Search results for: model based engineering MBE

Authors: Khalil Khanafer

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This study emphasizes on analyzing the effect of flow conditions and the geometric variation of the microcantilever’s bluff body on the microcantilever detection capabilities within a fluidic device using a finite element fluid-structure interaction model. Such parameters include inlet velocity, flow direction, and height of the microcantilever’s supporting system within the fluidic cell. The transport equations are solved using a finite element formulation based on the Galerkin method of weighted residuals. For a flexible microcantilever, a fully coupled fluid-structure interaction (FSI) analysis is utilized and the fluid domain is described by an Arbitrary-Lagrangian–Eulerian (ALE) formulation that is fully coupled to the structure domain. The results of this study showed a profound effect on the magnitude and direction of the inlet velocity and the height of the bluff body on the deflection of the microcantilever. The vibration characteristics were also investigated in this study. This work paves the road for researchers to design efficient microcantilevers that display least errors in the measurements.

Keywords: fluidic cell, FSI, microcantilever, flow direction

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Authors: Mannan Malik Muhammad Naeem, Jeong Myung Yung

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Functional near infrared spectroscopy (fNIRS) has a favorable position in non-invasive brain imaging techniques. The concentration change of oxygenated hemoglobin and de-oxygenated hemoglobin during particular cognitive activity is the basis for this neuro-imaging modality. Two wavelengths of near-infrared light can be used with modified Beer-Lambert law to explain the indirect status of neuronal activity inside brain. The temporal resolution of fNIRS is very good for real-time brain computer-interface applications. The portability, low cost and an acceptable temporal resolution of fNIRS put it on a better position in neuro-imaging modalities. In this study, an optimization model for impulse response function has been used to estimate/predict initial dip using fNIRS data. In addition, the activity strength parameter related to motor based cognitive task has been analyzed. We found an initial dip that remains around 200-300 millisecond and better localize neural activity.

Keywords: fNIRS, brain-computer interface, optimization algorithm, adaptive signal processing

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Authors: Jamal Ahmed Hama Kareem, Noraini Abu Talib

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The purpose of this paper is to explore the literature on 5S and Total Productive Maintenance (TPM) and the benefits that are to be derived from their implementation. It also seeks to highlight the main phases for implementing both the 5S and the TPM successfully, along with highlighting aspects that are needed for successful implementation of these two techniques simultaneously in the contemporary manufacturing scenario. The literature on classification of 5S and TPM has so far been very limited. The paper reviews a large number of papers in this field and presents the overview of several of implementation practices of 5S and TPM, and the benefits that can be achieved by the implementation of 5S and TPM as a one system by industrial organizations globally. The paper systematically categorizes the published literature and reveals important issues that influence the successful implementation of 5S and TPM in organizations to improve production effectiveness for competitiveness. Further, the paper also highlights various phases suggested by researchers and practitioners, which ensure smooth and effective implementation of the 5S and TPM in industrial organizations. In the end, study puts forth propositions based on the model of the study after extensive review of literature. The paper will be useful to researchers, maintenance professionals and other concerned officials with improving the performance of production processes effectiveness in industrial organizations.

Keywords: 5S, Total Productive Maintenance (TPM), phases of implementation of 5S and TPM, industrial organizations

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Authors: Bhavna Malik

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The study is build on a theoretical framework that links characteristics of job, key attitudes and intention to leave, why faculty may be disengaging from institutional service. The literature indicates that job characteristics, key attitudes and intention to leave are very important for effective organizational functioning. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attitudes predicted intention to leave negatively. The present study attempted to propose a new integrative model of the relationships among job characteristics, key attitudes, and intention to leave. The main purpose of the present study is to examine the effects of job characteristics on intention to leave. While examining the role of job characteristics, the mediating roles of key attitudes were taken into account in order to better understand how job characteristics affect the exhibition of intention to leave. The secondary purpose is to investigate the effects of job characteristics on key attitudes, and the effects of key attitudes on intention to leave. Job characteristics of remuneration, resource for professional activities, career opportunities were positively associated with the work attitude of job satisfaction. The aggregate job scope was positively associated with the work attitude of organizational commitment although no single job characteristic was significantly associated with organizational commitment. Commitment, however, did not significantly affect time spent on institutional service. Two job characteristics—time spent on research and time spent on teaching—were negatively associated with this behavior. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attiudes predicted intention to leave negatively. In turn, job satisfaction and organizational commitment were negatively associated with the intention to leave. In addition to these, organizational commitment was negatively associated with the intention to leave. However, no significant direct association was found between job characteristics and intention to leave.

Keywords: Job Characteristics Model, job satisfaction, organizational commitment, intention to leave

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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Nowadays, dialogue systems increasingly become the way for humans to access many computer systems. So, humans can interact with computers in natural language. A dialogue system consists of three parts: understanding what humans say in natural language, managing dialogue, and generating responses in natural language. In this paper, we survey deep learning based methods for dialogue management, response generation and dialogue evaluation. Specifically, these methods are based on neural network, long short-term memory network, deep reinforcement learning, pre-training and generative adversarial network. We compare these methods and point out the further research directions.

Keywords: dialogue management, response generation, deep learning, evaluation

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Authors: Anatoliy Kharkhurin

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Modifications that the prefix ‘trans-‘ refers to start within a person. This presentation focuses on the transpersonal that goes beyond the individual (trans-personal) to encompass wider aspects of humanities, specifically peak experience as a culminating stage of the creative act. It proposes a model according to which the peak experience results from a harmonious vibration of four spheres, which transcend an individual’s capacities and bring one to a qualitatively different level of experience. Each sphere represents an aspect of creative activity: superconscious, intellectual, emotive and active. Each sphere corresponds to one of four creative functions: authenticity, novelty, aesthetics, and utility, respectively. The creative act starts in the superconscious sphere: the supreme pleasure of Creation is reflected in creative pleasure, which is realized in creative will. These three instances serve as a source of force axes, which penetrate other spheres, and in place of infiltration establish restrictive, expansive, and integrative principles, respectively; the latter balances the other two and ensures a harmonious vibration within a sphere. This Hegelian-like triad is realized within each sphere in the form of creative capacities. The intellectual sphere nurtures capacities to invent and to elaborate, which are integrated by capacity to conceptualize. The emotive sphere nurtures satiation and restrictive capacities integrated by capacity to balance. The active sphere nurtures goal orientation and stabilization capacities integrated by capacity for self-expression. All four spheres vibrate within each other – the superconscious sphere being in the core of the structure followed by intellectual, emotive, and active spheres, respectively – thereby reflecting the path of creative production. If the spheres vibrate in-phase, their amplitudes amplify the creative energy; if in antiphase – the amplitudes reduce the creative energy. Thus, creative act is perceived as continuum with perfectly harmonious vibration within and between the spheres on one side and perfectly disharmonious vibration on the other.

Keywords: creativity, model, transpersonal, peak experience

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Authors: Daniela E. Marin, Cornelia Braicu, Gina C. Pistol, Roxana Cojocneanu-Petric, Ioana Berindan Neagoe, Mihail A. Gras, Ionelia Taranu

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Aristolochic acid (AA) is a carcinogenic, mutagenic, and nephrotoxic compound commonly found in the Aristolochiaceae family of plants. AA is frequently associated with urothelial carcinoma of the upper urinary tract in human and animals and is considered as being responsible for Balkan Endemic Nephropathy. The pig provides a good animal model because the porcine urological system is very similar to that of humans, both in aspects of physiology and anatomy. MicroRNA (miRNA) are small non-coding RNAs that have an impact on a wide range of biological processes by regulating gene expression at post-transcriptional level. The objective of this study was to analyze the miRNA profiling in the kidneys of AA intoxicated swine. For this purpose, ten TOPIGS-40 crossbred weaned piglets, 4-week-old, male and females with an initial average body weight of 9.83 ± 0.5 kg were studied for 28 days. They were given ad libitum access to water and feed and randomly allotted to one of the following groups: control group (C) or aristolochic acid group (AA). They were fed a maize-soybean-meal-based diet contaminated or not with 0.25mgAA/kg. To profile miRNA in the kidneys of pigs, microarrays and bioinformatics approaches were applied to analyze the miRNA in the kidney of control and AA intoxicated pigs. After normalization, our results have shown that a total of 5 known miRNAs and 4 novel miRNAs had different profiling in the kidney of intoxicated animals versus control ones. Expression of miR-32-5p, miR-497-5p, miR-423-3p, miR-218-5p, miR-128-3p were up-regulated by 0.25mgAA/kg feed, while the expression of miR-9793-5p, miR-9835-3p, miR-9840-3p, miR-4334-5p was down-regulated. The microRNA profiling in kidney of intoxicated animals was associated with modified expression of target genes as: RICTOR, LASP1, SFRP2, DKK2, BMI1, RAF1, IGF1R, MAP2K1, WEE1, HDGF, BCL2, EIF4E etc, involved in cell division cycle, apoptosis, cell differentiation and cell migration, cell signaling, cancer etc. In conclusion, this study provides new data concerning the microRNA profiling in kidney after aristolochic acid intoxications with important implications for human and animal health.

Keywords: aristolochic acid, kidney, microRNA, swine

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Authors: B. Hossen, Y. Helmut

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Soil salinity is a major problem for the coastal region of Bangladesh, which has been increasing for the last four decades. Determination of soil salinity is essential for proper land use planning for agricultural crop production. The aim of the research is to estimate and monitor the soil salinity in the study area. Remote sensing can be an effective tool for detecting soil salinity in data-scarce conditions. In the research, Landsat 8 is used, which required atmospheric and radiometric correction, and nine soil salinity indices are applied to develop a soil salinity map. Ground soil salinity data, i.e., EC value, is collected as a printed map which is then scanned and digitized to develop a point shapefile. Linear regression is made between satellite-based generated map and ground soil salinity data, i.e., EC value. The results show that maximum R² value is found for salinity index SI 7 = G*R/B representing 0.022. This minimal R² value refers that there is a negligible relationship between ground EC value and salinity index generated value. Hence, these indices are not appropriate to assess soil salinity though many studies used those soil salinity indices successfully. Therefore, further research is necessary to formulate a model for determining the soil salinity in the coastal of Bangladesh.

Keywords: soil salinity, EC, Landsat 8, salinity indices, linear regression, remote sensing

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Authors: Nassima Noufail, Sara Bouhali

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In this work, we develop a semi-supervised solution for the purpose of action detection in videos and propose an efficient algorithm for video segmentation. The approach is divided into video segmentation, feature extraction, and classification. In the first part, a video is segmented into clips, and we used the K-means algorithm for this segmentation; our goal is to find groups based on similarity in the video. The application of k-means clustering into all the frames is time-consuming; therefore, we started by the identification of transition frames where the scene in the video changes significantly, and then we applied K-means clustering into these transition frames. We used two image filters, the gaussian filter and the Laplacian of Gaussian. Each filter extracts a set of features from the frames. The Gaussian filter blurs the image and omits the higher frequencies, and the Laplacian of gaussian detects regions of rapid intensity changes; we then used this vector of filter responses as an input to our k-means algorithm. The output is a set of cluster centers. Each video frame pixel is then mapped to the nearest cluster center and painted with a corresponding color to form a visual map. The resulting visual map had similar pixels grouped. We then computed a cluster score indicating how clusters are near each other and plotted a signal representing frame number vs. clustering score. Our hypothesis was that the evolution of the signal would not change if semantically related events were happening in the scene. We marked the breakpoints at which the root mean square level of the signal changes significantly, and each breakpoint is an indication of the beginning of a new video segment. In the second part, for each segment from part 1, we randomly selected a 16-frame clip, then we extracted spatiotemporal features using convolutional 3D network C3D for every 16 frames using a pre-trained model. The C3D final output is a 512-feature vector dimension; hence we used principal component analysis (PCA) for dimensionality reduction. The final part is the classification. The C3D feature vectors are used as input to a multi-class linear support vector machine (SVM) for the training model, and we used a multi-classifier to detect the action. We evaluated our experiment on the UCF101 dataset, which consists of 101 human action categories, and we achieved an accuracy that outperforms the state of art by 1.2%.

Keywords: video segmentation, action detection, classification, Kmeans, C3D

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Authors: Shiyi He, Yan Xia, Xiaoping Ouyang, Liang Chen, Zhongbing Zhang, Jinlu Ruan

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As the key system of the spacecraft, various propelling system have been developing rapidly, including ion thrust, laser thrust, solar sail and other micro-thrusters. However, there still are some shortages in these systems. The ion thruster requires the high-voltage or magnetic field to accelerate, resulting in extra system, heavy quantity and large volume. The laser thrust now is mostly ground-based and providing pulse thrust, restraint by the station distribution and the capacity of laser. The thrust direction of solar sail is limited to its relative position with the Sun, so it is hard to propel toward the Sun or adjust in the shadow.In this paper, a novel nuclear thruster based on alpha decay and spontaneous fission is proposed and the principle of this radiation-thrust with alpha particle has been expounded. Radioactive materials with different released energy, such as 210Po with 5.4MeV and 238Pu with 5.29MeV, attached to a metal film will provides various thrust among 0.02-5uN/cm2. With this repulsive force, radiation is able to be a power source. With the advantages of low system quantity, high accuracy and long active time, the radiation thrust is promising in the field of space debris removal, orbit control of nano-satellite array and deep space exploration. To do further study, a formula lead to the amplitude and direction of thrust by the released energy and decay coefficient is set up. With the initial formula, the alpha radiation elements with the half life period longer than a hundred days are calculated and listed. As the alpha particles emit continuously, the residual charge in metal film grows and affects the emitting energy distribution of alpha particles. With the residual charge or extra electromagnetic field, the emitting of alpha particles performs differently and is analyzed in this paper. Furthermore, three more complex situations are discussed. Radiation element generating alpha particles with several energies in different intensity, mixture of various radiation elements, and cascaded alpha decay are studied respectively. In combined way, it is more efficient and flexible to adjust the thrust amplitude. The propelling model of the spontaneous fission is similar with the one of alpha decay, which has a more complex angular distribution. A new quasi-sphere space propelling system based on the radiation-thrust has been introduced, as well as the collecting and processing system of excess charge and reaction heat. The energy and spatial angular distribution of emitting alpha particles on unit area and certain propelling system have been studied. As the alpha particles are easily losing energy and self-absorb, the distribution is not the simple stacking of each nuclide. With the change of the amplitude and angel of radiation-thrust, orbital variation strategy on space debris removal is shown and optimized.

Keywords: alpha decay, angular distribution, emitting energy, orbital variation, radiation-thruster

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Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Maria Stepankova, Lucie Vistejnova, Pavel Klein, Tereza Blassova, Marketa Slajerova, Radek Sedlacek, Martin Bartos, Jaroslav Chlupac

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Background: Clinical outcome benefits of the segment rib fracture surgical therapy are well known and follow from better stabilization of the chest wall. Despite this, some authors still incline to conservative therapy and point out to possible rib fracture healing failure in connection with the bone vascular supply disturbance caused by metal plate implantation. This suggestion met neither experimental nor clinical verification and remains the object of discussion. In our pilot study we investigated the titanium plate fixation effect on the rib fracture healing in porcine model and its histological, biomechanical and radiological aspects. Materials and Method: Two porcine models (experimental group) underwent the operative chest wall stabilization with a titanium plate implantation after osteotomy. Two other porcine models (control group) were treated conservatively after osteotomy. Three weeks after surgery, all animals were sacrificed, treated ribs were explanted and the histological analysis, µCT imaging and biomechanical testing of the calluses tissue were performed. Results: In µCT imaging, experimental group showed a higher cortical bone volume compared to the control group. Histological analysis using the non-decalcified bone tissue blocks demonstrated more maturated callus with higher newly-formed osseous tissue ratio in experimental group in comparison to controls. In contrast, no significant differences in bone blood vessels supply in both groups were observed. This finding suggests that the bone blood supply in experimental group was not impaired. Biomechanical analysis using 3-point bending test demonstrated significantly higher bending stiffness and the maximum force in experimental group. Conclusion: Based on our observation, it could be concluded, that the titanium plate fixation of the rib fractures leads to faster bone callus maturation whereas does not cause the vascular supply impairment after 3 weeks and thus has a beneficial effect on the rib fracture healing.

Keywords: bone vascular supply, chest wall stabilization, fracture healing, histological analysis, titanium plate implantation

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Authors: Mohammed Hussein Ahmed, Bahar Mohammed Kareem

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This study is concerned with the pragmatic discoursal study of hedging constructions in English language. Hedging is a mitigated word used to lessen the impact of the utterance uttered by the speakers. Hedging could be either adverbs, adjectives, verbs and sometimes it may consist of clauses. It aims at finding out the extent to which speakers and participants of the discourse use hedging constructions during their conversations. The study also aims at finding out whether or not there are any significant differences in the types and functions of the frequency of hedging constructions employed by male and female. It is hypothesized that hedging constructions are frequent in English discourse more than any other languages due to its formality and that the frequency of the types and functions are influenced by the gender of the participants. To achieve the aims of the study, two types of procedures have been followed: theoretical and practical. The theoretical procedure consists of presenting a theoretical background of hedging topic which includes its definitions, etymology and theories. The practical procedure consists of selecting a sample of texts and analyzing them according to an adopted model. A number of conclusions will be drawn based on the findings of the study.

Keywords: hedging, pragmatics, politeness, theoretical

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Authors: Muhammed Ashiq Villanthenkodath, Shreya Pal

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Purpose: This study scrutinizes the impact of economic globalization on ecological footprint while endogenizing economic growth and energy consumption from 1990 to 2018 in India. Design/methodology/approach: The standard unit root test has been employed for time series analysis to unveil the integration order. Then, the cointegration was confirmed using autoregressive distributed lag (ARDL) analysis. Further, the study executed the dynamic ARDL simulation model to estimate long-run and short-run results along with simulation and robotic prediction. Findings: The cointegration analysis confirms the existence of a long-run association among variables. Further, economic globalization reduces the ecological footprint in the long run. Similarly, energy consumption decreases the ecological footprint. In contrast, economic growth spurs the ecological footprint in India. Originality/value: This study contributes to the literature in many ways. First, unlike studies that employ CO2 emissions and globalization nexus, this study employs ecological footprint for measuring environmental quality; since it is the broader measure of environmental quality, it can offer a wide range of climate change mitigation policies for India. Second, the study executes a multivariate framework with updated series from 1990 to 2018 in India to explore the link between EF, economic globalization, energy consumption, and economic growth. Third, the dynamic autoregressive distributed lag (ARDL) model has been used to explore the short and long-run association between the series. Finally, to our limited knowledge, this is the first study that uses economic globalization in the EF function of India amid facing a trade-off between sustainable economic growth and the environment in the era of globalization.

Keywords: economic globalization, ecological footprint, India, dynamic ARDL simulation model

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Authors: Armansyah, I. P. Almanar, M. Saiful Bahari Shaari, M. Shamil Jaffarullah

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Finite element approach have been used via three-dimensional models by using Altair Hyper Work, a commercially available software, to describe heat gradients along the welding zones (axially and coronaly) in Friction Stir Welding (FSW). Transient thermal finite element analyses are performed in AA 6061-T6 Aluminum Alloy to obtain temperature distribution in the welded aluminum plates during welding operation. Heat input from tool shoulder and tool pin are considered in the model. A moving heat source with a heat distribution simulating the heat generated by frictions between tool shoulder and work piece is used in the analysis. The developed model was then used to show the effect of various input parameters such as total rate of welding speed and rotational speed on temperature distribution in the work piece.

Keywords: Frictions Stir Welding (FSW), temperature distribution, Finite Element Method (FEM), altair hyperwork

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Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

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Authors: Alaba M. Dare, Idris A. Ayinde, Adebayo M. Shittu, Sam O. Sam-Wobo

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Households' source of water is one of the core development indicators recently gaining pre-eminence in Nigeria. This study examined rural households' sources of water, Willingness to Pay (WTP) and factors influencing mean WTP. A cross-sectional survey which involved the use of questionnaire was used. A dichotomous choice (DC) with follow up was used as elicitation method. A multi-stage random sampling technique was used to select 437 rural households. Descriptive statistics and Tobit model were used for data estimation. The result revealed that about 70% fetched from unimproved water sources. Most (74.4%) respondents showed WTP for improved water sources. Age (p < 0.01), sex (p < 0.01), education (p < 0.01), occupation (p < 0.01), income (p < 0.01), price of water (P < 0.01), quantity of water (p < 0.01), household size (p < 0.01) and distance (p < 0.01) to existing water sources significantly influenced rural households' WTP for these services. The inference from this study showed that rural dweller sources of water is highly primitive and deplorable. Governments and stakeholders should prioritize the provision of rural water at an affordable price by rural dwellers.

Keywords: households, source of water, willingness to pay (WTP), tobit model

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Authors: Benoit Rougier, Alexandre Lefrancois, Herve Aubert

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Microwave interrogation in the range 10-100 GHz is identified as an advanced technique to investigate simultaneously shock and particle velocity measurements. However, it requires the understanding of electromagnetic wave propagation in a multi-layered moving media. The existing models limit their approach to wave guides or evaluate the velocities with a fitting method, restricting therefore the domain of validity and the precision of the results. Moreover, few data of permittivity on high explosives at these frequencies under dynamic compression have been reported. In this paper, shock and particle velocities are computed concurrently for steady and unsteady shocks for various inert and reactive materials, via a propagation model based on Doppler shifts and signal amplitude. Refractive index of the material under compression is also calculated. From experimental data processing, it is demonstrated that Hugoniot curve can be evaluated. The comparison with published results proves the accuracy of the proposed method. This microwave interrogation technique seems promising for shock and detonation waves studies.

Keywords: electromagnetic propagation, experimental setup, Hugoniot measurement, shock propagation

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Authors: Firas M. Tuaimah

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This paper presents an Artificial Neural Network based approach for short-term load forecasting and exactly for two days ahead. Two seasons have been discussed for Iraqi power system, namely summer and winter; the hourly load demand is the most important input variables for ANN based load forecasting. The recorded daily load profile with a lead time of 1-48 hours for July and December of the year 2012 was obtained from the operation and control center that belongs to the Ministry of Iraqi electricity. The results of the comparison show that the neural network gives a good prediction for the load forecasting and for two days ahead.

Keywords: short-term load forecasting, artificial neural networks, back propagation learning, hourly load demand

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Authors: N. Azouaou, H. Mokaddem, D. Senadjki, K. Kedjit, Z. Sadaoui

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Introduction: Water contamination caused by dye industries, including food, leather, textile, plastic, cosmetics, paper-making, printing and dye synthesis, has caused more and more attention, since most dyes are harmful to human being and environments. Untreated coffee grounds were used as a high-efficiency adsorbent for the removal of a cationic dye (methylene blue, MB) from aqueous solution. Characterization of the adsorbent was performed using several techniques such as SEM, surface area (BET), FTIR and pH zero charge. The effects of contact time, adsorbent dose, initial solution pH and initial concentration were systematically investigated. Results showed the adsorption kinetics followed the pseudo-second-order kinetic model. Langmuir isotherm model is in good agreement with the experimental data as compared to Freundlich and D–R models. The maximum adsorption capacity was found equal to 52.63mg/g. In addition, the possible adsorption mechanism was also proposed based on the experimental results. Experimental: The adsorption experiments were carried out in batch at room temperature. A given mass of adsorbent was added to methylene blue (MB) solution and the entirety was agitated during a certain time. The samples were carried out at quite time intervals. The concentrations of MB left in supernatant solutions after different time intervals were determined using a UV–vis spectrophotometer. The amount of MB adsorbed per unit mass of coffee grounds (qt) and the dye removal efficiency (R %) were evaluated. Results and Discussion: Some chemical and physical characteristics of coffee grounds are presented and the morphological analysis of the adsorbent was also studied. Conclusions: The good capacity of untreated coffee grounds to remove MB from aqueous solution was demonstrated in this study, highlighting its potential for effluent treatment processes. The kinetic experiments show that the adsorption is rapid and maximum adsorption capacities qmax= 52.63mg/g achieved in 30min. The adsorption process is a function of the adsorbent concentration, pH and metal ion concentration. The optimal parameters found are adsorbent dose m=5g, pH=5 and ambient temperature. FTIR spectra showed that the principal functional sites taking part in the sorption process included carboxyl and hydroxyl groups.

Keywords: adsorption, methylene blue, coffee grounds, kinetic study

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Authors: Sawsan Eissa, Omnia Kabbany

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The coastline of Togo has been historically suffering from erosion for decades, which requires a solution to help control and reduce the erosion to allow for the development of the coastal area. A morpho-dynamic model using X-beach software was developed for the Western 14 Km of the Togolese coast. The model was coupled with the hydrodynamic module of DELFT 3D, flow, and the Wave module, SWAN. The data used as input included a recent bathymetric survey, a recent shoreline topographic survey, aerial photographs, ERA 5 water level and wave data, and recent test results of seabed samples. A number of scenarios were modeled: do nothing scenario, groynes, detached breakwaters system with different crest levels and alignments. The findings showed that groynes is not expected to be effective for protection against erosion, and that the best option is a system of detached breakwater, partially emerged-partially submerged couples with periodical maintenance.

Keywords: hydrodynamics, morphology, Togo, Delft3D, SWAN, XBeach, coastal erosion, detached breakwaters

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Authors: Khin Fai Chen, Jee-Hou Ho, Eng Hwa Yap

Abstract:

An acoustic micro-energy harvester (AMEH) is developed to convert wasted acoustical energy into useful electrical energy. AMEH is mathematically modeled using lumped element modelling (LEM) and Euler-Bernoulli beam (EBB) modelling. An experiment is designed to validate the mathematical model and assess the feasibility of AMEH. Comparison of theoretical and experimental data on critical parameter value such as Mm, Cms, dm and Ceb showed the variances are within 1% to 6%, which is reasonably acceptable. Hence, AMEH mathematical model is validated. Then, AMEH undergoes bandwidth tuning for performance optimization for further experimental work. The AMEH successfully produces 0.9 V⁄(m⁄s^2) and 1.79 μW⁄(m^2⁄s^4) at 60Hz and 400kΩ resistive load which only show variances about 7% compared to theoretical data. By integrating a capacitive load of 200µF, the discharge cycle time of AMEH is 1.8s and the usable energy bandwidth is available as low as 0.25g. At 1g and 60Hz resonance frequency, the averaged power output is about 2.2mW which fulfilled a range of wireless sensors and communication peripherals power requirements. Finally, the design for AMEH is assessed, validated and deemed as a feasible design.

Keywords: piezoelectric, acoustic, energy harvester

Procedia PDF Downloads 277

Authors: Mohamad Reza Khodabakhsh

Abstract:

The present study investigated the effectiveness of attachment-based family therapy on maladaptive schemas and depressive symptoms of adolescence. This study was a quasi-experimental study, and a pre-test and post-test design with a control group were used. In this study, the study population included all adolescence. The sample consisted of 30 adolescents who were selected by the available sampling method. Then they were randomly divided into experimental (n = 15) and control (n = 15) groups. Data were collected in this study using the Beck Depression Inventory (1974) and the short form of Young's early maladaptive schema questionnaire (1988). After taking the pre-test, group implementation of family therapy based on attachment style was presented for 11 sessions of two and a half hours for two months in the experimental group. At the end of the sessions, both groups were retested, and the data were analyzed using analysis of covariance in SPSS-22 software. The results showed that attachment-based family therapy led to a significant reduction in maladaptive schemas, including emotional deprivation, rejection/abandonment, mistrust/abuse, social isolation, disability/shame, dependence/inadequacy, vulnerability/trauma, and depressive symptoms were compared to the control group. It can be concluded that this treatment has an effect on maladaptive schemas and symptoms of depression.

Keywords: attachment-based family therapy, maladaptive schemas, depressive symptoms, adolescence

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Authors: Ali Kazemi

Abstract:

The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: N. N. Mosola, K. F. Moeketsi, R. Sehobai, N. Pule

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The Internet brings increasing use of Information and Communications Technology (ICT) services and facilities. Consequently, new computing paradigms emerge to provide services over the Internet. Although there are several benefits stemming from these services, they pose several risks inherited from the Internet. For example, cybercrime, identity theft, malware etc. To thwart these risks, this paper proposes a holistic approach. This approach involves multidisciplinary interactions. The paper proposes a top-down and bottom-up approach to deal with cyber security concerns in developing countries. These concerns range from regulatory and legislative areas, cyber awareness, research and development, technical dimensions etc. The main focus areas are highlighted and a cybersecurity model solution is proposed. The paper concludes by combining all relevant solutions into a proposed cybersecurity model to assist developing countries in enhancing a cyber-safe environment to instill and promote a culture of cybersecurity.

Keywords: cybercrime, cybersecurity, computer emergency response team, computer security incident response team

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Authors: Nasir Ashraf, Sajid Rahid Ahmad, Adeel Ahmad

Abstract:

Pakistan is a major tea consumer country and ranked as the third largest importer of tea worldwide. Out of all beverage consumed in Pakistan, tea is the one with most demand for which tea import is inevitable. Being an agrarian country, Pakistan should cultivate its own tea and save the millions of dollars cost from tea import. So the need is to identify the most suitable areas with favorable weather condition and suitable soils where tea can be planted. This research is conducted over District Mansehra and District Abbottabad in Khyber Pakhtoonkhwah Province of Pakistan where the most favorable conditions for tea cultivation already exist and National Tea Research Institute has done successful experiments to cultivate high quality tea. High tech approach is adopted to meet the objectives of this research by using the remotely sensed data i.e. Aster DEM, Landsat8 Imagery. The Remote Sensing data was processed in Erdas Imagine, Envi and further analyzed in ESRI ArcGIS spatial analyst for final results and representation of result data in map layouts. Integration of remote sensing data with GIS provided the perfect suitability analysis. The results showed that out of all study area, 13.4% area is highly suitable while 33.44% area is suitable for tea plantation. The result of this research is an impressive GIS based outcome and structured format of data for the agriculture planners and Tea growers. Identification of suitable tea growing areas by using remotely sensed data and GIS techniques is a pressing need for the country. Analysis of this research lets the planners to address variety of action plans in an economical and scientific manner which can lead tea production in Pakistan to meet demand. This geomatics based model and approach may be used to identify more areas for tea cultivation to meet our demand which we can reduce by planting our own tea, and our country can be independent in tea production.

Keywords: agrarian country, GIS, geoinformatics, suitability analysis, remote sensing

Procedia PDF Downloads 382

Authors: Nur Aisyah Jalalludin, Arwindra Rizqiawan, Goro Fujita

Abstract:

In this study, we aim to demonstrate a microgrid system experimental simulation for an easy understanding of a large-scale microgrid system. This model is required for industrial training and learning environments. However, in order to create an exact representation of a microgrid system, the laboratory-scale system must fulfill the requirements of a grid-connected inverter, in which power values are assigned to the system to cope with the intermittent output from renewable energy sources. Aside from that, during changes in load capacity, the grid-connected system must be able to supply power from the utility grid side and microgrid side in a balanced manner. Therefore, droop control is installed in the inverter’s control board to maintain equal power sharing in both sides. This power control in a stand-alone condition and droop control in a grid-connected condition must be implemented in order to maintain a stabilized system. Based on the experimental results, power control and droop control can both be applied in the system by comparing the experimental and reference values.

Keywords: droop control, droop characteristic, grid-connected inverter, microgrid, power control

Procedia PDF Downloads 879

Authors: Ismail Celik, Pavlo Antonenko, Seyit Ahmet Kiray, Ismail Sahin

Abstract:

The aim of the present study was to thoroughly investigate the teachers’ interactive whiteboards (IWBs) use within the scope of the technological pedagogical and content knowledge (TPACK) framework based on the school practice observations of in-service teachers collected by pre-service teachers. In this study, teachers’ use of IWBs in their classes was investigated by using phenomenography, which is a qualitative research method design. The participants of this study consisted of teachers working in a province of Turkey. Within the scope of the study, 337 teachers from 61 different schools were observed by preservice teachers during School Experience classes. The teachers use the IWBs to review the points not understood by the students, to share knowledge, to enhance motivation, to maintain student participation/practice and for in-process, formative assessment. The problems teachers face while using the IWBs can be IWB-based (touchscreen problems/frozen image/lack of software), administration-based, student-based and teacher-based (lack of knowledge of use, need for technical support). It is considered that technological knowledge (TK) is important in solving the problems experienced with IWBs, and technological pedagogy knowledge (TPK) and technological content knowledge (TCK) are important in using the IWBs in an interactive and pedagogically meaningful way that uses IWBs affordances and is relevant to the instructional objectives.

Keywords: TPACK, technology integration, interactive whiteboard, technology in education

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Authors: Getaneh Berie Tarekegn

Abstract:

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.

Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles

Procedia PDF Downloads 89

Authors: Abderrahmane Mousstain, Ez-Zohra Belkadi

Abstract:

Many authors support more participatory and inclusive place branding practices that empower stakeholders’ participation. According to this participatory point of view, the effectiveness of place branding strategies cannot be achieved without citizen involvement. However, the role of all residents as key participants in the city branding process has not been widely discussed. The aim of this paper was to determine how citizens’ involvement impacts their perceptions of the city's image, using a multivariate model. To test our hypotheses hypothetical-deductive reasoning by the quantitative method was chosen. Our investigation is based on data collected through a survey among 200 citizens of Casablanca. Results show that the more citizens are involved, the more they tend to evaluate the image of the brand positively. Additionally, the degree of involvement seems to impact satisfaction and a sense of belonging. As well, the more citizen develops a sense of belonging to the city, the more favorable his or her perception of the brand image is. Ultimately, the role of citizens shouldn’t be limited to reception. They are also Co-creators of the brand, who ensure the correlation of the brand with authentic place roots.

Keywords: citybranding, sense of belonging, satisfaction, impact, brand’s image

Procedia PDF Downloads 170