Miracle-dz/UniFAR-FTUs huggingface dataset:
Intraspecific variation of Turkish Green Toads , Bufo { Pseudepidaleà ) viridis LAURENTI , 1768 , based on 16 S ribosomal RNA sequences ( Anura : Bufonidae )

Fourteen individuals of Bufo {Pseudepidaleà) viridis LAURENTI, 1768 representing 14 populations from Turkey were examined for variation in the mitochondrial 16S rRNA. Ten haplotypes were recovered. Pairwise comparisons of DNA sequences among haplotypes showed differences of up to 12 base substitutions; sequence divergences ranged from 0.11 % to 1.28 %. The divergence to individuals from Armenia and Ukraine was similar (0.11 % to 1.08 %). The divergence time estimated between several mtDNA haplotypes suggested a Pleistocene differentiation approximately 0.78 million years ago. Maximum parsimony, maximum likelihood, Bayesian and TCS analyses show that, there is geographic substructuring in Turkish Green Toads in that they are represented by two clades in the study area: western populations (izmir, Tekirdag) including the Ukraine {'viridis') versus all others from the rest of Turkey including Armenia {'variabilis'). Further investigations are needed to better understand the genetic variation within the species.
Least Squared Error Design of FIR Filters *

Because the integral of the square of a signal is a measure of its energy, there is some physical reason for minimizing the integral of the squared error [8], [1]. Also, because of Parseval's theorem, a least squares approximation in the frequency domain is a least squares approximation in the time domain. However, minimizing the worst case squared error induces a minimum Chebyshev error problem in some formulations [22].
SUPPLEMENTAL NOTE FOR “ ESTIMATING UNOBSERVED AGENT HETEROGENEITY USING PAIRWISE COMPARISONS ”

This note is a supplemental note to Krasnokutskaya, Song, and Tang (2016a). It consists of five parts. Section 2 gives details about how to derive pairwise comparison index in examples of first-price and English auctions where bidders have asymmetric private values, or collusive behavior. Section 3 discusses a bootstrap method to construct a confidence set for the group structure. Section 4 presents further simulation results regarding the performance of our classification algorithm proposed in Krasnokutskaya, Song, and Tang (2016a), and Section 5 reports summary statistics for the data used in the empirical application in the paper.
A Novel Algorithm for Class Imbalance Learning on Big Data Using Under Sampling Technique

Classifiers are trained with datasets of imbalanced class distributions, imbalance big data is an important problem in data mining. Imbalance in the data occurs when the number of examples representing the class of interest is much lower than the ones of the other classes. The presence of Imbalance datasets in many real-world applications has brought along a growth of attention from researchers. By introducing the characteristics of the imbalanced dataset scenario in classification, presenting the specific metrics for evaluating performance in class imbalanced learning and enumerating the proposed solutions. In particular, we will describe preprocessing, and ensemble techniques, carrying out an experimental study to contrast these approaches. In this paper we propose an under sampling algorithm for big data and will carry out a detailed discussion on the main issues related to using data intrinsic 12 Dr. Mohammad Imran et al characteristics in this classification problem. Finally, we introduce several approaches and recommendations to address these problems in conjunction with imbalanced data, and we will show some experimental examples on the behavior of the learning algorithms on data with such intrinsic characteristics.
CRISPRi-Mediated Analysis of Biofilm Formation in Plant Growth Promoting Pseudomonas fluorescens

Rhizobacteria of the Pseudomonas fluorescens group exhibit beneficial activities on multiple plants including Populus trees. P. fluorescens was characterized as a mycorrhizal helper bacteria (MHB) that promotes growth of the ectomycorrhizal fungus Laccaria bicolor at Populus roots. P. fluorescens also exhibits strain-specific promotion of aspen seedling growth in a laboratory experimental system [1]. The mechanisms underlying these beneficial interactions between roots and microbes still remain poorly characterized. To gain deeper insight into the rhizobacterial mechanisms, we investigated the spatial and temporal dynamics of the colonization by P. fluorescens of mycorrhizal and non-mycorrhizal roots of aspen seedlings [2]. Seedlings were grown in vertical plates in the laboratory, inoculated with a fluorescently labeled Pseudomonas strain, and root colonization was monitored over a period of five weeks. We observed an unsuspected diversity of bacterial assemblages at seedling roots that changed over time and were strongly affected by root mycorrhization with Laccaria bicolor. Biofilm assemblies on mycorrhizal and non-mycorrhizal roots were distinct, thick biofilms exhibiting internal channellike structures were observed on non-mycorrhizal root surfaces whereas a layer of bacterial cells stacked along their long axis were found embedded within a gel-like substance at mycorrhizal roots. In the binary system, P. fluorescens SBW25 formed dense biofilms on aspen roots after 5 weeks and produced significant PGP phenotypes, suggesting that biofilms are associated with PGP activities [2].
FOR YIELD FOR SUB-22 nm FinFET-BASED FPGA

VIII CHAPTER 1 : INTRODUCTION . 1 MOTIVATION. 1 1.1. ORGANIZATION OF THE THESIS . 1 1.2. CHAPTER 2 : LITERATURE REVIEW . 3 VARIABILITY. 3 2.1. 2.1.1. Classification of variations. 3 2.1.1.1. Die-to-Die (D2D) Variations. 3 2.1.1.2. Within-Die (WID) Variations. 3 2.1.2. Sources of variability. 4 2.1.2.1. Process Variations (Static Variations). 4 2.1.2.2. Environmental Variations (Dynamic Variations). 7 2.1. 3. Impact of Variability on the Frequency and Power. 10 2.1. 4. State-of-Art Variations Mitigation Techniques. 11 2.1. 4.1. CAD Tool and Statistical Design. 11 2.1. 4.2. Variations Mitigation at the Architecture Level. 12 FPGAS. 13 2.2. 2.2.1. FPGA Logic Resources Architecture. 16 2.2.2. FPGA Under Study. 16 CHAPTER 3 : PERFORMANCE EVALUATION OF FINFET-BASED FPGA CLUSTER UNDER VTH VARIATION . 2
Formulation and In-vitro Evaluation of Ciclopirox Ethosomal Gel

Ethosomal systems were lipid vesicular carriers which contain high percentage of ethanol and ethosomal gels were prepared in present study using ciclopirox as model drug. EF1-EF12 different formulations were prepared by varying concentration of ethanol from 20-50% and soya lecithin from 2-4%. Ethosome formulations were characterized for compatibility, drug entrapment efficiency, drug content, invitro drug release studies, surface morphology, vesicle size and size distribution. Ethosomal gel was prepared for optimized ethosomal formulation EF7 by incorporated into 1-2% carbopol gel. Ethosomal gels were characterized for pH, viscosity and spreadability. Optimized ethosomal formulation’s invitro drug release pattern was studied for different release kinetic models.
Multimodal Emotion Recognition using Facial Expressions, Body Gestures, Speech, and Text Modalities

: Automatic emotion recognition from multimodal content has become an important and growing research field in human-computer interaction. Recent literature has used either audio or facial expression for emotion detection. However, emotion and body gestures are closely related to one another. This paper explores the effectiveness of using text, audio, facial expression and body gesture modalities of multimodal content and machine learning and deep learning based models for building more accurate and robust automatic multimodal emotion recognition systems. First, we get the best accuracy from the individual modalities. Then we use feature level fusion and ensemble based decision level fusion to combine multiple modalities to get better results. Proposed models were tested on IEMOCAP dataset and results show that proposed models with multiple modalities are more accurate compared to unimodal models in classifying emotions.
Beyond the dependencies of altmetrics : conceptualizing ‘ heterogeneous couplings ’ between social media and science

Altmetrics, and more specifically social media metrics, have a genuine network nature (Haustein, Bowman, & Costas, 2016). However, this networked component has been less explored in the altmetric literature. Recent developments proposing the analysis of communities of attention (Haustein, Bowman, & Costas, 2015), the follower/followee relationships for scholarly authors on Twitter (Robinson-Garcia, van Leeuwen, & Rafols, 2015), or the co-readership (Kraker, Schlögl, Jack, & Lindstaedt, 2015) and readership coupling (Haunschild & Bornmann, 2015) networks on Mendeley have been already proposed. However, a general conceptualization and modelling of the different types of network interactions between social media and scholarly objects is still missing. The aim of this paper is to provide some systematic discussion around this point.
Practical security guidance for real-world users and designers of authentication systems Thesis Proposal

A wealth of security guidance is available to users and security system designers. Much of this guidance assumes an idealized world in which users are motivated and attentive when completing security tasks interjected in front of their primary task; and in which system designers are free to design security systems that subject their user base to however poor a usability experience deemed necessary in order to maximize security benefits for those users. However, these idealized-world assumptions do not reflect reality. Users perform security as a secondary task, typically unmotivated to exert more than the minimum possible effort to accomplish security tasks, which they ultimately perform in an inattentive, error-prone manner. I will demonstrate how practical guidance can be given to users that assumes realworld settings but that does not abandon the worthwhile goal of improving security for those who do not want to or cannot take the security-optimal approach. First, I will show how users can be guided to create strong passwords while minimizing negative usability impacts, using password policies that incorporate a minimum neural-networkderived password-strength requirement. Second, I will show how latent features of passwords can be learned that can then be leveraged to improve password-creation guidance with more relevant and comprehensive text feedback. Lastly, I will show how practical guidance can be given to system designers in authentication domains other than passwords, using public-key verification as a case study. Specifically, I will examine ways of exposing fingerprint verification to ordinary users that remain effective at protecting against man-in-the-middle attacks in low-risk situations or usabilityfocused environments.
Mean Estimation from Multiple-Choice Questions

Given n values possessed by n agents, we study the problem of estimating the mean by truthfully eliciting agents’ answers to multiple-choice questions about their values. We consider two natural candidates for estimation error: mean squared error (MSE) and mean absolute error (MAE). We design a randomized estimator which is asymptotically optimal for both measures in the worst case. In the case where prior distributions over the agents’ values are known, we give an optimal, polynomial-time algorithm for MSE, and show that the task of computing an optimal estimate for MAE is #P-hard.
COMPARISON OF IMAGING CONDITIONS : APPLICATION TO MARMOUSI DATA

The application of an imaging condition in wave equation shot profile migration is important to provide illumination compensation and amplitude recovery. Particularly for true-amplitude waveequation migration algorithms, a stable imaging condition is essential to successfully recover the medium reflectivity. We continue our study of a set of image conditions with illumination compensation by application to the Marmousi data. The imaging conditions are evaluated by the quality of the stacked migrated sections. The most stable of the tested imaging condition with illumination compensation divides the crosscorrelation of the upand downgoing wavefields by the autocorrelation of the downgoing wavefield. Smoothing imaging conditions, which work perfectly in vertically inhomogeneous media, tend to fail for laterally varying velocities.
COUNTERMEASURES AGAINST COORDINATED CYBER-ATTACKS TOWARDS POWER GRID SYSTEMS

A study on countermeasures against coordinated cyber-attacks (CCA) towards power grid systems has been carried out. A coordinated cyber-attack is a cyber-based attack where multiple attackers use multiple attack-mechanisms towards multiple targets in a coordinated fashion. The coordination is based on that the different attack-mechanisms help each other in attacking the target. A CCA is made up of different stages where each stage consists of a number of attack-mechanisms and together have a certain purpose. The different stages are used to systematically advance towards its goal, which is to compromise the operation of internal systems or to steal confidential data. For example, the first stage may be used to locate entry points at the target system, and a second stage may be used to locate vulnerable hosts by sniffing ongoing network activity to further itself towards its attack goal. Power grids that are used to generate, transmit, and distribute electricity over large geographical areas are connected to the Internet. Within these environments, commercial IT systems have been adopted to control their electrical equipment, which poses cybersecurity risks to the power grid. Intrusion Detection Systems (IDS) are designed provide internal network protection in case of intruders. However, state-of-the-art IDSs has been found to have certain limitations in protecting against multi-stage and slow attacks. The inadequacy of state-of-the-art IDSs for protecting against CCAs motivates the need to identify alternate countermeasures that can mitigate CCAs, when the target is a power grid system. The method of choice to address this problem in this study is a systematic literature study where 48 countermeasures were identified and assessed to which extent they are suitable to mitigate CCAs. Results suggest to follow three approaches, namely to preemptively identify technical vulnerabilities in the local system, to distribute intrusion detection hosts across a larger network for better situational awareness, and to implement new types of IDS technologies. Countermeasures with references to specific publications are also provided. The study contributes to how security operators of power grids can fulfil the requirement on cybersecurity as demanded by the NIS directive of the European Union regarding protection against CCAs.
BLIND SPARSE SOURCE SEPARATION WITH SPATIALLY SMOOTHED TIME-FREQUENCY MASKING 1

In this paper, we handle the blind sparse source separation problem with time-frequency masks. Some existing methods employ time-frequency binary masks to extract the signals, and therefore, the extracted signals tend to contain loud musical noise. It causes from the winner-take-all property of the binary mask. To overcome the problem, this paper proposes some non-binary time-frequency masks that allow each time-frequency component to belong to several output signals. Experimental results show that our proposed method can separate signals with little distortion.
Tiered file system: Optimization of architecture and management algorithms

Automated storage tiering, from the business point of view, allows for a considerable cut of data storage costs while preserving the storage system performance at an acceptable level. The aim of this master’s thesis is to design and implement a tiered policy-based file system having, as tiers, a local disk or distributed POSIX-conformant file system and cloud object storage. As a result of this study, the tiered file system called CloudTieringFS, has been devised. The primary use case of CloudTieringFS is mass file storage. CloudTieringFS uses a POSIX-conformant file system as a permanent storage for metadata and as “capacious cache” for data and cloud object storage as a permanent storage for data. The key advantage of CloudTieringFS is simultaneous provision of features such as configurability of data migration via policies, underlying file system-agnosticism, and fault tolerance. The study is divided into four chapters. In the first chapter, the background required to familiarize the reader with the automated storage tiering in an environment that includes a file system and cloud object storage is given. A survey of similar solutions is provided and common problems to be overcome by the tiered file system developer are identified. The second chapter surveys the selected distributed file systems and compares some of their features important for design and implementation. The third chapter summarizes requirements for the tiered file system and proposes a detailed design for such a system. In the last chapter, the performance of CloudTieringFS is evaluated in singleand multi-node configurations with BtrFS and OrangeFS file systems correspondingly. The performance results of CloudTieringFS are promising. The average file access latency for the selected file access pattern differs insignificantly versus the file access latency of the underlying file system. Summarizing, it can be argued that properly adjusted automated storage tiering policies can preserve the underlying file system’s performance with neglectable overheads while reducing data storage costs.
’ Affiliation Information in Scientific Literature Using Centralities-The Researchers who Act as Mediators between Organizations -

The Institute of Statistical Mathematics aims to further develop statistics by promoting the exchange of data and resources between domestic and foreign researchers. This has been examined from a statistical viewpoint, which suggests using a new index whereby the progress and effectiveness of the joint use can be objectively assessed. We analyzed co-author information using betweenness centrality in articles written by researchers at the Institute of Statistical Mathematics in 2013, obtained from the Web of Science. The analysis results enable identification of the researched people that are in the center of their research field.
Physical Characteristics of Green Tea Powder Processed by Disc and Stone Mills ]

Size reduction could affect the physical properties of green tea powder. The aim of this study was to determine the physical properties of green tea powder processed by different milling methods. A disc mill (DM) with single screw made from stainless steel and a stone mill (SM) made from granite stone were used to produce green tea powder. Water holding capacity, water solubility index, swelling capacity, wettability, extraction yield, dispersibility and dispersion stability, and particle size distribution were analyzed to determine the physical properties of green tea powder. The morphology and shape of green tea powder were also observed using scanning electron microscopy. The DM method produced green tea powder with higher values of water absorption index, swelling capacity and water holding capacity, i.e. 4.57 g/g; 5.17 mL/g; and 6.18 g/g respectively. Green tea powder with SM method had a brighter color with L value of 60.1 and was a fine powder with d50 of 1.4 μm. Based on the above physical properties, green tea powder with SM milling method is more suitable for application in food products.
Modelling the Runtime of the IQMR Method for Large and Sparse Linear Systems on Parallel Computers

For the solutions of large and sparse linear systems of equations with unsymmetric coeÆcient matrices, we propose the IQMR method by using the Lanczos process as a major component combining elements of numerical stability and parallel algorithm design. The algorithm is derived such that all inner products and matrix-vector multiplications of a single iteration step are independent and communication time required for inner product can be overlapped eÆciently with computation time of vector updates. Therefore, the cost of global communication on parallel distributed memory computers can be signi cantly reduced. In this paper, we show the execution time of collective communication operations in PVM and PMI can be modelled by runtime functions in closed form on CrayT3D and CrayT3E. We also demonstrate that the runtime functions can be used to model the computation and communication of the IQMR method. Some theoretical and experimental results will be presented and compared as well.
Low Power Three Input XOR Gate For Arithmetic And Logical Operation Ms

With advancement of microelectronics technology scaling, the main objective of design i.e. low power consumption can be easily acquired. For any digital logic design the power consumption depends on; Supply voltage, number of transistors incorporated in circuit and scaling ratios of the same. As CMOS technology supports inversion logic designs; NAND & NOR structures are useful for converting any logic equation into physical level design that comprises of PMOS and NMOS transistors. In similar way, logic can be implemented in other styles as well, with the difference in number of transistors required. The conventional CMOS design for three input XOR logic can be possible with 10 or more than 10 transistors, with the methodology discussed in this paper, the same design for three inputs XOR logic can be made possible with 16 transistors. The proposed methodology consists of transmission gate and systematic cell design methodology (SCDM). This design consumes 45% (35%) less power dissipation than that of conventional LPHS-FA and SCDM based XO10 XOR logic design with CMOS technology. Since the design for XOR logic, is useful for variety of applications such as Data encryption, Arithmetic circuits, Binary to Gray encoding etc. the XOR logic has been selected for design. The design explained in this paper is simulated with 130nm technology.
An Improved Scheduling Technique based on Containers

: In hadoop, job scheduling is an independent module so that users can design or configure their own job scheduler based on their actual application requirements; thereby meet their specific business needs. Currently, hadoop has three schedulers: first is FIFO, Fair scheduler and Capacity Scheduler, all the schedulers can helps in scheduling the resources among different computers. All the three schedulers cannot fully support data locality due to which the performance is affected. In this paper, we took the concept of resource-prefetching into consideration, and proposed a job scheduling algorithm based on data locality. By which the PRISM scheduler will perform much better because along with data locality we also focus on containers by which we can schedule the containers among different map-reduce task.