Search results for: laminated segmented rotor flux switching permanent magnet machine

Authors: Chris Schoborg, Morgan C. Wang

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In the realm of the National Football League (NFL), substantial dedication of time and effort is invested by both players and coaches in meticulously analyzing the game footage of their opponents. The primary aim is to anticipate the actions of the opposing team. Defensive players and coaches are especially focused on deciphering their adversaries' intentions to effectively counter their strategies. Acquiring insights into the specific play type and its intended direction on the field would confer a significant competitive advantage. This study establishes pre-snap information as the cornerstone for predicting both the play type (e.g., deep pass, short pass, or run) and its spatial trajectory (right, left, or center). The dataset for this research spans the regular NFL season data for all 32 teams from 2013 to 2022. This dataset is acquired using the nflreadr package, which conveniently extracts play-by-play data from NFL games and imports it into the R environment as structured datasets. In this study, we employ a recently developed machine learning algorithm, XGBoost. The final predictive model achieves an impressive lift of 2.61. This signifies that the presented model is 2.61 times more effective than random guessing—a significant improvement. Such a model has the potential to markedly enhance defensive coaches' ability to formulate game plans and adequately prepare their players, thus mitigating the opposing offense's yardage and point gains.

Keywords: lift, NFL, sports analytics, XGBoost

Procedia PDF Downloads 48

Authors: Paua Ketan, Bhagate Rajkumar, Adiga Ganesh, M. Kiran

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Low gear noise is an important sound quality feature in modern passenger cars. Annoying gear noise from the gearbox is influenced by the gear design, gearbox shaft layout, manufacturing deviations in the components, assembly errors and the mounting arrangement of the complete gearbox. Geometrical deviations in the form of profile and lead errors are often present on the flanks of the inspected gears. Ghost frequencies of a gear are very challenging to identify in standard gear measurement and analysis process due to small wavelengths involved. In this paper, gear whine noise occurring at non-integral multiples of gear mesh frequency of passenger car gearbox is investigated and the root cause is identified using the displacement deviation analysis (DDA) method. DDA method is applied to identify ghost frequency excitations on the flanks of gears arising out of generation grinding. Frequency identified through DDA correlated with the frequency of vibration and noise on the end-of-line machine as well as vehicle level measurements. With the application of DDA method along with standard lead profile measurement, gears with ghost frequency geometry deviations were identified on the production line to eliminate defective parts and thereby eliminate ghost frequency noise from a vehicle. Further, displacement deviation analysis can be used in conjunction with the manufacturing process simulation to arrive at suitable countermeasures for arresting the ghost frequency.

Keywords: displacement deviation analysis, gear whine, ghost frequency, sound quality

Procedia PDF Downloads 134

Authors: Hong Lu, Yongquan Zhang, Wei Fan, Xiangang Su

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Bent mandrel has been widely used as precise mould in automobile industry, shipping industry and aviation industry. To improve the versatility and efficiency of turning method of bent mandrel with fixed rotational center, an instantaneous machining model based on cutting parameters and machine dimension is prospered in this paper. The spiral-like tool path generation approach in non-axisymmetric turning process of bent mandrel is developed as well to deal with the error of part-to-part repeatability in existed turning model. The actual cutter-location points are calculated by cutter-contact points, which are obtained from the approach of spiral sweep process using equal-arc-length segment principle in polar coordinate system. The tool offset is set to avoid the interference between tool and work piece is also considered in the machining model. Depend on the spindle rotational angle, synchronization control of X-axis, Z-axis and C-axis is adopted to generate the tool-path of the turning process. The simulation method is developed to generate NC program according to the presented model, which includes calculation of cutter-location points and generation of tool-path of cutting process. With the approach of a bent mandrel taken as an example, the maximum offset of center axis is 4mm in the 3D space. Experiment results verify that the machining model and turning method are appropriate for the characteristics of bent mandrel.

Keywords: bent mandrel, instantaneous machining model, simulation method, tool-path generation

Procedia PDF Downloads 328

Authors: D. J. Kalita

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

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

Procedia PDF Downloads 81

Authors: Craig A. Kaplan

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If AGI proves to be a “winner-take-all” scenario where the first company or country to develop AGI dominates, then the first AGI must also be the safest. The safest, and fastest, path to Artificial General Intelligence (AGI) may be to harness the collective intelligence of multiple AI and human agents in an AGI network. This approach has roots in seminal ideas from four of the scientists who founded the field of Artificial Intelligence: Allen Newell, Marvin Minsky, Claude Shannon, and Herbert Simon. Extrapolating key insights from these founders of AI, and combining them with the work of modern researchers, results in a fast and safe path to AGI. The seminal ideas discussed are: 1) Society of Mind (Minsky), 2) Information Theory (Shannon), 3) Problem Solving Theory (Newell & Simon), and 4) Bounded Rationality (Simon). Society of Mind describes a collective intelligence approach that can be used with AI and human agents to create an AGI network. Information theory helps address the critical issue of how an AGI system will increase its intelligence over time. Problem Solving Theory provides a universal framework that AI and human agents can use to communicate efficiently, effectively, and safely. Bounded Rationality helps us better understand not only the capabilities of SuperIntelligent AGI but also how humans can remain relevant in a world where the intelligence of AGI vastly exceeds that of its human creators. Each key idea can be combined with recent work in the fields of Artificial Intelligence, Machine Learning, and Large Language Models to accelerate the development of a working, safe, AGI system.

Keywords: AI Agents, Collective Intelligence, Minsky, Newell, Shannon, Simon, AGI, AGI Safety

Procedia PDF Downloads 77

Authors: Yu-Chu Yeh, WeiChin Hsu, Chih-Yen Chang

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Substitution, combination, modification, putting to other uses, elimination, and rearrangement (SCAMPER) has been regarded as an effective technique that provides a structured way to help people to produce creative ideas and solutions. Although some neuroscience studies regarding creativity training have been conducted, no study has focused on SCAMPER. This study therefore aimed at examining whether the learning of SCAMPER through video tutorials would result in alternations of neural activation. Thirty college students were randomly assigned to the experimental group or the control group. The experimental group was requested to watch SCAMPER videos, whereas the control group was asked to watch natural-scene videos which were regarded as neutral stimulating materials. Each participant was brain scanned in a Functional magnetic resonance imaging (fMRI) machine while undertaking a creativity test before and after watching the videos. Furthermore, a two-way ANOVA was used to analyze the interaction between groups (the experimental group; the control group) and tasks (C task; M task; X task). The results revealed that the left precuneus significantly activated in the interaction of groups and tasks, as well as in the main effect of group. Furthermore, compared with the control group, the experimental group had greater activation in the default mode network (left precuneus and left inferior parietal cortex) and the motor network (left postcentral gyrus and left supplementary area). The findings suggest that the SCAMPER training may facilitate creativity through the stimulation of the default mode network and the motor network.

Keywords: creativity, default mode network, neural activation, SCAMPER

Procedia PDF Downloads 96

Authors: Raz Flieshman, Adam Michael Altenbuchner, Jörg Krüger

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This paper presents an approach to optimizing the Fused Deposition Modeling (FDM) 3D printing process through a preprocess calibration routine of printing parameters. The core of this method involves the use of a low-cost thermal sensor capable of measuring tempera-tures within the range of -20 to 500 degrees Celsius for detailed process observation. The calibration process is conducted by printing a predetermined path while varying the process parameters through machine instructions (g-code). This enables the extraction of critical thermal, dimensional, and surface properties along the printed path. The calibration routine utilizes computer vision models to extract features and metrics from the thermal images, in-cluding temperature distribution, layer adhesion quality, surface roughness, and dimension-al accuracy and consistency. These extracted properties are then analyzed to optimize the process parameters to achieve the desired qualities of the printed material. A significant benefit of this calibration method is its potential to create printing parameter profiles for new polymer and composite materials, thereby enhancing the versatility and application range of FDM 3D printing. The proposed method demonstrates significant potential in enhancing the precision and reliability of FDM 3D printing, making it a valuable contribution to the field of additive manufacturing.

Keywords: FDM 3D printing, preprocess calibration, thermal sensor, process optimization, additive manufacturing, computer vision, material profiles

Procedia PDF Downloads 23

Authors: Fares Khalfallah, Zakaria Boumerzoug, Selvarajan Rajakumar, Elhadj Raouache

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The ceramic-aluminum bond is strongly present in industrial tools, due to the need to combine the properties of metals, such as ductility, thermal and electrical conductivity, with ceramic properties like high hardness, corrosion and wear resistance. In recent years, some joining techniques have been developed to achieve a good bonding between these materials such as brazing, diffusion bonding, ultrasonic joining and friction welding. In this work, AA1100 aluminum alloy rods were welded with Alumina 99.9 wt% ceramic rods, by friction welding. The effect of friction pressure on mechanical and structural properties of welded joints was studied. The welding was performed by direct friction welding machine. The welding samples were rotated at a constant rotational speed of 900 rpm, friction time of 4 sec, forging strength of 18 MPa, and forging time of 3 sec. Three different friction pressures were applied to 20, 34 and 45 MPa. The three-point bending test and Vickers microhardness measurements were used to evaluate the strength of the joints and investigate the mechanical properties of the welding area. The microstructure of joints was examined by optical microscopy (OM), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The results show that bending strength increased, and then decreased after reaching a maximum value, with increasing friction pressure. The SEM observation shows that the increase in friction pressure led to the appearance of cracks in the microstructure of the interface area, which is decreasing the bending strength of joints.

Keywords: welding of ceramic to aluminum, friction welding, alumina, AA1100 aluminum alloy

Procedia PDF Downloads 121

Authors: Maksim Barsakov

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Introduction. In modern plastic surgery, there are a large number of breast lift techniques.Due to the spreading information about the "side effects" of silicone implants, interest in implant-free mastopexy is increasing year after year. However, despite the variety of techniques, patients sometimes do not get full satisfaction from the results of mastopexy because of the unexpressed filling of the upper pole, extended anchoring postoperative scars and sometimes because of obtaining an aesthetically unattractive breast shape. The stability of the result after mastopexy depends on many factors, including postoperative rehabilitation. Stability of weight and hormonal background, stretchability of tissues. The high recurrence rate of ptosis and short-term aesthetic effect of mastopexy indicate the urgency of improving surgical techniques and increasing the stabilization of breast tissue. Purpose of the study. To develop and introduce into practice a technique of mastopexy based on the use of a modified Ribeiro flap, as well as elements of tissue movement and fixation designed to increase the stability of postoperative mastopexy. In addition, to give indications for the application of this surgical technique. Materials and Methods. it operated on 103 patients aged 18 to 53 years from 2019 to 2023 according to the reported method. These were patients with primary mastopexy, secondary mastopexy, and also patient with implant removal and one-stage mastopexy. The patients were followed up for 12 months to assess the stability of the result. Results and their discussion. Observing the patients, we noted greater stability of the breast shape and upper pole filling compared to the conventional classical methods. We did not have to resort to anchoring scars. In 90 percent of cases, a inverted T-shape scar was used. In 10 percent, the J-scar was used. The quantitative distribution of complications identified among the operated patients is as follows: worsened healing of the junction of vertical and horizontal sutures at the period of 1-1.5 months after surgery - 15 patients; at treatment with ointment method healing was observed in 7-30 days; permanent loss of NAC sensitivity - 0 patients; vascular disorders in the area of NAC/areola necrosis - 0 patients; marginal necrosis of the areola-2 patients. independent healing within 3-4 weeks without aesthetic defects. Aesthetically unacceptable mature scars-3 patients; partial liponecrosis of the autoflap unilaterally - 1 patient. recurrence of ptosis - 1 patient (after weight loss of 12 kg). In the late postoperative period, 2 patients became pregnant, gave birth, and no lactation problems were observed. Conclusion. Thus, in the world of plastic surgery methods of breast lift continue to improve, which is especially relevant in modern times, due to the increased attention to this operation. The author's proposed method of mastopexy with glandular autoflap allows obtaining in most cases a stable result, a fuller breast shape, avoiding the presence of extended anchoring scars, and also preserves the possibility of lactation. The author of this article has obtained a patent for invention for this method of mastopexy.

Keywords: mastopexy, mammoplasty, autoflap, personal technique

Procedia PDF Downloads 22

Authors: Abu Afree Andalib, M. Mezbah Uddin, M. Rafiur Rahman, M. Abir Hossain, Rajia Sultana Kamol

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This paper deals with the analysis of flow past the marine turbine blade which is designed by using the blade element theory and momentum theory for the purpose of using in the field of renewable energy. The designed blade is analyzed for various parameters using FSI module of Ansys. Computational Fluid Dynamics is used for the study of fluid flow past the blade and other fluidic phenomena such as lift, drag, pressure differentials, energy dissipation in water. Finite Element Analysis (FEA) module of Ansys was used to analyze the structural parameter such as stress and stress density, localization point, deflection, force propagation. Fine mesh is considered in every case for more accuracy in the result according to computational machine power. The relevance of design, search and optimization with respect to complex fluid flow and structural modeling is considered and analyzed. The relevancy of design and optimization with respect to complex fluid for minimum drag force using Ansys Adjoint Solver module is analyzed as well. The graphical comparison of the above-mentioned parameter using CFD and FEA and subsequently FSI technique is illustrated and found the significant conformity between both the results.

Keywords: blade element theory, computational fluid dynamics, finite element analysis, fluid-structure interaction, momentum theory

Procedia PDF Downloads 288

Authors: Al. Tsertsvadze. L. Ebralidze, I. Matchutadze. D. Berashvili, A. Bakuridze

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Peatlands are landscape elements, they are formed over a very long period by physical, chemical, biologic, and geologic processes. In the moderate zone of Caucasus, the Kolkheti lowlands are distinguished by the diversity of relictual plants, a high degree of endemism, orographic, climate, landscape, and other characteristics of high levels of biodiversity. The unique properties of the Kolkheti region lead to the formation of special, so-called, endemic peat peloids. The composition and properties of peloids strongly depend on peat-forming plants. Peat is considered a unique complex of raw materials, which can be used in different fields of the industry: agriculture, metallurgy, energy, biotechnology, chemical industry, health care. They are formed in permanent wetland areas. As a result of decay, higher plants remain in the anaerobic area, with the participation of microorganisms. Peat mass absorbs soil and groundwater. Peloids are predominantly rich with humic substances, which are characterized by high biological activity. Humic acids stimulate enzymatic activity, regenerative processes, and have anti-inflammatory activity. Objects of the research were Kolkheti peat peloids (Ispani, Anaklia, Churia, Chirukhi, Peranga) possessing different formation phases. Due to specific physical and chemical properties of research objects, the aim of the research was to develop analytical methods in order to study the chemical composition of the objects. The research was held using modern instrumental methods of analysis: Ultraviolet-visible spectroscopy and Infrared spectroscopy, Scanning Electron Microscopy, Centrifuge, dry oven, Ultraturax, pH meter, fluorescence spectrometer, Gas chromatography-mass spectrometry (GC-MS/MS), Gas chromatography. Based on the research ration between organic and inorganic substances, the spectrum of micro and macro elements, also the content of minerals was determined. The content of organic nitrogen was determined using the Kjeldahl method. The total composition of amino acids was studied by a spectrophotometric method using standard solutions of glutamic and aspartic acids. Fatty acid was determined using GC (Gas chromatography). Based on the obtained results, we can conclude that the method is valid to identify fatty acids in the research objects. The content of organic substances in the research objects was held using GC-MS. Using modern instrumental methods of analysis, the chemical composition of research objects was studied. Each research object is predominantly reached with a broad spectrum of organic (fatty acids, amino acids, carbocyclic and heterocyclic compounds, organic acids and their esters, steroids) and inorganic (micro and macro elements, minerals) substances. Modified methods used in the presented research may be utilized for the evaluation of cosmetological balneological and pharmaceutical means prepared on the base of Kolkheti's Sphagnum Peat Peloids.

Keywords: modern analytical methods, natural resources, peat, chemistry

Procedia PDF Downloads 118

Authors: Khin Mar Yee, Mu Mu Than, Kyi Lint, Aye Aye Oo, Chan Mya Hmway, Khin Zar Chi Winn

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The dynamic changes of Land Use and Land Cover (LULC) changes in Yangon have generally resulted the improvement of human welfare and economic development since the last twenty years. Making map of LULC is crucially important for the sustainable development of the environment. However, the exactly data on how environmental factors influence the LULC situation at the various scales because the nature of the natural environment is naturally composed of non-homogeneous surface features, so the features in the satellite data also have the mixed pixels. The main objective of this study is to the calculation of accuracy based on change detection of LULC changes by Support Vector Machines (SVMs). For this research work, the main data was satellite images of 1996, 2006 and 2015. Computing change detection statistics use change detection statistics to compile a detailed tabulation of changes between two classification images and Support Vector Machines (SVMs) process was applied with a soft approach at allocation as well as at a testing stage and to higher accuracy. The results of this paper showed that vegetation and cultivated area were decreased (average total 29 % from 1996 to 2015) because of conversion to the replacing over double of the built up area (average total 30 % from 1996 to 2015). The error matrix and confidence limits led to the validation of the result for LULC mapping.

Keywords: land use and land cover change, change detection, image processing, support vector machines

Procedia PDF Downloads 121

Authors: Abdullah Alotaiq, David Wallom, Malcolm McCulloch

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This study presents an archetype-based approach to designing effective strategies for low-carbon transitions in the power sector. To achieve global energy transition goals, a renewable energy transition is critical, and understanding diverse energy landscapes across different countries is essential to design effective renewable energy policies and strategies. Using a clustering approach, this study identifies 12 energy archetypes based on the electricity mix, socio-economic indicators, and renewable energy contribution potential of 187 UN countries. Each archetype is characterized by distinct challenges and opportunities, ranging from high dependence on fossil fuels to low electricity access, low economic growth, and insufficient contribution potential of renewables. Archetype A, for instance, consists of countries with low electricity access, high poverty rates, and limited power infrastructure, while Archetype J comprises developed countries with high electricity demand and installed renewables. The study findings have significant implications for renewable energy policymaking and investment decisions, with policymakers and investors able to use the archetype approach to identify suitable renewable energy policies and measures and assess renewable energy potential and risks. Overall, the archetype approach provides a comprehensive framework for understanding diverse energy landscapes and accelerating decarbonisation of the power sector.

Keywords: fossil fuels, power plants, energy transition, renewable energy, archetypes

Procedia PDF Downloads 44

Authors: Olubajo Olumide Olu

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This paper studies the effect of Metakaolin (MK) and Rice husk ash (RHA) on the compressive strength of ternary cement mortar at replacement level up to 30%. The compressive strength test of the blended cement mortars were conducted using Tonic Technic compression and machine. Nineteen ternary cement mortars were prepared comprising of ordinary Portland cement (OPC), Rice husk ash (RHA) and Metakaolin (MK) at different proportion. Ternary mortar prisms in which Portland cement was replaced by up to 30% were tested at various age; 2, 7, 28 and 60 days. Result showed that the compressive strength of the cement mortars increased as the curing days were lengthened for both OPC and the blended cement samples. The ternary cement’s compressive strengths showed significant improvement compared with the control especially beyond 28 days. This can be attributed to the slow pozzolanic reaction resulting from the formation of additional CSH from the interaction of the residual CH content and the silica available in the Metakaolin and Rice husk ash, thus providing significant strength gain at later age. Results indicated that the addition of metakaolin with rice husk ash kept constant was found to lead to an increment in the compressive strength. This can either be attributed to the high silica/alumina contribution to the matrix or the C/S ratio in the cement matrix. Whereas, increment in the rice husk ash content while metakaolin was held constant led to an increment in the compressive strength, which could be attributed to the reactivity of the rice husk ash followed by decrement owing to the presence of unburnt carbon in the RHA matrix. The best compressive strength results were obtained at 10% cement replacement (5% RHA, 5% MK); 15% cement replacement (10% MK and 5% RHA); 20% cement replacement (15% MK and 5% RHA); 25% cement replacement (20% MK and 5% RHA); 30% cement replacement (10%/20% MK and 20%/10% RHA). With the optimal combination of either 15% and 20% MK with 5% RHA giving the best compressive strength of 40.5MPa.

Keywords: metakaolin, rice husk ash, compressive strength, ternary mortar, curing days

Procedia PDF Downloads 331

Authors: Jongbae Lee, Seongsoo Lee

Abstract:

Modern sensors often embed small-size digital controller for sensor control, value calibration, and signal processing. These sensors require digital data communication with host microprocessors, but conventional digital communication protocols are too heavy for price reduction. SAE J2716 SENT (single edge nibble transmission) protocol transmits direct digital waveforms instead of complicated analog modulated signals. In this paper, a SENT interface is designed in Verilog HDL (hardware description language) and implemented in FPGA (field-programmable gate array) evaluation board. The designed SENT interface consists of frame encoder/decoder, configuration register, tick period generator, CRC (cyclic redundancy code) generator/checker, and TX/RX (transmission/reception) buffer. Frame encoder/decoder is implemented as a finite state machine, and it controls whole SENT interface. Configuration register contains various parameters such as operation mode, tick length, CRC option, pause pulse option, and number of nibble data. Tick period generator generates tick signals from input clock. CRC generator/checker generates or checks CRC in the SENT data frame. TX/RX buffer stores transmission/received data. The designed SENT interface can send or receives digital data in 25~65 kbps at 3 us tick. Synthesized in 0.18 um fabrication technologies, it is implemented about 2,500 gates.

Keywords: digital sensor interface, SAE J2716, SENT, verilog HDL

Procedia PDF Downloads 289

Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

Procedia PDF Downloads 134

Authors: Christopher Schwarz, Katrin Riegler, Erwin Zinser

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The management of outsourcing relationships between IT service providers and their customers proofs to be a critical issue that has to be stipulated by means of Service Level Agreements (SLAs). Since service requirements differ from customer to customer, SLA content and language structures vary largely, standardized SLA templates may not be used and an automated processing of SLA content is not possible. Hence, SLA management is usually a time-consuming and inefficient manual process. For overcoming these challenges, this paper presents an innovative and ITIL V3-conform approach for automated SLA design and management using controlled natural language in enterprise collaboration portals. The proposed novel concept is based on a self-developed controlled natural language that follows a subject-predicate-object approach to specify well-defined SLA content structures that act as templates for customized contracts and support automated SLA processing. The derived results eventually enable IT service providers to automate several SLA request, approval and negotiation processes by means of workflows and business rules within an enterprise collaboration portal. The illustrated prototypical realization gives evidence of the practical relevance in service-oriented scenarios as well as the high flexibility and adaptability of the presented model. Thus, the prototype enables the automated creation of well defined, customized SLA documents, providing a knowledge representation that is both human understandable and machine processable.

Keywords: automated processing, controlled natural language, knowledge representation, information technology outsourcing, service level management

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Authors: David B. Kisakye, Paul Mugabi

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Biomass briquettes have been identified as a plausible and close alternative to commonly used energy fuels such as charcoal and firewood, whose prices are escalating due to the dwindling natural resource base. However, briquettes do not seem to be as popular as would be expected. This study assessed the production, distribution, and acceptability of the briquettes in the Kampala district. A total of 60 respondents, 50 of whom were briquette users and 10 briquette producers, were sampled from five divisions of Kampala district to evaluate consumer acceptability, preference for briquette type and shape. Households and institutions were identified to be the major consumers of briquettes, while community-based organizations were the major distributors of briquettes. The Chi-square test of independence showed a significant association between briquette acceptability and briquette attributes of substitutability and low cost (p < 0,05). The Kruskal Wallis test showed that low-income class people preferred non-carbonized briquettes. Gender, marital status, and income level also cause variation in preference for spherical, stick, and honeycomb briquettes (p < 0,05). The major challenges faced by briquette users in Kampala were; production of a lot of ash, frequent crushing, and limited access to briquettes. The producers of briquettes were mainly challenged by regular machine breakdown, raw material scarcity, and poor carbonizing units. It was concluded that briquettes have a market and are generally accepted in Kampala. However, user preferences need to be taken into account by briquette produces, suitable cookstoves should be availed to users, and there is a need for standards to ensure the quality of briquettes.

Keywords: consumer acceptability, biomass residues, briquettes, briquette producers, distribution, fuel, marketability, wood fuel

Procedia PDF Downloads 131

Authors: Tran Ich Thinh, Nguyen Manh Cuong

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Free vibrations of partial fluid-filled composite truncated conical shells are investigated using the Dynamic Stiffness Method (DSM) or Continuous Element Method (CEM) based on the First Order Shear Deformation Theory (FSDT) and non-viscous incompressible fluid equations. Numerical examples are given for analyzing natural frequencies and harmonic responses of clamped-free conical shells partially and completely filled with fluid. To compare with the theoretical results, detailed experimental results have been obtained on the free vibration of a clamped-free conical shells partially filled with water by using a multi-vibration measuring machine (DEWEBOOK-DASYLab 5.61.10). Three glass fiber/polyester composite truncated cones with the radius of the larger end 285 mm, thickness 2 mm, and the cone lengths along the generators are 285 mm, 427.5 mm and 570 mm with the semi-vertex angles 27, 14 and 9 degrees respectively were used, and the filling ratio of the contained water was 0, 0.25, 0.50, 0.75 and 1.0. The results calculated by proposed computational model for studied composite conical shells are in good agreement with experiments. Obtained results indicate that the fluid filling can reduce significantly the natural frequencies of composite conical shells. Parametric studies including circumferential wave number, fluid depth and cone angles are carried out.

Keywords: dynamic stiffness method, experimental study, free vibration, fluid-shell interaction, glass fiber/polyester composite conical shell

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Authors: Zhu Weimin, Allegorico Carmine, Ruggiero Gionata

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

Keywords: analytics, diagnostics, monitoring, turbomachinery

Procedia PDF Downloads 66

Authors: Anastasios Papathanasiou, George Liontos, Athanasios Katsouras, Vasiliki Liagkou, Euripides Glavas

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Email remains a crucial communication tool due to its efficiency, accessibility and cost-effectiveness, enabling rapid information exchange across global networks. However, the global adoption of email has also made it a prime target for cyber threats, including phishing, malware and Business Email Compromise (BEC) attacks, which exploit its integral role in personal and professional realms in order to perform fraud and data breaches. To combat these threats, this research advocates for a multi-layered defense strategy incorporating advanced technological tools such as anti-spam and anti-malware software, machine learning algorithms and authentication protocols. Moreover, we developed an artificial intelligence model specifically designed to analyze email headers and assess their security status. This AI-driven model examines various components of email headers, such as "From" addresses, ‘Received’ paths and the integrity of SPF, DKIM and DMARC records. Upon analysis, it generates comprehensive reports that indicate whether an email is likely to be malicious or benign. This capability empowers users to identify potentially dangerous emails promptly, enhancing their ability to avoid phishing attacks, malware infections and other cyber threats.

Keywords: email security, artificial intelligence, header analysis, threat detection, phishing, DMARC, DKIM, SPF, ai model

Procedia PDF Downloads 37

Authors: Faheema Khan

Abstract:

To investigate the ability of sensitive and tolerant genotype of Glycine max to adapt to a saline environment in a field, we examined the growth performance, water relation and activities of antioxidant enzymes in relation to photosynthetic rate, chlorophyll a fluorescence, photosynthetic pigment concentration, protein and proline in plants exposed to salt stress. Ten soybean genotypes (Pusa-20, Pusa-40, Pusa-37, Pusa-16, Pusa-24, Pusa-22, BRAGG, PK-416, PK-1042, and DS-9712) were selected and grown hydroponically. After 3 days of proper germination, the seedlings were transferred to Hoagland’s solution (Hoagland and Arnon 1950). The growth chamber was maintained at a photosynthetic photon flux density of 430 μmol m−2 s−1, 14 h of light, 10 h of dark and a relative humidity of 60%. The nutrient solution was bubbled with sterile air and changed on alternate days. Ten-day-old seedlings were given seven levels of salt in the form of NaCl viz., T1 = 0 mM NaCl, T2=25 mM NaCl, T3=50 mM NaCl, T4=75 mM NaCl, T5=100 mM NaCl, T6=125 mM NaCl, T7=150 mM NaCl. The investigation showed that genotype Pusa-24, PK-416 and Pusa-20 appeared to be the most salt-sensitive. genotypes as inferred from their significantly reduced length, fresh weight and dry weight in response to the NaCl exposure. Pusa-37 appeared to be the most tolerant genotype since no significant effect of NaCl treatment on growth was found. We observed a greater decline in the photosynthetic variables like photosynthetic rate, chlorophyll fluorescence and chlorophyll content, in salt-sensitive (Pusa-24) genotype than in salt-tolerant Pusa-37 under high salinity. Numerous primers were verified on ten soybean genotypes obtained from Operon technologies among which 30 RAPD primers shown high polymorphism and genetic variation. The Jaccard’s similarity coefficient values for each pairwise comparison between cultivars were calculated and similarity coefficient matrix was constructed. The closer varieties in the cluster behaved similar in their response to salinity tolerance. Intra-clustering within the two clusters precisely grouped the 10 genotypes in sub-cluster as expected from their physiological findings.Salt tolerant genotype Pusa-37, was further analysed by 2-Dimensional gel electrophoresis to analyse the differential expression of proteins at high salt stress. In the Present study, 173 protein spots were identified. Of these, 40 proteins responsive to salinity were either up- or down-regulated in Pusa-37. Proteomic analysis in salt-tolerant genotype (Pusa-37) led to the detection of proteins involved in a variety of biological processes, such as protein synthesis (12 %), redox regulation (19 %), primary and secondary metabolism (25 %), or disease- and defence-related processes (32 %). In conclusion, the soybean plants in our study responded to salt stress by changing their protein expression pattern. The photosynthetic, biochemical and molecular study showed that there is variability in salt tolerance behaviour in soybean genotypes. Pusa-24 is the salt-sensitive and Pusa-37 is the salt-tolerant genotype. Moreover this study gives new insights into the salt-stress response in soybean and demonstrates the power of genomic and proteomic approach in plant biology studies which finally could help us in identifying the possible regulatory switches (gene/s) controlling the salt tolerant genotype of the crop plants and their possible role in defence mechanism.

Keywords: glycine max, salt stress, RAPD, genomic and proteomic variability

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

Abstract:

In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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Authors: Ram Sharma, Esha Chatterjee, Santosh Kumar Guru, Kunal Nepali

Abstract:

A tractable anti-lung cancer agent was identified via the installation of a Ring C expanded synthetic analogue of the alkaloid vasicinone [7,8,9,10-tetrahydroazepino[2,1-b] quinazolin-12(6H)-one (TAZQ)] as a surface recognition part in the HDAC inhibitory three-component model. Noteworthy to mention that the candidature of TAZQ was deemed suitable for accommodation in HDAC inhibitory pharmacophore as per the results of the fragment recruitment process conducted by our laboratory. TAZQ was pinpointed through the fragment screening program as a synthetically flexible fragment endowed with some moderate cell growth inhibitory activity against the lung cancer cell lines, and it was anticipated that the use of the aforementioned fragment to generate hydroxamic acid functionality (zinc-binding motif) bearing HDAC inhibitors would boost the antitumor efficacy of TAZQ. Consistent with our aim of applying epigenetic targets to the treatment of lung cancer, a strikingly potent anti-lung cancer scaffold (compound 6) was pinpointed through a series of in-vitro experiments. Notably, the compounds manifested a magnificent activity profile against KRAS and EGFR mutant lung cancer cell lines (IC50 = 0.80 - 0.96 µM), and the effects were found to be mediated through preferential HDAC6 inhibition (IC50 = 12.9 nM). In addition to HDAC6 inhibition, the compounds also elicited HDAC1 and HDAC3 inhibitory activity with an IC50 value of 49.9 nM and 68.5 nM, respectively. The HDAC inhibitory ability of compound 6 was also confirmed from the results of the western blot experiment that revealed its potential to decrease the expression levels of HDAC isoforms (HDAC1, HDAC3, and HDAC6). Noteworthy to mention that complete downregulation of the HDAC6 isoform was exerted by compound 6 at 0.5 and 1 µM. Moreover, in another western blot experiment, treatment with hydroxamic acid 6 led to upregulation of H3 acK9 and α-Tubulin acK40 levels, ascertaining its inhibitory activity toward both the class I HDACs and Class II B HDACs. The results of other assays were also encouraging as treatment with compound 6 led to the suppression of the colony formation ability of A549 cells, induction of apoptosis, and increase in autophagic flux. In silico studies led us to rationalize the results of the experimental assay, and some key interactions of compound 6 with the amino acid residues of HDAC isoforms were identified. In light of the impressive activity spectrum of compound 6, a pH-responsive nanocarrier (hyaluronic acid-compound 6 nanoparticles) was prepared. The dialysis bag approach was used for the assessment of the nanoparticles under both normal and acidic circumstances, and the pH-sensitive nature of hyaluronic acid-compound 6 nanoparticles was confirmed. Delightfully, the nanoformulation was devoid of cytotoxicity against the L929 mouse fibroblast cells (normal settings) and exhibited selective cytotoxicity towards the A549 lung cancer cell lines. In a nutshell, compound 6 appears to be a promising adduct, and a detailed investigation of this compound might yield a therapeutic for the treatment of lung cancer.

Keywords: HDAC inhibitors, lung cancer, scaffold, hyaluronic acid, nanoparticles

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

Abstract:

Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: Rana Alaa El-Deen Ahmed, M. Elemam Shehab, Shereen Morsy, Nermeen Mekawie

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With the growing popularity and acceptance of e-commerce platforms, users face an ever increasing burden in actually choosing the right product from the large number of online offers. Thus, techniques for personalization and shopping guides are needed by users. For a pleasant and successful shopping experience, users need to know easily which products to buy with high confidence. Since selling a wide variety of products has become easier due to the popularity of online stores, online retailers are able to sell more products than a physical store. The disadvantage is that the customers might not find products they need. In this research the customer will be able to find the products he is searching for, because recommender systems are used in some ecommerce web sites. Recommender system learns from the information about customers and products and provides appropriate personalized recommendations to customers to find the needed product. In this paper eleven classification algorithms are comparatively tested to find the best classifier fit for consumer online shopping attitudes and behavior in the experimented dataset. The WEKA knowledge analysis tool, which is an open source data mining workbench software used in comparing conventional classifiers to get the best classifier was used in this research. In this research by using the data mining tool (WEKA) with the experimented classifiers the results show that decision table and filtered classifier gives the highest accuracy and the lowest accuracy classification via clustering and simple cart.

Keywords: classification, data mining, machine learning, online shopping, WEKA

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Authors: Arash Sharafat Vaziri, Leila Aghaghazvini, Soodeh Jahangiri, Mohammad Tahami, Roham Borazjani, Mohammad Naghi Tahmasebi, Hamid Rabie, Hesan Jelodari Mamaghani, Fardis Vosoughi, Maryam Salimi

Abstract:

Aims: It is essential to know the normal extrusion measures in order to detect pathological ones. In this study, we aimed to define some normal reference values for meniscal extrusion in the normal knees during different ranges of motion. Methods: The amount of anterior and posterior portion of meniscal extrusion among twenty-one asymptomatic volunteers (42 knees) were tracked at 0, 45, and 90 degrees of knee flexion using an ultrasound machine. The repeated measures analysis of variance (ANOVA) was used to show the interaction between the amounts of meniscal extrusion and the different degrees of knee flexion. Result: The anterior portion of the lateral menisci at full knee extension (0.59±1.40) and the posterior portion of the medial menisci during 90° flexion (3.06±2.36) showed the smallest and the highest mean amount of extrusion, respectively. The normal average amounts of anterior extrusion were 1.12± 1.17 mm and 0.99± 1.34 mm for medial and lateral menisci, respectively. The posterior meniscal normal extrusions were significantly increasing in both medial and lateral menisci during the survey (F= 20.250 and 11.298; both P-values< 0.001) as they were measured at 2.37± 2.16 mm and 1.53± 2.18 mm in order. Conclusion: The medial meniscus can extrude 1.74± 1.84 mm normally, while this amount was 1.26± 1.82 mm for the lateral meniscus. These measures commonly increased with the rising of knee flexion motion. Likewise, the posterior portion showed more extrusion than the anterior portion on both sides. These measures commonly increased with higher knee flexion.

Keywords: meniscal extrusion, ultrasonography, knee

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Authors: Carol Yue-En Ong, Angelina Hui-Min Tan, Quan Liu, Paul Chi-Lui Ho

Abstract:

A public general hospital in Singapore has recently implemented an automated unit-dose machine in their inpatient dispensary, Swisslog, with the objective of reducing human error and improving patient safety. However, a concern in stability arises as tablets are removed from their original packaging (bottled loose tablets/capsules) and are repackaged into individual, clear plastic wrappers as unit doses in the system. Drugs that are light-sensitive and hygroscopic would be more susceptible to degradation as the wrapper does not offer full protection. Hence, this study was carried out to study the stability of haloperidol tablets and phenytoin capsules that are light-sensitive and hygroscopic respectively. Validated HPLC-UV assays were first established for quantification of these two compounds. The medications involved were put in the Swisslog and sampled every week for one month. The collected data was analysed and showed no degradation over time. This study also explored an alternative approach for drug stability determination-Raman spectroscopy. The advantage of Raman spectroscopy is its high time efficiency and non-destructive nature. The results suggest that drug degradation can indeed be detected using Raman microscopy, but further research is needed to establish this approach for quantification or qualification of compounds. NanoRam®, a portable Raman spectrocope was also used alongside Raman microscopy but was unsuccessful in detecting degradation in this study.

Keywords: drug stability, haloperidol, HPLC, phenytoin, raman spectroscopy, Swisslog

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Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

Abstract:

This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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Authors: Adam Patterson

Abstract:

This study analyzes the self-reported experiences of virtual reality users to develop insight into an optimal learning path for education within virtual reality. This research uses a sample of 1000 observations to statistically define factors influencing (i) immersion level and (ii) motion sickness rating for virtual reality experience respondents of college age. This paper recommends an efficient duration for each virtual reality session, to minimize sickness and maximize engagement, utilizing modern machine learning methods such as association rules. The goal of this research, in augmentation with previous literature, is to inform logistical decisions relating to implementation of pilot instruction for virtual reality at the collegiate level. Future research will include a Randomized Control Trial (RCT) to quantify the effect of virtual reality education on student learning outcomes and engagement measures. Current research aims to maximize the treatment effect within the RCT by optimizing the learning benefits of virtual reality. Results suggest significant gender heterogeneity amongst likelihood of reporting motion sickness. Females are 1.7 times more likely, than males, to report high levels of motion sickness resulting from a virtual reality experience. Regarding duration, respondents were 1.29 times more likely to select the lowest level of motion sickness after an engagement lasting between 24.3 and 42 minutes. Conversely, respondents between 42 to 60 minutes were 1.2 times more likely to select the higher levels of motion sickness.

Keywords: applications and integration of e-education, practices and cases in e-education, systems and technologies in e-education, technology adoption and diffusion of e-learning

Procedia PDF Downloads 62