Miracle-dz/UniFAR-FTUs huggingface dataset:
High Dimensional Separable Representations for Statistical Estimation and Controlled Sensing

High Dimensional Separable Representations for Statistical Estimation and Controlled Sensing by Theodoros Tsiligkaridis Chair: Alfred O. Hero III Separable approximations are effective dimensionality reduction techniques for high dimensional data. The statistical estimation performance of separable models is largely unexplored in high dimensions and model mismatch errors need to be accurately controlled. The need for performance bounds associated with statistical estimators in sample starved settings has been a topic of great interest in the field of signal processing and high-dimensional statistics. Many signal processing methods, including classical filtering, prediction and detection, are intimately linked to the data covariance. In multiple modality and spatio-temporal signal processing, separable models for the underlying covariance may be exploited for dimensionality reduction, improved estimation accuracy and reduction in computational complexity. In controlled sensing (or inference), estimation performance can be greatly optimized at the expense of query design (or control). Query-based multisensor controlled sensing systems used for target localization consist of a set of sensors (possibly heterogeneous and of different modality) that collaborate (through a fusion center or
Grid Service Specification

Building on both Grid and Web services technologies, the Open Grid Services Architecture (OGSA) defines mechanisms for creating, managing, and exchanging information among entities called Grid services. Succinctly, a Grid service is a Web service that conforms to a set of conventions (interfaces and behaviors) that define how a client interacts with a Grid service. These conventions, and other OGSA mechanisms associated with Grid service creation and discovery, provide for the controlled, fault resilient, and secure management of the distributed and often long-lived state that is commonly required in advanced distributed applications. In a separate document, we have presented in detail the motivation, requirements, structure, and applications that underlie OGSA. Here we focus on technical details, providing a full specification of the behaviors and Web Service Definition Language (WSDL) interfaces that define a Grid service.
Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain

Recently, the applications of Blockchain technology have begun to revolutionise different aspects of supply chain (SC) management. Among others, Blockchain is a platform to execute the smart contracts in the SC as transactions. We develop and test a new model for smart contract design in the SC with multiple logistics service providers and show that this problem can be presented as a multi-processor flexible flow shop scheduling. A distinctive feature of our approach is that the execution of physical operations is modelled inside the start and completion of cyber information services. We name this modelling concept ‘virtual operation’. The constructed model and the developed experimental environment constitute an event-driven dynamic approach to task and service composition when designing the smart contract. Our approach is also of value when considering the contract execution stage. The use of state control variables in our model allows for operations status updates in the Blockchain that in turn, feeds automated information feedbacks, disruption detection and control of contract execution. The latter launches the re-scheduling procedure, comprehensively combining planning and adaptation decisions within a unified methodological framework of dynamic control theory. The modelling complex developed can be used to design and control smart contracts in the SC.
Initial Empirical Testing of Potential Factors Contributing to Patient Use of Secure Medical Teleconferencing

ABSTRACT Providing timely and cost-effective healthcare appears to be significantly desired. Factors such as computer skills and comprehension of instructions impact people’s perception of the accessibility of such alternatives, especially for medical professionals. There are limited studies examining the aforementioned factors in information systems (IS) literature in the context of medical teleconferencing (ehealth) from the patients’ perspective. Thus, the purpose of this research study was to examine the underlying structure of four factors, namely IS usage (ISU), computer self-efficacy (CSE), ethical severity of misusing IS (ESMIS), and the resistance to use IS (RESUIS). Based on data gathered from 140 participants, confirmatory factor analysis (CFA) was conducted, using the partial least squares (PLS) technique. Results indicated a very strong validity and reliability of the constructs, however, with a relatively low overall model predictability. Furthermore, the constructs of CSE and RESUIS appear to demonstrate significant contribution toward ISU.
Analysis of cluster center initialization of 2FA‐kprototypes analogy‐based software effort estimation

Analogy‐based estimation is one of the most widely used techniques for effort prediction in software engineering. However, existing analogy‐based techniques suffer from an inability to correctly handle nonquantitative data. To deal with this limitation, a new technique called 2FA‐kprototypes was proposed and evaluated. 2FA‐kprototypes is based on the use of the fuzzy k‐prototypes clustering technique. Although fuzzy k‐prototypes algorithms are well known for their efficiency in clustering numerical and categorical data, they are sensitive to the selection of initial cluster centers. In this paper, the impact of cluster center initialization on improving the prediction accuracy of 2FA‐kprototypes was analyzed and discussed using two cluster initialization techniques: centrality‐based initialization and density‐based initialization. The performance of 2FA‐kprototypes using these two initialization techniques was evaluated and compared with that of 2FA‐kprototypes using random initialization over four datasets: ISBSG, COCOMO81, USP05‐FT, and USP05‐RQ. The results showed an improvement in the performance of 2FA‐kprototypes in terms of estimation accuracy when the all‐in method is used.
A method to measure small local strains in concrete surfaces using its natural texture and image cross‐correlation

This paper proposes a method to measure the displacement of every point on a concrete surface using its original surface texture and digital image cross‐correlation (DICC). The main advantage is that it does not need to add or attach any particular pattern or target to the surface, contrary to the current methods based in DICC. The method is tested in a concrete probe during loading–unloading cycles under its yield limit, with no cracks appearing in the surface. The total surface of the probe was tessellated in optimal local areas, and DICC with peak refinement was performed on each local area. In order to find the optimal size for that areas, we propose here a method based on the image local entropy. We show that, with natural nonoptimized textures, the proposed technique allows to locally measure the concrete deformation due to small strains (<0.1%) with an error below 50 με. Although results are more inaccurate than those obtained by a strain gauge, our method is able to noninvasively determine the strains in a concrete surface under small loads with reasonable accuracy, thus allowing its use in unreachable or historical structures where no attachment or target painting is possible.
Pedological Classification Of Soils Along A Toposequence In Faculty Of Agriculture Shabu-Lafia Campus, Nasarawa State University Keffi, Nigeria.

This study was conducted along a toposequence in faculty of agriculture Nasarawa State University Shabu-Lafia Campus (8° 33' 22.07'' N and 8° 34' 00.49'' N and longitude 8°32' 37.63'' E and 8° 33' 14.07'' E) Nigeria. Digital Elevation Model (DEM) of the study site was developed using Google earth map and GIS software (Arch GIS 10.3 version) and the site was divided into three slope classes (upper, middle and lower). Morphologically the upper and middle slope soils were deep (200 cm) and well drained while lower slope soils was moderately deep (90 cm) and poorly drained. Soil colour ranged from 10YR3/4, 10YR4/4 and 5YR5/1 in the surface horizons of upper, middle and lower slope landscape position to 2.5YR4/8, 7.5YR7/8 and 2.5YR6/1 in the underlying horizons. Bulk density values across the study area were generally high (1.52-1.62 gcm -3 ) and sand dominated the particle size fraction (648-848 gkg -1 ), then Clay (98-278 gkg -1 ) and finally silt. Soil reaction (pH) varied as strongly acid to moderately acid (4.67-5.73) and the soils were non saline (3.1-1.0 dSm -1 ), Ca dominated the exchangeable bases and were in the order Ca > Mg > K > Na, CEC were low across the three landscape position and percentage base saturation were high (73.080 %). Available P were generally high (36.1-28.8 mgkg -1 ), OC were moderate (10.1-14.0 gkg -1 ), TN were moderate too (2.1-2.8 gkg -1 ). The soils were classified as Typic Endoustalfs and Typic Endoaquents according to USDA Taxonomy while Haplic Acrisols (skeletic, Eutric) and Haplic Gleysols (Eutric, Colluvic) according to WRB.
Flexible Gait Enhancing Mechatronics System for Lower Limb Assistance (GEMS L-Type)

This paper presents a novel wearable walking assistance device for the elderly, designed to aid them in their physical gait. In compliance with human motion and the human body, the device not only fits tightly to the lower body of a wearer, but also transmits the assisting torque to the hip/knee joint efficiently and comfortably. To overcome the poor wearability and assistive performance of conventional wearable walking assistance devices, three novel mechanisms are proposed: first, a dual reduction actuator, which makes the mechanism more compact with minimal resistance, second, compliant joints, which adapt to human motion regardless of the wearing state, wearing position, and three-dimensional human joint motions, and third, a flexible foot/ankle mechanism, which helps in rigidly transmitting the assisting force only to the forefoot. The developed wearable walking assistance device based on these mechanisms was validated through experiments.
Data Reuse and Users’ Trust Judgments: Toward Trusted Data Curation

Ayoung Yoon: Data Reuse and Users’ Trust Judgments: Toward Trusted Data Curation (Under the direction of Dr. Helen R. Tibbo) Data reuse refers to the secondary use of data—not for its original purpose but for studying new problems. Although reusing data might not yet be the norm in every discipline, the benefits of reusing shared data have been asserted by a number of researchers, and data reuse has been a major concern in many disciplines. Assessing data for its trustworthiness becomes important in data reuse with the growth in data creation because of the lack of standards for ensuring data quality and potential harm from using poor-quality data. This dissertation aims to explore many facets of data reusers’ trust in data generated by other researchers, focusing on user-defined trust attributes and the judgment process with influential factors that determine these attributes. Because trust is a complex concept that is explored in multiple disciplines, this study developed a theoretical framework from an extensive literature review in the areas of sociology, social psychology, information, and information systems. This study takes an interpretive qualitative approach by using in-depth semi-structured interviews as the primary research method. The study population comprises reusers of quantitative social science data from public health and social work—the primary disciplines with data reuse cultures. By employing purposive sampling, a total of 38 participants were recruited.
Diagnosing Various Severity Levels of Congestive Heart Failure Based on Long-Term HRV Signal

Previous studies have attempted to find autonomic differences of the cardiac system between the congestive heart failure (CHF) disease and healthy groups using a variety of algorithms of pattern recognition. By comparing previous literature, we have found that there are two shortcomings: 1) Previous studies have focused on improving the accuracy of models, but the number of features used has mostly exceeded 10, leading to poor generalization performance; 2) Previous works rarely distinguish the severity levels of CHF disease. In order to make up for these two shortcomings, we proposed two models: model A was used for distinguishing CHF patients from the normal people; model B was used for diagnosing the four severity levels of CHF disease. Based on long-term heart rate variability (HRV) (40000 intervals–8h) signals, we extracted linear and non-linear features from the inter-beat-interval (IBI) series. After that, the sequence forward selection algorithm (SFS) reduced the feature dimension. Finally, models with the best performance were selected through the leave-one-subject-out validation. For a total of 113 samples of the dataset, we applied the support vector machine classifier and five HRV features for CHF discrimination and obtained an accuracy of 97.35%. For a total of 41 samples of the dataset, we applied k-nearest-neighbor (K = 1) classifier and four HRV features for diagnosing four severity levels of CHF disease and got an accuracy of 87.80%. The contribution in this work was to use the fewer features to optimize our models by the leave-one-subject-out validation. The relatively good generalization performance of our models indicated their value in clinical application.
Creating Customer-Centric Organizations: The Value of Design Artefacts

Abstract More organizations are adopting customer-centric innovation practices to increase business value; however, very little is known about the factors driving customer-centric innovation or the conditions under which innovation succeeds. Similarly, very little is known about the role of design artefacts as inputs in customer-centric innovation processes or as instruments that support the organizational change required for successful change. A practice-led case study was conducted to examine the role of design artefacts and to demonstrate how they are flexible and persuasive tools that mediate the social and intertwined demands of customer-centric innovation strategies. Five distinct roles of design artefacts are proposed and their value in contributing to innovation and organizational change are considered.
Monocular Visual-IMU Odometry: A Comparative Evaluation of Detector–Descriptor-Based Methods

Monocular visual-inertial measurement unit (IMU) odometry has been widely used in various intelligent vehicles. As a popular technique, detector–descriptor-based visual-IMU odometry is effective and efficient due to the fact that local descriptors are robust against occlusions, background clutter, and abrupt content changes. However, to our knowledge, there is not a comprehensive and comparative evaluation study on the performance of different combinations of detectors and descriptors recently developed. In order to bridge this gap, we conduct such a comparative study in a unified framework. In particular, six typical routes with different lengths, shapes, and road scenes are selected from the well-known KITTI dataset. We first evaluate the performance of different combinations of salient point detectors and local descriptors using the six routes. Then, we tune the parameters of the best detector or descriptor obtained for each route, to further augment the results. This paper provides not only comprehensive benchmarks for assessing various algorithms but also instructive guidelines and insights for developing detectors and descriptors to handle different road scenes.
The Determinants of Adoption of Cloud-Based ERP of Nigerian's SMES Manufacturing Sector Using Toe Framework and Doi Theory

Adoption factors relating to enterprise resource planning (ERP) have been studied quite extensively over the years. Most of the earlier studies on cloud ERP have focused only on technical and operational issues. A few studies have addressed the adoption of cloud ERP from the user's perspective, mostly assessing the effects of the innovation characteristics or the contextual factors. Very few studies to date have conducted a holistic evaluation of both the direct and indirect effects of the determinants on cloud ERP adoption in manufacturing SMEs. Therefore, this study aims to explore and gain an understanding of the determinants of adoption factors for cloud ERP and its relative advantage to small and medium enterprises (SME) organisations. The manufacturing SMEs in Nigeria are specifically targeted. This study also seeks to develop a research model that integrates the innovation characteristics and technology-organisation-environment (TOE) perspectives that underlie its adoption.
Sick building symptoms among hospital workers associated with indoor air quality and personal factors

This study assesses the interior air quality and infective factors in a hospital in Turkey to provide data about air quality to protect hospital workers. This study measured indoor air quality in eight different locations in a hospital, including particulate matter (PM2.5 and PM1), carbon dioxide, carbon monoxide, temperature, humidity and microbiological matter. The highest PM2.5 and PM1 concentrations were in emergency service, and the highest CO2 was measured in the paediatric clinic. The poor interior air quality results are the most important cross-sectional data. For all participants, the prevalence of eye, upper respiratory tract, lower respiratory tract, skin and non-specific sick building syndrome symptoms were 23.0%, 40.7%, 22.5%, 36.3% and 63.7%, respectively. When sick building syndrome symptoms and environmental factors were investigated, skin symptoms increased 1.82 times in areas with stagnant air flow (p = 0.046; OR = 1.823; 95% CI: 1.010–3.290). Non-specific symptoms increased 2.17 times in locations with dry indoor air (p = 0.039; OR = 2.176; 95% CI: 1.041–4.549). Hospital workers are exposed to conditions that may increase the risk of a variety of sick building syndrome symptoms. Although the air quality measurements were not above the recommended limits in the hospital, long-term exposures should be considered for those experiencing sick building syndrome-related symptoms.
Large-eddy simulations of high Reynolds number jets with a suitable subgrid-scale model for solver dependency study

Large-eddy simulations are performed of a turbulent round jet at Ma=0.5 and 0.9. The solver dependency is explored on computationally affordable grids of 5 and 20 million grid points, by taking advantage of the consistency of the subgrid-scale σ -model. Three different solvers are tested. With all three, the computed mean and second-order fluctuating quantities of the turbulent near field compare favorably with measurements, for both Mach numbers and both grids, showing the strength of the σ -model in adapting to different flow conditions and grid refinements.
The Effect Of Placement And Work Load On Work Motivation And Its Impact On Employee Work Performance At Labor And Population Mobility Agency Of Aceh Province, Indonesia

The purpose of this study was to determine the effect of placement and work load on employee work motivation in labor and population mobility department of Aceh. With a total population of 270 people and a total sample of 161 people, where the sample is obtained by reference to a number of Slovin formula that taken by stratified random sampling technique. The data analysis tool used is Path Analysis. Value of the correlation coefficient (R) of 0.815 in this study in which the value is a relationship between the independent variable with the dependent variable of 81.5% meaning that placement and work load related to work motivation and work performance of the employees in labor and population mobility of Aceh. Meanwhile, the coefficient of determination (R 2 ) obtained a value of 0.663 means that 66.3% of the changes in the dependent variable (work motivation and work performance) can be explained by the factors of placement and work load. The placement and work load just could not increase the employee work motivation, but it can be increase the work performance through work motivation. The results of statistical calculations both partially and simultaneously showed that placement, work load and work motivation have a significant effect on employee work performance in labor and population mobility department
State Feedback Control for a PM Hub Motor Based on Gray Wolf Optimization Algorithm

This paper presents an optimal control strategy for a permanent-magnet synchronous hub motor (PMSHM) drive using the state feedback control method plus the gray wolf optimization (GWO) algorithm. First, the linearized PMSHM mathematical model is obtained by voltage feedforward compensation. Second, to acquire satisfactory dynamics of speed response and zero d-axis current, the discretized state-space model of the PMSHM is augmented with the integral of rotor speed error and integral of d-axis current error. Then, the GWO algorithm is employed to acquire the weighting matrices Q and R in linear quadratic regulator optimization process. Moreover, a penalty term is introduced to the fitness index to suppress overshoots effectively. Finally, comparisons among the GWO-based state feedback controller (SFC) with and without the penalty term, the conventional SFC, and the genetic algorithm enhanced proportional–integral controllers are conducted in both simulations and experiments. The comparison results show the superiority of the proposed SFC with the penalty term in fast response.
Low-profile Slotted SIW Cavity Backed Antenna for Frequency Agility

The agile frequency antennas are widely used for wireless communication systems. This paper studies and designs a low-profile SIW antenna radiating from a circular slot graved in the ground plane, with the ability of alternating the frequency. The antenna is intentionally designed within a range of 1.8 GHz to 2.18 GHz obtained by varying the DC bias voltages from 0 to 26 V, which is able to cover the GSM1800, the LTE, and the UMTS wireless standards. The tuning technique consists in the integration of two varactor diodes across the circular slot. A prototype was manufactured, and the experiment results correspond well to those of the simulations.
On-the-Fly Machine Learning for Improving Image Resolution in Tomography

In tomography, the resolution of the reconstructed 3D volume is inherently limited by the pixel resolution of the detector and optical phenomena. Machine learning has demonstrated powerful capabilities for super-resolution in several imaging applications. Such methods typically rely on the availability of high-quality training data for a series of similar objects. In many applications of tomography, existing machine learning methods cannot be used because scanning such a series of similar objects is either impossible or infeasible. In this paper, we propose a novel technique for improving the resolution of tomographic volumes that is based on the assumption that the local structure is similar throughout the object. Therefore, our approach does not require a training set of similar objects. The technique combines a specially designed scanning procedure with a machine learning method for super-resolution imaging. We demonstrate the effectiveness of our approach using both simulated and experimental data. The results show that the proposed method is able to significantly improve resolution of tomographic reconstructions.