Search results for: structural vector autoregression

Authors: R. R. Ramsheeja, R. Sreeraj

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For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

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Authors: Adriana Garcia-Gurrola, Carlos Adrian Peña Natividad, Ana Laura Martinez Martinez, Alberto Abraham Escobar Puentes, Estefania Ochoa Ruiz, Aracely Serrano Medina, Abraham Wall Medrano, Simon Yobanny Reyes Lopez

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Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by elevated blood glucose levels. Quercetin is a natural flavonoid with a hypoglycemic effect, but reported data are inconsistent due mainly to the structural instability and low solubility of quercetin. Nanoencapsulation is a distinct strategy to overcome the intrinsic limitations of quercetin. Therefore, this work aims to develop a quercetin nano-formulation based on biopolymeric starch nanoparticles to enhance the release and hypoglycemic effect of quercetin in T2DM induced mice model. Starch-quercetin nanoparticles were synthesized using high-intensity ultrasonication, and structural and colloidal properties were determined by FTIR and DLS. For in vivo studies, CD1 male mice (n=25) were divided into five groups (n=5). T2DM was induced using a high-fat and high-sugar diet for 32 weeks and streptozotocin injection. Group 1 consisted of healthy mice fed with a normal diet and water ad libitum; Group 2 were diabetic mice treated with saline solution; Group 3 were diabetic mice treated with glibenclamide; Group 4 were diabetic mice treated with empty nanoparticles; and Group 5 was diabetic mice treated with quercetin nanoparticles. Quercetin nanoparticles had a hydrodynamic size of 232 ± 88.45 nm, a PDI of 0.310 ± 0.04 and a zeta potential of -4 ± 0.85 mV. The encapsulation efficiency of nanoparticles was 58 ± 3.33 %. No significant differences (p = > 0.05) were observed in biochemical parameters (lipids, insulin, and peptide C). Groups 3 and 5 showed a similar hypoglycemic effect, but quercetin nanoparticles showed a longer-lasting effect. Histopathological studies reveal that T2DM mice groups showed degenerated and fatty liver tissue; however, a treated group with quercetin nanoparticles showed liver tissue like that of the healthy mice group. These results demonstrate that quercetin nano-formulations based on starch nanoparticles are effective alternatives with hypoglycemic effects.

Keywords: quercetin, diabetes mellitus tipo 2, in vivo study, nanoparticles

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: Raymond Feng, Shadi Ghiasi

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An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

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Authors: Chun-Lin Zhang, Min Wan

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With the upgrade development of the tourism industry from the simple sightseeing tour to the leisure and vacation, people's travel idea has undergone a fundamental change. More and more people begin to pursue liberal and personal tourism, so self-driving tourism has become the main form of current tourism activities. With the self-driving tourism representing the general trend, the importance of convenient tourism transportation and perfect road traffic signs have become more and more prominent. A clear urban road traffic signs can help visitors quickly identify the direction and distance to the tourism destination. The purpose of this article is analyzing the planning of urban road traffic signs which can bring positive impact on the participation in the recreation involved of self-driving tourists. The content of this article is divided into three parts. Based on the literature review and theoretical analysis, the first part constructs a structural variance model. The model is from three dimensions: the attention of the self-driving tourists to the urban traffic signs along the road, the perception of the self-driving tourists to the road traffic signs itself, the perceptions of the self-driving tourists to the tourism destination information on the traffic signs. Through this model, the paper aims to explore the influence of the urban road traffic signs to the leisure psychological involvement and leisure behavior involvement of the self-driving tourists. The second part aims to verify through the hypothesis model the questionnaire survey and come to preliminary conclusions. The preliminary conclusions are as follows: firstly, the color, shape, size, setting mode and occurrence frequency of urban road traffic sign have significant influence on the leisure psychological involvement and leisure behavior involvement of the self-driving tourists. Secondly, the influence on the leisure behavior involvement is obviously higher than the influence on the leisure psychological involvement. Thirdly, the information about the tourism destination marked on the urban road traffic signs has not obviously influence on the leisure psychological involvement, but it has distinct influence on the leisure behavior involvement of self-driving tourists. The third part puts forward that the planning of urban road traffic signs should focus on the angle of the impact of road traffic signs on people's psychology and behavior. On the basis of the above conclusions, the paper researches the color, shape, size, setting mode and information labeling of urban road traffic signs so that they can preferably satisfy the demand of the leisure involvement of self-driving tourists.

Keywords: leisure involvement, self-driving tourism, structural equation, urban road traffic signs

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Authors: Timothy E. Frank, Peter J. Amaddio, Elizabeth D. Decko, Alexis M. Tri, Darcy A. Farrell, Cole M. Landes

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Ultra high performance concrete (UHPC) is a class of cementitious composites with a relatively large percentage of cement generating high compressive strength. Additionally, UHPC contains disbursed fibers, which control crack width, carry the tensile load across narrow cracks, and limit spalling. These characteristics lend themselves to a wide range of structural applications when UHPC members are reinforced with longitudinal steel. Efficient use of fibers and longitudinal steel is required to keep lifecycle cost competitive in reinforced UHPC members; this requires full utilization of both the compressive and tensile qualities of the reinforced cementitious composite. The objective of this study is to investigate the shear response of steel-reinforced UHPC beams to guide design decisions that keep initial costs reasonable, limit serviceability crack widths, and ensure a ductile structural response and failure path. Five small-scale, reinforced UHPC beams were experimentally tested. Longitudinal steel, transverse steel, and casting direction were varied. Results indicate that an increase in transverse steel in short-spanned reinforced UHPC beams provided additional shear capacity and increased the peak load achieved. Beams with very large longitudinal steel reinforcement ratios did not achieve yield and fully utilized the tension properties of the longitudinal steel. Casting the UHPC beams from the end or from the middle affected load-carrying capacity and ductility, but image analysis determined the fiber orientation was not significantly different. It is believed the presence of transverse and longitudinal steel reinforcement minimized the effect of different UHPC casting directions. Results support recent recommendations in the literature suggesting a 1% fiber volume fraction is sufficient within UHPC to prevent spalling and provide compressive fracture toughness under extreme loading conditions.

Keywords: fiber orientation, reinforced ultra high performance concrete beams, shear, transverse steel

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Authors: Qiuyu Chen, Bin Long, Junxi Yang

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Located in the southwest of the "roof of the world", Tibet is the origin center of Tibetan Culture.Lhasa, Shigatse and Gyantse are three famous historical and cultural cities in Tibet. They have always been prominent political, economic and cultural cities, and have accumulated the unique aesthetic orientation and value consciousness of Tibet's urban construction. "Archetype" usually refers to the theoretical origin of things, which is the collective unconscious precipitation. The archetype theory fundamentally explores the dialectical relationship between image expression, original form and behavior mode. By abstracting and describing typical phenomena or imagery of the archetype object can observe the essence of objects, explore ways in which object phenomena arise. Applying archetype theory to the field of urban planning helps to gain insight, evaluation, and restructuring of the complex and ever-changing internal structural units of cities. According to existing field investigations, it has been found that Dzong, Temple, Linka and traditional residential systems are important structural units that constitute the urban space of Lhasa, Shigatse and Gyantse. This article applies the thinking method of archetype theory, starting from the imagery expression of urban spatial pattern, using technologies such as ArcGIS, Depthmap, and Computer Vision to descriptively identify the spatial representation and plane relationship of three cities through remote sensing images and historical maps. Based on historical records, the spatial characteristics of cities in different historical periods are interpreted in a hierarchical manner, attempting to clarify the origin of the formation and evolution of urban pattern imagery from the perspectives of geopolitical environment, social structure, religious theory, etc, and expose the growth laws and key driving forces of cities. The research results can provide technical and material support for important behaviors such as urban restoration, spatial intervention, and promoting transformation in the region.

Keywords: archetype theory, urban spatial imagery, original form and pattern, behavioral driving force, Tibet

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Authors: Jawid Ahmad Baktash, Tadashi Shiroma, Tomokazu Nagata, Yuji Taniguchi, Morikazu Nakamura

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The goal of this paper is to explore the use of formal methods for Dynamic Routing, The purpose of network communication with dynamic routing is sending a massage from one node to others by using pacific protocols. In dynamic routing connections are possible based on protocols of Distance vector (Routing Information Protocol, Border Gateway protocol), Link State (Open Shortest Path First, Intermediate system Intermediate System), Hybrid (Enhanced Interior Gateway Routing Protocol). The responsibility for proper verification becomes crucial with Dynamic Routing. Formal methods can play an essential role in the Routing, development of Networks and testing of distributed systems. Event-B is a formal technique consists of describing rigorously the problem; introduce solutions or details in the refinement steps to obtain more concrete specification, and verifying that proposed solutions are correct. The system is modeled in terms of an abstract state space using variables with set theoretic types and the events that modify state variables. Event-B is a variant of B, was designed for developing distributed systems. In Event-B, the events consist of guarded actions occurring spontaneously rather than being invoked. The invariant state properties must be satisfied by the variables and maintained by the activation of the events.

Keywords: dynamic rout RIP, formal method, event-B, pro-B

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Authors: Bin Liu

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MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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Authors: Sutar Rani Ananda, M. V. Murugendrappa

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To investigate electrical properties of conducting polypyrrole (PPy) and cobalt aluminum oxide (CAO) nanocomposites, impedance analyzer in frequency range of 100 Hz to 5 MHz is used. In this work, PPy/CAO nanocomposites were synthesized by chemical oxidation polymerization method in different weight percent of CAO in PPy. The dielectric properties and AC conductivity studies were carried out for different nanocomposites in temperature range of room temperature to 180 °C. With the increase in frequency, the dielectric constant for all the nanocomposites was observed to decrease. AC conductivity of PPy was improved by addition of CAO nanopowder.

Keywords: polypyrrole, dielectric constant, dielectric loss, AC conductivity

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Authors: Jianming Cai

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Exposure to ionizing radiation causes severe damage to human body and an safe and effective radioprotector is urgently required for alleviating radiation damage. In 2008, flagellin, an agonist of TLR5, was found to exert radioprotective effects on radiation injury through activating NF-kB signaling pathway. From then, the radioprotective effects of TLR ligands has shed new lights on radiation protection. CpG-ODN is an unmethylated oligonucleotide which activates TLR9 signaling pathway. In this study, we demonstrated that CpG-ODN has therapeutic effects on radiation injuries induced by γ ray and 12C6+ heavy ion particles. Our data showed that CpG-ODN increased the survival rate of mice after whole body irradiation and increased the number of leukocytes as well as the bone marrow cells. CpG-ODN also alleviated radiation damage on intestinal crypt through regulating apoptosis signaling pathway including bcl2, bax, and caspase 3 etc. By using a radiation-induced pulmonary fibrosis model, we found that CpG-ODN could alleviate structural damage, within 20 week after whole–thorax 15Gy irradiation. In this model, Th1/Th2 imbalance induced by irradiation was also reversed by CpG-ODN. We also found that TGFβ-Smad signaling pathway was regulated by CpG-ODN, which accounts for the therapeutic effects of CpG-ODN in radiation-induced pulmonary injury. On another hand, for high LET radiation protection, we investigated protective effects of CpG-ODN against 12C6+ heavy ion irradiation and found that after CpG-ODN treatment, the apoptosis and cell cycle arrest induced by 12C6+ irradiation was reduced. CpG-ODN also reduced the expression of Bax and caspase 3, while increased the level of bcl2. Then we detected the effect of CpG-ODN on heavy ion induced immune dysfunction. Our data showed that CpG-ODN increased the survival rate of mice and also the leukocytes after 12C6+ irradiation. Besides, the structural damage of immune organ such as thymus and spleen was also alleviated by CpG-ODN treatment. In conclusion, we found that TLR9 ligand, CpG-ODN reduced radiation injuries in response to γ ray and 12C6+ heavy ion irradiation. On one hand, CpG-ODN inhibited the activation of apoptosis induced by radiation through regulating bcl2, bax and caspase 3. On another hand, through activating TLR9, CpG-ODN recruit MyD88-IRAK-TRAF6 complex, activating TAK1, IRF5 and NF-kB pathway, and thus alleviates radiation damage. This study provides novel insights into protection and therapy of radiation damages.

Keywords: TLR9, CpG-ODN, radiation injury, high LET radiation

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Authors: Sinethemba Yakobi, Lindiwe Zuma, Ofentse Pooe

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Gonococcal infections present a notable public health issue, and the major approach for treatment involves using β-lactam antibiotics that specifically target penicillin-binding protein 2 (PBP2) in Neisseria gonorrhoeae. This study examines the influence of flavonoids, namely rutin, on the structural changes of PBP2 in both penicillin-resistant (FA6140) and penicillin-susceptible (FA19) strains. The research clarifies the structural effects of particular mutations, such as inserting an aspartate residue at position 345 (Asp-345a) in the PBP2 protein. The strain FA6140, which is resistant to penicillin, shows specific changes that lead to a decrease in penicillin binding. These mutations, namely P551S and F504L, significantly impact the pace at which acylation occurs and the stability of the strain under high temperatures. Molecular docking analyses investigate the antibacterial activities of rutin and other phytocompounds, emphasizing its exceptional binding affinity and potential as an inhibitor of PBP2. Quercetin and protocatechuic acid have encouraging antibacterial effectiveness, with quercetin displaying characteristics similar to those of drugs. Molecular dynamics simulations offer a detailed comprehension of the interactions between flavonoids and PBP2, highlighting rutin's exceptional antioxidant effects and strong affinity for the substrate binding site. The study's wider ramifications pertain to the pressing requirement for antiviral treatments in the context of the ongoing COVID-19 epidemic. Flavonoids have a strong affinity for binding to PBP2, indicating their potential as inhibitors to impair cell wall formation in N. gonorrhoeae. Ultimately, this study provides extensive knowledge on the interactions between proteins and ligands, the dynamics of the structure, and the ability of flavonoids to combat penicillin-resistant N. gonorrhoeae bacteria. The verified simulation outcomes establish a basis for creating potent inhibitors and medicinal therapies to combat infectious illnesses.

Keywords: phytochemicals, penicillin-binding protein 2, gonococcal infection, ligand-protein interaction, binding energy, neisseria gonorrhoeae FA19, neisseria gonorrhoeae FA6140, flavonoids

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Authors: A. Atli, K. Candelier, J. Alteyrac

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Environmental and sustainability concerns push the industries to manufacture alternative materials having less environmental impact. The Wood Plastic Composites (WPCs) produced by blending the biopolymers and natural fillers permit not only to tailor the desired properties of materials but also are the solution to meet the environmental and sustainability requirements. This work presents the elaboration and characterization of the fully green WPCs prepared by blending a biopolymer, BIOPLAST® GS 2189 and spruce sawdust used as filler with different amounts. Since both components are bio-based, the resulting material is entirely environmentally friendly. The mechanical, thermal, structural properties of these WPCs were characterized by different analytical methods like tensile, flexural and impact tests, Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC) and X-ray Diffraction (XRD). Their water absorption properties and resistance to the termite and fungal attacks were determined in relation with different wood filler content. The tensile and flexural moduli of WPCs increased with increasing amount of wood fillers into the biopolymer, but WPCs became more brittle compared to the neat polymer. Incorporation of spruce sawdust modified the thermal properties of polymer: The degradation, cold crystallization, and melting temperatures shifted to higher temperatures when spruce sawdust was added into polymer. The termite, fungal and water absorption resistance of WPCs decreased with increasing wood amount in WPCs, but remained in durability class 1 (durable) concerning fungal resistance and quoted 1 (attempted attack) in visual rating regarding to the termites resistance except that the WPC with the highest wood content (30 wt%) rated 2 (slight attack) indicating a long term durability. All the results showed the possibility to elaborate the easy injectable composite materials with adjustable properties by incorporation of BIOPLAST® GS 2189 and spruce sawdust. Therefore, lightweight WPCs allow both to recycle wood industry byproducts and to produce a full ecologic material.

Keywords: biodegradability, color measurements, durability, mechanical properties, melt flow index, MFI, structural properties, thermal properties, wood-plastic composites, WPCs

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Authors: Chiara Magliacane

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This project aims to analyse the relationship between the post-conflict Northern Irish environment and youth trauma in deprived areas. Using an anthropological perspective and methodology, the study investigates the possible contribution that a socio-cultural perspective can give to the current research on the field, with a special focus on the role of transgenerational trauma. The recognition of the role that socio-economic determinants have on health is usually a challenge for social researchers. In post-conflict Northern Ireland, the overall lack of research about connections between the social context and youth trauma opens the way to the present project. Anthropological studies on social implications of mental disorders have achieved impressive results in many societies; they show how conditions of sufferance and poverty are not intrinsically given, but are the products of historical processes and events. The continuum of violence and the politics of victimhood sustains a culture of silence and fear in deprived areas; this implies the need of investigating the structural and symbolic violence that lies behind the diffusion of mental suffering. The project refers to these concepts from Medical Anthropology and looks at connections between trauma and social, political and economic structures. Accordingly, the study considers factors such as poverty, unemployment, social inequality and gender and class perspectives. At the same time, the project problematises categories such as youth and trauma. 'Trauma' is currently debated within the social sciences since the 'invention' of the Post-Traumatic Stress Disorder (PTSD) in 1980. Current critics made to its clinical conception show how trauma has been mainly analysed as a memory of the past. On the contrary, medical anthropological research focuses on wider perspectives on society and its structures; this is a new and original approach to the study of youth trauma considering that, to author’s best knowledge, there is no research of this kind regarding Northern Ireland. Methods: Qualitative interviews, participant observation. Expected Impact: Local Northern Ireland organizations, i.e. specific charities that provide mental health support. Ongoing and present connections will ensure they will hear about this research.

Keywords: health and social inequalities, Northern Ireland, structural violence, youth

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Authors: Laura Beckmann, Sabrina Rutter, Isabell Van Ackeren, Nina Bremm, Esther Dominique Klein, Kathrin Racherbäumer

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Current evidence demonstrates that schools in socially disadvantaged contexts are often characterized by lower school performance and lower educational qualifications among the student body, compared to schools in more privileged socio-spacial contexts. At the same time, national and international findings on schools with structural and social challenges show that certain school and classroom development strategies, as well as human and material resources, can significantly contribute to improved school performance of students. The aim of this contribution is to present a 6-year mixed-methods study (Talent Schools in North Rhine-Westphalia), which is designed as a school experiment addressing the well-acknowledged inequality of educational opportunities in the German school system. Started in the year 2019 and funded by the Ministry for School and Education of the State of North Rhine-Westphalia, the study targets schools in socio-spatially disadvantaged areas, which have increasingly been the focus of both public debate and educational policy. In the German-speaking countries, however, there is little knowledge available on the structure and design of complex strategies for school and classroom development that describe successful approaches to the further development of schools in disadvantaged locations in a process-oriented manner. Given these shortcomings, the present study aims at a longitudinal analysis of school and classroom development processes within 60 ‘talent schools’, whereby concrete micro-progressions within individual schools are documented and aggregated to general processes that may either impede or promote development. The main research question is the following: With the help of which strategies and (teaching) concepts, with which use of resources and with which forms of cooperation can schools contribute to the development of student achievement, including educational qualifications and transition rates in education and employment? Thus, the ‘talent schools’ may serve as examples of how social background can successfully be decoupled from educational success at schools with special structural and procedural challenges. The major chances and challenges of this project will be discussed.

Keywords: educational inequality, school development, student achievement, mixed-methods study

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Authors: Zhengkun Yi

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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

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Authors: Abdulkareem M. Hamid, Yaseen Elhebshi, Adam Daïch

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Luotonins and its derivatives (Isoluotonins) are alkaloids from the aerial parts of Peganum nigellastrum Bunge that display three major skeleton types. Luotonins A, B, and E are pyrroloquinazolinoquinoline alkaloids. A few methods were known for the sysnthesis of Isoluotonin. All luotonins have shown promising cytotoxicities towards selected human cancer cell lines, especially against leukemia P-388 cells. Luotonin A is the most active one, with its activity stemming from topoisomerase I-dependent DNA-cleavage. Such intriguing biological activities and unique structures have led not only to the development of synthetic methods for the efficient synthesis of these compounds, but also to interest in structural modifications for improving the biological properties. Recent progress in the study of luotonins is covered.

Keywords: luotonin A, isoluotonin, pyrroloquiolines, alkaloids

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Authors: Fazli Idris, Jihad Mohammad

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The study aims to determine the impact of technology and service operations flexibility, which is divided into external flexibility and internal robustness, on operations costs. A mediation model is proposed that links technology to operations costs via operation flexibility. Drawing on a sample of 475 of operations managers of various service sectors in Malaysia and South Africa, Structural Equation Modeling (SEM) was employed to test the relationship using Smart-PLS procedures. It was found that a significant relationship was established between technologies to operations costs via both operations flexibility dimensions. Theoretical and managerial implications are offered to explain the results.

Keywords: Operations flexibility, technology, costs, mediation

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Authors: Sunita Singh, Rajani Srivastava

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For natural resource management and in other applications about earth observation revolutionary remote sensing technology plays a significant role. One of such application in monitoring and classification of crop types at spatial and temporal scale, as it provides latest, most precise and cost-effective information. Present study emphasizes the use of three different vegetation indices of Rapid Eye imagery on crop type classification. It also analyzed the effect of each indices on classification accuracy. Rapid Eye imagery is highly demanded and preferred for agricultural and forestry sectors as it has red-edge and NIR bands. The three indices used in this study were: the Normalized Difference Vegetation Index (NDVI), the Green Normalized Difference Vegetation Index (GNDVI), and the Normalized Difference Red Edge Index (NDRE) and all of these incorporated the Red Edge band. The study area is Varanasi district of Uttar Pradesh, India and Radial Basis Function (RBF) kernel was used here for the Support Vector Machines (SVMs) classification. Classification was performed with these three vegetation indices. The contribution of each indices on image classification accuracy was also tested with single band classification. Highest classification accuracy of 85% was obtained using three vegetation indices. The study concluded that NDRE has the highest contribution on classification accuracy compared to the other vegetation indices and the Rapid Eye imagery can get satisfactory results of classification accuracy without original bands.

Keywords: GNDVI, NDRE, NDVI, rapid eye, vegetation indices

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Authors: Weikang Peng

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The innovation corridor is an important spatial carrier to promote regional collaborative innovation, and its development process is the spatial re-organization process of regional innovation resources. This paper takes the Nanjing-Zhenjiang G312 Industrial Innovation Corridor, which involves seven municipal districts in Jiangsu Province, as empirical evidence. Based on multi-source spatial big data in 2010, 2016, and 2022, this paper applies triangulated irregular network (TIN), head/tail breaks, regional innovation ecosystem (RIE) niche fitness evaluation model, and social network analysis to carry out empirical research on the spatial organization and functional structural evolution characteristics of innovation corridors and their correlation with the structural evolution of collaborative innovation network. The results show, first, the development of innovation patches in the corridor has fractal characteristics in time and space and tends to be multi-center and cluster layout along the Nanjing Bypass Highway and National Highway G312. Second, there are large differences in the spatial distribution pattern of niche fitness in the corridor in various dimensions, and the niche fitness of innovation patches along the highway has increased significantly. Third, the scale of the collaborative innovation network in the corridor is expanding fast. The core of the network is shifting from the main urban area to the periphery of the city along the highway, with small-world and hierarchical levels, and the core-edge network structure is highlighted. With the development of the Innovation Corridor, the main collaborative mode in the corridor is changing from collaboration within innovation patches to collaboration between innovation patches, and innovation patches with high ecological suitability tend to be the active areas of collaborative innovation. Overall, polycentric spatial layout, graded functional structure, diversified innovation clusters, and differentiated environmental support play an important role in effectively constructing collaborative innovation linkages and the stable expansion of the scale of collaborative innovation within the innovation corridor.

Keywords: innovation corridor development, spatial structure, niche fitness evaluation model, head/tail breaks, innovation network

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Steven D. P. Moore

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An electrical discharge in the air induces an electromagnetic (EM) wave capable of wireless transfer, reception, and conversion back into electrical discharge at a distant location. Following Norton’s ground wave principles, EM wave radiation (EMR) runs parallel to the Earth’s surface. Energy in an EMR wave can move through the air and be focused to create a spark at a distant location, focused by a receiver to generate a local electrical discharge. This local discharge can be amplified and stored but also has the propensity to initiate another EMR wave. In addition to typical EM waves, lightning is also associated with atmospheric events, trans-ionospheric pulse pairs, the most powerful natural EMR signal on the planet. With each lightning strike, regardless of global position, it generates naturally occurring pulse-pairs that are emitted towards space within a narrow cone. An EMR wave can self-propagate, travel at the speed of light, and, if polarized, contain vector properties. If this reflective pulse could be directed by design through structures that have increased probabilities for lighting strikes, it could theoretically travel near the surface of the Earth at light speed towards a selected receiver for local transformation into electrical energy. Through research, there are several influencing parameters that could be modified to model, test, and increase the potential for adopting this technology towards the goal of developing a global grid that utilizes natural sources of energy.

Keywords: electricity, sparkgap, wireless, electromagnetic

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Authors: Imran Hashmi, Sipkaduwa Arachchige Sashika Sureni Wickramasooriya

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Gene-drive technology has emerged as a promising tool for disease control by influencing the population dynamics of disease-carrying organisms. Various gene drive mechanisms, derived from global laboratory experiments, aim to strategically manage and prevent the spread of targeted diseases. One prominent strategy involves population replacement, wherein genetically modified mosquitoes are introduced to replace the existing local wild population. To enhance our understanding and aid in the design of effective release strategies, we employ a comprehensive mathematical model. The utilized approach employs agent-based modeling, enabling the consideration of individual mosquito attributes and flexibility in parameter manipulation. Through the integration of an agent-based model and a meta-population spatial approach, the dynamics of gene drive mosquito spreading in a released site are simulated. The model's outcomes offer valuable insights into future population dynamics, providing guidance for the development of informed release strategies. This research significantly contributes to the ongoing discourse on the responsible and effective implementation of gene drive technology for disease vector control.

Keywords: gene drive, agent-based modeling, disease-carrying organisms, malaria

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Authors: Sugandha Gupta, Arun Kumar Jha

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A large number of ferroelectric materials have been intensely investigated for applications in non-volatile ferroelectric random access memories (FeRAMs), piezoelectric transducers, actuators, pyroelectric sensors, high dielectric constant capacitors, etc. Bismuth layered ferroelectric materials such as Strontium Bismuth Tantalate (SBT) has attracted a lot of attention due to low leakage current, high remnant polarization and high fatigue endurance up to 1012 switching cycles. However, pure SBT suffers from various major limitations such as high dielectric loss, low remnant polarization values, high processing temperature, bismuth volatilization, etc. Significant efforts have been made to improve the dielectric and ferroelectric properties of this compound. Firstly, it has been reported that electrical properties vary with the Sr/ Bi content ratio in the SrBi2Ta2O9 compsition i.e. non-stoichiometric compositions with Sr-deficient / Bi excess content have higher remnant polarization values than stoichiometic SBT compositions. With the objective to improve structural, dielectric, ferroelectric and piezoelectric properties of SBT compound, rare earth holmium (Ho3+) was chosen as a donor cation for substitution onto the Bi2O2 layer. Moreover, hardly any report on holmium substitution in stoichiometric SrBi2Ta2O9 and non-stoichiometric Sr0.8Bi2.2Ta2O9 compositions were available in the literature. The holmium substituted SrBi2-xHoxTa2O9 (x= 0.00-2.0) and Sr0.8Bi2.2Ta2O9 (x=0.0 and 0.01) compositions were synthesized by the solid state reaction method. The synthesized specimens were characterized for their structural and electrical properties. X-ray diffractograms reveal single phase layered perovskite structure formation for holmium content in stoichiometric SBT samples up to x ≤ 0.1. The granular morphology of the samples was investigated using scanning electron microscope (Hitachi, S-3700 N). The dielectric measurements were carried out using a precision LCR meter (Agilent 4284A) operating at oscillation amplitude of 1V. The variation of dielectric constant with temperature shows that the Curie temperature (Tc) decreases on increasing the holmium content. The specimen with x=2.0 i.e. the bismuth free specimen, has very low dielectric constant and does not show any appreciable variation with temperature. The dielectric loss reduces significantly with holmium substitution. The polarization–electric field (P–E) hysteresis loops were recorded using a P–E loop tracer based on Sawyer–Tower circuit. It is observed that the ferroelectric property improve with Ho substitution. Holmium substituted specimen exhibits enhanced value of remnant polarization (Pr= 9.22 μC/cm²) as compared to holmium free specimen (Pr= 2.55 μC/cm²). Piezoelectric co-efficient (d33 values) was measured using a piezo meter system (Piezo Test PM300). It is observed that holmium substitution enhances piezoelectric coefficient. Further, the optimized holmium content (x=0.01) in stoichiometric SrBi2-xHoxTa2O9 composition has been substituted in non-stoichiometric Sr0.8Bi2.2Ta2O9 composition to obtain further enhanced structural and electrical characteristics. It is expected that a new class of ferroelectric materials i.e. Rare Earth Layered Structured Ferroelectrics (RLSF) derived from Bismuth Layered Structured Ferroelectrics (BLSF) will generate which can be used to replace static (SRAM) and dynamic (DRAM) random access memories with ferroelectric random access memories (FeRAMS).

Keywords: dielectrics, ferroelectrics, piezoelectrics, strontium bismuth tantalate

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Authors: Aishwarya Ravindra Fursule, Shruti Kshirsagar

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In the intersection of artificial intelligence and human-centered computing, this paper delves into speech emotion recognition (SER). It presents a comparative analysis of machine learning models such as K-Nearest Neighbors (KNN),logistic regression, support vector machines (SVM), decision trees, ensemble classifiers, and random forests, applied to SER. The research employs four datasets: Crema D, SAVEE, TESS, and RAVDESS. It focuses on extracting salient audio signal features like Zero Crossing Rate (ZCR), Chroma_stft, Mel Frequency Cepstral Coefficients (MFCC), root mean square (RMS) value, and MelSpectogram. These features are used to train and evaluate the models’ ability to recognize eight types of emotions from speech: happy, sad, neutral, angry, calm, disgust, fear, and surprise. Among the models, the Random Forest algorithm demonstrated superior performance, achieving approximately 79% accuracy. This suggests its suitability for SER within the parameters of this study. The research contributes to SER by showcasing the effectiveness of various machine learning algorithms and feature extraction techniques. The findings hold promise for the development of more precise emotion recognition systems in the future. This abstract provides a succinct overview of the paper’s content, methods, and results.

Keywords: comparison, ML classifiers, KNN, decision tree, SVM, random forest, logistic regression, ensemble classifiers

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Authors: Morteza Mohri Esfahani, Amir S. H. Rozatian, Morteza Mozaffari

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Single phase magnetite nanoparticles and Bi-substituted ones were prepared by mechanochemical processing (MCP). The effects of Bi-substitution on the structural and magnetic properties of the nanoparticles were studied by X-ray Diffraction (XRD) and magnetometry techniques, respectively. The XRD results showed that all samples have spinel phase and by increasing Bi content, the main diffraction peaks were shifted to higher angles, which means the lattice parameter decreases from 0.843 to 0.838 nm and then increases to 0.841 nm. Also, the results revealed that increasing Bi content lead to a decrease in saturation magnetization (Ms) from 74.9 to 48.8 emu/g and an increase in coercivity (Hc) from 96.8 to 137.1 Oe.

Keywords: bi-substituted magnetite nanoparticles, mechanochemical processing, X-ray diffraction, magnetism

Procedia PDF Downloads 535

Authors: A. Chellil, A. Nour, S. Lecheb, H.Mechakra, A. Bouderba, H. Kebir

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In this paper, the numerical study for the instability of a composite rotor is presented, under dynamic loading response in the harmonic analysis condition. The analysis of the stress which operates the rotor is done. Calculations of different energies and the virtual work of the aerodynamic loads from the rotor is developed. The use of the composite material for the rotor, offers a good Stability. Numerical calculations on the model develop of three dimensions prove that the damage effect has a negative effect on the stability of the rotor. The study of the composite rotor in transient system allowed to determine the vibratory responses due to various excitations.

Keywords: rotor, composite, damage, finite element, numerical

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Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman

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Over the years,increased demands on railways, the emergence of high-speed trains and heavy axle loads, ageing, and deterioration of the existing tracks, is imposing costly maintenance actions on the railway sector. The need for developing a fast andcost-efficient non-destructive assessment method for the structural evaluation of railway tracksis therefore critically important. The layer modulus is the main parameter used in the structural design and evaluation of the railway track substructure (foundation). Among many recently developed NDTs, Falling Weight Deflectometer (FWD) test, widely used in pavement evaluation, has shown promising results for railway track substructure monitoring. The surface deflection data collected by FWD are used to estimate the modulus of substructure layers through the back-analysis technique. Although there are different commerciallyavailableback-analysis programs are used for pavement applications, there are onlya limited number of research-based techniques have been so far developed for railway track evaluation. In this paper, the suitability, accuracy, and reliability of the BAKFAAsoftware are investigated. The main rationale for selecting BAKFAA as it has a relatively straightforward user interfacethat is freely available and widely used in highway and airport pavement evaluation. As part of the study, a finite element (FE) model of a railway track section near Leominsterstation, Herefordshire, UK subjected to the FWD test, was developed and validated against available field data. Then, a virtual experimental database (including 218 sets of FWD testing data) was generated using theFE model and employed as the measured database for the BAKFAA software. This database was generated considering various layers’ moduli for each layer of track substructure over a predefined range. The BAKFAA predictions were compared against the cone penetration test (CPT) data (available from literature; conducted near to Leominster station same section as the FWD was performed). The results reveal that BAKFAA overestimatesthe layers’ moduli of each substructure layer. To adjust the BAKFA with the CPT data, this study introduces a correlation model to make the BAKFAA applicable in railway applications.

Keywords: back-analysis, bakfaa, railway track substructure, falling weight deflectometer (FWD), cone penetration test (CPT)

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Authors: Salvatore Brischetto, Domenico Cesare

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Major improvements in future aircraft and spacecraft could be those dependent on an increasing use of conventional and unconventional multilayered structures embedding composite materials, functionally graded materials, piezoelectric or piezomagnetic materials, and soft foam or honeycomb cores. Layers made of such materials can be combined in different ways to obtain structures that are able to fulfill several structural requirements. The next generation of aircraft and spacecraft will be manufactured as multilayered structures under the action of a combination of two or more physical fields. In multifield problems for multilayered structures, several physical fields (thermal, hygroscopic, electric and magnetic ones) interact each other with different levels of influence and importance. An exact 3D shell model is here proposed for these types of analyses. This model is based on a coupled system including 3D equilibrium equations, 3D Fourier heat conduction equation, 3D Fick diffusion equation and electric and magnetic divergence equations. The set of partial differential equations of second order in z is written using a mixed curvilinear orthogonal reference system valid for spherical and cylindrical shell panels, cylinders and plates. The order of partial differential equations is reduced to the first one thanks to the redoubling of the number of variables. The solution in the thickness z direction is obtained by means of the exponential matrix method and the correct imposition of interlaminar continuity conditions in terms of displacements, transverse stresses, electric and magnetic potentials, temperature, moisture content and transverse normal multifield fluxes. The investigated structures have simply supported sides in order to obtain a closed form solution in the in-plane directions. Moreover, a layerwise approach is proposed which allows a 3D correct description of multilayered anisotropic structures subjected to field loads. Several results will be proposed in tabular and graphical formto evaluate displacements, stresses and strains when mechanical loads, temperature gradients, moisture content gradients, electric potentials and magnetic potentials are applied at the external surfaces of the structures in steady-state conditions. In the case of inclusions of piezoelectric and piezomagnetic layers in the multilayered structures, so called smart structures are obtained. In this case, a free vibration analysis in open and closed circuit configurations and a static analysis for sensor and actuator applications will be proposed. The proposed results will be useful to better understand the physical and structural behaviour of multilayered advanced composite structures in the case of multifield interactions. Moreover, these analytical results could be used as reference solutions for those scientists interested in the development of 3D and 2D numerical shell/plate models based, for example, on the finite element approach or on the differential quadrature methodology. The correct impositions of boundary geometrical and load conditions, interlaminar continuity conditions and the zigzag behaviour description due to transverse anisotropy will be also discussed and verified.

Keywords: composite structures, 3D shell model, stress analysis, multifield loads, exponential matrix method, layer wise approach

Procedia PDF Downloads 67

Authors: P. Suchismita Behera, V. G. Sathe, A. K. Nigam, P. A. Bhobe

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Co-existence of long-range ferromagnetism and semi-conductivity with correlated behavior of structural, magnetic, optical and electrical properties in various sites doping at CdCr2Se4 makes it a most promising candidate for spin-based electronic applications and magnetic devices. It orders ferromagnetically below TC = 130 K with a direct band gap of ~ 1.5 eV. The magnetic ordering is believed to result from strong competition between the direct antiferromagnetic Cr-Cr spin couplings and the ferromagnetic Cr-Se-Cr exchange interactions. With an aim of understanding the influence of crystal structure on its magnetic properties without disturbing the magnetic site, we investigated four compositions with 3%, 5%, 7% and 10% of Sn-substitution at Cd-site. Partial substitution of Cd2+ (0.78Å) by small sized nonmagnetic ion, Sn4+ (0.55Å), is expected to bring about local lattice distortion as well as a change in electronic charge distribution. The structural disorder would affect the Cd/Sn – Se bonds thus affecting the Cr-Cr and Cr-Se-Cr bonds. Whereas, the charge imbalance created due to Sn4+ substitution at Cd2+ leads to the possibility of Cr mixed valence state. Our investigation of the local crystal structure using the EXAFS, Raman spectroscopy and magnetic properties using SQUID magnetometry of the Cd1-xSnxCr2Se4 series reflects this premise. All compositions maintain the Fd3m cubic symmetry with tetrahedral distribution of Sn at Cd-site, as confirmed by XRD analysis. Lattice parameters were determined from the Rietveld refinement technique of the XRD data and further confirmed from the EXAFS spectra recorded at Cr K-edge. Presence of five Raman-active phonon vibrational modes viz. (T2g (1), T2g (2), T2g (3), Eg, A1g) in the Raman spectra further confirms the crystal symmetry. Temperature dependence of the Raman data provides interesting insight to the spin– phonon coupling, known to dominate the magneto-capacitive properties in the parent compound. Below the magnetic ordering temperature, the longitudinal damping of Eg mode associated with Se-Cd/Sn-Se bending and T2g (2) mode associated to Cr-Se-Cr interaction, show interesting deviations with respect to increase in Sn substitution. Besides providing the estimate of TC, the magnetic measurements recorded as a function of field provide the values of total magnetic moment for all the studied compositions indicative of formation of multiple Cr valences.

Keywords: exchange interactions, EXAFS, ferromagnetism, Raman spectroscopy, spinel chalcogenides

Procedia PDF Downloads 276