Miracle-dz/UniFAR-FTUs huggingface dataset:
An Integrated Model of Voice-User Interface Continuance Intention: The Gender Effect

ABSTRACT Advanced speech recognition technology facilitated the development of voice-based smart devices. Voice user interface (VUI) is now a common feature on smartphones, computers, smart home devices, and car systems. The fragmented and context focused literature on VUI motivates this examination of the relationship between perceived quality and customer satisfaction in VUI portable devices. This study is the first to introduce extrinsic motivational factors as an extension to Wixom and Todd’s model. These additional antecedent factors add an enriched explanation of VUI user behavior. This study is also the first to consider the role of gender in a VUI behavior model. Our findings suggest that the proposed driving factors, including trust, perceived risks, perceived enjoyment, and mobile self-efficacy, significantly affect VUI user attitudes, which influence their continuance intention. Our results also address the role of gender on the association of attitude toward VUI use and its antecedents. The findings show that perceived risk (privacy concerns) and perceived ease of use are more influential on VUI use behavior of males than females. However, the effect of trust and mobile self-efficacy play a more crucial role for females than males.
Students’ Perception on the Integrating of Information and Communication Technology (ICT)

The new trends of the integrating of ICT in English Class used by the researchers in Teaching English as Foreign Language (TEFL) methodology class that enables the students get more experience, knowledge and understanding. This research aims to know whether the students have positive perception on the integrating ICT in TEFL methodology class, describe the students’ attitude in learning TEFL methodology Class through the integration of ICT and get the information on the strengths and weaknesses of the integrating of ICT in TEFL methodology class from the students’ perception. The researchers conducted the research in TEFL Methodology Class. The students involved in this research were the students of fifth semester that consist of 30 students in English Department of STKIP Muhammadiyah Pringsewu Lampung. This research is qualitative research which involves case study. In collecting the data, the researchers used questionnaire, in-dept interview and observation. In getting the validity of the data the triangulation was applied by the researcher. From the research finding, the researchers got the information that the students have positive perception in ICT for TEFL methodology class, the students have positive attitude in learning, and integration of ICT for TEFL brings both strengths and weakness.
Simulation Analysis of Dynamic Characteristic of Harmonics for High-Speed Locomotive Running at Rated Power

An analytical method for calculating the dynamic characteristic of the harmonics of high-speed locomotives running at a rated power was presented by analyzing the generation process of harmonic voltage and the characteristics of harmonic impedance of a traction power supply system.Based on the double Fourier series and the Bessel function,the expression of harmonic voltage of a PWM(pulse width modulation) rectifier was deduced.Based on the distributed parameter model the formula of calculating harmonic impedance for an overhead contact system was derived,and from the formula,series resonances and parallel resonances were analyzed.Frequency spectrum characteristics of harmonic voltage and harmonic current under the condition that a high-speed locomotive runs at a rated power were simulated and analyzed.The research results indicate that the frequency spectrum characteristics of both harmonic current and harmonic voltage vary,especially the former;series resonances occur at some frequency and the resonance position depends on locomotive position along the line;harmonic current contents are small,and the main contents are the 3rd to 9th and series resonance harmonics.
Dynamic characteristic analysis and experimental study on a new type reducer with small tooth number difference

With finite element method of multi-body contact problems,the time-variant stiffness at different rota-tional position of a new type gear reducer with small tooth number difference was obtained,and the dynamic contact finite element method was used to analyze meshing impact excitations,then the internal excitations including excitations of time-variant stiffness,gear error and meshing impact were calculated.A dynamic finite element model of a gear reducer was es-tablished and used to analyze its dynamic response in time-domain and frequency-domain as well as one-third octave accel-eration grade for its structural borne noise of the gear reducer under dynamic excitation.At last,an experiment of vibration analysis of the reducer was conducted using an analysis instrument of vibration test.The computational results obtained were in a good agreement with the test data.
The influence of instruction set and test format on the detection of malingering

The Influence of Instruction Set and Test Format on the Detection of Malingering by Teri J. Forrest Dr. Daniel N. Allen, Examination Committee Chair Associate Professor o f Psychology University o f Nevada, Las Vegas It is increasingly common for individuals involved in civil litigation to undergo neuropsychological evaluation. This trend increases the possibility that individuals receive trade-secret test information from their attorneys before evaluation in order to maximize their ability to appear injured. However, no known research has examined what effeet this knowledge may have on an individual’s ability to successfully evade detection as a malingerer. The current investigation examined the performance of archival brain-damaged individuals, normal controls, and individuals in three malingering groups on both previously and newly developed malingering indices for the Wisconsin Card Sorting Test (WCST) and the Halstead Category Test (HCT). The three malingering groups differed as to the extent o f prior coaching they were given specifically regarding the nature, content, and requirements o f the WCST. Results indicated that individuals given the most explicit coaching about the WCST were able to escape detection on more malingering indices than individuals in the other malingering
Reimagining the Chalk Talk: Animated Handwriting as a Social Cue to Improve Motivation in Multimedia Video Lessons

REIMAGINING THE CHALK TALK: ANIMATED HANDWRITING AS A SOCIAL CUE TO IMPROVE MOTIVATION IN MULTIMEDIA VIDEO LESSONS Hillary C. Kaplowitz Old Dominion University, 2018 Director: Dr. Ginger S. Watson Animated handwriting in multimedia video lessons, such as those popularized by the Khan Academy, has reimagined the classic teaching technique of writing on a chalkboard while lecturing for online delivery. This digital chalk talk effect mimics classroom lectures where words are written letter by letter on a chalkboard as they are spoken. Low-cost applications, tablets, and document cameras allow instructors at all levels to easily create their own animated handwritten videos. As adoption increases, it is important to understand the effects of this strategy. This study employed a true experimental, between-subjects, posttest design that compared multimedia lessons with different text display formats on outcomes of motivation, mental effort, and learning. Undergraduate student volunteers (n = 234) from a large U.S., West Coast, regional, four-year public university were randomly assigned to one of three treatments: Animated handwritten, animated typewritten, or static typewritten. Each group watched a different version of a five-segment, twelve-minute multimedia lesson about cryptography. Lessons differed only in the visual text display format and contained identical narration and content. Results indicated that multimedia with animated handwritten text produced strong social cues motivating learners. Participants who viewed the animated handwriting reported significantly greater social agency attitudes toward the learning experience than with static typewritten text. They perceived the narrator’s voice as more dynamic with animated handwriting when compared to static, even though the voice was identical. They also reported more attention to the lesson and materials with animated handwriting than either animated typewritten or static typewritten. These motivational gains are accomplished without introducing extraneous cognitive load or negatively impacting learning outcomes. Significant findings from this research demonstrated that animated handwritten text is more than just a signaling strategy. The combination of text being hand-drawn and appearing as if a real person is writing it in real time adds a powerful social cue. Results of this study demonstrate that using animated handwriting in multimedia video lessons is an effective way to increase motivation through social cues that can be accomplished without requiring expansive technical knowledge, expensive equipment or extensive time investments.
Self-pulsing Characteristic of Hollow Cathode Discharge at Low Pressure Range in Argon

In order to increase the discharge stability and explore the mechanism of self-pulsing in hollow cathode discharge,the self-pulsing phenomenon was investigated in a cylindrical hollow cathode at low pressure in argon.The volt-ampere characteristics,the discharge images,and the time evolution of the current and voltage of self-pulsing were measured under different conditions.The influences of the gas pressure,the discharge current,and the external resistance on the self-pulsing were also studied.Results show that the self-pulsing can be observed in the negative differential resistance region of hollow cathode discharge.The pulse frequency ranges from several kilohertz to tens of kilohertz,and increases with the average current.It is determined mainly by the decay time of the current pulse.The external resistor in series has some influences on the discharge range where the self-pulsing exists.The self-pulsing can be created in a wider average current range as the resistance increasing.
Determinants of Dividend Policy in Nigerian Banks

The focus of this study was to provide research-basedevidence on the influence of certain variables on dividend policy using Nigerian banks. Specifically, the study examines the effects of profitability, firm size, leverage and previous levels of dividend payout on dividend policy. Using fifteen banks with data period spanning 2006-2013 and employing the fixed effects regression estimates, our results show the effect of profitability on dividend policy, we found that ROA is positive and significant at 5%. The positive sign as expected suggests that profitable firms will pay dividends. However, the possibility of an inverse relationship as observed for ROE is also likely in two scenarios; (i) In situations where less cash flow is expected in the future a firm pays less and (ii) where the firm has investment opportunities. Firm size (FSIZE) is positive and significant at 5%. Leverage (LEV) appeared negative and also significant in line with aprori expectation. Previous period dividend {DIV (-1)} is positive though not significant at 5%. The study recommends that no doubt companies have corporate incentives to engage in dividend announcements and since the market value responds favourably. However, the study recommends further especially for the benefits of potential investors that given the widespread abuse of Dividends amongst companies it is increasingly becoming difficult to distinguish between "good" and "bad" companies solely by depending on which is paying dividends and hence investors should also border to investigate the company's fundamentals. Original Research Article Dibia; ACRI, 15(2): 1-13, 2018; Article no.ACRI. 44463 2
IoT-Enabled Machine Learning for an Algorithmic Spectrum Decision Process

This paper investigates a data centric approach for future regulatory spectrum management (SM). Spectrum sensing data are collected by a spectrum environment awareness system built on a cloud-based service of Internet of Things. The data are used to characterize channel behaviors and establish a sharing predictor model which enables a set of efficient machine learning algorithms for automated spectrum sharing decision making. The performance of the decision process is evaluated, illustrating the feasibility and potential of this novel SM approach.
Are personas done? Evaluating their usefulness in the age of digital analytics

In this research, we conceptually examine the use of personas in an age of large-scale online analytics data. Based on the criticism and benefits outlined in prior work and by practitioners working with online data, we formulate the major arguments for and against the use of personas given real-time online analytics data about customers, analyze these arguments, and demonstrate areas for the productive employment of data-driven personas by leveraging online analytics data in their creation. Our key tenet is that data-driven personas are located between aggregated and individual customer statistics. At their best, digital data-driven personas capture the coverage of the customer base attributed to aggregated data representations while retaining the interpretability of individual-level analytics; they benefit from powerful computational techniques and novel data sources. We discuss how digital data-driven personas can draw from technological advancements to remedy the notable concerns voiced by scholars and practitioners, including persona validation, inconsistency problem, and long development times. Finally, we outline areas of future research of personas in the context of online analytics. We argue that to survive in the rapidly developing online customer analytics industry, personas must evolve by adopting new practices.
A comparison between large-size shaking table test results and numerical simulation of a subway station structure

Based on the results of the large-size shaking table test of a subway station structure built in liquable site,considering the influence of the soil-structure nonlinear dynamic interaction by 2D finite element methods,the seismic responses of the soil-subway station structure system under different test conditions are analyzed by using ABAQUS software. In the analysis model,dynamic visco-plastic memorial nested yield surface model is used to simulate the dynamic characteristics of soils,and the plastic-damage model is used to simulate the dynamic characteristics of station concrete.And then,the simulation results and the shaking table test records are compared in detail in this paper.The results show that the simulation results and the law of seismic responses of the soil-subway station structure system are basically identical with those of the shaking table test.So that,the analysis results and the shaking table test results are proved to be correct.
Automated taxiing for unmanned aircraft systems

Over the last few years, the concept of civil Unmanned Aircraft System(s) (UAS) has been realised, with small UASs commonly used in industries such as law enforcement, agriculture and mapping. With increased development in other areas, such as logistics and advertisement, the size and range of civil UAS is likely to grow. Taken to the logical conclusion, it is likely that large scale UAS will be operating in civil airspace within the next decade. Although the airborne operations of civil UAS have already gathered much research attention, work is also required to determine how UAS will function when on the ground. Motivated by the assumption that large UAS will share ground facilities with manned aircraft, this thesis describes the preliminary development of an Automated Taxiing System(ATS) for UAS operating at civil aerodromes. To allow the ATS to function on the majority of UAS without the need for additional hardware, a visual sensing approach has been chosen, with the majority of work focusing on monocular image processing techniques. The purpose of the computer vision system is to provide direct sensor data which can be used to validate the vehicle s position, in addition to detecting potential collision risks. As aerospace regulations require the most robust and reliable algorithms for control, any methods which are not fully definable or explainable will not be suitable for real-world use. Therefore, non-deterministic methods and algorithms with hidden components (such as Artificial Neural Network (ANN)) have not been used. Instead, the visual sensing is achieved through a semantic segmentation, with separate segmentation and classification stages. Segmentation is performed using superpixels and reachability clustering to divide the image into single content clusters. Each cluster is then classified using multiple types of image data, probabilistically fused within a Bayesian network. The data set for testing has been provided by BAE Systems, allowing the system to be trained and tested on real-world aerodrome data. The system has demonstrated good performance on this limited dataset, accurately detecting both collision risks and terrain features for use in navigation.
Assessing the long-term fragmentation of information systems research with a longitudinal multi-network analysis

ABSTRACT Over the decades, the evolving information systems (IS) research community and its academic output has greatly expanded. This paper offers an integrated analysis of multiple dimensions of network interconnectedness of the growing IS discipline. In line with the social and intellectual dimensions of the underlying theory of science, we synthesise multiple network views on authors, institutions, journal outlets, citations, and themes into a multi-dimensional knowledge network infrastructure analysis of collaborative networks of IS researchers and their academic output. We further introduce two fragmentation types to better address the dynamics of the IS discourse discussed in previous research. Based on a corpus of all 3587 AIS basket of 8 journal articles over 20 years, we use the analytical framework to study whether the fast growth of the IS discipline resulted in a reduced coherence of the overall academic collaboration and the research themes. The analysis reveals that the sampled IS researcher community developed a large core component with influential bridging people who mitigate fragmentation and centralisation. This IS community structure constitutes a valuable asset to cope with fragmentation tendencies in the intellectual dimension (research topics) resulting from many short-term topic bursts and from centralisation of conceptual terms.
Time Series Forecasting of Temperatures using SARIMA: An Example from Nanjing

Time series modelling and forecasting – a method that predicts future values by analysing past values - plays an important role in many practical fields. In this paper, we analyse the monthly mean temperature in Nanjing, China, from 1951 to 2017, using SARIMA (Seasonal Autoregressive Integrated Moving Average) techniques. Data from 1951 to 2014 are used as the training set, while data from 2015 to 2017 are used as the testing set. A detailed explanation of model selection and forecasting accuracy is presented. The results show that the proposed research approach obtains good forecasting accuracy.
Asynchronous Multisensor Data Fusion

Due to the reasons of sensors in itself and the communication delays, the research of the asynchronous multisensor data fusion problem is more practical than that of synchronous one. Firstly the continuous time system is discretiged in the fusion center and all the sensor nodes with different sample interval. Then the measurement noises are found to be correlated with each other and the process noise though the noises of the corresponding continuous time system are uncorrelated. Finally an asynchronous fusion algorithm is presented for the correlated noises case. Simulation results show the validity of the presented algorithm.
Scale Aware Deep Pedestrian Detection

In smart cities, traffic management is becoming a significant challenge owing to the rapid growth of population. In this regard, pedestrian detection and their safety are of the utmost importance for the city authorities. In this paper, a fully convolutional deep architecture is presented to detect pedestrians by automatically selecting the desired region proposals as well as learning the requisite feature representation with no need for any manual hand‐crafted feature design. The architecture facilitates end‐to‐end training and thereby improves the overall performance, eliminating the bottleneck caused by the multistage pipeline structure of conventional feature engineering. A state‐of‐the‐art deep framework, for general object detection, is suitably tailored for the task of pedestrian detection. A densely connected convolutional network is employed to learn the desired features. A two‐stage approach is proposed to separate the human‐look‐alike hard negative backgrounds from the true pedestrians. Besides, feature maps from multiple intermediate layers are taken into consideration to facilitate small‐scale detection. The proposed method alongside a few competent schemes is compared on the benchmark Caltech and INRIA datasets, where the log average miss rate is set as the performance metric. The obtained results demonstrate the potential of our approach in addressing the real‐world challenges.
Analysis of the Relationship between Managerial Competences and the Performance of Procurement Management Units in Public Sector: The Structural Equation Modelling Approach

Despite the importance of procurement management units in public procuring entities in Tanzania in terms of procurement functions conducted, the performance of this function is still poor and ineffective. This study focused on the analysis of the relationship of managerial competences in terms of managerial skills on the performance of procurement management unit in public procuring entities located in Dar es salaam and Dodoma regions. The structural equation model was used to explain the existing relationship between managerial competences (technical skills, communication skills, leadership skills, business skills and networking skills ) on the performance of procurement management unit (cost reduction, timely delivery and compliance of procurement rules and regulations. Results revealed that networking skills and leadership skills are significantly related to cost reduction, timely delivery and compliance of rules and regulations. Therefore, these are the key determinants of the performance of procurement management unit in public sectors. However, technical skills, business skills and communications skills are also significant related to cost reduction in public procuring entities whereby, communication skills are significantly related to timely delivery as the indicator of procurement performance in public procuring entities. Finally it was recommended that procurement and supplies managers should be well equipped with these managerial skills so as to improve the performance of procurement management units in terms of the conducted procurement functions in their respective public procuring entities in