Search results for: received signal strength indicator

Authors: Yichao Ma, Chengsiong Chin, Wailok Woo

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Since the last decade, there has been a rapid growth in digital multimedia, such as high-resolution media files and three-dimentional movies. Hence, there is a need for large digital storage such as Hard Disk Drive (HDD). As such, users expect to have a quieter HDD in their laptop. In this paper, a jury test has been conducted on a group of 34 people where 17 of them are students who is the potential consumer, and the remaining are engineers who know the HDD. A total 13 HDD sound samples have been selected from over hundred HDD noise recordings. These samples are selected based on an agreed subjective feeling. The samples are played to the participants using head acoustic playback system which enabled them to experience as similar as possible the same environment as have been recorded. Analysis has been conducted and the obtained results have indicated different group has different perception over the noises. Two neural network-based acoustic annoyance models are established based on back propagation neural network. Four psychoacoustic metrics, loudness, sharpness, roughness and fluctuation strength, are used as the input of the model, and the subjective evaluation results are taken as the output. The developed models are reasonably accurate in simulating both training and test samples.

Keywords: hdd noise, jury test, neural network model, psychoacoustic annoyance

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

Procedia PDF Downloads 156

Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

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Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

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Authors: Mabtho Moreroa-Monyelo, Grace Ijoma, Rosina Nkuna, Tonderayi Matambo

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A moving bed biofilm reactor (MBBR) was used for the bioremediation of high strength chemical oxygen demand (COD) Fisher-Tropsch (FT) wastewater. The aerobic MBBR system was operated over 60 days. For metagenomics profile assessment of the targeted 16S sequence of bacteria involved in the bioremediation of the chemical compounds, sludge samples were collected every second day of operation. Parameters such as pH and COD were measured daily to compare the system efficiency as the changedin microbial diversity progressed. The study revealed that pH was a contributing factor to microbial diversity, which further affected the efficiency of the MBBR system. The highest COD removal rate of 86.4% was achieved at pH 8.3. It was observed that when there was more, A higher bacterial diversity led to an improvement in the reduction of COD. Furthermore, an OTUof 4530 was obtained, which were divided into 12 phyla, 27 classes, 44 orders, 74 families, and 138 genera across all sludge samples from the MBBR. A determination of the relative abundance of microorganisms at phyla level indicates that the most abundant phylum on day it was Firmicutes (50%); thereafter, the most abundant phylum changed toProteobacteria.

Keywords: biodegradation, fischer-tropsch wastewater, metagenomics, moving bed biofilm reactor

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Authors: Nneka N. Uchegbu

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Physical, sensory properties and hypoglycemic effect of crackers produced from sprouted pigeon pea, unripe plantain and brewers’ spent grain fed to diabetic rats were investigated. Different composite flours were used to produce crackers. Physical and sensory properties of the crackers, the blood serum of the rats and changes in the rat body weight were measured. Spread ratio and break strength of the crackers from different flour blends ranges from 7.01 g to 8.51 g and 1.87 g to 3.01 g respectively. The acceptability of the crackers revealed that Sample A (100% wheat crackers) was not significantly (p>0.05) different from Samples C and D. Feeding the rats with formulated crackers caused an increase in the body weight of the rats but a reduced body weight was observed in diabetic rats fed with normal rat feed. The result indicated that cracker produced from the formulated flour blends caused a significant hypoglycemic effect in diabetic rats and led to a reduction of measured biochemical indices. Therefore, this work showed that consumption of crackers from the above formulated flour blend was able to decrease hyperglycemia in diabetic rats.

Keywords: hypoglyceamia, hyperlipidimia, total lipid, triglyceride, total cholesterol

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Authors: Evan W. Krieger, Vijayan K. Asari, Saibabu Arigela

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Video imagery captured for real-time security and surveillance applications is typically captured in complex lighting conditions. These less than ideal conditions can result in imagery that can have underexposed or overexposed regions. It is also typical that the video is too low in resolution for certain applications. The purpose of security and surveillance video is that we should be able to make accurate conclusions based on the images seen in the video. Therefore, if poor lighting and low resolution conditions occur in the captured video, the ability to make accurate conclusions based on the received information will be reduced. We propose a solution to this problem by using image preprocessing to improve these images before use in a particular application. The proposed algorithm will integrate an intensity enhancement algorithm with a super resolution technique. The intensity enhancement portion consists of a nonlinear inverse sign transformation and an adaptive contrast enhancement. The super resolution section is a single image super resolution technique is a Fourier phase feature based method that uses a machine learning approach with kernel regression. The proposed technique intelligently integrates these algorithms to be able to produce a high quality output while also being more efficient than the sequential use of these algorithms. This integration is accomplished by performing the proposed algorithm on the intensity image produced from the original color image. After enhancement and super resolution, a color restoration technique is employed to obtain an improved visibility color image.

Keywords: dynamic range compression, multi-level Fourier features, nonlinear enhancement, super resolution

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Authors: Min Kyung An

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In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional

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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: Maureen Gibney

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The examination of narrative in psychology has a long tradition, starting with psychoanalytic theory and embracing over time cognitive, social, and personality psychology, among others. Narrative use has been richly detailed as well in medicine, nursing, and social service. One aspect of narrative that has ready utility in higher education and in clinical work is the exploration of suffering and its meaning. Because it is such a densely examined topic, suffering provides a window into identity, sense of purpose, and views of humanity and of the divine. Storytelling analysis permits an exploration of a host of specific manifestations of suffering such as pain and illness, moral injury, and the impact of prolonged suffering on love and relationships. This presentation will review the origins and current understandings of narrative theory in general, and will draw from psychology, medicine, ethics, nursing, and social service in exploring the topic of suffering in particular. It is suggested that the use of narrative themes such as meaning making, agency and communion, generativity, and loss and redemption allows for a finely grained analysis of common and more atypical sources of suffering, their resolution, and the acceptance of their continuation when resolution is not possible. Such analysis, used in professional work and in higher education, can enrich one’s empathy and one’s sense of both the fragility and strength of everyday life.

Keywords: meaning making, narrative theory, suffering, teaching

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Authors: Sahar Esmaeili, Ramezanali Ghaderi sanavi, Masoomeh Maarefvand, Samaneh Hosseinzadeh

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Introduction: Conducted researches reveal that nowadays, 60 percent of women around the world are the households. The adverse economic condition causes female-headed households and their children to be the most vulnerable people against social harm. Mainly a symptoms of mental illness such as depression, anxiety, obsession and aggression can be seen in female-headed households and their children are potentially exposed to issues such as crime-work, child labor in the black and informal jobs, education deprivation and malnutrition. The aim of this study is to evaluate the effect of Orem self-care education with the FGC technique on the public health of female-headed households. Methods: Sixty-four Female-headed householders who were supported by Saleh Foundation participated in a clinical trial study and were assigned to the case (n=32) and control (n=32) groups. The case group received 4-session Orem’s self-care education with family group conferencing technique. Data were collected using the demographic questionnaire and General Health Questionnaire (GHQ-28) prior to intervention and post-intervention. ANOVA was used to evaluate outcomes. Results: The results showed significant improvement of the intervention group in GHQ (P<0.001) and subscales of Physical Health (P<0.001) Agitation and Insomnia (P<0.001) and Social disorder (P<0.001) and Depression (P<0.001) compared with the control group after the intervention. Conclusion: The intervention of Orem’s self-care education with family group conferencing technique was effective in improving the General Health of Female-headed households

Keywords: orem’s self-care, female-headed households, general health, group

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Authors: O. Yeret

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Visual resources are all around us, especially in today's media-driven world, which gravitates, more and more, towards the visual. As a result, authentic resources, such as television advertisements, become testaments – authentic cultural materials – that reflect the landscape of certain groups and communities during a specific point in time. Engaging language students with popular advertisements can provide a great opportunity for developing cultural awareness, a component that is sometimes overlooked in the foreign language classroom. This paper will showcase practical examples of using Israeli Television Ads in various Modern Hebrew language courses. Several approaches for combining the study of language and culture, through the use of advertisements, will be included; for example, targeted assignments based on students' proficiency levels, such as: asking to recognize vocabulary words and answer basic information questions, as opposed to commenting on the significance of an ad and analyzing its particular cultural elements. The use of visual resources in the language classroom does not only enable students to learn more about the culture of the target language, but also to combine their language skills. Most often, interacting with an ad requires close listening and some reading (through captions or other data). As students analyze the ad, they employ their writing and speaking skills by answering questions in text or audio form. Hence, these interactions are able to elicit complex language use across the four domains: listening, speaking, writing, and reading. This paper will include examples of practical assignments that were developed for several Modern Hebrew language courses, together with the specific advertisements and questions related to them. Conclusions from the process and recent feedback notes received from students regarding the use of visual resources will be mentioned as well.

Keywords: authentic materials, cultural awareness, second language acquisition, visual resources

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Authors: Bekhemmas Youcef

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The category of the disabled, like other social groups, is considered to have been affected by fate with a disability that led to a reduction in the fulfillment of its social roles to the fullest extent or led to its complete abandonment. Psychological, and until we understand its behavioral methods that express a lot of this complexity and intertwining, and despite all that, this category has not yet received the appropriate great interest from specialized researchers, and even officials, and it is natural that the category of people with disabilities has psychological and social requirements in order to regains their capabilities or some From her, it also needs to prepare the environment in which she lives in order to integrate into society As the motor disability is one of the most common types of disability in the world, and it is constantly increasing, considering the increase in the causes leading to it, such as the traffic accident, and the motor disability often affects individuals from a psychological point of view, but it also affects their social surroundings, whether close or extended, and thus it draws limits and quality For their way of life, as well as determining roles for them as actors of a special kind within their societies. The methodology is similar to the organizational framework for the production of any scientific knowledge and based on the fact that sociology is a project that aims to understand and interpret the social reality scientifically and through the nature of the subject studied in the framework of the reality of the disabled in the city and in order to get closer to the daily life of the physically disabled within the urban center, we adopted the qualitative approach A choice that complies with the spirit of Viberian sociology, especially since Max Weber insists on the need to search for the meaning that the social actor gives to his behavior. Through the results reached in this study, it was found that the city still suffers from several deficiencies at the level of equipment and urban planning in a way that keeps pace with the number of people with disabilities in the city.

Keywords: physically, handicapped, in, the city

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Authors: Mitchell Gohnert, Ryan Bradley

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This paper reviews some fundamental concepts of structural optimization, which are based on the type of materials used in construction and the shape of the structure. The first step in structural optimization is to break down all internal forces in a structure into fundamental stresses, which are tensions and compressions. Knowing the stress patterns directs our selection of structural shapes and the most appropriate type of construction material. In our selection of materials, it is essential to understand all construction materials have flaws, or micro-cracks, which reduce the capacity of the material, especially when subjected to tensions. Because of material defects, many construction materials perform significantly better when subjected to compressive forces. Structures are also more efficient if bending moments are eliminated. Bending stresses produce high peak stresses at each face of the member, and therefore, substantially more material is required to resist bending. The shape of the structure also has a profound effect on stress levels. Stress may be reduced dramatically by simply changing the shape. Catenary, triangular and linear shapes are the fundamental structural forms to achieve optimal stress flow. If the natural flow of stress matches the shape of the structures, the most optimal shape is determined.

Keywords: arches, economy of stresses, material strength, optimization, shells

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Authors: YingWei Tan, XueFeng Ding

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Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

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Authors: M. Abir Hossain, M. Shahjada Tarafder

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This paper deals with the analysis of potential flow past two-dimensional body by discretizing the body into panels where the Laplace equation was applied to each panel. The Laplace equation was solved at each panel by applying the boundary conditions. The boundary condition was applied at each panel to mathematically formulate the problem and then convert the problem into a computer-solvable problem. Kutta condition was applied at both the leading and trailing edges to see whether the condition is satisfied or not. Another approach that is applied for the analysis is Vortex Lattice Method (VLM). A vortex ring is considered at each control point. Using the Biot-Savart Law the strength at each control point is calculated and hence the pressure differentials are measured. For the comparison of the analytic result with the experimental result, different NACA section hydrofoil is used. The analytic result of NACA 0012 and NACA 0015 are compared with the experimental result of Abbott and Doenhoff and found significant conformity with the achieved result.

Keywords: Kutta condition, Law of Biot-Savart, pressure differentials, potential flow, vortex lattice method

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Authors: Pawel Twardowski, Tadeusz Chwalczuk, Szymon Wojciechowski

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Inconel 718 is a material characterized by the unique mechanical properties, high temperature strength, high thermal conductivity and the corrosion resistance. However, these features affect the low machinability of this material, which is usually manifested by the intense tool wear and low surface finish. Therefore, this paper is focused on the evaluation of surface roughness during hybrid machining of Inconel 718. The primary aim of the study was to determine the relations between the vibrations generated during hybrid turning and the formed surface roughness. Moreover, the comparison of tested machining techniques in terms of vibrations, tool wear and surface roughness has been made. The conducted tests included the face turning of Inconel 718 with laser assistance in the range of variable cutting speeds. The surface roughness was inspected with the application of stylus profile meter and accelerations of vibrations were measured with the use of three-component piezoelectric accelerometer. The carried out research shows that application of laser assisted machining can contribute to the reduction of surface roughness and cutting vibrations, in comparison to conventional turning. Moreover, the obtained results enable the selection of effective cutting speed allowing the improvement of surface finish and cutting dynamics.

Keywords: hybrid machining, nickel alloys, surface roughness, turning, vibrations

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Authors: Andreas Rudisch, Ralf Lampert, Andreas Kolbitsch

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It is a well-known fact among the engineering community that earthquakes with comparatively low magnitudes can cause serious damage to nonstructural components (NSCs) of buildings, even when the supporting structure performs relatively well. Past research works focused mainly on NSCs of nuclear power plants and industrial plants. Particular attention should also be given to architectural façade elements of old masonry buildings (e.g. ornamental figures, balustrades, vases), which are very vulnerable under seismic excitation. Large numbers of these historical nonstructural components (HiNSCs) can be found in highly frequented historical city centers and in the event of failure, they pose a significant danger to persons. In order to estimate the vulnerability of acceleration sensitive HiNSCs, the peak horizontal floor acceleration (PHFA) is used. The PHFA depends on the dynamic characteristics of the building, the ground excitation, and induced nonlinearities. Consequently, the PHFA can not be generalized as a simple function of height. In the present research work, an extensive case study was conducted to investigate the influence of induced nonlinearity on the PHFA for old masonry buildings. Probabilistic nonlinear FE time-history analyses considering three different hazard levels were performed. A set of eighteen synthetically generated ground motions was used as input to the structure models. An elastoplastic macro-model (multiPlas) for nonlinear homogenized continuum FE-calculation was calibrated to multiple scales and applied, taking specific failure mechanisms of masonry into account. The macro-model was calibrated according to the results of specific laboratory and cyclic in situ shear tests. The nonlinear macro-model is based on the concept of multi-surface rate-independent plasticity. Material damage or crack formation are detected by reducing the initial strength after failure due to shear or tensile stress. As a result, shear forces can only be transmitted to a limited extent by friction when the cracking begins. The tensile strength is reduced to zero. The first goal of the calibration was the consistency of the load-displacement curves between experiment and simulation. The calibrated macro-model matches well with regard to the initial stiffness and the maximum horizontal load. Another goal was the correct reproduction of the observed crack image and the plastic strain activities. Again the macro-model proved to work well in this case and shows very good correlation. The results of the case study show that there is significant scatter in the absolute distribution of the PHFA between the applied ground excitations. An absolute distribution along the normalized building height was determined in the framework of probability theory. It can be observed that the extent of nonlinear behavior varies for the three hazard levels. Due to the detailed scope of the present research work, a robust comparison with code-recommendations and simplified PHFA distributions are possible. The chosen methodology offers a chance to determine the distribution of PHFA along the building height of old masonry structures. This permits a proper hazard assessment of HiNSCs under seismic loads.

Keywords: nonlinear macro-model, nonstructural components, time-history analysis, unreinforced masonry

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Authors: Qura-tul-aain Khair

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Purpose- The purpose of this paper is to empirically examining the strength of association of responsive market orientation and proactive market orientation with new product performance and exploring the possible moderating role of organizational learning based on contingency theory. Design/methodology/approach- Data for this study was collected from FMCG manufacturing industry and services industry, where customers are in contact frequently and responses are recorded on continuous basis. Sample was collected through convenience sampling. The data collected from different marketing department and sales personnel were analysed using SPSS 16 version. Findings- The paper finds that responsive market orientation is more strongly associated with new product performance. The moderator, organizational learning, plays it significant role on the relationship between responsive market orientation and new product performance. Research limitations/implications- this paper has taken sample from just FMCG industry and service industry, more work can be done regarding how different-markets require different market orientation behaviours. Originality/value- This paper will be useful for foreign business looking for investing and expanding in Pakistan, they can find opportunity to get sustained competitive advantage through exploring the proactive side of market orientation and importance of organizational learning.

Keywords: organizational learning, proactive market orientation, responsive market orientation, new product performance

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Authors: Xiaolin Zeng, Lei Cheng, Zhirong Li, Xueping Liu

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Aiming at the problem of low accuracy and susceptibility to cultural relic diseases in the generation of high-resolution archaeology drawings by current image generation algorithms, an archaeology drawings generation algorithm based on a conditional generative adversarial network is proposed. An attention mechanism is added into the high-resolution image generation network as the backbone network, which enhances the line feature extraction capability and improves the accuracy of line drawing generation. A dual-branch parallel architecture consisting of two backbone networks is implemented, where the semantic translation branch extracts semantic features from orthophotographs of cultural relics, and the gradient screening branch extracts effective gradient features. Finally, the fusion fine-tuning module combines these two types of features to achieve the generation of high-quality and high-resolution archaeology drawings. Experimental results on the self-constructed archaeology drawings dataset of grotto temple statues show that the proposed algorithm outperforms current mainstream image generation algorithms in terms of pixel accuracy (PA), structural similarity (SSIM), and peak signal-to-noise ratio (PSNR) and can be used to assist in drawing archaeology drawings.

Keywords: archaeology drawings, digital heritage, image generation, deep learning

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Authors: O. Soji-Omoniwa, N. O. Muhammad, L. A. Usman, B. P. Omoniwa

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This study was conducted to investigate the effect of the leaf essential oil of C. sinensis harvested at 7.00a.m and 4.00p.m on some Liver and Kidney function indices of diabetic rats as well as investigate the effect of time of harvest on the observed effect. Experimental animals were divided into 4 groups (A, B, C and D). Diabetes mellitus was induced in all animals, except the normal control group (Group A), by injecting 150mg/kg body weight of alloxan monohydrate intraperitoneally. Group A received distilled water while group B (diabetic control group) was not treated. Group C and D were treated with leaf essential oil of C. sinensis harvested at 7.00 a.m and 4.00 p.m respectively at a dose of 110 mg/kg body weight every other day for 15 days. Alkaline phosphatase (ALP), Alanine Transaminase (ALT) and Aspartate Transaminase (AST) activity was evaluated in the serum, Liver and Kidney of studied animals. Total and Direct Bilirubin level, Total Protein and Globulin, Creatinine and Urea level were also evaluated. Result showed that creatinine and urea, serum ALP, AST and ALT levels was significantly reduced (p < 0.05), while the levels of total Protein and Globulin increased significantly (p < 0.05) for the treated animals compared to the diabetic control group. In conclusion, the leaf essential oil of Citrus sinensis ameliorated the impaired renal and liver function; however, the time of harvest of the leaf does not significantly affect its ameliorative effect.

Keywords: C. sinensis, function indices, harvest time, leaf essential oil.

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Authors: Nicholas Reinicke, Brennan Borlaug, Matthew Moniot

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The COVID-19 pandemic has resulted in a significant change in driving behavior as people respond to the new environment. However, existing methods for analyzing driver behavior, such as travel surveys and travel demand models, are not suited for incorporating abrupt environmental disruptions. To address this, we analyze a set of high-resolution trip data and introduce two new metrics for quantifying driving behavioral shifts as a function of time, allowing us to compare the time periods before and after the pandemic began. We apply these metrics to the Denver, Colorado metropolitan statistical area (MSA) to demonstrate the utility of the metrics. Then, we present a case study for comparing two distinct MSAs, Louisville, Kentucky, and Des Moines, Iowa, which exhibit significant differences in the makeup of their labor markets. The results indicate that although the regions of study exhibit certain unique driving behavioral shifts, emerging trends can be seen when comparing between seemingly distinct regions. For instance, drivers in all three MSAs are generally shown to have spent more time at residential locations and less time in workplaces in the time period after the pandemic started. In addition, workplaces that may be incompatible with remote working, such as hospitals and certain retail locations, generally retained much of their pre-pandemic travel activity.

Keywords: COVID-19, driver behavior, GPS data, signal analysis, telework

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Authors: M. Solairaju, Nithin J. Thomas, S. Ganesan

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Each and every rotating part of a machine element consists of bearings within its structure. In particular, the rolling element bearings such as cylindrical roller bearing and deep groove ball bearings are frequently used. Improper handling, excessive loading, improper lubrication and sealing cause bearing damage. Hence health monitoring of bearings is an important aspect for radiation pattern of bearing vibration is computed using the dipole model. Sound pressure level for defect-free and race defect the prolonged life of machinery and auto motives. This paper presents modeling and analysis of Acoustic response of deep groove ball bearing with localized race defects. Most of the ball bearings, especially in machine tool spindles and high-speed applications are pre-loaded along an axial direction. The present study is carried out with axial preload. Based on the vibration response, the orbit motion of the inner race is studied, and it was found that the oscillation takes place predominantly in the axial direction. Simplified acoustic is estimated. Acoustic response shows a better indication in identifying the defective bearing. The computed sound signal is visualized in diagrammatic representation using Symmetrised Dot Pattern (SDP). SDP gives better visual distinction between the defective and defect-free bearing

Keywords: bearing, dipole, noise, sound

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Authors: Jian Zheng

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Three-dimensional (3D) network structure has been recognized as an effective approach to enhance the mechanical and thermal conductive properties of polymeric composites. However, it has not been applied in energetic materials. In this work, a fluoropolymer based composite with vertically oriented and interconnected 3D graphite network was fabricated for polymer bonded explosives (PBXs). Here, the graphite and graphene oxide platelets were mixed, and self-assembled via rapid freezing and using crystallized ice as the template. The 3D structure was finally obtained by freezing-dry and infiltrating with the polymer. With the increasing of filler fraction and cooling rate, the thermal conductivity of the polymer composite was significantly improved to 2.15 W m⁻¹ K⁻¹ by 1094% than that of pure polymer. Moreover, the mechanical properties, such as tensile strength and elastic modulus, were enhanced by 82% and 310%, respectively, when the highly ordered structure was embedded in the polymer. We attribute the increased thermal and mechanical properties to this 3D network, which is beneficial to the effective heat conduction and force transfer. This study supports a desirable way to fabricate the strong and thermal conductive fluoropolymer composites used for the high-performance polymer bonded explosives (PBXs).

Keywords: mechanical properties, oriented network, graphite polymer composite, thermal conductivity

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Authors: Siti Hasnah Kamarudin, Luqman Chuah Abdullah, Min Min Aung, Chantara Thevy Ratnam

Abstract:

The primary objective of this work was to develop fully nanocomposite material based on poly(lactic acid), epoxidized jatropha oil (EJO) and nanocrystalline cellulose. EJO was investigated as a sustainable alternative to petrochemical-based plasticizers to reinforce the ductility and toughness of plastics, in this case, nanocellulose/poly(lactic acid) (PLA). The EJO was melt blended into nanocellulose/PLA at concentrations from 1 wt% to 5 wt%. The blends were then hot-pressed into sheets to characterize their mechanical and physical properties. Microcrystalline cellulose had been converted to nanocrystalline cellulose by acid mercerisation technique and the effects thereof on the composites’ tensile, flexural, and impact properties, as well as their water absorption and density, were studied. The impact strengths of the nanocomposites were improved with the addition of NCC up to 0.5 wt%, with a maximum over 10 times that of the neat PLA. The flexural strength and modulus increased 4% and 50%, respectively, for NCC/PLA plasticized with EJO. This increase demonstrated the nanocrystalline cellulose addition gave notable improvements to the composites’ properties. Furthermore, analysis by scanning electron microscopy (SEM) of the nanocomposites’ tensile fracture surfaces indicated better interaction adhesion of the NCC/PLA plasticized with EJO compared with the PLA/EJO composites.

Keywords: nanocrystalline cellulose, nanocomposite, poly (lactic acid), epoxidised jatropha oil

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Authors: Bambang Piscesa, Mario M. Attard, Dwi Presetya, Ali K. Samani

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A numerical strategy formulated using a plasticity approach is presented to model spalling of the concrete cover in reinforced concrete columns. The stage at which the concrete cover within reinforced concrete column spalls has a direct bearing on the load capacity. The concrete cover can prematurely spall before the full cross-section can be utilized if the concrete is very brittle under compression such as for very high strength concretes. If the confinement to the core is high enough, the column can achieve a higher peak load by utilizing the core. A numerical strategy is presented to model spalling of the concrete cover. Various numerical strategies are employed to model the behavior of reinforced concrete columns which include: (1) adjusting the material properties to incorporate restrained shrinkage; (2) modifying the plastic dilation rate in the presence of the tensile pressure; (3) adding a tension cut-off failure surface and (4) giving the concrete cover region and the column core different material properties. Numerical comparisons against experimental results are carried out that shown excellent agreement with the experimental results and justify the use of the proposed strategies to predict the axial load capacity of reinforce concrete columns.

Keywords: spalling, concrete, plastic dilation, reinforced concrete columns

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Authors: Mumtaz Begum Mustafa, Siti Salwah Salim, Feizal Dani Rahman

Abstract:

Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.

Keywords: Automatic Speech Recognition System, children speech, adaptation, Malay

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Authors: Sohaib Z. Khan, Farrukh Mustahsan, Essam R. I. Mahmoud, S. H. Masood

Abstract:

Materials or structures that contract laterally on the application of a compressive load and vice versa are said to be Auxetic materials which exhibit Negative Poisson’s Ratio (NPR). Numerous auxetic structures are proposed in the literature. One of the most studied periodic auxetic structure is the re-entrant honeycomb model. In this paper, a modified re-entrant model is proposed to enhance the auxetic behavior. The paper aimed to investigate the elastic behaviour of the proposed model to improve Young’s modulus and NPR by evaluating the analytical model. Finite Element Analysis (FEA) is also conducted to support the analytical results. A significant increment in Young’s modulus and NPR can be achieved in one of the two orthogonal directions of the loading at the cost of compromising these values in other direction. The proposed modification resulted in lower relative densities when compared to the existing re-entrant honeycomb structure. A trade-off in the elastic properties in one direction at low relative density makes the proposed model suitable for uni-direction applications where higher stiffness and NPR is required, and strength to weight ratio is important.

Keywords: 2D model, auxetic materials, re-entrant honeycomb, negative Poisson's ratio

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Authors: Ji Hye Im, Nguyen T. T. Phuong, Keon Wook Kang

Abstract:

Estrogens are important for the development and growth of estrogen receptor (ER)-positive breast cancer, for which anti-estrogen therapy is one of the most effective treatments. However, its efficacy can be limited by either de novo or acquired resistance. Aromatase is a key enzyme for the biosynthesis of estrogens, and inhibition of this enzyme leads to profound hypoestrogenism. Here, we found that the basal expression and activity of aromatase were significantly increased in tamoxifen (TAM)-resistant human breast cancer (TAMR-MCF-7) cells compared to control MCF-7 cells. We further revealed that aromatase immunoreactivity in tumor tissues was increased in recurrence group after TAM therapy compared to non-recurrence group after TAM therapy. Phosphorylation of Akt, extracellular signal-regulated kinase (ERK), and p38 kinase were all increased in TAMR-MCF-7 cells. Inhibition of phosphoinositide 3-kinase (PI3K) suppressed the transactivation of the aromatase gene and its enzyme activity. Furthermore, we have also shown that PI3K/Akt-dependent cAMP-response element binding protein (CREB) activation was required for the enhanced expression of aromatase in TAMR-MCF-7 cells. Our findings suggest that aromatase expression is up-regulated in TAM-resistant breast cancer via PI3K/Akt-dependent CREB activation.

Keywords: TAMR-MCF-7, CREB, estrogen receptor, aromatase

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Authors: T. Häfele, J. Kaspar, M. Vielhaber, W. Calles, J. Griebsch

Abstract:

The demand for an increasing diversification of the product spectrum associated with the current huge customization desire and subsequently the decreasing unit quantities of each production lot is gaining more and more importance within a great variety of industrial branches, e.g. automotive industry. Nevertheless, traditional product development and production processes (molding, extrusion) are already reaching their limits or fail to address these trends of a flexible and digitized production in view of a product variability up to lot size one. Thus, upcoming innovative production concepts like the additive manufacturing technology basically create new opportunities with regard to extensive potentials in product development (constructive optimization) and manufacturing (economic individualization), but mostly suffer from insufficient strength regarding structural components. Therefore, this contribution presents an innovative technological and procedural conception of a hybrid additive manufacturing process (fiber-reinforced sandwich structures based on selective laser sintering technology) to overcome these current structural weaknesses, and consequently support the design of complex lightweight components.

Keywords: additive manufacturing, fiber-reinforced plastics (FRP), hybrid design, lightweight design

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Authors: Rachel Ashwell, Sally Millett

Abstract:

Introduction: Adequate post-operative pain relief is a key priority in the delivery of caesarean sections. This improves patient experience, reduces morbidity and enables optimal mother-infant interaction. Recommendations outlined in the NICE guidelines for caesarean section (CS) include offering peri-operative intrathecal/epidural diamorphine and post-operative opioid analgesics; offering non-steroidal anti-inflammatory drugs (NSAIDs) unless contraindicated and taking hourly observations for 12 hours following intrathecal diamorphine. Method: This audit assessed the provision of post-CS analgesia in 29 women over a two-week period. Indicators used were the use of intrathecal/epidural opioids, use of post-operative opioids and NSAIDs, frequency of observations and patient satisfaction with pain management on post-operative days 1 and 2. Results: All women received intrathecal/epidural diamorphine, 97% were prescribed post-operative opioids and all were prescribed NSAIDs unless contraindicated. Hourly observations were not maintained for 12 hours following intrathecal diamorphine. 97% of women were satisfied with their pain management on post-operative day 1 whereas only 75% were satisfied on day 2. Discussion: This service meets the proposed standards for the provision of post-operative analgesia, achieving high levels of patient satisfaction 1 day after CS. However, patient satisfaction levels are significantly lower on post-operative day 2, which may be due to reduced frequency of observations. The lack of an official audit standard for patient satisfaction on postoperative day 2 may result in reduced incentive to prioritise pain management at this stage.

Keywords: Caesarean section, analgesia, postoperative care, patient satisfaction

Procedia PDF Downloads 382