Search results for: fault detection and isolation

Authors: Hamisu Idi

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The present study focuses on studying the impact of influencer recommendation in the quality of cement production. Exploratory research was done on monthly basis, where data were obtained from secondary source i.e. the record kept by an automated recompilation machine. The machine keeps all the records of the mills downtime which the process manager checks for validation and refer the fault (if any) to the department responsible for maintenance or measurement taking so as to prevent future occurrence. The findings indicated that the product of the Ashaka Cement Plc. were considered as qualitative, since all the production processes were found to be in control (preset specifications) with the exception of the natural cause of variation which is normal in the production process as it will not affect the outcome of the product. It is reduced to the bearest minimum since it cannot be totally eliminated. It is also hopeful that the findings of this study would be of great assistance to the management of Ashaka cement factory and the process manager in particular at various levels in the monitoring and implementation of statistical process control. This study is therefore of great contribution to the knowledge in this regard and it is hopeful that it would open more research in that direction.

Keywords: cement, quality, variation, assignable cause, common cause

Procedia PDF Downloads 246

Authors: Hamza Assiry, Gamal A. Mohamed, Sabrin R. M. Ibrahim, Hossam M. Abdallah

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Chemical investigation of the aerial parts of Barleria trispinosa(Forssk.) Vahl. resulted in isolation of four major iridoids that were identified as 6,8-O,O-diacetylshanhiside methyl ester (acetyl barlerin) (1), 8-O-acetylshanzhiside methyl ester (barlerin) (2), shanzhiside methyl ester (3), and 6- ⍺ -L-rhamnopyranosyl-8-O-acetylshanzihiside methyl ester (4). The isolated compounds were confirmed by detailed one and two-dimensional NMR. Isolated compounds were tested for their cytotoxic activity on breast cancer (MCF-7, MDA-MB-231) and colon cancer (LS174T) cell linesusing sulphorhodamine B (SRB) assay. It is noteworthy that compound 1 demonstrated a significant cytotoxic potential towards MDA-MB-231 cell line with IC5016.7 ± 2.7µg / mL compared to doxorubicin whereas compounds 2, showed moderate cytotoxic potential with IC5021.2 ± 1.9µg / mL on MCF-7. The other compounds showed moderate activity on the tested cell lines.

Keywords: acanthaceae, cytotoxicity, metabolites, barleria trispinosa

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Authors: Sheela Tiwari, R. Naresh, R. Jha

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The paper presents an investigation into the effect of neural network predictive control of UPFC on the transient stability performance of a multi-machine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers and an improved damping of the power oscillations as compared to the conventional PI controller.

Keywords: identification, neural networks, predictive control, transient stability, UPFC

Procedia PDF Downloads 361

Authors: Olivier Chaigneau, Damianos Oikonomidis, Marie-Cecile Delmas

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GAMBAS (Galileo Advanced features for the Maritime domain: Breakthrough Applications for Safety and security) is a project funded by the European Space Program Agency (EUSPA) aiming at identifying the search-and-rescue and ship security alert system needs for maritime users (including operators and fishing stakeholders) and developing operational concepts to answer these needs. The general objective of the GAMBAS project is to support the deployment of Galileo exclusive features in the maritime domain in order to improve safety and security at sea, detection of illegal activities and associated surveillance means, resilience to natural and human-induced emergency situations, and develop, integrate, demonstrate, standardize and disseminate these new associated capabilities. The project aims to demonstrate: improvement of the SAR (Search And Rescue) and SSAS (Ship Security Alert System) detection and response to maritime distress through the integration of new features into the beacon for SSAS in terms of cost optimization, user-friendly aspects, integration of Galileo and OS NMA (Open Service Navigation Message Authentication) reception for improved authenticated localization performance and reliability, and at sea triggering capabilities, optimization of the responsiveness of RCCs (Rescue Co-ordination Centre) towards the distress situations affecting vessels, the adaptation of the MCCs (Mission Control Center) and MEOLUT (Medium Earth Orbit Local User Terminal) to the data distribution of SSAS alerts.

Keywords: Galileo new advanced features, maritime, safety, security

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Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Huajuan Shi

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Background: The biopsy of the preimplantation embryo may increase the potential risk and concern of embryo viability. Clinically discarded spent embryo medium (SEM) has entered the view of researchers, sparking an interest in noninvasive embryo screening. However, one of the major restrictions is the extremelty low quantity of cf-RNA, which is difficult to efficiently and unbiased amplify cf-RNA using traditional methods. Hence, there is urgently need to an efficient and low bias amplification method which can comprehensively and accurately obtain cf-RNA information to truly reveal the state of SEM cf-RNA. Result: In this present study, we established an agarose PCR amplification system, and has significantly improved the amplification sensitivity and efficiency by ~90 fold and 9.29 %, respectively. We applied agarose to sequencing library preparation (named AG-seq) to quantify and characterize cf-RNA in SEM. The number of detected cf-RNAs (3533 vs 598) and coverage of 3' end were significantly increased, and the noise of low abundance gene detection was reduced. The increasing percentage 5' end adenine and alternative splicing (AS) events of short fragments (< 400 bp) were discovered by AG-seq. Further, the profiles and characterizations of cf-RNA in spent cleavage medium (SCM) and spent blastocyst medium (SBM) indicated that 4‐mer end motifs of cf-RNA fragments could remarkably differentiate different embryo development stages. Significance: This study established an efficient and low-cost SEM amplification and library preparation method. Not only that, we successfully described the characterizations of SEM cf-RNA of preimplantation embryo by using AG-seq, including abundance features fragment lengths. AG-seq facilitates the study of cf-RNA as a noninvasive embryo screening biomarker and opens up potential clinical utilities of trace samples.

Keywords: cell-free RNA, agarose, spent embryo medium, RNA sequencing, non-invasive detection

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Authors: Rafsan Al Mamun, Md. Motaharul Islam, Rabana Tajrin, Nabiha Noor, Shafinaz Qader

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In an attempt to enrich the lives of billions of people by providing proper information, security and a way of communicating with others, the need for efficient and improved satellites is constantly growing. Thus, there is an increasing demand for better error detection and correction (EDAC) schemes, which are capable of protecting the data onboard the satellites. The paper is aimed towards detecting and correcting such errors using a special algorithm called the Hamming Code, which uses the concept of parity and parity bits to prevent single-bit errors onboard a satellite in Low Earth Orbit. This paper focuses on the study of Low Earth Orbit satellites and the process of generating the Hamming Code matrix to be used for EDAC using computer programs. The most effective version of Hamming Code generated was the Hamming (16, 11, 4) version using MATLAB, and the paper compares this particular scheme with other EDAC mechanisms, including other versions of Hamming Codes and Cyclic Redundancy Check (CRC), and the limitations of this scheme. This particular version of the Hamming Code guarantees single-bit error corrections as well as double-bit error detections. Furthermore, this version of Hamming Code has proved to be fast with a checking time of 5.669 nanoseconds, that has a relatively higher code rate and lower bit overhead compared to the other versions and can detect a greater percentage of errors per length of code than other EDAC schemes with similar capabilities. In conclusion, with the proper implementation of the system, it is quite possible to ensure a relatively uncorrupted satellite storage system.

Keywords: bit-flips, Hamming code, low earth orbit, parity bits, satellite, single error upset

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Authors: Mehmet Salih Bayraktutan, Emre Tokmak

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Great Ararat Volcano is the highest peak in South Caucasus Volcanic Plateau. Uplifted by Quaternary basaltic pyroclastic and lava flows. Numerous volcanic cones formed along with the tensional fractures under N-S compressional geodynamic framework. Basaltic flows have fresh surface morphology give ages of 650-680 K years. Hyperstene andesites constitute a major mass of Greater Ararat gives ages of 450-490 K years. During the early eruption period, predominately pyroclastics, cinder, lapilly-ash volcanic bombs were extruded. Third-period eruptions dominantly basaltic lava flows. Andesitic domes aligned along with the NW-SE striking fractures. Hyalo basalt and hornblende basaltic lavas are the latest lava eruptions. Hyalo-basaltic eruptions occurred via parasitic cones distributed far from the center. Parasitic cones are most common at the foot of Mount covered by recent NW flowing basaltic lava. Some of the cones are distributed on a circular pattern. One of the most hazardous disasters recorded in Eastern Turkey was July 1840 Cehennem Canyon Flood. Volcanic activities seismically triggered resulted in melting of glacier cap, mixed with ash and pyroclastics, flowed down along the Valley. Mud rich Slush urged catastrophically northwards, crossed Ars River and damned Surmeli Basin, forming reservoir behind. Ararat volcanoes are located on NW-SE striking Agri Fault Zone. Right lateral extensional faults, along which a series of andesitic domes formed. Great Ararat, in general strato-type volcano. This huge structure, developed in two main parts with different topographic and morphological features. The large lower base covers a widespread area composed of predominantly pyroclastics, ignimbrites, aglomerates, thick pumice, perlite deposits. Approximately 1/3 of the Crest by height formed of this basement. And 2/3 of the upper part with a conic- shape composed of basaltic lava flows. The active tectonic structure consists of three different patterns. The first network is radially distributed fractures formed during the last stage of lava eruptions. The second group of active faults striking in NW direction, and continue in N30W strike, formes Igdir Fault Zone. The third set of faults, dipping in the northwest with 75-80 degrees, strikes NE- SW across the whole Mount, slicing Great Ararat into four segments. In the upper stage of Cehennem Canyon, this set cutting volcanic layers caused numerous Waterfalls, Rock Avalanches, Mud Flows along the canyon, threatens the Village of Yanidogan, at the apex of flood deposits. Great Ararat Region has high seismo-tectonic risk and by occurrence frequency and magnitude, which caused in history caused heavy disasters, at villages surrounding the Ararat Basement.

Keywords: Eastern Turkey, geohazard, great ararat volcano, seismo-tectonic features

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Authors: Zonglin Yang, Tatsuya Akiyama, Kerry S. Williamson, Michael J. Franklin, Thiruvarangan Ramaraj

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Pseudomonas aeruginosa is an opportunistic pathogen that forms surface-associated microbial communities (biofilms) on artificial implant devices and on human tissue. Biofilm infections are difficult to treat with antibiotics, in part, because the bacteria in biofilms are physiologically heterogeneous. One measure of biological heterogeneity in a population of cells is to quantify the cellular concentrations of ribosomes, which can be probed with fluorescently labeled nucleic acids. The fluorescent signal intensity following fluorescence in situ hybridization (FISH) analysis correlates to the cellular level of ribosomes. The goals here are to provide computationally and statistically robust approaches to automatically quantify cellular heterogeneity in biofilms from a large library of epifluorescent microscopy FISH images. In this work, the initial steps were developed toward these goals by developing an automated biofilm detection approach for use with FISH images. The approach allows rapid identification of biofilm regions from FISH images that are counterstained with fluorescent dyes. This methodology provides advances over other computational methods, allowing subtraction of spurious signals and non-biological fluorescent substrata. This method will be a robust and user-friendly approach which will enable users to semi-automatically detect biofilm boundaries and extract intensity values from fluorescent images for quantitative analysis of biofilm heterogeneity.

Keywords: image informatics, Pseudomonas aeruginosa, biofilm, FISH, computer vision, data visualization

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Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig

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This study applied traffic speed and occupancy to develop clustering models that identify different traffic conditions. Particularly, these models are based on the Dirichlet Process Mixture of Generalized Linear regression (DML) and change-point regression (CR). The model frameworks were implemented using 2015 historical traffic data aggregated at a 15-minute interval from an Interstate 295 freeway in Jacksonville, Florida. Using the deviance information criterion (DIC) to identify the appropriate number of mixture components, three traffic states were identified as free-flow, transitional, and congested condition. Results of the DML revealed that traffic occupancy is statistically significant in influencing the reduction of traffic speed in each of the identified states. Influence on the free-flow and the congested state was estimated to be higher than the transitional flow condition in both evening and morning peak periods. Estimation of the critical speed threshold using CR revealed that 47 mph and 48 mph are speed thresholds for congested and transitional traffic condition during the morning peak hours and evening peak hours, respectively. Free-flow speed thresholds for morning and evening peak hours were estimated at 64 mph and 66 mph, respectively. The proposed approaches will facilitate accurate detection and prediction of traffic congestion for developing effective countermeasures.

Keywords: traffic congestion, multistate speed distribution, traffic occupancy, Dirichlet process mixtures of generalized linear model, Bayesian change-point detection

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Authors: Madhuka G. P. D. Udantha, Gihan V. Dias, Surangika Ranathunga

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Today Websites contain very interesting applications. But there are only few methodologies to analyze User navigations through the Websites and formulating if the Website is put to correct use. The web logs are only used if some major attack or malfunctioning occurs. Web Logs contain lot interesting dealings on users in the system. Analyzing web logs has become a challenge due to the huge log volume. Finding interesting patterns is not as easy as it is due to size, distribution and importance of minor details of each log. Web logs contain very important data of user and site which are not been put to good use. Retrieving interesting information from logs gives an idea of what the users need, group users according to their various needs and improve site to build an effective and efficient site. The model we built is able to detect attacks or malfunctioning of the system and anomaly detection. Logs will be more complex as volume of traffic and the size and complexity of web site grows. Unsupervised techniques are used in this solution which is fully automated. Expert knowledge is only used in validation. In our approach first clean and purify the logs to bring them to a common platform with a standard format and structure. After cleaning module web session builder is executed. It outputs two files, Web Sessions file and Indexed URLs file. The Indexed URLs file contains the list of URLs accessed and their indices. Web Sessions file lists down the indices of each web session. Then DBSCAN and EM Algorithms are used iteratively and recursively to get the best clustering results of the web sessions. Using homogeneity, completeness, V-measure, intra and inter cluster distance and silhouette coefficient as parameters these algorithms self-evaluate themselves to input better parametric values to run the algorithms. If a cluster is found to be too large then micro-clustering is used. Using Cluster Signature Module the clusters are annotated with a unique signature called finger-print. In this module each cluster is fed to Associative Rule Learning Module. If it outputs confidence and support as value 1 for an access sequence it would be a potential signature for the cluster. Then the access sequence occurrences are checked in other clusters. If it is found to be unique for the cluster considered then the cluster is annotated with the signature. These signatures are used in anomaly detection, prevent cyber attacks, real-time dashboards that visualize users, accessing web pages, predict actions of users and various other applications in Finance, University Websites, News and Media Websites etc.

Keywords: anomaly detection, clustering, pattern recognition, web sessions

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Authors: Waleed K. Saib, Abdulsalam M. Alhawsawi, Essam Banoqitah

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The idea of this research is to design a radiation spectrometer using LSO scintillation detector coupled to a C series of SiPM (silicon photomultiplier). The device can be used to detects gamma and X-ray radiation. This device is also designed to estimates the activity of the source contamination. The SiPM will detect light in the visible range above the threshold and read them as counts. Three gamma sources were used for these experiments Cs-137, Am-241 and Co-60 with various activities. These sources are applied for four experiments operating the SiPM as a spectrometer, energy resolution, pile-up set and efficiency. The SiPM is connected to a MCA to perform as a spectrometer. Cerium doped Lutetium Silicate (Lu₂SiO₅) with light yield 26000 photons/Mev coupled with the SiPM. As a result, all the main features of the Cs-137, Am-241 and Co-60 are identified in MCA. The experiment shows how photon energy and probability of interaction are inversely related. Total attenuation reduces as photon energy increases. An analytical calculation was made to obtain the FWHM resolution for each gamma source. The FWHM resolution for Am-241 (59 keV) is 28.75 %, for Cs-137 (662 keV) is 7.85 %, for Co-60 (1173 keV) is 4.46 % and for Co-60 (1332 keV) is 3.70%. Moreover, the experiment shows that the dead time and counts number decreased when the pile-up rejection was disabled and the FWHM decreased when the pile-up was enabled. The efficiencies were calculated at four different distances from the detector 2, 4, 8 and 16 cm. The detection efficiency was observed to declined exponentially with increasing distance from the detector face. Conclusively, the SiPM board operated with an LSO scintillator crystal as a spectrometer. The SiPM energy resolution for the three gamma sources used was a decent comparison to other PMTs.

Keywords: PMT, radiation, radiation detection, scintillation detectors, silicon photomultiplier, spectrometer

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Authors: Aminu Muhammad, Mustapha Ya’u, Hasnah Mohd Sirat

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An investigation of the chemical constituents into the stem bark of Ficus platyphylla (Moraceae) has resulted in the isolation of hordenine, epicatechin, lupeol, lupeol acetate and α-amyrin acetate. Their structures were determined using spectroscopic data as well as comparison with literature data. The antibacterial assay has been tested against Gram positive and Gram negative bacteria, while the tyrosinase inhibition assay was examined using L-Dopa as a substrate of mushroom tyrosinase enzyme. hordenine, epicatechin, lupeol, lupeol acetate and α-amyrin acetate showed minimum inhibition concentration (MIC) values in the range of 225-900 µg/mL against the bacterial strains. Lupeol, lupeol acetate and α-amyrin acetate showed significant antityrosinase activity against mushroom tyrosinase enzyme with percent inhibition of 67.7%, 66.2% and 62.2%, respectively.

Keywords: antibacterial, antityrosinase, chemical constituents, Ficus platyphylla

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Authors: Xueqing Ivy Chen, Christo De Coning

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It is clear from practice that a gap exists between Result-Based Monitoring and Evaluation (RBME) as a discipline, and Knowledge Management (KM) on the other hand. Whereas various government departments have institutionalised these functions, KM and M&E has functioned in isolation from each other in a practical sense in the public sector. It’s therefore necessary to explore the relationship between KM and M&E and the necessity for integration, so that a convergence of these disciplines can be established. An integration of KM and M&E will lead to integration and improvement of evidence-based information and policy decision-making. M&E and KM process models are available but the complementarity between specific process steps of these process models are not exploited. A need exists to clarify the relationships between these functions in order to ensure evidence based information and policy decision-making. This paper will depart from the well-known policy process models, such as the generic model and consider recent on the interface between policy, M&E and KM.

Keywords: result-based monitoring and evaluation, RBME, knowledge management, KM, evident based decision making, public policy, information systems, institutional arrangement

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Authors: Rajendra N. Ghosh, Paramjeet Singh, Niranjan Khandelwal, Sameer Vyas, Pratibha Singhi, Naveen Sankhyan

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Background: Tuberculoma and neurocysticercosis (NCC) are two most common intracranial infections in developing country. They often simulate on neuroimaging and in absence of typical imaging features cause significant diagnostic dilemmas. Differentiation is extremely important to avoid empirical exposure to antitubercular medications or nonspecific treatment causing disease progression. Purpose: Better characterization and differentiation of CNS tuberculoma and NCC by using morphological and multiple advanced functional MRI. Material and Methods: Total fifty untreated patients (20 tuberculoma and 30 NCC) were evaluated by using conventional and advanced sequences like CISS, SWI, DWI, DTI, Magnetization transfer (MT), T2Relaxometry (T2R), Perfusion and Spectroscopy. rCBV,ADC,FA,T2R,MTR values and metabolite ratios were calculated from lesion and normal parenchyma. Diagnosis was confirmed by typical biochemical, histopathological and imaging features. Results: CISS was most useful sequence for scolex detection (90% on CISS vs 73% on routine sequences). SWI showed higher scolex detection ability. Mean values of ADC, FA,T2R from core and rCBV from wall of lesion were significantly different in tuberculoma and NCC (P < 0.05). Mean values of rCBV, ADC, T2R and FA for tuberculoma and NCC were (3.36 vs1.3), (1.09x10⁻³vs 1.4x10⁻³), (0.13 x10⁻³ vs 0.09 x10⁻³) and (88.65 ms vs 272.3 ms) respectively. Tuberculomas showed high lipid peak, more choline and lower creatinine with Ch/Cr ratio > 1. T2R value was most significant parameter for differentiation. Cut off values for each significant parameters have proposed. Conclusion: Quantitative MRI in combination with conventional sequences can better characterize and differentiate similar appearing tuberculoma and NCC and may be incorporated in routine protocol which may avoid brain biopsy and empirical therapy.

Keywords: advanced functional MRI, differentiation, neurcysticercosis, tuberculoma

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Authors: Rohita Gupta, G. S. Brah, R. Verma, C. S. Mukhopadhayay

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Although chicken strains show differences in susceptibility to a number of diseases, the underlying immunological basis is yet to be elucidated. In the present study, heterophils were subjected to LPS stimulation and total RNA extraction, further differential gene expression was studied in broiler, layer and indigenous Aseel strain by Real Time RT-PCR at different time periods before and after induction. The expression of the 14 AvBDs and chTLR 1, 2, 3, 4, 5, 7, 15 and 21 was detectable in heterophils. The expression level of most of the AvBDs significantly increased (P<0.05) 3 hours post in vitro lipopolysaccharide challenge. Higher expression level and stronger activation of most AvBDs, NFkB-1 and IRF-3 in heterophils was observed with the stimulation of LPS in layer compared to broiler, and in Aseel compared to both layer and broiler. This investigation will allow more refined interpretation of immuno-genetic basis of the variable disease resistance/susceptibility in divergent stock of chicken including indigenous breed. Moreover, this study will be helpful in formulation of strategy for isolation of antimicrobial peptides from heterophils.

Keywords: differential expression, heterophils, cytokines, defensin, TLR

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Authors: Funmilola O. Omoya, Joseph O. Obameso, Titus A. Olukibiti

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This study was carried out to reveal the bacterial composition of aerosol in the studied abattoirs. Bacteria isolated were characterized according to microbiological standards. Factors such as temperature and distance were considered as variable in this study. The isolation was carried out at different temperatures such as 27oC, 31oC and 29oC and at various distances of 100meters and 200meters away from the slaughter sites. Result obtained showed that strains of Staphylococcus aureus, Escherichia coli, Bacillus subtilis, Lactobacillus alimentarius and Micrococcus sp. were identified. The total viable counts showed that more microorganisms were present in the morning while the least viable count of 388 cfu was recorded in the evening period of this study. This study also showed that more microbial loads were recorded the further the distance is to the slaughter site. Conclusively, the array of bacteria isolated suggests that abattoir sites may be a potential source of pathogenic organisms to commuters if located within residential environment.

Keywords: abattoir, aerosol, bacterial composition, environment

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Authors: Areej Salaymeh, Loren Schwiebert, Stephen Remias, Jonathan Waddell

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Extracting information from new data sources has emerged as a crucial task in many traffic planning processes, such as identifying traffic patterns, route planning, traffic forecasting, and locating infrastructure improvements. Given the advanced technologies used to collect Global Positioning System (GPS) data from dedicated GPS devices, GPS equipped phones, and navigation tools, intelligent data analysis methodologies are necessary to mine this raw data. In this research, an automatic detection framework is proposed to help identify and classify the locations of stopped GPS waypoints into two main categories: signalized intersections or highway congestion. The Delaunay triangulation is used to perform this assessment in the clustering phase. While most of the existing clustering algorithms need assumptions about the data distribution, the effectiveness of the Delaunay triangulation relies on triangulating geographical data points without such assumptions. Our proposed method starts by cleaning noise from the data and normalizing it. Next, the framework will identify stoppage points by calculating the traveled distance. The last step is to use clustering to form groups of waypoints for signalized traffic and highway congestion. Next, a binary classifier was applied to find distinguish highway congestion from signalized stop points. The binary classifier uses the length of the cluster to find congestion. The proposed framework shows high accuracy for identifying the stop positions and congestion points in around 99.2% of trials. We show that it is possible, using limited GPS data, to distinguish with high accuracy.

Keywords: Delaunay triangulation, clustering, intelligent transportation systems, GPS data

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Guillermo E. Quintero, Edwin G. Perez, Oriel Sanchez, Christian Espinosa-Bustos, Denis Fuentealba, Margarita E. Aliaga

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Bisulfite ion (HSO3-) has been used as a preservative in food, drinks, and medication. However, it is well-known that HSO3- can cause health problems like asthma and allergic reactions in people. Due to the above, the development of analytical methods for detecting this ion has gained great interest. In line with the above, the current use of colorimetric and/or fluorescent probes as a detection technique has acquired great relevance due to their high sensitivity and accuracy. In this context, 2-quinolinone derivatives have been found to possess promising activity as antiviral agents, sensitizers in solar cells, antifungals, antioxidants, and sensors. In particular, 7-(diethylamino)-2-quinolinone derivatives have attracted attention in recent years since their suitable photophysical properties become promising fluorescent probes. In Addition, there is evidence that photophysical properties and reactivity can be affected by the study medium, such as micellar media. Based on the above background, 7-(diethylamino)-2-quinolinone derivatives based chalcone will be able to be incorporated into a cationic micellar environment (Cetyltrimethylammonium bromide, CTAB). Furthermore, the supramolecular control induced by the micellar environment will increase the reactivity of these derivatives towards nucleophilic analytes such as HSO3- (Michael-type addition reaction), leading to the generation of new colorimetric and/or fluorescent probes. In the present study, two derivatives of 7-(diethylamino)-2-quinolinone based chalcone DQD1-2 were synthesized according to the method reported by the literature. These derivatives were structurally characterized by 1H, 13C NMR, and HRMS-ESI. In addition, UV-VIS and fluorescence studies determined absorption bands near 450 nm, emission bands near 600 nm, fluorescence quantum yields near 0.01, and fluorescence lifetimes of 5 ps. In line with the foregoing, these photophysical properties aforementioned were improved in the presence of a cationic micellar medium using CTAB thanks to the formation of adducts presenting association constants of the order of 2,5x105 M-1, increasing the quantum yields to 0.12 and the fluorescence lifetimes corresponding to two lifetimes near to 120 and 400 ps for DQD1 and DQD2. Besides, thanks to the presence of the micellar medium, the reactivity of these derivatives with nucleophilic analytes, such as HSO3-, was increased. This was achieved through kinetic studies, which demonstrated an increase in the bimolecular rate constants in the presence of a micellar medium. Finally, probe DQD1 was chosen as the best sensor since it was assessed to detect HSO3- with excellent results.

Keywords: bisulfite detection, cationic micelle, colorimetric probes, quinolinone derivatives

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Authors: P. Selva, B. Lorraina, J. Alexis, A. Seror, A. Longuet, C. Mary, F. Denard

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Over the past four decades, the fatigue behavior of nickel-based alloys has been widely studied. However, in recent years, significant advances in the fabrication process leading to grain size reduction have been made in order to improve fatigue properties of aircraft turbine discs. Indeed, a change in particle size affects the initiation mode of fatigue cracks as well as the fatigue life of the material. The present study aims to investigate the fatigue behavior of a newly developed nickel-based superalloy under biaxial-planar loading. Low Cycle Fatigue (LCF) tests are performed at different stress ratios so as to study the influence of the multiaxial stress state on the fatigue life of the material. Full-field displacement and strain measurements as well as crack initiation detection are obtained using Digital Image Correlation (DIC) techniques. The aim of this presentation is first to provide an in-depth description of both the experimental set-up and protocol: the multiaxial testing machine, the specific design of the cruciform specimen and performances of the DIC code are introduced. Second, results for sixteen specimens related to different load ratios are presented. Crack detection, strain amplitude and number of cycles to crack initiation vs. triaxial stress ratio for each loading case are given. Third, from fractographic investigations by scanning electron microscopy it is found that the mechanism of fatigue crack initiation does not depend on the triaxial stress ratio and that most fatigue cracks initiate from subsurface carbides.

Keywords: cruciform specimen, multiaxial fatigue, nickel-based superalloy

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Authors: Sapna Bhargav

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Contemporary fiction is an intricate exercise where novelist acquires the role of a philosopher, a sociologist and a psychologist. The dilemma of fragmented self that a man experiences, is a crucial subject of contemporary fiction. Paul Auster's fiction is exemplary of the merger of Existentialism and Postmodernism, and while both of these movements insist on isolation of the self from all aspects of social affiliation, Auster's unique blend of these concepts presents man in a state which is not just alienated, but stranded in a desolate abyss, rendering even the release of death as questionable. The conundrums of the self is a compulsory consequence of the existentialist alienation that postmodern man is subjected to, and is further accentuated by the fact that existentialist freedom dictates that not only are one's actions not dictated by any form of external entity, but also the onus of one's destiny lies on an individual's own deeds. This paper will analyse Auster's The Brooklyn Follies from an Existentialist perspective, and will attempt to trace the alienation and identity conflicts of the Auster’s characters along with some of the common Austerian themes. An emphasis will be laid on the characters’ endeavour to reconstruct their lost self.

Keywords: alienation, existentialism, identity, postmodernism, self

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Authors: M. Magrini, D. Moroni, G. Palazzese, G. Pieri, D. Azzarelli, A. Spada, L. Fanucci, O. Salvetti

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Railway crossings are complex entities whose optimal management cannot be addressed unless with the help of an intelligent transportation system integrating information both on train and vehicular flows. In this paper, we propose an integrated system named SIMPLE (Railway Safety and Infrastructure for Mobility applied at level crossings) that, while providing unparalleled safety in railway level crossings, collects data on rail and road traffic and provides value-added services to citizens and commuters. Such services include for example alerts, via variable message signs to drivers and suggestions for alternative routes, towards a more sustainable, eco-friendly and efficient urban mobility. To achieve these goals, SIMPLE is organized as a System of Systems (SoS), with a modular architecture whose components range from specially-designed radar sensors for obstacle detection to smart ETSI M2M-compliant camera networks for urban traffic monitoring. Computational unit for performing forecast according to adaptive models of train and vehicular traffic are also included. The proposed system has been tested and validated during an extensive trial held in the mid-sized Italian town of Montecatini, a paradigmatic case where the rail network is inextricably linked with the fabric of the city. Results of the tests are reported and discussed.

Keywords: Intelligent Transportation Systems (ITS), railway, railroad crossing, smart camera networks, radar obstacle detection, real-time traffic optimization, IoT, ETSI M2M, transport safety

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Authors: Mostafa Feiz, Hossein Hadizadeh, Mohammad Safari

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The Chalpo copper area is located in northeastern Iran, which is part of the structural zone of central Iran and the back-arc basin of Sabzevar. This sedimentary basin accumulated in destructive-Oligomiocene sediments is named the Nasr-Chalpo-Sangerd (NCS) basin. The sedimentary layers in this basin originated mainly from Upper Cretaceous ophiolitic rocks and intermediate to mafic-post ophiolitic volcanic rocks, deposited as a nonconformity. The mineralized sandstone layers in the Chalpo area include leached zones (with a thickness of 5 to 8 meters) and mineralized lenses with a thickness of 0.5 to 0.7 meters. Ore minerals include primary sulfide minerals, such as chalcocite, chalcopyrite, and pyrite, as well as secondary minerals, such as covellite, digenite, malachite, and azurite, formed in three stages that comprise primary, simultaneously, and supergene stage. The best agents that control the mineralization in this area include the permeability of host rocks, the presence of fault zones as the conduits for copper oxide solutions, and significant amounts of plant fossils, which create a reducing environment for the deposition of mineralized layers. Statistical studies on copper layers indicate that Ag, Cd, Mo, and S have the maximum positive correlation with Cu, whereas TiO₂, Fe₂O₃, Al₂O₃, Sc, Tm, Sn, and the REEs have a negative correlation. The calculations of mass changes on copper-bearing layers and primary sandstone layers indicate that Pb, As, Cd, Te, and Mo are enriched in the mineralized zones, whereas SiO₂, TiO₂, Fe₂O₃, V, Sr, and Ba are depleted. The combination of geological, stratigraphic, and geochemical studies suggests that the origin of copper may have been the underlying red strata that contained hornblende, plagioclase, biotite, alkaline feldspar, and labile minerals. Dehydration and hydrolysis of these minerals during the diagenetic process caused the leaching of copper and associated elements by circling fluids, which formed an oxidant-hydrothermal solution. Copper and silver in this oxidant solution might have moved upwards through the basin-fault zones and deposited in the reducing environments in the sandstone layers that have had abundant organic matters. Copper in these solutions probably was carried by chloride complexes. The collision of oxidant and reduced solutions caused the deposition of Cu and Ag, whereas some stable elements in oxidant environments (e.g., Fe₂O₃, TiO₂, SiO₂, REEs) become unstable in the reduced condition. Therefore, the copper-bearing sandstones in the study area are depleted from these elements resulting from the leaching process. The results indicate that during the mineralization stage, LREEs and MREEs were depleted, but Cu, Ag, and S were enriched. Based on field evidence, it seems that the circulation of connate fluids in the reb-bed strata, produced by diagenetic processes, encountered to reduced facies, which formed earlier by abundant fossil-plant debris in the sandstones, is the best model for precipitating sulfide-copper minerals.

Keywords: Chalpo, oligo-miocene red beds, sandstone-hosted copper mineralization, mass change, LREEs, MREEs

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Authors: Nicole A. Alford

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The study of online graduate education started just 30 years ago, with the first online graduate program in the 1990s. Institutions are looking for ways to increase retention and support the needs of students with the rapid expansion of online higher education due to the global pandemic. Online education provides access and opportunities to those who otherwise would be unable to pursue an advanced degree for logistical reasons. Thus, the objective of the critical literature review is to survey current research of student experiences given the expanding role of online doctoral programs. The guiding research questions are: What are the personal, professional, and student life practices of graduate students who enrolled in a fully online university doctoral program or course? and How do graduate students who enrolled in a fully online doctoral program or course describe the factors that contributed to their continued study? The systematic literature review was conducted employing a variety of databases to locate articles using key Boolean terms and synonyms within three categories of the e-learning, doctoral education, and student perspectives. Inclusion criteria for the literature review consisted of empirical peer-reviewed studies with original data sources that focused on doctoral programs and courses within a fully online environment and centered around student experiences. A total of 16 articles were selected based on the inclusion criteria and systemically analyzed through coding using the Boote and Beile criteria. Major findings suggest that doctoral students face stressors related to social and emotional wellbeing in the online environment. A lack of social connection, isolation, and burnout were the main challenges experienced by students. Students found support from their colleagues, advisors, and faculty to persist. Communities and cohorts of online doctoral students were found to guard against these challenges. Moreover, in the methods section of the articles, there was a lack of specificity related to student demographics, general student information, and insufficient detail about the online doctoral program. Additionally, descriptions regarding the experiences of cohorts and communities in the online environment were vague and not easily replicable with the given details. This literature review reveals that doctoral students face social and emotional challenges related to isolation and the rigor of the academic process and lean on others for support to continue in their studies. Given the lack of current knowledge about online doctoral students, it proves to be a challenge to identify effective practices and create high-retention doctoral programs in online environments. The paucity of information combined with the dramatic transition to e-learning due to the global pandemic can provide a perfect storm for attrition in these programs. Several higher education institutions have transitioned graduate studies online, thus providing an opportunity for further exploration. Given the new necessity of online learning, this work provides insight into examining current practices in online doctoral programs that have moved to this modality during the pandemic. The significance of the literature review provides a springboard for research into online doctoral programs as the solution to continue advanced education amongst a global pandemic.

Keywords: e-learning, experiences, higher education, literature review

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Authors: Muhammad Tariq, Muhammad Waseem, Muhammad Hidayat Rasool

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Isolation and characterization of chromium tolerant Staphylococcus aureus from industrial wastewater and their potential use to bioremediate environmental chromium. Objectives: Chromium with its great economic importance in industrial use is major metal pollutant of the environment. Chromium are used in different industries for various applications such as textile, dyeing and pigmentation, wood preservation, manufacturing pulp and paper, chrome plating, steel and tanning. The release of untreated chromium in industrial effluents causes serious threat to environment and human health, therefore, the current study designed to isolate chromium tolerant Staphylococcus aureus for removal of chromium prior to their final discharge into the environment due to its cost effective and beneficial advantage over physical and chemical methods. Methods: Wastewater samples were collected from discharge point of different industries. Heavy metal analysis by atomic absorption spectrophotometer and microbiological analysis such as total viable count, total coliform, fecal coliform and Escherichia coli were conducted. Staphylococcus aureus was identified through gram’s staining, biomeriux vitek 2 microbial identification system and 16S rRNA gene amplification by polymerase chain reaction. Optimum growth conditions with respect to temperature, pH, salt concentrations and effect of chromium on the growth of bacteria, resistance to other heavy metal ions, minimum inhibitory concentration and chromium uptake ability of Staphylococcus aureus strain K1 was determined by spectrophotometer. Antibiotic sensitivity pattern was also determined by disc diffusion method. Furthermore, chromium uptake ability was confirmed by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope equipped with Oxford Energy Dipersive X-ray (EDX) micro analysis system. Results: The results presented that optimum temperature was 35ᵒC, pH was 8.0 and salt concentration was 0.5% for growth of Staphylococcus aureus K1. The maximum uptake ability of chromium by bacteria was 20mM than other heavy metal ions. The antibiotic sensitivity pattern revealed that Staphylococcus aureus was vancomycin and methicillin sensitive. Non hemolytic activity on blood agar and negative coagulase reaction showed that it was non-pathogenic. Furthermore, the growth of bacteria decreases in the presence of chromium and maximum chromium uptake by bacteria observed at optimum growth conditions. Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM) and Energy dispersive X-ray (EDX) analysis confirmed the presence of chromium uptake by Staphylococcus aureus K1. Conclusion: The study revealed that Staphylococcus aureus K1 have the potential to bio-remediate chromium toxicity from wastewater. Gradually, this biological treatment becomes more important due to its advantage over physical and chemical methods to protect environment and human health.

Keywords: wastewater, staphylococcus, chromium, bioremediation

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Authors: Patricia B. Cruz, Catrina Jean G. Valenzuela, Analyn N. Yumang

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Nearly a hundred per million of the Filipino population is diagnosed with Chronic Kidney Disease (CKD). The early stage of CKD has no symptoms and can only be discovered once the patient undergoes urinalysis. Over the years, different methods were discovered and used for the quantification of the urinary albumin such as the immunochemical assays where most of these methods require large machinery that has a high cost in maintenance and resources, and a dipstick test which is yet to be proven and is still debated as a reliable method in detecting early stages of microalbuminuria. This research study involves the use of the liquid chromatography concept in microfluidic instruments with biosensor as a means of separation and detection respectively, and linear regression to quantify human urinary albumin. The researchers’ main objective was to create a miniature system that quantifies and detect patients’ urinary albumin while reducing the amount of volume used per five test samples. For this study, 30 urine samples of unknown albumin concentrations were tested using VITROS Analyzer and the microfluidic system for comparison. Based on the data shared by both methods, the actual vs. predicted regression were able to create a positive linear relationship with an R² of 0.9995 and a linear equation of y = 1.09x + 0.07, indicating that the predicted values and actual values are approximately equal. Furthermore, the microfluidic instrument uses 75% less in total volume – sample and reagents combined, compared to the VITROS Analyzer per five test samples.

Keywords: Chronic Kidney Disease, Linear Regression, Microfluidics, Urinary Albumin

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Authors: Supannika Klangphukhiew, Roongnapa Srichana, Rina Patramanon

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Cortisol has been used as a well-known commercial stress biomarker. A homeostasis response to psychological stress is indicated by an increased level of cortisol produced in hypothalamus-pituitary-adrenal (HPA) axis. Chronic psychological stress contributing to the high level of cortisol relates to several health problems. In this study, the cortisol biosensor was fabricated that mimicked the natural receptors. The artificial antibodies were prepared using molecular imprinted polymer technique that can imitate the performance of natural anti-cortisol antibody with high stability. Cortisol-molecular imprinted polymer (cortisol-MIP) was obtained using the multi-step swelling and polymerization protocol with cortisol as a target molecule combining methacrylic acid:acrylamide (2:1) with bisacryloyl-1,2-dihydroxy-1,2-ethylenediamine and ethylenedioxy-N-methylamphetamine as cross-linkers. Cortisol-MIP was integrated to the sensor. It was coated on the disposable screen-printed carbon electrode (SPCE) for portable electrochemical analysis. The physical properties of Cortisol-MIP were characterized by means of electron microscope techniques. The binding characteristics were evaluated via covalent patterns changing in FTIR spectra which were related to voltammetry response. The performance of cortisol-MIP modified SPCE was investigated in terms of detection range, high selectivity with a detection limit of 1.28 ng/ml. The disposable cortisol biosensor represented an application of MIP technique to recognize steroids according to their structures with feasibility and cost-effectiveness that can be developed to use in point-of-care.

Keywords: stress biomarker, cortisol, molecular imprinted polymer, screen-printed carbon electrode

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Authors: Yagahira E. Castro-Sesquen, Robert H. Gilman, Carolina Mejia, Daniel E. Clark, Jeong Choi, Melissa J. Reimer-Mcatee, Rocio Castro, Jorge Flores, Edward Valencia-Ayala, Faustino Torrico, Ricardo Castillo-Neyra, Lance Liotta, Caryn Bern, Alessandra Luchini

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Early diagnosis of reactivation of Chagas disease in HIV patients could be lifesaving; however, in Latin American the diagnosis is performed by detection of parasitemia by microscopy which lacks sensitivity. To evaluate if levels of T. cruzi antigens in urine determined by Chunap (Chagas urine nanoparticle test) are correlated with parasitemia levels in T. cruzi/HIV co-infected patients. T. cruzi antigens in urine of HIV patients (N=55: 31 T. cruzi infected and 24 T. cruzi serology negative) were concentrated using hydrogel particles and quantified by Western Blot and a calibration curve. The percentage of Chagas positive patients determined by Chunap compared to blood microscopy, qPCR, and ELISA was 100% (6/6), 95% (18/19) and 74% (23/31), respectively. Chunap specificity was 91.7%. Linear regression analysis demonstrated a direct relationship between parasitemia levels (determined by qPCR) and urine T. cruzi antigen concentrations (p<0.001). A cut-off of > 105 pg was chosen to determine patients with reactivation of Chagas disease (6/6). Urine antigen concentration was significantly higher among patients with CD4+ lymphocyte counts below 200/mL (p=0.045). Chunap shows potential for early detection of reactivation and with appropriate adaptation can be used for monitoring Chagas disease status in T. cruzi/HIV co-infected patients.

Keywords: antigenuria, Chagas disease, Chunap, nanoparticles, parasitemia, poly N-isopropylacrylamide (NIPAm)/trypan blue particles (polyNIPAm/TB), reactivation of Chagas disease.

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Authors: H. Boulahyaoui, S. Alaoui Amine, C. Loutfi, H. El Annaz, N. Touil, El M. El Fahim, S. Mrani

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Three Moroccan children fully vaccinated with Rotarix™ have been hospitalized for Rotavirus Gastroenteritis (RVGE) in the pediatric division of the Farabi Hospital, Oujda. Rotavirus G/P genotypes could not be typed because of their delayed crossing threshold (Ct) resolute with a group A rotavirus (RVA) real time RT-PCR. These strains were adapted to cell culture. All viruses replicated and caused extensive cytopathic effects after four or five passages in MA104 cell lines. Significant improvements have been obtained in the amount of viral particles. Each virus multiplied to a high titer (7.5 TCID50/ml). VP7 and VP4 partial gene sequencing revealed distinct genotypes compared to the Rotarix(®) vaccine strain. Two strains were of G2P[4] genotype whereas the third was G9P[8] genotype. Virus isolation while labor intensive, is recommended as a second test, especially when higher sensitivity for conventional RVA genotyping RT-PCR is needed. VP7 antigenic similarities between these strains and Rotarix were determined.

Keywords: esacpe-vaccine, Morocco, Rotarix, G2P[4], G9P[8]

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