Miracle-dz/UniFAR-FTUs huggingface dataset:
What type of happiness are you looking for? - A closer look at detecting mental health from language

Computational models to detect mental illnesses from text and speech could enhance our understanding of mental health while offering opportunities for early detection and intervention. However, these models are often disconnected from the lived experience of depression and the larger diagnostic debates in mental health. This article investigates these disconnects, primarily focusing on the labels used to diagnose depression, how these labels are computationally represented, and the performance metrics used to evaluate computational models. We also consider how medical instruments used to measure depression, such as the Patient Health Questionnaire (PHQ), contribute to these disconnects. To illustrate our points, we incorporate mixed-methods analyses of 698 interviews on emotional health, which are coupled with self-report PHQ screens for depression. We propose possible strategies to bridge these gaps between modern psychiatric understandings of depression, lay experience of depression, and computational representation.
Global change and conservation triage on National Wildlife Refuges

National Wildlife Refuges (NWRs) in the United States play an important role in the adaptation of social-ecological systems to climate change, land-use change, and other global-change processes. Coastal refuges are already experiencing threats from sea-level rise and other change processes that are largely beyond their ability to influence, while at the same time facing tighter budgets and reduced staff. We engaged in workshops with NWR managers along the U.S. Atlantic coast to understand the problems they face from global-change processes and began a multidisciplinary collaboration to use decision science to help address them. We are applying a values-focused approach to base management decisions on the resource objectives of land managers, as well as those of stakeholders who may benefit from the goods and services produced by a refuge. Two insights that emerged from our workshops were a conspicuous mismatch between the scale at which management can influence outcomes and the scale of environmental processes, and the need to consider objectives related to ecosystem goods and services that traditionally have not been explicitly considered by refuges (e.g., protection from storm surge). The broadening of objectives complicates the decision-making process, but also provides opportunities for collaboration with stakeholders who may have agendas different from those of the refuge, as well as an opportunity for addressing problems across scales. From a practical perspective, we recognized the need to (1) efficiently allocate limited staff time and budgets for short-term management of existing programs and resources under the current refuge design and (2) develop long-term priorities for acquiring or protecting new land/habitat to supplement or replace the existing refuge footprint and thus sustain refuge values as the system evolves over time. Structuring the decision-making problem in this manner facilitated a better understanding of the issues of scale and suggested that a long-term solution will require a significant reassessment of objectives to better reflect the comprehensive values of refuges to society. We discuss some future considerations to integrate these two problems into a single framework by developing novel optimization approaches for dynamic problems that account for uncertainty in future conditions.
Battling Latency in Modern Wireless Networks

Buffer sizing has a tremendous effect on the performance of Wi-Fi based networks. Choosing the right buffer size is challenging due to the dynamic nature of the wireless environment. Over buffering or ‘bufferbloat’ may produce unacceptable end-to-end delays. On the other hand, small buffers may limit the performance gains that can be obtained with various IEEE 802.11n/ac enhancements, such as frame aggregation. We propose wireless queue management (WQM), a novel, practical, and lightweight queue management scheme for wireless networks. WQM adapts the buffer size based on the wireless link characteristics and the network load. Furthermore, it accounts for aggregates length when deciding on the optimal buffer size. We evaluate WQM using our 10 nodes wireless testbed. WQM reduces the end-to-end delay by an order of magnitude compared to the default buffer size in Linux while achieving similar network throughput. Also, WQM outperforms state of the art bufferbloat solutions, namely CoDel and PIE. WQM achieves seven times less latency compared to PIE, and two times compared to CoDel at the cost of 8% drop in goodput in the worst case. Further, WQM improves network fairness as it limits the ability of a single flow to saturate the buffers.
Built to Learn: How Work Practices Affect Employee Learning During Healthcare Information Technology Implementation

We test the hypothesis that work practices complement IT investment, in part, by accelerating how rapidly employees acquire the skills needed to use new IT systems. We combine support request data from an EMR vendor with survey responses on work practices from 962 employees from 15 client nursing homes. Nursing homes using work practices that prior studies have shown to complement IT investment—those promoting discretion, teamwork, training, high staffing levels, and communication—experienced more rapid declines in requests for technical support. We then show that these benefits are due, in part, because the use of these work practices facilitates learning for workers in frontline occupations who otherwise may not have the freedom to experiment with and adapt the new technology systems. For many frontline workers, discretion was more important than training in explaining IT learning. Implications for the healthcare industry are discussed.
BORE: boosted-oriented edge optimization for robust, real time remote pupil center detection

Undoubtedly, eye movements contain an immense amount of information, especially when looking to fast eye movements, namely time to the fixation, saccade, and micro-saccade events. While, modern cameras support recording of few thousand frames per second, to date, the majority of studies use eye trackers with the frame rates of about 120 Hz for head-mounted and 250 Hz for remote-based trackers. In this study, we aim to overcome the challenge of the pupil tracking algorithms to perform real time with high speed cameras for remote eye tracking applications. We propose an iterative pupil center detection algorithm formulated as an optimization problem. We evaluated our algorithm on more than 13,000 eye images, in which it outperforms earlier solutions both with regard to runtime and detection accuracy. Moreover, our system is capable of boosting its runtime in an unsupervised manner, thus we remove the need for manual annotation of pupil images.
Collaborative matrix factorization mechanism for group recommendation in big data-based library systems

Academic groups are designed specifically for researchers. A group recommendation procedure is essential to support scholars’ research-based social activities. However, group recommendation methods are rarely applied in online libraries and they often suffer from scalability problem in big data context. The purpose of this paper is to facilitate academic group activities in big data-based library systems by recommending satisfying articles for academic groups. ,The authors propose a collaborative matrix factorization (CoMF) mechanism and implement paralleled CoMF under Hadoop framework. Its rationale is collaboratively decomposing researcher-article interaction matrix and group-article interaction matrix. Furthermore, three extended models of CoMF are proposed. ,Empirical studies on CiteULike data set demonstrate that CoMF and three variants outperform baseline algorithms in terms of accuracy and robustness. The scalability evaluation of paralleled CoMF shows its potential value in scholarly big data environment. ,The proposed methods fill the gap of group-article recommendation in online libraries domain. The proposed methods have enriched the group recommendation methods by considering the interaction effects between groups and members. The proposed methods are the first attempt to implement group recommendation methods in big data contexts. ,The proposed methods can improve group activity effectiveness and information shareability in academic groups, which are beneficial to membership retention and enhance the service quality of online library systems. Furthermore, the proposed methods are applicable to big data contexts and make library system services more efficient. ,The proposed methods have potential value to improve scientific collaboration and research innovation. ,The proposed CoMF method is a novel group recommendation method based on the collaboratively decomposition of researcher-article matrix and group-article matrix. The process indirectly reflects the interaction between groups and members, which accords with actual library environments and provides an interpretable recommendation result.
Towards a unified methodology for software engineering and knowledge engineering

The paper presents a first step towards building a unified methodology for both knowledge engineering and software engineering. The idea is to combine the acquisition and conceptualisation phases of the IDEAL methodology (a knowledge engineering methodology) with an object oriented design and implementation. This methodology has been successfully applied to three projects at CETTICO (Centre of Computing and Communications Technology Transfer). The paper describes the techniques used and the results obtained in developing a unified methodology.
Short-segment decompression and fixation for thoracolumbar osteoporotic fractures with neurological deficits

Objective We assessed our results of short-segment decompression and fixation for osteoporotic thoracolumbar fractures with neurological deficits. Methods We evaluated 20 elderly patients (age, 60–89 years; mean, 73.2 years) with osteoporotic thoracolumbar fractures and neurological deficits. They underwent short-segment decompression and fixation and followed up for 40.6 (range, 24–68) months. A visual analog scale (VAS) and the Oswestry Disability Index (ODI) were used to measure back pain and disability. We also analyzed patients’ radiologic findings and neurological status. Perioperative and postoperative complications were recorded. Results At the latest follow-up, the average VAS score for back pain and ODI scores had significantly improved. The radiologic assessment showed significant improvements in local kyphosis, anterior vertebral height, and the vertebral wedge angle compared with the original measures. Neurological function also improved in 18 of 20 patients. No major complications occurred perioperatively. Our techniques included preservation of the posterior ligament complex, decortication of facet joints for fusion, no tapping to increase the screw insertional torque, pre-contouring of the rods according to the “adaptive” curve obtained from postural reduction, and postoperative spinal bracing. Conclusions Posterior short-segment decompression and fixation could be an effective surgical option for osteoporotic thoracolumbar burst fractures with neurological deficits.
Characterizing queries in cross-device OPAC search: a large-scale log study

The study focused on online public access catalog (OPAC) users’ cross-device search behavior. The purpose of this paper is to understand the characteristics of cross-device OPAC searches, and to identify query reformulation (QR) patterns during device transitions. ,The transaction log from a university library, spanning six months, was used to conduct the quantitative analysis. The query vocabulary richness, which refers to the average number of unique words each query contains in a search session, can evaluate query diversity, and contribute to the analysis of QR. ,The results show that PC-PC transition is the most important pattern of device transition. The time interval of device transition was different to the time interval of transitions in web searches. Short device transitions mainly occurred in daytime, and the number of transitions that occurred in less than one minute was higher than on the web. Searches for Industry and Technology triggered the most device transitions, and the users tended to choose the same search field. In addition, the authors made a detailed analysis of the reasons for same-type device transitions and different-type device transitions. Furthermore, the authors focused on the characteristics of adjacent QR patterns. The authors not only refined the concept of cross-device to include the same-type device transition, but also summarized the characteristics of the cross-device QR patterns, which can be used to predict post-switch queries. ,This study extends research into cross-device interaction and cross-device search to the domain of digital library research. The authors also introduced QR perspective on cross-device interaction on OPAC.
An inconspicuous and modular head-mounted eye tracker

State of the art head mounted eye trackers employ glasses like frames, making their usage uncomfortable or even impossible for prescription eyewear users. Nonetheless, these users represent a notable portion of the population (e.g. the Prevent Blindness America organization reports that about half of the USA population use corrective eyewear for refractive errors alone). Thus, making eye tracking accessible for eyewear users is paramount to not only improve usability, but is also key for the ecological validity of eye tracking studies. In this work, we report on a novel approach for eye tracker design in the form of a modular and inconspicuous device that can be easily attached to glasses; for users without glasses, we also provide a 3D printable frame blueprint. Our prototypes include both low cost Commerical Out of The Shelf (COTS) and more expensive Original Equipment manufacturer (OEM) cameras, with sampling rates ranging between 30 and 120 fps and multiple pixel resolutions.
Information-Maximizing Sampling to Promote Tracking-By-Detection

The performance of an adaptive tracking-by-detection algorithm not only depends on the classification and updating processes but also on the sampling. Typically, such trackers select their samples from the vicinity of the last predicted object location, or from its expected location using a predefined motion model, which does not exploit the contents of the samples nor the information provided by the classifier. We introduced the idea of most informative sampling, in which the sampler attempts to select samples that trouble the classifier of a discriminative tracker. We then proposed an active discriminative co-tracker that embed an adversarial sampler to increase its robustness against various tracking challenges. Experiments show that our proposed tracker outperforms state-of-the-art trackers on various benchmark videos.
Finding the personal fitness trip plan in road networks

With the development of wireless telecommunications networks and GPS, relative location-based services are growing rapidly. Many services are proposed for providing route plans, business activities, recommendation locations for users. However, none of them considers the time-related factors, such as time constraints of interesting points, duration time, start time, the orders of activities and the traffic conditions, in real life. In this work, we integrate these factors and propose a query of Finding Personal Fitness Trip Plan in Road Networks. This query can hit the users' requirements in the real life. In this paper, we propose an indexing algorithm with the goal of efficiency and accuracy.
Decentralized predictive control of multi-reach canals

Presents a digital control scheme for water level regulation in canals. The scheme considers a prototype canal composed by a series of pools connected with active gates. A control system is designed for each pool with the objective of manipulating the upstream gate in order to drive and maintain the downstream level at desired values. Each control system is composed of two controllers: one implements a discrete time predictive control law that gives the desired discharge through the gate as to ensure the downstream desired level; another one implements a local control law to move the gate to achieve the desired discharge. The paper presents the formulation of the global control scheme and shows results from simulations to illustrate and discuss the performance in different operation scenarios.
Wearable Sensors Integrated with Internet of Things for Advancing eHealth Care

Health and sociological indicators alert that life expectancy is increasing, hence so are the years that patients have to live with chronic diseases and co-morbidities. With the advancement in ICT, new tools and paradigms are been explored to provide effective and efficient health care. Telemedicine and health sensors stand as indispensable tools for promoting patient engagement, self-management of diseases and assist doctors to remotely follow up patients. In this paper, we evaluate a rapid prototyping solution for information merging based on five health sensors and two low-cost ubiquitous computing components: Arduino and Raspberry Pi. Our study, which is entirely described with the purpose of reproducibility, aimed to evaluate the extent to which portable technologies are capable of integrating wearable sensors by comparing two deployment scenarios: Raspberry Pi 3 and Personal Computer. The integration is implemented using a choreography engine to transmit data from sensors to a display unit using web services and a simple communication protocol with two modes of data retrieval. Performance of the two set-ups is compared by means of the latency in the wearable data transmission and data loss. PC has a delay of 0.051 ± 0.0035 s (max = 0.2504 s), whereas the Raspberry Pi yields a delay of 0.0175 ± 0.149 s (max = 0.294 s) for N = 300. Our analysis confirms that portable devices (p<<0.01) are suitable to support the transmission and analysis of biometric signals into scalable telemedicine systems.
Design of a walking machine structure using evolutionary strategies

Commonly, the design of a walking machine (WM) use to imitate the nature like multilegged creatures, which try to do the best approaching to a spider, a biped, quadruped or any other living animal. Trying to imitate the way that nature has generated animals seems to be more interesting and promising than imitating special results of the natural process of evolution; if we could imitate the motor that generates walking beings, then we may found better solutions, even in the scenarios where life doesn't exist. In this paper we present an algorithm using evolutionary strategies, to aid in key steps of the design of a walking machine structure. Mathematical models are developed together with objective functions.
Acute Pancreatitis with Disturbed Consciousness Caused by Hyperparathyroidism

Although hyperparathyroidism has been reported to cause acute pancreatitis, little is known about the mechanism involved. This study describes the case of an 86-year-old woman with acute pancreatitis and consciousness disturbance caused by hyperparathyroidism and hypercalcemia, respectively. The consciousness disturbance caused by severe hypercalcemia probably masked the typical symptoms associated with pancreatitis because she did not report abdominal pain during the clinical course.
A Framework Exploiting Process Variability to Improve Energy Efficiency in FPGA Applications

As technology node scales-down and process variability increases, the vendors impose even more conservative guard-bands to prevent potential malfunction of their microchips. However, this approach introduces considerable amounts of unexploited performance to individual chips, which can be harvested by developing novel customization tools. In the current work, we focus on the exploitation of process variability in modern FPGA chips to provide more energy efficient solutions. We propose a framework that i) generates variability maps characterizing the energy efficiency of commercial chips and ii) combines voltage and frequency scaling to limit the power dissipation of any given design for a given set of performance constraints. Experimental results on Zynq XC7Z020 28nm FPGAs show that the developed framework achieves up to 28.3% power reduction while maintaining the performance and functional integrity of realistic benchmarks. Moreover, by selecting the most efficient chip, we achieve up to 5.1% additional power savings.
isualizing search behavior with adaptive discriminations

We examined different aspects of the visual search behavior of a pigeon using an open-ended, adaptive testing procedure controlled by a genetic algorithm. The animal had to accurately search for and peck a gray target element randomly located from among a variable number of surrounding darker and lighter distractor elements. Display composition was controlled by a genetic algorithm involving the multivariate configuration of different parameters or genes (number of distractors, element size, shape, spacing, target brightness, and distractor brightness). Sessions were composed of random displays, testing randomized combinations of these genes, and selected displays, representing the varied descendants of displays correctly identified by the pigeon. Testing a larger number of random displays than done previously, it was found that the bird’s solution to the search task was highly stable and did not change with extensive experience in the task. The location and shape of this attractor was visualized using multivariate behavioral isual search surfaces in which element size and the number of distractors were the most important factors controlling search accuracy and search time. The resulting visualizations of the bird’s search behavior are discussed with reference to the potential of using adaptive, open-ended experimental techniques for investigating animal cognition and their implications for Bond and Kamil’s innovative development of virtual ecologies using an analogous methodology. This article is part of a Special Issue entitled: CO3 2013.
D User Interfaces , from Mobile Devices to Immersive Virtual Environments

Résumé Enhancing interaction between users and 3D environments is a challenging research question that is fundamental for the positive widespread of interactive 3D graphics in many fields of our societies (e.g. education and art). In this document, I present various 3D User Interfaces (3D UIs) we have developed these past few years, and that contribute to this general quest. The first chapter focuses on 3D interaction for mobile devices. In particular, I present 3D UIs for interaction from keystrokes, and for interaction from stylus/finger input. Then, I present two multi degrees-of-freedom prototypes based on the embedded cameras of mobile devices. In the second chapter, I concentrate on 3D interaction for general touch-screens (e.g. tables and large interactive screens). I present Navidget, an example of 3D UI dedicated to camera viewpoint control from pen/finger inputs, and I discuss the challenges of 3D interaction on multi-touch devices. Finally, the third chapter of this document is dedicated to immersive virtual environments, with a strong focus on musical interfaces. I present the new directions we have explored to enhance interaction between musicians, audiences, sounds, and interactive 3D environments. I conclude by discussing some directions for the future of 3D User Interfaces.