Search results for: subjective bias detection

Authors: Neha Verma, Manik Rakhra

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Statement of the Problem: Nowadays, a tremendous increase in population and advanced industrialization augment the problems related to air and water pollutions. Growing industries promoting environmental danger, which is an alarming threat to the ecosystem. For safeguard, the environment, detection of perilous gases and release of colored wastewater is required for eutrophication pollution. Researchers around the globe are trying their best efforts to save the environment. For this remediation advanced oxidation process is used for potential applications. ZnO is an important semiconductor photocatalyst with high photocatalytic and gas sensing activities. For efficient photocatalytic and gas sensing properties, it is necessary to prepare a doped/co-doped ZnO compound to decrease the electron-hole recombination rates. However, lanthanide doped and co-doped metal oxide is seldom studied for photocatalytic and gas sensing applications. The purpose of this study is to describe the best photocatalyst for the photodegradation of dyes and gas sensing properties. Methodology & Theoretical Orientation: Economical framework has to be used for the synthesis of ZnO. In the depth literature survey, a simple combustion method is utilized for gas sensing and photocatalytic activities. Findings: Rare earth doped and co-doped ZnO nanoparticles were the best photocatalysts for photodegradation of organic dyes and different gas sensing applications by varying various factors such as pH, aging time, and different concentrations of doping and codoping metals in ZnO. Complete degradation of dye was observed only in min. Gas sensing nanodevice showed a better response and quick recovery time for doped/co-doped ZnO. Conclusion & Significance: In order to prevent air and water pollution, well crystalline ZnO nanoparticles were synthesized by rapid and economic method, which is used as photocatalyst for photodegradation of organic dyes and gas sensing applications to sense the release of hazardous gases from the environment.

Keywords: ZnO, photocatalyst, photodegradation of dye, gas sensor

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Authors: Stephen L. Roberts

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This article offers a critical analysis of the rise of syndromic surveillance systems for the advanced detection of pandemic threats within contemporary global health security frameworks. The article traces the iterative evolution and ascendancy of three such novel syndromic surveillance systems for the strengthening of health security initiatives over the past two decades: 1) The Program for Monitoring Emerging Diseases (ProMED-mail); 2) The Global Public Health Intelligence Network (GPHIN); and 3) HealthMap. This article demonstrates how each newly introduced syndromic surveillance system has become increasingly oriented towards the integration of digital algorithms into core surveillance capacities to continually harness and forecast upon infinitely generating sets of digital, open-source data, potentially indicative of forthcoming pandemic threats. This article argues that the increased centrality of the algorithm within these next-generation syndromic surveillance systems produces a new and distinct form of infectious disease surveillance for the governing of emergent pathogenic contingencies. Conceptually, the article also shows how the rise of this algorithmic mode of infectious disease surveillance produces divergences in the governmental rationalities of global health security, leading to the rise of an algorithmic governmentality within contemporary contexts of Big Data and these surveillance systems. Empirically, this article demonstrates how this new form of algorithmic infectious disease surveillance has been rapidly integrated into diplomatic, legal, and political frameworks to strengthen the practice of global health security – producing subtle, yet distinct shifts in the outbreak notification and reporting transparency of states, increasingly scrutinized by the algorithmic gaze of syndromic surveillance.

Keywords: algorithms, global health, pandemic, surveillance

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Authors: O. S. Ebrahim, K. O. Shawky, M. O. S. Ebrahim, P. K. Jain

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Induction Motor (IM) driving pump is the main consumer of electricity in a typical fluid transportation system (FTS). It was illustrated that changing the connection of the stator windings from delta to star at no load could achieve noticeable active and reactive energy savings. This paper proposes a supervisory hysteresis liquid-level control with three-state energy saving mode (ESM) for IM in FTS including storage tank. The IM pump drive comprises modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to computer ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. A logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction, considering the motor thermal capacity used. An artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and, computer simulations are performed to show the effectiveness of the proposed control in terms of reliability, power quality and energy/coenergy cost reduction with the suggestion of power factor correction.

Keywords: ANN, ESM, IM, star/delta switch, supervisory control, FT, reliability, power quality

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Authors: Yen Yen Tan, Lynn Lam, Cynthia Lam, Angela Koh, Edwin Seng

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Entrepreneurial education plays a crucial role in nurturing future innovators and change-makers. Over time, significant progress has been made in refining instructional approaches to develop the necessary skills among learners effectively. Two highly valuable frameworks, Kearney's "4 Principles of Entrepreneurial Pedagogy" and Bloom's "Three Domains of Learning," serve as guiding principles in entrepreneurial education. Kearney's principles align with experiential and student-centric learning, which are crucial for cultivating an entrepreneurial mindset. The potential synergies between these frameworks hold great promise for enhancing entrepreneurial acumen among students. However, despite this potential, their integration remains largely unexplored. This study aims to bridge this gap by building upon the Business Essentials through Action (BETA) module and investigating its contributions to nurturing the entrepreneurial mindset. This study employs a quasi-experimental mixed-methods approach, combining quantitative and qualitative elements to ensure comprehensive and insightful data. A cohort of 235 students participated, with 118 enrolled in the BETA module and 117 in a traditional curriculum. Their Personal Entrepreneurial Competencies (PECs) were assessed before admission (pre-Y1) and one year into the course (post-Y1) using a comprehensive 55-item PEC questionnaire, enabling measurement of critical traits such as opportunity-seeking, persistence, and risk-taking. Rigorous computations of individual entrepreneurial competencies and overall PEC scores were performed, including a correction factor to mitigate potential self-assessment bias. The orchestration of Kearney's principles and Bloom's domains within the BETA module necessitates a granular examination. Here, qualitative revelations surface, courtesy of structured interviews aligned with contemporary research methodologies. These interviews act as a portal, ushering us into the transformative journey undertaken by students. Meanwhile, the study pivots to explore the BETA module's influence on students' entrepreneurial competencies from the vantage point of faculty members. A symphony of insights emanates from intimate focus group discussions featuring six dedicated lecturers, who share their perceptions, experiences, and reflective narratives, illuminating the profound impact of pedagogical practices embedded within the BETA module. Preliminary findings from ongoing data analysis indicate promising results, showcasing a substantial improvement in entrepreneurial skills among students participating in the BETA module. This study promises not only to elevate students' entrepreneurial competencies but also to illuminate the broader canvas of applicability for Kearney's principles and Bloom's domains. The dynamic interplay of quantitative analyses, proffering precise competency metrics, and qualitative revelations, delving into the nuanced narratives of transformative journeys, engenders a holistic understanding of this educational endeavour. Through a rigorous quasi-experimental mixed-methods approach, this research aims to establish the BETA module's effectiveness in fostering entrepreneurial acumen among students at Singapore Polytechnic, thereby contributing valuable insights to the broader discourse on educational methodologies.

Keywords: entrepreneurial education, experiential learning, pedagogical frameworks, innovative competencies

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Authors: Saeed Vahedikamal, Ian Hepburn

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Microwave Kinetic Inductance Detectors (MKIDs) are considered as one of the most promising photon detectors of the future in many Astronomical applications such as exoplanet detections. The MKID advantages stem from their single photon sensitivity (ranging from UV to optical and near infrared), photon energy resolution and high temporal capability (~microseconds). There has been substantial progress in the development of these detectors and MKIDs with Megapixel arrays is now possible. The unique capability of recording an incident photon and its energy (or wavelength) while also registering its time of arrival to within a microsecond enables an array of MKIDs to produce a four-dimensional data block of x, y, z and t comprising x, y spatial, z axis per pixel spectral and t axis per pixel which is temporal. This offers the possibility that the spectrum and brightness variation for any detected piece of space debris as a function of time might offer a unique identifier or fingerprint. Such a fingerprint signal from any object identified in multiple detections by different observers has the potential to determine the orbital features of the object and be used for their tracking. Modelling performed so far shows that with a 20 cm telescope located at an Astronomical observatory (e.g. La Palma, Canary Islands) we could detect sub cm objects at GEO. By considering a Lambertian sphere with a 10 % reflectivity (albedo of the Moon) we anticipate the following for a GEO object: 10 cm object imaged in a 1 second image capture; 1.2 cm object for a 70 second image integration or 0.65 cm object for a 4 minute image integration. We present details of our modelling and the potential instrument for a dedicated GEO surveillance system.

Keywords: space debris, orbital debris, detection system, observation, microwave kinetic inductance detectors, MKID

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Authors: Mutaz Dwairy

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Solid tumors have high interstitial fluid pressure (IFP), high mechanical stress, and low oxygen levels. Solid stresses may induce apoptosis, stimulate the invasiveness and metastasis of cancer cells, and lower their proliferation rate, while oxygen concentration may affect the response of cancer cells to treatment. Although tumors grow in a nonhomogeneous environment, many existing theoretical models assume homogeneous growth and tissue has uniform mechanical properties. For example, the brain consists of three primary materials: white matter, gray matter, and cerebrospinal fluid (CSF). Therefore, tissue inhomogeneity should be considered in the analysis. This study established a physical model based on convection-diffusion equations and continuum mechanics principles. The model considers the geometrical inhomogeneity of the brain by including the three different matters in the analysis: white matter, gray matter, and CSF. The model also considers fluid-solid interaction and explicitly describes the effect of mechanical factors, e.g., solid stresses and IFP, chemical factors, e.g., oxygen concentration, and biological factors, e.g., cancer cell concentration, on growing tumors. In this article, we applied the model on a brain tumor positioned within the white matter, considering the brain inhomogeneity to estimate solid stresses, IFP, the cancer cell concentration, oxygen concentration, and the deformation of the tissues within the neoplasm and the surrounding. Tumor size was estimated at different time points. This model might be clinically crucial for cancer detection and treatment planning by measuring mechanical stresses, IFP, and oxygen levels in the tissue.

Keywords: biomechanical model, interstitial fluid pressure, solid stress, tumor microenvironment

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Authors: Ana Vulic, Tina Lesic, Nina Kudumija, Maja Kis, Manuela Zadravec, Nada Vahcic, Tomaz Polak, Jelka Pleadin

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Mycotoxins are toxic secondary metabolites produced by numerous types of molds. They can contaminate both food and feed so that they represent a serious public health concern. Production of dry-fermented meat products involves ripening, during which molds can overgrow the product surface, produce mycotoxins, and consequently contaminate the final product. Citrinin is a mycotoxin produced mainly by the Penicillium citrinum. Data on citrinin occurrence in both food and feed are limited. Therefore, there is a need for research on citrinin occurrence in these types of meat products. The LC-MS/MS method for citrinin determination was developed and validated. Sample preparation was performed using immunoaffinity columns, which resulted in clean sample extracts. Method validation included the determination of the limit of detection (LOD), the limit of quantification (LOQ), recovery, linearity, and matrix effect in accordance to the latest validation guidance. The determined LOD and LOQ were 0.60 µg/kg and 1.98 µg/kg, respectively, showing a good method sensitivity. The method was tested for its linearity in the calibration range of 1 µg/L to 10 µg/L. The recovery was 100.9 %, while the matrix effect was 0.7 %. This method was employed in the analysis of 47 samples of dry-fermented sausages collected from local households. Citrinin wasn’t detected in any of these samples, probably because of the short ripening period of the tested sausages that takes three months tops. The developed method shall be used to test other types of traditional dry-cured products, such as prosciuttos, whose surface is usually more heavily overgrown by surface molds due to the longer ripening period.

Keywords: citrinin, dry-fermented meat products, LC-MS/MS, mycotoxins

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Authors: Marwa A. A. Ragab, Amira F. El-Yazbi, Amr El-Hawiet

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The analysis of heavy metals in honey samples is crucial. When found in honey, they denote environmental pollution. Some of these heavy metals as lead either present at low or high concentrations are considered to be toxic. Other heavy metals, for example, copper and zinc, if present at low concentrations, they considered safe even vital minerals. On the contrary, if they present at high concentrations, they are toxic. Their voltammetric determination in honey represents a challenge due to the presence of other electro-active components as vitamins, which may overlap with the peaks of the metal, hindering their accurate and precise determination. The simultaneous analysis of some vitamins: nicotinic acid (B3) and riboflavin (B2), and heavy metals: lead, cadmium, and zinc, in honey samples, was addressed. The analysis was done in 0.1 M Potassium Chloride (KCl) using a hanging mercury drop electrode (HMDE), followed by chemometric manipulation of the voltammetric data using the derivative method. Then the derivative data were convoluted using discrete Fourier functions. The proposed method allowed the simultaneous analysis of vitamins and metals though their varied responses and sensitivities. Although their peaks were overlapped, the proposed chemometric method allowed their accurate and precise analysis. After the chemometric treatment of the data, metals were successfully quantified at low levels in the presence of vitamins (1: 2000). The heavy metals limit of detection (LOD) values after the chemometric treatment of data decreased by more than 60% than those obtained from the direct voltammetric method. The method applicability was tested by analyzing the selected metals and vitamins in real honey samples obtained from different botanical origins.

Keywords: chemometrics, overlapped voltammetric peaks, derivative and convoluted derivative methods, metals and vitamins

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Authors: Tzong-Ying Hao, Mohammad T. Rahmani

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The Torre Central building is a 9-story shear wall structure located in Santiago, Chile, and has been instrumented since 2009. Events of different intensity (ambient vibrations, weak and strong earthquake motions) have been recorded, and thus the building can serve as a full-scale benchmark to evaluate the structural health monitoring method developed. The first part of this article presents an analysis of inter-story drifts, and of changes in the first system frequencies (estimated from the relative displacement response of the 8th-floor with respect to the basement from recorded data) as baseline indicators of the occurrence of damage. During 2010 Chile earthquake the system frequencies were detected decreasing approximately 24% in the EW and 27% in NS motions. Near the end of shaking, an increase of about 17% in the EW motion was detected. The structural health monitoring (SHM) method based on changes in wave traveling time (wave method) within a layered shear beam model of structure is presented in the second part of this article. If structural damage occurs the velocity of wave propagated through the structure changes. The wave method measures the velocities of shear wave propagation from the impulse responses generated by recorded data at various locations inside the building. Our analysis and results show that the detected changes in wave velocities are consistent with the observed damages. On this basis, the wave method is proven for actual implementation in structural health monitoring systems.

Keywords: Chile earthquake, damage detection, earthquake response, impulse response, layered shear beam, structural health monitoring, Torre Central building, wave method, wave travel time

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Authors: Mei Han, Jinkou Zhao, Yuan Yao, Liangui Feng, Xianbin Ding, Guohui Wu, Chao Zhou, Lin Ouyang, Rongrong Lu, Bo Zhang

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To compare the HIV incidence estimated using BED capture enzyme linked immunosorbent assay (BED-CEIA) and observed in a cohort against the HIV incidence among men who have sex with men (MSM) measured by pooling polymerase chain reaction (pooling-PCR). A total of 617 MSM subjects were included in a respondent driven sampling survey in Chongqing in 2008. Among the 129 that were tested HIV antibody positive, 102 were defined with long-term infection, 27 were assessed for recent HIV infection (RHI) using BED-CEIA. The remaining 488 HIV negative subjects were enrolled to the prospective cohort and followed-up every 6 months to monitor HIV seroconversion. All of the 488 HIV negative specimens were assessed for acute HIV infection (AHI) using pooling-PCR. Among the 488 negative subjects in the open cohort, 214 (43.9%) were followed-up for six months, with 107 person-years of observation and 14 subjects seroconverted. The observed HIV incidence was 12.5 per 100 person-years (95% CI=9.1-15.7). Among the 488 HIV negative specimens, 5 were identified with acute HIV infection using pooling-PCR at an annual rate of 14.02% (95% CI=1.73-26.30). The estimated HIV-1 incidence was 12.02% (95% CI=7.49-16.56) based on BED-CEIA. The HIV incidence estimated with three different approaches was different among subgroups. In the highly HIV prevalent MSM, it costs US$ 1724 to detect one AHI case, while detection of one case of RHI with BED assay costs only US$ 42. Three approaches generated comparable and high HIV incidences, pooling PCR and prospective cohort are more close to the true level of incidence, while BED-CEIA seemed to be the most convenient and economical approach for at-risk population’s HIV incidence evaluation at the beginning of HIV pandemic. HIV-1 incidences were alarmingly high among MSM population in Chongqing, particularly within the subgroup under 25 years of age and those migrants aged between 25 to 34 years.

Keywords: BED-CEIA, HIV, incidence, pooled PCR, prospective cohort

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Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

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The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

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Authors: Belgherbi Aicha, Bessaid Abdelhafid

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In the recent years a great deal of research work has been devoted to the development of semi-automatic and automatic techniques for the analysis of abdominal CT images. The first and fundamental step in all these studies is the semi-automatic liver and spleen segmentation that is still an open problem. In this paper, a semi-automatic liver and spleen segmentation method by the mathematical morphology based on watershed algorithm has been proposed. Our algorithm is currency in two parts. In the first, we seek to determine the region of interest by applying the morphological to extract the liver and spleen. The second step consists to improve the quality of the image gradient. In this step, we propose a method for improving the image gradient to reduce the over-segmentation problem by applying the spatial filters followed by the morphological filters. Thereafter we proceed to the segmentation of the liver, spleen. The aim of this work is to develop a method for semi-automatic segmentation liver and spleen based on watershed algorithm, improve the accuracy and the robustness of the liver and spleen segmentation and evaluate a new semi-automatic approach with the manual for liver segmentation. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work. The system has been evaluated by computing the sensitivity and specificity between the semi-automatically segmented (liver and spleen) contour and the manually contour traced by radiological experts. Liver segmentation has achieved the sensitivity and specificity; sens Liver=96% and specif Liver=99% respectively. Spleen segmentation achieves similar, promising results sens Spleen=95% and specif Spleen=99%.

Keywords: CT images, liver and spleen segmentation, anisotropic diffusion filter, morphological filters, watershed algorithm

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Authors: Patrick M. Garvey, Roger P. Pech, Daniel M. Tompkins

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Competition is a widespread interaction and natural selection will encourage the development of mechanisms that recognise and respond to dominant competitors, if this information reduces the risk of a confrontation. As olfaction is the primary sense for most mammals, our research tested whether olfactory ‘eavesdropping’ mediates alien species interactions and whether we could exploit our understanding of this behaviour to create ‘super-lures’. We used a combination of pen and field experiments to evaluate the importance of this behaviour. In pen trials, stoats (Mustela erminea) were exposed to the body odour of three dominant predators (cat / ferret / African wild dog) and these scents were found to be attractive. A subsequent field trial tested whether attraction displayed towards predator odour, particularly ferret (Mustela furo) pheromones, could be replicated with invasive predators in the wild. We found that ferret odour significantly improved detection and activity of stoats and hedgehogs (Erinaceus europaeus), while also improving detections of ship rats (Rattus rattus). Our current research aims to identify the key components of ferret odour, using chemical analysis and behavioural experiments, so that we can produce ‘scent from a can’. A lure based on a competitors’ odour would be beneficial in many circumstances including: (i) where individuals display variability in attraction to food lures, (ii) there are plentiful food resources available, (iii) new immigrants arrive into an area, (iv) long-life lures are required. Pest management can therefore benefit by exploiting behavioural responses to odours to achieve conservation goals.

Keywords: predator interactions, invasive species, eavesdropping, semiochemicals

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Authors: Bangun F., Crevits B., Bellet T., Banet A., Boy G. A., Katili I.

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This paper seeks the incoherencies in cognitive process during an accident of Powered Two Wheelers (PTW) by understanding the factual sequences of events and causal relations for each case of accident. The principle of this approach is undertaking in-depth investigations on case per case of PTW accidents based on elaborate data acquisitions on accident sites that officially stamped in Police Crash Report (PCRs) 2012 of Medan with criteria, involved at least one PTW and resulted in serious injury and fatalities. The analysis takes into account four modules: accident chronologies, perpetrator, and victims, injury surveillance, vehicles and road infrastructures, comprising of traffic facilities, road geometry, road alignments and weather. The proposal for improvement could have provided a favorable influence on the chain of functional processes and events leading to collision. Decision Aiding Processes (DAP) assists in structuring different entities at different decisional levels, as each of these entities has its own objectives and constraints. The entities (A) are classified into 6 groups of accidents: solo PTW accidents; PTW vs. PTW; PTW vs. pedestrian; PTW vs. motor-trishaw; and PTW vs. other vehicles and consecutive crashes. The entities are also distinguished into 4 decisional levels: level of road users and street systems; operational level (crash-attended police officers or CAPO and road engineers), tactical level (Regional Traffic Police, Department of Transportation, and Department of Public Work), and strategic level (Traffic Police Headquarters (TCPHI)), parliament, Ministry of Transportation and Ministry of Public Work). These classifications will lead to conceptualization of Problem Situations (P) and Problem Formulations (I) in DAP context. The DAP concerns the sequences process of the incidents until the time the accident occurs, which can be modelled in terms of five activities of procedural rationality: identification on initial human features (IHF), investigation on proponents attributes (PrAT), on Injury Surveillance (IS), on the interaction between IHF and PrAt and IS (intercorrelation), then unravel the sequences of incidents; filtering and disclosure, which include: what needs to activate, modify or change or remove, what is new and what is priority. These can relate to the activation or modification or new establishment of law. The PrAt encompasses the problems of environmental, road infrastructure, road and traffic facilities, and road geometry. The evaluation model (MP) is generated to bridge P and I since MP is produced by the intercorrelations among IHF, PrAT and IS extracted from the PCRs 2012 of Medan. There are 7 findings of incoherences: lack of knowledge and awareness on the traffic regulations and the risks of accidents, especially when riding between 0 < x < 10 km from house, riding between 22 p.m.–05.30 a.m.; lack of engagements on procurement of IHF Data by CAPO; lack of competency of CAPO on data procurement in accident-sites; no intercorrelation among IHF and PrAt and IS in the database systems of PCRs; lack of maintenance and supervision on the availabilities and the capacities of traffic facilities and road infrastructure; instrumental bias with wash-back impacts towards the TCPHI; technical robustness with wash-back impacts towards the CAPO and TCPHI.

Keywords: decision aiding processes, evaluation model, PTW accidents, police crash reports

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Authors: Yogesh Kumar, Adarsh Kumar

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A body farm is a research facility where research is done on forensic investigation and medico-legal disciplines like forensic entomology, forensic pathology, forensic anthropology, forensic archaeology, and related areas of forensic veterinary. All the research is done to collect data on the rate of decomposition (animal and human) and forensically important insects to assist in crime detection. The data collected is used by forensic pathologists, forensic experts, and other experts for the investigation of crime cases and further research. The research work includes different conditions of a dead body like fresh, bloating, decay, dry, and skeleton, and data on local insects which depends on the climatic conditions of the local areas of that country. Therefore, it is the need of time to collect appropriate data in managed conditions with a proper set-up in every country. Hence, it is the duty of the scientific community of every country to establish/propose such facilities for justice and social management. The body farms are also used for training of police, military, investigative dogs, and other agencies. At present, only four countries viz. U.S., Australia, Canada, and Netherlands have body farms and related facilities in organised manner. There is no body farm in Asia also. In India, we have been trying to establish a body farm in A&N Islands that is near Singapore, Malaysia, and some other Asian countries. In view of the above, it becomes imperative to discuss the matter with Asian countries to collect the data on decomposition in a proper manner by establishing a body farm. We can also share the data, knowledge, and expertise to collaborate with one another to make such facilities better and have good scientific relations to promote science and explore ways of investigation at the world level.

Keywords: body farm, rate of decomposition, forensically important flies, time since death

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Authors: Herke Csongor

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The artificial intelligence (AI) has been used in the United States of America in the decisionmaking process of the criminal justice system for decades. In the field of law, including criminal law, AI can provide serious assistance in decision-making in many places. The paper reviews four main areas where AI still plays a role in the criminal justice system and where it is expected to play an increasingly important role. The first area is the predictive policing: a number of algorithms are used to prevent the commission of crimes (by predicting potential crime locations or perpetrators). This may include the so-called linking hot-spot analysis, crime linking and the predictive coding. The second area is the Big Data analysis: huge amounts of data sets are already opaque to human activity and therefore unprocessable. Law is one of the largest producers of digital documents (because not only decisions, but nowadays the entire document material is available digitally), and this volume can only and exclusively be handled with the help of computer programs, which the development of AI systems can have an increasing impact on. The third area is the criminal statistical data analysis. The collection of statistical data using traditional methods required enormous human resources. The AI is a huge step forward in that it can analyze the database itself, based on the requested aspects, a collection according to any aspect can be available in a few seconds, and the AI itself can analyze the database and indicate if it finds an important connection either from the point of view of crime prevention or crime detection. Finally, the use of AI during decision-making in both investigative and judicial fields is analyzed in detail. While some are skeptical about the future role of AI in decision-making, many believe that the question is not whether AI will participate in decision-making, but only when and to what extent it will transform the current decision-making system.

Keywords: artificial intelligence, international criminal cooperation, planning and organizing of the investigation, risk assessment

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Authors: Chia-Ting Chang, Chia-Yu Lin

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We report on the decisive role of iron phosphate (FePO₄), formed in-situ during the electrochemical characterization, played in the electrocatalytic activity, especially its oxygen tolerance of iron oxides towards H₂O₂ reduction. Iron oxides studied including, Nanorod arrays (NRs) of β-FeOOH, γ-Fe₂O₃, α-Fe₂O₃, α-Fe₂O₃ nanosheets (α-Fe₂O₃NS), α-Fe₂O₃ nanoparticles (α-Fe₂O₃NP), were synthesized using chemical bath deposition. The nanostructure was controlled simply by adjusting the composition of precursor solution and reaction duration for CBD process, whereas the crystal phase was controlled by adjusting the annealing temperature. It was found that iron phosphate (FePO₄) was deposited in-situ onto the surface of this nanostructured α-Fe₂O₃ during the electrochemical pretreatment in the phosphate electrolyte, and both FePO₄ and α-Fe₂O₃ showed the activity in catalysing the electrochemical reduction of H₂O₂. In addition, the interaction/compatibility between deposited FePO₄ and iron oxides has a decisive effect on the overall electrocatalytic activity of the resultant electrodes; FePO₄ only showed synergetic effect on the overall electrocatalytic activity of α-Fe₂O₃NR and α-Fe2O₃NS. Both α-Fe₂O₃NR and α-Fe₂O₃NS showed two reduction peaks in phosphate electrolyte containing H₂O₂, one being pH-dependent and related to the electrocatalytic properties of FePO₄, and the other one being pH-independent and only related to the intrinsic electrocatalytic properties of α-Fe₂O₃NR and α-Fe₂O₃NS. However, all iron oxides showed only one pH-independent reductive peak in non-phosphate electrolyte containing H₂O₂. The synergesitic catalysis exerted by FePO₄ with α-Fe₂O₃NR or α-Fe₂O₃NS providing additional oxygen-insensitive active site for H₂O₂ reduction, which allows their applications to electrochemical detection of H₂O₂ without the interference of O₂ involving in oxidase-catalyzed chemical processes.

Keywords: H₂O₂ reduction, Iron oxide, iron phosphate, O₂ tolerance

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Authors: Krish Jhurani

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The research paper presents an in-depth analysis of symmetry properties in linear algebraic systems under the operation of non-canonical scalar multiplication structures, specifically semirings, and near-rings. The objective is to unveil the profound alterations that occur in traditional linear algebraic structures when we replace conventional field multiplication with these non-canonical operations. In the methodology, we first establish the theoretical foundations of non-canonical scalar multiplication, followed by a meticulous investigation into the resulting symmetry properties, focusing on eigenvectors, eigenspaces, and invariant subspaces. The methodology involves a combination of rigorous mathematical proofs and derivations, supplemented by illustrative examples that exhibit these discovered symmetry properties in tangible mathematical scenarios. The core findings uncover unique symmetry attributes. For linear algebraic systems with semiring scalar multiplication, we reveal eigenvectors and eigenvalues. Systems operating under near-ring scalar multiplication disclose unique invariant subspaces. These discoveries drastically broaden the traditional landscape of symmetry properties in linear algebraic systems. With the application of these findings, potential practical implications span across various fields such as physics, coding theory, and cryptography. They could enhance error detection and correction codes, devise more secure cryptographic algorithms, and even influence theoretical physics. This expansion of applicability accentuates the significance of the presented research. The research paper thus contributes to the mathematical community by bringing forth perspectives on linear algebraic systems and their symmetry properties through the lens of non-canonical scalar multiplication, coupled with an exploration of practical applications.

Keywords: eigenspaces, eigenvectors, invariant subspaces, near-rings, non-canonical scalar multiplication, semirings, symmetry properties

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Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

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Authors: Norah Al Hokbany, Ibrahim Al Jammaz, Basem Al Otaibi, Yousif Al Malki, Subhani M. Okarvi

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Objective: The folate receptor is over-expressed in a wide variety of human tumors. Conjugates of folate have been shown to be selectively taken up by tumor cells via the folate receptor. In an attempt to develop new folate radiotracers with favorable biochemical properties for detecting folate receptor-positive cancers. Methods: we synthesized ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugates using a straightforward and simple one-step reaction. Radiochemical yields were greater than 95% (decay-corrected) with a total synthesis time of less than 20 min. Results: Radiochemical purities were always greater than 98% without high-performance liquid chromatography (HPLC) purification. These synthetic approaches hold considerable promise as a rapid and simple method for ⁶⁴Cu-folate conjugate preparation with high radiochemical yield in a short synthesis time. In vitro tests on the KB cell line showed that significant amounts of the radio conjugates were associated with cell fractions. Bio-distribution studies in nude mice bearing human KB xenografts demonstrated a significant tumor uptake and favorable bio-distribution profile for ⁶⁴Cu-NOTA- and ⁶⁴Cu-NOTAM-folate conjugate. The uptake in the tumors was blocked by the excess injection of folic acid, suggesting a receptor-mediated process. Conclusion: These results demonstrate that the ⁶⁴Cu-NOTAM-folate conjugate may be useful as a molecular probe for the detection and staging of folate receptor-positive cancers, such as ovarian cancer and their metastasis, as well as monitoring tumor response to treatment.

Keywords: folate, receptor, tumor imaging, ⁶⁴Cu-NOTA-folate, PET

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Authors: Revalin Herdianto

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Recent climate changes increase uncertainties in vegetation conditions such as health and biomass globally and locally. The detection is, however, difficult due to the spatial and temporal scale of vegetation coverage. Due to unique vegetation response to its environmental conditions such as water availability, the interplay between vegetation dynamics and hydrologic conditions leave a signature in their feedback relationship. Vegetation indices (VI) depict vegetation biomass and photosynthetic capacity that indicate vegetation dynamics as a response to variables including hydrologic conditions and microclimate factors such as rainfall characteristics and land surface temperature (LST). It is hypothesized that the signature may be depicted by VI in its relationship with other variables. To study this signature, several catchments in Asia, Australia, and Indonesia were analysed to assess the variations in hydrologic characteristics with vegetation types. Methods used in this study includes geographic identification and pixel marking for studied catchments, analysing time series of VI and LST of the marked pixels, smoothing technique using Savitzky-Golay filter, which is effective for large area and extensive data. Time series of VI, LST, and rainfall from satellite and ground stations coupled with digital elevation models were analysed and presented. This study found that the hydrologic response of vegetation to rainfall variations may be shown in one hydrologic year, in which a drought event can be detected a year later as a suppressed growth. However, an annual rainfall of above average do not promote growth above average as shown by VI. This technique is found to be a robust and tractable approach for assessing catchment dynamics in changing climates.

Keywords: vegetation indices, land surface temperature, vegetation dynamics, catchment

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Authors: Alessandro Preziosi, Antonio Prioletti, Luca Castangia

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Deformable part models achieve high precision in pedestrian recognition, but all publicly available implementations are too slow for real-time applications. We implemented a deformable part model algorithm fast enough for real-time use by exploiting information about the camera position and orientation. This implementation is both faster and more precise than alternative DPM implementations. These results are obtained by computing convolutions in the frequency domain and using lookup tables to speed up feature computation. This approach is almost an order of magnitude faster than the reference DPM implementation, with no loss in precision. Knowing the position of the camera with respect to horizon it is also possible prune many hypotheses based on their size and location. The range of acceptable sizes and positions is set by looking at the statistical distribution of bounding boxes in labelled images. With this approach it is not needed to compute the entire feature pyramid: for example higher resolution features are only needed near the horizon. This results in an increase in mean average precision of 5% and an increase in speed by a factor of two. Furthermore, to reduce misdetections involving small pedestrians near the horizon, input images are supersampled near the horizon. Supersampling the image at 1.5 times the original scale, results in an increase in precision of about 4%. The implementation was tested against the public KITTI dataset, obtaining an 8% improvement in mean average precision over the best performing DPM-based method. By allowing for a small loss in precision computational time can be easily brought down to our target of 100ms per image, reaching a solution that is faster and still more precise than all publicly available DPM implementations.

Keywords: autonomous vehicles, deformable part model, dpm, pedestrian detection, real time

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Authors: Tobias Huwer, Thomas Bobek, Gunter Spöcker

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Driving forces for enhancements in production are trends like digitalization and individualized production. Currently, such developments are restricted to assembly parts. Thus, complex freeform surfaces are not addressed in this context. The need for efficient use of resources and near-net-shape production will require individualized production of complex shaped workpieces. Due to variations between nominal model and actual geometry, this can lead to changes in operations in Computer-aided process planning (CAPP) to make CAPP manageable for an adaptive serial production. In this context, 3D CAD data can be a key to realizing that objective. Along with developments in the geometrical adaptation, a preceding inspection method based on CAD data is required to support the process planner by finding objective criteria to make decisions about the adaptive manufacturability of workpieces. Nowadays, this kind of decisions is depending on the experience-based knowledge of humans (e.g. process planners) and results in subjective decisions – leading to a variability of workpiece quality and potential failure in production. In this paper, we present an automatic part inspection method, based on design and measurement data, which evaluates actual geometries of single workpiece preforms. The aim is to automatically determine the suitability of the current shape for further machining, and to provide a basis for an objective decision about subsequent adaptive manufacturability. The proposed method is realized by a workflow-based approach, keeping in mind the requirements of industrial applications. Workflows are a well-known design method of standardized processes. Especially in applications like aerospace industry standardization and certification of processes are an important aspect. Function blocks, providing a standardized, event-driven abstraction to algorithms and data exchange, will be used for modeling and execution of inspection workflows. Each analysis step of the inspection, such as positioning of measurement data or checking of geometrical criteria, will be carried out by function blocks. One advantage of this approach is its flexibility to design workflows and to adapt algorithms specific to the application domain. In general, within the specified tolerance range it will be checked if a geometrical adaption is possible. The development of particular function blocks is predicated on workpiece specific information e.g. design data. Furthermore, for different product lifecycle phases, appropriate logics and decision criteria have to be considered. For example, tolerances for geometric deviations are different in type and size for new-part production compared to repair processes. In addition to function blocks, appropriate referencing systems are important. They need to support exact determination of position and orientation of the actual geometries to provide a basis for precise analysis. The presented approach provides an inspection methodology for adaptive and part-individual process chains. The analysis of each workpiece results in an inspection protocol and an objective decision about further manufacturability. A representative application domain is the product lifecycle of turbine blades containing a new-part production and a maintenance process. In both cases, a geometrical adaptation is required to calculate individual production data. In contrast to existing approaches, the proposed initial inspection method provides information to decide between different potential adaptive machining processes.

Keywords: adaptive, CAx, function blocks, turbomachinery

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Authors: Vahid Saatchian, Seyyed Farideh Hadavi

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The main aim of this study was developing the collaboration model of physical education and sport sciences faculties with service section of sport industrial.The research methods of this study was a qualitative. So researcher with of identifying the priority list of collaboration between colleges and service section of sport industry and according to sampling based of subjective and snowball approach, conducted deep interviews with 22 elites that study around the field of research topic. indeed interviews were analyzed through qualitative coding (open, axial and selective) with 5 category such as causal condition, basic condition, intervening conditions, action/ interaction and strategy. Findings exposed that in causal condition 10 labels appeared. So because of heterogeneity of labes, researcher categorized in total subject. In basic condition 59 labels in open coding identified this categorized in 14 general concepts. Furthermore with composition of the declared category and relationship between them, 5 final and internal categories (culture, intelligence, marketing, environment and ultra-powers) were appeared. Also an intervening condition in the study includes 5 overall scopes of social factors, economic, cultural factors, and the management of the legal and political factors that totally named macro environment. Indeed for identifying strategies, 8 areas that covered with internal and external challenges relationship management were appeared. These are including, understanding, outside awareness, manpower, culture, integrated management, the rules and regulations and marketing. Findings exposed 8 labels in open coding which covered the internal and external of challenges of relation management of two sides and these concepts were knowledge and awareness, external view, human source, madding organizational culture, parties’ thoughts, unit responsible for/integrated management, laws and regulations and marketing. Eventually the consequences categorized in line of strategies and were at scope of the cultural development, general development, educational development, scientific development, under development, international development, social development, economic development, technology development and political development that consistent with strategies. The research findings could help the sport managers witch use to scientific collaboration management and the consequences of this in those sport institutions. Finally, the consequences that identified as a result of the devopmental strategies include: cultural, governmental, educational, scientific, infrastructure, international, social, economic, technological and political that is largely consistent with strategies. With regard to the above results, enduring and systematic relation with long term cooperation between the two sides requires strategic planning were based on cooperation of all stakeholders. Through this, in the turbulent constantly changing current sustainable environment, competitive advantage for university and industry obtained. No doubt that lack of vision and strategic thinking for cooperation in the planning of the university and industry from its capability and instead of using the opportunity, lead the opportunities to problems.

Keywords: university and industry collaboration, sport industry, physical education and sport science college, service section of sport industry

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Authors: Prittesh Patel, Rushabh Shah, Krishnamurthy Ramar, Vakulbhushan Bhaskar

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The present research work aims at finding genetic differences in the genomes of sugarcane red rot isolates Colletotrichum falcatum Went using Random Amplified Polymorphic DNA (RAPD) and interspersed simple sequence repeat (ISSR) molecular markers. Ten isolates of C. falcatum isolated from different red rot infected sugarcane cultivars stalk were used in present study. The amplified bands were scored across the lanes obtained in 15 RAPD primes and 21 ISSR primes successfully. The data were analysed using NTSYSpc 2.2 software. The results showed 80.6% and 68.07% polymorphism in RPAD and ISSR analysis respectively. Based on the RAPD analysis, ten genotypes were grouped into two major clusters at a cut-off value of 0.75. Geographically distant C. falcatum isolate cfGAN from south Gujarat had a level of similarity with Coimbatore isolate cf8436 presented on separate clade of bootstrapped dendrograms. First and second cluster consisted of five and three isolates respectively, indicating the close relation among them. The 21 ISSR primers produced 119 distinct and scorable loci in that 38 were monomorphic. The number of scorable loci for each primer varied from 2 (ISSR822) to 8 (ISSR807, ISSR823 and ISSR15) with an average of 5.66 loci per primer. Primer ISSR835 amplified the highest number of bands (57), while only 16 bands were obtained by primers ISSR822. Four primers namely ISSR830, ISSR845, ISSR4 and ISSR15 showed the highest value of percentage of polymorphism (100%). The results indicated that both of the marker systems RAPD and ISSR, individually can be effectively used in determination of genetic relationship among C falcatum accessions collected from different parts of south Gujarat.

Keywords: Colletotrichum falcatum, ISSR, RAPD, Red Rot

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Authors: Amar Ramesh Wayal

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Marathi cinema, an integral part of India’s diverse film industry, has significantly evolved in its storytelling and aesthetics, with the Tamasha genre being central to this evolution. Tamasha, a traditional form of Marathi theatre, features vibrant dance and music, especially the rhythmic and often suggestive musical genre, lavani. It gained cinematic prominence in the 1960s with Anant Mane’s Sangtye Aika (1959), which brought and popularized Tamasha to the silver screen, and V. Shantaram’s Pinjra (1972), an iconic Tamasha drama. Despite early success, Tamasha films declined in popularity until Natarang (2010) revitalized interest in this traditional form. This study examines the relevance and evolution of the Tamasha genre in Marathi cinema through contemporary films like Ek Hota Vidushak by Jabbar Patel (1992), Natarang (2010) by Ravi Jadhav, and Tamasha Live (2022) by Sanjay Jadhav. The selection of the films is based on their significant roles in the evolution of the Tamasha in Marathi cinema. Ek Hota Vidushak explores socio-political themes through Tamasha, Natarang depicts the struggles and emotional depth of Tamasha performers, and Tamasha Live integrates traditional Tamasha into modern cinema. By analysing films from different periods, this study highlights the genre’s reinterpretation and adaptation over time. The study employs a qualitative approach, utilizing textual analysis and cultural critique to examine the portrayal and evolution of Tamasha in selected films. It aims to illuminate the complex relationship between tradition and modernity in Marathi cinema through Foucauldian discourse analysis and Pierre Bourdieu’s concept of “vernacular habitus,” which refers to local, indigenous cultural spaces that shape people’s perceptions and expressions. By analyzing these films, the study seeks to understand how traditional cultural forms are integrated into contemporary cinematic narratives. However, this method has limitations, such as subjectivity in interpretation and the need for extensive contextual knowledge. Qualitative research can be subject to researcher bias, affecting analysis and conclusions. To mitigate this, this study maintains rigorous reflexivity and transparency regarding the researcher’s positionality. Furthermore, findings from specific film analyses may not be universally applicable to all Tamasha films or broader Marathi cinema. To enhance the study’s robustness, future research could incorporate comparative or quantitative data to complement qualitative insights. Despite these challenges, qualitative research is crucial for exploring cultural artifacts and their significance within specific contexts. By triangulating qualitative findings with diverse perspectives and acknowledging limitations, this study aims to provide a nuanced understanding of how Tamasha cinema preserves and revitalizes Maharashtra’s folk traditions while adapting them to contemporary contexts. Analyzing films by Jabbar Patel, Ravi Jadhav, and Sanjay Jadhav shows how these filmmakers balance traditional aesthetics with modern storytelling, bridging historical continuity with contemporary relevance. This study offers insights into how indigenous traditions like Tamasha continue to shape and define cinematic narratives in Maharashtra.

Keywords: Marathi cinema, Tamasha genre, vernacular habitus, discourse analysis, cultural evolution

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Authors: Sanjeewa Seneviratne, Ian Campbell, Nina Scott, Ross Lawrenson

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Introduction: Indigenous Māori women experience a 60% higher breast cancer mortality rate compared with European women in New Zealand. We explored the impact of difference in the rate of screen detected breast cancer between Māori and European women on more advanced disease at diagnosis and lower survival in Māori women. Methods: All primary in-situ and invasive breast cancers diagnosed in screening age women (as defined by the New Zealand National Breast Cancer Screening Programme) between 1999 and 2012 in the Waikato area were identified from the Waikato Breast Cancer Register and the national screening database. Association between screen versus non-screen detection and cancer stage at diagnosis and survival were compared by ethnicity and socioeconomic deprivation. Results: Māori women had 50% higher odds of being diagnosed with more advance staged cancer compared with NZ European women, a half of which was explained by the lower rate of screen detected cancer in Māori women. Significantly lower breast cancer survival rates were observed for Māori compared with NZ European and most deprived compared with most affluent socioeconomic groups for symptomatically detected breast cancer. No significant survival differences by ethnicity or socioeconomic deprivation were observed for screen detected breast cancer. Conclusions: Low rate of screen detected breast cancer appears to be a major contributor for more advanced stage disease at diagnosis and lower breast cancer survival in Māori compared with NZ European women. Increasing screening participation for Māori has the potential to substantially reduce breast cancer mortality inequity between Māori and NZ European women.

Keywords: breast cancer, screening, ethnicity, inequity

Procedia PDF Downloads 511

Authors: Reza Soleimanpour, Ching Tai Ng

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Fibre-composites are widely used in various structures due to their attractive properties such as higher stiffness to mass ratio and better corrosion resistance compared to metallic materials. However, one serious weakness of this composite material is delamination, which is a subsurface separation of laminae. A low level of this barely visible damage can cause a significant reduction in residual compressive strength. In the last decade, the application of guided waves for damage detection has been a topic of significant interest for many researches. Among all guided wave techniques, nonlinear guided wave has shown outstanding sensitivity and capability for detecting different types of damages, e.g. cracks and delaminations. So far, most of researches on applications of nonlinear guided wave have been dedicated to isotropic material, such as aluminium and steel, while only a few works have been done on applications of nonlinear characteristics of guided waves in anisotropic materials. This study investigates the nonlinear interactions of the fundamental antisymmetric lamb wave (A0) with delamination in composite laminates using three-dimensional (3D) explicit finite element (FE) simulations. The nonlinearity considered in this study arises from interactions of two interfaces of sub-laminates at the delamination region, which generates contact acoustic nonlinearity (CAN). The aim of this research is to investigate the phenomena of CAN in composite laminated beams by a series of numerical case studies. In this study interaction of fundamental antisymmetric lamb wave with delamination of different sizes are studied in detail. The results show that the A0 lamb wave interacts with the delaminations generating CAN in the form of higher harmonics, which is a good indicator for determining the existence of delaminations in composite laminates.

Keywords: contact acoustic nonlinearity, delamination, fibre reinforced composite beam, finite element, nonlinear guided waves

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Authors: Numair Ahmed Siddiqui, Abdul Hadi bin Abd Rahman, Chow Weng Sum, Wan Ismail Wan Yousif, Asif Zameer, Joel Ben-Awal

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Advances in data capturing from outcrop studies have made possible the acquisition of high-resolution digital data, offering improved and economical reservoir modelling methods. Terrestrial laser scanning utilizing LiDAR (Light detection and ranging) provides a new method to build outcrop based reservoir models, which provide a crucial piece of information to understand heterogeneities in sandstone facies with high-resolution images and data set. This study presents the detailed application of outcrop based sandstone facies connectivity model by acquiring information gathered from traditional fieldwork and processing detailed digital point-cloud data from LiDAR to develop an intermediate small-scale reservoir sandstone facies model of the Miocene Sandakan Formation, Sabah, East Malaysia. The software RiScan pro (v1.8.0) was used in digital data collection and post-processing with an accuracy of 0.01 m and point acquisition rate of up to 10,000 points per second. We provide an accurate and descriptive workflow to triangulate point-clouds of different sets of sandstone facies with well-marked top and bottom boundaries in conjunction with field sedimentology. This will provide highly accurate qualitative sandstone facies connectivity model which is a challenge to obtain from subsurface datasets (i.e., seismic and well data). Finally, by applying this workflow, we can build an outcrop based static connectivity model, which can be an analogue to subsurface reservoir studies.

Keywords: LiDAR, outcrop, high resolution, sandstone faceis, connectivity model

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Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

Procedia PDF Downloads 179