Miracle-dz/UniFAR-FTUs huggingface dataset:
Technological innovativeness and information quality as neoteric predictors of users' acceptance of learning management system

PurposeThis study aims to expand the Unified Theory of Acceptance and Use of Technology (UTAUT2) by exploring the effect of two new predictors: technological innovativeness and information quality, along with the learning value and the original determinants that influence faculty and students’ acceptance of the Moodle-Learning Management System. The modified model includes nine predictors: performance expectancy, effort expectancy, social influence, facilitating conditions, learning value, hedonic motivation, habit, technological innovativeness and information quality.Design/methodology/approachThe study is based on a cross-sectional survey design. The target population was faculty and students of the University of Kufa in Iraq. An online questionnaire was used to collect 228 responses from faculty and 553 from students.FindingsResults of the Structural Equation Modeling (SEM) Partial Least Squares (PLS) analysis revealed that factors which influence faculty acceptance were social influence, facilitating conditions, hedonic motivation, habit, technological innovativeness and information quality, while factors which influence student acceptance were performance expectancy, facilitating conditions, learning value, hedonic motivation, habit, technological innovativeness and information quality.Originality/valueThe theoretical and practical contribution of the present study lies in the expansion of the UTAUT2 model through adding neoteric predictors, which are technological innovativeness and information quality. This study provides insights and further understanding of the effect of predictors (original and additive) on users’ acceptance of e-learning management system. In addition, the ﬁndings of the current study enable decision-makers and those interested in developing Moodle-LMS to obtain in-depth information on these indicators, especially in the Iraqi higher education environment.
Estimate of high-order linear system with identical design specifications

A novel technique for obtaining low-order estimates of a high-order linear system is proposed. This meets the need for a computationally efficient and conceptually simple algorithm which will yield an estimate of a high-order linear system appropriate for system design purposes. The proposed technique will guarantee that the commonly used system design specifications are identical for both plant and estimate. It overcomes the limitations of most of the existing methods at no additional cost in efficiency. <<ETX>>
Evaluation of CDRAD and TO20 test objects and associated software in digital radiography

Adequate reproduction of low contrast image detail is essential for accurate diagnosis in diagnostic radiology. Artinis CDRAD and Leeds Test Object TO20 are commercially available test objects that can be used to test this aspect of imaging performance in digital radiography. Automated analysis software is available for both test objects (CDRAD Analyser and AutoPIA (TO20)). This study evaluated and compared both test objects and software, including their sensitivity to changes in exposure parameters and image processing. Images of the test objects were acquired in scatter and scatter-free environments and analysed using a range of metrics derived from automated analysis, visual assessment and manual contrast-to-noise ratio measurements. The CNR (TO20) and correctly identified holes (%) (CDRAD) were found to be the most sensitive to changes in exposure conditions. The total number of detected discs (TO20) was the least sensitive. None of the image quality metrics was sensitive to a change in image processing. Other methods, such as anthropomorphic phantoms, would therefore be required to evaluate changes in clinical image processing. The results of this investigation help to inform best use of these test objects in routine quality control and image quality benchmarking for optimisation.
Asymptotic Analysis of RZF in Large-Scale MU-MIMO Systems Over Rician Channels

In this paper, we focus on the downlink ergodic sum rate of a single-cell large-scale multiuser MIMO system in which the base station employs <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> antennas to communicate with <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> single-antenna user equipments (UEs). A regularized zero-forcing (RZF) scheme is used for precoding under the assumption that each UE uses a specific power and each link forms a spatially correlated MIMO Rician fading channel. The analysis is conducted assuming that <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> grow large with a given ratio and perfect channel state information is available at the base station. New results from random matrix theory and large system analysis are used to compute an asymptotic expression of the signal-to-interference-plus-noise ratio as a function of system parameters, spatial correlation matrix, and Rician factor. Numerical results are used to validate the accuracy of asymptotic approximations in the finite system regime and to evaluate the performance under different operating conditions. It turns out that the asymptotic expressions provide accurate approximations even for relatively small values of <inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>.
Analytic Treatment of Deep Neural Networks Under Additive Gaussian Noise

Analytic Treatment of Deep Neural Networks Under Additive Gaussian Noise Modar M. Alfadly Despite the impressive performance of deep neural networks (DNNs) on numerous vision tasks, they still exhibit yet-to-understand uncouth behaviours. One puzzling behaviour is the reaction of DNNs to various noise attacks, where it has been shown that there exist small adversarial noise that can result in a severe degradation in the performance of DNNs. To rigorously treat this, we derive exact analytic expressions for the first and second moments (mean and variance) of a small piecewise linear (PL) network with a single rectified linear unit (ReLU) layer subject to general Gaussian input. We experimentally show that these expressions are tight under simple linearizations of deeper PL-DNNs, especially popular architectures in the literature (e.g. LeNet and AlexNet). Extensive experiments on image classification show that these expressions can be used to study the behaviour of the output mean of the logits for each class, the inter-class confusion and the pixel-level spatial noise sensitivity of the network. Moreover, we show how these expressions can be used to systematically construct targeted and non-targeted adversarial attacks. Then, we proposed a special estimator DNN, named mixture of linearizations (MoL), and derived the analytic expressions for its output mean and variance, as well. We employed these expressions to train the model to be particularly robust against Gaussian attacks without the need for data augmentation. Upon training this network on a loss that is consolidated with the derived output probabilistic moments, the network is not only robust under very high variance Gaussian attacks but is also as robust as networks that are trained with 20 fold data augmentation.
Phonemic Categorization and Phonotactic Repair as Parallel Sublexical Processes

Phonemic perception exhibits coarticulation sensitivity, phonotactic sensitivityand lexical sensitivity. Three kinds of models of speech perception are found in the literature, which embody different answers to the question of how the three kinds of sensitivity are related to each other:two-step models, one-step modelsandlexicalist models. In two-step models (Church, 1987), phonemes are first extracted, and phonotactic repairs are subsequently made on the obtained phoneme string; both phonemic categorization and phonotactic repair are sublexical, and coarticulation sensitivity should only affect initial (prephonotactic) phonemic categorization. In one-step models (Dehaene-Lambertz et al., 2000; Dupoux et al., 2011; Mehler et al., 1990), phonemic categorization and phonotactic repair are sublexical and simultaneous; phonotactic repairs themselves depend on coarticulation cues. Such models can be implemented in two different versions:suprasegmental matching, according to which a speech signal is matched against phonotactics-respecting suprasegmental units (such as syllables), rather than phonemes, and slot filling , according to which a speech signal is matched against phonemes as fillers for slotsin phonotactics-respecting suprasegmental units. In lexicalist models (Cutler et al., 2009; McClelland & Elman, 1986), coarticulation sensitivity and/or phonotactic sensitivity reduce to lexical sensitivity. McClelland & Elman (1986) claim a lexicalist reduction of phonotactic sensitivity; Cutler et al.’s (2009) make a claim implying lexicalist reductions both of phonotactic sensitivity and of coarticulation sensitivity.
Topic Tensor Network for Implicit Discourse Relation Recognition in Chinese

In the literature, most of the previous studies on English implicit discourse relation recognition only use sentence-level representations, which cannot provide enough semantic information in Chinese due to its unique paratactic characteristics. In this paper, we propose a topic tensor network to recognize Chinese implicit discourse relations with both sentence-level and topic-level representations. In particular, besides encoding arguments (discourse units) using a gated convolutional network to obtain sentence-level representations, we train a simplified topic model to infer the latent topic-level representations. Moreover, we feed the two pairs of representations to two factored tensor networks, respectively, to capture both the sentence-level interactions and topic-level relevance using multi-slice tensors. Experimentation on CDTB, a Chinese discourse corpus, shows that our proposed model significantly outperforms several state-of-the-art baselines in both micro and macro F1-scores.
Analysis of Service Innovation Performance in Turkish Banking Sector Using a Combining Method of Fuzzy MCDM and Text Mining

The purpose of the study is to examine the effecting factors for new service development capabilities in Turkish banking sector and to evaluate the performance of the banks in listed BIST based on the service innovation performance. The novelty of the study is to employ a two-step analysis considering the data mining and the hybrid MCDM respectively. The method is applied by using the data mining for extracting the literature based-criteria of service innovation. Accordingly, the fuzzy AHP is computed for weighting the criteria and the fuzzy TOPSIS is considered to rank the banks based on the service innovation performance. The results demonstrate that the service conditions for the customers are the most important factor in the service innovation performance while the employees are weakly considered to evaluate the new service development. Additionally, the private banks have both the best and worst degrees in the performance results. These results show that private banks don’t have the standardized qualifications due to their changing market shares.
RADICALLY REDESIGNING INTRODUCTORY MIS LARGE-SCALE LECTURES: CREATING ENHANCED LEARNING ENVIRONMENTS

: Traditional introductory Management Information Systems (MIS) large-scale lecture course models include a textbook, PowerPoint slides, and electronic files of exam questions utilized for assessing students’ understanding of the topics. Today’s Business professionals are required to think critically and apply explicit and tacit knowledge. The MIS department recognized that this traditional large-scale lecture format was not sustaining student engagement and it was evident that students were not developing these critical business skills when MIS professors were prescribing to the traditional textbook methodologies. The MIS Department revisited the traditional large-scale lecture-based format and created a new classroom curriculum centered on Activity Based Learning and conceptualized an Active Learning Funnel incorporating three dimensions: Technology, Content and Activity which form an Enhanced Learning Environment.
Automatic aspect extraction in information retrieval diversity

In this master thesis we describe a new automatic aspect extraction algorithm by incorporating relevance information to the dynamics of the Probabilistic Latent Semantic Analysis. An utility-biased likelihood statistical framework is described to formalize the incorporation of prior relevance information to the dynamics of the algorithm intrinsically. Moreover, a general abstract algorithm is presented to incorporate any arbitrary new feature variables to the analysis. A tempering procedure is inferred for this general algorithm as an entropic regularization of the utility-biased likelihood functional and a geometric interpretation of the algorithm is described, showing the intrinsic changes in the information space of the problem produced when different sources of prior utility estimations are provided over the same data. The general algorithm is applied to several information retrieval, recommendation and personalization tasks. Moreover, a set of post-processing aspect filters is presented. Some characteristics of the aspect distributions such as sparsity or low entropy are identified to enhance the overall diversity attained by the diversification algorithm. Proposed filters assure that the final aspect space has those properties, thus leading to better diversity levels. An experimental setup over TREC web track 09-12 data shows that the algorithm surpasses classic pLSA as an aspect extraction tool for the search diversification. Additional theoretical applications of the general procedure to information retrieval, recommendation and personalization tasks are given, leading to new relevanceaware models incorporating several variables to the latent semantic analysis. Finally the problem of optimizing the aspect space size for diversification is addressed. Analytical formulas for the dependency of diversity metrics on the choice of an automatically extracted aspect space are given under a simplified generative model for the relation between system aspects and evaluation true aspects. An experimental analysis of this dependence is performed over TREC web track data using pLSA as aspect extraction algorithm. ACM Computing Classification System. H.3. 3 [Search and Retrieval]: retrieval models, relevance feedback I.2. 7 [Natural Language Processing]: Language models.
Fault detection in level and flow rate sensors for safe and performant remote-control in a water supply system

This work presents an algorithm for real-time fault detection in the SCADA system of a modern water supply system (WSS) in an Italian alpine valley. By means of both hardware and analytical redundancy, the proposed algorithm compares data and isolates faults on sensors through analysis of residuals. Moreover, the algorithm performs a real-time selection of the most reliable measurements for the automated control of the WSS operations. A coupled model of the hydraulic and remote-control system is developed to test the performance of the WSS when the proposed algorithm is applied or not. Simulations show that the occurrence of errors in the sensors causes significant worsening in the economic, energy and mechanical performance of the infrastructure. In many cases, the operations of the WSS are seriously compromised. The error detection and measurement assessment performed by the proposed algorithm proves to be crucial for the safe control of the WSS.
Communications of the Association for Information Systems

Discussants play an important role in conferences, yet little practical advice exists to help them make best use of their time beyond informal guidelines. Two new approaches to the intellectual discussion of conference papers are introduced: Group Support Systems and Conversational Learning. The discussant’s role is illustrated with reference to each of these approaches. Recommendations for discussant practice are presented
Impact of IT offerings strategies and IT integration capability on IT vendor value creation

ABSTRACT While IT integration is recognised as an important capability, the mechanisms through which it creates value and the contingencies that delimit its effectiveness are unclear – particularly, in the case of firms that deliver solutions embodying both products and services. We focus on IT vendors to investigate the effectiveness of IT integration capability with respect to three aspects of IT solution offerings: breadth, modularity and customisation. We find a complementarity effect between IT integration capability and management of the IT offer strategy: IT integration is fundamental regardless of whether the firm relies on customisation or a broad set of heterogeneous knowledge bases. However, when IT vendors adopt a modular design strategy, IT integration is made redundant and can be counterproductive.
Energy-efficient routing protocol based on sink mobility for wireless sensor networks

Recently, many routing protocols have been implemented to accomplish progress in the energy consumption field for data collecting wireless sensor networks. Owing to the existence of many drawbacks for employing a static sink, this study utilises the idea of moving the sink node to achieve amelioration in energy utilisation and provide longer network lifetime. The idea of the proposed protocol depends on combining the mobile sink improved energy-efficient power-efficient gathering in sensor information system-based routing protocol (MIEEPB) with the direct transmission (DT) protocol to utilise the limited energy of wireless sensors efficiently. As the motorised movement of the sink is operated by petrol or electricity, the data loss through the transition of this sink from its current location to the next location must be diminished by restricting the moving distance. In the proposed protocol, the mobile sink must spend at least a certain amount of time (sojourn time) at each of its sojourn locations to avoid overhead. Extensive analysis was implemented on the proposed protocol (called MIEEPB-DT) to appraise and compare it with MIEEPB and DT. Simulation results show that the proposed MIEEPB-DT protocol gives better improvement in energy efficiency and network lifetime than both MIEEPB and DT.
OUTCOME OF NEONATES VENTILATED IN NICU OF A TERTIARY CARE HOSPITAL AND FACTORS ASSOCIATED WITH POOR OUTCOME

Objective: To ascertain the outcome of neonates who are ventilated for various reasons in our Neonatal Intensive Care Unit (NICU) and determine the risk factors associated with increased incidence of adverse outcome.Study Design: Retrospective study.Place and Duration of Study: Neonatal Intensive Care Unit of Combined Military Hospital Rawalpindi from Jul2016 to Dec 2016.Material and Methods: All neonates who received mechanical ventilation during the study period were included in the study.Results: Total sixty seven (35.8% females and 64.15% males) neonates were ventilated during the study period for various reasons. Of these 67 neonates who were ventilated, 35 (52.23%) died and 32 (47.76%) survived to be discharged home. 10 babies were born less than 28+ 0weeks gestation and all (100%) expired. Of 7 babies born between 28+1-31+6 weeks gestation, only 01 (14.28%) survived. Of 50 newborns between 32+0-36+6 weeks, 20 (40%) died and 30 (60%) survived to be discharged home.In our cohort of ventilated babies, 7 weighed less than 1000 gm of which 6 (85.71%) died and only 01 (14.28%) survived. Of 18 babies born 1000-1499 gm, 14 (77.77%) died and 4 (22.22%) survived. Of 14 babies born between 1500-2499 gm, 6 (42.85%) died and 8 (57.14%) survived. Of all ventilated babies, 28 weighed more than 2500 gm, of which 10 (35.71%) died and 18 (64.28%) survived.Out of our cohort of 67 babies, 14 were diagnosed with hypoxic ischemic encephalopathy grade 3, of which 11 (78.57%) died and 3 (21.42%) were discharged. Twenty three had RDS, of which 11 (47.82%) died and 12 (52.17%) survived. Ten babies were ventilated due to sepsis, of which 6 (60%) died and 4 (40%) survived.Conclusion: We conclude that gestational age less than 32+0 weeks, birth weight less than 1500 gm, HypoxicIschemic Encephalopathy grade 3 and sepsis are associated with a poor outcome in babies who are mechanically ventilated.
Identity, Power, and Representation in Virtual Environments

The proliferation of immersive, three dimensional virtual environments presents educators with a moment of creative possibility in designing the next generation of computer­assisted learning. At the same time, the fact that these environments may be inscribed with particular value sets and power relations presents educators with a burden of pedagogical responsibility. This paper attempts to begin a conversation about some of the hidden considerations that may be confronted as virtual learning environments become more accessible, acceptable, and assessable. The author challenges the view that virtual environments are reliably neutral venues for the creation of virtual identities that escape the culturally constructed power configurations of the offline world. Indeed, the very dichotomy between real and virtual is itself questionable. While the promise of virtual learning environments is real, it is often unrealized. Educators have a responsibility to critically engage the implicit assumptions embedded in the technology they would ask students to use.
Biometric watermarking via wavelet approach, reverse engineering in info-security and dematerialization of public administration

Abstract This research wants to present a highly-performing system to establish the intellectual property of a file by using advanced Information Fusion (IF) techniques. IF is different depending on the fact that it can be a textual file, an image or multimedial; indeed, the further step consists in creating blue biometric codes with different watermarking mechanisms based on wavelet and wavelet packet respectively. Thanks to reverse engineering algorithms which this work have generated, such a system seems particularly appropriate to contexts like Public Administration or production companies which present complex industrial/documental processes where it is relevant to trace the access to information, and the sequence of accesses made by operators/users. Hence it seems also clear that such a system can be useful for all that concerns files/contents distributed online for what regards both the intellectual property and the access/modification/use of information.