Miracle-dz/UniFAR-FTUs huggingface dataset:
On Gesture Combination: An Exploration of a Solution to Augment Gesture Interaction

Current gesture interaction paradigm mainly involves a one-to-one gesture-command mapping. This leads to memorability issues regarding (1) the mapping - as each new command requires a new gesture, and (2) the gestures specifics (e.g., motion paths) - that can be complex to leverage the recognition of several gestures. We explore the concept of combining 3D gestures when interacting in smart environments. We first propose a design space to characterize the temporal and spatial combination aspects, and the gesture types used by the combination. We then report results from three user studies in the context of smart TV interaction. The first study reveals that end-users can create gesture sets with combinations fully optimized to reuse gestures. The second study shows that combining gestures can lead to improved memorability compared to single gestures. The third study reveals that preferences for gestures combination appear when single gestures have an abstract gesture-command mapping.
Understanding Multilingual Four-Scene Comics with Deep Learning Methods

Artificial intelligence has been developed tremendously in the last decades and is applied in many fields nowadays. On the other hand, understanding human creations is one of the most important subject concerning AI. Comic computing is a branch of computing dealing with comics in engineering. In this field, multimodal data with natural languages and pictures are used. Although tasks such as comic frame recognition in comic computing are performed using image processing techniques, artificial intelligence focuses on pictures in comics rather than the comic content to solve these tasks. To make models understand the contents in comics, we should deal with natural languages in comics in the form of character words. We used a dataset which was suitable for analysing comic contents and set up tasks for the analysis of four-scene comics. However, the current dataset was only in Japanese, therefore we have proposed an English version of the dataset in this paper. In order to extend our research to foreign countries, we consider that having a multilingual dataset is required. We did a comparison study between the Japanese version and the English version by the means of sentimental analysis. We demonstrated and analysed the results to determine the feasibility of computers understanding comics. From the results, we could remark that it was possible to obtain a good accuracy rate with our multilingual dataset. As a matter of fact, it was possible to show results similar to the ones from the original Japanese version. Hence, our research can be extended to multiple languages without affecting the output.
Structured Sparse Matrix Sketching based Detection for Media-Based Modulation

In this paper, we consider media-based modulation (MBM) in a cyclic-prefixed single-carrier setting (CPSC-MBM) in inter-symbol interference channels and focus on low-complexity signal detection at the receiver. For this, we exploit the structured sparsity that is inherently present in CPSC-MBM signals. We formulate the sparse vector detection problem of interest as an equivalent sparse matrix detection problem, whose reconstruction complexity can be significantly less without incurring much loss in recovery performance. This technique of recovering sparse matrices, termed as {\em sparse matrix sketching}, applied to CPSC-MBM signal recovery is shown to achieve good bit error performance with significant complexity gains compared to the sparse vector detection approach.
How Do People Change Their Technology Use in Protest?

Researchers and the media have become increasingly interested in protest users, or people who change (protest use) or stop (protest non-use) their use of a company's products because of the company's values and/or actions. Past work has extensively engaged with the phenomenon of technology non-use but has not focused on non-use (nor changed use) in the context of protest. With recent research highlighting the potential for protest users to exert leverage against technology companies, it is important for technology stakeholders to understand the prevalence of protest users, their motivations, and the specific tactics they currently use. In this paper, we report the results of two surveys (n = 463 and n = 398) of representative samples of American web users that examine if, how, and why people have engaged in protest use and protest non-use of the products of five major technology companies. We find that protest use and protest non-use are relatively common, with 30% of respondents in 2019 reporting they were protesting at least one major tech company. Furthermore, we identify that protest users' most common motivations were (1) concerns about business models that profit from user data and (2) privacy; and the most common tactics were (1) stopping use and (2) leveraging ad blockers. We also identify common challenges and roadblocks faced by active and potential protest users, which include (1) losing social connections and (2) the lack of alternative products. Our results highlight the growing importance of protest users in the technology ecosystem and the need for further social computing research into this phenomenon. We also provide concrete design implications for existing and future technologies to support or account for protest use and protest non-use.
CONTRASTING BIOMECHANICS OF ACUTE HAMSTRING STRAINS

Hamstring strains are common in sports. Recently, two different types of hamstring strain have been described, one related to sprinting, the other to stretching exercises (Askling et al., 2006). MRI showed that the sprint-related injury was situated in the long head of the biceps femoris muscle (Askling et al. 2007). Biomechanical modelling has been used to explore mechanisms of the sprint-related injury (Thelen et al. 2006). The purpose here was to contrast the stretch-related injury with the sprint-related one, with respect to injury location and biomechanics.
Managing Beyond the Comfort Zone: An Exploratory Study of IS Project Managers

This paper reports preliminary results from a case research on the question of how project managers adapt to managing IS projects when the project is beyond their comfort zone. ‘Comfort zone’ is used in this study to denote the area or areas in which a project manager has technical expertise, or a background in a particular area of IS, and at the same time a good understanding of project management methodologies. The main finding from this study is the development of an emergent model of Active Knowledge Gapping which describes the processes that project managers use when they adapt to managing IS projects which are beyond their comfort zone.
Strategic Management of Supply Base for Product Innovation from Resource Dependence Perspective ( Full Paper Submission )

This paper uses the resource dependence theory to understand as to how buyers develop, control, align, and utilize supply base to obtain enhanced product innovation to improve buyer performance. The study uses data from 296 companies from India and Pakistan to test the hypotheses using structural equation modeling and PLS approach. Overall, the study finds that buyer’s innovation strategy positively impacts product innovation through innovation intent, potential, and engagement of supply base. Also, the study finds support for the positive moderation effect of engaging suppliers on supply-base potential. Comparative analysis of Indian and Pakistani datasets endorse the direct relationships.
ed Trial of a Mobile Phone Personalized Behavioral Intervention for Blood Glucose Control

OBJECTIVE—To test whether adding mobile application coaching and patient/provider webportalstocommunityprimarycarecomparedwithstandarddiabetesmanagementwouldreduceglycated hemoglobin levels in patients with type 2 diabetes.RESEARCHDESIGNANDMETHODS—Acluster-randomizedclinicaltrial,theMobileDiabetesInterventionStudy,randomlyassigned26primarycarepracticestooneofthreesteppedtreatment groups or a control group (usual care). A total of 163 patients were enrolled andincluded in analysis. The primary outcome was change in glycated hemoglobin levels over a1-year treatment period. Secondary outcomes were changes in patient-reported diabetes symp-toms, diabetes distress, depression, and other clinical (blood pressure) and laboratory (lipid)values. Maximal treatment was a mobile- and web-based self-management patient coachingsystem and provider decision support. Patients received automated, real-time educational andbehavioral messaging in response to individually analyzed blood glucose values, diabetes med-ications, and lifestyle behaviors communicated by mobile phone. Providers received quarterlyreports summarizing patient’s glycemic control, diabetes medication management, lifestylebehaviors, and evidence-based treatment options.RESULTS—The mean declines in glycated hemoglobin were 1.9% in the maximal treatmentgroup and 0.7% in the usual care group, a difference of 1.2% (P , 0.001) over 12 months.Appreciabledifferenceswerenotobservedbetweengroupsforpatient-reporteddiabetesdistress,depression, diabetes symptoms, or blood pressure and lipid levels (all P . 0.05). CONCLUSIONS—Thecombinationof behavioralmobile coachingwithbloodglucosedata,lifestyle behaviors, and patient self-management data individually analyzed and presented withevidence-based guidelines to providers substantially reduced glycated hemoglobin levels over1year.Diabetes Care 34:1934–1942, 2011
Weighted Fair Precoding Based on Traffic Demands for Multibeam Satellite Systems

In this paper, a linear precoding scheme is proposed to maximize the total throughput of a broadband geostationary earth orbit (GEO) satellite system based on traffic demands. The weighted max-min fair (WMMF) problem under the per-antenna power constraints and the traffic demands constraints is investigated to achieve this purpose. Semidefinite relaxation (SDR) approach and bisection search method are jointly adopted to solve the corresponding related problem, and then Gaussian randomization and a power control problem are proposed to get a suboptimal solution of the WMMF problem. Different traffic demands scenarios and weighted values selection schemes are considered to analyze the impact of them on the precoding design. Simulation results demonstrate that the total performance of the proposed scheme has been improved significantly over the traditional schemes and is better than the rate balance scheme.
Applying Long Short-Term Memory (LSTM) Mechanisms for Fingerprinting Outdoor Positioning in Hybrid Networks

Recently, Location Based Services (LBSs) becomes an important technology to enhance the applicability of Internet-of-Things (IoT) to provide better services in wireless environments. The Global Positioning System (GPS) is not always optimal for urban and suburban areas to provide positioning services. Because GPS is easily affected by signal fluctuations and shadowing effects in a complex and dynamic environments, consumes much power and it is hardware dependent. In this paper, we present an accurate Fingerprinting Outdoor Positioning Scheme (FOPS) that contains Wi-Fi and Orthogonal Frequency Division Multiplexing (OFDM) signal values as a dataset using Long Short-Term Memory (LSTM) network approach. To select the most representative features from Wi-Fi data, we apply Linear Discriminant Analysis (LDA) techniques as preprocessing stage to optimize positioning services. The experimental results revealed that, the proposed system achieves positioning results with error no more than 1.7 m. Moreover, the positioning time improved due to the integrations of LDA and LSTM algorithms. Therefore, the proposed system provides a promising positioning services of the IoT devices in wireless environments.
Long-Term Impact of Bariatric Surgery on Renal Outcomes at a Community-Based Publicly Funded Bariatric Program: The Regina Bariatric Study

Background: Obesity is recognized as an independent risk factor for chronic kidney disease through multiple direct and indirect biological pathways. Bariatric surgery is a proven, effective method for sustained weight loss. However, there is a relative paucity of data on the impact of bariatric surgery on renal outcomes. Objective: The primary objective was to evaluate the change in urine albumin/creatinine ratio (ACR) in patients undergoing bariatric surgery, at 12 months after the procedure. Secondary objectives were to determine the changes in ACR at (6 and 24 months), estimated glomerular filtration rate (eGFR; 6, 12, and 24 months), and hemoglobin A1c (HbA1c); 12 and 24 months) after the procedure. Design: This observational retrospective cohort study included consecutive obese patients who underwent bariatric surgery. Setting: Provincial Bariatric Surgery Clinic at the Regina General Hospital, Saskatchewan. Patients: This study includes 471 consecutive obese adult patients who underwent bariatric surgery between 2008 and 2015. Measurements: We studied the impact of bariatric surgery on body mass index (BMI), renal outcomes (urine ACR and eGFR) and metabolic outcomes (fasting glucose, total cholesterol, low-density lipoprotein, triglycerides, and HbA1c) in 471 patients. Methods: Patients were followed for 2 years postsurgery in the bariatric clinic. Mixed linear models that accounted for the repeated nature of the data were used to access changes in outcomes over time. Results: Patients were predominantly female (81%) with a mean age (±SD) of 46 ± 10 years. Most patients (87%) had a BMI > 40 kg/m2 and 81% of the patients underwent Roux-en-Y gastric bypass. The mean BMI decreased from 47.7 ± 7.8 kg/m2 at baseline to 37.1 ± 7.9 kg/m2 at 6 months and 34.8 ± 8.8 kg/m2 at 12 months. In a subcohort of patients with microalbuminuria, ACR showed an improvement from a median [interquartile] value of 5.1 [3.7-7.5] mg/mmol at baseline to 2.3 [1.2-3.6] mg/mmol at 6 months (P = .007), to 1.4 [0.9-3.7] mg/mmol at 2-year follow-up (P < .001). Similarly, eGFR increased in patients with microalbuminuria from 109 ± 10 mL/min/1.73 m2 at baseline to 120 ± 36 mL/min/1.73 m2 at 2-year follow-up (P = .013). There were statistically significant reductions in triglycerides, fasting glucose, and HbA1c. Limitations: This was a retrospective chart review, with the lack of a control group. Patients with eGFR less than 60 mL/min/1.73 m2 were not considered for surgery, and we had to measure renal outcomes predominantly on the presence of proteinuria. Conclusions: Our results suggest bariatric surgery significantly decreased weight and consequently improved renal and metabolic outcomes (eGFR, ACR, fasting glucose, cholesterol, and triglycerides) in patients with elevated BMI.
What do We Expect from Comic Panel Extraction?

Among comic elements including panels, balloons, comic characters, texts, etc. panels play an important role in content adaptation and story animation for small devices such as mobile phones or tablets. Different panel extraction techniques have been investigated over the last ten years; most of the existing approaches rely on the assumption that a comic panel is either simple as a rectangle or more complex as a polygon having 4 edges. In this paper, we re-examine the definition of comic panels, is a 4-edge polygon really sufficient to represent integral information of a comic panel? We suggest using a modern definition of comic panels, together with a strong panel extraction baseline method for the approach.
MalMax: Multi-Aspect Execution for Automated Dynamic Web Server Malware Analysis

This paper presents MalMax, a novel system to detect server-side malware that routinely employ sophisticated polymorphic evasive runtime code generation techniques. When MalMax encounters an execution point that presents multiple possible execution paths (e.g., via predicates and/or dynamic code), it explores these paths through counterfactual execution of code sandboxed within an isolated execution environment. Furthermore, a unique feature of MalMax is its cooperative isolated execution model in which unresolved artifacts (e.g., variables, functions, and classes) within one execution context can be concretized using values from other execution contexts. Such cooperation dramatically amplifies the reach of counterfactual execution. As an example, for Wordpress, cooperation results in 63% additional code coverage. The combination of counterfactual execution and cooperative isolated execution enables MalMax to accurately and effectively identify malicious behavior. Using a large (1 terabyte) real-world dataset of PHP web applications collected from a commercial web hosting company, we performed an extensive evaluation of MalMax. We evaluated the effectiveness of MalMax by comparing its ability to detect malware against VirusTotal, a malware detector that aggregates many diverse scanners. Our evaluation results show that MalMax is highly effective in exposing malicious behavior in complicated polymorphic malware. MalMax was also able to identify 1,485 malware samples that are not detected by any existing state-of-the-art tool, even after 7 months in the wild.
POSTER: Variable Sized Cache-Block Compaction

Data blocks compressed to different sizes can be stored together inside a single cache-block to increase space utilization. However, the lack of a common size offset makes it challenging to locate individual blocks without additional tag overhead. We propose Variable Sized Cache-Block Compaction (VSCC) that allows us to store variable sized compressed blocks together and locate them inside a cache-block by using their compression encodings – available inside the tag metadata. We introduce a novel read/write scheme and a new BDI compression encoding, which reduce the necessary operations by 50%. Experimental results reveal that VSCC outperforms state-of-the-art techniques from the performance and energy point of view while keeping the storage overheads within acceptable limits.
Scalability analysis of optical Beneš networks based on thermally/electrically tuned Mach-Zehnder interferometers

Silicon Photonic interconnects are a promising technology for scaling computing systems into the exa-scale domain. However, significant challenges exist in terms of optical losses and complexity. In this work, we examine the applicability of thermally/electrically tuned Beneš network based on Mach-Zehnder Interferometers for on-chip interconnects as regards its scalability and how optical loss and laser power scale with the number of endpoints. In addition, we propose three hardware-inspired routing strategies that leverage the inherent asymmetry present in the switching components. We evaluate a range of NoC sizes, from 16 up to 1024 endpoints, using 4 realistic workloads and found very promising results. Our routing strategies offer an optical loss reduction of up to 32% as well as a laser power reduction by 33% for 32 endpoints.
Estimation of Volatile Organic Compounds (VOCs) and Human Health Risk Assessment of Simulated Indoor Environment Consisting of Upholstered Furniture Made of Commercially Available Foams

This study was conducted for the qualitative and quantitative determination of volatile organic compounds (VOCs) and total volatile organic compounds (TVOC) from polymeric foam materials used in upholstered furniture. Six different types of foams viz. Highly elastic foam K5040, standard PU foam N5063, bonded polyurethane foam R100, viscoelastic foam V5020, self-extinguishing foam KF5560, and foam rubber were used. Short-term and long-term (24, 48, 72, 672 hours (28 day)) measurements were done to differentiate the role of primary emissions (present in new products) and secondary emissions (due to chemical reactions in material or slowly released due to the porous structure of material). The samples were collected using a small-space sampling chamber at a temperature of 23°C and a humidity of 50% depending on the aspect of time. The concentrations of VOC and TVOC were identified and quantified using a Gas chromatography–Mass spectroscopy (GC-MS) based method. Based on the VOC measurements, the standard room concentrations were simulated to estimate the human health risk assessment for all six types of foams. The results of simulations suggest no possibility of human health risk for the very long period (28 days), as the estimated values were found to be much below the prescribed limits.
When Indoor Localization Meets New Communication Technologies

Accurate and low-cost indoor localization continues to be a research challenge. The emerging communication technologies in 5G and 802.11 standards (e.g., 802.11n and 802.11 ac), such as massive MIMO and mmWave, provide opportunities for accurate indoor localization. Meanwhile, location information is also critical for the development of new technologies, e.g., directional communication using beamforming. It leads to a synergistic relationship between localization and communication. In this paper, we review the potential benefits of the emerging communication technologies (i.e., smart antennas, Massive MIMO, mmWave, beamforming, CSI) for indoor localization. It may provide a useful guide for researchers who are interested in developing indoor localization systems based on emerging communication technologies.
Should We Use an Abstract Comic Form to Persuade?

This paper examines the use of the abstract comic form for persuading online charitable donations. Persuading individuals to contribute to charitable causes online is hard and responses to the appeals are typically low; charitable donations share the structure of public goods dilemmas where the rewards are distant and non-exclusive. In this paper, we examine if comics in abstract form are more persuasive than in the plain text form. Drawing on a rich literature on comics, we synthesized a three-panel abstract comic to create our appeal. We conducted a between-subject study with 307 participants from Amazon Mechanical Turk on the use of abstract comic form to appeal for charitable donations. As part of our experimental procedure, we sought to persuade individuals to contribute to a real charity focused on Autism research with monetary costs. We compared the average amount of donation to the charity under three conditions: the plain text message, an abstract comic that includes the plain text, and an abstract comic that additionally includes the social proof. We use Bayesian modeling to analyze the results, motivated by model transparency and its use in small-sized studies. Our experiments reveal that the message in abstract comic form elicited significantly more donations than text form (medium to large effect size=0.59). Incorporating social proof in the abstract comic message did not show a significant effect. Our studies have design implications: non-profits and governmental agencies interested in alleviating public goods dilemmas that share a similar structure to our experiment (single-shot task, distant, non-exclusive reward) ought to consider including messages in the abstract comic form as part of their online fund-raising campaign.