Miracle-dz/UniFAR-FTUs huggingface dataset:
Channel Scanning and Access Point Selection Mechanisms for 802.11 Handoff: A Survey

While the cellular technology has been evolving continuously in recent years and client hando↵s remain unnoticed, the 802.11 networks still impose an enormous latency issue once the client device decides to roam between the Access Point (AP). This latency is caused by many factors reckoning on scanning the channels and searching for APs with better signal strength. Once data from all the nearby APs has been collected, the client picks the most suitable AP and tries to connect with it. The AP verifies if it has enough capability to serve the client. It also ensures that the client has the required parameters and supported rates to match with the AP. The AP then processes this request, generates a new Association ID and sends it back to the client, thereby granting access to connect. Throughout this re-association process, the client fails to receive or send any data frames and experiences a lag between leaving the old and associating with a new AP. Originally, 802.11 authentication frames were designed for Wired Equivalent Privacy protocol, but later it was found to be insecure and thus got depreciated. Keeping these security aspects concerning shared key authentication in mind, few additional drafts were introduced by IEEE that concerned many key exchanges between the devices. IEEE 802.11r was introduced in 2008 that permits wireless clients to perform faster hando↵ along with additional data security standards. The key exchange method was v redefined and also the new security negotiation protocol started serving wireless devices with a better approach. This enables a client to set up the Quality of Service state and security on an alternative AP before making a transition which ends up in minimal connectivity losses. Although this was an excellent step towards minimizing the service disruption and channel scanning, failure to remain connected with consecutive suitable APs within the minimum time continued to be a challenge. Di↵erent manufacturers use their custom-built methodology of handling a client hando↵ and hence the latency costs di↵er based on the type of hando↵ scheme deployed on the device. This thesis focuses on the foremost economical researches throughout recent years which targets minimizing the delays involved with channel scanning and AP selection. A wide sort of enhancements, whether it is on a client device or the AP, has been discussed and compared. Some modifications are associated with enhancing channel scan period or using beacons, and probe requests/responses in an e cient manner. Others concentrate on modifying the device hardware configuration and switching between Network Interfaces. Central controllers are a solution to hando↵ delays that may track the status of each device within the network and guide them to provide the appropriate Quality of Service to the end-users.
On the Behaviour of Weighted Permutation Entropy on Fractional Brownian Motion in the Univariate and Multivariate Setting

The estimation of the qualitative behaviour of fractional Brownian motion is an important topic for modelling real-world applications. Permutation entropy is a well-known approach to quantify the complexity of univariate time series in a scalar-valued representation. As an extension often used for outlier detection, weighted permutation entropy takes amplitudes within time series into account. As many real-world problems deal with multivariate time series, these measures need to be extended though. First, we introduce multivariate weighted permutation entropy, which is consistent with standard multivariate extensions of permutation entropy. Second, we investigate the behaviour of weighted permutation entropy on both univariate and multivariate fractional Brownian motion and show revealing results.
Evaluation of Pathogens Isolated from Central Venous Catheters Used for Cardiovascular Interventions

Amac: Bu calismanin amaci kardiyovaskuler girisimler nedeniyle santral venoz kateterizasyon uygulanan hastalarda izole edilen patojenleri degerlendirmektir. Materyal ve Metot: Hastalar, kateter iliskili infeksiyonlarin gelisimi icin gunluk olarak izlendi. Nisan 2017 ile Temmuz 2019 tarihleri arasinda, kateterizasyondan sonra akinti, ates, agri, lenfadenopati ve kasinti gibi infeksiyon semptomlari gosteren hastalar geriye donuk calismaya dahil edildi. Hastalarin kateter tipleri, kateter yerlestirme bolgeleri, toplam kateterizasyon sureleri, kultur sonuclari, patojenlerin antimikrobiyal ilaclara karsi duyarliliklari ve direncleri kaydedildi ve analiz edildi. Bulgular: Cesitli endikasyonlar nedeniyle santral venoz kateterizasyon uygulanan 86 hasta calismaya alindi. Hastalarin ortalama yasi 52,70±17,82 yil idi. Hastalarin %62,79'unda bakteri uremesi mevcuttu. En sik kateter yerlestirme yerleri sag subklavyen ven, sag juguler ven ve sag femoral venlerdi. En sik izole edilen mikroorganizma %25,58 ile S.aureus idi ve onu E. coli (%6,98), S. haemolyticus (%5,81) ve K. pneumonia (%5,81) izlemekte idi. S. aureus'un vankomisin ve linezolide duyarli oldugu tespit edildi. Sonuc: Bu infeksiyonlarin insidansini etkileyen faktorler arasinda kateter yerlestirme bolgesi, kateterizasyon suresi, kateter secimi ve uygulayicilarin becerileri bulunur. Literaturdeki kateterle iliskili infeksiyonlarda izole edilen patojenler ve bunlarin antimikrobiyal ajanlara duyarliligi ve direnci hakkindaki veriler cogunlukla eskidir. Bu konuda daha kapsamli, cok merkezli calismalara ihtiyac vardir.
Comparing Optimization Methods for Deep Learning at the Example of Artistic Style Transfer

Artistic style transfer is an application of deep learning using convolutional neural networks (CNN). It combines the content of one image with the style of another one using so-called perceptual loss functions. More precisely, the training of the network consists in choosing the weights such that the perceptual loss is minimized. Here, we study the impact of the choice of the optimization method on the ﬁnal transformation result. Training an artistic style transfer network with several optimization methods commonly used in deep learning, we obtain signiﬁcantly differing models. In a default parameter setting, we show that Adam, AdaMax, Adam AMSGrad, Nadam, and RM-SProp yield better results than AdaDelta, AdaGrad or RProp, both measured by the perceptual loss function and by visual perception. The results of the last three methods strongly depend on the chosen parameters. With a suitable selection, AdaGrad and AdaDelta can achieve results similar to the versions of Adam or RMSProp.
Robust Task Planning with Uncertain Models

Many autonomous systems execute in a continuous environment with several constraints. These could include limited energy supply, restrictions in the movement or limited physical abilities. To deal with those constraints, recently predictions made by learned models have been incorporated in a new task planning framework, called hybrid planning. Within my PhD thesis, I aim at providing robustness in task planning even when incorporating uncertain models in an environment with constraints.
Political Voice and (Mortgage) Market Participation: Evidence from Minority Disenfranchisement

This paper documents the link between political voice and economic decision-making. Combining the repeal of Section 5 of the Voting Rights Act as a shock to the enfranchisement of black Americans with granular data on the US mortgage market, we document a 14% decline in mortgage origination for black Americans. This is driven by their self-selection out of the mortgage market rather than a change in denial rate. Additionally, we observe a flight of black demand to black lenders, indicating an increase in racial homophily. Our results indicate that disenfranchisement reduces demand directly by increasing uncertainty, violence, and borrowing constraints and indirectly by increasing the threat of rejection.
Csc5160: Combinatorial Optimization and Approximation Algorithms Topic: Theta Function

In communication, we usually encode our messages using the letters in a particular alphabet for transmission in some kind of channels. However, with the presence of noise in the channel, it might be the case when some letters can be confused with others. Assume some pairs of letters are similar in representation, and the noise may flip a letter into another if their representation is similar, but can’t flip those that are “different”. In this case, we want to find a set of messages which are pairwise “different”, such that we can distinguish them even if noise is present.
Understanding the Classification of Data Mining and Web Mining

The amount of data stored in databases is rapidly increasing. This creates the need for new technologies and tools to auto handle and enables humans to manage and analyze large data sets in a smart way to gather useful information. This growing need is generating a new field of research called Knowledge Discovery in Database (KDD) or Data Mining, which has cached researchers' interest in many different fields including database design, statistics, pattern recognition, machine learning, and data visualization. Web Mining is part of data mining technology, which aims to extract interesting and useful hidden patterns and information from web documents and web activities.
The Ranking and Comparison of Extracted Anchor Fragments

It is an immensely challenging task for search engines to generate a suitable snippet, defined as a short description of a web page since the textual content on the Internet is constantly decreasing and being replaced by the hypermedia. This work aims to address the issue of web document summarization and investigate an alternative approach to improve the quality of snippets. Our hypothesis is that the surrounded texts of a link could possibly be related to its target and could, therefore, be used to generate snippets. First, we will describe a pipeline which receives a link as input and retrieves several ranked lists of snippet candidate generated from surrounded texts (anchor fragments) of the links. consequently, we divide this pipeline into three major procedures. The first one finds and mines the text from the web documents. The second procedure tries to enhance the quality of the extracted texts and finally, the last procedure ranks the texts with different methods. Subsequently, we evaluate the results of this pipeline by conducting an online user study, which measures the satisfaction of participants on the results. Eventually, the effectiveness of each ranking method will be assessed based on participants votes. Our findings include that (1) the most effective way of ranking fragments depends on the frequency of the similar fragments existing in different web pages, and (2) combining the fragments which have an identical part has a great impact on improving the quality of the fragments.
Women and Local Government Elections in Turkey: Analysis of Supply and Demand-Side Framework

How do women perform in Turkish local government elections? Existing studies have delved on the subject of participation and representation of women in political activities and the main concern has been to assess the factors responsible for the underrepresentation of women in politics. However, previous studies have largely focused on the representation of women in national legislative assemblies seemingly to assert that political representation of women is confined to national politics and their representation in local governments is largely overlooked. This paper seeks to fill the lacuna in the literature by focusing on participation and representation of women in local government in Turkey. By using the supply and demand-side framework, we seek to understand factors that have contributed to the low representation of women in local governments in Turkey.
Alteration of brain structural organization after sepsis with Fatigue - a structural brain network analysis

In our recent cross-sectional investigation, we found in sepsis survivors with persistent cognitive impairment a high number of patients who still suffer from Fatigue. This fi nding is of importance because Fatigue is highlighted as an associated long-term sequela after sepsis and therefore these patients require an appropriate rehabilitation therapy. The aim of this study was to verify whether sepsis survivors with both cognitive impairment and Fatigue show any alteration in brain structure. 19 survivors of severe sepsis (longer than 2 years post sepsis) with persistent cognitive defi cits ascertained with a battery of neuropsychological tests with cognitive and motor Fatigue symptoms (according to two German Fatigue scales) were investigated with a high-resolution. T1 weighted image of the brain at a 3.0 Tesla MRI scanner. The Voxel-based morphometry (VBM) was performed using VBM8 toolbox. 19 ageand sex-matched healthy control subjects were also scanned with MRI. VBM analysis revealed signifi cant gray matter volume reduction in sepsis survivors particularly in the lateral frontal operculum and anterior cingulate cortex. These regions are part of the cingulo-opercular network which maintains alertness. Gray matter volume loss of the orbitofrontal cortex is functionally associated with Fatigue. These fi ndings emphasize that networks of structural brain organization can be altered with corresponding clinical symptoms and neuropsychological defi cits after sepsis. Research Article Alteration of brain structural organization after sepsis with Fatigue a structural brain network analysis Gundula Seidel1,2*, Alexander Ritter1, Florian Bähr1,3 and Farsin Hamzei1,2 1Section of Neurological Rehabilitation, Hans Berger Department of Neurology, Jena University Hospital, Germany 2Department of Neurology, Moritz Klinik Bad Klosterlausnitz, Germany 3Department of Sports Medicine and Health Promotion, Friedrich Schiller University Jena, Germany Received: 24 April, 2021 Accepted: 04 June, 2021 Published: 07 June, 2021 *Corresponding author: Gundula Seidel, Section of Neurological Rehabilitation, Hans Berger Department of Neurology, Jena University Hospital, Germany, E-mail: https://www.peertechzpublications. com
Disagreement and Discretionary Monetary Policy

This paper identi es a new coordination motive endogenously induced by a central banks lack of commitment in the presence of information imperfection. We show that when di¤erentially informed economic agents disagree about central banks ination incentives, discretion in monetary policy-making induces agents to coordinate by forecasting the forecasts of othersin order to forecast central banks policy actions. In particular, the induced coordination mechanism compels the central bank to choose monetary policy that responds to uctuations in the average belief about its incentive. As a result, discretion has the potential to vastly increase uctuations in employment and ination, especially when the disagreement among agents is low. More broadly, our paper makes an argument for the inclusion of information diversity among agents in monetary policy discussions and in the characterization of the ination dynamics. Marvin Goodfriend passed away in December 2019. He was our colleague, mentor, and friend. We dedicate this paper to his memory and his contributions to the eld of economics. Goodfriend was a faculty member of the Tepper School of Business at the Carnegie Mellon University and also had a research a¢ liation with NBER. Pierre Jinghong Liang is from the Tepper School of Business at the Carnegie Mellon University and also has a research a¢ liation with Shanghai Advanced Institute of Finance and China Academy of Financial Research at Shanghai Jiaotong University. Gaoqing Zhang is from the Carlson School of Management at the University of Minnesota. Pierre Liang gratefully acknowledges the Deans Summer Research funding of the Tepper School. We thank John McDermott, Ariel ZetlinJones and participants at Chicago-Minnesota Theory Conference for valuable comments. Please e-mail comments or suggestions to liangj@andrew.cmu. edu, and zhangg@umn.edu.
PYTHON BASED MACHINE LEARNING FOR PROFILE MATCHING

- Information retrieval from different social sites has to be done for various Inter-social activities & functionalities for that matching user profiles has to be done. User creates same profiles under different sites. (for personal use, for work etc.,). The current work explores the different algorithms foe similarity measures for classifications, presenting new analysis. Different data sets are used to check the value and also classification. A model is built using Decision tree algorithm in order to check the similarity measures between two profiles. Experiments on real data sets are used to compare methods and their changes to the similarity-based learning.
Intervention of hydrogen on memory damage induced by chronic hypoxia-hypercapnia in rats

AIM: To investigate the effects of hydrogen on the memory damage caused by chronic hypoxia-hypercapnia in rats.METHODS: Twenty-four SD rats trained by eight-arm radial maze test were randomly divided into 3 groups:normal control group(NC),hypoxia-hypercapnia+saline group(MS) and hypoxia-hypercapnia+ hydrogen group(MH). The rats in the latter 2 groups were placed in a closed cabin for 8 h/day,6 days/week and lasted for 4 weeks,in which O2 was 9%-11% and CO2 was 5%-6%. In every time after the animals were out of the cabin,the MS rats were intraperitoneally injected with saline(5 mL/kg) and the MH rats were intraperitoneally injected with hydrogen solution at the same dose.The learning and memory function,the activity of superoxide dismutase(SOD),the content of malondialdehyde(MDA) and 8-hydroxydeoxyguanosine(8-OHdG) were examined after the cabin training.The ultramicrostructures of hippocampus were also observed.RESULTS: (1) Compared with NC group,the number of working memory errors,the total errors,the content of hippocampus 8-OHdG and serum MDA in MS and MH groups were higher and the activity of serum SOD was lower(P0.05). The hippocampus structure was destroyed and some degree of edema and more apoptosis in the neurons were obserued in MS group and MH group. (2) Compared with MS group,the number of working memory errors(WME),the total errors,the content of hippocampus 8-OHdG and serum MDA were lower and the activity of serum SOD was higher in MH group(P0.05). In MH group,the morphology of hippocampus structures kept nearly normal arrangement and the only mild edema and fewer apoptosis in the neurons were found.CONCLUSION: Hydrogen may attenuate chronic hypoxia-hypercapnia-induced memory damage in rats by inhibiting apoptosis of the neurons and decreasing detrimental free radicals reaction.
Deliverable 4 . 1 Baseline components of speech activity detection , acoustic / speech event classification and distant-talking ASR for the DICIT scenario

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DETECTION OF CATARACT BY STATISTICAL FEATURES AND CLASSIFICATION

------------------------------------------------------------------------***---------------------------------------------------------------------- Abstract-Cataract is the major cause of blindness in the world and the most prevalent ocular disease. Increased risk of cataract development is associated with UV exposure, steroid use, diabetes, and smoking. This process cannot be reversed, but a healthy lifestyle may slow the progression. Earlier diagnosis of cataract will prevent vision loss. In this paper a new method has been proposed to diagnosis of cataract using statistical features and its severity has been classified using K-means and ANFIS classifier.
Simulating sedimentary burial cycles – Part 1: Investigating the role of apatite fission track annealing kinetics using synthetic data

Abstract. Age dispersion is a common feature of apatite fission track (AFT) and apatite (U–Th) / He (AHe) thermochronological data, and it can be attributed to multiple factors. One underappreciated and underreported cause for dispersion is variability in apatite composition and its influence on thermal annealing of fission tracks. Using synthetic data we investigate how multikinetic AFT annealing behaviour, defined using the rmr0 parameter, can be exploited to recover more accurate, higher-resolution thermal histories than are possible using conventional interpretation and modelling approaches. Our forward model simulation spans a 2 Gyr time interval with two separate heating and cooling cycles and was used to generate synthetic AFT and AHe data for three different apatite populations with significantly different annealing kinetics. The synthetic data were then used as input for inverse modelling in the Bayesian QTQt software to recover thermal-history information under various scenarios. Results show that essential features of the dual peak thermal history are captured using the multikinetic AFT data alone, with or without imposed constraints. Best results are achieved when the multikinetic AFT data are combined with the AHe data and geologic constraint boxes are included. In contrast, a more conventional monokinetic interpretation that ignores multikinetic AFT behaviour reproduces all the input data but yields incorrect thermal-history solutions. Under these conditions, incorporation of constraints can be misleading and fail to improve model results. In general, a close fit between observed and modelled parameters is no guarantee of a robust thermal-history solution if data are incorrectly interpreted. For the case of overdispersed AFT data, it is strongly recommended that elemental data be acquired to investigate if multikinetic annealing is the cause of the AFT apparent age scatter. Elemental analyses can also be similarly useful for broadly assessing AHe data. A future companion paper (Issler et al., 2021) will explore multikinetic AFT methodology and application to detrital apatite samples from Yukon, Canada.
Individual similarities and regional differences: the impact of 2015 refugee crisis on Europeans’ attitudes toward immigration

ABSTRACT Whereas the extant literature has found similarities in attitudes toward immigration to Europe, there is less attention on European East–West attitudinal differences on immigration. We account for attitude variations brought about by the 2015 Europe's refugee crisis in two geopolitical regions of the continent, namely the EU East and the EU west. We found that, the 2015 refugee crisis sparked different attitudinal reaction between these regions related to immigration, with trust in domestic and EU institutions predicting much of attitudes toward migration. We tested our hypotheses with data from the 7th and 8th rounds of the European Social Survey.