Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Classification of Text Streams: Limitations, Challenges, and Solutions

Text stream classification is an important problem that is difficult to solve at scale. Batch processing systems, widely adopted for text classification tasks, cannot provide for low latency. Distributed stream processing systems can offer low latency, but do not support the same level of fault tolerance and determinism as the batch systems. In this work, we demonstrate how the distributed stream processing features can affect the results of a typical text classification data flow. Our analysis shows emerged trade-offs between fault tolerance and reproducibility on the one side, and performance on the other side. We outline potential ways to solve the revealed issues and to handle streaming features.
AutoWSD: Virtual Reality Automated Driving Simulator for Rapid HCI Prototyping

Human factors research in automated driving is nowadays often conducted using either low-quality setups such as 2D monitors or highly expensive driving simulators with motion platforms. Additionally, software for automated driving scenarios is often expensive and hard to modify for different scenarios. We intend to bridge this gap by proposing a low-cost, high-fidelity immersive prototyping solution by utilizing the recent advances in development of virtual reality (VR): AutoWSD - Automated driving simulator for research on windshield displays. We showcase a hybrid software and hardware solution that is based on the popular and widely used Unity development platform. Furthermore, we demonstrate the little effort needed to create scenarios for user studies, and thereby foster discussion about potential improvements and extensions for AutoWSD, as well as the topic of trust, acceptance, user experience and simulator sickness in automation.
CONSEQUENCES: CONstrained SEQUENCE alignmentS With Multiple User Weights

Proteins are sequences of amino acids which can be represented abstractly as words of single letter residue abbreviations such as GAPPM. A variety of pharmaceutical drugs achieve their effects by binding, or interacting with, specific amino acids on a protein's surface. Pharmaceutical companies design medicines to have maximal impact by targeting specific regions of a protein. Because multiple drugs might target different regions of a protein, there may be multiple subsequences in a protein that are of interest. Currently there is no algorithm which allows a user to search the publicly available amino acid sequences in the Protein Data Bank for multiple sequences of varying lengths, each with a different user-specified priority, or weight. We present here a proof-of-concept computation approach, ConSequenceS, for CONstrained SEQUENCE alignmentS, which relies on BLAST and a weighted Levenshtein Distance formula. We demonstrate the utility of ConSequenceS via several case studies, and show that our approach is able to identify matches of protein sequences which tools such as BLAST are not able to find. A web server running the software is available at http://consequences.cs. wwu.edu/
Java Stream Fusion: Adapting FP mechanisms for an OO setting

In this paper, we show how stream fusion, a program transformation technique used in functional programming, can be adapted for an Object-Oriented setting. This makes it possible to have more Stream operators than the ones currently provided by the Java Stream API. The addition of more operators allows for a greater deal of expressiveness. To this extent, we show how these operators are incorporated in the stream setting. Furthermore, we also demonstrate how a specific set of optimizations eliminates overheads and produces equivalent code in the form of for loops. In this way, programmers are relieved from the burden of writing code in such a cumbersome style, thus allowing for a more declarative and intuitive programming approach.
Appraisal theory-based mobile app for physiological data collection and labelling in the wild

Numerous studies on emotion recognition from physiological signals have been conducted in laboratory settings. However, differences in the data on emotions elicited in the lab and in the wild have been observed. Thus, there is a need for systems collecting and labelling emotion-related physiological data in ecological settings. This paper proposes a new solution to collect and label such data: an open-source mobile application (app) based on the appraisal theory. Our approach exploits a commercially available wearable physiological sensor connected to a smartphone. The app detects relevant events from the physiological data, and prompts the users to report their emotions using a questionnaire based on the Ortony, Clore and Collins (OCC) Model. We believe that the app can be used to collect emotional and physiological data in ecological settings and to ensure high quality of ground truth labels.
Compaction and Compression Techniques for File Systems based on Persistent Memories

File systems are the most popular means of data storage in many computing environments. The appropriate designs of file systems therefore become key research highlights to enhance the data access performance and storage space utilization. As diversified persistent memories (PMs) are considered powerful competitors of mechanical hard disks due to their ideal access performance and energy efficiency, file system designers need to adopt various compression or compaction techniques to reduce the space wastes, because the storage density of PMs are still considerably lower than that of hard disks. However, there are still missing pieces in the puzzle which overviews the potential approaches that enhance the storage space utilization from various perspectives of a file system. In this work, we shall take a revisit to the promising techniques that help enhance the storage space utilization of file systems based on PMs. It is observed that an effective compression or compaction technique not only benefits the storage space utilization, but also ameliorates the access performance of the file system.
Perceptions of a Help-Requesting Robot - Effects of Eye-Expressions, Colored Lights and Politeness of Speech

In this paper we report results from a web- and video-based study on the perception of a request for help from a robot head. Colored lights, eye-expressions and politeness of speech were varied. We measured effects on expression identification, hedonic user experience, perceived politeness, and help intention. Additionally, sociodemographic data, a 'face blindness' questionnaire, and negative attitudes towards robots were collected to control for possible influences on the dependent variables. A total of n=139 participants were included in the analysis. Significant differences were found for the identification performance for our intended eye-expressions, for perceived politeness, help intentions and hedonic user experience. Especially for the negative attitudes towards robots, we found significant relationships with perceived politeness and help intentions.
Dynamic Cluster-based Retrieval and Discovery for Biomedical Literature

Due to increased specialization and experimentation, the volume of biomedical literature is rapidly increasing, where the current modalities of search and retrieval system can no longer support effective and efficient knowledge discovery. Standard information retrieval systems such as PubMed make assumptions as to users' prior knowledge and expect them to formulate a proper query term for the information they are looking for. There exist user feedback mechanisms to help users reformulate their queries, which still assumes that users know how the search results could be effectively narrowed down by way of additional keywords and/or filters. As an alternative, we revisit the Scatter/Gather information retrieval paradigm. Specifically, we explore a real-time dynamic cluster-based document browsing approach in the biomedical domain, discuss the system architecture involving keyword discovery and dynamic clustering, and present a working prototype with a relevant use case in comparison with a standard ranking-based information retrieval system.
Effects of the textile-sensor interface on stitched strain sensor performance

The influence of the textile substrate on the performance of a textile-based strain sensor has not been well understood or characterized in many wearable sensor evaluations. The underlying textile has its own anisotropic mechanical behaviors due to its woven or knit fabrication process, and introduces non-trivial structural influences on integrated wearable strain sensors. This study considers stitched strain sensors of two stitch geometries, fabricated on two different knit fabrics, with the sensor stitched in different orientations with respect to the knit structure. The resulting mechanical and electrical performance is characterized under cyclic extension, as the angle of extension (relative to the fabric) is also incrementally changed. The results illustrate a shift from linear to non-linear mechanical behavior as fabric stiffness increases, and variations in behavior between stitch geometries. Results show that force direction and sensor placement both introduce variability in calculated elastic modulus, which affect sensor modeling (e.g. predicting applied force from sensor response). A novel stitch geometry (the chainstitch sensor) is characterized as having a higher gauge force and lower transverse sensitivity factor than the coverstitch sensor. This work offers insight into the textile-sensor interface and design implications for development of textile-based sensors.
Identifying availability tactics to support security architectural design of microservice-based systems

Microservices is an architectural style that considers systems as modular, customer-centric, independent, and scalable suite of services. In order to address security requirements in microservices-based systems, architects often must focus on critical quality attributes, such as availability, aiming at employing architectural solutions that provide design decisions that address key security concerns (also known as architectural tactics). Although current architectural tactics for availability offer an extensive catalog of alternatives to improve availability and security factors, new availability concerns (emerging from security microservices requirements) demand new or improved architectural tactics. In this article, we examined the source code and documentation of 17 open source microservices-based systems, identified 5 uses of availability tactics, and characterized them using a newly introduced descriptive template. We found that almost all (4 out of 5) tactics did focus on preventing faults rather than detecting, mitigating or recovering from them (which are the traditional tactics taxonomies' branches). This approach can be further used to systematically identify and characterize architectural tactics in existing microservices-based systems in other critical quality attributes concerning security, such as confidentiality and integrity.
RecRules

Nowadays, end users can personalize their smart devices and web applications by defining or reusing IF-THEN rules through dedicated End-User Development (EUD) tools. Despite apparent simplicity, such tools present their own set of issues. The emerging and increasing complexity of the Internet of Things, for example, is barely taken into account, and the number of possible combinations between triggers and actions of different smart devices and web applications is continuously growing. Such a large design space makes end-user personalization a complex task for non-programmers, and motivates the need of assisting users in easily discovering and managing rules and functionality, e.g., through recommendation techniques. In this article, we tackle the emerging problem of recommending IF-THEN rules to end users by presenting RecRules, a hybrid and semantic recommendation system. Through a mixed content and collaborative approach, the goal of RecRules is to recommend by functionality: it suggests rules based on their final purposes, thus overcoming details like manufacturers and brands. The algorithm uses a semantic reasoning process to enrich rules with semantic information, with the aim of uncovering hidden connections between rules in terms of shared functionality. Then, it builds a collaborative semantic graph, and it exploits different types of path-based features to train a learning to rank algorithm and compute top-N recommendations. We evaluate RecRules through different experiments on real user data extracted from IFTTT, one of the most popular EUD tools. Results are promising: they show the effectiveness of our approach with respect to other state-of-the-art algorithms and open the way for a new class of recommender systems for EUD that take into account the actual functionality needed by end users.
EEGlass: an EEG-eyeware prototype for ubiquitous brain-computer interaction

Contemporary Head-Mounted Displays (HMDs) are progressively becoming socially acceptable by approaching the size and design of normal eyewear. Apart from the exciting interaction design prospects, HMDs bear significant potential in hosting an array of physiological sensors very adjacent to the human skull. As a proof of concept, we illustrate EEGlass, an early wearable prototype comprised of plastic eyewear frames for approximating the form factor of a modern HMD. EEGlass is equipped with an Open-BCI board and a set of EEG electrodes at the contact points with the skull for unobtrusively collecting data related to the activity of the human brain. We tested our prototype with 1 participant performing cognitive and sensorimotor tasks while wearing an established Electroencephalography (EEG) device for obtaining a baseline. Our preliminary results showcase that EEGlass is capable of accurately capturing resting state, detect motor-action and Electrooculographic (EOG) artifacts. Further experimentation is required, but our early trials with EEGlass are promising in that HMDs could serve as a springboard for moving EEG outside of the lab and in our everyday life, facilitating the design of neuroadaptive systems.
Perception of Differences in Directed Acyclic Graphs: Influence Factors & Cognitive Strategies

Visual comparison of graphs has become widespread in various disciplines. To support this task, it is necessary to generate graph drawings that facilitate the perception of differences. However, while readability of single graphs has been widely investigated, knowledge about the recognition of differences in graphs in general and directed acyclic graphs (DAGs) specifically is quite limited. Towards this end, we conducted an exploratory qualitative study to ascertain which factors influence the perception of changes in DAGs and to better understand the strategies adopted to compare them. Specifically, we investigated pairs of DAGs of varying structure and size (about 50 to 100 nodes) and displayed side-by-side. Based on video recordings and thinking aloud protocols of 22 participants we identified eight factors including edge crossings, shape, symmetry, white space, and density to affect the perception of differences. In addition, we identified three strategies which were used to compare the graphs: layer-by-layer, hierarchical, and a mixture of these two. These strategies were adapted flexibly by the participants based on the graph structure.
A logical architecture design method for microservices architectures

The use of microservices architectures has been widely adopted in software development, especially for cloud-based solutions. Developing such solutions faces several challenges beyond typical architecture and service design concerns, including service exposition (API), inter-service communication, and infrastructure deployment, among others. Although model-driven approaches allow abstracting microservices behavior from the business domain, there is a lack of proper methods for addressing the referred challenges. In this paper, the elicitation of microservices, their identification uses using functionally decomposed UML use cases as input within a logical architecture derivation method, namely an adapted version of the Four Step Rule Set (4SRS), using SoaML diagrams, that responds to microservices specific characteristics. We demonstrate the approach using a scenario within a live industrial project.
EyeControl: wearable assistance for industrial maintenance tasks

Due to the explicit and implicit facets of gaze-based interaction, eye tracking is a major area of interest within the field of cognitive industrial assistance systems. In this position paper, we describe a scenario which includes a wearable platform built around a mobile eye tracker, which can support and guide an industrial worker throughout the execution of a maintenance task. The potential benefits of such a solution are discussed and the key components are outlined.
ProxiTalk

Speech input, such as voice assistant and voice message, is an attractive interaction option for mobile users today. However, despite its popularity, there is a use limitation for smartphone speech input: users need to press a button or say a wake word to activate it before use, which is not very convenient. To address it, we match the motion that brings the phone to mouth with the user's intention to use voice input. In this paper, we present ProxiTalk, an interaction technique that allows users to enable smartphone speech input by simply moving it close to their mouths. We study how users use ProxiTalk and systematically investigate the recognition abilities of various data sources (e.g., using a front camera to detect facial features, using two microphones to estimate the distance between phone and mouth). Results show that it is feasible to utilize the smartphone's built-in sensors and instruments to detect ProxiTalk use and classify gestures. An evaluation study shows that users can quickly acquire ProxiTalk and are willing to use it. In conclusion, our work provides the empirical support that ProxiTalk is a practical and promising option to enable smartphone speech input, which coexists with current trigger mechanisms.
A qualitative study on personal hygiene knowledge and practices among food handlers at selected primary schools in Klang Valley area, Selangor, Malaysia

A study was conducted to determine personal hygiene knowledge among 25 food handlers at 12 selected primary schools in Klang Valley area, Selangor, Malaysia. A qualitative approach using in-depth interviews was employed and respondents were selected by a convenience sampling. The results showed that the respondents had basic knowledge on personal hygiene practices, mainly on hand washing (30.7%) and glove use (18.7%). The food handlers (<11%) also demonstrated their knowledge on other good personal hygiene practices that were related to the use of hair restrain/cap/apron, keeping tidy hair/ clean nails/ clean hand, no bare hand contact with food, not wearing ring/jewelry, no smoking, tidy/clean attire and typhoid injection. Further assessment demonstrated that only 12% respondents were able to describe a reasonable procedure for hand washing and the steps that were missed most were the failure to specify the need to rinse and dry hands after washing. The respondents knew that the use of glove was to prevent bare hand contact (80%) and can reduce risk of food contamination (88%). All the respondents agreed that food handlers with abrasion or cuts on their fingers or hands should not touch unwrapped foods. A high percentage respondents (>90%) practiced various good hand washing practices, with only 36% did not practice washing hands after eating or drinking. Most respondents (>70%) practiced glove use, however more than 50% did not wash hands with every glove change, change gloves when change type of products and after preparing raw material. The study showed that the food handlers have basic knowledge one good personal hygiene practices. However, some discrepancies were revealed in the proper hand washing procedure. This study recommended good hand washing procedure to be reiterated among the food handlers. There is also an immediate need for continuous training among food handlers regarding good personal hygiene practices.
Optimal resource scheduling for energy-efficient next generation wireless networks

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A simulation study of bed allocation to reduce blocking probability in emergency departments: A case study in China

Abstract Improving the bed allocation policy can alleviate the blocking, a situation where admitted patients cannot be transferred from the Emergency Departments (the upstream) to inpatient departments (the downstream) due to unavailability of beds. We aim to find a bed allocation policy that reduces the blocking probability and improves bed utilisation considering the interaction between the neighboring departments, as well as the priorities of different departments. This concept and the proposed model are tested in a real-life case at a hospital in China. A two-stage bed allocation simulation model is developed to evaluate the effect of bed assignment on the blocking probability and bed utilisation. Results show that the blocking probabilities can be reduced by 1.32%–8.98% and 1.74%–4.16% under different priority assignment cases and total number of beds. Sensitivity analyses are performed to examine the effect of varying patient arrival rate on the performance of bed allocation policy.
Using interRAI assessment systems to measure and maintain quality of long-term care

Rapidly ageing populations and increasing prevalence of chronic diseases present major challenges for policy makers. Populations as well as individuals have different prevalence of conditions related to ageing and chronic disease. This is compounded by cultural and institutional differences in care service provision, eligibility criteria and funding models. Comparing differences at population and individual level helps policy makers address the complexities of maintaining quality in long-term care. This chapter describes how evolution in development of needs assessment instruments has led to a way of producing high-quality data for policy makers. It describes in detail the interRAI system of standardised needs assessment instruments for routine care that generate aggregatable data. Data driven algorithms generate outcome scales, care planning support protocols, quality indicators, and a resource-use casemix system. The chapter then illustrates, with data from nine OECD countries and regions, how needs assessment data recorded at the point of care using the interRAI system can inform policy. It ends with a discussion of factors for consideration when implementing sophisticated needs assessment tools.
Effects of dynamic mold temperature control on melt pressure, cellular structure, and mechanical properties of microcellular injection-molded parts: An experimental study

In this work, the effects of dynamic mold temperature control (DMTC) on melt pressure, cellular structure, and mechanical properties of microcellular injection molding (MIM)-molded parts are investigated experimentally. It is found that with the increase of the mold temperature, the duration of foaming pressure in the cooling stage increases. Meanwhile, the average cell diameter and cell diameter dispersion increases as well as the cell density decreases in MIM molded parts. The turning point of mold temperature after which the foaming pressure in the cooling stage and the cellular structure in MIM molded parts generate a significant change is around the glass transition temperature of the used plastic material. Under DMTC conditions, with the increase of mold temperature, the tensile strength, flexural strength, and impact strength of MIM molded specimens of single gate without weld line change a little, while the tensile strength, flexural strength of MIM molded specimens of double gates with weld line increase obviously. When the mold temperature increases to 120°C and over, the tensile strength, flexural strength of MIM molded specimens of double gates with weld line reach an equivalent level of specimens of single gate without weld line.