Search results for: fault detection and classification

Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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Authors: Jaturong Som-ard

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The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings

Procedia PDF Downloads 192

Authors: Christopher B. Obida, George A. Blackburn, James D. Whyatt, Kirk T. Semple

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In many regions of the world, especially in developing countries, river network data are outdated or completely absent, yet such information is critical for supporting important functions such as flood mitigation efforts, land use and transportation planning, and the management of water resources. In this study, a method was developed for delineating river networks using Sentinel 1 imagery. Unsupervised classification was applied to multi-temporal Sentinel 1 data to discriminate water bodies from other land covers then the outputs were combined to generate a single persistent water bodies product. A thinning algorithm was then used to delineate river centre lines, which were converted into vector features and built into a topologically structured geometric network. The complex river system of the Niger Delta was used to compare the performance of the Sentinel-based method against alternative freely available water body products from United States Geological Survey, European Space Agency and OpenStreetMap and a river network derived from a Shuttle Rader Topography Mission Digital Elevation Model. From both raster-based and vector-based accuracy assessments, it was found that the Sentinel-based river network products were superior to the comparator data sets by a substantial margin. The geometric river network that was constructed permitted a flow routing analysis which is important for a variety of environmental management and planning applications. The extracted network will potentially be applied for modelling dispersion of hydrocarbon pollutants in Ogoniland, a part of the Niger Delta. The approach developed in this study holds considerable potential for generating up to date, detailed river network data for the many countries where such data are deficient.

Keywords: Sentinel 1, image processing, river delineation, large scale mapping, data comparison, geometric network

Procedia PDF Downloads 139

Authors: Upasana Bhumbla

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Background: Hepatitis C virus is a major cause of chronic hepatitis, which can further lead to cirrhosis of the liver and hepatocellular carcinoma. Worldwide the burden of Hepatitis C infection has become a serious threat to the human race. Hepatitis C virus (HCV) has population-specific genotypes and provides valuable epidemiological and therapeutic information. Genotyping and assessment of viral load in HCV patients are important for planning the therapeutic strategies. The aim of the study is to study the changing trends of prevalence and genotypic distribution of hepatitis C virus in a tertiary care hospital in Western India. Methods: It is a retrospective study; blood samples were collected and tested for anti HCV antibodies by ELISA in Dept. of Microbiology. In seropositive Hepatitis C patients, quantification of HCV-RNA was done by real-time PCR and in HCV-RNA positive samples, genotyping was conducted. Results: A total of 114 patients who were seropositive for Anti HCV were recruited in the study, out of which 79 (69.29%) were HCV-RNA positive. Out of these positive samples, 54 were further subjected to genotype determination using real-time PCR. Genotype was not detected in 24 samples due to low viral load; 30 samples were positive for genotype. Conclusion: Knowledge of genotype is crucial for the management of HCV infection and prediction of prognosis. Patients infected with HCV genotype 1 and 4 will have to receive Interferon and Ribavirin for 48 weeks. Patients with these genotypes show a poor sustained viral response when tested 24 weeks after completion of therapy. On the contrary, patients infected with HCV genotype 2 and 3 are reported to have a better response to therapy.

Keywords: hepatocellular, genotype, ribavarin, seropositive

Procedia PDF Downloads 127

Authors: Shalini Rankawat, Mansi Rankawat, Rahul Dubey, Mazad Zaveri

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Physiological signals such as electrocardiogram (ECG) and arterial blood pressure (ABP) in the intensive care unit (ICU) are often seriously corrupted by noise, artifacts, and missing data, which lead to errors in the estimation of heart rate (HR) and incidences of false alarm from ICU monitors. Clinical support in ICU requires most reliable heart rate estimation. Cardiac activity, because of its relatively high electrical energy, may introduce artifacts in Electroencephalogram (EEG), Electrooculogram (EOG), and Electromyogram (EMG) recordings. This paper presents a robust heart rate estimation method by detection of R-peaks of ECG artifacts in EEG, EMG & EOG signals, using energy-based function and a novel Signal Quality Index (SQI) assessment technique. SQIs of physiological signals (EEG, EMG, & EOG) were obtained by correlation of nonlinear energy operator (teager energy) of these signals with either ECG or ABP signal. HR is estimated from ECG, ABP, EEG, EMG, and EOG signals from separate Kalman filter based upon individual SQIs. Data fusion of each HR estimate was then performed by weighing each estimate by the Kalman filters’ SQI modified innovations. The fused signal HR estimate is more accurate and robust than any of the individual HR estimate. This method was evaluated on MIMIC II data base of PhysioNet from bedside monitors of ICU patients. The method provides an accurate HR estimate even in the presence of noise and artifacts.

Keywords: ECG, ABP, EEG, EMG, EOG, ECG artifacts, Teager-Kaiser energy, heart rate, signal quality index, Kalman filter, data fusion

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Authors: Saoussen Dhib, Chris M. Mannaerts, Zoubeida Bargaoui, Ben H. P. Maathuis, Petra Budde

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In this study, a new method to delineate rain areas in northern Tunisia is presented. The proposed approach is based on the blending of the geostationary Meteosat Second Generation (MSG) infrared channel (IR) with the low-earth orbiting passive Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). To blend this two products, we need to apply two main steps. Firstly, we have to identify the rainy pixels. This step is achieved based on a classification using MSG channel IR 10.8 and the water vapor WV 0.62, applying a threshold on the temperature difference of less than 11 Kelvin which is an approximation of the clouds that have a high likelihood of precipitation. The second step consists on fitting the relation between IR cloud top temperature with the TMI rain rates. The correlation coefficient of these two variables has a negative tendency, meaning that with decreasing temperature there is an increase in rainfall intensity. The fitting equation will be applied for the whole day of MSG 15 minutes interval images which will be summed. To validate this combined product, daily extreme rainfall events occurred during the period 2007-2009 were selected, using a threshold criterion for large rainfall depth (> 50 mm/day) occurring at least at one rainfall station. Inverse distance interpolation method was applied to generate rainfall maps for the drier summer season (from May to October) and the wet winter season (from November to April). The evaluation results of the estimated rainfall combining MSG and TMI was very encouraging where all the events were detected rainy and the correlation coefficients were much better than previous evaluated products over the study area such as MSGMPE and PERSIANN products. The combined product showed a better performance during wet season. We notice also an overestimation of the maximal estimated rain for many events.

Keywords: combination, extreme, rainfall, TMI-MSG, Tunisia

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Authors: Chiang-Lead Woo

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In reply to serious environmental problems, the Taiwan government quickly adjusted some articles to suit the needs of environmental protection recently, such as the amendment to article 190-1 of the Taiwan Criminal Code. The transfer of legislation comes as an improvement which canceled the limitation of ‘endangering public safety’. At the same time, the article 190-1 goes from accumulative concrete offense to abstract crime of danger. Thus, the public looks forward to whether environmental crime following the imposition of fines or penalties works efficiently in anti-pollution by the deterrent effects. However, according to the addition to article 38-2 of the Taiwan Criminal Code, the confiscation system seems controversial legislation to restrain ill-gotten gains. Most prior studies focused on comparisons with the Administrative Penalty Law and the Criminal Code in environmental issue in Taiwan; recently, more and more studies emphasize calculations on ill-gotten gains. Hence, this paper try to examine the deterrent effect in environmental crime by economic analysis of law and environmental economics perspective. This analysis shows that only if there is an extremely high probability (equal to 100 percent) of an environmental crime case being prosecuted criminally by Taiwan Environmental Protection Agency, the deterrent effects will work. Therefore, this paper suggests deliberating the confiscation system from supplementing the System of Environmental and Economic Accounting, reasonable deterrent fines, input management, real-time system for detection of pollution, and whistleblower system, environmental education, and modernization of law.

Keywords: confiscation, ecosystem services, environmental crime, ill-gotten gains, the deterrent effect, the system of environmental and economic accounting

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Authors: Azizollah Khodakaram- Tafti, Ali Mohammadi, Ghasem Farjanikish

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Bovine viral diarrhea virus (BVDV) is one of the most important viral pathogens of cattle worldwide caused by Pestivirus genus, Flaviviridae family.The aim of the present study was to comparison several diagnostic methods and determine the prevalence of BVDV infection for the first time in dairy herds of Fars province, Iran. For initial screening, a total of 400 blood samples were randomly collected from 12 industrial dairy herds and analyzed using reverse transcription (RT)-PCR on the buffy coat. In the second step, blood samples and also ear notch biopsies were collected from 100 cattle of infected farms and tested by antigen capture ELISA (ACE), RT-PCR and immunohistochemistry (IHC). The results of nested RT-PCR (outer primers 0I100/1400R and inner primers BD1/BD2) was successful in 16 out of 400 buffy coat samples (4%) as acute infection in initial screening. Also, 8 out of 100 samples (2%) were positive as persistent infection (PI) by all of the diagnostic tests similarly including RT-PCR, ACE and IHC on buffy coat, serum and skin samples, respectively. Immunoreactivity for bovine BVDV antigen as brown, coarsely to finely granular was observed within the cytoplasm of epithelial cells of epidermis and hair follicles and also subcutaneous stromal cells. These findings confirm the importance of monitoring BVDV infection in cattle of this region and suggest detection and elimination of PI calves for controlling and eradication of this disease.

Keywords: antigen capture ELISA, bovine viral diarrhea virus, immunohistochemistry, RT-PCR, cattle

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Authors: Nikhil A. Gavhane, Sachin Shah, Ishant S. Mahajan, Pawan D. Bahekar

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Introduction: Millions of people are affected with dengue fever every year, which drives up healthcare expenses in many low-income countries. Organ failure and other serious symptoms may result. Another worldwide public health problem is sickle cell anaemia, which is most prevalent in Africa, the Caribbean, and Europe. Dengue epidemics have reportedly occurred in locations with a high frequency of sickle cell disease, compounding the health problems in these areas. Aims and Objectives: This study examines dengue infection in sickle cell disease-afflicted pre-schoolers. Method:This Retrospective cohort study examined paediatric patients. Young people with sickle cell disease (SCD), dengue infection, and a control group without SCD or dengue were studied. Data on demographics, SCD consequences, medical treatments, and laboratory findings were gathered to analyse the influence of SCD on dengue severity and clinical outcomes, classified as severe or non-severe by the 2009 WHO classification. Using fever or admission symptoms, the research estimated acute illness duration. Result: Table 1 compares haemoglobin genotype-based dengue episode features in SS, SC, and controls. Table 2 shows that severe dengue cases are older, have longer admission delays, and have particular symptoms. Table 3's multivariate analysis indicates SS genotype's high connection with severe dengue, multiorgan failure, and acute pulmonary problems. Table 4 relates severe dengue to greater white blood cell counts, anaemia, liver enzymes, and reduced lactate dehydrogenase. Conclusion: This study is valuable but confined to hospitalised dengue patients with sickle cell illness. Small cohorts limit comparisons. Further study is needed since findings contradict predictions.

Keywords: dengue, chills, headache, severe myalgia, vomiting, nausea, prostration

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Authors: Ramin Zargarbashi, Hamid Rabie, Behnam Panjavi, Hooman Kamran, Seyedarad Mosalamiaghili, Zohre Erfani, Seyed Peyman Mirghaderi, Maryam Salimi

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Background: Posterior shoulder dislocation is one of the disabling complications of brachial plexus birth injury (BPBI), and various treatment options, including capsule and surrounding muscles release for open reduction, humeral derotational osteotomy, and tendon transfers, have been recommended to manage it. In the present study, we aimed to determine the clinical outcome of open reduction with soft tissue release, tendon transfer, and glenoid osteotomy inpatients with BPBI and posterior shoulder dislocation or subluxation. Methods: From 2018 to 2020, 33 patients that underwent open reduction, glenoid osteotomy, and tendon transfer were included. The glenohumeral deformity was classified according to the Waters radiographic classification. Functional assessment was performed using the Mallet grading system before and at least two years after the surgery. Results: The patients were monitored for 26.88± 5.47 months. Their average age was 27.5±14 months. Significant improvement was seen in the overall Mallet score (from 13.5 to 18.91 points) and its segments, including hand to mouth, hand to the neck, global abduction, global external rotation, abduction degree, and external rotation degree. Hand-to-back score and the presence of trumpet sign were significantly decreased in the post-operation phase (all p values<0.001). The above-mentioned variables significantly changed for both infantile and non-infantile dislocations. Conclusion: Our study demonstrated that open reduction along with glenoid osteotomy improves retroversion, and muscle strengthening with different muscle transfers is an effective technique for BPBI.

Keywords: birth injuries, nerve injury, brachial plexus birth palsy, Erb palsy, tendon transfer

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Authors: Sokkhey Phauk, Takeo Okazaki

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The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

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Authors: Phang Moon Leng

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Automated Early Warning Scores is a newly developed clinical decision tool that is used to streamline and improve the process of obtaining a patient’s vital signs so a clinical decision can be made at an earlier stage to prevent the patient from further deterioration. This technology provides immediate update on the score and clinical decision to be taken based on the outcome. This paper aims to study the use of an automated early warning score system on whether the technology has assisted the hospital in early detection and escalation of clinical condition and improve patient outcome. The hospital adopted the Modified Early Warning Scores (MEWS) Scoring System and MEWS Clinical Response into Philips IntelliVue Guardian Automated Early Warning Score equipment and studied whether the process has been leaned, whether the use of technology improved the usage & experience of the nurses, and whether the technology has improved patient care and outcome. It was found the steps required to obtain vital signs has been significantly reduced and is used more frequently to obtain patient vital signs. The number of deaths, and length of stay has significantly decreased as clinical decisions can be made and escalated more quickly with the Automated EWS. The automated early warning score equipment has helped improve work efficiency by removing the need for documenting into patient’s EMR. The technology streamlines clinical decision-making and allows faster care and intervention to be carried out and improves overall patient outcome which translates to better care for patient.

Keywords: automated early warning score, clinical quality and safety, patient safety, medical technology

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: retail stores, faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition

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Authors: Chao Ma

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In this paper, the evaluation criteria of authenticity evaluation system model are taken as the foundation so as to discuss the establishment problems about decentralization supervision system and mechanism of historical cultural town and village. The filtration of fitting towns and village's authenticity is conducted from the level, characteristic index and authentic assessment of evaluation model, thereby, supervising subject -interest related- coordinate organization can be taken as the venation in the management level, thus supervision mechanism of town and village's cultural inheritance can be combed, and the cultural inheritance management system and mechanism which is suitable to historical and cultural Chinese town and village will be provided. As the settlement with strong self-organizing characteristic, town and village don't recognize the management system as deeply as city. Therefore, it is necessary to establish town and village cultural evaluation system based on authenticity evaluation criteria. In this paper, authenticity evaluation system is established by taking this village's value evaluation criteria and protection as the cores, and the classification of participating options is beneficial to distribute local limited resources, protect hierarchically and accord with the local characters of town and village, build the evaluation system to run through the whole process of cultural inheritance, moreover, provide abundant information resources and make sure the value judgment criteria, thus supervision and management can be strengthened to effectively guard risk. By the above judgement and filtration of participating options, the management object with clear functions and supervision and coordination organization are established, thereby, the managerial logic of interest-related persons' decentralization can be clarified, evaluation system can be established, and the more targeted decentralization supervision system and mechanism of historical and cultural village will be built ultimately. Taking this method as a fundamental in cultural protection of town and village, not only can it be carried forward in the mass media, but also can cultivate the identity sense of indigenous people to come back historical and cultural villages, and resist the replacement of city culture.

Keywords: authenticity, rural culture, inheritance, supervision

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Authors: Ballari Bagchi

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The dynamism ingrained in the process of urban-rural integration is manifested in the emergence of rurban settlements, referring to areas that combine the characteristics of agricultural activities found in rural zones with those of suburban living areas and industrialised zones. The concept of rurbanisation refers to the idea of introducing urban conveniences and opportunities, to rural areas in an attempt to stem rural urban migration. In the backdrop of the worldwide problem of disharmonised urban-rural dependence and the associated problems in urban and rural areas, the present study seeks to explore the potentialities of few settlements having a blend of rural and urban characteristics in the urban field of Koch Bihar. The prime concern of the present paper is three-fold: (i) to identify the rurban centres, (ii) to analyse the spatial integration of these identified centres with the rural areas situated in the urban periphery, and (iii) to suggest the necessities to be introduced in these settlements. The methodology applied here includes rurban index, gravity model, and functional classification of rurban centres, correlation and regression analysis and cartographic representation of data collected through primary and secondary sources. The investigation has identified a number of settlements potentially viable to be termed as rurban centres which may render services to the other less equipped rural areas in all aspects of life and thereby would lessen the burden on Koch Bihar urban centre. The levels of infrastructure of these settlements should be such that it might even attract the urban population in a reverse direction. The villages belonging to the lower rung of these service settlements would require metalled road connection with these intermediate settlements in addition to their connection with the core town. That is to say, a proper policy needs to be adopted in this regard to furnish these settlements with required infrastructures for serving their own population as well as the population of other villages. As a consequence of that, the idea of a well-coordinated settlement hierarchy may emerge in future.

Keywords: Hinterland, rurban, settlement hierarchy, urban-rural integration

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Authors: D. J. Kalita

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Cancer is one of the prime causes of early death worldwide. Mutation of the gene involve in DNA repair and damage, like BRCA2 (Breast cancer gene two) genes, can be detected efficiently by PCR-RFLP to early breast cancer diagnosis and adopt the suitable method of treatment. Host Defense Peptide can be used as blueprint for the design and synthesis of novel anticancer drugs to avoid the side effect of conventional chemotherapy and chemo resistance. The change at nucleotide position 392 of a -› c in the cancer sample of dog mammary tumour at BRCA2 (exon 7) gene lead the creation of a new restriction site for SsiI restriction enzyme. This SNP may be a marker for detection of canine mammary tumour. Support vector machine (SVM) algorithm was used to design and predict the anticancer peptide from the mature functional peptide. MTT assay of MCF-7 cell line after 48 hours of post treatment showed an increase in the number of rounded cells when compared with untreated control cells. The ability of the synthesized peptide to induce apoptosis in MCF-7 cells was further investigated by staining the cells with the fluorescent dye Hoechst stain solution, which allows the evaluation of the nuclear morphology. Numerous cells with dense, pyknotic nuclei (the brighter fluorescence) were observed in treated but not in control MCF-7 cells when viewed using an inverted phase-contrast microscope. Thus, PCR-RFLP is one of the attractive approach for early diagnosis, and synthetic cationic peptide can be used for the treatment of canine mammary tumour.

Keywords: cancer, cationic peptide, host defense peptides, Breast cancer genes

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Authors: Abdelrahman Elsehsah, Abdelazim Negm, Eid Ashour, Mohamed Elsahabi

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Water resources management is a critical field that encompasses the planning, development, conservation, and allocation of water resources to meet societal needs while ensuring environmental sustainability. This paper reviews the key concepts and challenges in water resources management, emphasizing the significance of a holistic approach that integrates social, economic, and environmental factors. Traditional water management practices, characterized by supply-oriented strategies and centralized control, are increasingly inadequate in addressing contemporary challenges such as water scarcity, climate change impacts, and ecosystem degradation. Emerging technologies, particularly machine learning and remote sensing, offer innovative solutions to enhance decision-making processes in water management. Machine learning algorithms facilitate accurate water demand forecasting, quality monitoring, and leak detection, while remote sensing technologies provide vital data for assessing water availability and quality. This review highlights the need for integrated water management strategies that leverage these technologies to promote sustainable practices and foster resilience in water systems. Future research should focus on improving data quality, accessibility, and the integration of diverse datasets to optimize the benefits of these technological advancements.

Keywords: water resources management, water scarcity, climate change, machine learning, remote sensing, water quality, water governance, sustainable practices, ecosystem management

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Authors: Iván Rivet, Narges Dialami, Miguel Cervera, Michele Chiumenti

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Process parameters in Additive Manufacturing (AM) play a critical role in the mechanical performance of the final component. In order to find the input configuration that guarantees the optimal performance of the printed part, the process-performance relationship must be found. Fused Filament Fabrication (FFF) is the selected demonstrative AM technology due to its great popularity in the industrial manufacturing world. A material model that considers the different printing patterns present in a FFF part is used. A voxelized mesh is built from the manufacturing toolpaths described in the G-Code file. An Adaptive Mesh Refinement (AMR) based on the octree strategy is used in order to reduce the complexity of the mesh while maintaining its accuracy. High-fidelity and cost-efficient Finite Element (FE) simulations are performed and the influence of key process parameters in the mechanical performance of the component is analyzed. A robust optimization process based on appropriate failure criteria is developed to find the printing direction that leads to the optimal mechanical performance of the component. The Tsai-Wu failure criterion is implemented due to the orthotropy and heterogeneity constitutive nature of FFF components and because of the differences between the strengths in tension and compression. The optimization loop implements a modified version of an Anomaly Detection (AD) algorithm and uses the computed metrics to obtain the optimal printing direction. The developed methodology is verified with a case study on an industrial demonstrator.

Keywords: additive manufacturing, optimization, printing direction, mechanical performance, voxelization

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Authors: Hamsini Pulugurtha, V.S. Lakshmi Jagadmaba Paluri

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Distributed denial of service attack (DDoS) is one altogether the top-rated cyber threats presently. It runs down the victim server resources like a system of measurement and buffer size by obstructing the server to supply resources to legitimate shoppers. Throughout this text, we tend to tend to propose a mathematical model of DDoS attack; we discuss its relevancy to the choices like inter-arrival time or rate of arrival of the assault customers accessing the server. We tend to tend to further analyze the attack model in context to the exhausting system of measurement and buffer size of the victim server. The projected technique uses an associate in nursing unattended learning technique, self-organizing map, to make the clusters of identical choices. Lastly, the abstract applies mathematical correlation and so the standard likelihood distribution on the clusters and analyses their behaviors to look at a DDoS attack. These systems not exclusively interconnect very little devices exchanging personal data, but to boot essential infrastructures news standing of nuclear facilities. Although this interconnection brings many edges and blessings, it to boot creates new vulnerabilities and threats which might be conversant in mount attacks. In such sophisticated interconnected systems, the power to look at attacks as early as accomplishable is of paramount importance.

Keywords: application attack, bandwidth, buffer correlation, DDoS distribution flooding intrusion layer, normal prevention probability size

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Authors: K. H. Teng, A. Shaw, M. Ateeq, A. Al-Shamma'a, S. Wylie, S. N. Kazi, B. T. Chew

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Numerical and experimental of using novel electromagnetic wave technique to detect water hardness concentration has been presented in this paper. Simulation is powerful and efficient engineering methods which allow for a quick and accurate prediction of various engineering problems. The RF module is used in this research to predict and design electromagnetic wave propagation and resonance effect of a guided wave to detect water hardness concentration in term of frequency domain, eigenfrequency, and mode analysis. A cylindrical cavity resonator is simulated and designed in the electric field of fundamental mode (TM010). With the finite volume method, the three-dimensional governing equations were discretized. Boundary conditions for the simulation were the cavity materials like aluminum, two ports which include transmitting and receiving port, and assumption of vacuum inside the cavity. The design model was success to simulate a fundamental mode and extract S21 transmission signal within 2.1 – 2.8 GHz regions. The signal spectrum under effect of port selection technique and dielectric properties of different water concentration were studied. It is observed that the linear increment of magnitude in frequency domain when concentration increase. The numerical results were validated closely by the experimentally available data. Hence, conclusion for the available COMSOL simulation package is capable of providing acceptable data for microwave research.

Keywords: electromagnetic wave technique, frequency domain, signal spectrum, water hardness concentration

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Authors: Kefi Rahmadio, Filipus Armando Ginting, Richard Nainggolan

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This research shows the formation of the West Buru Basin and the potential utilization of this West Buru Basin as a geothermal potential. The research area is West Buru Island which is part of the West Buru Basin. The island is located in Maluku Province, with its capital city named Namlea. The island is divided into 10 districts, namely District Kepalamadan, Airbuaya District, Wapelau District, Namlea District, Waeapo District, Batabual District, Namrole District, Waesama District, Leksula District, and Ambalau District. The formation in this basin is Permian-Quarter. They start from the Formation Ghegan, Dalan Formation, Mefa Formation, Kuma Formation, Waeken Formation, Wakatin Formation, Ftau Formation and Leko Formation. These formations are composing this West Buru Basin. Determination of prospect area in the geothermal area with preliminary investigation stage through observation of manifestation, topographic shape and structure are found around prospect area. This is done because there is no data of earth that support the determination of prospect area more accurately. In Waepo area, electric power generated based on field observation and structural analysis, geothermal area of ​Waeapo was approximately 6 km², with reference to the SNI 'Classification of Geothermal Potential' (No.03-5012-1999), an area of ​​1 km² is assumed to be 12.5 MWe. The speculative potential of this area is (Q) = 6 x 12.5 MWe = 75 MWe. In the Bata Bual area, the geothermal prospect projected 4 km², the speculative potential of the Bata Bual area is worth (Q) = 4 x 12.5 MWe = 50 MWe. In Kepala Madan area, based on the estimation of manifestation area, there is a wide area of ​​prospect in Kepala Madan area about 4 km². The geothermal energy potential of the speculative level in Kepala Madan district is (Q) = 4 x 12.5 MWe = 50 MWe. These three areas are the largest geothermal potential on the island of West Buru. From the above research, it can be concluded that there is potential in West Buru Island. Further exploration is needed to find greater potential. Therefore, researchers want to explain the geothermal potential contained in the West Buru Basin, within the scope of West Buru Island. This potential can be utilized for the community of West Buru Island.

Keywords: West Buru basin, West Buru island, potential, Waepo, Bata Bual, Kepala Madan

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Authors: Tomohiro Uchida, Noriaki Satake, Toshimichi Nakaho, Akira Inoue, Hidemitsu Saito

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In this study, we assessed the bereavement risk of family caregivers of patients with cancer. In the palliative care unit of Tohoku University Hospital, we conducted a family psychoeducation session to support the family caregivers of patients with cancer. A total of 50 participants (8 males and 42 females; mean age = 62.98 years, SD = 11.10) were assessed after the session for bereavement risk using the Japanese version of the Bereavement Risk Assessment Tool (BRAT-J). According to the BRAT-J scores, eight participants were considered to be having no known risk (Level 1), seventeen had minimal risk (Level 2), twenty had a low risk (Level 3), four had a moderate risk (Level 4), and one had a high risk (Level 5). Of these participants, seven participants had completed the follow-up postal survey that assessed their psychological distress (the Kessler Psychological Distress Scale: K6) to compare the bereavement risk. According to the K6 scores, three-fourth of the individuals, who were considered to be at Level 3 on the BRAT-J, scored higher than the cutoff point (>10) for the detection of depressive disorder. On the other hand, one-third of the individuals, who were considered to be at Level 2 on the BRAT-J, scored higher than the cutoff point. Therefore, it appears that the BRAT-J can predict the likelihood of difficulties or complications in bereaved family caregivers. This research was approved by the Ethics Committee of Tohoku University Graduate School of Medicine and Tohoku University Hospital.

Keywords: palliative care, family caregivers, bereavement risk, BRAT, post-loss psychological distress

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Authors: Rose-Michelle Smith, Musandji Fuamba, Salomon Salumu

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Water is vital for life. Access to drinking water and sanitation for humans is one of the Sustainable Development Goals (specifically the sixth) approved by United Nations Member States in September 2015. There are various problems identified relating to water: insufficient fresh water, inequitable distribution of water resources, poor water management in certain places on the planet, detection of water-borne diseases due to poor water quality, and the negative impacts of climate change on water. One of the major challenges in the world is finding ways to ensure that people and the environment have enough water resources to sustain and support their existence. Thus, this research project aims to develop a tool to assess the availability, quality and needs of water in current and future situations with regard to climate change. This tool was tested using threshold values for three regions in three countries: the Metropolitan Community of Montreal (Canada), Normandie Region (France) and North Department (Haiti). The WEAP software was used to evaluate the available quantity of water resources. For water quality, two models were performed: the Canadian Council of Ministers of the Environment (CCME) and the Malaysian Water Quality Index (WQI). Preliminary results showed that the ratio of the needs could be estimated at 155, 308 and 644 m3/capita in 2023 for Normandie, Cap-Haitian and CMM, respectively. Then, the Water Quality Index (WQI) varied from one country to another. Other simulations regarding the water availability and quality are still in progress. This tool will be very useful in decision-making on projects relating to water use in the future; it will make it possible to estimate whether the available resources will be able to satisfy the needs.

Keywords: climate change, water needs, balance sheet, water quality

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Authors: Shara Toibayeva, Irbulat Utepbergenov, Lyazzat Issabekova, Aidana Bodesova

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The article discusses the importance of quality assessment as a strategic tool in business and emphasizes the significance of the effectiveness of quality management systems (QMS) for enterprises. The evaluation of these systems takes into account the specificity of quality indicators, the multilevel nature of the system, and the need for optimal selection of the number of indicators and evaluation of the system state, which is critical for making rational management decisions. Methods and models of automated enterprise quality management are proposed, including an intelligent automated quality management system integrated with the Management Information and Control System. These systems make it possible to automate the implementation and support of QMS, increasing the validity, efficiency, and effectiveness of management decisions by automating the functions performed by decision makers and personnel. The paper also emphasizes the use of recurrent neural networks to improve automated quality management. Recurrent neural networks (RNNs) are used to analyze and process sequences of data, which is particularly useful in the context of document quality assessment and non-conformance detection in quality management systems. These networks are able to account for temporal dependencies and complex relationships between different data elements, which improves the accuracy and efficiency of automated decisions. The project was supported by a grant from the Ministry of Education and Science of the Republic of Kazakhstan under the Zhas Galym project No. AR 13268939, dedicated to research and development of digital technologies to ensure consistency of QMS regulatory documents.

Keywords: automated control system, quality management, document structure, formal language

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Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: drug addiction, artificial neural networks, multilayer perceptron (MLP), decision support system

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Authors: Chee Dhang Chen, Hiroyuki Takaoka, Koon Weng Lau, Poh Ruey Tan, Ai Chdon Chin, Van Lun Low, Abdul Aziz Azidah, Mohd Sofian-Azirun

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Susceptibility status of Simulium (Simulium) nobile (Diptera: Simuliidae) adults obtained from Pahang, Malaysia was evaluated against 11 adulticides representing four major insecticide classes: organochlorines (DDT, dieldrin), organophosphates (malathion, fenitrothion), carbamates (bendiocarb, propoxur) and pyrethroids (etofenprox, deltamethrin, lambdacyhalothrin, permethrin, cyfluthrin). The adult bioassay was conducted according to WHO standard protocol to determine the insecticide susceptibility. Mortality at 24 h post treatment was used as indicator for susceptibility status. The results revealed that S. nobile obtained was susceptible to propoxur, cyfluthrin and bendiocarb with 100% mortality. S. nobile was resistant or exhibited some tolerant against lambdacyhalothrin and deltamethrin with mortality ranged ≥ 90% but < 98%. S. nobile populations in Pahang exhibited different level of resistant against 11 adulticides with mortality ranged from 60.00 ± 10.00 to 100.00 ± 0.00. In conclusion, S. nobile populations in Pahang were susceptible to propoxur, cyfluthrin and bendiocarb. The susceptibility status of S. nobile in descending order was propoxur, cyfluthrin > bendicarb > deltamethrin > lambdacyhalothrin > permethrin > etofenprox > DDT > malathion > fenitrothion > dieldrin. Regular surveys should be conducted to monitor the susceptibility status of this insect vector in order to prevent further development of resistance.

Keywords: black fly, adult bioassay, insecticide resistance, Malaysia

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Authors: Alma Ramić, Mirjana Skočibušić, Renata Odžak, Tomica Hrenar, Ines Primožič

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In an attempt to identify a new class of antimicrobial agents, the antimicrobial potential of Cinchona alkaloid derivatives was evaluated. The bark of the Cinchona trees is the source of a variety of alkaloids, among which the best known are quinine, quinidine, cinchonine and cinchonidine. They are very useful as organocatalysts in stereoselective synthesis. On the other hand, quinine is traditionally used in the treatment of malaria. Furthermore, Cinchona alkaloids possess various analgesic, anti-inflammatory and anti–arrhythmic properties as well. In this work we present the synthesis of twenty quaternary derivatives of pseudo−enantiomeric Cinchona alkaloid derivatives to evaluate their antibacterial activity. Quaternization of quinuclidine moiety was carried out with groups diverse in their size. The structures of compounds were systematically modified to obtain drug-like properties with proper physical and chemical properties and avoiding toxophore. All compounds were prepared in good yields and were characterized by standard analytical spectroscopy methods (1D and 2D NMR, IR, MS). The antibacterial activities of all compounds were evaluated against series of recent clinical isolates of antibiotic susceptible Gram-positive and resistant Gram-negative pathogens by determining their zone of inhibition and minimum inhibitory concentrations. All compounds showed good to strong broad-spectrum activity, equivalent or better in comparison with standard antibiotics used. Furthermore, seven compounds exhibited significant antibacterial efficiency against Gram-negative isolates. To visualize the results, principal component analysis was used as an additional classification tool. Cytotoxicity of compounds with different cell lines in human cell culture was determined. Based on these results, substituted quaternary Cinchona scaffold can be considered as promising new class of antimicrobials and further investigations should be performed. Supported by Croatian Science Foundation, Project No 3775 ADESIRE.

Keywords: antibacterial efficiency, cinchona alkaloids, cytotoxicity, pseudo‐enantiomers

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Authors: Rashima Mahajan, Dipali Bansal, Shweta Singh

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Real time non-invasive Brain Computer Interfaces have a significant progressive role in restoring or maintaining a quality life for medically challenged people. This manuscript provides a comprehensive review of emerging research in the field of cognitive/affective computing in context of human neural responses. The perspectives of different emotion assessment modalities like face expressions, speech, text, gestures, and human physiological responses have also been discussed. Focus has been paid to explore the ability of EEG (Electroencephalogram) signals to portray thoughts, feelings, and unspoken words. An automated workflow-based protocol to design an EEG-based real time Brain Computer Interface system for analysis and classification of human emotions elicited by external audio/visual stimuli has been proposed. The front end hardware includes a cost effective and portable Emotive EEG Neuroheadset unit, a personal computer and a set of external stimulators. Primary signal analysis and processing of real time acquired EEG shall be performed using MATLAB based advanced brain mapping toolbox EEGLab/BCILab. This shall be followed by the development of MATLAB based self-defined algorithm to capture and characterize temporal and spectral variations in EEG under emotional stimulations. The extracted hybrid feature set shall be used to classify emotional states using artificial intelligence tools like Artificial Neural Network. The final system would result in an inexpensive, portable and more intuitive Brain Computer Interface in real time scenario to control prosthetic devices by translating different brain states into operative control signals.

Keywords: brain computer interface, electroencephalogram, EEGLab, BCILab, emotive, emotions, interval features, spectral features, artificial neural network, control applications

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Authors: Kim Byung-Kon, Kim Young-Jin

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As project opportunities for the Architecture, Engineering and Construction (AEC) industry have grown more complex and larger, the utilization of BIM (Building Information Modeling) technologies for 3D design and simulation practices has been increasing significantly; the typical applications of the BIM technologies include clash detection and design alternative based on 3D planning, which have been expanded over to the technology of construction management in the AEC industry for virtual design and construction. As for now, commercial BIM software has been operated under a single-user environment, which is why initial costs for its introduction are very high. Cloud computing, one of the most promising next-generation Internet technologies, enables simple Internet devices to use services and resources provided with BIM software. Recently in Korea, studies to link between BIM and cloud computing technologies have been directed toward saving costs to build BIM-related infrastructure, and providing various BIM services for small- and medium-sized enterprises (SMEs). This study addressed how to develop the usage metering functions of BIM software under cloud computing architecture in order to archive and use BIM data and create an optimal revenue structure so that the BIM services may grow spontaneously, considering a demand for cloud resources. To this end, the author surveyed relevant cases, and then analyzed needs and requirements from AEC industry. Based on the results & findings of the foregoing survey & analysis, the author proposed herein how to optimally develop the usage metering functions of cloud BIM software.

Keywords: construction IT, BIM (Building Information Modeling), cloud computing, BIM-based cloud computing, 3D design, cloud BIM

Procedia PDF Downloads 506