Miracle-dz/UniFAR-FTUs huggingface dataset:
Maintenance strategy selection in a cement industry using analytic network process

Purpose The purpose of this paper is to demonstrate the application of analytic network process (ANP) as a methodology to make multiple criteria decision in selecting the most appropriate maintenance strategy for organizations with critical manufacturing requirements. Design/methodology/approach Maintenance strategy selection problems are multiple criteria decision making (MCDM) problems which consist of many qualitative and quantitative characteristics. For solving MCDM problems, the ANP is highly recommended as it considers the interdependent influences among and between the various levels of decision attributes. In this research paper, the ANP method is used to select the optimum maintenance strategy in a cement industry in India. Findings The ANP method can be used as an effective tool for the evaluation of possible alternatives in maintenance strategy decision problems by considering the dependency among the strategic factors. Research limitations/implications As illustrated in this paper, ANP method can also be used in other industries for adopting the optimum maintenance strategy to enhance the business performance by decreasing the losses associated with equipment effectiveness. Practical implications The major contribution of this research is the successful development of the comprehensive ANP model for the cement plant. ANP model incorporates diversified variables of the cement plant supply chain and includes their interdependencies. The proposed ANP model in this paper, not only guides the decision makers in the selection of the best services but also enables them to visualize the impact of various criteria in the arrival of the final solution. Social implications The model can be extended to certain other manufacturing sectors as the future scope of research and may assist in obtaining a clear idea regarding the status of current maintenance strategies. It should be carried out with a larger number of firms in India focusing on small and medium firms to confirm these results and reinforce their applicability to these kinds of firms. Studies of such a nature would help in identifying successful organizational factors or successful maintenance practices that lead to superior performance. Originality/value This paper explores the value of implementing ANP as a decision making method in maintenance strategy, which is currently not a prevalent method.
Deep Convolutional Neural Network for Condition Identification of Connections in Steel Structures

The deep learning technologies have transformed many research areas with accuracy levels that the traditional methods are not comparable with. Recently, they have received increasing attention in the structural health monitoring (SHM) domain. In this paper, we aim to develop a new deep learning algorithm for structural condition monitoring and to evaluate its performance in a challenging case, bolt loosening damage in a frame structure. First, the design of a one-Dimensional Convolutional Neural Network (1DCNN) is introduced. Second, a series of impact hammer tests are conducted on a steel frame in the laboratory under ten scenarios, with bolts loosened at different locations and quantities. For each scenario, ten repeated tests are performed to provide enough training data for the algorithm. Third, the algorithm is trained with different quantities of training data (from one to seven test data for each scenario), and then is tested with the rest test data. The results show that the proposed 1D-CNN with three convolutional layers provide reliable identification results (over 95% accuracy) with sufficient training data sets. It has the potential to transform the SHM practice.
Atopowe zapalenie skóry - diagnostyka różnicowa zmian chorobowych Atopic dermatitis - differential diagnosis of the skin lesions

Streszczenie Atopowe zapalenie skory (AZS) jest przewleklą dermatozą zapalną, charakteryzującą sie wystepowaniem okresow zaostrzen i remisji oraz uporczywego i nawrotowego świądu. Rozpoznanie AZS w praktyce klinicznej stawiane jest w oparciu o powszechnie uznane kryteria diagnostyczne zaproponowane przez Hanifina i Rajke, w ktorych uwzglednia sie obraz kliniczny zmian skornych, dane uzyskane z wywiadu oraz wybrane parametry laboratoryjne. Takie postepowanie moze niekiedy prowadzic do zbyt czestego rozpoznawania choroby, szczegolnie wowczas, gdy obraz kliniczny nie jest pelnoobjawowy. Rodzi sie wiec pytanie, jak czesto mozemy miec do czynienia z nadrozpoznawalnością atopowego zapalenia skory, szczegolnie u malych dzieci ponizej 1. roku zycia. Bledy diagnostyczne, a w konsekwencji wdrozenie nieodpowiedniego postepowania terapeutycznego, najcześciej wynikają z nieprawidlowo przeprowadzonej diagnostyki roznicowej. Stąd celem niniejszego artykulu jest omowienie jednostek chorobowych, ktore imitują zmiany skorne charakterystyczne dla AZS, a ich czestośc wystepowania zalezy od wieku, podobnie jak zmieniający sie obraz kliniczny wyprysku atopowego. W pracy zwrocono rowniez uwage na najcześciej popelniane bledy diagnostyczne, ktore mogą pogarszac rokowanie i obnizac komfort zycia pacjentow. Obserwacje kliniczne wskazują, ze rozpoznanie AZS nie jest proste i wymaga od lekarza duzej znajomości obrazow klinicznych zmian skornych oraz, niekiedy, wykonania kompleksowych badan dodatkowych, ze szczegolnym uwzglednieniem badania histopatologicznego zmian skornych. Slowa kluczowe: atopowe zapalenie skory, diagnostyka roznicowa, nadrozpoznawalnośc, obraz kliniczny, badania dodatkowe Summary Atopic dermatitis (AD) is a chronic inflammatory skin disorder with severe, recurrent pruritus, and is characterized by periods of remission and relapses. In a clinical practice the diagnosis is made using the most common criteria recommended by Hanifin and Rajka which include the picture of skin lesions, medical history and selected laboratory parameters. This procedure may lead to more frequent diagnosis of the disease than really occurs, especially in the cases where not all clinical features are present. This statement raises the question whether AD is not over-diagnosed, especially in children under 1 year of life. Diagnostic mistakes leading to incorrect treatment usually result from insufficient differential diagnosis. The aim of the article is to discuss diseases which may imitate skin lesions typical for atopic eczema occurring in three age-related stages. The article draws our attention to unnecessary diagnostic mistakes, which exacerbate patients’ prognosis and reduce their comfort of life. Clinical experience shows that the diagnosis of AD is problematic. Therefore, physicians are required to have a huge knowledge of dermatological disorders, and to perform additional tests, especially histopathology of the skin.
Effects of soil–structure cluster interactions on ground motions

The effects of soil–structure cluster interaction (SSCI) on ground motion are presented through shaking table tests and parametric numerical simulation using the finite element method. The superstructure is simplified as a concrete column at a 1/20 scale, with a total mass of 60 kg installed on top of the structures. The Davidenkov foundation model is used to simulate soil nonlinearity. The results of the shaking table test are then compared with the results of the numerical simulation. It is found that the spectral amplification and fundamental resonance frequency are reduced because of the SSCI effects. Further, the structure amount, spacing, height, and distribution play a significant role in the SSCI effects on the ground motion. It is also inferred that having more structures, less spacing, and higher structures may result in a reduction in the acceleration response.
3-Sulphinyl-5-Amino-1H-1,2,4-Triazoles as Inhibitors of Copper Corrosion

A set of electrochemical and full-scale corrosion testing methods demonstrates that 3-sulphinylalkyl-5-amino-1H-1,2,4-triazoles can be used as inhibitors of copper corrosion in neutral chloride solutions and under atmospheric corrosion. It was shown that the inhibition effect of 3-sulphinylalkyl derivatives of 5-amino-1H-1,2,4-triazole increases with the growth of the chain of the additive. By means of the impedance spectroscopy method, the authors determined that the polarisation resistance and the Warburg impedance increases whereas the double-layer capacitance decreased with the growth of the inhibitor chain and the concentration of the inhibitor. In addition, the period when the first signs of corrosion attack appear on the copper plates in the salt spray chamber increased with the growth of the inhibitor chain and its concentrations. The lowest value of this period was measured for 3-sulphinylpropyl derivatives. However, it is still 12 times higher that this value measured without any inhibitors. Full-scale testing in 1% HCl solution showed that the corrosion rate slows down by 10–20 times upon the introduction of the derivatives of 3-sulphinylbutyl and 3-sulphinylpentyl at a concentration of ≥5.00 mM. If the concentration of 3-phenethylsulphinyl is equal to or higher than 1.00 mM, then the protection level is about 85%.
Reliability and Validity of Chinese Version of Oxford Hip Score

Objective To evaluate the reliability and validity of the Chinese version of Oxford Hip Score(OHS). Methods A total of 127 patients undergoing total hip arthroplasty were divided into three groups,including those pre-operative,one year and three years post-operative and investigated with OHS(Chinese version),SF-8 and EQ-5D.Then 20 cases were selected within the three groups respectively for repeated testing.Results The reliability coefficient(Cronbach's α) of the OHS was 0.94. Test-retest Spearman correlation coefficient was 0.98,0.91,0.76. Two public factors were extracted with factor analysis,and the corresponding factors of the projects were satisfied with factor loading.Conclusion The Chinese version of Oxford Hip Score is reliable and valid to determine the function of hip for Chinese patients.
A NOVEL RAISIN SEGMENTATION ALGORITHM BASED ON DEEP LEARNING AND MORPHOLOGICAL ANALYSIS

We propose a segmentation algorithm for raisin extraction. The proposed approach consists of the following aspects. Deep learning is used to predict the number of raisins in each connected region, and the shape features such as the roundness, area, X-axis value for the centroid, Y-axis value for the centroid, axis length and perimeter of each region will be used to establish the prediction model. Morphological analysis, based on edge parameters including the polar axis, polar angle and angular velocity, is applied to search for the suitable break points that are useful for identifying the dividing lines between two adjacent raisins. To make our segmentation more accurate, some machine-learning algorithms such as the random forest (RF), support vector machine (SVM) and deep
The application of BIM and photogrammetric methods to the inspection and management of the Sydney Harbour Tunnel

Sydney Harbour Tunnel provides a four lane crossing beneath Sydney Harbour between the Warringah Expressway at North Sydney and the Domain Tunnel in the City. The approximate length, portal to portal is 2.3 km and comprises twin driven and cut and cover tunnels at each end, and an immersed tunnel for the 1km long section beneath the harbour. The tunnel is a critical artery in Sydney's road network. As part of the development of an Enhanced Asset Management Plan for the tunnel, Arup has used digital tools including a business information model (BIM) and a photogrammetric survey. The paper will show how the use of these tools enabled the creation of a 3D immersive environment with embedded asset or condition information that allows engineers to virtually 'walk through' and inspect the asset. The paper will also discuss the benefits to asset owners and current areas of research to develop the technique further.
Phased and Synchronous Sampling Between Multiple Smart Network Sensors for Modal Assessment of Large Structures

Operational modal analysis and vibration-based damage detection of engineering structures have become important issues for Structural Health Monitoring (SHM) and maintenance operations. For this task, embedded wireless platforms such as the PEGASE platform are appealing and suitable to collect vibration data and then perform off-line and remote computation easily. To obtain detailed modal information of large and very large structures, many sensors would be required to cover the geometry of the structure with a reasonable accuracy. However, when only a limited amount of sensors is available, large structures can be measured in several sensor setups, where some sensors remain fixed and some are moved between different measurement setups. With the sensors connected to different wireless platforms, the synchronous acquisition of data is required. In this paper, a solution of data acquisition synchronization, as well as signal processing for merging the information taking into account the change of sensor positions and environmental variability is presented.
The effects of three blue light filter conditions for smartphones on visual fatigue and visual performance

Although blue light filters have been developed to decrease visual fatigue, the decreased screen brightness and contrast ratios inherent in current filtering techniques should be resolved. To address these issues, we developed a blue light filter, named the Eye Care blue light filter. This study investigated the effects of three blue light filtering techniques (the Eye Care blue light filter, an 80% blue light filter application [app], and a 60% blue light filter app) on visual fatigue and task performance. Thirty‐six healthy adults were recruited. Critical fusion frequency, task performance, and subjective visual fatigue scale were used to assess visual perception and task performance. All subjects played a smartphone game for 40 min in each experimental condition. Task performance was better with the Eye Care blue light filter than with the two filter apps. The value of the Eye Care blue light filter is that it immerses the user in a good task performance environment while reducing blue light exposure per unit of time more than is possible with filter apps.
Optimized Server Utilization In Multi Speciality Hospital By Using The Queuing Model Through Iot

: In modern multi-speciality hospital the need for sorting out patients in a queue and optimising the time in the entry stage is an essential activity. This activity can do quick and effective treatment to the patients. At present, the queuing system found in the hospital is chaotic and disorganised. This includes increased waiting time in queues, time delay for the patients and queue cutting by individuals due to unorganised queuing systems. This research work gives a solution to these problems by creating an Internet of Things (IoT) based environment in a multi-speciality hospital for initial data entry. IoT environment performs initial data entry of patients, functions of sorting out patient‘s queue and sends them to general physicians for treatment and diagnosis in a neat manner. The use of IoT and machine learning devices help to streamline the current system by the use of a Cloud based medical History (CBMH) database. This helps to access error free data quickly and also eliminate the usage of phony data given by the individuals. Here the queue sorting is done by the IoT devices through the optimized study of different types of queuing methods such as the single server queue, multi-server parallel queue and On Demand queue. The various performance parameters like queue length, number of servers and service rate are analysed for the different queuing systems and the most efficient queuing method is selected for the current situation.
Second‐order lead compensator‐based quadrature PLL for sensorless interior permanent magnet synchronous motor control

To eliminate harmonic components in estimated speed and position information generated by inverter non-linearities for the interior permanent-magnet synchronous motor (IPMSM) sensorless control, a second-order lead compensator-based quadrature phase-locked loop (SOLC-Q-PLL) is proposed for the sliding mode observer. An adaptive super-twisting sliding mode observer is taken to estimate back electromotive forces (EMFs) for IPMSM. Harmonic components in estimated position information generated by inverter non-linearities are analysed. Being dependent on the corresponding analysis, the SOLC-Q-PLL is proposed to eliminate sixth position estimation errors only by introducing a second-order lead compensator without causing phase delay for the phase-locked loop system. The introduction of the second-order lead compensator does not influence the bandwidth of the phase-locked loop system so that a fast transient response can be achieved, and this algorithm is easy to implement digitally due to its simple structure. Eventually, a series of experiments are conducted to validate the capability of the proposed algorithm.
Implementation of Grading Method for Gambier Leaves Based on Combination of Area, Perimeter, and Image Intensity Using Backpropagation Artificial Neural Network

Gambier leaves are widely used in cosmetics, beverages, and medicine. Tarantang village in West Sumatera, Indonesia, is famous for its gambier commodity. Farmers usually classify gambier leaves by area and color. They inherit this ability through generations. This research creates a tool to imitate the skill of the farmers to classify gambier leaves. The tool is a box covered from outside light. Two LEDs are attached inside the box to get maintain light intensity. A camera is used to capture the leaf image and a raspberry Pi processes the leaf features. A mini monitor is provided to operate the system. Six hundred and twenty-five gambier leaves were classified into five grades. Leaves categorized into grades 1, 2, and 3 are forbidden to be picked. Grade 4 leaves are allowed to be picked and those in grade 5 are the recommended ones for picking. Leaf features are area, perimeter, and intensity of leaf image. Three artificial neural networks are developed based on each feature. One thousand leaf images were used for training and 500 leaf images were used for testing. The accuracies of the features are about 93%, 96% and 97% for area, perimeter and intensity, respectively. A combination of rules are introduced into the system based on the feature accuracy. Those rules can give 100% accuracy compared to the farmer’s recommendation. A real time application to classify the leaves could provide classification with the same decision result as the classifying performed by the farmers.
Conjugation of Urokinase to Water-Soluble Magnetic Nanoparticles for Enhanced Thrombolysis

In this study, covalent conjugation of thrombolytic drug urokinase to water-soluble magnetic nanoparticles (NPs) is proposed to enhance the efficiency of thrombolysis. Hydrophobic NPs of oleic acid (OA)-coated Fe3O4 are first synthesized and then surface-modified with the amphipathic copolymer poly(maleic anhydride-alt-1-octadecylene) (PMAO) to form water-soluble NPs of PMAO-OA-Fe3O4 with monodispersed sizes. PMAO-OA-Fe3O4 NPs display a good water-based stability without aggregation at near neutral pH and show good magnetic separation characteristics. The thrombolytic drug urokinase is then covalently linked with the former product through dehydration condensation reaction between the amino and carboxyl produced by dehydration of the anhydride under N-Ethyl-N′-(3-dimethylaminopropyl) carbodiimide (EDC) and N-hydroxysuccinimide (NHS). Transmission electron microscope (TEM) images and dynamic light scattering (DLS) results show that the urokinase@PMAO-OA-Fe3O4 NPs are uniformly dispersed in water. The in vitro thrombolytic effect based on the manipulation of magnetic coupling, combined with static and alternating current (AC) magnetic fields, in a mimic blood-vascular system was studied. Drug release test shows that AC magnetic field can be used as switch and accelerator for NPs to release drugs. In addition, thrombolytic efficiency is nearly four times that of pure urokinase. This indicates that the coupling magnetic field may be a promising method to improve thrombolytic effect of the prepared magnetic carrier drug conjugates.
NFRP strengthening of reinforced concrete beams

The construction industry is currently the second largest consumer of synthetic FRP products. Increasing environmental awareness and the push for sustainable development fuels the drive to develop high strength natural fibres and bioplastics that can replace the conventional synthetic FRP components. Lignocellulosic plant fibres have considerable high strength and they are currently being used for non-structural applications in various industries. With proper fibre selection, the right fibre orientation, optimal fibre aspect ratio and good interfacial adhesion property between fibre and matrix, natural fibre reinforced polymer (NFRP) composite can be developed for structural applications. This review discusses NFRP composite in terms of its constituents, the fibre-matrix interaction, its manufacture and its use for strengthening of reinforced concrete (RC) beams.
Volume-volume matching

approved: Dr. Mike Bailey Oftentimes in visualization, the goal of using volume datasets is not just to visualize them but also to analyze and compare them. In order to compare the two volumes, we cannot take all the voxels into consideration. The size of a typical volume data set is quite large (maybe a billion or more voxels), thus it is not feasible to compare all these voxels to all in the other volume set. This project uses optimization methods to find the best orientation for aligning a second volume data set with a first. Using these methods, we will be able to determine how well one medical data volume matches against a “normally-developed” volume of the same type. c ©Copyright by Avneet Sandhu September 21, 2006 All Rights Reserved Volume-Volume Matching
Review of Multilevel Voltage Source Inverter Topologies and Analysis of Harmonics Distortions in FC-MLI

We review the most common topology of multi-level inverters. As is known, the conventional inverters are utilized to create an alternating current (AC) source from a direct current (DC) source. The two-level inverter provides various output voltages [(Vdc/2) and (−Vdc/2)] of the load. It is a successive method, but it makes the harmonic distortion of the output side, Electromagnetic interference (EMI), and high dv/dt. We solve this problem by constructing the sinusoidal voltage waveform. This is achieved by a “multilevel inverter” (MLI). The multilevel inverter creates the output voltage with multiple DC voltages as inputs. Many voltage levels are combined to produce a smoother waveform. During the last decade, the multilevel inverter has become very popular in medium and high-power applications with some advantages, such as the reduced power dissipation of switching elements, low harmonics, and low EMIs. We introduce the information about several multilevel inverters such as the diode-clamped multilevel inverter (DC-MLI), cascaded H-bridge multilevel inverter (CHB-MLI), and flying-capacitor multilevel inverter (FC-MLI) with Power systems CAD (PSCAD) simulation. It is shown that THD is 28.88% in three level FC-MLI while THD is 18.56% in five level topology. Therefore, we can decrease the total harmonic distortion adopting the higher-level topology.