Miracle-dz/UniFAR-FTUs huggingface dataset:
Generating 3D Model for Human Body Shapes from 2D images using Deep Learning

Online shopping started to grow all over the world in the last decade, predominantly in the last year due to COVID19. As a result of the lockdown and because many people did not want to take the risk of visiting stores not to be infected, customers direct their full attention to online shopping. That affected both customers and stores’ owners since customers always spend a long time trying to pick the right size and fail most of the time causing high percentage of returns which affects stores’ sales. In this paper part of the solution is introduced by collecting 5 anthropometric parameters from the user and the rest is predicted using an imputation strategy. Feature selection techniques are also applied and a 3D model for the human body is presented to the user on a mobile application.
Performance Analysis of Polar Codes against Rain Attenuation in Ka-band Satellite Communication

In satellite communication, Ka-band has gradually become a hotspot for solving the problem of band resource shortage. In order to against the varying channel distortion in Ka-band caused by rain attenuation and large-scale fading, polar codes, which show strong ability to correct errors and can flexibly specify the data rate to meet the demands of different situations, can be adopted to improve the communication performance. The paper establishes the model of channel attenuation in Ka-band and conducts performance simulation of system using polar codes. Results show that compared with the uncoded situation, rate-1/8 polar codes can achieve a considerable gain of 22dB.
Analysis of Interlaboratory Safety Related Tests in Power and Force Limited Collaborative Robots

The use of collaborative robots in the industrial domain has significantly grown in the last years, allowing humans to operate in the same workspace occupied by robots without any physical barriers. Understandably, the safety of the human operator has been a major concern both for researchers and regulatory bodies. The power and force limited modality of robots is of particular interest in that sense, being used in order to bound the energy of eventual collisions when a close physical interaction with humans is necessary. Such an interaction modality allows the robotic system to operate without the use of barriers, but a measurement of the force and pressure occurring due to a contact must be provided as part of the risk assessment. However, the precise procedure to follow in order to reliably provide such measures is still unclear for users and system integrators willing to self-assess the safety of their own collaborative robotic system. In this work, the repeatability and reliability of such testing procedures and measures are analyzed with an interlaboratory comparison approach, with the aim to establish the degree of variability possibly encountered when performing the same test under slightly different conditions.
Risk-aware Mission Design for In situ Asteroid Exploration under Uncertainty

In-situ robotic asteroid exploration is integral to current and future space programs for sustainable human exploration and resupply in deep space, deflection of potentially hazardous objects, and study of the early solar system formulation. Meanwhile, dynamical environments around asteroids are highly perturbed and uncertain, and pose challenges for spacecraft to safely navigate around them. The dynamics are influenced by a variety of sources of uncertainty, such as asteroid properties, exogenous disturbances, and errors associated with operations. These uncertainties need to be properly quantified and taken into account of the mission design processes. On the other hand, characteristics of such uncertainties are not usually given or fixed but rather dependent on the mission architecture and operational scenarios. To aid in the decision-making processes with trade-offs between the mission feasibility and uncertainties, mission designers need to quantify the feasibilities of a number of architectures for a range of possible combinations of uncertainty characteristics. To explore the solution space efficiently and reliably, this paper presents a systematic approach that leverages techniques from the fields of stochastic optimal control and convex optimization. Formulated as a convex optimization problem, the solution method enables us to solve many number (as many as ~ 105) of stochastic optimal control problems without initial guesses. The proposed approach is applied to the design of asteroid global-mapping campaigns, which demonstrates the effectiveness and validity of our approach. The result reveals important trade-off relationships between the mission feasibility and assumed uncertainty characteristics in the context of asteroid global mapping. While the convex formulation involves a dynamical approximation, the validity of the convex-programming-based solutions is confirmed through nonlinear Monte-Carlo simulations under the original dynamics.
Custom High-Performance-Computing Software Justification: Advanced Thermoelectric Prediction Model (ATPM)

Custom high-performance-computing software is expensive and time consuming to develop and verify; therefore, expending the resources to develop such software needs to be rationalized. Predicting radioisotope thermoelectric generator (RTG) performance is such a case where the software development effort can be justified. Some of the demands of such a modeling tool are time and temperature dependent material properties, anisotropic materials, quasi-steady state analysis, thousands of components, multi-physics (thermal conduction, thermal radiation, electrical conduction, thermoelectric effect, sublimation, etc.), and variable dimensions. Each of the above will slow down the computation of a single simulation, combining that slow down with the need to perform multi-parameter non-linear optimization, Monte Carlo analysis, and parametric studies; thousands to millions of simulations are often required. Current commercial general-purpose modeling tools meet the RTG modeling demands, but run times are impractical and/or require expensive computational resources (cost prohibitive or scheduling prohibitive). This leads to the effort to design a custom modeling tool for RTG's. The financial costs, personnel costs, and performance are compared for a variety of modeling solutions including other custom options and commercial software. Benefits of configuration management options, verification options, validation options, and long-term support are discussed. Lastly, the versatility of the custom model versus the commercial solutions are compared.
FAWOS: Fairness-Aware Oversampling Algorithm Based on Distributions of Sensitive Attributes

With the increased use of machine learning algorithms to make decisions which impact people’s lives, it is of extreme importance to ensure that predictions do not prejudice subgroups of the population with respect to sensitive attributes such as race or gender. Discrimination occurs when the probability of a positive outcome changes across privileged and unprivileged groups defined by the sensitive attributes. It has been shown that this bias can be originated from imbalanced data contexts where one of the classes contains a much smaller number of instances than the other classes. It is also important to identify the nature of the imbalanced data, including the characteristics of the minority classes’ distribution. This paper presents FAWOS: a Fairness-Aware oversampling algorithm which aims to attenuate unfair treatment by handling sensitive attributes’ imbalance. We categorize different types of datapoints according to their local neighbourhood with respect to the sensitive attributes, identifying which are more difficult to learn by the classifiers. In order to balance the dataset, FAWOS oversamples the training data by creating new synthetic datapoints using the different types of datapoints identified. We test the impact of FAWOS on different learning classifiers and analyze which can better handle sensitive attribute imbalance. Empirically, we observe that this algorithm can effectively increase the fairness results of the classifiers while not neglecting the classification performance. Source code can be found at: https://github.com/teresalazar13/FAWOS
Precision-Driven Partial Ambiguity Resolution Technique for Short to Medium Baseline Positioning

GNSS carrier phase observations are fundamental for safety-critical applications where the requirements of accuracy and availability are stringent. Upon the deployment of new GNSS constellation and frequencies, the large number of observations can lead to a decreased probability of successfully mapping the real-valued carrier phase ambiguities to integer ones. Partial Ambiguity Resolution (PAR) relaxes the condition of fixing the complete set of ambiguities and finds instead the subset which maximizes the success rate or grants a low failure rate. This work introduces Precision-Driven (PD) PAR, a technique for which a constraint on the formal precision of the fixed solution is added, and the subset selection is realized based on the projection of the ambiguities into the position domain. The performance characterization is realized on a synthetic scenario, where observations from a triple-frequency, triple-constellation are employed and the estimation is realized on a snapshot (memoryless) manner.
Global Pain State Questionnaire: Reliability, Validity, and Gender Gap

Objective: To quantify patients’ pain more objectively is essential to guide an individualized therapy, all the more so in patients under long-term opioid-use. Only a thoughtful and objective understanding of risks and benefits could improve an individualized standard of care. Our aim was to assess metric reliability and validity of an integrated and self-report Global Pain Status questionnaire to quantify the impact of pain on patient’s health in a more precise manner. Methods: A cross-sectional study was conducted to analyse the reliability, agreement, and validity of an integrated questionnaire compared to isolated scales, due to kappa statistics, intra- class and other correlation coefficients. Level of pain (intensity and relief), quality of life, most prevalent analgesic adverse events and hospital frequentation were registered in a total of 38 cases (pain unit patients) and 52 painless matched-controls. A reduced multitrait-multimethod matrix and a canonical-correlation analysis were developed together with a multiple linear regression. Results: Cases (56 ± 10 years old, 63% females, pain intensity 66 ± 23 mm, incidence rate of 5 adverse events) represented a regular pain population. A high intraobserver correlation (r0.75- 0.88, weighted-κ 0.41–0.51, unweighted-κ 0.66-0.82) was evidenced together with significant correlation coefficients in test-retest reliability, and for validity, even more, in a reduced multitrait-multimethod matrix (>0.8) and canonical-correlation (>0.95). A gender gap was evidenced in cases’ companions, mostly middle-aged females (78%), who experienced negative effects on their health. Conclusions: The Global Pain Status questionnaire is an evaluation instrument with enough reliability and validity, being a low-cost method to determine the multidimensional pain management at clinical routine. A gender-gap within pain caregivers was found that affect their health outcomes. Support interventions for pain patients’ companions should consider specific gender risk factors.
Effect of Pediatric Orthopedic Bundle guideline on Nurses' Performance Regarding Surgical Site Infections

The occurrence of surgical site infections (SSIs) in orthopedic surgeries results in reduced quality of life, increased hospital length of stay, increased likelihood of mortality, higher change of readmissions and reinterventions. Aim of the study: to evaluate the effect of pediatric orthopedic bundle guidelines on nurses' performance regarding surgical site infections for children undergoing orthopedic surgeries. Design: A Quasiexperimental research design was (pre/post-test) utilized to conduct the current study. Settings: The study was conduct at orthopedic surgery departments at Benha University Hospital, Benha Health Insurance Hospital and Benha Teaching Hospital. Subjects: A convenient sample of all available nurses (124) working at the previously mentioned study settings regardless of their personal characteristics. Tools of data collection: Two tools were used; a structural interviewing questionnaire to collect personal data of the studied nurses and their knowledge regarding orthopedic surgeries, surgical site infections and bundle of nursing care to reduce surgical site infections. The second tool; Centers for Disease Control and Prevention Guideline for the Prevention of Surgical Site Infection. Results: The study results showed that there was a highly statistical significant improvement in total nurses' performance after implementation of Pediatric Orthopedic Bundle guidelines. Moreover, there was a highly statistically significant relation in nurses’ practice and their educational level, occupation, years of experience, and attendance of training courses. Conclusion: Based on the present study findings, it was concluded that there was unsatisfactory knowledge as well as an incompetent practice among nurses regarding surgical site infections before the orthopedic bundle guideline compared with after implementation, and there was an improvements in nurses’ knowledge and performance regarding surgical site infections. Recommendations: The study recommended that implementing the Pediatric Orthopedic Bundle guidelines for staff nurses are important to improve care provided to children in orthopedic departments to reduce surgical site infection.
Effect of loading on organic matter removal and nitrification in membrane aeration bioreactor

The effects of organic loading and nitrogen loading on organic matter removal and nitrification in membrane aeration bioreactor under the condition that the simulant domestic wastewater concentration changing stagely were discussed.The results showed that,when the TOC loading and the TN loading varied from 6.6 g/(m2·d) and 3.2 g/(m2·d) to 26 g/(m2·d) and 5.8 g/(m2·d) respectively,the mass ratio of C to N varied from 2.1 to 4.6,the removal rate of TOC ranging between 94% and 97%. The nitrification efficiencies were about 90% when C/N ratios varied from 2.1 to 3.7,while it decreased to about 81% at C/N ratio of 4.6. In the first stage,when the C/N ratio was 2.85,the TN loading varied from 2.5 to 9.5 g/(m2·d),the TOC removal rate was 95%,and the maximum nitrification efficiency and nitrification rate were 7.5 g/(m2·d) and 90% respectively.Comparing with traditional biological membranes,membrane aeration bioreactor could improve the organic matter removal rate and the nitrification efficiency simultaneously when treating wastewater.
Synthesis, Characterization, and Electrochemistry of Nanotubular Polypyrrole and Polypyrrole-Derived Carbon Nanotubes

Polypyrrole nanotubes (PPy-NTs) were prepared by the oxidation of pyrrole with iron(III) chloride in the presence of a structure-guiding agent, methyl orange. Upon carbonization of the salt form of PPy-NTs, the conducting nitrogen-containing nanotubular carbonaceous material (C-PPy-NT) was obtained. The morphology, structure, and physicochemical properties of PPy-NTs in salt and base form as well as C-PPy-NTs were investigated by transmission electron microscopy, Fourier transform infrared and Raman spectroscopies, conductivity measurements, elemental microanalysis, inductively coupled plasma optical emission spectroscopy, X-ray photoelectron spectroscopy, and nitrogen physisorption. Results of the material characterization were linked to their electrochemical behavior. Specific capacitance of around 120 F g–1 at low potential sweep rate of 5 mV s–1 was observed for original PPy-NTs. However, when the potential sweep rate was increased to 100 mV s–1, PPy-NT salt retained the value of specific capacitance,.
Contested Ground: Disentangling Material and Symbolic Attachment to Territory

A large literature argues that territorial disputes are prone to conflict because of the value of territory to publics, whether due to its strategic and material worth, or to its intangible, symbolic value. Yet despite the implications of the distinction for both theory and policy, empirically disentangling the material from the symbolic has posed a formidable methodological challenge. We propose a method for assessing the nature of individual territorial attachment, drawing on a series of survey experiments in Israel. Our empirical analysis illustrates how the distribution of territorial preferences in the domestic population can have powerful implications for conflict and its resolution. ∗Arizona State University †University of Pennsylvania ‡Columbia University
Bulk Transfer Scheduling with Deadline in Best-Effort SD-WANs

Many cloud providers have multiple geo-distributed inter-connected datacenters around the globe. These datacenters are increasingly being inter-connected using software-defined WANs (SD-WANs), which extend the capabilities of SDN architecture to wide-area networks. While conventional MPLS tunneling has proven to be a practical approach for inter-connecting datacenters, such tunnels have a static nature and incur substantial maintenance costs. Given the centralized control and programmability of SDN, it is possible to utilize multiple Internet tunnels to provide a low-cost alternative to MPLS tunnels in SD-WANs. However, the best-effort nature of Internet tunnels means that they undergo capacity fluctuations throughout the day, making it difficult to provide any service guarantees such as completion time for inter-datacenter transmissions. In this paper, we consider the problem of scheduling bulk transfer requests with deadline in a best-effort SD-WAN. We propose an approximate scheduling algorithm called xBESD which utilizes tunnel capacity estimations to design a robust transfer schedule that maximizes a cloud provider’s profit by transmitting bulk transfers before their deadlines. We analyze xBESD and show that it attains an approximation ratio that only depends on the number of overlapping requests that have the same profit to bandwidth ratio. Furthermore, we provide extensive simulation as well as realistic Mininet experimental results to assess the performance of xBESD in a variety of network scenarios. Our results show that xBESD improves the provider’s profit by approximately 60% on average compared to other baseline scheduling methods, in addition to cutting down the Internet service provider costs.
EXERCISE INTENSITY DURING SOCCER TRAINING DRILLS WITH PROFESSIONAL SOCCER PLAYERS

Little, T. , and A.G. Williams. Measures of exercise intensity during soccer training drills with professional soccer players. J. Strength Cond. Res. 21(2):367–371. 2007. —Recent evidence supports the use of certain soccer drills for combined technical and physical training. Therefore, it is important to be able to accurately monitor training intensity during soccer drills intended for physical development to allow the optimization of training parameters. Twenty-eight professional soccer players were assessed for heart rate (HR) and rating of perceived exertion (RPE) responses to 5 commonly used soccer training drills (2v2 to 8v8 drills). The responses of both HR and RPE differed significantly (p ! 0.05) between the drills, generally showing an elevated response to drills involving lower player numbers. However, the 2v2 drill showed a significantly (p ! 0.05) lower HR response (mean " SD: 88.7 " 1.2% HRmax) than 3v3 (91.2 " 1.3% HRmax) and 4v4 drills (90.2 " 1.6% HRmax). There was no significant correlation between the HR and RPE responses to the various drills (r # 0.60, p # 0.200). This poor relationship is probably because during the 2v2 drill, RPE was higher than during any of the other 6 drills, whereas HR was only fourth highest of the 6 drills. This demonstrates that HR and RPE are only poorly related during the intense drills used in this study, and that HR underestimates the intensity of the 2v2 drill. Heart rate demonstrated lower intersubject variability (1.3–2.2%) than RPE (5.1–9.9%). However, unlike HR, Borg 15-point RPE appears to be a valid marker of exercise intensity over a wide range of soccer training drills by maintaining validity in all drills and demonstrating acceptable intersubject variability. A combination of both HRand RPE-based training load calculations appears optimal for use in soccer training.
An Approach for Finding Semantic Relatedness Score Between Two Sentences Based on their Senses

Corresponding Author: Nazreena Rahman Department of Computer Science and Engineering, Kaziranga University, India Email: nazreena.rehman@gmail.com Abstract: Finding semantic relatedness score between two sentences is useful in many research areas. Existing relatedness methods do not consider its sense while computing semantic relatedness score between two sentences. In this study, a Word Sense Disambiguation (WSD) method is proposed which is used in finding the sense-oriented sentence semantic relatedness measure. The WSD method is used to find the correct sense of a word present in a sentence. The proposed method uses both the WordNet lexical dictionary and the Wikipedia corpus. The sense-oriented sentence semantic relatedness measure combines edge-based score between words depending the context of the sentence; sense based score which finds sentences having similar senses; as well as word order score. We have evaluated the proposed WSD method on publicly available English WSD corpora. We have compared our proposed sense-oriented sentence semantic relatedness measure on standard datasets. Experimental analysis illustrates the significance of proposed method over many baseline and current systems like Lesk, UKB, IMS, Babelfy.
Impact of wired telecommunication network latency on demand-side management in smart grids

Demand-side management relies on the flexibility of consumers’ load to avoid electrical network issues, including grid congestion. Recent advances in smart grid systems (also called Energy Internet) allow using demand-side management reactive strategies based on the dynamical shedding of residential consumers appliances. Both centralized and decentralized approaches are considered in literature, depending on the considered system size, but only few contributions consider the potential impact of the telecommunication network on their performance. In this paper, we conduct a comparative analysis on a realistic scenario based on representative power consumption time series of a residential power system. Our results show that latency may have a significant impact on energy management strategies in terms of performance for the smart grid, and that it should be considered when designing such strategies.
Transformer-Based Deep Survival Analysis

In this work, we propose a new Transformer-based survival model which estimates the patient-specific survival distribution. Our contributions are twofold. First, to the best of our knowledge, existing deep survival models use either fully connected or recurrent networks, and we are the first to apply the Transformer in survival analysis. In addition, we use ordinal regression to optimize the survival probabilities over time, and penalize randomized discordant pairs. Second, many survival models are evaluated using only the ranking metrics such as the concordance index. We propose to also use the absolute error metric that evaluates the precise duration predictions on observed subjects. We demonstrate our model on two publicly available real-world datasets, and show that our mean absolute error results are significantly better than the current models, meanwhile, it is challenging to determine the best model under the concordance index.