Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-Stage Stochastic Optimization of Sodium-Sulfur Energy Storage Technology in Hybrid Renewable Power Systems

Energy storage systems (ESS) are considered among the key elements for mitigating the impact of renewable intermittency and improving the economics for establishing a sustainable power grid. The high cost combined with the need for optimal capacity and allocation of ESS proves to be pertinent to maintain the power quality as well as the economic and operational viability of a renewable integrated power grid. In case of ESS sizing in terms of optimized power (kW) and energy (kWh) capacity, an oversized ESS results in high capital investment and in some cases increases the system losses. Conversely, an undersized ESS significantly impacts the reliability and availability of the power network. In this paper, a two-stage stochastic optimization strategy is presented for sodium-sulfur (NaS) battery considering the output power uncertainties of wind and solar energy sources. The objective aims at minimizing the total cost of NaS-ESS incorporation while maintaining acceptable system operation using AC optimal power flow. Many scenarios from the historical data are considered for the development of the system stochasticity on a 24-bus reliability test system (RTS) that is incorporated with a hybrid renewable energy system (HRES), namely solar and wind. Moreover, to demonstrate the efficacy of the proposed stochastic optimization framework a comparative analysis is performed with a deterministic optimization technique based on several reliability indices.
Geospatial Based Approach for Enhancing Environment Sustainability of Srinagar city - A Study on Solid Waste Disposal

In today’s world solid waste management is a major global urban environmental issue which leads to health and environmental risk by intensifying air pollution, ground water contamination, providing breeding ground for flies, rodents, and stray dogs. The improper solid waste disposal in urban center like Srinagar city has resulted in environmental deterioration and negative aesthetic value of this tourist destination. There is an increase in commercial, residential and infrastructure development due to the population growth and huge tourist flow which resulted in generation of huge amount of solid waste. This study was carried out with the aim to analyze the present solid waste management system of the city by delineating a suitable site for the disposal of urban solid waste using geospatial technology. Multicriteria analysis method has been employed, i.e. ground water, slope, Land use, and other sensitive areas etc. in determination of an appropriate dumping site for solid waste disposal. The study has successfully identified two potential sites in north and south of the city, which would lessen the burden on the existing waste disposal site and enhance the waste management process in the city. The results showed that geospatial technology can serve as an efficient way of employing and managing various data that can be utilized in locating more appropriate places for the disposal of solid waste.
Very Large Calculation Systems A Specialized Solution for the Complex Needs of Advanced Knowledge Workers

Motivation. Advanced calculations on large data sets provide important business insights. Such calculations must be flexible enough for the dynamic nature of advanced analytics done by actuaries and other high-skill users, yet must also leverage the power and stability of large-scale IT systems. The system design detailed in this paper balances these concerns, delivering the optimal combination of both. Method. The design is based on a pattern the author observed repeatedly during a decade of building systems for actuaries and researchers: data is provided using traditional data warehousing, the calculations are implemented by IT in a manner that solidifies stable elements yet externalizes change-prone elements, system operation is exposed through self-service interfaces that allow users to configure and run the calculations against large data volumes, and the output is delivered by standard business intelligence tools and customized approaches. Results. Systems with this design: optimize the users’ time by moving the majority of the lower-value work to IT, have solid auditability and legal compliance, and provide high computing power and storage capacity, but do require users to give up some amount of control and flexibility. Conclusions. Organizations should use this design to give their most advanced knowledge workers high power, localized control, and optimal efficiency.
Contemporary Neuroprotection Strategies during Cardiac Surgery: State of the Art Review

Open-heart surgery is the leading cause of neuronal injury in the perioperative state, with some patients complicating with cerebrovascular accidents and delirium. Neurological fallout places an immense burden on the psychological well-being of the person affected, their family, and the healthcare system. Several randomised control trials (RCTs) have attempted to identify therapeutic and interventional strategies that reduce the morbidity and mortality rate in patients that experience perioperative neurological complications. However, there is still no consensus on the best strategy that yields improved patient outcomes, such that standardised neuroprotection protocols do not exist in a significant number of anaesthesia departments. This review aims to discuss contemporary evidence for preventing and managing risk factors for neuronal injury, mechanisms of injury, and neuroprotection interventions that lead to improved patient outcomes. Furthermore, a summary of existing RCTs and large observational studies are examined to determine which strategies are supported by science and which lack definitive evidence. We have established that the overall evidence for pharmacological neuroprotection is weak. Most neuroprotective strategies are based on animal studies, which cannot be fully extrapolated to the human population, and there is still no consensus on the optimal neuroprotective strategies for patients undergoing cardiac surgery. Large multicenter studies using universal standardised neurological fallout definitions are still required to evaluate the beneficial effects of the existing neuroprotective techniques.
Research of A-SMGCS System for Complex Airport

According the present complicated and lacks of high-leveled automation ground operation supporting system, based on the concept of ICAO'S A-SMGCS (advanced surface movement guidance and control systems) and the existed facilities of the airport, this paper focuses on the research of a new ground operation supporting system in accordance with A-SMGCS, including the basis system hardware, the surveillance ground monitoring subsystem and the lighting subsystem, etc. The system is capable of not only detecting and predicting the traffic conflicts on the ground but also providing solutions and suggestions. Meanwhile the system can help controllers to arrange and use the airport resources so as to reduce the ground holding time and delay time.
Real-Time Traffic Measurement from Single Loop Inductive Signatures

Accurate traffic data acquisition is essential for effective traffic surveillance, which is the backbone of advanced transportation management and information systems (ATMIS). Inductive loop detectors (ILDs) are still widely used for traffic data collection in the United States and many other countries. Three fundamental traffic parameters—speed, volume, and occupancy—are obtainable via single or double (speed-trap) ILDs. Real-time knowledge of such traffic parameters typically is required for use in ATMIS from a single loop detector station, which is the most commonly used. However, vehicle speeds cannot be obtained directly. Hence, the ability to estimate vehicle speeds accurately from single loop detectors is of considerable interest. In addition, operating agencies report that conventional loop detectors are unable to achieve volume count accuracies of more than 90% to 95%. The improved derivation of fundamental real-time traffic parameters, such as speed, volume, occupancy, and vehicle class, from single loop detectors and inductive signatures is demonstrated.
Some Electromagnetic Transmission and Reflection Properties of a Strip Grating

Summary-Some theoretical and experimental results for the reflection and transmission of a dorm plane electromagnetic wave, normally incident on an ideal strip grating, are presented. The theory is based on the variational method, and the measurements were made at normal incidence in a parallel plate region operating in the f3- to 10-cms wavelength range. A few results for oblique incidence are also included; the experiments in this case were carried out at 1.24-cm wavelength in a parallel plate spectrometer. Resasonable agreement between theory and experiment was obtained throughout.
Maneuvering target tracking based on multiple model methods

Trajectory prediction is essential for the maneuvering target tracking. Nowadays, one of the major challenges for precise prediction of position and velocity of one maneuvering target is the mismatching of target motion model and the movement mode the target performs. In order to solve this problem, the interacting multiple model method is proposed, which is able to adopt the current model to match the target motion mode so that the precision of prediction can be improved. One of the major problems of the interacting mult iple model methods is the selection of models for the algorithm. In this paper, such three models as constant velocity model, exponential increasing accelerat ion model, and the generalized coordinated turn model is selected. Afterwards, one simulat ion to verify the validation of the algorithm is performed, and it indicates that the interacting mult iple model methods with the specific models utilized in this paper does have the ability to track maneuvering target quite precisely.
Nonlinear modeling and validation of solenoid-controlled pilot-operated servovalves

Solenoid-controlled pilot-operated servovalves are flow control devices widely used to drive high-flow hydraulic actuators in heavy-duty off-highway machinery. In these applications, a spool-operated pilot stage is required to account for large flow force in the main hydraulic valve. Design optimization, performance improvement, and fault diagnosis of such complex two-stage servovalves often require sophisticated analytical models with accurate physical parameters. The paper presents a step-by-step methodology for nonlinear modeling, parameter determination, model validation, and performance evaluation of solenoid-controlled pilot-operated spool valves. The proposed model takes into account such nonlinearities as pilot spool dead band, spool friction, flow coefficient variability, and leakage. This new model is complete in the sense that all nonlinear interactions between various electromechanical elements have been incorporated in a compact yet comprehensive model. The simulation model accepts a command voltage to the solenoids as input and gives the second stage spool displacement as output. To obtain the physical parameters used in the valve model, a systematic approach is proposed based on state measurement and curve-fitting techniques. The identified parameters of an example valve were used in simulations both to validate the nonlinear valve model and also to assess the valve's performance when certain valve parameters change.
Let’s Get Smart and Set Goals to ASPIRE

Abstract Goal setting has been a long-supported performance enhancement and behavior change strategy. However, a goal’s efficacy is largely dependent on its structure (specific, measurable, moderately difficult, performance focused, and proximal) and related support systems (assessing individual and environmental factors and evaluating and supporting goal progress). While goal structures are often employed, support systems have not always been effectively implemented. Our purpose is to assist practitioners in attending to both goal structure and support systems by using the ASPIRE goal framework. By using this framework, individuals may be more likely to avoid issues that detract from goal setting effectiveness.
Physical therapy using robotics: A project-based learning experience for undergraduate students

The dynamic society we live in requires constant adaptation and innovation on every aspect of our daily lives, allowing us to improve the necessities of different people by doing it. For this study, we used a new approach with project-based learning to go beyond the typical environment in higher education and bring solutions to real-life scenarios. The project was developed with undergraduate engineering students in collaboration with a rehabilitation institute in Mexico City to design a physical therapy routine using the NAO robot. It allowed interaction between young patients in real time and fostered empathy while developing a final usable product. The study measured the usability of the robotic platform during the rehabilitation sessions and the reproducibility of the project through Cronbach's alpha evaluation. The usability results show a higher interest in the project from both the patients and the medical staff involved while constructing the material needed to develop a product that matches the standards given by the rehabilitation institute. Implications for practice or policy: Therapists could change traditional approaches to caregiving while adopting new technological methodologies using robots. Higher education students could supplement their school curricula with real-case scenarios such as creating innovative therapy sessions for people with physical disabilities. Schools might need to collaborate with a wide range of institutions to provide technological solutions to real problems.
Cyanide removal from aqueous environment by resting cells and PTFE immobilized cells of Sphingobacterium spp.

Microbial detoxification of cyanide offered an inexpensive, safe, and viable alternative to physiochemical processes for the treatment of cyanide in industrial effluents or contaminated sites. This study involved isolation of novel strain with high resistance against cyanide toxicity and able to degrade the cyanide radical. The strain was isolated from rocky area and identified as Sphingobacterium multivorium using 16S ribosomal RNA. Resting pregrown cells were used in simple reaction mixture to avoid the complication associated with the media. One‐gram fresh weight of this bacteria was able to remove 98.5% from 1.5 g/L cyanide which is a unique result. Factor affecting the biochemical process such as pH, temperature, agitation, glucose concentration was examined. The optimum conditions were, pH 6–7, 30–40°C, and 100–150 rpm shaking speed and 0.25% glucose. Furthermore, the cells were used after immobilization in polytetrafluoroethylene (PTFE) polymer. The PTFE is very safe carrier and the cells withstand the entrapment process and were able to remove 92% (1 g/L cyanide). The immobilized cells were used for six successive cycles with about 50% removal efficiency. The storage life extended to 14 days. No previous work studied the cyanide removal by Sphingobacterium spp. The strain showed good applicable characters.
Künstliche Neuronale Netzwerke – ein Modelltyp mit Zukunft in der Bauphysik?

Künstliche Neuronale Netzwerke (Artificial Neural Networks, ANN) sind eine Gruppe von mathematischen Modellen, die erst vor wenigen Jahren in das Bauwesen allgemein und in die Bauphysik im besonderen Eingang gefunden hat. Aufgrund ihrer ausgeprägten Flexibilität werden ANNs auf eine laufend anwachsende Zahl verschiedenster Aufgabenstellungen angewandt. Der vorliegende Beitrag beschreibt zunächst die Funktionsweise und Eigenschaften des im Bauingenieurwesen meistverwendeten ANN‐Typs, des sogenannten Multilayer Perceptrons (MLP), und erörtert darauf aufbauend potentielle Anwendungsgebiete und einige bereits vorliegende Erfahrungen in der Bauphysik. Auf der Grundlage des derzeitigen Entwicklungsstands auf diesem Gebiet können Künstliche Neuronale Netzwerke als ein intelligenter und flexibler Berechnungsansatz vom Typ der ‘Black Box’‐Modelle charakterisiert werden, dessen Anwendungspotential in der Bauphysik sicherlich noch nicht ausgeschöpft ist.
ANALYSIS OF DENIAL OF SERVICE (DOS) ATTACKS IN WIRELESS SENSOR NETWORKS

WSN are made of hundreds of constraints dependent sensors for solving real world sensitive applications. These nodes are scattered over an area to monitor and record the data as desired by the application and to forward same to the center node for further observation, which may generate an alert to control the situation. In recent years, WSN has been grown tremendously in the applications, resulted the demand of a strong, consistent security mechanism. WSN issues, challenges are needed to be addressed for designing such security mechanism. Irrespective of various limited capabilities of nodes, even, on-time collection of information and reliable, secure delivery is expected in WSN. Tiny sensors with small hardware, processing capabilities and limited power resource cannot afford traditional security measures to fight against vulnerabilities. Different layers of WSN nodes have variety of roles to play for proper their proper functioning at different layers like signaling, framing, forwarding, reliable transportation and user interaction at both receiving as well as sending end. Many denial of service attacks are identified at each layer which are meant for purposeful, planned attacks to jeopardize the availability of service, restricting the WSN utility for application. In this paper we will focus on the WSN characteristics, constraints and types of DoS attacks at different layer.
An Optimal Power Flow Solution of a System Integrated with Renewable Sources Using a Hybrid Optimizer

A solution to reduce the emission and generation cost of conventional fossil-fuel-based power generators is to integrate renewable energy sources into the electrical power system. This paper outlines an efficient hybrid particle swarm gray wolf optimizer (HPS-GWO)-based optimal power flow solution for a system combining solar photovoltaic (SPV) and wind energy (WE) sources with conventional fuel-based thermal generators (TGs). The output power of SPV and WE sources was forecasted using lognormal and Weibull probability density functions (PDFs), respectively. The two conventional fossil-fuel-based TGs are replaced with WE and SPV sources in the existing IEEE-30 bus system, and total generation cost, emission and power losses are considered the three main objective functions for optimization of the optimal power flow problem in each scenario. A carbon tax is imposed on the emission from fossil-fuel-based TGs, which results in a reduction in the emission from TGs. The results were verified on the modified test system that consists of SPV and WE sources. The simulation results confirm the validity and effectiveness of the suggested model and proposed hybrid optimizer. The results confirm the exploitation and exploration capability of the HPS-GWO algorithm. The results achieved from the modified system demonstrate that the use of SPV and WE sources in combination with fossil-fuel-based TGs reduces the total system generation cost and greenhouse emissions of the entire power system.
Quantitative Assessment of Chirality of Protein Secondary Structures and Phenylalanine Peptide Nanotubes

In this study we consider the features of spatial-structure formation in proteins and their application in bioengineering. Methods for the quantitative assessment of the chirality of regular helical and irregular structures of proteins are presented. The features of self-assembly of phenylalanine (F) into peptide nanotubes (PNT), which form helices of different chirality, are also analyzed. A method is proposed for calculating the magnitude and sign of the chirality of helix-like peptide nanotubes using a sequence of vectors for the dipole moments of individual peptides.
Forensic Facial Comparison: Current Status, Limitations, and Future Directions

Simple Summary Facial identification is an emerging field in forensic anthropology, largely due to the rise in closed circuit television presence worldwide, yet there is little published research in it. Our research group has conducted a series of studies testing the validity and reliability of the facial identification practice of morphological analysis. In this paper, we summarize the results of our studies and other latest advances in facial identification practice. In addition, we present a review of relevant technical literature on the limiting factors imposed on facial identification by closed circuit television, while making recommendations for practice and the future of this research niche based on a combination of our results and the technical know-how available. Facial identification research is a multidisciplinary task, with involvement from the field of anatomy, forensic anthropology, photography, image science, and psychology, among others. The value of this brief review is the bridging of these multiple disciplines to discuss the relevant needs and requirements of facial identification in forensic practice and future research. Abstract Global escalation of crime has necessitated the use of digital imagery to aid the identification of perpetrators. Forensic facial comparison (FFC) is increasingly employed, often relying on poor-quality images. In the absence of standardized criteria, especially in terms of video recordings, verification of the methodology is needed. This paper addresses aspects of FFC, discussing relevant terminology, investigating the validity and reliability of the FISWG morphological feature list using a new South African database, and advising on standards for CCTV equipment. Suboptimal conditions, including poor resolution, unfavorable angle of incidence, color, and lighting, affected the accuracy of FFC. Morphological analysis of photographs, standard CCTV, and eye-level CCTV showed improved performance in a strict iteration analysis, but not when using analogue CCTV images. Therefore, both strict and lenient iterations should be conducted, but FFC must be abandoned when a strict iteration performs worse than a lenient one. This threshold ought to be applied to the specific CCTV equipment to determine its utility. Chance-corrected accuracy was the most representative measure of accuracy, as opposed to the commonly used hit rate. While the use of automated systems is increasing, trained human observer-based morphological analysis, using the FISWG feature list and an Analysis, Comparison, Evaluation, and Verification (ACE-V) approach, should be the primary method of facial comparison.