Usability framework for mobile augmented reality language learning

After several decades since its introduction, the existing ISO9241-11 usability framework is still vastly used in Mobile Augmented Reality (MAR) language learning. The existing framework is generic and can be applied to diverse emerging technologies such as electronic and mobile learning. However, technologies like MAR have interaction properties that are significantly unique and require different usability processes. Hence, implementing the existing framework on MAR can lead to non-optimized, inefficient, and ineffective outcomes. Furthermore, state-of-the-art analysis models such as machine learning are not apparent in MAR usability studies, despite evidence of positive outcomes in other learning technologies. In recent MAR learning studies, machine learning benefits such as problem identification and prioritization were non-existent. These setbacks could slow down the advancement of MAR language learning, which mainly aims to improve language proficiency among MAR users, especially in English communication. Therefore, this research proposed the Usability Framework for MAR (UFMAR) that addressed the currently identified research problems and gaps in language learning. UFMAR introduced an improved data collection method called Individual Interaction Clustering-based Usability Measuring Instrument (IICUMI), followed by a machine learning-driven analysis model called Clustering-based Usability Prioritization Analysis (CUPA) and a prioritization quantifier called Usability Clustering Prioritization Model (UCPM). UFMAR showed empirical evidence of significantly improving usability in MAR, capitalizing on its unique interaction properties. UFMAR enhanced the existing framework with new abilities to systematically identify and prioritize MAR usability issues. Through the experimental results of UFMAR, it was found that the IICUMI method was 50% more effective, while CUPA and UCPM were 57% more effective than the existing framework. The outcome through UFMAR also produced 86% accuracy in analysis results and was 79% more efficient in framework implementation. UFMAR was validated through three cycles of the experimental processes, with triangulation through expert reviews, to be proven as a fitting framework for MAR language learning

Quantitative 3D analysis of complex single border cell behaviors in coordinated collective cell migration

Understanding the mechanisms of collective cell migration is crucial for cancer metastasis, wound healing and many developmental processes. Imaging a migrating cluster in vivo is feasible, but the quantification of individual cell behaviours remains challenging. We have developed an image analysis toolkit, CCMToolKit, to quantify the Drosophila border cell system. In addition to chaotic motion, previous studies reported that the migrating cells are able to migrate in a highly coordinated pattern. We quantify the rotating and running migration modes in 3D while also observing a range of intermediate behaviours. Running mode is driven by cluster external protrusions. Rotating mode is associated with cluster internal cell extensions that could not be easily characterized. Although the cluster moves slower while rotating, individual cells retain their mobility and are in fact slightly more active than in running mode. We also show that individual cells may exchange positions during migration

Ultra-wideband and off-optimised five-port reflectometer using power splitters

This paper presents an ultra-wideband (UWB) and off-optimised Five-Port Reflectometer (FPR) configured by power splitters. The proposed non-multi-state FPR is characterised and realised for complex reflection coefficient determinations. The measurement system can be easily setup using commercial power splitters, three detectors and a microwave source. The transmission lines method is used as calibration standard for FPR measurement system. Both the FPR setup and the transmission lines are characterised with a Vector Network Analyser prior to be used for the off-optimised measurement system. The results show good agreement between actual and calculated reflection coefficient for frequency range of 0.1 to 40 GHz. This novel FPR setup provides a simple, cost effective and accurate alternative in measuring broadband complex reflection coefficient

Imbalanced Classification Methods for Student Grade Prediction : A Systematic Literature Review

Student success is essential for improving the higher education system student outcome. One way to measure student success is by predicting students’ performance based on their prior academic grades. Concerning the significance of this area, various predictive models are widely developed and applied to help the institution identify students at risk of failure. However, building a high-accuracy predictive model is challenging due to the dataset’s imbalanced nature, which caused biased results. Therefore, this study aims to review the existing research article by providing a state-of-the-art approach for handling imbalanced classification in higher education, including the best practices of dataset characteristics, methods, and comparative analysis of the proposed algorithms, focusing on student grade prediction context problems. The study also presents the most common balancing methods published from 2015 to 2021 and highlights their impact on resolving imbalanced classification in three approaches: data-level, algorithm-level, and hybrid-level. The survey results reveal that the data-level approach using SMOTE oversampling is broadly applied in determining imbalanced problems for student grade prediction. However, the application of hybrid and feature selection methods supporting the generalization of the predictive model to boost student grade prediction performance is generally lacking. Other than that, some of the strengths and weaknesses of the proposed methods are discussed and summarized for the direction of future research. The outcomes of this review will guide the professionals, practitioners, and academic researchers in dealing with imbalanced classification, mainly in the higher education field

Exploration of Road Traffic Tweets for Congestion Monitoring

Online social network services such as Twitter and Facebook have gained popularity in recent years with continuous increase of users. This is especially true for Twitter, a popular micro-blogging service that enables users to send tweets which contain valuable data in real-time. Real-time tweets information can be used in many areas and one of the least explored areas is crowdsourcing of road traffic conditions. We have found that not many people tweet about traffic conditions; however, there are formal sources that keep their accounts updated with the latest traffic info. In this paper, we present an analysis of tweets that are related to the traffic conditions in Malaysia. Detailed analysis was conducted to understand the structures and the nature of the traffic tweets. Based on our analysis, we found that the real-time nature of the tweets is useful in reporting road traffic conditions and such information will be useful to the road-user

Maritime threat response

This report was prepared by Systems Engineering and Analysis Cohort Nine (SEA-9) Maritime Threat Response, (MTR) team members.Background: The 2006 Naval Postgraduate School (NPS) Cross-Campus Integrated Study, titled “Maritime Threat Response” involved the combined effort of 7 NPS Systems Engineering students, 7 Singaporean Temasek Defense Systems Institute (TDSI) students, 12 students from the Total Ship Systems Engineering (TSSE) curriculum, and numerous NPS faculty members from different NPS departments. After receiving tasking provided by the Wayne E. Meyer Institute of Systems Engineering at NPS in support of the Office of the Assistant Secretary of Defense for Homeland Defense, the study examined ways to validate intelligence and respond to maritime terrorist attacks against United States coastal harbors and ports. Through assessment of likely harbors and waterways to base the study upon, the San Francisco Bay was selected as a representative test-bed for the integrated study. The NPS Systems Engineering and Analysis Cohort 9 (SEA-9) Maritime Threat Response (MTR) team, in conjunction with the TDSI students, used the Systems Engineering Lifecycle Process (SELP) [shown in Figure ES-1, p. xxiii ] as a systems engineering framework to conduct the multi-disciplinary study. While not actually fabricating any hardware, such a process was well-suited for tailoring to the team’s research efforts and project focus. The SELP was an iterative process used to bound and scope the MTR problem, determine needs, requirements, functions, and to design architecture alternatives to satisfy stakeholder needs and desires. The SoS approach taken [shown in Figure ES-2, p. xxiv ]enabled the team to apply a systematic approach to problem definition, needs analysis, requirements, analysis, functional analysis, and then architecture development and assessment.In the twenty-first century, the threat of asymmetric warfare in the form of terrorism is one of the most likely direct threats to the United States homeland. It has been recognized that perhaps the key element in protecting the continental United States from terrorist threats is obtaining intelligence of impending attacks in advance. Enormous amounts of resources are currently allocated to obtaining and parsing such intelligence. However, it remains a difficult problem to deal with such attacks once intelligence is obtained. In this context, the Maritime Threat Response Project has applied Systems Engineering processes to propose different cost-effective System of Systems (SoS) architecture solutions to surface-based terrorist threats emanating from the maritime domain. The project applied a five-year time horizon to provide near-term solutions to the prospective decision makers and take maximum advantage of commercial off-the-shelf (COTS) solutions and emphasize new Concepts of Operations (CONOPS) for existing systems. Results provided insight into requirements for interagency interactions in support of Maritime Security and demonstrated the criticality of timely and accurate intelligence in support of counterterror operations.This report was prepared for the Office of the Assistant Secretary of Defense for Homeland DefenseApproved for public release; distribution is unlimited

Pneumococcal conjugate vaccine implementation in middle-income countries

Since 2000, the widespread adoption of pneumococcal conjugate vaccines (PCVs) has had a major impact in the prevention of pneumonia. Limited access to international financial support means some middle-income countries (MICs) are trailing in the widespread use of PCVs. We review the status of PCV implementation, and discuss any needs and gaps related to low levels of PCV implementation in MICs, with analysis of possible solutions to strengthen the PCV implementation process in MICs

Riverine sustainment 2012

Student Integrated ProjectIncludes supplementary materialThis technical report analyzed the Navy's proposed Riverine Force (RF) structure and capabilities for 2012. The Riverine Sustainment 2012 Team (RST) examined the cost and performance of systems of systems which increased RF sustainment in logistically barren environments. RF sustainment was decomposed into its functional areas of supply, repair, and force protection. The functional and physical architectures were developed in parallel and were used to construct an operational architecture for the RF. The RST used mathematical, agent-based and queuing models to analyze various supply, repair and force protection system alternatives. Extraction of modeling data revealed several key insights. Waterborne heavy lift connectors such as the LCU-2000 are vital in the re-supply of the RF when it is operating up river in a non-permissive environment. Airborne heavy lift connectors such as the MV-22 were ineffective and dominated by the waterborne variants in the same environment. Increase in manpower and facilities did appreciable add to the operational availability of the RF. Mean supply response time was the biggest factor effecting operational availability and should be kept below 24 hours to maintain operational availability rates above 80%. Current mortar defenses proposed by the RF are insufficient.N

Hepato-specific microRNA-122 facilitates accumulation of newly synthesized miRNA through regulating PRKRA

microRNAs (miRNAs) are a versatile class of non-coding RNAs involved in regulation of various biological processes. miRNA-122 (miR-122) is specifically and abundantly expressed in human liver. In this study, we employed 3′-end biotinylated synthetic miR-122 to identify its targets based on affinity purification. Quantitative RT-PCR analysis of the affinity purified RNAs demonstrated a specific enrichment of several known miR-122 targets such as CAT-1 (also called SLC7A1), ADAM17 and BCL-w. Using microarray analysis of affinity purified RNAs, we also discovered many candidate target genes of miR-122. Among these candidates, we confirmed that protein kinase, interferon-inducible double-stranded RNA-dependent activator (PRKRA), a Dicer-interacting protein, is a direct target gene of miR-122. miRNA quantitative-RT–PCR results indicated that miR-122 and small interfering RNA against PRKRA may facilitate the accumulation of newly synthesized miRNAs but did not detectably affect endogenous miRNAs levels. Our findings will lead to further understanding of multiple functions of this hepato-specific miRNA. We conclude that miR-122 could repress PRKRA expression and facilitate accumulation of newly synthesized miRNAs

‘In vivo’ optical approaches to angiogenesis imaging

In recent years, molecular imaging gained significant importance in biomedical research. Optical imaging developed into a modality which enables the visualization and quantification of all kinds of cellular processes and cancerous cell growth in small animals. Novel gene reporter mice and cell lines and the development of targeted and cleavable fluorescent “smart” probes form a powerful imaging toolbox. The development of systems collecting tomographic bioluminescence and fluorescence data enabled even more spatial accuracy and more quantitative measurements. Here we describe various bioluminescent and fluorescent gene reporter models and probes that can be used to specifically image and quantify neovascularization or the angiogenic process itself