Towards a new ITU-T recommendation for subjective methods evaluating gaming QoE

This paper reports on activities in Study Group 12 of the International Telecommunication Union (ITU-T SG12) to define a new Recommendation on subjective evaluation methods for gaming Quality of Experience (QoE). It first resumes the structure and content of the current draft which has been proposed to ITU-T SG12 in September 2014 and then critically discusses potential gaming content and evaluation methods for inclusion into the upcoming Recommendation. The aim is to start a discussion amongst experts on potential evaluation methods and their limitations, before finalizing a Recommendation. Such a recommendation might in the end be applied by non -expert users, hence wrong decisions in the evaluation design could negatively affect gaming QoE throughout the evaluation

Evil from Within: Machine Learning Backdoors through Hardware Trojans

Backdoors pose a serious threat to machine learning, as they can compromise the integrity of security-critical systems, such as self-driving cars. While different defenses have been proposed to address this threat, they all rely on the assumption that the hardware on which the learning models are executed during inference is trusted. In this paper, we challenge this assumption and introduce a backdoor attack that completely resides within a common hardware accelerator for machine learning. Outside of the accelerator, neither the learning model nor the software is manipulated, so that current defenses fail. To make this attack practical, we overcome two challenges: First, as memory on a hardware accelerator is severely limited, we introduce the concept of a minimal backdoor that deviates as little as possible from the original model and is activated by replacing a few model parameters only. Second, we develop a configurable hardware trojan that can be provisioned with the backdoor and performs a replacement only when the specific target model is processed. We demonstrate the practical feasibility of our attack by implanting our hardware trojan into the Xilinx Vitis AI DPU, a commercial machine-learning accelerator. We configure the trojan with a minimal backdoor for a traffic-sign recognition system. The backdoor replaces only 30 (0.069%) model parameters, yet it reliably manipulates the recognition once the input contains a backdoor trigger. Our attack expands the hardware circuit of the accelerator by 0.24% and induces no run-time overhead, rendering a detection hardly possible. Given the complex and highly distributed manufacturing process of current hardware, our work points to a new threat in machine learning that is inaccessible to current security mechanisms and calls for hardware to be manufactured only in fully trusted environments

Working With Environmental Noise and Noise-Cancelation: A Workload Assessment With EEG and Subjective Measures

As working and learning environments become open and flexible, people are also potentially surrounded by ambient noise, which causes an increase in mental workload. The present study uses electroencephalogram (EEG) and subjective measures to investigate if noise-canceling technologies can fade out external distractions and free up mental resources. Therefore, participants had to solve spoken arithmetic tasks that were read out via headphones in three sound environments: a quiet environment (no noise), a noisy environment (noise), and a noisy environment but with active noise-canceling headphones (noise-canceling). Our results of brain activity partially confirm an assumed lower mental load in no noise and noise-canceling compared to noise test condition. The mean P300 activation at Cz resulted in a significant differentiation between the no noise and the other two test conditions. Subjective data indicate an improved situation for the participants when using the noise-canceling technology compared to “normal” headphones but shows no significant discrimination. The present results provide a foundation for further investigations into the relationship between noise-canceling technology and mental workload. Additionally, we give recommendations for an adaptation of the test design for future studies

Quality of life in people with dementia living in nursing homes: validation of an eight-item version of the QUALIDEM for intensive longitudinal assessment

Purpose: Our aim was to examine whether quality of life which was repeatedly assessed over time is related with the comprehensive assessment of quality of life (QoL) and thereby to validate a brief QoL assessment. Method: This longitudinal study used a comprehensive assessment of quality of life at baseline (QUALIDEM; 37 items) to validate an eight-item version of QUALIDEM to assess momentary quality of life which was repeatedly administered using a tablet device after baseline. In all, 150 people with dementia from 10 long-term facilities participated. Momentary quality of life and comprehensive quality of life, age, gender, activities of daily living (Barthel Index), Functional assessment staging (FAST), and Geriatric Depression (GDS) have been assessed. Results: Comprehensive and momentary quality of life showed good internal consistency with Cronbach’s alpha of .86 and .88 to .93, respectively. For multiple associations of momentary quality of life with the comprehensive quality of life, momentary quality of life was significantly related to comprehensive quality of life (B = .14, CI .08/.20) and GDS (B = − .13, CI − .19/− .06). More specifically, the comprehensive QUALIDEM subscales ‘positive affect’, ‘negative affect’, ‘restlessness’, and ‘social relationships’ showed significant positive associations with momentary quality of life (p < .001). Conclusion: We found that momentary quality of life, reliably assessed by tablet, was associated with comprehensive measures of quality of life and depressive symptoms in people with dementia. Broader use of tablet-based assessments within frequent QoL measurements may enhance time management of nursing staff and may improve the care quality and communication between staff and people with dementia

Sulfated glycosaminoglycans inhibit transglutaminase 2 by stabilizing its closed conformation

Transglutaminases (TGs) catalyze the covalent crosslinking of proteins via isopeptide bonds. The most prominent isoform, TG2, is associated with physiological processes such as extracellular matrix (ECM) stabilization and plays a crucial role in the pathogenesis of e.g. fibrotic diseases, cancer and celiac disease. Therefore, TG2 represents a pharmacological target of increasing relevance. The glycosaminoglycans (GAG) heparin (HE) and heparan sulfate (HS) constitute high-affinity interaction partners of TG2 in the ECM. Chemically modified GAG are promising molecules for pharmacological applications as their composition and chemical functionalization may be used to tackle the function of ECM molecular systems, which has been recently described for hyaluronan (HA) and chondroitin sulfate (CS). Herein, we investigate the recognition of GAG derivatives by TG2 using an enzyme-crosslinking activity assay in combination with in silico molecular modeling and docking techniques. The study reveals that GAG represent potent inhibitors of TG2 crosslinking activity and offers atom-detailed mechanistic insights