Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Voice Priority Queue (VPQ) Scheduler Architectures and Algorithm for VoIP over WLAN Networks

Voice over Internet Protocol (VoIP) over Wireless Local Area Networks (WLAN) might be a leading application in collaboration with 3rd Generation (3G) mobile network. VoIP is moving on WLAN based on IEEE 802.11 standards. For audio speech quality in packet switch applications, the main concerns are end-to-end delay and packet loss. Currently, many of packet scheduling algorithms like Weighted Fair Queuing (WFQ), was manly designed to provide the bandwidth reservation. Low Latency Queuing (LLQ) addresses this problem but undergo from low priority traffic starvation problem. The Strict Priority (SP) is low-cost to maintain the delay sensitive voice traffic. Also, a number of research scheduling solution have been proposed like General processor sharing (GPS), Deficit Round Robin (DDR), Low Latency Efficient Packet Scheduling (LLEPS), Efficient Scheduler (ES) for the IP-based network. Unfortunately, they have some drawbacks for real time application. The objective of this research, to propose a novel Voice Priority Queue (VPQ) packet scheduling algorithm to ensure more throughput, low latency and efficient packet scheduling for VoIP performance of queues and traffics. Experimental topology using on NS-2 network simulator were analysed for voice traffic. Preliminary results show that this can achieve maximum and more accurate VoIP quality.
Performance Comparison Between Hama and Hadoop

Massive scientific computations such as matrix, graph and network algorithms are very attractive when they come to modelling real-world data. Apache Hama is a pure BSP (Bulk Synchronous Parallel) distributed computing framework for massive scientific computations. In this paper, our experiments were conducted on a 4-node Hadoop cluster. We implement Monte Carlo algorithm of Pi in Hama and Hadoop under the same software and hardware environment. The experimental results show that Hama can achieve much higher performance than Hadoop in our testbed.
Driver Behavioral Adaptation in Response to a Novel Haptic Driver Support System

Behavior adaptation refers to any change in behavior as a result of the inclusion of a technology that serves a need of the driver other than intended by the technology. Driver support systems that facilitate vehicle controllability may allow for driver resources to be redirected to activities unrelated to that goal. The current study sought to examine the relationship between increased vehicle controllability, which is a design goal of a novel haptic driver support system, and behavioral adaptation as measured by in-vehicle secondary task productivity. Participants drove a simulated rural Minnesota highway with and without the use of a driver support system and with and without engaging in a self paced in-vehicle secondary task. Measures were taken of car-following performance and entropy (controllability) as well as secondary-task performance. Results indicate improved controllability with some marginal behavioral adaptation is acceptable to the extent that the secondary-task engagement is not a risk factor.
The Influence of Internet Celebrity on Purchase Decision and Materialism: The Mediating Role of Para-social Relationships and Identification

The objective of this paper is to examine the influence of internet celebrities on customer purchase decision and materialism, with special attention on parasocial relationships and identification as mediators and how they play a role in celebrity influence on purchase decision and materialism. 413 female students from three universities in Dalian, Liaoning Province, China were sampled randomly using structured questionnaires. Structural equation modelling was used with the help of SmartPls3. The highlight of the study is the mediating roles of para-social relationships and identification between internet celebrities and purchase decision and materialism. Again, the study portrayed that internet celebrity significantly influence parasocial relationships, whereas parasocial relationships in turn influence identification with the celebrity. More so, identification significantly influences purchase decision and materialism. Furthermore, internet celebrity ultimately influences purchase decision and materialism through the mediating roles of para-social relationships and identification. The study made available some significant findings for marketers and academics. Marketers can use the internet celebrities as third parties to communicate to their target audience through their blogs and pages on the internet by endorsing their brands. Academics can explore how para-social relationships and identification mediates between internet celebrities and purchase decision and materialism. To the knowledge of the authors, this study is the first of its kind in an attempt to examine the influence of internet celebrity on purchase decision and materialism using parasocial relationships and identification as mediators. Keywords - Internet celebrity, Para-social relationships, Identification, Purchase decision and materialism, Structural equation modelling Paper type : Research paper DOI : 10.7176/EJBM/11-15-20 Publication date :May 31 st 2019
New themes and approaches in second language motivation research

The study of L2 motivation has reached an exciting turning point in the 1990s, with a variety of new models and approaches proposed in the literature, resulting in what Gardner and Tremblay (1994) have called a ‘motivational renaissance. ’ In this chapter I provide an overview of some of the current themes and research directions that I find particularly novel or forward-looking. The summary is divided into three sections: theoretical advances, new approaches in research methodology, and emerging new motivational themes. I argue that the initial research inspiration and standard-setting empirical work on L2 motivation originating from Canada has borne fruit by ‘educating’ a new generation of international scholars who, together with the pioneers of the field, have applied their expertise in diverse contexts and in creative ways, thereby creating a colorful mixture of approaches comparable to the multi-faceted arena of mainstream motivational psychology.
Clarifying the brand personality construct in Malaysia

Purpose This paper aims to investigate the variations in brand personality trait items to describe both global and local brands in Malaysia. Design/methodology/approach The authors adopted both factor analytic and experimental methods to investigate the internal and external validity of Malaysia brand personality (MBP) scale. They followed a stringent scale development process that ensures the scale conform to psychometric properties. Findings In seven studies, the results show that the 22-item four-factor Malaysian brand personality scale adheres to strong psychometric properties of scale development process. The findings further indicate that there are seven indigenous traits, while most traits emerge from factor analyses originate from studies of Aaker (1997) and colleagues (2001). This confirms universality of some brand personality traits and dimensions. Research limitations/implications Within the limits of the study, we did not examine the MBP facet level, and were confined to those respondents in Klang Valley only. Practical implications The MBP scale enables marketing managers in Malaysia to focus on brand personality dimensions that their customers can relate to. In other words, marketing communications can be more efficient when managers can identify brand personality traits that enhance customers’ behaviors and profitability. Originality/value Malaysia is a multicultural and multiethnic country which is increasingly becoming the focus of international brand expansion. The authors view that the development of the MBP scale is timely and should provide managers further insights into the brand personality structure that is relevant in Malaysia.
Beyond Time and Space: The Impact of Autonomy from Politics and Commercialization Pressure on Mediatization in German and Austrian Newspapers—A Multilevel Approach

Theorizing on mediatization of politics stresses the importance of structural conditions on different levels of media systems for explaining the increasing importance of media logic in media coverage. Levels of autonomy of media from politics and the extent of commercialization pressure are considered particularly important. However, most studies investigate differences between countries and the passing of time as proxies and qualitatively infer which structural conditions might account for the level of mediatization. The current study goes beyond these proxies. It reviews and systematizes how structural autonomy from political institutions and extent of commercialization pressure influences the importance of media logic in media coverage and operationalizes these influences in a comparative analysis of election campaign coverage in Germany and Austria over 60 years. A multi-level analysis finds that between-country differences and within-country changes in macro- and meso-level autonomy from politics/commercialization pressure account for a large part of the time/space (campaign/country) variation of the importance of media logic. It complements earlier research (1) by demonstrating that between-country differences and within-country changes in media coverage reflect underlying media structures; (2) by specifying which structural influences (representing the media’s autonomy from politics and commercialization pressure) are most important in shaping the importance of media logic in campaign coverage.
Pronunciation Adaption at the Lexical Level

There are various kinds o f adaptation which can be used to enhance the perform ance o f automatic speech recognizers. This paper is about pronunciation adaptation at the lexical level, i.e. about m odeling pronunciation variation at the lexical level. In the early years o f automatic speech recognition (ASR) research, the amount o f pronunciation variation was lim ited by using isolated w ords. Since the focus gradually shifted from isolated w ords to conversational speech, the amount o f pronunciation variation present in the speech signals has increased, as has the need to m odel it. This is reflected by the growing attention for this topic. In this paper, an overview o f the studies on lexicon adaptation is presented. Furtherm ore, m any examples are m entioned o f situations in which lexicon adaptation is likely to improve the perform ance o f speech recognizers. Finally, it is argued that some assumptions made in current standard A SR systems are not in line with the properties o f the speech signals. Consequently, the problem o f pronunciation variation at the lexical level probably cannot be solved by simply adding new transcriptions to the lexicon, as it is generally done at the moment.
Generating a Style-Adaptive Trajectory from Multiple Demonstrations

Trajectory learning and generation from demonstration have been widely discussed in recent years, with promising progress made. Existing approaches, including the Gaussian Mixture Model (GMM), affine functions and Dynamic Movement Primitives (DMPs) have proven their applicability to learning the features and styles of existing trajectories and generating similar trajectories that can adapt to different dynamic situations. However, in many applications, such as grasping an object, shooting a ball, etc., different goals require trajectories of different styles. An issue that must be resolved is how to reproduce a trajectory with a suitable style. In this paper, we propose a style-adaptive trajectory generation approach based on DMPs, by which the style of the reproduced trajectories can change smoothly as the new goal changes. The proposed approach first adopts a Point Distribution Model (PDM) to get the principal trajectories for different styles, then learns the model of each principal trajectory independently using DMPs, and finally adapts the parameters of the trajectory model smoothly according to the new goal using an adaptive goal-to-style mechanism. This paper further discusses the application of the approach on small-sized robots for an adaptive shooting task and on a humanoid robot arm to generate motions for table tennis-playing with different styles.
A neural network to visually understand and autonomously navigate unknown environments

A complex sensor based control system is presented. The sensor used is a pair of TV cameras providing a stereogram for a stereo vision system based on a cellular neural network (CNN). The 3D information retrieved are used by a simple path planning algorithm and actuated on two different robots. Results of experiments are reported. The usability of the CNN paradigm in robotics applications is demonstrated
Non-moraic geminates in Leti

The representation of geminate consonants remains a controversial topic in phonological theory. In a skeletal theoretic approach, for example, a geminate is represented as bipositional: a single root node multiply linked to two skeletal positions, as in (1) (see e.g. Clements & Keyser 1983, Levin 1985). formula here Conversely, in moraic theory, geminates are inherently moraic (see e.g. Hayes 1989, 1995, Davis 1994, 1996). Thus, an underlying geminate consonant differs from a single consonant of the same quality in terms of a mora, as shown in (2): formula here It is noteworthy that evidence bearing on the representation of geminates has thus far come predominantly from the patterning of intervocalic geminates, where the first part of a geminate occurs in coda position. Discussion of syllable-initial geminates, on the other hand, has received little attention in the literature.
Node-Pore Sensing: A Robust, High Dynamic Range Method for Multi-Parametric Screening of Biological Samples

Author(s): Balakrishnan, Karthik Ratna | Advisor(s): Sohn, Lydia L | Abstract: Resistive-pulse sensing is a technique that allows for measurements of particles in a solution. The underlying principle relies on measuring the electrical resistance across a small pore connecting two reservoirs filled with fluid. As an insulating particle enters the pore, the particle displaces the conducting fluid, leading to an increase in the resistance measured. Pulse magnitude and width reveal information about the particle in transit. The size of the pulse magnitude corresponds to the size of the particle, while the width of the pulse represents the length of time the particle takes to transit the pore. We show that resistive pulse sensing can be used in combination with protein functionalization to achieve surface marker screening of small sample sizes. We analyze single satellite cells from muscle fibers of mice. We also present unique channel geometries that offer advancements to traditional resistive-pulse sensing. This new technique, node-pore sensing, provides unique signal detection benefits and essentially provides particle tracking, allowing us to determine specifically when a particle transits a specific region of a pore. Ultimately, node-pore sensing provides unprecedented sensitivity, which we show can be used to detect human immunodeficiency virus in human plasma. The particle tracking aspect of this technique affords us the capability of probing particle interactions in different regions of the pore, ultimately allowing us to perform single-cell screening of multiple biomarkers in a single device. We demonstrate multi-marker screening on cultured leukemia cells and bone marrow from leukemia patients. These studies showcase the promise of our platform for broad screening and diagnostic applications.
PROVENANCE OF SANDSTONE CLASTS FROM CONGLOMERATE OF THE PALEOCENE-EOCENE ORCA GROUP IN PRINCE WILLIAM SOUND, ALASKA

The thick flysch facies of the Cretaceous to Eocene Chugach-Prince William terrane (CPW) represents a thick accretionary complex that extends approximately 2200 km across southern Alaska, and in the central area is comprised mainly of the Valdez Group and the Orca Group (Fig. 1) (Garver and Davidson, 2015; Davidson and Garver, 2017). The Valdez Group is traditionally viewed as a Campanian to Maastrichtian turbidite deposit with mafic volcanic rocks that have experienced lower greenschist facies metamorphism (Dusel-Bacon, 1991; Gasser et al., 2012). The Orca Group is Paleocene to Eocene turbidite and volcanic deposit that, in most places, has undergone prehnitepumpellyite facies metamorphism (Dusel-Bacon, 1991; Wilson et al., 2012).
Consumption capability analysis for Micro-blog users based on data mining

Data mining is an effective method of discovering useful information in a large amount of data. The capability of understanding the user’s consumption is vital for a company. Discovering the significant customers allows the company to focus on the most valuable customers. This paper uses micro-blog users’ check-in data and shop information for analysis and cluster method of data mining. We analyze user’s spending ability quantitatively based on user’s check-in actions. Compared with other clustering method, we choose DBSCAN clustering method of data mining to analyze the shop information and position. Users are divided into different categories according to their spending power. Discovering the users with high consumption level in large amounts of data, which is significant for a firm, can help the firm develop better strategies.
Improving Teaching through Collaborative Reflective Teaching Cycles

Abstract Reflection and collaboration are two activities teachers can use to change and improve their practice. However, finding the time and space to do so can be challenging. The collaborative reflective teaching cycle is a structured activity teachers can use to engage in reflection and collaboration. This article describes how a seventh grade teaching team implemented a series of cycles and in what ways the cycles impacted their practice. Implications for instruction and suggestions for use of the cycles in practice are discussed.
Domain wall motion and magnetization switching driven by magnetic/laser fields

The work presented in this thesis mainly focus on the domain wall motion in planar Permalloy nanowires and magnetization switching in ferromagnetic Co/Pt thin films studied with both static Kerr imaging and dynamic pump and probe time-resolved magneto-optical Kerr effect (TR-MOKE) measurement techniques. The aim is to provide insightful support for the future novel data storage devices based on magnetic nanostructures. A spatially resolved wide-field magneto-optical Kerr imaging system has been successfully built during this project. The dependence of the coercivity of the Permalloy nanowires on different notch depth and geometries have been investigated systematically. The results show that the depinning field is strongly dependent on the detailed notch geometry. We have found that even the notches with same triangular feature, but different orientations will have a large depinning field difference. Our micromagnetic simulations support the experimental observations and show the correlation between the notch geometry, and the domain wall pinning and depinning processes. The laser-induced precession dynamics in Co/Pt thin films with multiple layers have been investigated by pump and probe TR-MOKE. By fitting the experimental curves via phenomenological formula, the effective Gilbert damping constants are retrieved. The results show that Gilbert damping constant has a significant external field and layer repetition number dependences. The more Co/Pt layer repeats number, the higher value of constant. This enhancement of the Gilbert damping constant value with more Co/Pt layer repeats could be due to the interfacial effect or decoherence. As the lattice mismatching in the Co/Pt structures increases with the thickness, the increased dislocation may promote electron hopping between two different sites which enhances the intrinsic damping in the thicker films. Combing the TR-MOKE system with the Kerr imaging, the magneto-optical responses of the ferromagnetic Co/Pt films with different Co thicknesses under the action of femtosecond laser beam have been explored systematically. We have developed a new approach to study the helicity dependence in the all optical switching (AOS) by varying the degree of helicity. Our results demonstrate unambiguously that the laser helicity plays an essential role in the AOS. We have further established a detailed relationship between domain switching percentage and the degree of the pumping laser helicity.
A Microstrip Nonreciprocal Tunable YIG Filter

A nonreciprocal tunable YIG filter in a microstrip configuration has been constructed which makes use of a novel method of generating a circularly polarized field in the plane of a microstrip circuit. Nonreciprocities in excess of 40 dB have been obtained at X band with relatively low insertion loss and VSWR.
Retrieval of stratospheric aerosol characteristics from spaceborne limb sounders

Stratospheric aerosols play an important role in atmospheric chemistry and climate. In particular, information about the amount and distribution of stratospheric aerosols is required to initialize climate models, as well as validate aerosol microphysics models and investigate geoengineering. Besides, good knowledge of stratospheric aerosol loading is needed to increase the retrieval accuracy of key trace gases (e.g. ozone or water vapor), when interpreting remote sensing measurements of the scattered solar light. The most commonly used characteristic to describe stratospheric aerosols is the aerosol extinction coefficient (Ext), and there are several datasets providing this parameter in the stratosphere. However, it is well-known, that for the limb-scatter instruments, this parameter contains uncertainties due to the need to assume an aerosol particle size distribution (PSD) within the retrieval process. These uncertainties can be mitigated if PSD parameters are provided for each profile. In this thesis, the methods to retrieve Ext and PSD parameters from the remote sensing instruments measuring the scattered solar light in the limb-viewing geometry are presented. The Ext retrieval algorithm is applied for Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instrument, which was operating from 2002 till 2012, as well as for Ozone Mapper and Profiler Suite (OMPS) measurements, which started in 2012 and are conducted ever since. These products compose global stratospheric aerosol databases, which are covering over 16 years. Additionally, the aerosol PSD parameters are retrieved in the tropical region (20° N – 20° S) from SCIAMACHY limb measurements, creating a unique product. SCIAMACHY Ext retrieval algorithm is improved since the previous version, and the obtained results are compared to the datasets from Stratospheric Aerosol and Gas Experiment (SAGE) II and Optical Spectrograph and InfraRed Imager System (OSIRIS) instruments. In the tropical region, the agreement between the instruments is within 20%, while in the high latitudes of both hemispheres the differences increase. This is related to the fixed PSD assumed in the retrieval. Retrieving the Ext profiles from SCIAMACHY and comparing them to SAGE II it is shown, that in the high latitudes the change of the PSD parameters within realistic values is responsible for up to 100% of the errors, while
Evolutionary Spatial Histogram Features for Vehicle Detection

The evolutionary methods for detection aims to improve the accuracy and efiective of detection task. In this paper, an evolutionary object detection approach is proposed. The proposed algorithm employs the 5-fold validation as fltness criterion to direct the selection of templates, which is vital for creating spatial histogram features. In evolutionary process, for overcome the limitation of manually choosing trail vector generation strategies and its associate control parameters, the self-adaptive evolutionary method is employed to evolve templates more efiectively. We evaluate the proposed approach compared with two difierent kinds of methods. The experimental results prove that by using of self-adapt evolutionary search, we are able to flnd object templates with a higher detection rate.