Miracle-dz/UniFAR-FTUs huggingface dataset:
LOAD BALANCING OPTIMIZATION FOR RPL BASED EMERGENCY RESPONSE USING Q-LEARNING

Internet of Things technology has given rise to Smart Cities, Smart Health, Smart Transport Logistics, Smart Production and Supply chain management, Smart Home and many more. For IoT deployments, ROLL-WG has standardized Routing Protocol for Low Power and Lossy Networks (RPL) for urban environment (RFC 5548). RPL is designed to address the needs of constrained IoT environment. RPL uses Objective Functions (ETX & Hop Count) to optimize route selection. Many new Objective Functions for IoT applications are suggested by researchers to optimize path selection. Load Balancing Optimization for emergency response is least explored. In this article, we propose load balancing optimization for RPL based emergency response using Q-learning (LBO-QL). We have tested the proposed model in Contiki OS and Cooja simulator. Proposed model provides improved efficiency in Packet Delivery Ratio, Traffic Control Overhead and Power consumption. Hence, DODAG optimization using Q-Learning for disaster response is effective in optimized usage of constrained resources for disaster response operations with improved efficiency and reliability. Article DOI: https://dx.doi. org/10.20319/mijst.2018. 42.7492 This work is licensed under the Creative Commons Attribution-Non-commercial 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.
Static and dynamic mechanical properties of impregnated carbon nanotube fiber

Carbon nanotube fiber (CNT fiber) with excellent electrical and mechanical properties, as well as stable thermal and chemical properties has great potential application in areas such as ultra-fine wires, ultra-light cables, sensors, composite materials, energy conversion and electro-actuation. In this paper, the static and dynamic mechanical properties of impregnated CNT fiber were studied through single and cyclic tensile experiments and continuous dynamic analysis (CDA). The dynamic properties of impregnated CNT fiber such as storage and loss modulus was obtained. In addition, the storage modulus and loss modulus of impregnated CNT fiber increases with the increase of loading frequency. The research work in this paper has an important reference value for the engineering applications of impregnated CNT fiber in the fields of sensors and composites.
Wafer Map Defect Pattern Recognition Using Rotation-Invariant Features

In semiconductor manufacturing, the patterns on the wafer map provide important information for engineers to identify the root causes of production problems. The detection and recognition of wafer map patterns is thus an important issue in semiconductor industry. Automatic techniques are required to cut down on cost and to improve accuracy. In this study, we propose an approach to recognize patterns in the wafer maps which uses the extracted features based on the proposed weight masks. The proposed masks contain three types, namely, polar masks, line masks and arc masks. Polar masks aim to extract features of concentric patterns, while line and arc masks are designed to mainly deal with eccentric patterns like scratches. These masks can be applied to extract rotation-invariant features for the classification of the defect patterns. To demonstrate the effectiveness of our model, we apply the method to a real-world wafer map dataset. Comparisons with alternative methods show superiority of our method in the task of wafer map defect pattern recognition.
Exploiting Functionally Graded Elastomeric Materials to Program Collapse and Mechanical Properties

The development of materials with periodic microstructures provides the means to tune mechanical properties via prescribed collapse mechanisms. As investigations give attention to tunable unit cell designs, questions arise regarding strategic ways to exploit built‐up materials to empower large, programmable control over properties and material functionality. The potential to rationally design functionally graded elastomeric materials to yield prescribed mechanical properties is demonstrated herein. Following computational and experimental studies of simplified unit cells and layers, the results inspire ways to exploit linear elastic network analogies to design built‐up and functionally graded materials. This approach exemplifies a streamlined means to create pre‐programmed properties on the basis of simple calculations related to measurements from fundamental material constituents. The results build a foundation for innovative approaches to newly leverage elastomeric materials with programmable collapse for myriad engineering applications.
Low-cost optimization under uncertainty through box representation of robustness measures

This work is devoted to tackle multi-objective optimization under uncertainty problems using the SABBa framework (Surrogate-Assisted Bounding-Box approach). It aims at efficiently dealing with robust optimization problems with approximated robustness measures. The basic ingredient of this framework is the Bounding-Box (BB) approach, which has been formulated in [2] and [1]. A Bounding-Box (or conservative box) is defined as a multi-dimensional product of intervals centered on approximated objectives and containing the associated true values. In SABBa, it is supplemented with a surrogate-assisting strategy, which is very effective in order to reduce the overall computational cost associated to the BB approach, notably at the end of the optimization. In [3], we have provide a mathematical proof of the robustness of the framework and of its convergence under some assumptions. It has been shown that the Bounding-Box approach yields a strong coupling between the costly convergence of the uncertainty quantification (UQ) process and the quality of the associated design. Intuitively, UQ refinement is only performed on promising designs, while non-efficient ones are frozen as soon as they are dominated. This allow a quick convergence of the optimization algorithm toward the most promising area. The surrogate-assisting strategy is then automatically refined in this area, leading to a very quick convergence of the uncertainty-based optimization process. This paper is focused on the extension of SABBa to reliability-based constrained optimization problems. This implies a redefinition of the Boxed Pareto dominance introduced in [3], which will be discussed in details. The behavior of the algorithm will be explored both in separated and coupled spaces by comparing against some recent method [4] permitting to naturally correlate quantities of interest in the design dimensions. In order to compare strategies from a quantitative point of view, the convergence of the algorithm will be measured by means of Hausdorff distance to the Pareto optimal set. This distance is extended to aleatory Pareto optimal designs by considering boxes as uniform distributions on the robustness measures. The indicator of interest is then the expected modified Hausdorff distance. Several comparisons on analytical and applicative test cases will be provided against the classical nested-loop strategy both on true function evaluations and on metamodels built a priori.
A Computational Study of Bubble Suspensions and Foamed Cement using Extended Stokesian Dynamics

Foamed cement is created by injecting gas into a cement slurry to create a dispersion of bubbles in the cement. The cement is foamed to reduce the density of the cement slurry when a lightweight cement is needed. The gas bubbles influence the rheological properties of the cement base slurry. The goal of this work was to determine the influence of the bubble size and spatial arrangement on the potential for bubble clustering or structuring in a foamed cement slurry, as this could lead to connected bubbles once the foamed cement fully hydrates, or which could result in crack formation along a line of bubbles. Either condition would affect the cement’s ability to properly isolate the well. A bubble interaction to simulate bubbles in a Newtonian fluid was developed in this research. The bubble interaction accounts for the nature of the bubbles by allowing for slip on the bubble surface, the deflection on the bubble surface, a bubble-bubble pairwise interaction that represents the surfactant properties, and was developed for polydisperse bubble sizes. The size distributions of bubbles determined from a real foamed cement sample were used as simulation inputs. It was possible to simulate a realistic bubble size distribution using the bubble interaction. Thismethod can be used to simulate relevant volume fractions of bubbles that represent real foams. The LAMMPS simulation code is available publicly at lammps.sandia. gov. Our implementation within the LAMMPS framework of the interactions described in this paper are publicly available atgithub.com/eilisjill/Pair_style_bubble.
Curious Cases of Automatically Generated Text and Detecting Probabilistic Context Free Grammar Sentences with Grammatical Structure Similarity

Automatically generated papers have been used to manipulate bibliography indexes on numerous occasions. This paper is interested in different means to generate texts such as by a recurrent neural network, a Markov model, or a probabilistic context free grammar and if it is possible to detect them using a current approach. Then, probabilistic context free grammar (PCFG) is focused on as the one most used. However, despite that there have been multiple approaches to detecting such types of paper. Yet, they are all working at the document level and are unable to detect a small amount of generated text inside a larger body of genuinely written text. Thus, we present the Grammatical Structure Similarity (GSS) measurement to detect sentences or short fragments of automatically generated text from known PCFG generators. The proposed approach is tested against a pattern checker and various common machine learning methods. Additionally, the ability to detect a modified generator is also tested.
Computational Investigation of Ion Transport and Selectivity in a Nanoporous Desalination Membrane using Advanced Sampling Techniques

The ability of semipermeable membranes to selectively impede the transport of undesirable solutes is key to many applications, including water desalination and chemical separation. Yet, the relationship between a membrane's structure and its selectivity for different types of solutes is far from fully understood. While experiments lack the spatiotemporal resolution necessary for probing the molecular pathways of solute transport, conventional computational techniques cannot access timescales relevant to solute transport through semipermeable membranes or are incapable of providing kinetic information altogether. By utilizing jumpy forward-flux sampling (jFFS) [Haji-Akbari, J. Chem. Phys., 149, 072303 (2018)], an advanced sampling technique recently developed by us, we are able to circumvent these limitations, and to accurately estimate arbitrarily large mean passage times-- and arbitrarily small solute passage ratios. We use this method to investigate the transport of sodium and chloride ions through a graphitic membrane with sub-nm pores, and compute solute passage ratios as small as one ion per 10,000 solvent molecules, corresponding to a salt rejection of 99.99\%. By analyzing the transition path ensemble, we identify two major impediments to ion transport through the pore. In addition to its partial dehydration which is energetically and entropically disfavored, its traversal through the pore generates a net electrostatic potential that pulls back the leading ion through a net restraining force. While the role of partial dehydration in ion transport is widely accepted, it is the first time that the crucial role of such electrostatic pull-back is revealed at a molecular level.
Assessment of Lorentzian Model of nano-optical antennas

The present paper covers that inside the previous quite a while a huge advancement with respect to nano-optical radio wires could be seen. It is one motivation behind nano-optical nano-radio wires to thunderously improve light-matter associations at the nanoscale, for example the association of an outside light with particles. In this particular, however in practically all plans that exploit resoundingly improved electromagnetic fields in the region of nano-radio wires, the exact learning of the unearthly position of resonances is of vital significance to completely misuse their valuable impacts. Up to this point, be that as it may, numerous nano-recieving wires were just advanced as for their far-field qualities, for example regarding their dispersing or annihilation cross segments. In spite of the fact that being a rising component in numerous numerical reproductions, it was as of late completely valued that there exists an inconspicuous however significant contrast in the phantom position of resonances in the close and the far-field. With the reason to measure this move, Zuloaga et al. recommended a Lorentzian model to assess the reverberation move. Here, we devise on completely investigative grounds a methodology to foresee the reverberation in the close field legitimately from that in the far-field and uncover that the issue is included and multifaceted, as a rule. We plot the restrictions of our hypothesis if progressively advanced nano-optical nano-radio wires are viewed as where higher request multipolar commitments and higher request recieving wire resonances become progressively significant. The two perspectives are featured by numerically concentrating important nano-recieving wires.
Crystalline structure of the manganites solid solution RE(Me,Mn)O3, (RE=Gd,Er; Me=Ni,Co)

Las propiedades estructurales de las soluciones solidas RE(Me,Mn)O3, RE=Gd,Er, Me=Ni,Co, han sido estudiadas por difraccion de rayos X, (DRX) y medidas electricas. Las fases se sintetizaron por reaccion en estado solido entre los oxidos componentes. La incorporacion de los cationes Ni2+ y Co2+,3+ en la red en lugar de Mn lleva a cambios en los parametros de red y en la simetria de la perovskita, GdMnO3 o del compuesto hexagonal ErMnO3 respectivamente. Las transiciones de fase dependen de la cantidad de Mn3+ sustituido, y por tanto de la debilitacion del efecto co-operativo Jahn-Teller. Las soluciones solidas basadas en GdMnO3 cambian de perovskita tipo O� a perovskita tipo O. Esta transicion ocurre para una menor cantidad de Ni que para Co como sustituyentes. Las soluciones basadas en ErMnO3 muestran un comportamiento algo diferente: la incorporacion induce cambios desde la estructura hexagonal a una estructura tipo perovskita en la forma O, para cantidades de ~20 at% Ni y para ~30 at% Co. La influencia del factor esterico en las transiciones observadas parece jugar un papel secundario frente a la desaparicion progresiva de los cationes Jahn-Teller Mn3+.
The effects of dielectric values, breast and tumor size on the detection of breast tumor

Although breast cancer is the second main cause of female deaths after lung cancer, early diagnosis plays a crucial role to diminish the death rate. Many techniques have been improved to detect the cancerous cells. At different microwave frequencies, the malignant cells indicate different electrical characteristics as compared to the normal cells. According to these frequencies, the breast tissue is more permeable than other tissues such as the brain and muscle. Due to this property of the breast tissue, microwaves can be used for the detection of breast cancer. In this study, the breast prototype was modelled using the CST STUDIO SUITE electromagnetic simulation software with respect to different breast size, tumor size and dielectric values tested at a range of the 0-3.0 GHz frequency. The objective of this paper is to investigate the effects of each factor and the interactions of factors on detecting cancer cells using the factorial analysis. The results indicate that the factors such as fat and skin permittivity, tumor and breast sizes are more effective in the detection of breast tumor. Although the effect of fibro permittivity is not significant alone, there are considerable interaction effects of a large breast size and small tumor size through low-to-high values of fibro permittivity. Furthermore, the combinations of a breast radius smaller than almost 8.5 cm with a high level tumor radius and breast radius larger than 8.5 cm with a low level tumor radius are desirable for lessening the return loss value.
Design of a droplet based microfluidic reactor to synthesize chitosan coated iron oxide nanoparticles

DESIGN OF A DROPLET BASED MICROFLUIDIC REACTOR TO SYNTHESIZE CHITOSAN COATED IRON OXIDE NANOPARTICLES Malik Abdul Wahab M.S. in Mechanical Engineering Advisor: Emine Yegan Erdem June 2019 Nanoparticles possess unique structural, mechanical, thermal, optical and chemical properties which are highly dependent on their size; therefore it is important to be able to synthesize them uniformly. In general they are synthesized using conventional batch-wise techniques; however microfluidic platforms are also used because they provide precise control over reaction conditions like mixing time, temperature, concentration and improved reaction kinetics. This work is the first study where coating of magnetic nanoparticles with chitosan is realized by utilizing a microfluidic platform. These particles have potential application in targeted drug delivery due to their magnetic behavior and the possibility of carrying drug in the chitosan layer. In the past, this synthesis reaction was performed by using batch wise techniques. In this work we demonstrate the synthesis of chitosan coated nanoparticles using a droplet based microfluidic platform. PDMS devices are fabricated using conventional soft lithography technique. Droplets from two different reagents are generated using double T junction with tapered geometry. The taper angle is optimized such that both reagents generate droplets alternatively with efficiency of more than 95%. Viscosity and surface tension of both droplet phase and continuous phase is taken into account to optimize the geometry. As both reagents need to be mixed in equal proportion, flow rates are adjusted to make the spacing and size of droplets identical. Later, two consecutive droplets are merged in a pillar structure by using the fact that increasing the width of channel will slow down the droplets. Dimensions of channels are optimized so that only two consecutive droplets are merging while pillars avoid accumulation of droplets at that location. Olive oil and silicon oil are used as the continuous phase while chitosan solution and iron chloride solution are used as dispersed phases to form alternating droplets. Then ammonia solution is added as dispersed phase and it forms another droplet at a T-junction and this iii
The study on optimization of cement and fine aggregate by blast furnace slag in concrete

Generation of industrial by-products has increased significantly with industrialization. One such by-product from iron smelting industry is iron slag, which is generated from blast-furnaces while extracting iron. This blast furnace slag is used to make a cementitious material by grinding it into fine powder, known as Ground Granulated Blast Furnace Slag (GGBS). This blast furnace slag is also used to make a glassy granular product, Granulated blast furnace Slag (GBFS) which can be used as fine aggregate. Present experimental work investigates feasibility of using GBFS as replacement of natural sand and GGBS as replacement of cement in concrete respectively. Concrete cubes have been prepared and their compressive strength is checked for M30 grade of concrete. Thus, it can be concluded that GGBS and GBFS can be used to partially replace cement up to 55% and sand up to 50% in concrete respectively without affecting their compressive strength. Thereby reducing carbon dioxide emission and curtailing cost of concrete by 20.25%. Generation of industrial by-products has increased significantly with industrialization. One such by-product from iron smelting industry is iron slag, which is generated from blast-furnaces while extracting iron. This blast furnace slag is used to make a cementitious material by grinding it into fine powder, known as Ground Granulated Blast Furnace Slag (GGBS). This blast furnace slag is also used to make a glassy granular product, Granulated blast furnace Slag (GBFS) which can be used as fine aggregate. Present experimental work investigates feasibility of using GBFS as replacement of natural sand and GGBS as replacement of cement in concrete respectively. Concrete cubes have been prepared and their compressive strength is checked for M30 grade of concrete. Thus, it can be concluded that GGBS and GBFS can be used to partially replace cement up to 55% and sand up to 50% in concrete respectively without affecting their compressive strength. Thereby reducing carbon dioxide emission and curtailing cost of co.
High corrosion resistance of metal-graphene oxide-metal multilayer coatings

ABSTRACT Attributes such as chemical inertness and impermeability make graphene and graphene oxide (GO) ideal materials for corrosion protection coatings. This work shows the application of chemically synthesised GO for corrosion protection by sandwiching it within metallic coatings to form a metal-GO-metal multilayer geometry. Two different multilayer systems were investigated: SnZn–GO–SnZn and ZnNi–GO–ZnNi multilayer coatings. Metallic coating was electrodeposited on mild steel. Followed by drop casting of as-synthesised GO over the metal deposit. The final metal layer was then electrodeposited over the drop casted GO. A control experiment was conducted by decreasing the thickness of the top metal in order to bring the GO nearer to the exposed surface. For both the systems, one pristine coating and three different multilayer coatings were electrodeposited. Total time of metal deposition was kept constant for all the coatings. Corrosion resistance of the coatings was investigated in 3 wt% NaCl solution by potentiodynamic polarisation and electrochemical impedance spectroscopy methods. The corrosion measurements clearly showed that the corrosion resistance of all the multilayer coatings was greater than the pristine metallic coating and between the multilayer coatings, as the thickness of the top metal layer decreased thereby causing the GO layer to advance towards the surface facing the corrosive medium the corrosion resistance of the multilayer coating increased. This study clearly illustrates the effect of inertness and impermeable of GO in protecting the underlying substrate against corrosion reaction.
GRAPHENE OXIDE-MODIFIED HYDROXYAPATITE NANOCOMPOSITES IN BIOMEDICAL APPLICATIONS: A REVIEW

Bacterial infection and cytotoxicity associated with implant materials used in medical devices are the major cause of implant failures. This review focusses upon the development of graphene oxide (GO) – hydroxyapatite (HA) nanocomposites as potential coating materials that can provide a solution to the rejection of implants. These nanocomposites combine the unique antibacterial properties of graphene oxide with the natural mineral composition of hydroxyapatite, as found in human bones and tooth enamel. They have potential antibacterial applications in the fields of orthopaedics, orthodontics and cardiovascular medicine. The methods used for preparation of HA and GO in addition to the combining of GO–HA nanocomposite are discussed. Cytotoxicity and antibacterial affects of GO and GO–HA to biological systems are examined as well as future applications in related fields.