Miracle-dz/UniFAR-FTUs huggingface dataset:
Accessibility and Personalization in OpenCourseWare : An Inclusive Development Approach

OpenCourseWare (OCW) has become a desirable source for sharing free educational resources which means there will always be users with differing needs. It is therefore the responsibility of OCW platform developers to consider accessibility as one of their prioritized requirements to ensure ease of use for all, including those with disabilities. However, the main challenge when creating an accessible platform is the ability to address all the different types of barriers that might affect those with a wide range of physical, sensory and cognitive impairments. This article discusses accessibility and personalization strategies and their realisation in the SlideWiki platform, in order to facilitate the development of accessible OCW. Previously, accessibility was seen as a complementary feature that can be tackled in the implementation phase. However, a meaningful integration of accessibility features requires thoughtful consideration during all project phases with active involvement of related stakeholders. The evaluation results and lessons learned from the SlideWiki development process have the potential to assist in the development of other systems that aim for an inclusive approach.
Engineering a Standard Cell Library for an Industrial Router with ASAP7 PDK

In this work we first look into the standard cell library enclosed with ASAP7 PDK to uncover the root causes that limit the use of this cell library for research and development. In view of the root causes, we propose a revised technology LEF file for the cell library. Experimental results show that, with the revised technology LEF file, an industrial router can complete place&route of a design up to 180 thousand cells with a core utilization of 90%. We further add 23 frequently used cells into the cell library and reshape pin layout of each cell to increase on-grid pin accessibility. The designs with the improved cell library are more routable and have fewer DRC errors.
Toward Automated Assessment of User Experience in Extended Reality

Designers of extended reality systems need to predict users feedback about designed elements to evaluate their systems. Manual user experience testing can not cover all preferences of users and user-system interactions. To improve and accelerate this process, automated user experience testing is a field of growing interest. Since users’ emotions affect their experience, the automated testing framework should represent users with different emotional states. In this study, we propose an approach to deploy an automated user experience testing framework using BDI test agents which work with a computational model of emotion to regulate their testing behavior.
Photo-identification of fin whales ( Balaenoptera physalus L.) off the south coast of Ireland

Photo-identification of fin whales ( Balaenoptera physalus L.) was carried out off the south coast of Ireland between 2003 and 2008. During 79 research trips, mainly on-board a whale watching vessel, 62 individual fin whales were identified using a variety of marks, including notches in the dorsal fin, blotches and scars. Forty (65%) of these whales were only seen once but eleven whales (18%) have been recorded within a year on up to four occasions within a season and eleven whales (18%) re-sighted between years with one recorded in four and one in five of the last seven years. Re-sighting rate varied depending on the marks used to identify whales but was 17.7% overall. The mean interval between the first and last reported sighting was 33.2 days, with a minimum of one day and a maximum interval of 165 days. The south coast of Ireland is an important site for fin whales and provides excellent research opportunities due to their close proximity to land.
A NAS Integrated File System for On-site IoT Data Storage

In the case of IoT data acquisition, long-term storage of large amounts of sensor data is a significant challenge. When a cloud service is used, fixed costs such as a communication line for uploading and a monthly fee are unavoidable. In addition, the use of large-capacity storage servers incurs high initial installation costs. In this paper, we propose a Network Attached Storage (NAS) integrated file system called the “Sensor Data File System (SDFS)”, which has advantages of being on-site, low-cost, and highly scalable. We developed the SDFS using FUSE, which is an interface for implementing file systems in user-space. SDFS not only allows multiple NAS to be treated as a single file system but also has functions that facilitate the ease of the addition of storage. In this paper, we compared SDFS with existing integrated storage modalities such as aufs and unionfs-fuse. The results indicate that SDFS achieves an equivalent throughput compared with existing file systems in terms of read/write performance.
A General Purpose Single-Slope MEMS Capacitive Sensors Interface Circuit For IoT Applications

A new energy-efficient single-slope capacitance-to-digital interface circuit is proposed. The proposed interface circuit is a general purpose interface that can be adapted for multi-sensors IoT applications. This interface utilizes a new iterative charge sharing technique, which can be easily configures for different capacitive sensor ranges. The interface employs a switched capacitor circuit followed by a low-power dynamic comparator and a digital controller with a counter to generate the digital output, corresponding to the input capacitance of the sensor. The simplicity of the proposed capacitance-to-digital converter (CDC) architecture leads to an energy efficient interface. Detailed analysis of the proposed CDC architecture with emphasis on the linearity, conversion time, and noise are presented and verified by the simulation. The proposed CDC achieves a resolution of 8.4 bit and a figure-of-merit (FoM) of 1.56pJ for a capacitor sensor range of 8pF and a supply voltage of 1.2V in $0.18\mu \mathrm{m}$ CMOS technology node.
Screams of joy yield creative projects at the educational robotics workshop in Namibia

A workshop on educational robotics introduced (mostly) undergraduate students to basic robotics and sensor technology skills. Creative robotics projects were developed using sensor technologies. At the beginning of the workshop, the participants indicated that they were excited about the workshop. This was confirmed by the data analyzed with the Intrinsic Motivation Instrument where most participants mentioned that they enjoyed, learned, and were able come up with creative projects within a limited time of four days. This was the first time for some to practically assemble and code robots and the first time for many to practically work with robotics sensor technologies. The workshop was a very unique workshop to be held in Namibia, the first of its kind where 1) participants developed creative projects which fostered collaboration between a local university and two international universities; 2) doors were opened for local and international collaborators which contributes to educational robotics growth in Namibia and beyond; and 3) business opportunities were created as projects developed have market potential.
Oh! Another Deadline: Cohort Analysis of Learner’s Behaviors in Self-Directed Tasks

Self-direction skills in the context of learning can be supported with data in this digital era. This study analyzes the behaviors of learners during a self-directed reading and summarization task. Our work investigates an undergraduate course (n=72) where students worked on a reading and summarizing assignment while planning and monitoring the task in GOAL, a platform synthesizing learner’s activity data from learning and physical activity contexts. This study focuses on the initial cohort analysis of the students’ behavior based on the fine grain interaction data collected in the different systems using visual analytics techniques. Such a data-rich narrative of self-directed in-semester activities is not discussed yet in the literature to our knowledge. We discuss the implications of the trends that is found in our collected dataset for designing AI-support for self-direction skills with the GOAL platform and the scope of deeper analysis to further understand the process.
Machine Learning for a Context Mining Facility

This paper considers generalizing context reasoning capabilities through a context mining facility offered to all Information System applications. This facility requires mining context data at the system scale, which raises several challenges for Machine Learning approaches used for such mining. Through a detailed literature review, we analyze these approaches with regard to the requirements of such a context mining facility at the Information System level, pointing to the potential and to the challenges raised by this perspective.
iGLU: Non-Invasive Device for Continuous Glucose Measurement with IoMT Framework

The extended abstract is for a Research Demo Session based on our previous article [1]. There is a requirement of Continuous Glucose Measurement (CGM) to control diabetes by insulin secretion or medications. A novel non-invasive measurement device iGLU is introduced to determine continuous blood glucose value with optical detection technique. iGLU model is integrated with Internet of Medical Things (IoMT) framework for remote located diabetic patients to provide prescribed diet and medication with the help of diabetologist.
Using mutation testing to measure behavioural test diversity

Diversity has been proposed as a key criterion to improve testing effectiveness and efficiency. It can be used to optimise large test repositories but also to visualise test maintenance issues and raise practitioners’ awareness about waste in test artefacts and processes. Even though these diversitybased testing techniques aim to exercise diverse behavior in the system under test (SUT), the diversity has mainly been measured on and between artefacts (e.g., inputs, outputs or test scripts). Here, we introduce a family of measures to capture behavioural diversity (b-div) of test cases by comparing their executions and failure outcomes. Using failure information to capture the SUT behaviour has been shown to improve effectiveness of history-based test prioritisation approaches. However, historybased techniques require reliable test execution logs which are often not available or can be difficult to obtain due to flaky tests, scarcity of test executions, etc. To be generally applicable we instead propose to use mutation testing to measure behavioral diversity by running the set of test cases on various mutated versions of the SUT. Concretely, we propose two specific b-div measures (based on accuracy and Matthew’s correlation coefficient, respectively) and compare them with artefact-based diversity (a-div) for prioritising the test suites of 6 different open-source projects. Our results show that our b-div measures outperform a-div and random selection in all of the studied projects. The improvement is substantial with an average increase in average percentage of faults detected (APFD) of between 19% to 31% depending on the size of the subset of prioritised tests.
Survival and tumorigenicity of agrobacterium vitis in living and decaying grape roots and canes in soil

Agrobacterium vitis was recovered from living and decaying grape roots and canes 23 months after grapes were artificially inoculated with a mixture of six strains of the bacterium. Each strain contained a unique plasmid profile. Following inoculation, some plants were treated with the herbicide Roundup to speed up plant death and tissue decay. Roots and canes were assayed over time, and by comparing plasmid profiles of recovered strains it was determined that certain A. vitis strains used in the inoculum mixture were recovered more frequently than others. Profiles identical to those identified for each strain used in the inoculum mixture were observed at least twice in strains recovered during the experiment. Of 133 plasmid profiles that were observed, only 18 did not resemble any of the strains used in the inoculum mixture. Of 333 strains recovered from roots and canes, 321 were tumorigenic, indicating that this trait was stable throughout the experiment. A group of six strains having plasmid profiles identical to strain CG49 that were recovered over an 16-month period were further characterized using restriction fragment length polymorphic analysis of plasmid DNA, random amplified polymorphic DNA analysis of total genomic DNA, and ribofingerprinting of a chromosomal region including 1,479 bp (99.5%) of the 16S rDNA, the intergenic spacer between 16S and 23S rDNA genes, and 132 bp of the 23S rDNA gene. All six strains were shown to be identical to CG49.
An Automata-Based Generation Method for Combinatorial Sequence Testing of Finite State Machines

Combinatorial Interaction Testing has been applied to event-driven software systems by using as test suite a set of sequences of inputs in desired combinations. This is generally called combinatorial sequence testing (CST). CST requires possibly new system models from which tests are generated and new test generation methods (or an adaptation of the classical ones). Finite State Machines (FSMs) can easily represent event-based systems where certain inputs are valid only in some states and such constraints can be represented by the incompleteness of the FSM. In this paper, we propose an approach to CST where tests are generated from FSMs which are represented by automata together with test requirements. First, automata can be used to check if test sequences contain invalid inputs. We propose three methods to repair tests with invalid inputs. Moreover, we can directly embed into automata the system constraints over the inputs during generations, to generate only valid test sequences. We compare our automata-based method with the standard approach of Sequences Covering Arrays (SCAs) that produces a set of sequences, all with the same length, composed by the permutation of all the events supported by the system. We found that generating only valid tests from automata provides several advantages iv.r. t. repairing tests and SCAs.
A High Voltage Multi-Purpose On-the-fly Reconfigurable Half-Bridge Gate Driver for GaN HEMTs in 0.18-μm HV SOI CMOS Technology

Intended to be the core design of a configurable and flexible high voltage power system for aerospace applications, the gate driver in this work is capable of driving a wide range of GaN devices of different sizes, in half-bridge configuration, with configurable driving strength and dead-time. These features eliminate the need for discrete gate resistors and allow for higher density designs, such as SiP integration. The on-the-fly reconfigurability enables local efficiency optimization and EMI reduction, which is essential in safety-critical applications. The proposed IC was fabricated using XFAB's 0.18 $\mu \mathrm{m}$ HV SOI CMOS process (xt018). Measurement results show that the chip can drive targeted GaN HEMTs from smallest to largest size at the desired turn-on and turn-off speeds, as fast as 1.46/1.18 ns of rise/fall-time. The measured dead-time is from 4.5 ns to 58 ns with an input voltage up to 86 V. The parameters can be reconfigured on-the-fly at a pulse width modulation frequency up to 20 MHz.
Ontology-based Testing: An Emerging Paradigm for Modeling and Testing Systems and Software

Model-based testing has been successfully applied for test case generation in practice. Its underlying idea is to utilize models of the system for obtaining system inputs and their corresponding expected outputs. In this paper, we report on experiences gained when using a different methodology relying on models, i.e., ontology-based testing, for generating test suites in practice. Instead of modeling the system’s behavior, ontologybased testing relies on models of the system’s environment, i.e., an environmental ontology. Test cases are generated from ontologies converting them into an input model for combinatorial testing, and using a combinatorial testing algorithm for finally computing the test cases. We show how ontology-based testing can be applied in three different application domains, i.e., testing autonomous driving functionality, security testing, and compiler testing, discuss issues arising and indicate future research objectives.
Implicit Modeling of Membranes

Biological lipid membranes are central to many biological processes. They form selectively permeable barriers, allowing cells to control their contents and create concentration gradients. However, in contrast to the totally passive view espoused by standard undergraduate texts, biological membranes also actively modify cell behavior by altering the function of membrane proteins, modulating the stability of protein–protein associations, and altering the binding and distribution of small molecules including salts and osmolytes (Jensen and Mouritsen, 2004; Brown, 1994; White and Wimley, 1999; Epand, 1998, 2003; Mouritsen and Bloom, 1993; Nyholm et al., 2007). Membrane composition varies significantly in different tissues within a given organism, emphasizing that the distribution of specific lipid species is not a matter of simple abundance. For example, rod outer segment disk membrane, found in the mammalian visual system, contain roughly 50% polyunsaturated ω-3 fatty acids; this is an enormous enrichment considering their natural abundance is more like 5% (Boesze-Battaglia and Albert, 1989; Boesze-Battaglia et al., 1989) Since humans are unable to synthesize ω-3s, this implies the body must be specifically trafficking them to the disk membranes. Polyunsaturated lipids have been shown ctm60 v.2008/03/05 Prn:17/03/2008; 16:30 F:ctm605.tex; VTEX/Rita p. 1 aid: 5 pii: S1063-5823(08)00005-7 docsubty: REV
Estimation of Walking Direction with Vibration Sensor based on Piezoelectric Device

Recently, device-free indoor positioning and tracking of persons is attracting attention. Some approaches use vibration sensors installed on the floor to identify the position of the vibration source by measuring and analyzing vibration strength and vibration fingerprints. However, vibration sensors can give the output information only on the strength of the vibration which shows that the vibration source is near or far from the sensor. Since the moving direction cannot be measured, it is difficult to apply the vibration sensor to track persons walking around in indoor space. In this paper, we propose a method for estimating the walking direction of a person using two vibration sensors. In the proposed method, we capture floor vibration using a pair of piezoelectric vibration sensors installed at a certain distance, calculate frequency domain features and estimate walking direction by machine learning. We conducted an experiment in a smart home where we installed our vibration sensors on the floor, asked four participants to pass near the sensors 20 times in two directions and estimated the walking direction by the proposed method. As a result, the walking direction was estimated with a maximum accuracy of 90%.
STA for Mixed Cyclic, Acyclic Circuits

In this work, we present a Static Timing Analysis (STA) methodology for cyclic circuits with attached acyclic datapaths, as an alternative to SPICE level electrical simulation, based on ASTA (Asynchronous STA). Our methodology uses Graph-based Analysis (GBA) STA principles, is fast, is able to compute setup or hold slacks on sequential elements, and operates without cycle cutting. Industrial Timing Libraries, Verilog input and multiple PVT corners are supported. To perform STA on the cyclic circuit portion, a Graph-based Event Model, a live and 1-bounded Signal Transition Graph (STG), i.e. a simplified PeTri-Net (PTnet), the Event Timing Graph (ETG), is automatically generated from the netlist and the associated timing arcs. The ETG is a cyclic, timing arcs graph, the period analysis of which can identify the cyclic portion's period and Critical Cycle(s). The acyclic portion's STA may be subsequently performed, based on the cyclic portion's Arrival Times (AT). We illustrate an algorithm for automated ETG construction, based solely on circuit components, and their technology library (.lib) timing arcs unateness. We prove that the generated ETG will be live and 1-bounded. Our STA approach is demonstrated on three practical, mixed cyclic, acyclic circuits, a ring-oscillator, a Vernier delay line, and a GALS controller.
Full Mouth Rehabilitation by Implant Supported Fixed Prosthesis

The purpose of this study is to report a case of full-mouth rehabilitation on six endosseous implants loaded following the standard procedure. It was decided to insert six implants in the maxillary and six implants in the mandibular arch in a patient with no systemic disease. The surgery was performed with the patient under local anesthesia with lignocaine and 1:100,000 adrenaline. Implant stability was sufficient (35 N/cm measured with a torque spring) for all 12 implants. An impression is taken in the open tray with a silicone impression material. Vertical dimension for rest and occlusion was checked with wax occlusal rims placed in the mouth. Interocclusal records were made with the metal framework in place. The final restoration was realized with ceramic layering completed. Good impressions and meticulous attention to detail are crucial for a successful implant-supported fixed prosthesis.
Poster: Is Euclidean Distance the best Distance Measurement for Adaptive Random Testing?

Adaptive random testing (ART) aims at enhancing the testing effectiveness of random testing (RT) by more evenly spreading test cases over the input domain. Many ART methods have been proposed, based on various, different notions. For example, distance-based ART (DART) makes use of the concept of distance to implement ART, attempting to generate new test cases that are far away from previously executed ones. The Euclidean distance has been a popular choice of distance metric, used in DART to evaluate the differences between test cases. However, is the Euclidean distance the most suitable choice for DART? To answer this question, we conducted a series of simulations to investigate the impact that the Euclidean distance, and its many variations, has on the testing effectiveness of DART. The results show that when the dimensionality of the input domain is low, the Euclidean distance may indeed be a good choice. However, when the dimensionality is high, it appears to be less suitable.
Delivering IoT Smart Services through Collective Awareness, Mobile Crowdsensing and Open Data

IoT is spreading heavily in many use cases that surround our everyday life; however, existing IoT ecosystems are still behaving as close islands with little interoperability with each other. Recent research efforts tend to propose new architectures and standards to which private customers and companies producing data are supposed to adhere in order to make them consistent. However, such entities have their own vested interests that hinder data integration. We instead leverage information acquisition through Collective Awareness Paradigms (CAPs) such as Open Data and Mobile Crowdsensing (MCS) in order to use what is already available. As a proof of concept, we developed SenSquare, a prototype IoT architecture and platform for Smart Cities and environmental monitoring that gathers raw data through CAPs, adapts it to a common semantic and composes customizable flexible services. Inexperienced users can generate their own services using an easy visual programming plugin designed around a customized language. Furthermore, we test the platform on a real world use case.