Miracle-dz/UniFAR-FTUs huggingface dataset:
Massive MIMO With Massive Connectivity for Industrial Internet of Things

In this paper, we investigate the feasibility of using massive multi-in multi-out (MIMO) to provide connectivity to Industrial Internet of Things (IIoT) wirelessly. Single-cell massive MIMO is used to support a large number of low-power IIoT devices in the uplink simultaneously. To support a large number of devices simultaneously, orthogonal uplink reference signals are heavily reused, which severely compromises the quality of the channel estimation for all devices. We show that the attempt by zero-forcing (ZF) decoding to zero out the interference from a large number of devices results in very poor performance, whereas maximum ratio (MR) decoding outperforms ZF decoding by a large margin. We present theoretical closed-form equations of spectral efficiency for both MR and ZF processings with massive connectivity. Simulation results validate our theoretical analysis. Furthermore, we provide analyses that are useful for designing low-power massive IIoT networks using massive MIMO.
CNN-Based Fault Localization Method Using Memory-Updated Patterns for Integration Test in an HiL Environment

Automotive electronic components are tested via hardware-in-the-loop (HiL) testing at the unit and integration test stages, according to ISO 26262. It is difficult to obtain debugging information from the HiL test because the simulator runs a black-box test automatically, depending on the scenario in the test script. At this time, debugging information can be obtained in HiL tests, using memory-updated information, without the source code or the debugging tool. However, this method does not know when the fault occurred, and it is difficult to select the starting point of debugging if the execution flow of the software is not known. In this paper, we propose a fault-localization method using a pattern in which each memory address is updated in the HiL test. Via a sequential pattern-mining algorithm in the memory-updated information of the transferred unit tests, memory-updated patterns are extracted, and the system learns using a convolutional neural network. Applying the learned pattern in the memory-updated information of the integration test can determine the fault point from the normal pattern. The point of departure from the normal pattern is highlighted as a fault-occurrence time, and updated addresses are presented as fault candidates. We applied the proposed method to an HiL test of an OSEK/VDX-based electronic control unit. Through fault-injection testing, we could find the cause of faults by checking the average memory address of 3.28%, and we could present the point of fault occurrence with an average accuracy of 80%.
Dynamic Graph Algorithms

This report documents the program and the outcomes of Dagstuhl Seminar 22461 “Dynamic Graph Algorithms”, which took place from November 13 to November 18, 2022. The field of dynamic graph algorithms studies algorithms for processing graphs that are changing over time. Formally, the goal is to process an interleaved sequence of update and query operations, where an update operation changes the input graph (e.g. inserts/deletes an edge), while the query operation is problem-specific and asks for some information about the current graph – for example, an s-t path, or a minimum spanning tree. The field has evolved rapidly over the past decade, and this Dagstuhl Seminar brought together leading researchers in dynamic algorithms and related areas of graph algorithms.
Spectroscopic investigation and oxidation of the anticholinergic drug atropine sulfate monohydrate by hexacyanoferrate(III) in aqueous alkaline media: a mechanistic approach

The oxidation of the anticholinergic drug atropine sulfate monohydrate by hexacyanoferrate(III) in aqueous alkaline media was investigated spectrophotometrically by monitoring the decrease in absorbance of hexacyanoferrate(III) (HCF(III)). Oxidation products were identified. The oxidation mechanism was proposed from kinetic studies. The reaction constants involved in the different steps of the mechanism were calculated. The effects of added products, ionic strength, and dielectric constant of the reaction were investigated. The polymerization test revealed that oxidation occurred with intervention of free radicals. The activation parameters were evaluated.
Low-Power Floating-Point Adaptive-CORDIC-Based FFT Twiddle Factor on 65-nm Silicon-on-Thin-BOX (SOTB) With Back-Gate Bias

In this brief, a silicon-on-thin-BOX (SOTB) implementation of single-precision floating-point fast-Fourier-transform (FFT) twiddle factor (TF) is presented. The architecture of the proposed TF is developed based on the adaptive method of the coordinate rotation digital computer (CORDIC) algorithm. The 65-nm SOTB technology was chosen because of its ultra-low-power advantage. Furthermore, the back-gate bias technique can be applied on an SOTB chip to adjust the operation for high-performance or low-power requirement. The layout of the SOTB 65-nm TF core is about 22869 gate-count on the die area of 86721 $ \mu \text {m}^{2}$ . The measurement results show that the core reached its highest operating frequency of 55 MHz at the 1.2-V supply voltage (VDD) with the forward back-gate bias (FBB) ≥ 1.5 V. The power and energy consumptions at this point were 1.54 mW and 27.91 pJ/cycle, respectively. The lowest operating VDD was at 0.5 V with the FBB ≥ 0.5 V. In the standby mode, when the clock-gating technique was deployed, the leakage current can be reduced to 0.4 nA at the 0.4 V VDD and −2.5-V reverse back-gate bias (RBB).
Environmentally Sustainable Solvent-based Process Chemistry for Metals in Printed Circuit Boards

This chapter describes the development of several new processes relating to the fabrication, characterisation and recycling of printed circuit board (PCB) metal assemblies in alternative, sustainable solvent technologies based on an emergent class of liquids know as deep eutectic solvents (DES). It has been demonstrated that in many cases, the use of DES technologies can be disruptive to current process thinking and in principle can deliver benefits including increased efficiency,lower costs and better process control. These technologies offer the opportunity to incorporate new ideas into PCB fabrication and assembly that facilitate downstream, end-of-life recovery and separation consistent with a circular economy model. Current PCB manufacturing is carried out using many complex metal deposition processes involving aqueous solutions of toxic metal salts, strong inorganic acids, precious and expensive noble metals, and requires careful process control and monitoring. As a result, these processes are often costly to operate and inefficient. DES-based technologies can: (1) improve the economic and efficient use of essential metals; (2) reduce or eliminate use of precious and expensive metals; (3) reduce the use of complex and difficult to maintain process chemistry; (4) reduce reliance on toxic and noxious materials; and (5) improve recovery, recycling and reuse of PCB metals.
Usability Metrics for Gamified E-learning Course: A Multilevel Approach

This paper discusses the effect of a gamified learning system for students of the master course on Web Design and Programming performed at the Faculty of Organization and Informatics. A new set of usability metrics was derived from web-based learning usability, user experience and instructional design literature and incorporated into the questionnaire which consists of three main categories: Usability, Educational Usability and User Experience. The main contribution of this paper is the development and validation of a questionnaire for measuring the usability of a gamified e-learning course from students’ perspective. Usability practitioners can use the developed metrics with confidence when evaluating the design of a gamified e-learning course in order to improve students’ engagement and motivation.
Analysis of some techniques of biometric authentication systems with emphasis on 2D and 3D face recognition technology

The paper describes some authentication techniques based on face recognition with emphasis on 2D and 3D facial recognition technologies. The paper presents analyzes that show that the success of a biometric system requires the measurement of its performances through several different types of parameters. Presented are the features and comparative analysis of the two120 | Zoran Lončarević , Muzafer Saračević, Muhedin Hadžić dimensional method of face recognition in relation to three-dimensional ones, based on numerous researches published in professional and scientific papers. The paper emphasize that it is necessary to analyze, in addition to the system performance, the errors that occur in biometric systems during the process of registration, verification and identification. An OpenCV library has been analyzed with it’s over 500 functions that cover several areas of Computer Vision and the area of automatic format recognition.
Hyper-spectral Recovery of Cerebral and Extra-Cerebral Tissue Properties Using Continuous Wave Near-Infrared Spectroscopic Data

Near-infrared spectroscopy (NIRS) is widely used as a non-invasive method to monitor the hemodynamics of biological tissue. A common approach of NIRS relies on continuous wave (CW) methodology, i.e. utilizing intensity-only measurements, and, in general, assumes homogeneity in the optical properties of the biological tissue. However, in monitoring cerebral hemodynamics within humans, this assumption is not valid due to complex layered structure of the head. The NIRS signal that contains information about cerebral blood hemoglobin levels is also contaminated with extra-cerebral tissue hemodynamics, and any recovery method based on such a priori homogenous approximation would lead to erroneous results. In this work, utilization of hyper-spectral intensity only measurements (i.e., CW) at multiple distances are presented and are shown to recover two-layered tissue properties along with the thickness of top layer, using an analytical solution for a two-layered semi-infinite geometry. It is demonstrated that the recovery of tissue oxygenation index (TOI) of both layers can be achieved with an error of 4.4%, with the recovered tissue thickness of 4% error. When the data is measured on a complex tissue such as the human head, it is shown that the semi-infinite recovery model can lead to uncertain results, whereas, when using an appropriate model accounting for the tissue-boundary structure, the tissue oxygenation levels are recovered with an error of 4.2%, and the extra-cerebral tissue thickness with an error of 11.8%. The algorithm is finally used together with human subject data, demonstrating robustness in application and repeatability in the recovered parameters that adhere well to expected published parameters.
An Overview of Climate Change and Building Energy: Performance, Responses and Uncertainties

It is becoming increasingly crucial to develop methods and strategies to assess building performance under the changing climate and to yield a more sustainable and resilient design. However, the outputs of climate models have a coarse spatial and temporal resolution and cannot be used directly in building energy simulation tools. This paper reviews methods to develop fine spatial and temporal weather files that incorporate climate emissions scenarios by means of downscaling. An overview of the climate change impact on building energy performance is given, and potential adaptation and mitigation factors in response to the changing climate in the building sector are presented. Also, methods to reflect, propagate, and partition main sources of uncertainties in both weather files and buildings are summarized, and a sample approach to propagate the uncertainties is demonstrated.
A Damage Model for Concrete under Fatigue Loading

For concrete, fatigue is an essential mechanical behavior. Concrete structures subjected to fatigue loads usually experience a progressive degradation/damage process and even an abrupt failure. However, in the literature, certain essential damage behaviors are not well considered in the study of the mechanism for fatigue behaviors such as the development of irreversible/residual strains. In this work, a damage model with the concept of mode-II microcracks on the crack face and nearby areas contributing to the development of irreversible strains was proposed. By using the micromechanics method, a micro-cell-based damage model under multi-axial loading was introduced to understand the damage behaviors for concrete. By a thermodynamic interpretation of the damage behaviors, a novel fatigue damage variable (irreversible deformation fatigue damage variable) was defined. This variable is able to describe irreversible strains generated by both mode-II microcracks and irreversible frictional sliding. The proposed model considered both elastic and irreversible deformation fatigue damages. It is found that the prediction by the proposed model of cyclic creep, stiffness degradation and post-fatigue stress-strain relationship of concrete agrees well with experimental results.
Research on Risk Management of Aviation Complex Equipment Collaborative Development Project

Firstly, this paper expounds the background of the risk management problem of aviation complex equipment collaborative development project, and points out the significance of studying this problem. Secondly, this paper analyzes the risk occurrence mechanism of aviation complex equipment collaborative development project, and introduces the milestone events and the relationship between events. In addition, based on the system optimal control theory and the risk transfer function, with the goal of minimizing risk loss and risk control cost, this paper constructs a risk optimization model for the aviation complex equipment collaborative development system, and solves the degree of risk optimization of the milestone events. Finally, the model is validated by an example, which proves the validity of the model and provides reference for the collaborative development of aviation complex equipment in the future. Keywords—aviation complex equipment; risk management; milestone events
Evaluation of Root Water Uptake and Urea Fertigation Distribution under Subsurface Drip Irrigation

Shallow groundwater contamination by nitrate is frequent in agricultural lands in Egypt because of the use of urea fertilizers. The urea transformation process in the vadose zone was simulated using a HYDRUS-2D model, Software package for simulations of 2D movement of water, heat, and multiple solutes in variably saturated media, for subsurface drip irrigation. The root water and nutrient uptake were assessed for three soil types (sandy loam, loam, and silty loam) with three emitter discharge levels (1.0 L h−1, 1.50 L h−1, and 2.0 L h−1), for a comparison of three fertigation strategies (A) at the beginning, (B) at the end, and (C) at the middle of the irrigation cycle. The extension of the wetted area mainly depends on soil hydraulic conductivity. The high emitter discharge with a short irrigation time is suitable for shallow-rooted crops. The cumulative flux was highest for silty loam soil and the lowest was for the sandy loam soil (1891, and 1824 cm3) for the 2 L h−1 emitter discharge within the 35 days simulation. The cumulative drainage significantly differs among soil types with little effect of emitter discharge. It recorded 1213, 295, 11.9 cm3 for sandy loam, loam, silty loam, respectively. Urea transformation is controlled by hydrolysis and nitrification as well as the adsorption coefficient of ammonium. Nitrate distribution is mainly governed by soil type rather than the emitter discharge where the sandy loam soil is more highly susceptible to nitrate leaching than to silty loam. Nitrate concentration has recorded the minimum possible level when applying the urea fertilizer at the beginning of the irrigation event for sandy loam and loam soil while for the silty loam soil, urea application at the middle of the irrigation event is more effective. Urea application at the end of the irrigation event gives the highest accumulated leached nitrate concentration below the root zone and should be avoided (the worst strategy).
Introduction to Special Collection on Arctic Ocean Modeling and Observational Synthesis (FAMOS) 2: Beaufort Gyre Phenomenon

One of the foci of the Forum for Artic Modeling and Observational Synthesis (FAMOS) project is improving Arctic regional ice‐ocean models and understanding of physical processes regulating variability of Arctic environmental conditions based on synthesis of observations and model results. The Beaufort Gyre, centered in the Canada Basin of the Arctic Ocean, is an ideal phenomenon and natural laboratory for application of FAMOS modeling capabilities to resolve numerous scientific questions related to the origin and variability of this climatologic freshwater reservoir and flywheel of the Arctic Ocean. The unprecedented volume of data collected in this region is nearly optimal to describe the state and changes in the Beaufort Gyre environmental system at synoptic, seasonal, and interannual time scales. The in situ and remote sensing data characterizing ocean hydrography, sea surface heights, ice drift, concentration and thickness, ocean circulation, and biogeochemistry have been used for model calibration and validation or assimilated for historic reconstructions and establishing initial conditions for numerical predictions. This special collection of studies contributes time series of the Beaufort Gyre data; new methodologies in observing, modeling, and analysis; interpretation of measurements and model output; and discussions and findings that shed light on the mechanisms regulating Beaufort Gyre dynamics as it transitions to a new state under different climate forcing.
17 Functional forms of competence : Interviewing

Employment interviews are ubiquitous in the workplace, providing a necessary step in the hiring process and influencing organizational composition and applicant employment. Research pertaining to professional interviewing is frequently conducted outside of the communication discipline, yet the nature of the interview interaction is highly communicative. The purpose of this chapter is to develop a solid foundation for understanding communication in employment interviews by utilizing the concept of communication competence as a theoretical basis. Specifically, we address aspects of communication effectiveness and appropriateness in employment interviews, including how they vary according to the degree of their standardization. For instance, both parties (interviewer and interviewee) have the goal of reducing uncertainty, although the nature of those goals differ (e.g., organizational perspectives regarding potential interviewee performance verses interviewee perceptions of job fit and the likelihood of being offered the job). Directions for future research are presented, including a pressing need for research examining how the two parties adjust communication during the interaction based on perceptions of the other’s communication behaviors.
Developments of an Expert System for On-Farm Irrigation Water Management Under Arid Conditions

Arid ecosystem conditions are characterized by water scarcity offer as well due to limited water resources, low irrigation efficiency. Therefore, more efforts had to be carried out in order to find out suitable solutions for this problem and maximizing irrigation unit net return. Therefore, the aim of this investigation was to build; verify; and validate of a developed computer program under arid conditions of Egypt. A developed computer program, ISM-ES (Irrigation Systems Management-Expert System), had been coded by using visual basic 2013 programming language and access software for building up the required database. The developed rule based ES is running under windows media. Moreover, SCWU (seasonal crop-water use); SCWR (seasonal crop-water requirements); WSP (water saving percentage) and IWP (irrigation water productivity) processed as judgment indices in the verification and validation processes. Results revealed that the developed ISM-ES resulted in improving the crop-water production as function of tomato crop and maximize the water unit productivity compared with other ES (IMOC-ES) and conventional treatment based on FAO concepts by using program (CropWat 8.1). Results indicate that SCWR had been decreased under investigated ISM-ES compared with the conventional method approved by FAO at all times of investigations. Meanwhile, there is no significant difference between IMOC-ES and conventional method approved by FAO. On the other hand, by applying the (ISM-ES) to determine the SCWR found that a significant difference. Moreover, data analysis indicated that the developed ISM-ES and IMOC-ES had saved the irrigation water with about 20.49 and 4.88 % compared with conventional method approved by FAO, respectively.
Adaptive Fading Filter Based on IMM Filter Structure and Its Application to UAV Navigation

Adaptive Fading Filter Based on IMM Filter Structure and Its Application to UAV Navigation Jun Kyu Lim Department of Mechanical & Aerospace Engineering The Graduate School Seoul National University The filter should consider the model and measurement uncertainty for estimating one system. The uncertainty of the model can be compensated by the IMM (Interacting Multiple Model) filter. The uncertainty of the measurement can be compensated by the adaptive filter. Especially, the AF (Adaptive Fading) filter with forgetting factor for compensating filter gain is very adequate filter. However, these two filters, which are the IMM and AF filter, can hardly consider two uncertainties at the same time. Thus, the main goal of this dissertation is to design an adaptive fading filter based on IMM filter structure. The proposed filter combines the advantages of the AF filter and IMM filter. In order to improve AF filter performance, 2-norm method is used for calculating forgetting factor and IMM filter structure is applied.
Examining the effect of interstitial space on Eastern oysters (Crassostrea virginica): applications of photogrammetry and three-dimensional modeling

Many oyster restoration efforts are focused around the addition of substrate to marine ecosystems. These substrates provide larval oysters with a firm surface to recruit and settle to. While natural oyster shell is undoubtedly the most effective substrate for larval oyster recruitment, the loss of natural shell is imminent due to continued overharvest of mature oyster populations. The loss of natural shell has led to the development of artificial substrates, such as concrete pyramids, castles, or domes. In contrast, natural oyster reefs exhibit a high number of interstitial spaces. We hypothesized that oyster recruitment and survival correlate with interstitial space. To examine the effect of interstitial space on oyster recruitment and survival, we conducted a field experiment from May 2018 January 2019 in the Lynnhaven River located in the Chesapeake Bay using an artificial substrate designed with three treatments of interstitial space. We found oyster survival to be up to 57% greater on the intermediate interstitial space treatment, relative to treatments with high or low interstitial space. Incorporating intermediate interstitial space into artificial substrates used for oyster restoration may increase population growth. Intermediate interstitial space provides juvenile oyster spat with adequate room for growth and refuge from predation. Restoring native oyster populations to even a fraction of their historic populations may have significant positive impacts on marine ecosystems and marine food web dynamics, as well as the oyster fishing industry and coastal economies.