructed in all the allowed representations of the SU(4) R-symmetry group and their two-point functions are computed in the semiclassical approximation. Analysing the moduli space integrals the sectors in which the scaling dimensions receive non-perturbative contributions are identified. The requirement that the integrations over the fermionic collective coordinates which arise in the instanton background are saturated leads to non-renormalisation properties for a large class of operators. Instanton-induced corrections to the scaling dimensions are found only for dimension 4 SU(4) singlets and for dimension 5 operators in the 6 of SU(4). In many cases the non-renormalisation results are argued to be specific to operators of small dimension, but for some special sectors it is shown that they are valid for arbitrary dimension. Comments are also made on the implications of the results on the form of the instanton contributions to the dilation operator of the theory and on the possibility of realising its action on the instanton moduli space.
Harmonic Resonance Reduction using Hybrid Active Filter with Fuzzy Logic Controller in Industrial Power Systems

This paper proposes a hybrid active filter for damping harmonic resonance and reducing harmonic distortion in industrial power systems. The change in load and variation in parameters causes harmonic distortions which are reduced to a considerable level by operating hybrid filter as variable harmonic conductance in accordance with voltage total harmonic distortion. The hybrid filter consists of an active filter and a seventh tuned passive filter connected in series. Therefore the dc voltage and kVA rating are reduced noticeably in comparison with the pure shunt active filter. The simulation study for the proposed method is carried out in Matlab/Simulink software which validates the efficiency. This paper also considers the filtering performances on line resistance, line impedance, capacitive filters and voltage unbalance.
Resistance coefficients for compound channels

For most natural rivers and some artificial channels, their cross sections consist of subsections of different cross sectional shapes with overbank floodplains, defined as compound channels. Besides, the wall roughness of the channels usually changes along the wetted perimeter. It can be found that the way one divides the cross section into subsections would change the sub-cross sectional areas and the perimeters of the main channel and each side channel and would result in different overall roughness of the compound channels. This study presents a set of equations derived based on different assumptions, including those have been proposed previously, to estimate the overall compound composite channel resistance. To know how many of them are theoretically appropriate, in this study variation of Manning’s n over depth is evaluated for a series of hypothetical compound channels with different shapes based on two types of subarea division lines. The results of evaluation provide usefid information for hydraulic engineers dealing with velocity and discharge of open charnels.
Early and Robust Malware Detection in Enterprise Networks

Behavioral malware detectors, by using statistical methods, promise to expose previously unknown malware and are an important security primitive. However, even the best behavioral detectors suffer from high false positives and negatives. In this paper, we address the challenge of aggregating weak per-device behavioral detectors (local detectors or LDs) in noisy communities (i.e., ones that produce alerts at unpredictable rates) into an accurate and robust global anomaly detector (GD). Our system – Shape GD – combines two insights: Structural: actions such as visiting a website (waterhole attack) or membership in a shared email thread (phishing attack) by nodes correlate well with malware spread, and create dynamic neighborhoods of nodes that were exposed to the same attack vector; and Statistical: feature vectors corresponding to true and false positives of local detectors have markedly different conditional distributions – i.e. their shapes differ. We use neighborhoods to amplify the transient low-dimensional structure that is latent in high-dimensional feature vectors – but neighborhoods vary unpredictably, and we use shape to extract robust neighborhood-level features that identify infected neighborhoods. Unlike prior works that aggregate local detectors’ alert bitstreams or cluster the feature vectors, Shape GD analyzes the feature vectors that led to local alerts (alert-FVs) to separate true and false positives. Shape GD first filters these alert-FVs into neighborhoods and efficiently maps a neighborhood’s alert-FVs’ statistical shapes into a scalar score (‘ShapeScore’). Shape GD then acts as a neighborhood level anomaly detector – training on benign program traces (e.g., from developers’ test inputs) to learn the ShapeScore of false positive neighborhoods, and classifying neighborhoods with anomalous ShapeScores as malicious. We evaluate Shape GD by emulating a large community of Windows systems – using system call traces from a few thousand malware and benign applications and simulating a phishing attack in a corporate email network and a waterhole attack through a popular website. In both these scenarios, we show that Shape GD detects malware early (∼100 infected nodes in a ∼100K node system for waterhole and ∼10 of 1000 for phishing) and robustly (with ∼100% global TP and ∼1% global FP rates).
CALL Syllabus Integration through ICT-Mediated Tasks

The present article addresses the integration into the syllabus of Computer Assisted Language Learning (CALL), and particularly of Information and Communication Technologies (ICT), as a measure to achieve full normalization. After reviewing distinct phases in the history of CALL, we briefly describe a model of an ICT-task within a Content and Languate Integrated Learning (CLIL) framework. The task is conceptualized here as a means for syllabus organization into which the new technologies are naturally integrated.
A Character-Based Model for Pragmatic Caption Generation

Following the work of ([14]) and ([11]), we implement a pragmatic image captioning system, which generates informative captions in the context of distractor regions or images. We extend previous work by making use of a character LSTM in our neural model, which allows for improved pragmatic captioning. We use Visual Genome for data, which allows us to obtain captions for different regions in a single image, for regions which are similar. Qualitatively, we found that, in addition to describing a target image with less ambiguity in context with another image, the pragmatic captions often offered a more accurate, longer description of the target image than just the literal caption.
Scalable High-order Methods for Multi-Scale Problems: Analysis, Algorithms and Application

Abstract : It is anticipated that in future generations of massively parallel computer systems a significant portion of processors may suffer from hardware or software faults rendering large-scale computations useless. In this project, the PI and his students address this problem from the algorithmic side, proposing resilient frameworks that can recover and continue the solution with gappy fields from such faults irrespective of their fault origin. In addition to its robustness and resilience, the new framework generalizes previous multiscale and multifidelity approaches in a unified parallel computational framework.
1 IN VITRO POLLEN SELECTION FOR HEAT-TOLERANCE IN LILIES

Heat-tolerance is an important character for lily bulb and flower production under subtropical and tropical conditions. Since a gametophytic-sporophytic genetic overlap has been demonstrated in many plant species, pollen selection at high temperatures might be an efficient method to achieve heattolerance. An in vitro pollen germination assay was performed with a range of lily genotypes at various temperatures (20 to 35°C) to determine the differences in pollen germination and pollen tube growth. At 35°C differences in pollen tube length and percentage of pollen germination were found among accessions. Accessions in which heat-tolerance was expected, i.e. wild types of L. formosanum, L. neilgherense and L. longiflorum , gave the longest pollen tubes at 35°C. An in vitro pollination system was used to select heat-tolerant seedlings within L. longiflorum by pollinating at 25, 30 and 35°C. The preliminary results are discussed.
Effect of Frying on Quality Characteristics of Chicken Meat Samosas

Present study was undertaken to assess the effect of deep fat frying on quality characteristics of chicken meat samosas. The formulation and processing conditions for preparation of chicken meat samosas were standardized. A total of three types of samosa were prepared by using various frying methods as deep fat frying (T1, 185oC for 6 min), flash frying (T2, 185oC for 2 min) and flash frying followed by deep fat frying (T3, 185oC for 5 min). The developed products along with raw samosas (C) were studied for various physico-chemical, proximate parameters, instrumental colour profile and sensory analysis. T1 and T3 products were compared for sensory attributes. The pH of T3 samples was noted significantly (P<0.05) lower than T1, T2 and raw samosa. T3 samosa was recorded with highest fat percentage and calorific value. Protein content of T1 and T2 were comparable and was significantly (P<0.05) higher than T3. The T1 samples were noted with significant (P<0.05) higher flavour and overall acceptability attributes as compared to T3 samples. Thus, it can be concluded that samosa cooked by frying in refined soybean oil at 185oC for 6 minutes had better sensory attributes with good nutritive value.