Search results for: Klippel–Feil anomaly

Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

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The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: environmental internet of things, EIoT, machine learning, anomaly detection, environment monitoring

Procedia PDF Downloads 121

Authors: Ahmad Lutfi, Nikolas Dhega

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The Malala deposit in northwest Sulawesi is the only known porphyry molybdenum and the only source for rhenium, occurrence in Indonesia. The neural network method produces results that correspond very closely to those of the knowledge-based fuzzy logic method and weights of evidence method. This method required data of solid geology, regional faults, airborne magnetic, gamma-ray survey data and GIS data. This interpretation of the network output fits with the intuitive notion that a prospective area has characteristics that closely resemble areas known to contain mineral deposits. Contrasts with the weights of evidence and fuzzy logic methods, where, for a given grid location, each input-parameter value automatically results in an increase in the prospective estimated. Malala District indicated molybdenum anomalies in stream sediments from in excess of 15 km2 were obtained, including the Takudan Fault as most prominent structure with striking 40̊ to 60̊ over a distance of about 30 km and in most places weakly at anomaly B, developed over an area of 4 km2, with a ‘shell’ up to 50 m thick at the intrusive contact with minor mineralization occurring in the Tinombo Formation. Series of NW trending, steeply dipping fracture zones, named the East Zone has an estimated resource of 100 Mt at 0.14% MoS2 and minimum target of 150 Mt 0.25%. The Malala porphyries occur as stocks and dykes with predominantly granitic, with fluorine-poor class of molybdenum deposits and belongs to the plutonic sub-type. Unidirectional solidification textures consisting of subparallel, crenulated layers of quartz that area separated by layers of intrusive material textures. The deuteric nature of the molybdenum mineralization and the dominance of carbonate alteration.The nature of the Stage I with alteration barren quartz K‐feldspar; and Stage II with alteration quartz‐K‐feldspar‐apatite-molybdenite veins combined with the presence of disseminated molybdenite with primary biotite in the host intrusive.

Keywords: molybdenite, Malala, porphyries, anomaly B

Procedia PDF Downloads 128

Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: Aldilla Damayanti Purnama Ratri, Hendri Subakti, Buldan Muslim

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Ionosphere’s anomalies as an effect of earthquake activity is a phenomenon that is now being studied in seismo-ionospheric coupling. Generally, variation in the ionosphere caused by earthquake activity is weaker than the interference generated by different source, such as geomagnetic storms. However, disturbances of geomagnetic storms show a more global behavior, while the seismo-ionospheric anomalies occur only locally in the area which is largely determined by magnitude of the earthquake. It show that the earthquake activity is unique and because of its uniqueness it has been much research done thus expected to give clues as early warning before earthquake. One of the research that has been developed at this time is the approach of seismo-ionospheric-coupling. This study related the state in the lithosphere-atmosphere and ionosphere before and when earthquake occur. This paper choose the total electron content in a vertical (VTEC) in the ionosphere as a parameter. Total Electron Content (TEC) is defined as the amount of electron in vertical column (cylinder) with cross-section of 1m2 along GPS signal trajectory in ionosphere at around 350 km of height. Based on the analysis of data obtained from the LAPAN agency to identify abnormal signals by statistical methods, obtained that there are an anomaly in the ionosphere is characterized by decreasing of electron content of the ionosphere at 1 TECU before the earthquake occurred. Decreasing of VTEC is not associated with magnetic storm that is indicated as an earthquake precursor. This is supported by the Dst index showed no magnetic interference.

Keywords: earthquake, DST Index, ionosphere, seismoionospheric coupling, VTEC

Procedia PDF Downloads 558

Authors: Anacletus Ogbunkwu

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It is very disheartening that fake news or inaccurate information spread like wide fire and even with greater speed than fact based news/information. The peak of this anomaly is manifest in information management on the Corona virus pandemic, political/leadership based information, ethnic bigotry, unwarranted panics, false alarms, religious fanaticism, and business moguls in their advertorials, comedies, etc. This ugly situation has left Nigeria and her citizens with emotional trauma, unguided agitations, incessant tribal wars, lost of life and property, widened disunity among Nigerian ethnic and religious groups, amplified insecurity, aided election violence, etc. Unfortunately, among the major driving factors to this misinformation and conspiracy are the official/government and private news agencies, gossip, comedians, and social media handles such as; facebook, twitter, whatsapp, instagram, and online news agencies, etc. Thus this paper examines the impact of misinformation here referred to as infodemic. Also, it studies the epistemic effect of misinformation on the citizens of Nigeria in order to find ways of abating this anomaly for a better society. The methods of exposition and hermeneutics will be used in order to gain in-depth study of the details of infodemic in Nigeria and to offer philosophical analysis/interpretation of data as gathered, respectively. This paper concludes that misinformation or fake news has a perilous effect of epistemic mistrust to Nigeria and her citizens; hence infodemic is a cog in the wheel of National progress.

Keywords: nigeria, infodemic, language, media, news, progress

Procedia PDF Downloads 92

Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Zhu Weimin, Allegorico Carmine, Ruggiero Gionata

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During decades of Baker Hughes (BH) iCenter experience, it is demonstrated that in addition to conventional insights on equipment steady operation conditions, insights on transient conditions can add significant and exclusive value for anomaly detection, downtime saving, and predictive maintenance. Our work shows examples from the BH iCenter experience to introduce the advantages and features of using transient condition analytics: (i) Operation under critical engine conditions: e.g., high level or high change rate of temperature, pressure, flow, vibration, etc., that would not be reachable in normal operation, (ii) Management of dedicated sub-systems or components, many of which are often bottlenecks for reliability and maintenance, (iii) Indirect detection of anomalies in the absence of instrumentation, (iv) Repetitive sequences: if data is properly processed, the engineering features of transients provide not only anomaly detection but also problem characterization and prognostic indicators for predictive maintenance, (v) Engine variables accounting for fatigue analysis. iCenter has been developing and deploying a series of analytics based on transient conditions. They are contributing to exclusive value adding in the following areas: (i) Reliability improvement, (ii) Startup reliability improvement, (iii) Predictive maintenance, (iv) Repair/overhaul cost down. Illustrative examples for each of the above areas are presented in our study, focusing on challenges and adopted techniques ranging from purely statistical approaches to the implementation of machine learning algorithms. The obtained results demonstrate how the value is obtained using transient condition analytics in the BH iCenter experience.

Keywords: analytics, diagnostics, monitoring, turbomachinery

Procedia PDF Downloads 47

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: Samim Khair Mohammad, Takeshi Tsuji, Chanmaly Chhun

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The Afghan Tajik (foreland) basin, located in the depression zone between mountain axes, is under compression and deformation during the collision of India with the Eurasian plate. The southern part of the Afghan Tajik basin in the Northern part of Afghanistan has not been well studied and explored, but considered for the significant potential for oil and gas resources. The Afghan Tajik basin depositional environments (< 8km) resulted from mixing terrestrial and marine systems, which has potential prospects of Jurrasic (deep) and Tertiary (shallow) petroleum systems. We used 2D regional seismic profiles with a total length of 674.8 km (or over an area of 2500 km²) in the southern part of the basin. To characterize hydrocarbon systems and structures in this study area, we applied advanced seismic attributes such as spectral decomposition (10 - 60Hz) based on time-frequency analysis with continuous wavelet transform. The spectral decomposition results yield the (averaging 20 - 30Hz group) spectral amplitude anomaly. Based on this anomaly result, seismic, and structural interpretation, the potential hydrocarbon accumulations were inferred around the main thrust folds in the tertiary (Paleogene+Neogene) petroleum systems, which appeared to be accumulated around the central study area. Furthermore, it seems that hydrocarbons dominantly migrated along the main thrusts and then concentrated around anticline fold systems which could be sealed by mudstone/carbonate rocks.

Keywords: The Afghan Tajik basin, seismic lines, spectral decomposition, thrust folds, hydrocarbon reservoirs

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Authors: L. C. Prasanna, Antony Sylvan D’Souza, Kumar M. R. Bhat

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Although life as a conjoined twin would seem intolerable, there has recently been an increased interest in this subject because of the increasing number of cases where attempts have been made to separate them surgically. We have reviewed articles on cardiovascular anomalies in conjoined twins and presenting rarest anomaly in dicephalus parapagus fetus having two heads attached to one body from the neck or upper chest downwards, with a pair of limbs and a set of reproductive organs. Both the twins shared a common thoracic cavity with a single sternum. When the thoracic cavity was opened, a common anterior mediastinum was found. On opening the pericardium, two separate, closely apposed hearts were exposed. The two cardia are placed side by side. The left heart was slightly larger than the right and were joined at the atrial levels. Four atrial appendages were present, two for each twin. The atrial complex was a common chamber posterior to the ventricles. A single large tributary which could be taken as inferior vena cava drains into the common atrial chamber. In this case, the heart could not be assigned to either twin and therefore, it is referred to as the shared heart within a common pericardial sac. The right and left descending thoracic aorta have joined with each other just above the diaphragm to form a common descending thoracic aorta which has an opening in the diaphragm to be continued as common abdominal aorta which has a normal branching pattern. Upon an interior dissection, it is observed that the two atria have a wide communication which could be a wide patent foramen ovale and this common atrial cavity has a communication with a remnant of a possible common sinus venosus.

Keywords: atrium, congenital anomaly, conjoined twin, sinus venosus

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Authors: Nam-Uk Kim, Sung-Hwan Kim, Tai-Myoung Chung

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Typical security management systems are not suitable for detecting APT attack, because they cannot draw the big picture from trivial events of security solutions. Although SIEM solutions have security analysis engine for that, their security analysis mechanisms need to be verified in academic field. Although this paper proposes merely an architectural model for APT detection, we will keep studying on correlation analysis mechanism in the future.

Keywords: advanced persistent threat, anomaly detection, data mining

Procedia PDF Downloads 495

Authors: Mehmet Akif Bütüner, İlhan Koşalay

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Hydroelectric power plants (HEPPs) are renewable energy power plants with the highest installed power in the world. While the control systems operating in these power plants ensure that the system operates at the desired operating point, it is also responsible for stopping the relevant unit safely in case of any malfunction. While these control systems are expected not to miss signals that require stopping, on the other hand, it is desired not to cause unnecessary stops. In traditional control systems including modern systems with SCADA infrastructure, alarm conditions to create warnings or trip conditions to put relevant unit out of service automatically are usually generated with predefined limits regardless of different operating conditions. This approach results in alarm/trip conditions to be less likely to detect minimal changes which may result in serious malfunction scenarios in near future. With the methods proposed in this research, routine behavior of the oil circulation of hydraulic governor of a HEPP will be modeled with machine learning methods using historical data obtained from SCADA system. Using the created model and recently gathered data from control system, oil pressure of hydraulic accumulators will be estimated. Comparison of this estimation with the measurements made and recorded instantly by the SCADA system will help to foresee failure before becoming worse and determine remaining useful life. By using model outputs, maintenance works will be made more planned, so that undesired stops are prevented, and in case of any malfunction, the system will be stopped or several alarms are triggered before the problem grows.

Keywords: hydroelectric, governor, anomaly detection, machine learning, regression

Procedia PDF Downloads 61

Authors: Jingwen Shi, Qi Wu

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We study the role played interest rate risk in carry trade return in order to understand the forward premium puzzle. In this study, our goal is to investigate to what extent carry trade return is indeed due to compensation for risk taking and, more important, to reveal the nature of these risks. Using option data not only on exchange rates but also on interest rate swaps (swaptions), our first finding is that, besides the consensus currency risks, interest rate risks also contribute a non-negligible portion to the carry trade return. What strikes us is our second finding. We find that large downside risks of future exchange rate movements are, in fact, priced significantly in option market on interest rates. The role played by interest rate risk differs structurally from the currency risk. There is a unique premium associated with interest rate risk, though seemingly small in size, which compensates the tail risks, the left tail to be precise. On the technical front, our study relies on accurately retrieving implied distributions from currency options and interest rate swaptions simultaneously, especially the tail components of the two. For this purpose, our major modeling work is to build a new international asset pricing model where we use an orthogonal setup for pricing kernels and specify non-Gaussian dynamics in order to capture three sets of option skew accurately and consistently across currency options and interest rate swaptions, domestic and foreign, within one model. Our results open a door for studying forward premium anomaly through implied information from interest rate derivative market.

Keywords: carry trade, forward premium anomaly, FX option, interest rate swaption, implied volatility skew, uncovered interest rate parity

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

Procedia PDF Downloads 116

Authors: Madeleine Gadd, Rose How, Edward Mathews, John Buchanan, Vicky Cottrell, Andre Coetzee, Karuna Katti

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Introduction: Triphallia, a congenital anomaly describing the presence of three distinct penile shafts, has been reported only once in the literature. This case report describes the serendipitous discovery of the first reported human case of partial orthotopic triphallia during cadaveric dissection. Case Summary: Despite the normal appearance of external genitalia on examination, the dissection of a 78-year-old male revealed a remarkable anatomical variation: two small supernumerary penises situated in a transverse orientation postero inferiorly to the primary penis. The main and the larger supernumerary penile shafts displayed their own corpora cavernosa and glans penis, sharing a single urethra, which coursed through the secondary penis prior to its passage through the primary penis. The smallest of the supernumerary penises was similar in dimension to the secondary penis, at 3.7cm long and 1.2cm wide (compared to the secondary penis at 3.8cm long and 1.3cm wide). However, it lacked a urethra and a typical arrangement of the corpora cavernosa and spongiosum, making this a case of partial triphallia rather than true triphallia. Conclusion: This case report provides a comprehensive anatomical description of partial triphallia in a cadaver, shedding light on the morphology, embryology, and clinical implications of this anomaly. This case report underscores the importance of meticulous anatomical dissections, particularly since, without dissection, this anatomical variation would have remained undiscovered. Although we can only speculate the functional implications of this condition, understanding such anatomical variations contributes to both knowledge of human anatomy and clinical management, should the condition be encountered in living individuals.

Keywords: triphallia, diphallia, congenital abnormalities, genitourinary abnormalities, urology

Procedia PDF Downloads 39

Authors: Shaidatul Azdawiyah Abdul Talib, Wan Mohd Razi Idris, Liew Ju Neng, Tukimat Lihan, Muhammad Zamir Abdul Rasid

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Climate change has received great attention worldwide due to the impact of weather causing extreme events. Rainfall and temperature are crucial weather components associated with climate change. In Malaysia, increasing temperatures and changes in rainfall distribution patterns lead to drought and flood events involving agricultural areas, especially rice fields. Muda Agricultural Development Authority (MADA) is the largest rice growing area among the 10 granary areas in Malaysia and has faced floods and droughts in the past due to changing climate. Changes in rainfall and temperature patter affect rice yield. Therefore, trend analysis is important to identify changes in temperature and rainfall patterns as it gives an initial overview for further analysis. Six locations across the MADA area were selected based on the availability of meteorological station (MetMalaysia) data. Historical data (1991 to 2020) collected from MetMalaysia and future climate projection by multi-model ensemble of climate model from CMIP5 (CNRM-CM5, GFDL-CM3, MRI-CGCM3, NorESM1-M and IPSL-CM5A-LR) have been analyzed using Mann-Kendall test to detect the time series trend, together with standardized precipitation anomaly, rainfall anomaly index, precipitation concentration index and temperature anomaly. Future projection data were analyzed based on 3 different periods; early century (2020 – 2046), middle century (2047 – 2073) and late-century (2074 – 2099). Results indicate that the MADA area does encounter extremely wet and dry conditions, leading to drought and flood events in the past. The Mann-Kendall (MK) trend analysis test discovered a significant increasing trend (p < 0.05) in annual rainfall (z = 0.40; s = 15.12) and temperature (z = 0.61; s = 0.04) during the historical period. Similarly, for both RCP 4.5 and RCP 8.5 scenarios, a significant increasing trend (p < 0.05) was found for rainfall (RCP 4.5: z = 0.15; s = 2.55; RCP 8.5: z = 0.41; s = 8.05;) and temperature (RCP 4.5: z = 0.84; s = 0.02; RCP 8.5: z = 0.94; s = 0.05). Under the RCP 4.5 scenario, the average temperature is projected to increase up to 1.6 °C in early century, 2.0 °C in the middle century and 2.4 °C in the late century. In contrast, under RCP 8.5 scenario, the average temperature is projected to increase up to 1.8 °C in the early century, 3.1 °C in the middle century and 4.3 °C in late century. Drought is projected to occur in 2038 and 2043 (early century); 2052 and 2069 (middle century); and 2095, 2097 to 2099 (late century) under RCP 4.5 scenario. As for RCP 8.5 scenario, drought is projected to occur in 2021, 2031 and 2034 (early century); and 2069 (middle century). No drought is projected to occur in the late century under the RCP 8.5 scenario. Thus, this information can be used for the analysis of the impact of climate change scenarios on rice growth and yield besides other crops found in MADA area. Additionally, this study, it would be helpful for researchers and decision-makers in developing applicable adaptation and mitigation strategies to reduce the impact of climate change.

Keywords: climate projection, drought, flood, rainfall, RCP 4.5, RCP 8.5, temperature

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Authors: Huda Al Shuaily, Karen Renaud

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Databases comprise the foundation of most software systems. System developers inevitably write code to query these databases. The de facto language for querying is SQL and this, consequently, is the default language taught by higher education institutions. There is evidence that learners find it hard to master SQL, harder than mastering other programming languages such as Java. Educators do not agree about explanations for this seeming anomaly. Further investigation may well reveal the reasons. In this paper, we report on our investigations into how novices learn SQL, the actual problems they experience when writing SQL, as well as the differences between expert and novice SQL query writers. We conclude by presenting a model of SQL learning that should inform the instructional material design process better to support the SQL learning process.

Keywords: pattern, SQL, learning, model

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Authors: Dhekra Khazri, Hakim Gabtni

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Because of Sidi Bouzid water table overexploitation, this study aims at integrating geophysical methods to determinate aquifers geometry assessing their geological situation and geophysical characteristics. However in highly tectonic zones controlled by Atlassic structural features with NE-SW major directions (central Tunisia), Bouguer gravimetric responses of some areas can be as much dominated by the regional structural tendency, as being non-identified or either defectively interpreted such as the case of Sidi Bouzid basin. This issue required a residual gravity anomaly elaboration isolating the Sidi Bouzid basin gravity response ranging between -8 and -14 mGal and crucial for its aquifers geometry characterization. Several gravity techniques helped constructing the Sidi Bouzid basin's residual gravity anomaly, such as Upwards continuation compared to polynomial regression trends and power spectrum analysis detecting deep basement sources at (3km), intermediate (2km) and shallow sources (1km). A 3D Euler Deconvolution was also performed detecting deepest accidents trending NE-SW, N-S and E-W with depth values reaching 5500 m and delineating the main outcropping structures of the study area. Further gravity treatments highlighted the subsurface geometry and structural features of Sidi Bouzid basin over Horizontal and vertical gradient, and also filters based on them such as Tilt angle and Source Edge detector locating rooted edges or peaks from potential field data detecting a new E-W lineament compartmentalizing the Sidi Bouzid gutter into two unequally residual anomaly and subsiding domains. This subsurface morphology is also detected by the used 2D seismic reflection sections defining the Sidi Bouzid basin as a deep gutter within a tectonic set of negative flower structures, and collapsed and tilted blocks. Furthermore, these structural features were confirmed by forward gravity modeling process over several modeled residual gravity profiles crossing the main area. Sidi Bouzid basin (central Tunisia) is also of a big interest cause of the unknown total thickness and the undefined substratum of its siliciclastic Tertiary package, and its aquifers unbounded structural subsurface features and deep accidents. The Combination of geological, hydrogeological and geophysical methods is then of an ultimate need. Therefore, a geophysical methods integration based on gravity survey supporting available seismic data through forward gravity modeling, enhanced lateral and vertical extent definition of the basin's complex sedimentary fill via 3D gravity models, improved depth estimation by a depth to basement modeling approach, and provided 3D isochronous seismic mapping visualization of the basin's Tertiary complex refining its geostructural schema. A subsurface basin geomorphology mapping, over an ultimate matching between the basin's residual gravity map and the calculated theoretical signature map, was also displayed over the modeled residual gravity profiles. An ultimate multidisciplinary geophysical study of the Sidi Bouzid basin aquifers can be accomplished via an aeromagnetic survey and a 4D Microgravity reservoir monitoring offering temporal tracking of the target aquifer's subsurface fluid dynamics enhancing and rationalizing future groundwater exploitation in this arid area of central Tunisia.

Keywords: aquifer geometry, geophysics, 3D gravity modeling, improved depths, source edge detector

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Authors: Konstantopoulos N., Samitas A., E. Vasileiou, Kinias I.

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This article introduces a new view on the month effect study. Applying a Markov Switching Regime model on data from the Greek Time Deposits (TDs) market for the time span January 2003 to October 2013, we examine if there is a month effect on the Greek banking industry. The empirical findings provide convincing evidence for a new king of monthly anomaly. The explanation for the specific abnormality may be the upward deposits window dressing. Further research should be done in order to examine if the specific calendar effect exists in other countries or it is only a Greek phenomenon.

Keywords: calendar anomalies, banking crisis, month effect, Greek banking industry

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Authors: Taufik Nugroho, Firsty Dzainuurahmana, Tika Widiastuti

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The polemic about the salt crisis re-emerged, this is a classic problem in Indonesia and is still a homework that is not finished yet. This salt crisis occurs due to low productivity of salt commodities that have not been able to meet domestic demand and lack of salt productivity caused by several factors. One of the biggest factors of the crisis is the weather anomaly that disrupts salt production, less supportive technology and price stability. This study will try to discuss the salt scarcity and crisis solution in Islamic view. As for the conclusion of this study is the need for equilibrium or balancing between demand and supply, need to optimize the role of the government as Hisbah to maintain the balance of market mechanisms and prepare the stock system of salt stock by buying farmers products at reasonable prices then storing them.

Keywords: crisis, Islamic solution, scarcity, salt

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Authors: Harris Niavis, Dimitra Politaki

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The manufacturing industry was collecting vast amounts of data for monitoring product quality thanks to the advances in the ICT sector and dedicated IoT infrastructure is deployed to track and trace the production line. However, industries have not yet managed to unleash the full potential of these data due to defective data collection methods and untrusted data storage and sharing. Blockchain is gaining increasing ground as a key technology enabler for Industry 4.0 and the smart manufacturing domain, as it enables the secure storage and exchange of data between stakeholders. On the other hand, AI techniques are more and more used to detect anomalies in batch and time-series data that enable the identification of unusual behaviors. The proposed scheme is based on smart contracts to enable automation and transparency in the data exchange, coupled with anomaly detection algorithms to enable reliable data ingestion in the system. Before sensor measurements are fed to the blockchain component and the smart contracts, the anomaly detection mechanism uniquely combines artificial intelligence models to effectively detect unusual values such as outliers and extreme deviations in data coming from them. Specifically, Autoregressive integrated moving average, Long short-term memory (LSTM) and Dense-based autoencoders, as well as Generative adversarial networks (GAN) models, are used to detect both point and collective anomalies. Towards the goal of preserving the privacy of industries' information, the smart contracts employ techniques to ensure that only anonymized pointers to the actual data are stored on the ledger while sensitive information remains off-chain. In the same spirit, blockchain technology guarantees the security of the data storage through strong cryptography as well as the integrity of the data through the decentralization of the network and the execution of the smart contracts by the majority of the blockchain network actors. The blockchain component of the Data Traceability Software is based on the Hyperledger Fabric framework, which lays the ground for the deployment of smart contracts and APIs to expose the functionality to the end-users. The results of this work demonstrate that such a system can increase the quality of the end-products and the trustworthiness of the monitoring process in the smart manufacturing domain. The proposed AI-enabled data traceability software can be employed by industries to accurately trace and verify records about quality through the entire production chain and take advantage of the multitude of monitoring records in their databases.

Keywords: blockchain, data quality, industry4.0, product quality

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Authors: D. Aboutaleb, B. Safi

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The borate glasses are known by their structural characterized by existence of unit’s structural composed by triangles and tetrahedrons boron in different configurations depending on the percentage of B2O3 in the glass chemical composition. In this paper, effect of lithium oxide addition on the thermal and physical properties of an alumina borate glass, was investigated. It was found that the boron abnormality has a significant effect in the change of glass properties according to the addition rate of lithium oxide.

Keywords: borate glasses, triangles and tetrahedrons boron, lithium oxide, boron anomaly, thermal properties, physical properties

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Authors: Balogun R. Ayodeji, Adefisan E. Adesanya, Adeyewa Z. Debo, E. C. Okogbue

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The need to investigate diurnal weather circles in West Africa is coined in the fact that complex interactions often results from diurnal weather patterns. This study investigates diurnal circles of wind, rainfall and convective properties using six (6) hour interval data from the ERA-Interim and the Tropical Rainfall Measurement Mission (TRMM). The seven distinct zones, used in this work and classified as rainforest (west-coast, dry, Nigeria-Cameroon), Savannah (Nigeria, and Central Africa and South Sudan (CASS)), Sudano-Sahel, and Sahel, were clearly indicated by the rainfall pattern in each zones. Results showed that the land‐ocean warming contrast was more strongly sensitive to seasonal cycle and has been very weak during March-May (MAM) but clearly spelt out during June-September (JJAS). Dipoles of wind convergence/divergence and wet/dry precipitation, between CASS and Nigeria Savannah zones, were identified in morning and evening hours of MAM, whereas distinct night and day anomaly, in the same location of CASS, were found to be consistent during the JJAS season. Diurnal variation of convective properties showed that stratiform precipitation, due to the extremely low occurrence of flashcount climatology, was dominant during morning hours for both MAM and JJAS than other periods of the day. On the other hand, diurnal variation of the system sizes showed that small system sizes were most dominant during the day time periods for both MAM and JJAS, whereas larger system sizes were frequent during the evening, night, and morning hours. The locations of flashcount and system sizes agreed with earlier results that morning and day-time hours were dominated by stratiform precipitation and small system sizes respectively. Most results clearly showed that the eastern locations of Sudano and Sahel were consistently dry because rainfall and precipitation features were predominantly few. System sizes greater than or equal to 800 km² were found in the western axis of the Sudano and Sahel zones, whereas the eastern axis, particularly in the Sahel zone, had minimal occurrences of small/large system sizes. From the results of locations of extreme systems, flashcount greater than 275 in one single system was never observed during the morning (6Z) diurnal, whereas, the evening (18Z) diurnal had the most frequent cases (at least 8) of flashcount exceeding 275 in one single system. Results presented had shown the importance of diurnal variation in understanding precipitation, flashcount, system sizes patterns at diurnal scales, and understanding land-ocean contrast, precipitation, and wind field anomaly at diurnal scales.

Keywords: convective properties, diurnal circle, flashcount, system sizes

Procedia PDF Downloads 99

Authors: Pelangi Wiyantika

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Sustainable energy is the main concern in According to solve any problems on energy sectors. One of the sustainable energy that has lack of presentation is Geothermal energy which has developed lately as the new promising sustainable energy. Indonesia as country that has been passed by the ring of fire zone has many geothermal sources. This is the good opportunity to elaborate and learn more about geothermal as sustainable and renewable energy. Geothermal systems have special characteristic whom the zone of sources can be detected by measuring the resistivity of the subsurface. There are many methods to measuring the anomaly of the systems. One of the best method is Magnetotelluric approchment. Magnetotelluric is the passive method which the resistivity is obtained by injecting the eddy current of rocks in the subsurface with the sources. The sources of Magnetotelluric method can be obtained from lightning or solar wind which has the frequencies each below 1 Hz and above 1 Hz.

Keywords: geothermal, magnetotelluric, renewable energy, resistivity, sustainable energy

Procedia PDF Downloads 271

Authors: Christina Klippel, Lucia Pezzi, Silvio Neto, Rafael Bertani, Priscila Mendes, Flavio Machado, Aline Szeliga, Maria Cosendey, Adilson Mariz, Raquel Santos, Lys Bendett, Pedro Velasco, Thalita Rolleigh, Bruna Bellote, Daria Coelho, Bruna Martins, Julia Almeida, Juliana Cerqueira

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This project presents a framework for teaching intracranial pressure monitoring (ICP) concepts using a low-cost experimental model in a neurointensive care education program. Data concerning ICP monitoring contribute to the patient's clinical assessment and may dictate the course of action of a health team (nursing, medical staff) and influence decisions to determine the appropriate intervention. This study aims to present a safe method for teaching ICP monitoring to medical students in a Simulation Center. Methodology: Medical school teachers, along with students from the 4th year, built an experimental model for teaching ICP measurement. The model consists of a mannequin's head with a plastic bag inside simulating the cerebral ventricle and an inserted ventricular catheter connected to the ICP monitoring system. The bag simulating the ventricle can also be changed for others containing bloody or infected simulated cerebrospinal fluid. On the mannequin's ear, there is a blue point indicating the right place to set the "zero point" for accurate pressure reading. The educational program includes four steps: 1st - Students receive a script on ICP measurement for reading before training; 2nd - Students watch a video about the subject created in the Simulation Center demonstrating each step of the ICP monitoring and the proper care, such as: correct positioning of the patient, anatomical structures to establish the zero point for ICP measurement and a secure range of ICP; 3rd - Students train the procedure in the model. Teachers help students during training; 4th - Student assessment based on a checklist form. Feedback and correction of wrong actions. Results: Students expressed interest in learning ICP monitoring. Tests concerning the hit rate are still being performed. ICP's final results and video will be shown at the event. Conclusion: The study of intracranial pressure measurement based on an experimental model consists of an effective and controlled method of learning and research, more appropriate for teaching neurointensive care practices. Assessment based on a checklist form helps teachers keep track of student learning progress. This project offers medical students a safe method to develop intensive neurological monitoring skills for clinical assessment of patients with neurological disorders.

Keywords: neurology, intracranial pressure, medical education, simulation

Procedia PDF Downloads 140

Authors: Marwa Djebbi, Hakim Gabtni

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Gravity is a continuously advancing method that has become a mature technology for geological studies. Increasingly, it has been used to complement and constrain traditional seismic data and even used as the only tool to get information of the sub-surface. In fact, in some regions the seismic data, if available, are of poor quality and hard to be interpreted. Such is the case for the current study area. The Nefza zone is part of the Tellian fold and thrust belt domain in the north west of Tunisia. It is essentially made of a pile of allochthonous units resulting from a major Neogene tectonic event. Its tectonic and stratigraphic developments have always been subject of controversies. Considering the geological and hydrogeological importance of this area, a detailed interdisciplinary study has been conducted integrating geology, seismic and gravity techniques. The interpretation of Gravity data allowed the delimitation of the dune reservoir and the identification of the regional lineaments contouring the area. It revealed the presence of three gravity lows that correspond to the dune of Zouara and Ouchtata separated along with a positive gravity axis espousing the Ain Allega_Aroub Er Roumane axe. The Bouguer gravity map illustrated the compartmentalization of the Zouara dune into two depressions separated by a NW-SE anomaly trend. This constitution was confirmed by the vertical derivative map which showed the individualization of two depressions with slightly different anomaly values. The horizontal gravity gradient magnitude was performed in order to determine the different geological features present in the studied area. The latest indicated the presence of NE-SW parallel folds according to the major Atlasic direction. Also, NW-SE and EW trends were identified. The maxima tracing confirmed this direction by the presence of NE-SW faults, mainly the Ghardimaou_Cap Serrat accident. The quality of the available seismic sections and the absence of borehole data in the region, except few hydraulic wells that been drilled and showing the heterogeneity of the substratum of the dune, required the process of gravity modeling of this challenging area that necessitates to be modeled for the geometrical characterization of the dune reservoir and determine the different stratigraphic series underneath these deposits. For more detailed and accurate results, the scale of study will be reduced in coming research. A more concise method will be elaborated; the 4D microgravity survey. This approach is considered as an expansion of gravity method and its fourth dimension is time. It will allow a continuous and repeated monitoring of fluid movement in the subsurface according to the micro gal (μgall) scale. The gravity effect is a result of a monthly variation of the dynamic groundwater level which correlates with rainfall during different periods.

Keywords: 3D gravity modeling, dune reservoir, heterogeneous substratum, seismic interpretation

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Authors: Abhishek Mangal, Kunal Tongaria, S. Mandal, Devendra Mohan

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Carbonation of reinforced concrete structures has emerged as one of the major challenges for Civil engineers across the world. With increasing emissions from various activities, carbon dioxide concentration in the atmosphere has been eve rising, enhancing its penetration in porous concrete, reaching steel bars and ultimately leading to premature failure. Several literatures have been published dealing with the various interdependent variables related to carbonation. However, with innumerable variability a generalization of these data proves to be a troublesome task. This paper looks into this carbonation anomaly in concrete structures caused by various external variables such as relative humidity, concentration of CO2, curing period and ambient temperature. Significant discussions and comparisons have been presented on the basis of various studies conducted with an aim to predict the depth of carbonation as a function of these multidimensional parameters using various numerical and statistical modelling techniques.

Keywords: carbonation, curing, exposure conditions, relative humidity

Procedia PDF Downloads 219

Authors: Mohammad Alqattan, Tala Alkhunani, Reema Al, Aldawish, Felwa Almurshard, Abdullah Alzahrani

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: Poland’s Syndrome is a congenital anomaly with two clinical features : unilateral agenesis of the pectoralis major and ipsilateral hand symbrachydactyly. Case presentation: We report a rare case of bilateral Poland’s syndrome with several unique features. Discussion: Poland’s syndrome is thought to be due to a vascular insult to the subclavian axis around the 6th week of gestation. Our patient has multiple rare and unique features of Poland’s syndrome. Conclusion: To our best knowledge, for the first time in the literature we associate Poland’s syndrome with cone-shaped epiphysis of the metacarpals of all fingers. Bilaterality, cleft hand deformity, and dextrocardia, were also rare features in our patient.

Keywords: Poland's syndrome, cleft hand deformity, bilaterality, dextrocardia, cone-shaped epiphysis

Procedia PDF Downloads 96

Authors: Hasmithaa Neha, Atul Kumar Patidar, Girish Ch Kothyari

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The northward convergence of the Indian plate has a dominating influence over the structural and geomorphic development of the Himalayan region. The highly deformed and complex stratigraphy in the area arises from a confluence of exogenic and endogenetic geological processes. This region frequently experiences natural hazards such as debris flows, flash floods, avalanches, landslides, and earthquakes due to its harsh and steep topography and fragile rock formations. Therefore, remote sensing technique-based examination and real-time monitoring of tectonically sensitive regions may provide crucial early warnings and invaluable data for effective hazard mitigation strategies. In order to identify unusual changes in the river gradients, the current study demonstrates a spatial quantitative geomorphic analysis of the upper Alaknanda River basin, Uttarakhand Himalaya, India, using gradient length anomaly analysis (GLAA). This basin is highly vulnerable to ground creeping and landslides due to the presence of active faults/thrusts, toe-cutting of slopes for road widening, development of heavy engineering projects on the highly sheared bedrock, and periodic earthquakes. The intersecting joint sets developed in the bedrocks have formed wedges that have facilitated the recurrence of several landslides. The main objective of current research is to identify abnormal gradient lengths, indicating potential landslide-prone zones. High-resolution digital elevation data and geospatial techniques are used to perform this analysis. The results of GLAA are corroborated with the historical landslide events and ultimately used for the generation of landslide susceptibility maps of the current study area. The preliminary results indicate that approximately 3.97% of the basin is stable, while about 8.54% is classified as moderately stable and suitable for human habitation. However, roughly 19.89% fall within the zone of moderate vulnerability, 38.06% are classified as vulnerable, and 29% fall within the highly vulnerable zones, posing risks for geohazards, including landslides, glacial avalanches, and earthquakes. This research provides valuable insights into the spatial distribution of landslide-prone areas. It offers a basis for implementing proactive measures for landslide risk reduction, including land-use planning, early warning systems, and infrastructure development techniques.

Keywords: landslide vulnerability, geohazard, GLA, upper Alaknanda Basin, Uttarakhand Himalaya

Procedia PDF Downloads 38

Authors: Albert T. Akume, Ankama G. Rosecana, Micheal Solomon

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Every citizen has rights that must be respected by others in the community. Ironically however, women in most communities are not accorded some of those rights as the male folks. This has not only facilitated their disempowerment but inhibited them from being treated with equal dignity that they deserve as their male counterpart; despite their valuable contribution to the society. Those forces against women empowerment are not limited to socio-cultural practices alone, but the character and nature of the state in Nigeria point to indicators of systemic and structural exclusion embedded in its framework. The consequence of this is that the vital contributions of women to sustainable community development have eluded many communities in Nigeria with adverse tell-tell signs on the environment. It is for this reason that the objective of this study is not only to highlight the causes and challenges associated with women disempowerment, but also to draw attention to the need to correct those anomaly against women in order to genuinely empower them to contribute to sustainable community development in Nigeria.

Keywords: capacity development, community, social sustainability, sustainable development, women empowerment

Procedia PDF Downloads 389