Search results for: nonuniform signal processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4982

Search results for: nonuniform signal processing

1502 DNA Methylation Changes in Response to Ocean Acidification at the Time of Larval Metamorphosis in the Edible Oyster, Crassostrea hongkongensis

Authors: Yong-Kian Lim, Khan Cheung, Xin Dang, Steven Roberts, Xiaotong Wang, Vengatesen Thiyagarajan

Abstract:

Unprecedented rate of increased CO₂ level in the ocean and the subsequent changes in carbonate system including decreased pH, known as ocean acidification (OA), is predicted to disrupt not only the calcification process but also several other physiological and developmental processes in a variety of marine organisms, including edible oysters. Nonetheless, not all species are vulnerable to those OA threats, e.g., some species may be able to cope with OA stress using environmentally induced modifications on gene and protein expressions. For example, external environmental stressors, including OA, can influence the addition and removal of methyl groups through epigenetic modification (e.g., DNA methylation) process to turn gene expression “on or off” as part of a rapid adaptive mechanism to cope with OA. In this study, the above hypothesis was tested through testing the effect of OA, using decreased pH 7.4 as a proxy, on the DNA methylation pattern of an endemic and a commercially important estuary oyster species, Crassostrea hongkongensis, at the time of larval habitat selection and metamorphosis. Larval growth rate did not differ between control pH 8.1 and treatment pH 7.4. The metamorphosis rate of the pediveliger larvae was higher at pH 7.4 than those in control pH 8.1; however, over one-third of the larvae raised at pH 7.4 failed to attach to an optimal substrate as defined by biofilm presence. During larval development, a total of 130 genes were differentially methylated across the two treatments. The differential methylation in the larval genes may have partially accounted for the higher metamorphosis success rate under decreased pH 7.4 but with poor substratum selection ability. Differentially methylated loci were concentrated in the exon regions and appear to be associated with cytoskeletal and signal transduction, oxidative stress, metabolic processes, and larval metamorphosis, which implies the high potential of C. hongkongensis larvae to acclimate and adapt through non-genetic ways to OA threats within a single generation.

Keywords: adaptive plasticity, DNA methylation, larval metamorphosis, ocean acidification

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1501 Predictive Maintenance of Industrial Shredders: Efficient Operation through Real-Time Monitoring Using Statistical Machine Learning

Authors: Federico Pittino, Thomas Arnold

Abstract:

The shredding of waste materials is a key step in the recycling process towards the circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need for frequent maintenance of critical components. Maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for one year, and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for the efficient operation of industrial shredders.

Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning

Procedia PDF Downloads 118
1500 Camptothecin Promotes ROS-Mediated G2/M Phase Cell Cycle Arrest, Resulting from Autophagy-Mediated Cytoprotection

Authors: Rajapaksha Gedara Prasad Tharanga Jayasooriya, Matharage Gayani Dilshara, Yung Hyun Choi, Gi-Young Kim

Abstract:

Camptothecin (CPT) is a quinolone alkaloid which inhibits DNA topoisomerase I that induces cytotoxicity in a variety of cancer cell lines. We previously showed that CPT effectively inhibited invasion of prostate cancer cells and also combined treatment with subtoxic doses of CPT and TNF-related apoptosis-inducing ligand (TRAIL) potentially enhanced apoptosis in a caspase-dependent manner in hepatoma cancer cells. Here, we found that treatment with CPT caused an irreversible cell cycle arrest in the G2/M phase. CPT-induced cell cycle arrest was associated with a decrease in protein levels of cell division cycle 25C (Cdc25C) and increased the level of cyclin B and p21. The CPT-induced decrease in Cdc25C was blocked in the presence of proteasome inhibitor MG132, thus reversed the cell cycle arrest. In addition to that treatment of CPT-increased phosphorylation of Cdc25C was the resulted of activation of checkpoint kinase 2 (Chk2), which was associated with phosphorylation of ataxia telangiectasia-mutated. Interestingly CPT induced G2/M phase of the cell cycle arrest is reactive oxygen species (ROS) dependent where ROS inhibitors NAC and GSH reversed the CPT-induced cell cycle arrest. These results further confirm by using transient knockdown of nuclear factor-erythroid 2-related factor 2 (Nrf2) since it regulates the production of ROS. Our data reveal that treatment of siNrf2 increased the ROS level as well as further increased the CPT induce G2/M phase cell cycle arrest. Our data also indicate CPT-enhanced cell cycle arrest through the extracellular signal-regulated kinase (ERK) and the c-Jun N-terminal kinase (JNK) pathway. Inhibitors of ERK and JNK more decreased the Cdc25C expression and protein expression of p21 and cyclin B. These findings indicate that Chk2-mediated phosphorylation of Cdc25C plays a major role in G2/M arrest by CPT.

Keywords: camptothecin, cell cycle, checkpoint kinase 2, nuclear factor-erythroid 2-related factor 2, reactive oxygen species

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1499 Stability of Novel Peptides (Linusorbs) in Flaxseed Meal Fortified Gluten-Free Bread

Authors: Youn Young Shim, Martin J. T. Reaney

Abstract:

Flaxseed meal is rich in water-soluble gums and, as such, can improve texture in gluten-free products. Flaxseed bioactive-antioxidant peptides, linusorbs (LOs, a.k.a. cyclolinopeptides), are a class of molecules that may contribute health-promoting effects. The effects of dough preparation, baking, and storage on flaxseed-derived LOs stability in doughs and baked products are un-known. Gluten-free (GF) bread dough and bread were prepared with flaxseed meal and the LO content was determined in the flaxseed meal, bread flour containing the flaxseed meal, bread dough, and bread. The LO contents during storage (0, 1, 2, and 4 weeks) at different temperatures (−18 °C, 4 °C, and 22−23 °C) were determined by high-performance liquid chromatog-raphy-diode array detection (HPLC-DAD). The content of oxidized LOs like [1–9-NαC],[1(Rs, Ss)-MetO]-linusorb B2 (LO14) were substantially constant in flaxseed meal and flour produced from flaxseed meal under all conditions for up to 4 weeks. However, during GF-bread production LOs decreased. Due to microbial contamination dough could not be stored at either 4 or 21°C, and bread could only be stored for one week at 21°C. Up to 4 weeks storage was possible for bread and dough at −18 °C and bread at 4 °C without the loss of LOs. The LOs change mostly from processing and less so from storage. The concentration of reduced LOs in flour and meal were much higher than measured in dough and bread. There was not a corre-sponding increase in oxidized LOs. The LOs in flaxseed meal-fortified bread were stable for products stored at low temperatures. This study is the first of the impact of baking conditions on LO content and quality.

Keywords: flaxseed, stability, gluten-free, antioxidant

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1498 Brain-Computer Interfaces That Use Electroencephalography

Authors: Arda Ozkurt, Ozlem Bozkurt

Abstract:

Brain-computer interfaces (BCIs) are devices that output commands by interpreting the data collected from the brain. Electroencephalography (EEG) is a non-invasive method to measure the brain's electrical activity. Since it was invented by Hans Berger in 1929, it has led to many neurological discoveries and has become one of the essential components of non-invasive measuring methods. Despite the fact that it has a low spatial resolution -meaning it is able to detect when a group of neurons fires at the same time-, it is a non-invasive method, making it easy to use without possessing any risks. In EEG, electrodes are placed on the scalp, and the voltage difference between a minimum of two electrodes is recorded, which is then used to accomplish the intended task. The recordings of EEGs include, but are not limited to, the currents along dendrites from synapses to the soma, the action potentials along the axons connecting neurons, and the currents through the synaptic clefts connecting axons with dendrites. However, there are some sources of noise that may affect the reliability of the EEG signals as it is a non-invasive method. For instance, the noise from the EEG equipment, the leads, and the signals coming from the subject -such as the activity of the heart or muscle movements- affect the signals detected by the electrodes of the EEG. However, new techniques have been developed to differentiate between those signals and the intended ones. Furthermore, an EEG device is not enough to analyze the data from the brain to be used by the BCI implication. Because the EEG signal is very complex, to analyze it, artificial intelligence algorithms are required. These algorithms convert complex data into meaningful and useful information for neuroscientists to use the data to design BCI devices. Even though for neurological diseases which require highly precise data, invasive BCIs are needed; non-invasive BCIs - such as EEGs - are used in many cases to help disabled people's lives or even to ease people's lives by helping them with basic tasks. For example, EEG is used to detect before a seizure occurs in epilepsy patients, which can then prevent the seizure with the help of a BCI device. Overall, EEG is a commonly used non-invasive BCI technique that has helped develop BCIs and will continue to be used to detect data to ease people's lives as more BCI techniques will be developed in the future.

Keywords: BCI, EEG, non-invasive, spatial resolution

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1497 Natural Fibre Composite Structural Sections for Residential Stud Wall Applications

Authors: Mike R. Bambach

Abstract:

Increasing awareness of environmental concerns is leading a drive towards more sustainable structural products for the built environment. Natural fibres such as flax, jute and hemp have recently been considered for fibre-resin composites, with a major motivation for their implementation being their notable sustainability attributes. While recent decades have seen substantial interest in the use of such natural fibres in composite materials, much of this research has focused on the materials aspects, including fibre processing techniques, composite fabrication methodologies, matrix materials and their effects on the mechanical properties. The present study experimentally investigates the compression strength of structural channel sections of flax, jute and hemp, with a particular focus on their suitability for residential stud wall applications. The section geometry is optimised for maximum strength via the introduction of complex stiffeners in the webs and flanges. Experimental results on both natural fibre composite channel sections and typical steel and timber residential wall studs are compared. The geometrically optimised natural fibre composite channels are shown to have compression capacities suitable for residential wall stud applications, identifying them as a potentially viable alternative to traditional building materials in such application, and potentially other light structural applications.

Keywords: channel sections, natural fibre composites, residential stud walls, structural composites

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1496 Preparation and Characterization of Iron/Titanium-Pillared Clays

Authors: Rezala Houria, Valverde Jose Luis, Romero Amaya, Molinari Alessandra, Maldotti Andrea

Abstract:

The escalation of oil prices in 1973 confronted the oil industry with the problem of how to maximize the processing of crude oil, especially the heavy fractions, to give gasoline components. Strong impetus was thus given to the development of catalysts with relatively large pore sizes, which were able to deal with larger molecules than the existing molecular sieves, and with good thermal and hydrothermal stability. The oil embargo in 1973 therefore acted as a stimulus for the investigation and development of pillared clays. Iron doped titania-pillared montmorillonite clays was prepared using bentonite from deposits of Maghnia in western-Algeria. The preparation method consists of differents steps (purification of the raw bentonite, preparation of a pillaring agent solution and exchange of the cations located between the clay layers with the previously formed iron/titanium solution). The characterization of this material was carried out by X-ray fluorescence spectrometry, X-ray diffraction, textural measures by BET method, inductively coupled plasma atomic emission spectroscopy, diffuse reflectance UV visible spectroscopy, temperature- programmed desorption of ammonia and atomic absorption.This new material was investigated as photocatalyst for selective oxygenation of the liquid alkylaromatics such as: toluene, paraxylene and orthoxylene and the photocatalytic properties of it were compared with those of the titanium-pillared clays.

Keywords: iron doping, montmorillonite clays, pillared clays, oil industry

Procedia PDF Downloads 301
1495 A Verification Intellectual Property for Multi-Flow Rate Control on Any Single Flow Bus Functional Model

Authors: Pawamana Ramachandra, Jitesh Gupta, Saranga P. Pogula

Abstract:

In verification of high volume and complex packet processing IPs, finer control of flow management aspects (for example, rate, bits/sec etc.) per flow class (or a virtual channel or a software thread) is needed. When any Software/Universal Verification Methodology (UVM) thread arbitration is left to the simulator (e.g., Verilog Compiler Simulator (VCS) or Incisive Enterprise Simulator core simulation engine (NCSIM)), it is hard to predict its pattern of resulting distribution of bandwidth by the simulator thread arbitration. In many cases, the patterns desired in a test scenario may not be accomplished as the simulator might give a different distribution than what was required. This can lead to missing multiple traffic scenarios, specifically deadlock and starvation related. We invented a component (namely Flow Manager Verification IP) to be intervening between the application (test case) and the protocol VIP (with UVM sequencer) to control the bandwidth per thread/virtual channel/flow. The Flow Manager has knobs visible to the UVM sequence/test to configure the required distribution of rate per thread/virtual channel/flow. This works seamlessly and produces rate stimuli to further harness the Design Under Test (DUT) with asymmetric inputs compared to the programmed bandwidth/Quality of Service (QoS) distributions in the Design Under Test.

Keywords: flow manager, UVM sequencer, rated traffic generation, quality of service

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1494 Process Optimization for Albanian Crude Oil Characterization

Authors: Xhaklina Cani, Ilirjan Malollari, Ismet Beqiraj, Lorina Lici

Abstract:

Oil characterization is an essential step in the design, simulation, and optimization of refining facilities. To achieve optimal crude selection and processing decisions, a refiner must have exact information refer to crude oil quality. This includes crude oil TBP-curve as the main data for correct operation of refinery crude oil atmospheric distillation plants. Crude oil is typically characterized based on a distillation assay. This procedure is reasonably well-defined and is based on the representation of the mixture of actual components that boil within a boiling point interval by hypothetical components that boil at the average boiling temperature of the interval. The crude oil assay typically includes TBP distillation according to ASTM D-2892, which can characterize this part of oil that boils up to 400 C atmospheric equivalent boiling point. To model the yield curves obtained by physical distillation is necessary to compare the differences between the modelling and the experimental data. Most commercial use a different number of components and pseudo-components to represent crude oil. Laboratory tests include distillations, vapor pressures, flash points, pour points, cetane numbers, octane numbers, densities, and viscosities. The aim of the study is the drawing of true boiling curves for different crude oil resources in Albania and to compare the differences between the modeling and the experimental data for optimal characterization of crude oil.

Keywords: TBP distillation curves, crude oil, optimization, simulation

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1493 Implementation Association Rule Method in Determining the Layout of Qita Supermarket as a Strategy in the Competitive Retail Industry in Indonesia

Authors: Dwipa Rizki Utama, Hanief Ibrahim

Abstract:

The development of industry retail in Indonesia is very fast, various strategy was undertaken to boost the customer satisfaction and the productivity purchases to boost the profit, one of which is implementing strategies layout. The purpose of this study is to determine the layout of Qita supermarket, a retail industry in Indonesia, in order to improve customer satisfaction and to maximize the rate of products’ sale as a whole, so as the infrequently purchased products will be purchased. This research uses a literature study method, and one of the data mining methods is association rule which applied in market basket analysis. Data were tested amounted 100 from 160 after pre-processing data, so then the distribution department and 26 departments corresponding to the data previous layout will be obtained. From those data, by the association rule method, customer behavior when purchasing items simultaneously can be studied, so then the layout of the supermarket based on customer behavior can be determined. Using the rapid miner software by the minimal support 25% and minimal confidence 30% showed that the 14th department purchased at the same time with department 10, 21st department purchased at the same time with department 13, 15th department purchased at the same time with department 12, 14th department purchased at the same time with department 12, and 10th department purchased at the same time with department 14. From those results, a better supermarket layout can be arranged than the previous layout.

Keywords: industry retail, strategy, association rule, supermarket

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1492 Design of a Photovoltaic Power Generation System Based on Artificial Intelligence and Internet of Things

Authors: Wei Hu, Wenguang Chen, Chong Dong

Abstract:

In order to improve the efficiency and safety of photovoltaic power generation devices, this photovoltaic power generation system combines Artificial Intelligence (AI) and the Internet of Things (IoT) to control the chasing photovoltaic power generation device to track the sun to improve power generation efficiency and then convert energy management. The system uses artificial intelligence as the control terminal, the power generation device executive end uses the Linux system, and Exynos4412 is the CPU. The power generating device collects the sun image information through Sony CCD. After several power generating devices feedback the data to the CPU for processing, several CPUs send the data to the artificial intelligence control terminal through the Internet. The control terminal integrates the executive terminal information, time information, and environmental information to decide whether to generate electricity normally and then whether to convert the converted electrical energy into the grid or store it in the battery pack. When the power generation environment is abnormal, the control terminal authorizes the protection strategy, the power generation device executive terminal stops power generation and enters a self-protection posture, and at the same time, the control terminal synchronizes the data with the cloud. At the same time, the system is more intelligent, more adaptive, and longer life.

Keywords: photo-voltaic power generation, the pursuit of light, artificial intelligence, internet of things, photovoltaic array, power management

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1491 A Transformer-Based Question Answering Framework for Software Contract Risk Assessment

Authors: Qisheng Hu, Jianglei Han, Yue Yang, My Hoa Ha

Abstract:

When a company is considering purchasing software for commercial use, contract risk assessment is critical to identify risks to mitigate the potential adverse business impact, e.g., security, financial and regulatory risks. Contract risk assessment requires reviewers with specialized knowledge and time to evaluate the legal documents manually. Specifically, validating contracts for a software vendor requires the following steps: manual screening, interpreting legal documents, and extracting risk-prone segments. To automate the process, we proposed a framework to assist legal contract document risk identification, leveraging pre-trained deep learning models and natural language processing techniques. Given a set of pre-defined risk evaluation problems, our framework utilizes the pre-trained transformer-based models for question-answering to identify risk-prone sections in a contract. Furthermore, the question-answering model encodes the concatenated question-contract text and predicts the start and end position for clause extraction. Due to the limited labelled dataset for training, we leveraged transfer learning by fine-tuning the models with the CUAD dataset to enhance the model. On a dataset comprising 287 contract documents and 2000 labelled samples, our best model achieved an F1 score of 0.687.

Keywords: contract risk assessment, NLP, transfer learning, question answering

Procedia PDF Downloads 128
1490 Continuous Measurement of Spatial Exposure Based on Visual Perception in Three-Dimensional Space

Authors: Nanjiang Chen

Abstract:

In the backdrop of expanding urban landscapes, accurately assessing spatial openness is critical. Traditional visibility analysis methods grapple with discretization errors and inefficiencies, creating a gap in truly capturing the human experi-ence of space. Addressing these gaps, this paper introduces a distinct continuous visibility algorithm, a leap in measuring urban spaces from a human-centric per-spective. This study presents a methodological breakthrough by applying this algorithm to urban visibility analysis. Unlike conventional approaches, this tech-nique allows for a continuous range of visibility assessment, closely mirroring hu-man visual perception. By eliminating the need for predefined subdivisions in ray casting, it offers a more accurate and efficient tool for urban planners and architects. The proposed algorithm not only reduces computational errors but also demonstrates faster processing capabilities, validated through a case study in Bei-jing's urban setting. Its key distinction lies in its potential to benefit a broad spec-trum of stakeholders, ranging from urban developers to public policymakers, aid-ing in the creation of urban spaces that prioritize visual openness and quality of life. This advancement in urban analysis methods could lead to more inclusive, comfortable, and well-integrated urban environments, enhancing the spatial experience for communities worldwide.

Keywords: visual openness, spatial continuity, ray-tracing algorithms, urban computation

Procedia PDF Downloads 41
1489 Taguchi-Based Six Sigma Approach to Optimize Surface Roughness for Milling Processes

Authors: Sky Chou, Joseph C. Chen

Abstract:

This paper focuses on using Six Sigma methodologies to improve the surface roughness of a manufactured part produced by the CNC milling machine. It presents a case study where the surface roughness of milled aluminum is required to reduce or eliminate defects and to improve the process capability index Cp and Cpk for a CNC milling process. The six sigma methodology, DMAIC (design, measure, analyze, improve, and control) approach, was applied in this study to improve the process, reduce defects, and ultimately reduce costs. The Taguchi-based six sigma approach was applied to identify the optimized processing parameters that led to the targeted surface roughness specified by our customer. A L9 orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of feed rate, depth of cut, spindle speed, and surface roughness. The noise factor is the difference between the old cutting tool and the new cutting tool. The confirmation run with the optimal parameters confirmed that the new parameter settings are correct. The new settings also improved the process capability index. The purpose of this study is that the Taguchi–based six sigma approach can be efficiently used to phase out defects and improve the process capability index of the CNC milling process.

Keywords: CNC machining, six sigma, surface roughness, Taguchi methodology

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1488 Assessment of Microbiological Feed Safety from Serbian Market from 2013 to 2017

Authors: Danijela Vuković, Radovan Čobanović, Milorad Plačkić

Abstract:

The expansion of population imposes increase in usage of animal meat, on whose quality directly affects the quality of the feed that the animals are fed with. The selection of raw materials, hygiene during the technological process, various hydrothermal treatments, methods of mixing etc. have an influence on the quality of feed. Monitoring of the feed is very important to obtain information about the quality of feed and the possible prevention of animal diseases which can lead to different human diseases outbreaks. In this study parameters of feed safety were monitored. According to the mentioned, the goal of this study was to evaluate microbiological safety of feed (feedstuffs and complete mixtures). Total number of analyzed samples was 4399. Analyzed feed samples were collected in various retail shops and feed factories during the period of 44 months (from January 2013 untill September 2017). Samples were analyzed on Salmonella spp. and Clostridium perfringens in quantity of 50g according to Serbian regulation. All microorganisms were tested according to ISO methodology: Salmonella spp. ISO 6579:2002 and Clostridium perfringens ISO 7937:2004. Out of 4399 analyzed feed samples 97,5% were satisfactory and 2,5% unsatisfactory concerning Salmonella spp. As far as Clostridium perfringens is concerned 100% of analyzed samples were satisfactory. The obtained results suggest that technological processing of feed in Serbia is at high level when it comes to safety and hygiene of the products, but there are still possibilities for progress and improvement which only can be reached trough the permanent monitoring of feed.

Keywords: microbiology, safety, hygiene, feed

Procedia PDF Downloads 296
1487 Green Technologies Developed by JSC “NIUIF”

Authors: Andrey Norov

Abstract:

In the recent years, Samoilov Research Institute for Mineral Fertilizers JSC “NIUIF”, the oldest (established in September 1919) industry-oriented institute in Russia, has developed a range of sustainable, environment-friendly, zero-waste technologies that ensure minimal consumption of materials and energy resources and fully consistent with the principles of Green Chemistry that include: - Ecofriendly energy and resource saving technology of sulfuric acid from sulfur according to DC-DA scheme (double conversion - double absorption); - Improved zero-waste technology of wet phosphoric acid (WPA) by dihydrate-hemihydrate process applicable to various types of phosphate raw materials; - Flexible, efficient, zero-waste, universal technology of NP / NPS / NPK / NPKS fertilizers with maximum heat recovery from chemical processes; - Novel, zero-waste, no-analogue technology of granular PK / PKS / NPKS fertilizers with controlled dissolution rate and nutrient supply into the soil, which allows to process a number of wastes and by-products; - Innovative resource-saving joint processing of wastes from the production of phosphogypsum and fluorosilicic acid (FSA) into ammonium sulfate with simultaneous neutralization of fluoride compounds with no lime used. - New fertilizer technology of increased environmental and agrochemical efficiency (currently under development). All listed green technologies are patented with Russian and Eurasian patents. The development of ecofriendly, safe, green technologies is ongoing in JSC “NIUIF”.

Keywords: NPKS fertilizers, FSA, sulfuric acid, WPA

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1486 Leveraging Automated and Connected Vehicles with Deep Learning for Smart Transportation Network Optimization

Authors: Taha Benarbia

Abstract:

The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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1485 From Type-I to Type-II Fuzzy System Modeling for Diagnosis of Hepatitis

Authors: Shahabeddin Sotudian, M. H. Fazel Zarandi, I. B. Turksen

Abstract:

Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty.

Keywords: hepatitis disease, medical diagnosis, type-I fuzzy logic, type-II fuzzy logic, feature selection

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1484 Cloud Shield: Model to Secure User Data While Using Content Delivery Network Services

Authors: Rachna Jain, Sushila Madan, Bindu Garg

Abstract:

Cloud computing is the key powerhouse in numerous organizations due to shifting of their data to the cloud environment. In recent years it has been observed that cloud-based-services are being used on large scale for content storage, distribution and processing. Various issues have been observed in cloud computing environment that need to be addressed. Security and privacy are found topmost concern area. In this paper, a novel security model is proposed to secure data by utilizing CDN services like image to icon conversion. CDN Service is a content delivery service which converts an image to icon, word to pdf & Latex to pdf etc. Presented model is used to convert an image into icon by keeping image secret. Here security of image is imparted so that image should be encrypted and decrypted by data owners only. It is also discussed in the paper that how server performs multiplication and selection on encrypted data without decryption. The data can be image file, word file, audio or video file. Moreover, the proposed model is capable enough to multiply images, encrypt them and send to a server application for conversion. Eventually, the prime objective is to encrypt an image and convert the encrypted image to image Icon by utilizing homomorphic encryption.

Keywords: cloud computing, user data security, homomorphic encryption, image multiplication, CDN service

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1483 Development and Characterization of Ethiopian Bamboo Fiber Polypropylene Composite

Authors: Tigist Girma Kedane

Abstract:

The purpose of this paper is to evaluate the properties of Ethiopian bamboo fiber polymer composites for headliner materials in the automobile industry. Accurate evaluation of its mechanical properties is thus critical for predicting its behavior during a vehicle's interior impact assessment. Conventional headliner materials are higher in weight, nonbiodegradable, expensive in cost, and unecofriendly during processing compared to the current researched materials. Three representatives of bamboo plants are harvested in three regions of bamboo species, three groups of ages, and two harvesting months. The statistical analysis was performed to validate the significant difference between the mean strength of bamboo ages, harvesting seasons, and bamboo species. Two-year-old bamboo fibers have the highest mechanical properties in all ages and November has higher mechanical properties compared to February. Injibara and Kombolcha have the highest and the lowest mechanical properties of bamboo fibers, respectively. Bamboo fiber epoxy composites have higher mechanical properties compared to bamboo fiber polypropylene composites. The flexural strength of bamboo fibre polymer composites has higher properties compared to tensile strength. Ethiopian bamboo fibers and their polymer composites have the best mechanical properties for the composite industry, which is used for headliner materials in the automobile industry compared to conventional headliner materials.

Keywords: bampoo species, culm age, harvesting seasons, mechanical properties, polymer composite

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1482 Additive Manufacturing Optimization Via Integrated Taguchi-Gray Relation Methodology for Oil and Gas Component Fabrication

Authors: Meshal Alsaiari

Abstract:

Fused Deposition Modeling is one of the additive manufacturing technologies the industry is shifting to nowadays due to its simplicity and low affordable cost. The fabrication processing parameters predominantly influence FDM part strength and mechanical properties. This presentation will demonstrate the influences of the two manufacturing parameters on the tensile testing evaluation indexes, infill density, and Printing Orientation, which were analyzed to create a piping spacer suitable for oil and gas applications. The tensile specimens are made of two polymers, Acrylonitrile Styrene Acrylate (ASA) and High high-impact polystyrene (HIPS), to characterize the mechanical properties performance for creating the final product. The mechanical testing was carried out per the ASTM D638 testing standard, following Type IV requirements. Taguchi's experiment design using an L-9 orthogonal array was used to evaluate the performance output and identify the optimal manufacturing factors. The experimental results demonstrate that the tensile test is more pronounced with 100% infill for ASA and HIPS samples. However, the printing orientations varied in reactions; ASA is maximum at 0 degrees while HIPS shows almost similar percentages between 45 and 90 degrees. Taguchi-Gray integrated methodology was adopted to minimize the response and recognize optimal fabrication factors combinations.

Keywords: FDM, ASTM D638, tensile testing, acrylonitrile styrene acrylate

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1481 Nano-Plasmonic Diagnostic Sensor Using Ultraflat Single-Crystalline Au Nanoplate and Cysteine-Tagged Protein G

Authors: Hwang Ahreum, Kang Taejoon, Kim Bongsoo

Abstract:

Nanosensors for high sensitive detection of diseases have been widely studied to improve the quality of life. Here, we suggest robust nano-plasmonic diagnostic sensor using cysteine tagged protein G (Cys3-protein G) and ultraflat, ultraclean and single-crystalline Au nanoplates. Protein G formed on an ultraflat Au surface provides ideal background for dense and uniform immobilization of antibodies. The Au is highly stable in diverse biochemical environment and can immobilize antibodies easily through Au-S bonding, having been widely used for various biosensing applications. Especially, atomically smooth single-crystalline Au nanomaterials synthesized using chemical vapor transport (CVT) method are very suitable to fabricate reproducible sensitive sensors. As the C-reactive protein (CRP) is a nonspecific biomarker of inflammation and infection, it can be used as a predictive or prognostic marker for various cardiovascular diseases. Cys3-protein G immobilized uniformly on the Au nanoplate enable CRP antibody (anti-CRP) to be ordered in a correct orientation, making their binding capacity be maximized for CRP detection. Immobilization condition for the Cys3-protein G and anti-CRP on the Au nanoplate is optimized visually by AFM analysis. Au nanoparticle - Au nanoplate (NPs-on-Au nanoplate) assembly fabricated from sandwich immunoassay for CRP can reduce zero-signal extremely caused by nonspecific bindings, providing a distinct surface-enhanced Raman scattering (SERS) enhancement still in 10-18 M of CRP concentration. Moreover, the NP-on-Au nanoplate sensor shows an excellent selectivity against non-target proteins with high concentration. In addition, comparing with control experiments employing a Au film fabricated by e-beam assisted deposition and linker molecule, we validate clearly contribution of the Au nanoplate for the attomolar sensitive detection of CRP. We expect that the devised platform employing the complex of single-crystalline Au nanoplates and Cys3-protein G can be applied for detection of many other cancer biomarkers.

Keywords: Au nanoplate, biomarker, diagnostic sensor, protein G, SERS

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1480 Iris Feature Extraction and Recognition Based on Two-Dimensional Gabor Wavelength Transform

Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

Abstract:

Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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1479 Isolation and Screening of Fungal Strains for β-Galactosidase Production

Authors: Parmjit S. Panesar, Rupinder Kaur, Ram S. Singh

Abstract:

Enzymes are the biocatalysts which catalyze the biochemical processes and thus have a wide variety of applications in the industrial sector. β-Galactosidase (E.C. 3.2.1.23) also known as lactase, is one of the prime enzymes, which has significant potential in the dairy and food processing industries. It has the capability to catalyze both the hydrolytic reaction for the production of lactose hydrolyzed milk and transgalactosylation reaction for the synthesis of prebiotics such as lactulose and galactooligosaccharides. These prebiotics have various nutritional and technological benefits. Although, the enzyme is naturally present in almonds, peaches, apricots and other variety of fruits and animals, the extraction of enzyme from these sources increases the cost of enzyme. Therefore, focus has been shifted towards the production of low cost enzyme from the microorganisms such as bacteria, yeast and fungi. As compared to yeast and bacteria, fungal β-galactosidase is generally preferred as being extracellular and thermostable in nature. Keeping the above in view, the present study was carried out for the isolation of the β-galactosidase producing fungal strain from the food as well as the agricultural wastes. A total of more than 100 fungal cultures were examined for their potential in enzyme production. All the fungal strains were screened using X-gal and IPTG as inducers in the modified Czapek Dox Agar medium. Among the various isolated fungal strains, the strain exhibiting the highest enzyme activity was chosen for further phenotypic and genotypic characterization. The strain was identified as Rhizomucor pusillus on the basis of 5.8s RNA gene sequencing data.

Keywords: beta-galactosidase, enzyme, fungal, isolation

Procedia PDF Downloads 248
1478 Non Interferometric Quantitative Phase Imaging of Yeast Cells

Authors: P. Praveen Kumar, P. Vimal Prabhu, Renu John

Abstract:

In biology most microscopy specimens, in particular living cells are transparent. In cell imaging, it is hard to create an image of a cell which is transparent with a very small refractive index change with respect to the surrounding media. Various techniques like addition of staining and contrast agents, markers have been applied in the past for creating contrast. Many of the staining agents or markers are not applicable to live cell imaging as they are toxic. In this paper, we report theoretical and experimental results from quantitative phase imaging of yeast cells with a commercial bright field microscope. We reconstruct the phase of cells non-interferometrically based on the transport of intensity equations (TIE). This technique estimates the axial derivative from positive through-focus intensity measurements. This technique allows phase imaging using a regular microscope with white light illumination. We demonstrate nano-metric depth sensitivity in imaging live yeast cells using this technique. Experimental results will be shown in the paper demonstrating the capability of the technique in 3-D volume estimation of living cells. This real-time imaging technique would be highly promising in real-time digital pathology applications, screening of pathogens and staging of diseases like malaria as it does not need any pre-processing of samples.

Keywords: axial derivative, non-interferometric imaging, quantitative phase imaging, transport of intensity equation

Procedia PDF Downloads 381
1477 Principle Component Analysis on Colon Cancer Detection

Authors: N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Rita Magdalena, R. D. Atmaja, Sofia Saidah, Ocky Tiaramukti

Abstract:

Colon cancer or colorectal cancer is a type of cancer that attacks the last part of the human digestive system. Lymphoma and carcinoma are types of cancer that attack human’s colon. Colon cancer causes deaths about half a million people every year. In Indonesia, colon cancer is the third largest cancer case for women and second in men. Unhealthy lifestyles such as minimum consumption of fiber, rarely exercising and lack of awareness for early detection are factors that cause high cases of colon cancer. The aim of this project is to produce a system that can detect and classify images into type of colon cancer lymphoma, carcinoma, or normal. The designed system used 198 data colon cancer tissue pathology, consist of 66 images for Lymphoma cancer, 66 images for carcinoma cancer and 66 for normal / healthy colon condition. This system will classify colon cancer starting from image preprocessing, feature extraction using Principal Component Analysis (PCA) and classification using K-Nearest Neighbor (K-NN) method. Several stages in preprocessing are resize, convert RGB image to grayscale, edge detection and last, histogram equalization. Tests will be done by trying some K-NN input parameter setting. The result of this project is an image processing system that can detect and classify the type of colon cancer with high accuracy and low computation time.

Keywords: carcinoma, colorectal cancer, k-nearest neighbor, lymphoma, principle component analysis

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1476 Designing, Processing and Isothermal Transformation of Al-Si High Carbon Ultrafine High Strength Bainitic Steel

Authors: Mohamed K. El-Fawkhry, Ahmed Shash, Ahmed Ismail Zaki Farahat, Sherif Ali Abd El Rahman, Taha Mattar

Abstract:

High-carbon, silicon-rich steels are commonly suggested to obtain very fine bainitic microstructure at low temperature ranged from 200 to 300°C. Thereby, the resulted microstructure consists of slender of bainitic-ferritic plates interwoven with retained austenite. The advanced strength and ductility package of this steel is much dependent on the fineness of bainitic ferrite, as well as the retained austenite phase. In this article, Aluminum to Silicon ratio, and the isothermal transformation temperature have been adopted to obtain ultra high strength high carbon steel. Optical and SEM investigation of the produced steels have been performed. XRD has been used to track the retained austenite development as a result of the change in the chemical composition of developed steels and heat treatment process. Mechanical properties in terms of hardness and microhardness of obtained phases and structure were investigated. It was observed that the increment of aluminum to silicon ratio has a great effect in promoting the bainitic transformation, in tandem with improving the stability and the fineness of retained austenite. Such advanced structure leads to enhancement in the whole mechanical properties of the high carbon steel.

Keywords: high-carbon steel, silicon-rich steels, fine bainitic microstructure, retained austenite, isothermal transformation

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1475 Identifying of Hybrid Lines for Lpx-B1 Gene in Durum Wheat

Authors: Özlem Ateş Sönmezoğlu, Begüm Terzi, Ahmet Yıldırım, Ramazan Özbey

Abstract:

The basic criteria which determine durum wheat quality is its suitability for pasta processing that is pasta making quality. Bright yellow color is a desired property in pasta products. Durum wheat pasta making quality is affected by grain pigment content and oxidative enzymes which affect adversely bright yellow color. Of the oxidative enzymes, lipoxygenase LOX is the most effective one on oxidative bleaching of yellow pigments in durum wheat products. Thus, wheat cultivars that are high in yellow pigments but low in LOX enzyme activity should be preferred for the production of pasta with high color quality. The aim of this study was to reduce lipoxygenase activities of the backcross durum wheat lines that were previously improved for their protein quality. For this purpose, two advanced lines with different parents (TMB2 and TMB3) were used recurrent parents. Also, Gediz-75 wheat with low LOX enzyme activity was used as the gene source. In all of the generations, backcrossed plants carrying the targeted gene region (Lpx-B1.1) were selected using SSR markers by marker assisted selection method. As a result, the study will be completed in three years instead of six years required in a classical backcross breeding study, leading to the development of high-quality candidate varieties. This research has been financially supported by TÜBİTAK (Project No: 112T910).

Keywords: durum wheat, lipoxygenase, LOX, Lpx-B1.1, MAS, Triticum durum

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1474 Enhancing Information Technologies with AI: Unlocking Efficiency, Scalability, and Innovation

Authors: Abdal-Hafeez Alhussein

Abstract:

Artificial Intelligence (AI) has become a transformative force in the field of information technologies, reshaping how data is processed, analyzed, and utilized across various domains. This paper explores the multifaceted applications of AI within information technology, focusing on three key areas: automation, scalability, and data-driven decision-making. We delve into how AI-powered automation is optimizing operational efficiency in IT infrastructures, from automated network management to self-healing systems that reduce downtime and enhance performance. Scalability, another critical aspect, is addressed through AI’s role in cloud computing and distributed systems, enabling the seamless handling of increasing data loads and user demands. Additionally, the paper highlights the use of AI in cybersecurity, where real-time threat detection and adaptive response mechanisms significantly improve resilience against sophisticated cyberattacks. In the realm of data analytics, AI models—especially machine learning and natural language processing—are driving innovation by enabling more precise predictions, automated insights extraction, and enhanced user experiences. The paper concludes with a discussion on the ethical implications of AI in information technologies, underscoring the importance of transparency, fairness, and responsible AI use. It also offers insights into future trends, emphasizing the potential of AI to further revolutionize the IT landscape by integrating with emerging technologies like quantum computing and IoT.

Keywords: artificial intelligence, information technology, automation, scalability

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1473 Antioxidant Properties, Ascorbic Acid and Total Carotenoids Values of Sweet and Hot Red Pepper Paste: A Traditional Food in Turkish Diet

Authors: Kubra Sayin, Derya Arslan

Abstract:

Red pepper (Capsicum annum L.) has long been recognized as a good source of antioxidants, being rich in ascorbic acid and other phytochemicals. In Turkish cuisine red pepper is sometimes consumed raw in salads and baked as a garnish, but its most wide consumption type is red pepper paste. The processing of red pepper into pepper paste includes various thermal treatment steps such as heating and pasteurizing. There are reports demonstrating an enhancement or reduction in antioxidant activity of vegetables after thermal treatment. So this study was conducted to investigate the total phenolics, ascorbic acid and total carotenoids as well as free radical scavenging activity of raw red pepper and various red pepper pastes obtainable on the market. The samples were analyzed for radical-scavenging activity (RSA) and total polyphenol (TP) content using 1,1-diphenyl-2-picrylhydrazyl (DPPH) and Folin-Ciocalteu methods, respectively. They were also evaluated for ascorbic acid content (AsA) by HPLC. Total carotenoids content was determined spectrophotometrically. Results suggest that there is no significant (P > 0.05) difference in RSA, TP, AsA and total carotenoids content between various red pepper paste products. However, red pepper paste showed marked differences (P < 0.05) in the RSA, TP and AsA contents compared with raw red pepper. It is concluded that the red pepper paste, that has a wide range of consumption in Turkish cuisine, presents a good dose of phenolic compounds and antioxidant capacity and it should be regarded as a functional food.

Keywords: red pepper paste, antioxidant properties, total carotenoids, total phenolics

Procedia PDF Downloads 571