Search results for: axial flux induction machine

Authors: Zanele D. Ngwenya, Mustapha Mohammed, Felix D. Dakora

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Legumes are a major source of biological nitrogen, and therefore play a crucial role in maintaining soil productivity in smallholder agriculture in southern Africa. Through their ability to fix atmospheric nitrogen in root nodules, legumes are a better option for sustainable nitrogen supply in cropping systems than chemical fertilisers. For decades, farmers have been highly receptive to the use of rhizobial inoculants as a source of nitrogen due mainly to the availability of elite rhizobial strains at a much lower compared to chemical fertilisers. To improve the efficiency of the legume-rhizobia symbiosis in African soils would require the use of highly effective rhizobia capable of nodulating a wide range of host plants. This study assessed the morphogenetic diversity, photosynthetic functioning and relative symbiotic effectiveness (RSE) of groundnut, jack bean and soybean microsymbionts in Eswatini soils as a first step to identifying superior isolates for inoculant production. According to the manufacturer's instructions, rhizobial isolates were cultured in yeast-mannitol (YM) broth until the late log phase and the bacterial genomic DNA was extracted using GenElute bacterial genomic DNA kit. The extracted DNA was subjected to enterobacterial repetitive intergenic consensus-PCR (ERIC-PCR) and a dendrogram constructed from the band patterns to assess rhizobial diversity. To assess the N2-fixing efficiency of the authenticated rhizobia, photosynthetic rates (A), stomatal conductance (gs), and transpiration rates (E) were measured at flowering for plants inoculated with the test isolates. The plants were then harvested for nodulation assessment and measurement of plant growth as shoot biomass. The results of ERIC-PCR fingerprinting revealed the presence of high genetic diversity among the microsymbionts nodulating each of the three test legumes, with many of them showing less than 70% ERIC-PCR relatedness. The dendrogram generated from ERIC-PCR profiles grouped the groundnut isolates into 5 major clusters, while the jack bean and soybean isolates were grouped into 6 and 7 major clusters, respectively. Furthermore, the isolates also elicited variable nodule number per plant, nodule dry matter, shoot biomass and photosynthetic rates in their respective host plants under glasshouse conditions. Of the groundnut isolates tested, 38% recorded high relative symbiotic effectiveness (RSE >80), while 55% of the jack bean isolates and 93% of the soybean isolates recorded high RSE (>80) compared to the commercial Bradyrhizobium strains. About 13%, 27% and 83% of the top N₂-fixing groundnut, jack bean and soybean isolates, respectively, elicited much higher relative symbiotic efficiency (RSE) than the commercial strain, suggesting their potential for use in inoculant production after field testing. There was a tendency for both low and high N₂-fixing isolates to group together in the dendrogram from ERIC-PCR profiles, which suggests that RSE can differ significantly among closely related microsymbionts.

Keywords: genetic diversity, relative symbiotic effectiveness, inoculant, N₂-fixing

Procedia PDF Downloads 221

Authors: Taiwo Ebenezer Abioye, Alexis Medrano-Tellez, Peter Kayode Farayibi, Peter Kayode Oke,

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Laser metal deposition by wire feedstock has been established as a process which can provide a high material deposition rate with good quality. Sound mechanical properties of the deposited parts are the pre-requisites for the real applications of this process. This paper investigates the laser metal deposition of 308LSi stainless steel wire within a process window. Single tracks and multiple layer thin-walls of 308LSi stainless steel wire were deposited on 304 stainless steel substrate. The grain structures of the built walls were examined using optical microscopy. The mechanical properties of the built walls including the micro-hardness and tensile properties along the transverse and longitudinal directions were investigated using Vickers hardness tester and tensile test machine. Long columnar grains were found growing in the wall building direction (transverse) and nucleation were observed at the boundary between two deposited layers due to remelting of the previously deposited layers. The results showed that the hardness values of the deposited walls (ranging between 194 HV and 167 HV) decreased from the track-substrate interface to the top of the wall. The ultimate tensile strength (UTS) of the wall (518 ± 7 MPa) showed dependence on wall building directions.

Keywords: laser metal deposition, ultimate tensile strength, hardness, wall, microstructure

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

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

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

Procedia PDF Downloads 313

Authors: N. H. Othman, N. Udin, M. Ishak, L. H. Shah

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This study focuses on the effect of pin taper tool ratio on friction stir welding of magnesium alloy AZ31. Two pieces of AZ31 alloy with thickness of 6 mm were friction stir welded by using the conventional milling machine. The shoulder diameter used in this experiment is fixed at 18 mm. The taper pin ratio used are varied at 6:6, 6:5, 6:4, 6:3, 6:2 and 6:1. The rotational speeds that were used in this study were 500 rpm, 1000 rpm and 1500 rpm, respectively. The welding speeds used are 150 mm/min, 200 mm/min and 250 mm/min. Microstructure observation of welded area was studied by using optical microscope. Equiaxed grains were observed at the TMAZ and stir zone indicating fully plastic deformation. Tool pin diameter ratio 6/1 causes low heat input to the material because of small contact surface between tool surface and stirred materials compared to other tool pin diameter ratio. The grain size of stir zone increased with increasing of ratio of rotational speed to transverse speed due to higher heat input. It is observed that worm hole is produced when excessive heat input is applied. To evaluate the mechanical properties of this specimen, tensile test was used in this study. Welded specimens using taper pin ratio 6:1 shows higher tensile strength compared to other taper pin ratio up to 204 MPa. Moreover, specimens using taper pin ratio 6:1 showed better tensile strength with 500 rpm of rotational speed and 150mm/min welding speed.

Keywords: friction stir welding, magnesium AZ31, cylindrical taper tool, taper pin ratio

Procedia PDF Downloads 287

Authors: Benjamin M Dauda, Esther Ibrahim, Sylvester Gadimoh, Asabe Mustapha, Jiyah Mohammed

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Despite diverse optimization techniques on natural hydrophilic fibers, hydrophobic synthetic fibers are still the best oil sorption materials. However, these hydrophobic fibers are not biodegradable, making their disposal problematic. To this end, this work sets out to develop Nonwoven sorbents from epoxy-coated Cotton fibers. As a way of improving the compatibility of the crude oil and reduction of moisture absorption, cotton fibers were coated with epoxy resin by immersion in acetone-thinned epoxy solution. A needle-punching machine was used to convert the fibers into coherent nonwoven sheets. An oil sorption experiment was then carried out. The result indicates that the developed epoxy-modified sorbent has a higher crude oil-sorption capacity compared with those of untreated cotton and commercial polypropylene sorbents. Absorption Curves show that the coated fiber and polypropylene sorbent saturated faster than the uncoated cotton fiber pad. The result also shows that the coated cotton sorbent adsorbed crude faster than the polypropylene sorbent, and the equilibrium exhaustion was also higher. After a simple mechanical squeezing process, the Nonwoven pads could be restored to their original form and repeatedly recycled for oil/water separation. The results indicate that the cotton-coated non-woven pads hold promise for the cleanup of oil spills. Our data suggests that the sorption behaviors of the epoxy-coated Nonwoven pads and their crude oil sorption capacity are relatively stable under various environmental conditions compared to the commercial sheet.

Keywords: oil spill, adsorption, cotton, epoxy, nonwoven

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Authors: Shohreh Ghasemi

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Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

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Authors: Faheema Khan

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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: Jasmin Cowin

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Augmented reality digital technologies, big data, and the need for a teacher workforce able to meet the demands of a knowledge-based society are poised to lead to major changes in the field of education. This paper explores applications and educational use cases of augmented reality digital technologies for educational organizations during the Fourth Industrial Revolution. The Fourth Industrial Revolution requires vision, flexibility, and innovative educational conduits by governments and educational institutions to remain competitive in a global economy. Educational organizations will need to focus on teaching in and for a digital age to continue offering academic knowledge relevant to 21st-century markets and changing labor force needs. Implementation of contemporary disciplines will need to be embodied through learners’ active knowledge-making experiences while embracing ubiquitous accessibility. The power of distributed ledger technology promises major streamlining for educational record-keeping, degree conferrals, and authenticity guarantees. Augmented reality digital technologies hold the potential to restructure educational philosophies and their underpinning pedagogies thereby transforming modes of delivery. Structural changes in education and governmental planning are already increasing through intelligent systems and big data. Reimagining and redesigning education on a broad scale is required to plan and implement governmental and institutional changes to harness innovative technologies while moving away from the big schooling machine.

Keywords: fourth industrial revolution, artificial intelligence, big data, education, augmented reality digital technologies, distributed ledger technology

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Authors: Joy Shihyi Huang

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This paper discusses the concept of community in Anna Deavere Smith’s performance, one that challenges and explores existing notions of justice and the other. In contrast to unwavering assumptions of essentialism that have helped to propel a discourse on moral agency within the black community, Smith employs postmodern ideas in which the theatrical attributes of doubling and repetition are conceptualized as part of what Marvin Carlson coined as a ‘memory machine.’ Her dismissal of the need for linear time, such as that regulated by Aristotle’s The Poetics and its concomitant ethics, values, and emotions as a primary ontological and epistemological construct produced by the existing African American historiography, demonstrates an urgency to produce an alternative communal self to override metanarratives in which the African Americans’ lives are contained and sublated by specific historical confines. Drawing on Emmanuel Levinas’ theories in ethics, specifically his notion of ‘proximity’ and ‘the third,’ the paper argues that Smith enacts a new model of ethics by launching an acting method that eliminates the boundary of self and other. Defying psychological realism, Smith conceptualizes an approach to acting that surpasses the mere mimetic value of invoking a ‘likeness’ of an actor to a character, which as such, resembles the mere attribution of various racial or sexual attributes in identity politics. Such acting, she contends, reduces the other to a representation of, at best, an ultimate rendering of me/my experience. She instead appreciates ‘unlikeness,’ recognizes the unavoidable actor/character gap as a power that humbles the self, whose irreversible journey to the other carves out its own image.

Keywords: Anna Deavere Smith, Emmanuel Levinas, other, performance

Procedia PDF Downloads 155

Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

Procedia PDF Downloads 216

Authors: Varun Kumar, Chandra Shakher

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Micro-optical components such as microlenses and microlens array have numerous engineering and industrial applications for collimation of laser diodes, imaging devices for sensor system (CCD/CMOS, document copier machines etc.), for making beam homogeneous for high power lasers, a critical component in Shack-Hartmann sensor, fiber optic coupling and optical switching in communication technology. Also micro-optical components have become an alternative for applications where miniaturization, reduction of alignment and packaging cost are necessary. The compliance with high-quality standards in the manufacturing of micro-optical components is a precondition to be compatible on worldwide markets. Therefore, high demands are put on quality assurance. For quality assurance of these lenses, an economical measurement technique is needed. For cost and time reason, technique should be fast, simple (for production reason), and robust with high resolution. The technique should provide non contact, non-invasive and full field information about the shape of micro- optical component under test. The interferometric techniques are noncontact type and non invasive and provide full field information about the shape of the optical components. The conventional interferometric technique such as holographic interferometry or Mach-Zehnder interferometry is available for characterization of micro-lenses. However, these techniques need more experimental efforts and are also time consuming. Digital holography (DH) overcomes the above described problems. Digital holographic microscopy (DHM) allows one to extract both the amplitude and phase information of a wavefront transmitted through the transparent object (microlens or microlens array) from a single recorded digital hologram by using numerical methods. Also one can reconstruct the complex object wavefront at different depths due to numerical reconstruction. Digital holography provides axial resolution in nanometer range while lateral resolution is limited by diffraction and the size of the sensor. In this paper, Mach-Zehnder based digital holographic interferometric microscope (DHIM) system is used for the testing of transparent microlenses. The advantage of using the DHIM is that the distortions due to aberrations in the optical system are avoided by the interferometric comparison of reconstructed phase with and without the object (microlens array). In the experiment, first a digital hologram is recorded in the absence of sample (microlens array) as a reference hologram. Second hologram is recorded in the presence of microlens array. The presence of transparent microlens array will induce a phase change in the transmitted laser light. Complex amplitude of object wavefront in presence and absence of microlens array is reconstructed by using Fresnel reconstruction method. From the reconstructed complex amplitude, one can evaluate the phase of object wave in presence and absence of microlens array. Phase difference between the two states of object wave will provide the information about the optical path length change due to the shape of the microlens. By the knowledge of the value of the refractive index of microlens array material and air, the surface profile of microlens array is evaluated. The Sag of microlens and radius of curvature of microlens are evaluated and reported. The sag of microlens agrees well within the experimental limit as provided in the specification by the manufacturer.

Keywords: micro-optics, microlens array, phase map, digital holographic interferometric microscopy

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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 56

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 148

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

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Authors: D. J. Kalita

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

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

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Authors: 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

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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

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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

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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

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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

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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

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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

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Authors: Olubajo Olumide Olu

Abstract:

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

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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

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

Abstract:

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

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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

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Authors: Prajna Paramita Naik, Sujit Kumar Bhutia

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Background: Regardless of the development multimodal treatment strategies, oral squamous cell carcinoma (OSCC) is often associated with a high rate of recurrence, metastasis and chemo- and radio- resistance. The present study inspected the relevance of CD44, ABCB1 and ADAM17 expression as a putative stem cell compartment in oral squamous cell carcinoma (OSCC) and deciphered the role of autophagy in regulating the expression of aforementioned proteins, stemness and chemoresistance. Methods: A retrospective analysis of CD44, ABCB1 and ADAM17 expression with respect to the various clinicopathological factors of sixty OSCC patients were determined via immunohistochemistry. The correlation among CD44, ABCB1 and ADAM17 expression was established. Sphere formation assay, flow cytometry and fluorescence microscopy were conducted to elucidate the stemness and chemoresistance nature of established cisplatin-resistant oral cancer cells (FaDu). The pattern of expression of CD44, ABCB1 and ADAM17 in parental (FaDu-P) and resistant FaDu cells (FaDu-CDDP-R) were investigated through fluorescence microscopy. Western blot analysis of autophagy marker proteins was performed to compare the status of autophagy in parental and resistant FaDu cell. To investigate the role of autophagy in chemoresistance and stemness, sphere formation assay, immunofluorescence and Western blot analysis was performed post transfection with siATG14 and the level of expression of autophagic proteins, mitochondrial protein and stemness-associated proteins were analyzed. The statistical analysis was performed by GraphPad Prism 4.0 software. p-value was defined as follows: not significant (n.s.): p > 0.05;*: p ≤ 0.05; **: p ≤ 0.01; ***: p ≤ 0.001; ****: p ≤ 0.0001 were considered statistically significant. Results: In OSCC, high CD44, ABCB1 and ADAM17 expression were significantly correlated with higher tumor grades and poor differentiation. However, the expression of these proteins was not related to the age and sex of OSCC patients. Moreover, the expression of CD44, ABCB1 and ADAM17 were positively correlated with each other. In vitro and OSCC tissue double labeling experiment data showed that CD44+ cells were highly associated with ABCB1 and ADAM17 expression. Further, FaDu-CDDP-R cells showed higher sphere forming capacity along with increased fraction of the CD44+ population and β-catenin expression FaDu-CDDP-R cells also showed accelerated expression of CD44, ABCB1 and ADAM17. A comparatively higher autophagic flux was observed in FaDu-CDDP-R against FaDu-P cells. The expression of mitochondrial proteins was noticeably reduced in resistant cells as compared to parental cells indicating the occurrence of autophagy-mediated mitochondrial degradation in oral cancer. Moreover, inhibition of autophagy was coupled with the decreased formation of orospheres suggesting autophagy-mediated stemness in oral cancer. Blockade of autophagy was also found to induce the restoration of mitochondrial proteins in FaDu-CDDP-R cells indicating the involvement of mitophagy in chemoresistance. Furthermore, a reduced expression of CD44, ABCB1 and ADAM17 was also observed in ATG14 deficient cells FaDu-P and FaDu-CDDP-R cells. Conclusion: The CD44+ ⁄ABCB1+ ⁄ADAM17+ expression in OSCC might be associated with chemoresistance and a putative CSC compartment. Further, the present study highlights the contribution of mitophagy in chemoresistance and confirms the potential involvement of autophagic regulation in acquisition of stem-like characteristics in OSCC.

Keywords: ABCB1, ADAM17, autophagy, CD44, chemoresistance, mitophagy, OSCC, stemness

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Authors: Tran Ich Thinh, Nguyen Manh Cuong

Abstract:

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

Abstract:

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 75