Miracle-dz/UniFAR-FTUs huggingface dataset:
Study of distortion detection and enhancement methods for fingerprint images

Image quality degradation and its enhancement is widely studied recently in many research articles in order to deliver best recognition accuracy in presence of poor quality or distorted fingerprinting images as input to fingerprint recognition methods. The distorted or less quality fingerprint images may have the missing and specious features, which may degrade the recognition performance of entire system. Hence it is required for fingerprint recognition system to detect the distorted fingerprint images and then enhance its quality automatically before going to actual recognition functions. The main cause for the false non-match in fingerprint recognition frameworks is fingerprint images elastic distortion. Such research challenge is impacting on complete applications based on fingerprint systems. The scope this paper is limited to presenting the survey on different methods of distortion or poor quality detection in images as well as different methods of image quality enhancement. The goal of this paper is present the complete analysis and review of existing methods presented so far for distortion detection and its quality improvement for further roadmap in this domain. We presented the novel approach for efficient fingerprint distortion detection and mitigation design and framework. The outcome of this paper is the research gap and issues to solve in future works of method designed in this paper.
Cloud Computing - European Perspectives on impacts and potentials of Cloud Computing and Social Network Sites (STOA Cloud Computing Del.1)

Deliverable No. 1 of the STOA Project "Potential and Impacts of Cloud Computing Services and Social Network Sites" This document is the result of the consultation phase of the STOA-project “Potential and Impacts of Cloud Computing Services and Social Network Sites”. It addresses in the first place cloud computing and furthermore social network sites. While Cloud computing (CC) has broad implications for all areas of society and business applications are perhaps crucial for its sustained breakthrough, social network sites (SNS) have their main impact on relationships between private citizens or private citizens and businesses. Beside the impact on the IT industry itself, the development of both is also seen as pivotal for the overall competitiveness of the European economy and society. However, both also pose a number of challenges for enterprises as well as for private citizens. There could be increasing virtualisation of the processing of personal and other sensitive data that is transmitted and stored by commercial providers on servers situated in a location unknown to the costumer. Given these challenges, it is not clear whether both and in particular cloud computing will meet its potential and the high expectations connected to it. Therefore the goal of the project is to analyse this blurry situation and to assess potentials as well as positive and negative impacts for citizens, business and public authorities from a European perspective. This interim report summarises the results of the first project phase, which lasted from April 15th to June 15th 2012. The main objective of this first project phase was the development of a detailed plan for the next four phases of the project. A preparatory meeting, held in May 2012, and several telephone conferences during the consultation phase with the project partners were very instrumental in discussing and prioritising research themes and issues. The report itself consists of two parts. The main part presents an introductory overview of the debates on Cloud Computing Services and Social Network Sites and their potentials and impacts for the European society as a whole. Against this background, the main research perspectives of the project are discussed in detail. Finally, the project’s research questions are presented. The annex describes the project plan, gives an overview of the project schedule and the deliverables. An important element of the whole project is the involvement of those MEPs who are particularly interested in the issue of Cloud Computing and Social Network Sites. We are convinced that taking the perspective of these representatives into account will help to generate recommendations that are considered useful by European decision-makers and practitioners.
Building Maximum Entropy Text Classifier Using Semi-supervised Learning

Over the recent years, text classification has become one of the key techniques for organizing information. Since hand-coding text classifiers is impractical and hand-labeling text is time and labor consuming, it is preferable to learn classifiers from a small amount of labeled examples and a large example of unlabeled data. In many cases, such as online information retrieval or database applications, such unlabeled data are easily and abundantly available. Although a lot of this kind of learning algorithms have been designed, most of them rely on certain assumptions, which are dependent on specific datasets. Consequently, the lack of generality makes these algorithms unstable across different datasets. Therefore, we favor an algorithm with as little dependence on such assumptions or as weak assumption as possible. The maximum entropy models (MaxEnt) offers a generic framework meeting this requirement. Built upon a set of features which is equivalent to undirected graphical models, it provides a natural leverage of feature selection. Most importantly, the only assumption made by MaxEnt is that the average feature values on labeled data give a reasonable (not too deviated) estimation of those values on both labeled and unlabeled data. This is a very weak statistical assumption, underpinning the generality of MaxEnt. Even if the assumption is not strictly satisfied in some situations, theoretical bounds are derived on the generalization error. Similar to soft-max regression, MaxEnt also employs a straightforward mechanism for multi-class classification. With its standard form equivalent to maximum likelihood estimation, there are numerous smoothing approaches proposed to overcome overfitting. Several algorithms for solving this convex optimization problem are also proposed, with different performance and constraints. The main focus of the project is how to incorporate unlabeled data into MaxEnt. As the standard MaxEnt does not perform satisfactorily, side information is considered to be added to MaxEnt, in forms of minimal spanning tree, k-nearest neighbor, multi-representation of examples, etc. Our initial experimental result suggests that MaxEnt with side information is a promising tool. Other promising research areas under this framework are also pointed out in this report, after a comprehensive survey on both learning with unlabeled data and MaxEnt.
İlköğretim İkinci Kademedeki (6–7. Sınıf) Öğretmen ve Öğrencilerin Bitişik Eğik Yazıya İlişkin Görüşleri Doi: 10.14686/BUEFAD.2015USOSOzelsayi13216

Bu arastirmanin amaci ilkogretim II. kademede ki ogretmen ve ogrencilerin bitisik egik yaziya iliskin goruslerini ve bitisik egik yazi yazma basarilarini ortaya koymaktir. Arastirmanin evrenini Hatay ili Antakya merkez ilcesinde bulunan ozel ve resmi ilkogretim okullarinda ogrenim gormekte olan 6. ve 7. sinif ogrencileri ve bu okullarda gorev yapan brans ogretmenleri olusturmaktadir. Arastirmanin ornekleminde 60 ogretmen ve 300 ogrenci yer almistir. Ozel okullarda evrenin tamami kullanilirken resmi okullarda yansiz kume ornekleme yontemi ile secilen uc resmi okul belirlenmistir. Arastirmada ogretmen ve ogrencilerin bitisik egik yazi uygulamalarina iliskin gorusleri ile bitisik egik yazi yazma basarilari arastirmaci tarafindan gelistirilen Ogretmen Anket Formu, Ogretmen Gorusme Formu, Ogrenci Anket Formu, Bitisik Egik Yazi Puanlama Anahtari ve Dikte Metni kullanilarak degerlendirilmistir. Ogretmenlerle yapilan gorusme sonuclarina gore brans ogretmenlerinin tamamina yakini bitisik egik yaziyi yeterince bilmedigi icin ders icinde ve gunluk hayatta dik temel yaziyi kullandiklari tespit edilmistir. Ogrencilerin ise okunakli yazamadiklari icin bitisik egik yaziyi kullanamadiklari saptanmistir. Ayrica sosyal hayatta dik temel yazinin kullanilmasinin bitisik egik yaziya gecisi guclestirdigi belirlenmistir. Arastirmada 5’li dereceli puanlama anahtarina gore yapilan puanlamada brans ogretmenlerinin bitisik egik yazi yazmadaki basari ortalamalari 2.08ile basarisiz, ilkogretim 6 ve 7. sinif ogrencilerinin basari ortalamasi 2.70 ile orta duzeyde bulunmustur. Uygulanan anket formu sonuclarina gore ilkogretim brans ogretmenlerinin bitisik egik yaziya iliskin goruslerinde cinsiyete, kideme ve mezun olunan bolume dayali bir farklilik gorulmemistir. Ancak okul turune gore incelendiginde ozel okullar lehine bir farklilik oldugu gorulmektedir. Ilkogretim 6-7.sinif ogrencilerinin bitisik egik yaziya iliskin gorusleri incelendiginde 6. siniflar lehine farklilik ortaya cikmistir. Ogrenim gorulen okul turune gore yapilan incelemede resmi okullar lehine anlamli bir farklilik tespit edilmistir.
Ranvier nodes impedance match with internodal transmission lines of myelinated axons

Most myelinated axon models are not concerned with internodal segments delay. Distributed effects could be thought as the cause of these delays. In this paper we use a myelinated axon model which takes into account both the distributed nature of the internodal segment and the loading effect of Ranvier nodes. Impedance match of Ranvier nodes is researched. We provide a detailed frequency domain analysis of axon behavior within the context of our model. Results show that Ranvier nodes are roughly matched with internodal segments.
Contrastive Connectors in English and Chinese: A Corpus-Based Study

This study examines the features of contrastive connectors in modern British English by employing corpus evidence and discourse analysis. It aims to find out the total number and frequency of these contrastive connectors in modern BrE evidenced in the BNC with a focus on four genres, the genre-related usage of eleven high-frequency contrastive connectors, and detailed usage of HOWEVER. It also compares the overall frequency of contrastive connectors in the four genres of BrE and AmE, and the usage of contrastive connectors in BrE and Chinese, as evidenced in large corpora. Altogether about 68 contrastive connectors in the BNC (containing modern BrE) and 57 in the CCL corpus (containing modern Chinese) are pinpointed. In the BNC, but is most frequent, covering more than half of the total usage of contrastive connectors. In the CCL, 但 dàn (but) is most frequent, covering nearly one fifth of their total usage. In both corpora, 20 most frequent members cover about 95% of all the usage of contrastive connectors. Contrastive connectors are significantly more frequent in the BNC (BrE) than in the COCA (AmE), and so are Chinese contrastive connectors in Taiwan than in mainland China, but with greater variation. About 1.1 times as many contrastive connectors are used in spoken English as in written English, but twice as many such connectors are used in written Chinese as in conversation. The usage of contrastive connectors co-varies with genre. In English such connectors are generally used alone. Even when they occasionally form complex units, contrastive conjunctions still lead and overshadow contrastive adverbials. Concessive clauses in English are flexible in clause order. Contrastive connectors in English are typically used sentencemedially or -initially, but are occasionally used sentencefinally. By comparison, contrastive connectors in Chinese often form correlations or complex units on a more equal basis. Historical influence has led to the co-existence of “one-character” and “two-character” contrastive connectors in Chinese, the former frequent in written genres, the latter in conversation. Concessive clauses in Chinese are of two major patterns which are closely related to specific connectors. Chinese contrastive connectors can never be used sentencefinally. A profile of the usage of however has emerged from a case study of this second most frequent contrastive connector in BrE, concerning the contrastive vs. adverb function, the “unmarked” position, the syntactic patterns and corresponding functions, the semantic reasons for its wide use and dual function in second-initial position of the sentence, the occasional “coordinative” use of however, and its translation into Chinese. Three pedagogical implications arise from this study, based on which concrete teaching suggestions are made. Limitations of this study are acknowledged and some possible lines for future research are proposed.
Answering Questions about Complex Events

Abstract : Reasoning about event structure is a fundamental research problem in Artificial Intelligence. Event scenarios and procedures are inherently about change of state. To understand them and answer questions about them requires a means of describing, simulating and analyzing the underlying processes, taking into account preconditions and effects, the resources they produce and consume, and their interactions with each other. We propose a novel, comprehensive event schema that covers many of the parameters required and has explicit links to language through FrameNet. Based on the event schema, we have implemented a dynamic model of events capable of simulation and causal inference. We describe the results of applying this event reasoning platform to question answering and system diagnosis, providing responses to questions on justification, temporal projection, ability and 'what-if' hypotheticals, as well as complex problems in diagnosis of systems with incomplete knowledge.
Approaches To Summarize Multi Documents Using Information Extraction

No one has time to read everything, yet we often have to make critical decisions based on what we are able to understand. With summaries, we can make effective decisions in less time. Thus the technology of automatic text summarization is becoming essential to deal with the problem of information overload. Text summarization is the process of extracting the most important information from a single document or from a set of documents to produce a short and information rich summary for a particular user or task. Multi-document summarization is an automatic procedure for extraction of information from multiple texts about the same topic. Most of the MDS systems have been based on an extraction method, which identifies key textual segments (e.g., sentences or paragraphs) in source documents and selects them for the summary. Multi-document summarization aims to distill the most important information from a set of documents to generate a compressed summary. In this paper we are introducing various approaches for multi document summarization using information extraction. (Hari Om Sharan, Rajeev Kumar, Garima Singh, Mohammad Haroon. Approaches To Summarize Multi Documents Using Information Extraction. Academia Arena. 2011;3(7):62-67) (ISSN 1553-992X). http://www.sciencepub. net.
The effects of chronic marijuana use.

Summary There has been much controversy in the literature as to whether marijuana is detrimental to the psychological functioning of the user. In light of this issue, 14 male and female users, nonusers, and quitters of high school and college age were studied in a pre-posttest design to determine if chronic use affects the variables of aggression, frustration, alienation, and social- and self-adjustment. The quitters group discontinued use for two months after a two-week baseline period. Statistical analysis showed no significant differences among groups on any of the measures. Relating these findings to the literature suggests that differences which have been previously indicated may be due to the use of naive vs. experienced marijuana users as Ss.
Assessment of Methods to Trigger Transition Between Multiple SBAS

This paper provides an assessment of various parameters that might be used by DFMC SBAS airborne equipment to trigger transition from one SBAS to another. Currently only the approach phase of flight has requirements related to SBAS selection. There are no airborne equipment standards related to SBAS selection in the en route or terminal phases of flight. Current equipment transitions are based on unpublished manufacturer algorithms. The reported response of SBAS transitions and the pending introduction of new SBAS systems suggest a need for improvement of the transition methodology. SBAS has the potential to provide global capability for en route, terminal and precision approach operations. Unlike most ground-based navigation systems, DFMC SBAS can provide valid navigation in regions with no supported ground infrastructure. The extension to DFMC can increase the extent of service availability from existing SBAS, resulting in larger regions of overlapping SBAS service availability. Without any new SBAS selection requirements in the standards, this may result in equipment operating in the same airspace in the en route or terminal mode using different SBAS. For some SBAS, the equipment might be relatively far away from the reference network providing the augmentation. However, SBAS users are likely to achieve better performance when using corrections from an SBAS with nearby reference stations. Selection methods might want to leverage this measurable performance difference. This paper assesses SBAS selection and transition regions based on broadcast integrity parameters. It assesses parameters expected to be available to DFMC SBAS avionics from five operating SBAS systems implementing dual-frequency augmentation service. The assessment uses a simulation tool to generate the integrity parameters. Results demonstrate a reasonable capability to select the SBAS using the broadcast data. Results include an assessment of either a single core constellation (Global Positioning System (GPS)) or two core constellations, (GPS and Galileo); with the expectation that these results will be applicable to SBAS that also augment other core constellations such as Global Orbiting Navigation Satellite System (GLONASS) or BeiDou.
The architecture of delta sigma analog-to-digital converters using a voltage-controlled oscillator as a multibit quantizer

This brief proposes a new- architecture for the oversampling delta-sigma analog-to-digital converter (ADC) utilizing a voltage controlled oscillator (VCO). The VCO, associated with a pulse counter, works as a high-speed quantizer. This VCO quantizer also has the function of first-order noise shaping because the phase of the output pulse is an integrated quantity of the input voltage. If the maximum VCO frequency (fvm) is designed in the range of (2/sup bq/-2)fos<fvm< (2/sup bq/-1) fos and a bq-bit counter is used, a multibit (bq-bit) quantizer can be realized, where fos is the oversampling frequency. The performance of the proposed converter is evaluated using a functional simulation. A 59-dB SNR at a 5-MHz bandwidth is obtained with fos=400 MHz, even in the case of a 1-bit quantizer. The multibit quantizer using a high frequency VCO significantly improves an SNR and signal bandwidth. This architecture is highly suitable for implementation with deep sub-/spl mu/m CMOS devices, which can attain improved switching speeds and reduce power dissipation during low voltage operation. It provides wideband oversampling ADC for video and wireless signals and a low voltage system-on-a-chip solution for multimedia applications.
Multi classifier-based score level fusion of multi-modal biometric recognition and its application to remote biometrics authentication

Biometric recognition has become a common and reliable way to authenticate the identity of a person. Multimodal biometrics has become an interest of areas for researches in the recent past as it provides more reliability and accuracy. In multimodal biometric recognition, score level fusion has been a very promising approach to improve the overall system's accuracy. In this paper, score level fusion is carried out using three categories of classifiers like, rule classifier (fuzzy classifier), lazy classifier (Naïve Bayes) and learning classifiers (ABC-NN). These three classifiers have their own advantages and disadvantages so the hybridization of classifiers leads to provide overall improvements. The proposed technique consists of three modules, namely processing module, classifier module and combination module. Finally, the proposed fusion method is applied to remote biometric authentication. The implementation is carried out using MATLAB and the evaluation metrics employed are False Acceptance Rate (FAR), False Rejection Rate (FRR) and accuracy. The proposed technique is also compared with other techniques and by employing various combinations of modalities. From the results, we can observe that the proposed technique has achieved better accuracy value and Receiver Operating Characteristic (ROC) curves when compared to other techniques. The proposed technique reached maximum accuracy of having 95% and shows the effectiveness of the proposed technique.
An Extract Function Refactoring for the Go Language

Refactoring is a disciplined technique for restructuring an existing body of code, altering its internal code structure without changing its external behavior [22]. Refactoring is specified as a parameterized program transformation that requires a set of preconditions to be satisfied. The Go Doctor is a refactoring tool for the Go language. This thesis focuses on the design and implementation of an Extract Function refactoring adapted to the unique requirements of the Go language. The code that is to be refactored is parsed and type checked before the process is initialized. The tool ensures that certain preconditions are met; if they are not, it warns the user with the exact details as to why the refactoring will not continue. Then, a Live Variable analysis is used to determine what variables need to be passed to, returned from and declared in the new function that is created from the extracted code. To analyze the robustness of the refactoring, it was applied to 200 random statements selected from the top 100 GitHub projects using Go. These projects were also used to assess the potential impact of some of the refactoring limitations specifically, its inability to extract return statements, defer statements, and anonymous functions.
Random sequence analysis of optimum near-far resistance in a variable chipping rate dual-rate CDMA system

Direct-sequence code-division multiple-access (DS/CDMA) provides natural implementations for multi-rate communications systems. In this work, we will extend prior results on multi-rate systems with constant chipping rates to the case of variable chipping rate access (VCR) where chipping rates are proportional to user data rates. We use optimum near-far resistance as the performance measure of interest; thus for random sequences, the goal is to determine the average optimum near-far resistance. A random signature sequence analysis for the MMSE receiver operating in a single-rate system has been developed previously. We will combine the previous techniques; results on random matrices; and our prior work on variable spreading length (VSL) systems. The resulting two propositions for VCR systems are provided here.