Search results for: Madari gold mine

Authors: Shraddha Chaudhary, Raksha Agarwal, Niladri Chatterjee

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This work demonstrates a web crawler-based generalized end-to-end open domain Question Answering (QA) system. An efficient QA system requires a significant amount of domain knowledge to answer any question with the aim to find an exact and correct answer in the form of a number, a noun, a short phrase, or a brief piece of text for the user's questions. Analysis of the question, searching the relevant document, and choosing an answer are three important steps in a QA system. This work uses a web scraper (Beautiful Soup) to extract K-documents from the web. The value of K can be calibrated on the basis of a trade-off between time and accuracy. This is followed by a passage ranking process using the MS-Marco dataset trained on 500K queries to extract the most relevant text passage, to shorten the lengthy documents. Further, a QA system is used to extract the answers from the shortened documents based on the query and return the top 3 answers. For evaluation of such systems, accuracy is judged by the exact match between predicted answers and gold answers. But automatic evaluation methods fail due to the linguistic ambiguities inherent in the questions. Moreover, reference answers are often not exhaustive or are out of date. Hence correct answers predicted by the system are often judged incorrect according to the automated metrics. One such scenario arises from the original Google Natural Question (GNQ) dataset which was collected and made available in the year 2016. Use of any such dataset proves to be inefficient with respect to any questions that have time-varying answers. For illustration, if the query is where will be the next Olympics? Gold Answer for the above query as given in the GNQ dataset is “Tokyo”. Since the dataset was collected in the year 2016, and the next Olympics after 2016 were in 2020 that was in Tokyo which is absolutely correct. But if the same question is asked in 2022 then the answer is “Paris, 2024”. Consequently, any evaluation based on the GNQ dataset will be incorrect. Such erroneous predictions are usually given to human evaluators for further validation which is quite expensive and time-consuming. To address this erroneous evaluation, the present work proposes an automated approach for evaluating time-dependent question-answer pairs. In particular, it proposes a metric using the current timestamp along with top-n predicted answers from a given QA system. To test the proposed approach GNQ dataset has been used and the system achieved an accuracy of 78% for a test dataset comprising 100 QA pairs. This test data was automatically extracted using an analysis-based approach from 10K QA pairs of the GNQ dataset. The results obtained are encouraging. The proposed technique appears to have the possibility of developing into a useful scheme for gathering precise, reliable, and specific information in a real-time and efficient manner. Our subsequent experiments will be guided towards establishing the efficacy of the above system for a larger set of time-dependent QA pairs.

Keywords: web-based information retrieval, open domain question answering system, time-varying QA, QA evaluation

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Authors: Rizka Aisha Rahmi Hariadi, Chao Ou-Yang, Han-Cheng Wang, Rajesri Govindaraju

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As the increasing of medical check-up popularity, there are a huge number of medical check-up data stored in database and have not been useful. These data actually can be very useful for future strategic planning if we mine it correctly. In other side, a lot of patients come with unpredictable coming and also limited available facilities make medical check-up service offered by hospital not maximal. To solve that problem, this study used those medical check-up data to predict patient re-coming. Sequential pattern mining (SPM) and association rules method were chosen because these methods are suitable for predicting patient re-coming using sequential data. First, based on patient personal information the data was grouped into … groups then discriminant analysis was done to check significant of the grouping. Second, for each group some frequent patterns were generated using SPM method. Third, based on frequent patterns of each group, pairs of variable can be extracted using association rules to get general pattern of re-coming patient. Last, discussion and conclusion was done to give some implications of the results.

Keywords: patient re-coming, medical check-up, health examination, data mining, sequential pattern mining, association rules, discriminant analysis

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Authors: B. N. Makhanya, S. F. Ndulini, M. S. Mthembu

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Heavy metals are hazardous pollutants present in both industrial and domestic wastewater. They are usually disposed directly into natural streams, and when left untreated, they are a major cause of natural degradation and diseases. This study aimed to determine the ability of microalgae to remove heavy metals from coal mine wastewater. The green algae were grown and used for heavy metal removal in a laboratory bench. The physicochemical parameters and heavy metal removal were determined at 24 hours intervals for 5 days. The highest removal efficiencies were found to be 85%, 95%, and 99%, for Fe, Zn, and Cd, respectively. Copper and aluminium both had 100%. The results also indicated that the correlation between physicochemical parameters and all heavy metals were ranging from (0.50 ≤ r ≤ 0.85) for temperature, which indicated moderate positive to a strong positive correlation, pH had a very weak negative to a very weak positive correlation (-0.27 ≤ r ≤ 0.11), and chemical oxygen demand had a fair positive to a very strong positive correlation (0.69 ≤ r ≤ 0.98). The paired t-test indicated the removal of heavy metals to be statistically significant (0.007 ≥ p ≥ 0.000). Therefore, results showed that the microalgae used in the study were capable of removing heavy metals from industrial wastewater using possible mechanisms such as binding and absorption. Compared to the currently used technology for wastewater treatment, the microalgae may be the alternative to industrial wastewater treatment.

Keywords: heavy metals, industrial wastewater, microalgae, physiochemical parameters

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Authors: David Alejandro Torres-Lopez , Lilia Albores-Gallo, Ronald Soto-Calderon, Roberto Lagunes-Cordoba

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Autism Screening Questionnaire for Daycare Attendees (ASQ-DAT) is a screening instrument that assesses the risk of autism in children between 12 and 47 months, being the first free observational instrument created according to the criteria of the DSM-5 that can be applied by teachers in nurseries. The people in charge of answering the questionnaires are the daycare assistants. Its application presents a series of previous activities with which daycare assistants are familiar (dance, games, oral narration and breakfast), which are executed with the children and then answer a questionnaire with dichotomous questions "Yes/No" in approximately 3 minutes per child. The instrument was developed with the participation of nurseries according to the protocols of the creation of psychometric instruments of the Classical Test Theory having as a gold standard ADOS-2 Modules T and 1. The results of the investigation show that the use of ASQ-DAT combined with the application of M-CHAT / RF provides more information about the risk of ASD in young children, which allows improvements in the screening.

Keywords: diagnosis, screening, autism, daycare

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Authors: A. Nusrath Unissa, Sameer Hassan, Luke Elizabeth Hanna

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Altered drug binding may be an important factor in isoniazid (INH) resistance, rather than major changes in the enzyme’s activity as a catalase or peroxidase (KatG). The identification of structural or functional defects in the mutant KatGs responsible for INH resistance remains as an area to be explored. In this connection, the differences in the binding affinity between wild-type (WT) and mutants of KatG were investigated, through the generation of three mutants of KatG, Ser315Thr [S315T], Ser315Asn [S315N], Ser315Arg [S315R] and a WT [S315]) with the help of software-MODELLER. The mutants were docked with INH using the software-GOLD. The affinity is lower for WT than mutant, suggesting the tight binding of INH with the mutant protein compared to WT type. These models provide the in silico evidence for the binding interaction of KatG with INH and implicate the basis for rationalization of INH resistance in naturally occurring KatG mutant strains of Mycobacterium tuberculosis.

Keywords: Mycobacterium tuberculosis, KatG, INH resistance, mutants, modelling, docking

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Authors: Krupali Mukeshkumar, Jinesh Shah

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Background: Bilateral Sagittal Split Osteotomy (BSSO), used for the correction of mandibular deformities, is a common oral and maxillofacial surgical procedure. Inferior alveolar nerve dysfunction is commonly reported post-operatively by patients as paresthesia or anesthesia. The current literature lacks a consensus on the incidence of inferior alveolar nerve dysfunction as patients are not routinely assessed pre and post-operatively with an objective assessment. The range of incidence varies from 9% to 85% of patients, with some authors arguing that 100% of patients experience nerve dysfunction immediately post-surgery. Systematic reviews have shown a difference between incidence rates at different follow-up periods using objective and subjective methods. Aim: To identify the incidence of inferior alveolar nerve dysfunction following BSSO. Gold standard: Nerve dysfunction incidence rates similar or lower than current literature of 83% day one post-operatively and 18.4% at one year follow up. Setting: A retrospective cross-sectional audit of patients treated between 2017-2019 at the Royal Stoke University Hospital, Maxillofacial and Orthodontic departments. Sample: All patients who underwent a BSSO (with or without le fort one osteotomy) between 2017–2019 were identified from the database. Patients with pre-existing neurosensory disturbance, those who had a genioplasty at the same time and those with no follow-up were excluded. The sample consisted of 121 patients, 37 males and 84 females between the ages of 17-50 years at the time of surgery. Methods: Clinical records of 121 cases were reviewed to assess the age, sex, type of mandibular osteotomy, status of the nerve during the surgical procedure, type of bony split and incidence of nerve dysfunction at follow-up appointments. The surgical procedure was carried out by three Maxillo-facial surgeons and follow-up appointments were carried out in the Orthodontic and Oral and Maxillo-facial departments. Results: 120 patients were treated to correct the mandibular facial deformity and 1 patient was treated for sleep apnoea. Seventeen patients had a mandibular setback and 104 patients had mandibular advancement. 68 patients reported inferior alveolar nerve dysfunction at one week following their surgery. Seventy-six patients had temporary paresthesia present between 2 weeks and 12 months post-surgery. 13 patients had persistent nerve dysfunction at 12 months, of which 1 had a bad bony split during the BSSO. The incidence of nerve dysfunction postoperatively was 6.6% after 1 day, 56.1% at 1 week, 62.8% at 2 weeks, 59.5% between 3-6 weeks, 43.0% between 8-16 weeks and 10.7% at 1 year. Conclusions: The results of this audit show a similar incidence rate to the research gold standard at the one-year follow-up. Future Recommendations: No changes to surgical procedure or technique are indicated, but a need for improved documentation and a standardized approach for assessment of post-operative nerve dysfunction would be beneficial.

Keywords: bilateral sagittal split osteotomy, inferior alveolar nerve, mandible, nerve dysfunction

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Authors: Miroslav Čulík, Petr Gurný

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This paper is aimed at the financial assessment of the hard coal mining in a given region by real option methodology application. Hard coal mining in this mine makes net loss for the owner during the last years due to the long-term unfavourable mining conditions and significant drop in the coal prices during the last years. Management is going to shut down the operation and abandon the project to reduce the loss of the company. The goal is to assess whether the shutting down the operation is the only and correct solution of the problem. Due to the uncertainty in the future hard coal price evolution, the production might be again restarted if the price raises enough to cover the cost of the production. For the assessment, real option methodology is applied, which captures two important aspect of the financial decision-making: risk and flexibility. The paper is structured as follows: first, current state is described and problem is analysed. Next, methodology of real options is described. At last, project is evaluated by applying real option methodology. The results are commented and recommendations are provided.

Keywords: real option, investment, option to abandon, option to shut down and restart, risk, flexibility

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Authors: Şakir Bingöl, Bayram İslamoğlu, Ebubekir Furkan Tepeli, Fatih Mehmet Karakule, Fatih Küçük, Merve Sena Arpacık, Mustafa Taha Kabar, Muhammet Metin Molak, Osman Emre Turan, Ömer Faruk Yesir, Sıla İnanır

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This study introduces an IoT-based real-time safety system for mining, addressing global safety challenges. The wearable device, seamlessly integrated into miners' jackets, employs LoRa technology for communication and offers real-time monitoring of vital health and environmental data. Unique features include an LCD panel for immediate information display and sound-based location tracking for emergency response. The methodology involves sensor integration, data transmission, and ethical testing. Validation confirms the system's effectiveness in diverse mining scenarios. The study calls for ongoing research to adapt the system to different mining contexts, emphasizing its potential to significantly enhance safety standards in the industry.

Keywords: mining safety, internet of things, wearable technology, LoRa, RFID tracking, real-time safety system, safety alerts, safety measures

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Authors: Saeedeh Hajihosseini, Zahra Aghili, Navid Nasirizadeh

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An innovative method of a DNA electrochemical biosensor based on Oracet Blue (OB) as an electroactive label and gold electrode (AuE) for detection of Helicobacter pylori, was offered. A single–stranded DNA probe with a thiol modification was covalently immobilized on the surface of the AuE by forming an Au–S bond. Differential pulse voltammetry (DPV) was used to monitor DNA hybridization by measuring the electrochemical signals of reduction of the OB binding to double– stranded DNA (ds–DNA). Our results showed that OB–based DNA biosensor has a decent potential for detection of single–base mismatch in target DNA. Selectivity of the proposed DNA biosensor was further confirmed in the presence of non–complementary and complementary DNA strands. Under optimum conditions, the electrochemical signal had a linear relationship with the concentration of the target DNA ranging from 0.3 nmol L-1 to 240.0 nmol L-1, and the detection limit was 0.17 nmol L-1, whit a promising reproducibility and repeatability.

Keywords: DNA biosensor, oracet blue, Helicobacter pylori, electrode (AuE)

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Authors: Motahare Aali, Fatemeh Tajik

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Here, we investigate the sensitivity the Casimir force and consequently dynamical actuation of a three-layer microswitch to some ambient conditions. In fact, we have considered the effect of optical properties on the stable operation of the microswitch for both good (e.g. metals) and poor conductors via a three layer Casimir oscillator. Indeed, gold (Au) has been chosen as a good conductor which is widely used for Casimir force measurements, and highly doped conductive silicon carbide (SiC) has been considered as a poor conductor which is a promising material for device operating under harsh environments. Also, the intervening stratum is considered ethanol or water. It is also supposed that the microswitches are frictionless and autonomous. Using reduction factor diagrams and bifurcation curves, it has been shown how performance of the microswitches is sensitive to temperature and intervening stratum, moreover it is investigated how the conductivity of the components can affect this sensitivity.

Keywords: Casimir force, optical properties, Lifshitz theory, dielectric function

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Authors: Neeraj Vij, Amber Brennan, Jenni Winters, Hadi Salehi, Hamy Temkit, Emily Andrisevic, Mohan V. Belthur

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Idiopathic clubfoot is a common lower extremity deformity with an incidence of 1:500. The Ponseti Method is well known as the gold standard of treatment. However, there is limited functional data demonstrating correction of the clubfoot after treatment with the Ponseti method. The purpose of this study was to study the clinical and functional outcomes after the Ponseti method with the Clubfoot Disease-Specific Instrument (CDS) and pedobarography. This IRB-approved prospective study included patients aged 3-18 who were treated for idiopathic clubfoot with the Ponseti method between January 2008 and December 2018. Age-matched controls were identified through siblings of clubfoot patients and other community members. Treatment details were collected through a chart review of the included patients. Laboratory assessment included a physical exam, gait analysis, and pedobarography. The Pediatric Outcomes Data Collection Instrument and the Clubfoot Disease-Specific Instrument were also obtained on clubfoot patients (CF). The Wilcoxson rank-sum test was used to study differences between the CF patients and the typically developing (TD) patients. Statistical significance was set at p < 0.05. There were a total of 37 enrolled patients in our study. 21 were priorly treated for CF and 16 were TD. 94% of the CF patients had bilateral involvement. The age at the start of treatment was 29 days, the average total number of casts was seven to eight, and the average total number of casts after Achilles tenotomy was one. The reoccurrence rate was 25%, tenotomy was required in 94% of patients, and ≥1 tenotomy was required in 25% of patients. There were no significant differences between step length, step width, stride length, force-time integral, maximum peak pressure, foot progression angles, stance phase time, single-limb support time, double limb support time, and gait cycle time between children treated with the Ponseti method and typically developing children. The average post-treatment Pirani and Dimeglio scores were 5.50±0.58 and 15.29±1.58, respectively. The average post-treatment PODCI subscores were: Upper Extremity: 90.28, Transfers: 94.6, Sports: 86.81, Pain: 86.20, Happiness: 89.52, Global: 88.6. The average post-treatment Clubfoot Disease-Specific Instrument scores subscores were: Satisfaction: 73.93, Function: 80.32, Overall: 78.41. The Ponseti Method has a very high success rate and remains to be the gold standard in the treatment of idiopathic clubfoot. Timely management leads to good outcomes and a low need for repeated Achilles tenotomy. Children treated with the Ponseti method demonstrate good functional outcomes as measured through pedobarography. Pedobarography may have clinical utility in studying congenital foot deformities. Objective measures for hours of brace wear could represent an improvement in clubfoot care.

Keywords: functional outcomes, pediatric deformity, patient-reported outcomes, talipes equinovarus

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Authors: S. S. Pati, L. Herojit Singh, A. C. Oliveira, V. K. Garg

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Chitosan functionalized Fe3O4-Au core shell nanoparticles have been prepared using a two step wet chemical approach using NaBH4 as reducing agent for formation of Au inethylene glycol. X-ray diffraction studies shows individual phases of Fe3O4 and Au in the as prepared samples with crystallite size of 5.9 and 11.4 nm respectively. The functionalization of the core-shell nanostructure with Chitosan has been confirmed using Fourier transform infrared spectroscopy along with signatures of octahedral and tetrahedral sites of Fe3O4 below 600cm-1. Mössbauer spectroscopy shows decrease in particle-particle interaction in presence of Au shell (72% sextet) than pure oleic coated Fe3O4 nanoparticles (88% sextet) at room temperature. At 80K, oleic acid coated Fe3O4 shows only sextets whereas the Chitosan functionalized Fe3O4 and Chitosan functionalized Fe3O4@Au core shell show presence of 5 and 11% doublet, respectively.

Keywords: core shell, drug delivery, gold nanoparticles, magnetic nanoparticles

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Authors: Yang Yang, Dan Liu

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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

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Authors: Silvania M. P. Silva, Ricardo A. Mazaro, Gemilde M. Queiroz, Josefa Barbosa, Lucas S. Victorino, Grasiela J. Silva

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The Minas Gerais sweets have a remarkable personality, perceived on the original usage of fruits, sweets, and cheeses in the Brazilian gastronomic landscape, as a unique representation of Minas Gerais. This memory-related and feeling-oriented food is one of the treasures common to all Brazilians. It is mandatory to mention its Portuguese roots for the use of honey, as well as sugar cane and its countless possibilities. This work will show that this heritage is predominantly Portuguese, born in Portuguese convents and that it crossed the Atlantic. Through a historical survey, visits to mining towns known for their sweet culture and material collected in these places, we present the protagonists of this journey of flavors: the Portuguese cake makers (boleiras), who brought the knowledge, ingredients, and the dream of a better life in the crowded mines of gold and opportunities, helping to form a new Minas Gerais knowledge with their delicacies.

Keywords: sweets from portugal, convent sweets, minas gerais, brazil

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Authors: Muhammad Ilham Agus Salim, Mohammad Ali

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In this article, we have elaborated a study over the nature of Islamic financial transaction by comparing between Dinar and IDR currency in Indonesia. We have found the interesting issue among scholars and practitioners in which Dinar would be a single currency ASEAN Economic Community (AEC), then becoming motivation and added value research. The assessment among dinar volatility analysis for three years ago and IDR fluctuation as well as outlook qualitative test regarding dinar are components of analysis that weak Indonesian currency should be altered to be better coinage. The value of dinar more stable than IDR and also eligible as a currency e.g. limited quantities, easy to carry, durable, easy to saved, and has the same quality. On the other hand, the existing of IDR has defeated by inflation. The EViews program explained that Dinar at current level still fluctuate, but in the first different have fixed variant. The result of analysis describing that dinar has potential as the medium exchange, because the material of dinar is relevant and feasible since 14 century until present. Therefore, dinar should be considered to solve Indonesia crisis today.

Keywords: medium of exchange, dinar & IDR currency, volatility analysis, EViews program

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Authors: Belkacem Selma, Boumediene Selma, Tourkia Guerzou, Abbes Labdelli

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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. The Earthquakes prediction to prevent the loss of human lives and even property damage is an important factor; that is why it is crucial to develop techniques for predicting this natural disaster. This present study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 10^4J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines has been analyzed. The results obtained show that the ANN with high accuracy was able to predict earthquake parameters; the classification accuracy through neural networks is more than 94%, and that the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: earthquake prediction, ANN, seismic bumps

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Authors: M. Salvador, J. C. Martinez-Garcia, A. Moyano, M. C. Blanco-Lopez, M. Rivas

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Biosensors play a crucial role in the detection of molecules nowadays due to their advantages of user-friendliness, high selectivity, the analysis in real time and in-situ applications. Among them, Lateral Flow Immunoassays (LFIAs) are presented among technologies for point-of-care bioassays with outstanding characteristics such as affordability, portability and low-cost. They have been widely used for the detection of a vast range of biomarkers, which do not only include proteins but also nucleic acids and even whole cells. Although the LFIA has traditionally been a positive/negative test, tremendous efforts are being done to add to the method the quantifying capability based on the combination of suitable labels and a proper sensor. One of the most successful approaches involves the use of magnetic sensors for detection of magnetic labels. Bringing together the required characteristics mentioned before, our research group has developed a biosensor to detect biomolecules. Superparamagnetic nanoparticles (SPNPs) together with LFIAs play the fundamental roles. SPMNPs are detected by their interaction with a high-frequency current flowing on a printed micro track. By means of the instant and proportional variation of the impedance of this track provoked by the presence of the SPNPs, quantitative and rapid measurement of the number of particles can be obtained. This way of detection requires no external magnetic field application, which reduces the device complexity. On the other hand, the major limitations of LFIAs are that they are only qualitative or semiquantitative when traditional gold or latex nanoparticles are used as color labels. Moreover, the necessity of always-constant ambient conditions to get reproducible results, the exclusive detection of the nanoparticles on the surface of the membrane, and the short durability of the signal are drawbacks that can be advantageously overcome with the design of magnetically labeled LFIAs. The approach followed was to coat the SPIONs with a specific monoclonal antibody which targets the protein under consideration by chemical bonds. Then, a sandwich-type immunoassay was prepared by printing onto the nitrocellulose membrane strip a second antibody against a different epitope of the protein (test line) and an IgG antibody (control line). When the sample flows along the strip, the SPION-labeled proteins are immobilized at the test line, which provides magnetic signal as described before. Preliminary results using this practical combination for the detection and quantification of the Prostatic-Specific Antigen (PSA) shows the validity and consistency of the technique in the clinical range, where a PSA level of 4.0 ng/mL is the established upper normal limit. Moreover, a LOD of 0.25 ng/mL was calculated with a confident level of 3 according to the IUPAC Gold Book definition. Its versatility has also been proved with the detection of other biomolecules such as troponin I (cardiac injury biomarker) or histamine.

Keywords: biosensor, lateral flow immunoassays, point-of-care devices, superparamagnetic nanoparticles

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Authors: S. S. Patil, Sachidanand Kini

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Classification of land use patterns is compelling in complexity and variability of remote sensing imageries data. An imperative research in remote sensing application exploited to mine some of the significant spatially variable factors as land cover and land use from satellite images for remote arid areas in Karnataka State, India. The diverse classification techniques, unsupervised and supervised consisting of maximum likelihood, Mahalanobis distance, and minimum distance are applied in Bellary District in Karnataka State, India for the classification of the raw satellite images. The accuracy evaluations of results are compared visually with the standard maps with ground-truths. We initiated with the maximum likelihood technique that gave the finest results and both minimum distance and Mahalanobis distance methods over valued agriculture land areas. In meanness of mislaid few irrelevant features due to the low resolution of the satellite images, high-quality accord between parameters extracted automatically from the developed maps and field observations was found.

Keywords: Mahalanobis distance, minimum distance, supervised, unsupervised, user classification accuracy, producer's classification accuracy, maximum likelihood, kappa coefficient

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Authors: Vivek Krishna, Nikhil Jain, A. Mary Posonia A., Albert Mayan J

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Terrorism and insurgency are significant global issues that require constant attention and effort from governments and scientists worldwide. To combat these threats, nations invest billions of dollars in developing new defensive technologies to protect civilians. Breakthroughs in vehicle automation have led to the use of sophisticated machines for many dangerous and critical anti-terrorist activities. Our concept of an "Unmanned Ground Vehicle" can carry out tasks such as border security, surveillance, mine detection, and active combat independently or in tandem with human control. The robot's movement can be wirelessly controlled by a person in a distant location or can travel to a pre-programmed destination autonomously in situations where personal control is not feasible. Our defence system comprises two units: the control unit that regulates mobility and the motion tracking unit. The remote operator robot uses the camera's live visual feed to manually operate both units, and the rover can automatically detect movement. The rover is operated by manpower who controls it using a joystick or mouse, and a wireless modem enables a soldier in a combat zone to control the rover via an additional controller feature.

Keywords: robotics, computer vision, Machine learning, Artificial intelligence, future of AI

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Authors: Cheng-Jhe Lee, Chiun-Chieh Hsu

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Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms.

Keywords: FIHC, documents clustering, ontology, closed frequent itemset

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Authors: Farah El Mohtadi, Richard d'Arcy, Nicola Tirelli

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Since 40 years, poly (ethylene glycol) (PEG) has been the gold standard in biomaterials and drug delivery, because of its combination of chemical and biological inertness. However, the possibility of its breakdown under oxidative conditions and the demonstrated development of anti-PEG antibodies highlight the necessity to develop carriers based on materials with increased stability in a challenging biological environment. Here, we describe the synthesis of polysulfide via anionic ring-opening polymerization. In vitro, the synthesized polymer was characterized by low toxicity and a level of complement activation (in human plasma) and macrophage uptake slightly lower than PEG and poly (2‐methyl-2‐oxazoline) (PMOX), of a similar size. Importantly, and differently from PEG, on activated macrophages, the synthesized polymer showed a strong and dose-dependent ROS scavenging activity, which resulted in the corresponding reduction of cytokine production. Therefore, the results from these studies show that polysulfide is highly biocompatible and are potential candidates to be used as an alternative to PEG for various applications in nanomedicine.

Keywords: PEG, low toxicity, ROS scavenging, biocompatible

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Authors: Ceren Vardar Acar, Mine Caglar

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In finance, the price of a volatile asset can be modeled using fractional Brownian motion (fBm) with Hurst parameter H>1/2. The Black-Scholes model for the values of returns of an asset using fBm is given as, 〖Y_t=Y_0 e^((r+μ)t+σB)〗_t^H, 0≤t≤T where Y_0 is the initial value, r is constant interest rate, μ is constant drift and σ is constant diffusion coefficient of fBm, which is denoted by B_t^H where t≥0. Black-Scholes model can be constructed with some Markov processes such as Brownian motion. The advantage of modeling with fBm to Markov processes is its capability of exposing the dependence between returns. The real life data for a volatile asset display long-range dependence property. For this reason, using fBm is a more realistic model compared to Markov processes. Investors would be interested in any kind of information on the risk in order to manage it or hedge it. The maximum possible loss is one way to measure highest possible risk. Therefore, it is an important variable for investors. In our study, we give some theoretical bounds on the distribution of maximum possible loss of fBm. We provide both asymptotical and strong estimates for the tail probability of maximum loss of standard fBm and fBm with drift and diffusion coefficients. In the investment point of view, these results explain, how large values of possible loss behave and its bounds.

Keywords: maximum drawdown, maximum loss, fractional brownian motion, large deviation, Gaussian process

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Authors: Dina Dahood Dabash

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Palestine Refugee Camps have never been settings that can be overlooked; they even became (as physical settings) a cornerstone topic of negotiations whenever Palestinian matters are on the table (specifically in Jordan). Consequently, maintaining the familiar face of the camp with its dilapidated shelters and narrow streets that rarely allowed its residents to extinguish a fire or evacuate a building safely has become a fundamental method to protect the “right of the return” from the perspective of various stakeholders. When the Infrastructure and Camp Improvement Programme (ICIP) was established in 2007 as an additional UNRWA program, some concerns were raised around the newly established section, mainly due to its direct impact on the “image” of the camp through a provision of a relatively nonconventional service that differs from what the Agency used to provide in the past seventy years. By presenting the Urban Improvement Project in Jerash camp (UIP) -Jordan, this paper aims to contribute to the ongoing discussion around enduring the improvement of Palestine refugee camps “programmatically” in UNRWA or not. The UIP as a co-product by UNRWA and the camp’s community within one of the most vulnerable refugee camps in Jordan offers a remarkable opportunity to excerpt lessons that can contribute to the strategic shaping of the ICIP. The paper concludes with five mine uptakes mainly related to community engagement, power structures and UNRWA's role in camps.

Keywords: camp improvement program, Jerash camp, Palestine refugee camps, UNRWA.

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Authors: N. Ouslimani, M. T. Abadlia, S. Yakoub, F. Tebbani

Abstract:

Water has always been synonymous with life and growth. Blue gold is first essential to the survival of the human being whose body consists of more than 65% with the development of industrialization and consumption patterns; volumes of wastewater discharges have increased considerably whether industrial or domestic, waste water must be purified before discharge. Treatment, therefore, aims to reduce the pollution load which contain. The resources in Algeria are limited and unevenly distributed. Thus, to meet all the water needs of the country and to preserve the waters of good quality drinking water supply, one solution would be to use them according to their quality and to irrigate crops for the food or be directed to the irrigation of green areas or sports complex. The purification performance of this STEP has been established since the pH analyzed pollution criteria (7.36) and temperature (16°C), MES (10 mg / l), electrical conductivity (1122 / µs / cm), DBO5 (6mg / l), DCO (15mg / l) meet the discharge standards. Arguably the purified water discharged out of the boumerdes STEP comply with Algerian regulations and can be reused in agriculture. COD biodegradability of the coefficient / BOD5 is 2.5 (less than 3) indicates that of the effluent are biodegradable hence their urban origin.

Keywords: irrigation, recovery, treated, wastewater

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Authors: M. Simchi, M. Amiri, E. Rezvani, I. Mirzaei, M. Berahman, A. Simchi, M. Fardmanesh

Abstract:

Graphene is a single-atomic two-dimensional crystal of carbon atoms that has considerable properties due to its unique structure and physics with applications in different fields. Graphene has sensitive electrical properties due to its atomic-thin structure. Along with the substrate materials and their influence on the transport properties in graphene, design and fabrication of graphene-based devices for biomedical and biosensor applications are challenging. In this work, large-area high-quality graphene nanosheets were prepared by low pressure chemical vapor deposition using methane gas as carbon source on copper foil and transferred on the biocompatible substrates. Through deposition of titanium and gold contacts, current-voltage response of the transferred graphene on four biocompatible substrates, including PDMS, SU-8, Nitrocellulose, and Kapton (Fig. 2) were experimentally determined. The considerable effect of the substrate type on the electrical properties of graphene is shown. The sheet resistance of graphene is changed from 0.34 to 14.5 kΩ/sq, depending on the substrate.

Keywords: biocompatible substrates, electrical properties, graphene, sheet resistance

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Authors: Li Guoyou, Zhang Tao, Ji Wenzhan, Huo Liang, Lin Xiqiang, Zhang Nan

Abstract:

The three dimensional (3D) printing technology has undergone rapid development in the last few years and it is possible to print engineering structures. 3D printing buildings use wastes from constructions, industries and mine tailings as “ink”, and mix it with property improved materials, such as cement, fiber etc. This paper presents a study of the Thermodynamic performance of 3D printed walls using cement and steel slag powder. Analyses the thermal simulation regarding 3D printed walls and solid brick wall by the way of the hot-box methods and the infrared technology, and the results were contrasted with theoretical calculation. The results show that the excellent thermodynamic performance of 3D printed concrete wall made it suitable as the partial materials for self-thermal insulation walls in residential buildings. The thermodynamic performance of 3D printed concrete walls depended on the density of materials, distribution of holes, and the filling materials. Decreasing the density of materials, increasing the number of holes or replacing the filling materials with foamed concrete could improve its thermodynamic performance significantly. The average of heat transfer coefficient and thermal inertia index of 3D printed steel slag powder concrete wall all better than the traditional solid brick wall with a thickness of 240mm.

Keywords: concrete, 3D printed walls, thermodynamic performance, steel slag powder

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Authors: Sukhleen Kaur

Abstract:

In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

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Authors: Zain Khan, Steve Ahn, Kathy Monypenny, James Fink

Abstract:

In Australian public hospitals, there were approximately 34,000 reported inpatient falls between 2015 to 2016. The gold standard for diagnosing intracranial injury is non-contrast enhanced brain computed tomography (CTB). Over a three-month timeframe, a total of one hundred and eighty (180) falls were documented between the hours of 4pm and 8am at a large metro hospital. Only three (3) of these scans demonstrated a positive intra-cranial finding. The rationale for scanning varied. The common indications included a fall with head strike, the presence of blood thinning medication, loss of consciousness, reduced Glasgow Coma Scale (GCS), vomiting and new neurological findings. There are several validated tools to aid in decision-making around ordering CTB scans in the acute setting, but no such accepted tool exists for the inpatient space. With further data collection, spanning a greater length of time and through involving multiple centres, work can be done towards generating such a tool that can be utilized for inpatient falls.

Keywords: computed tomography, falls, inpatient, intracranial hemorrhage

Procedia PDF Downloads 168

Authors: Memnun Seven, Mine Bahar, Aygül Akyüz, Hatice Erdoğan

Abstract:

Background: The workplace has been deemed a suitable location for educating many women at once about cancer screening. Objective: To determine how group education about early diagnostic methods for breast and cervical cancer affects women’s behavior and readiness to receive mammography and Pap smears. Methods: This semi-interventional study was conducted at a textile factory in Istanbul, Turkey. Female workers (n = 125) were included in the study. A participant identification form and knowledge evaluation form developed for this study, along with the trans-theoretical model, were used to collect data. A 45-min interactive group education was given to the participants. Results: Upon contacting participants 3 months after group education, 15.4% (n = 11) stated that they had since received a mammogram and 9.8% (n = 7) a Pap smear. As suggested by the trans-theoretical model, group education increased participants’ readiness to receive cancer screening, along with their knowledge of breast and cervical cancer. Conclusions: Group education positively impacted women’s knowledge of cancer and their readiness to receive mammography and Pap smears. Group education can therefore potentially create awareness of cancer screening tests among women and improve their readiness to receive such tests.

Keywords: cancer screening, educational intervention, participation, women

Procedia PDF Downloads 326

Authors: Tanvi P. Patel, Warish D. Patel

Abstract:

Association rule mining forms the core of data mining and it is termed as one of the well-known methodologies of data mining. Objectives of mining is to find interesting correlations, frequent patterns, associations or casual structures among sets of items in the transaction databases or other data repositories. Hence, association rule mining is imperative to mine patterns and then generate rules from these obtained patterns. For efficient targeted query processing, finding frequent patterns and itemset mining, there is an efficient way to generate an itemset tree structure named Memory Efficient Itemset Tree. Memory efficient IT is efficient for storing itemsets, but takes more time as compare to traditional IT. The proposed strategy generates maximal frequent itemsets from memory efficient itemset tree by using levelwise pruning. For that firstly pre-pruning of items based on minimum support count is carried out followed by itemset tree reconstruction. By having maximal frequent itemsets, less number of patterns are generated as well as tree size is also reduced as compared to MEIT. Therefore, an enhanced approach of memory efficient IT proposed here, helps to optimize main memory overhead as well as reduce processing time.

Keywords: association rule mining, itemset mining, itemset tree, meit, maximal frequent pattern

Procedia PDF Downloads 368