Search results for: software transactional memory

Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: Xin Li

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The uncertainty and the complexity of the urban environment combining with the threat of climate change are contributing factors to the vulnerability in multiple-dimensions in Chinese megacities, especially in Shanghai. The urban area occupied high valuable technological infrastructure and density buildings is under the threats of climate change and can provide insufficient ecological service to remain the trade-off on urban sustainable development. Urban ecological-based adaptation (UEbA) combines practices and theoretical work and integrates ecological services into multiple-layers of urban environment planning in order to reduce the impact of the complexity and uncertainty. To understand and to respond to the challenges in the urban level, this paper considers Shanghai as the research objective. It is necessary that its urban adaptation strategies should be reflected and contain the concept and knowledge of EbA. In this paper, we firstly use software to illustrates the visualizing patterns and trends of UEBA research in the current 10 years. Specifically, Citespace software was used for interpreting the significant hubs, landmarks points of peer-reviewed literature on the context of ecological service research in recent 10 years. Secondly, 135 evidence-based EbA literature were reviewed for categorizing the methodologies and framework of evidence-based EbA by the systematic map protocol. Finally, a conceptual framework combined with culture, economic and social components was developed in order to assess the current adaptation strategies in Shanghai. This research founds that the key to reducing urban vulnerability does not only focus on co-benefit arguments but also should pay more attention to the concept of trade-off. This research concludes that the designed framework can provide key knowledge and indicates the essential gap as a valuable tool against climate variability in the process of urban adaptation in Shanghai.

Keywords: urban ecological-based adaptation, climate change, sustainable development, climate variability

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Authors: Dalal N. Hammod, Ekhlas K. Gbashi

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Today, cryptography is used in many applications to achieve high security in data transmission and in real-time communications. AES has long gained global acceptance and is used for securing sensitive data in various industries but has suffered from slow processing and take a large time to transfer data. This paper suggests a method to enhance Advance Encryption Standard (AES) Algorithm based on time and permutation. The suggested method (MAES) is based on modifying the SubByte and ShiftRrows in the encryption part and modification the InvSubByte and InvShiftRows in the decryption part. After the implementation of the proposal and testing the results, the Modified AES achieved good results in accomplishing the communication with high performance criteria in terms of randomness, encryption time, storage space, and avalanche effects. The proposed method has good randomness to ciphertext because this method passed NIST statistical tests against attacks; also, (MAES) reduced the encryption time by (10 %) than the time of the original AES; therefore, the modified AES is faster than the original AES. Also, the proposed method showed good results in memory utilization where the value is (54.36) for the MAES, but the value for the original AES is (66.23). Also, the avalanche effects used for calculating diffusion property are (52.08%) for the modified AES and (51.82%) percentage for the original AES.

Keywords: modified AES, randomness test, encryption time, avalanche effects

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Authors: NeisaKuonuo Tungoe

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Tenyidie, also known as Angami, is spoken by the Angami tribe of Nagaland, North-East India, bordering Myanmar (Burma). It belongs to the Tibeto-Burman language group, falling under the Kuki-Chin-Naga sub-family. Tenyidie studies have seen random attempts at explaining the phonemic inventory of Tenyidie. Different scholars have variously emphasized the grammar or the history of Tenyidie. Many of these claims have been stimulating, but they were often based on a small amount of merely suggestive data or on auditory perception only. The principal objective of this paper is to analyse the affricate segments of Tenyidie as an acoustic study. There are seven categories to the inventory of Tenyidie; Plosives, Nasals, Affricates, Laterals, Rhotics, Fricatives, Semi vowels and Vowels. In all, there are sixty phonemes in the inventory. As mentioned above, the only prominent readings on Tenyidie or affricates in particular are only reflected through auditory perception. As noted above, this study aims to lay out the affricate segments based only on acoustic conclusions. There are seven affricates found in Tenyidie. They are: 1) Voiceless Labiodental Affricate - / pf /, 2) Voiceless Aspirated Labiodental Affricate- / pfh /, 3) Voiceless Alveolar Affricate - / ts /, 4) Voiceless Aspirated Alveolar Affricate - / tsh /, 5) Voiced Alveolar Affricate - / dz /, 6) Voiceless Post-Alveolar Affricate / tʃ / and 7) Voiced Post- Alveolar Affricate- / dʒ /. Since the study is based on acoustic features of affricates, five informants were asked to record their voice with Tenyidie phonemes and English phonemes. Throughout the study of the recorded data, PRAAT, a scientific software program that has made itself indispensible for the analyses of speech in phonetics, have been used as the main software. This data was then used as a comparative study between Tenyidie and English affricates. Comparisons have also been drawn between this study and the work of another author who has stated that there are only six affricates in Tenyidie. The study has been quite detailed regarding the specifics of the data. Detailed accounts of the duration and acoustic cues have been noted. The data will be presented in the form of spectrograms. Since there aren’t any other acoustic related data done on Tenyidie, this study will be the first in the long line of acoustic researches on Tenyidie.

Keywords: tenyidie, affricates, praat, phonemic inventory

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Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

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Authors: Christina Adly, Meena Abdelmeseeh, Tamer Basha

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This paper proposes a system for hand movement recognition using multichannel surface EMG(sEMG) signals obtained from 40 subjects using 40 different exercises, which are available on the Ninapro(Non-Invasive Adaptive Prosthetics) database. First, we applied processing methods to the raw sEMG signals to convert them to their amplitudes. Second, we used deep learning methods to solve our problem by passing the preprocessed signals to Fully connected neural networks(FCNN) and recurrent neural networks(RNN) with Long Short Term Memory(LSTM). Using intrasubject evaluation, The accuracy using the FCNN is 72%, with a processing time for training around 76 minutes, and for RNN's accuracy is 79.9%, with 8 minutes and 22 seconds processing time. Third, we applied some postprocessing methods to improve the accuracy, like majority voting(MV) and Movement Error Rate(MER). The accuracy after applying MV is 75% and 86% for FCNN and RNN, respectively. The MER value has an inverse relationship with the prediction delay while varying the window length for measuring the MV. The different part uses the RNN with the intersubject evaluation. The experimental results showed that to get a good accuracy for testing with reasonable processing time, we should use around 20 subjects.

Keywords: hand movement recognition, recurrent neural network, movement error rate, intrasubject evaluation, intersubject evaluation

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Authors: Halil Baris Cit, Mert Durmaz

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Subsequent to the design of the compact centrifugal compressor, which is specifically intended to be used in aviation platforms, the process has been evaluated within the context of this study. A trade-off study matrix for future studies has been formed after making comparison between the design and the previous studies taking part in literature. While the power consumption of the designed compressor will be approximately 25 kW, the working fluid will be refrigerant. Properties such as thermodynamic properties and Global Warmin Potential(GWP)-Ozone Depletion Potential(ODP) Values of the fluid have been taken into consideration during the selection process of the refrigerant. Concepts NREC and ANSYS Vista CCD software have been used in the part of conceptual design, and R1233ZD has been selected as the refrigerant. Real-gas Computational Fluid Dynamic(CFD) analysis has been carried out with different cubic equations of state in the ANSYS CFX solver so as to figure out the most suitable solution method. These equations are named as “The Redlich Kwong”, “Soave Redlich Kwong”, “Augnier Redlick Kwong,” and “Peng Robinson.” By being used the mentioned solution equations in the same compressor configuration, analysis also have been carried out with two gases having different characteristics. As a result of the 12 analysis carried out with three different refrigerants—R11, R134A, and R1233zd—and four different solution equations mentioned above, the most accurate solution method has been selected by comparing the densities of the gases at different pressure and temperature points. The results have been analyzed within two titles following to the completion of the design with the selected equation. The first one is a trade-off study matrix presenting a comparison regarding the compact centrifugal compressor operating with the refrigerant to be designed. This comparison is between some dimensionless and dimensional parameters determined before the design and their values in the literature. Second one will show the differences between the actual density and the density in the design software in each real gas analysis method, along with the effects of it on the design.

Keywords: turbocompressor, refrigerant, aviation, aerospace compressor

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Authors: G. Rajapakse, S. Jayasinghe, A. Fleming

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This paper aims to experimentally validate the control strategy used for electrical power converters in grid integrated oscillating water column (OWC) wave energy converter (WEC). The particular OWC’s unidirectional air turbine-generator output power results in discrete large power pulses. Therefore, the system requires power conditioning prior to integrating to the grid. This is achieved by using a back to back power converter with an energy storage system. A Li-Ion battery energy storage is connected to the dc-link of the back-to-back converter using a bidirectional dc-dc converter. This arrangement decouples the system dynamics and mitigates the mismatch between supply and demand powers. All three electrical power converters used in the arrangement are controlled using finite control set-model predictive control (FCS-MPC) strategy. The rectifier controller is to regulate the speed of the turbine at a set rotational speed to uphold the air turbine at a desirable speed range under varying wave conditions. The inverter controller is to maintain the output power to the grid adhering to grid codes. The dc-dc bidirectional converter controller is to set the dc-link voltage at its reference value. The software modeling of the OWC system and FCS-MPC is carried out in the MATLAB/Simulink software using actual data and parameters obtained from a prototype unidirectional air-turbine OWC developed at Australian Maritime College (AMC). The hardware development and experimental validations are being carried out at AMC Electronic laboratory. The designed FCS-MPC for the power converters are separately coded in Code Composer Studio V8 and downloaded into separate Texas Instrument’s TIVA C Series EK-TM4C123GXL Launchpad Evaluation Boards with TM4C123GH6PMI microcontrollers (real-time control processors). Each microcontroller is used to drive 2kW 3-phase STEVAL-IHM028V2 evaluation board with an intelligent power module (STGIPS20C60). The power module consists of a 3-phase inverter bridge with 600V insulated gate bipolar transistors. Delta standard (ASDA-B2 series) servo drive/motor coupled to a 2kW permanent magnet synchronous generator is served as the turbine-generator. This lab-scale setup is used to obtain experimental results. The validation of the FCS-MPC is done by comparing these experimental results to the results obtained by MATLAB/Simulink software results in similar scenarios. The results show that under the proposed control scheme, the regulated variables follow their references accurately. This research confirms that FCS-MPC fits well into the power converter control of the OWC-WEC system with a Li-Ion battery energy storage.

Keywords: dc-dc bidirectional converter, finite control set-model predictive control, Li-ion battery energy storage, oscillating water column, wave energy converter

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Authors: Corinne Zurmuehle, Andreas Christoph Weber

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In 2019, the Swiss Federal Institute of Sport Magglingen (SFISM) conducted a mixed-methods study on the Swiss elite sports system, which yielded a large quantity of research data. In a quantitative online survey, 1151 elite sports athletes, 542 coaches, and 102 Performance Directors of national sports federations (NF) have submitted their perceptions of the national support measures of the Swiss elite sports system. These data provide an essential database for the further development of the Swiss elite sports system. The results were published in a report presenting the results divided into 40 Olympic summer and 14 winter sports (Olympic classification). The authors of this paper assume that, in practice, this division is too unspecific to assess where further measures would be needed. The aim of this paper is to find appropriate parameters for data visualization in order to identify disparities in sports promotion that allow an assessment of where further interventions by Swiss Olympic (NF umbrella organization) are required. Method: First, the variable 'salary earned from sport' was defined as a variable to measure the impact of elite sports promotion. This variable was chosen as a measure as it represents an important indicator for the professionalization of elite athletes and therefore reflects national level sports promotion measures applied by Swiss Olympic. Afterwards, the variable salary was tested with regard to the correlation between Olympic classification [a], calculating the Eta coefficient. To estimate the appropriate parameters for data visualization, the correlation between salary and four further parameters was analyzed by calculating the Eta coefficient: [a] sport; [b] prioritization (from 1 to 5) of the sports by Swiss Olympic; [c] gender; [d] employment level in sports. Results & Discussion: The analyses reveal a very small correlation between salary and Olympic classification (ɳ² = .011, p = .005). Gender demonstrates an even small correlation (ɳ² = .006, p = .014). The parameter prioritization was correlating with small effect (ɳ² = .017, p = .001) as did employment level (ɳ² = .028, p < .001). The highest correlation was identified by the parameter sport with a moderate effect (ɳ² = .075, p = .047). The analyses show that the disparities in sports promotion cannot be determined by a particular parameter but presumably explained by a combination of several parameters. We argue that the possibility of combining parameters for data visualization should be enabled when the analysis is provided to Swiss Olympic for further strategic decision-making. However, the inclusion of multiple parameters massively multiplies the number of graphs and is therefore not suitable for practical use. Therefore, we suggest to apply interactive dashboards for data visualization using Business Intelligence Software. Practical & Theoretical Contribution: This contribution provides the first attempt to use Business Intelligence Software for strategic decision-making in national level sports regarding the prioritization of national resources for sports and athletes. This allows to set specific parameters with a significant effect as filters. By using filters, parameters can be combined and compared against each other and set individually for each strategic decision.

Keywords: data visualization, business intelligence, Swiss elite sports system, strategic decision-making

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Authors: Sophio Kalmakhelidze, Eka Shekiladze, Tamar Sanikidze, Mikheil Gogebashvili, Nazi Ivanishvili

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Radiation-induced various degrees of brain injury and cognitive impairment have been described after cranial radiotherapy of brain tumors. High doses of ionizing radiation have a severe impact on the central nervous system, resulting in morphological and behavioral impairments. Structures of the limbic system are especially sensitive to radiation exposure. Hence, compounds or drugs that can reduce radiation-induced impairments can be used as promising antioxidants or radioprotectors. In our study Mice whole-body irradiation with 137Cs was performed at a dose rate of 1,1 Gy/min for a total dose of 5 Gy with a “Gamma-capsule-2”. Irradiated mice were treated with Herniarin (20 mg/kg) for five days before irradiation and the same dose was administrated after one hour of irradiation. The immediate and delayed effects of ionizing radiation, as well as, protective effect of Herniarin was evaluated during early and late post-irradiation periods. The results reveal that ionizing radiation (5 Gy) alters the structure of the hippocampus in adult mice during the late post-irradiation period resulting in the decline of memory formation and learning process. Furthermore, Simple Coumarin-Herniarin reveals a radiosensitizing effect reducing morphological and behavioral alterations.

Keywords: ionizing radiation, cognitive impairments, hippocampus, limbic system, Herniarin

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Authors: Catherine Wright, Kate Luedke

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This paper questions whether or not individuals who had been exposed to narratives describing secure and insecure-avoidant attachment styles experienced temporary changes in their attachment style when compared to individuals who had been exposed to neutral narratives. The Attachment Style Questionnaire (or ASQ) developed by Feeney, Noller, and Hanrahan in 1994 was utilized to assess attachment style. Participants filled out a truncated version of the ASQ prior to reading the respective narratives assigned to their groups, and filled out the entirety of the ASQ after reading the narratives. Utilizing a one-way independent groups ANOVA, researchers found that the group which read the insecure-avoidant narrative experienced a statistically significant decrease in secure attachment, as did the group which read the secure narrative. The control group, however, experienced a statistically significant increase in secure attachment. Based on these findings, researchers concluded that narratives may have the ability to call attention to parental shortcomings that individuals have experienced in the forms of reminding individuals of positive experiences that they were not able to experience while spending time with their parental figures and calling attention to the shortcomings of said parental figures by reminding them of the negative experiences which they did have with them.

Keywords: attachment, insecure-avoidant, memory, secure

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Authors: Ghada Badr, Arwa Alturki

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The biological function of an RNA molecule depends on its structure. The objective of the alignment is finding the homology between two or more RNA secondary structures. Knowing the common functionalities between two RNA structures allows a better understanding and a discovery of other relationships between them. Besides, identifying non-coding RNAs -that is not translated into a protein- is a popular application in which RNA structural alignment is the first step A few methods for RNA structure-to-structure alignment have been developed. Most of these methods are partial structure-to-structure, sequence-to-structure, or structure-to-sequence alignment. Less attention is given in the literature to the use of efficient RNA structure representation and the structure-to-structure alignment methods are lacking. In this paper, we introduce an O(N2) Component-based Pairwise RNA Structure Alignment (CompPSA) algorithm, where structures are given as a component-based representation and where N is the maximum number of components in the two structures. The proposed algorithm compares the two RNA secondary structures based on their weighted component features rather than on their base-pair details. Extensive experiments are conducted illustrating the efficiency of the CompPSA algorithm when compared to other approaches and on different real and simulated datasets. The CompPSA algorithm shows an accurate similarity measure between components. The algorithm gives the flexibility for the user to align the two RNA structures based on their weighted features (position, full length, and/or stem length). Moreover, the algorithm proves scalability and efficiency in time and memory performance.

Keywords: alignment, RNA secondary structure, pairwise, component-based, data mining

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Authors: In-Hwan Baek

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Valsartan is a potent and highly selective antagonist of the angiotensin II type 1 receptor, and is widely used for the treatment of hypertension. The aim of this study was to investigate the pharmacokinetic properties of the valsartan in dogs following oral administration of a single dose using quantitative modeling approaches. Forty beagle dogs were randomly divided into two group. Group A (n=20) was administered a single oral dose of valsartan 80 mg (Diovan® 80 mg), and group B (n=20) was administered a single oral dose of valsartan 160 mg (Diovan® 160 mg) in the morning after an overnight fast. Blood samples were collected into heparinized tubes before and at 0.5, 1, 1.5, 2, 2.5, 3, 4, 6, 8, 12 and 24 h following oral administration. The plasma concentrations of the valsartan were determined using LC-MS/MS. Non-compartmental pharmacokinetic analyses were performed using WinNonlin Standard Edition software, and modeling approaches were performed using maximum-likelihood estimation via the expectation maximization (MLEM) algorithm with sampling using ADAPT 5 software. After a single dose of valsartan 80 mg, the mean value of maximum concentration (Cmax) was 2.68 ± 1.17 μg/mL at 1.83 ± 1.27 h. The area under the plasma concentration-versus-time curve from time zero to the last measurable concentration (AUC24h) value was 13.21 ± 6.88 μg·h/mL. After dosing with valsartan 160 mg, the mean Cmax was 4.13 ± 1.49 μg/mL at 1.80 ± 1.53 h, the AUC24h was 26.02 ± 12.07 μg·h/mL. The Cmax and AUC values increased in proportion to the increment in valsartan dose, while the pharmacokinetic parameters of elimination rate constant, half-life, apparent of total clearance, and apparent of volume of distribution were not significantly different between the doses. Valsartan pharmacokinetic analysis fits a one-compartment model with first-order absorption and elimination following a single dose of valsartan 80 mg and 160 mg. In addition, high inter-individual variability was identified in the absorption rate constant. In conclusion, valsartan displays the dose-dependent pharmacokinetics in dogs, and Subsequent quantitative modeling approaches provided detailed pharmacokinetic information of valsartan. The current findings provide useful information in dogs that will aid future development of improved formulations or fixed-dose combinations.

Keywords: dose-dependent, modeling, pharmacokinetics, valsartan

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Authors: Ozlem Temiz-Arpaci, Meryem Tasci, Fatma Sezer Senol, İlkay Erdogan Orhan

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Alzheimer’s disease (AD), a neurodegenerative disorder characterized by a progressive deterioration of memory and cognition, occurs more frequently in elderly people. Current treatment approaches in this disease with the major therapeutic strategy are based on the AChE and BChE inhibition. On the other hand, tyrosinase inhibition has become a target for the treatment of Parkinson’s disease (PD) since this enzyme may play a role in neuromelanin formation in the human brain and could be critical in the formation of dopamine neurotoxicity associated with neurodegeneration linked to PD. Also benzoxazoles are structural isosteres of natural nucleotides that can interact with biopolymers so that benzoxazoles showed a lot of different biological activities. In this study, a series of 2,5-disubstituted-benzoxazole derivatives were synthesized and were evaluated as possible inhibitors of acetylcholinesterase (AChE) / butyrylcholinesterase (BChE) and tyrosinase. The results demonstrated that the compounds exhibited a weak spectrum of AChE / BChE inhibitory activity ranging between 3.92% - 54.32% except compound 8 which showed no activity against AChE and compound 4 which showed no activity against BChE at the specified molar concentrations. Also, the compounds indicated lower than tyrosinase inhibitory activity of ranging between 8.14% - 22.90% to that of reference (kojic acid).

Keywords: AChE and BChE inhibition, Alzheimer’s disease, benzoxazoles, tyrosinase inhibition

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Authors: S. Nqayi

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Understanding the structural, electronic, and magnetic properties of nanomaterials is essential for developing next-generation electronic and spintronic devices, contributing to the progress of nanoscience and nanotechnology applications. Multiferroic materials, with intimately coupled ferroic-order parameters, are widely considered to breed fascinating physical properties and provide unique opportunities for the development of next-generation devices, like multistate non-volatile memory. In this study, we are set to investigate the structural, electronic, and magnetic properties of the frustrated Feᴵᴵ/Smⱽᴵ sublattice in relation to the widely studied perovskites for spintronics applications. The atomic composition, microstructure, crystallography, magnetization, thermal, and dielectric properties of a pyrochlore Sm₂Fe₂O₇ system synthesized using sol-gel methods are currently being investigated. Precursor powders were dissolved in citric acid monohydrate to obtain a solution. The obtained solution was stirred and heated using a magnetic stirrer to obtain the gel phase. Then, the gel was dried at 200°C to remove water and organic compounds and form an orange powder. The X-ray diffraction analysis confirms that the structure crystallized as a pyrochlore structure with a tetragonal F4mm (107) symmetry. The presence of Fe³⁺/Fe⁴⁺ mixed states is also revealed by XPS analysis.

Keywords: nanostructures, multiferroic materials, pyrochlores, spintronics

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Authors: A. Alao Olumuyiwa

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Health hazards reported to be associated with exposure to electromagnetic radiations which include brain tumors, genotoxic effects, neurological effects, immune system deregulation, allergic responses and some cardiovascular effects are discussed under a closed tabular model in this study. This review however showed that there is strong and robust evidence that chronic exposures to electromagnetic frequency across the spectrum, through strength, consistency, biological plausibility and many dose-response relationships, may result in brain cancer and other carcinogenic disease symptoms. There is therefore no safe threshold because of the genotoxic nature of the mechanism that may however be involved. The discussed study explains that the cell phone has induced effects upon the blood –brain barrier permeability and the cerebellum exposure to continuous long hours RF radiation may result in significant increase in albumin extravasations. A physical Biomodeling approach is however employed to review this health effects using Specific Absorption Rate (SAR) of different GSM machines to critically examine the symptoms such as a decreased loco motor activity, increased grooming and reduced memory functions in a variety of animal spices in classified grouped and sub grouped models.

Keywords: brain cancer, electromagnetic radiations, physical biomodeling, specific absorption rate (SAR)

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Authors: Triza Edwar Fawzi Deif

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In the process of urbanization in China, new rural construction is on the ascendant, which is becoming more and more popular. Under the driving effect of rural urbanization, the house pattern and tectonic methods of traditional vernacular houses have shown great differences from the family structure and values of contemporary peasant families. Therefore, it is particularly important to find a prototype, form and strategy to make a balance between the traditional memory and modern functional requirements. In order for research to combine the regional culture with modern life, under the situation of the current batch production of new rural residences, Badie village, in Zhejiang province, is taken as the case. This paper aims to put forward a prototype which can not only meet the demand of modern life but also ensure the continuation of traditional culture and historical context for the new rural dwellings design. This research not only helps to extend the local context in the construction of the new site but also contributes to the fusion of old and new rural dwellings in the old site construction. Through the study and research of this case, the research methodology and results can be drawn as reference for the new rural construction in other areas.

Keywords: steel slag, co-product, primary coating, steel aggregate capital, rural areas, rural planning, rural governance village, design strategy, new rural dwellings, regional context, regional expression

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Authors: Cao Jiayu, Lan Ximing, Huang Jingjia, Burra Venkata Durga Kumar

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The first virus to attack personal computers was born in early 1986, called C-Brain, written by a pair of Pakistani brothers. In those days, people still used dos systems, manipulating computers with the most basic command lines. In the 21st century today, computer performance has grown geometrically. But computer viruses are also evolving and escalating. We never stop fighting against security problems. Stack overflow is one of the most common security vulnerabilities in operating systems. It may result in serious security issues for an operating system if a program in it has a vulnerability with administrator privileges. Certain viruses change the value of specific memory through a stack overflow, allowing computers to run harmful programs. This study developed a mechanism to detect and respond to time whenever a stack overflow occurs. We demonstrate the effectiveness of standard machine learning algorithms and control flow enforcement techniques in predicting computer OS security using generating suspicious vulnerability functions (SVFS) and associated suspect areas (SAS). The method can minimize the possibility of stack overflow attacks occurring.

Keywords: operating system, security, stack overflow, buffer overflow, machine learning, control-flow enforcement technology

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Authors: Ganbat Danaa, Chuluundorj Puntsag

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The steel structures of the Oyu-Tolgoi mining Concentrator plant are corroded during operation, which raises doubts about the continued use of some important structures of the plant, which is one of the problems facing the plant's regular operation. As a part of the main operation of the plant, the bottom part of the pressure vessel, which plays an important role in the reliable operation of the concentrate filter-drying unit, was heavily corroded, so it was necessary to study by engineering calculations, modeling, and simulation using modern advanced engineering programs and methods. The purpose of this research is to investigate whether the corroded part of the pressure vessel can be used normally in the future using advanced engineering software and to predetermine the remaining life of the time of the pressure vessel based on engineering calculations. When the thickness of the bottom part of the pressure vessel was thinned by 0.5mm due to corrosion detected by non-destructive testing, finite element analysis using ANSYS WorkBench software was used to determine the mechanical stress, strain and safety factor in the wall and bottom of the pressure vessel operating under 2.2 MPa working pressure, made conclusions on whether it can be used in the future. According to the recommendations, by using sand-blast cleaning and anti-corrosion paint, the normal, continuous and reliable operation of the Concentrator plant can be ensured, such as ordering new pressure vessels and reducing the installation period. By completing this research work, it will be used as a benchmark for assessing the corrosion condition of steel parts of pressure vessels and other metallic and non-metallic structures operating under severe conditions of corrosion, static and dynamic loads, and other deformed steels to make analysis of the structures and make it possible to evaluate and control the integrity and reliable operation of the structures.

Keywords: corrosion, non-destructive testing, finite element analysis, safety factor, structural reliability

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Authors: A. C. Dey, H. M. Ahsan

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Heterogeneous traffic composed of both motorized and non-motorized vehicles that are a common feature of urban Bangladeshi roads. Popular non-motorized vehicles include rickshaws, rickshaw-van, and bicycle. These modes performed an important role in moving people and goods in the absence of a dependable mass transport system. However, rickshaws play a major role in meeting the demand for door-to-door public transport services to the city dwellers. But there is no separate lane for non-motorized vehicles in this city. Non-motorized vehicles generally occupy the outermost or curb-side lanes, however, at intersections non-motorized vehicles get mixed with the motorized vehicles. That’s why the conventional models fail to analyze the situation completely. Microscopic traffic simulation software VISSIM 5.3, itself a lane base software but default behavioral parameters [such as driving behavior, lateral distances, overtaking tendency, CCO=0.4m, CC1=1.5s] are modified for calibrating a model to analyze the effects of non-motorized traffic at an intersection (Mirpur-10) in a non-lane based mixed traffic condition. It is seen from field data that NMV occupies an average 20% of the total number of vehicles almost all the link roads. Due to the large share of non-motorized vehicles, capacity significantly drop. After analyzing simulation raw data, significant variation is noticed. Such as the average vehicular speed is reduced by 25% and the number of vehicles decreased by 30% only for the presence of NMV. Also the variation of lateral occupancy and queue delay time increase by 2.37% and 33.75% respectively. Thus results clearly show the negative effects of non-motorized vehicles on capacity at an intersection. So special management technics or restriction of NMV at major intersections may be an effective solution to improve this existing critical condition.

Keywords: lateral occupancy, non lane based intersection, nmv, queue delay time, VISSIM 5.3

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Authors: Mafawez Alharbi, Mahdi Jemmali

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E-learning is a developing area especially in education. E-learning can provide several benefits to learners. An intelligent system to collect all components satisfying user preferences is so important. This research presents an approach that it capable to personalize e-information and give the user their needs following their preferences. This proposal can make some knowledge after more evaluations made by the user. In addition, it can learn from the habit from the user. Finally, we show a walk-through to prove how intelligent process work.

Keywords: artificial intelligence, architecture, e-learning, software engineering, processing

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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Authors: Pawel Magryta, Mateusz Paszko

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In today's world, a big problem of individual mobility, especially in large urban areas, occurs. Commonly used grand way of transport such as buses, trains or cars do not fulfill their tasks, i.e. they are not able to meet the increasing mobility needs of the growing urban population. Additional to that, the limitations of civil infrastructure construction in the cities exist. Nowadays the most common idea is to transfer the part of urban transport on the level of air transport. However to do this, there is a need to develop an individual flying transport vehicle. The biggest problem occurring in this concept is the type of the propulsion system from which the vehicle will obtain a lifting force. Standard propeller drives appear to be too noisy. One of the ideas is to provide the required take-off and flight power by the machine using the innovative ejector system. This kind of the system will be designed through a suitable choice of the three-dimensional geometric structure with special shape of nozzle in order to generate overpressure. The authors idea is to make a device that would allow to cumulate the overpressure using the a five-sided geometrical structure that will be limited on the one side by the blowing flow of air jet. In order to test this hypothesis a computer simulation study of aerodynamic drag of such 3D structures have been made. Based on the results of these studies, the tests on real model were also performed. The final stage of work was a comparative analysis of the results of simulation and real tests. The CFD simulation studies of air flow was conducted using the Star CD - Star Pro 3.2 software. The design of virtual model was made using the Catia v5 software. Apart from the objective to obtain advanced aviation propulsion system, all of the tests and modifications of 3D structures were also aimed at achieving high efficiency of this device while maintaining the ability to generate high value of overpressures. This was possible only in case of a large mass flow rate of air. All these aspects have been possible to verify using CFD methods for observing the flow of the working medium in the tested model. During the simulation tests, the distribution and size of pressure and velocity vectors were analyzed. Simulations were made with different boundary conditions (supply air pressure), but with a fixed external conditions (ambient temp., ambient pressure, etc.). The maximum value of obtained overpressure is 2 kPa. This value is too low to exploit the power of this device for the individual transport vehicle. Both the simulation model and real object shows a linear dependence of the overpressure values obtained from the different geometrical parameters of three-dimensional structures. Application of computational software greatly simplifies and streamlines the design and simulation capabilities. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: aviation propulsion, CFD, 3d structure, aerodynamic drag

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Authors: Azizeh Chalak, Firouzeh Baktash

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Reticence is a prominent and complex phenomenon which occurs in foreign language classrooms and influences students’ oral passivity. The present study investigated the extent in which students experience reticence in the EFL classrooms and explored the underlying factors triggering reticence. The participants were 104 Iranian freshmen undergraduate male and female EFL students, who enrolled in listening and speaking courses, all majoring in English studying at Islamic Azad University Isfahan (Khorasgan) Branch and University of Isfahan, Isfahan, Iran. To collect the data, the Reticence Scale-12 (RS-12) questionnaire which measures the level of reticence consisting of six dimensions (anxiety, knowledge, timing, organization, skills, and memory) was administered to the participants. The statistical analyses showed that the reticent level was high among the Iranian EFL undergraduate students, and their major problems were feelings of anxiety and delivery skills. Moreover, the results revealed that factors such as low English proficiency, the teaching method, and lack of confidence contributed to the students’ reticence in Iranian EFL classrooms. It can be implied that language teachers’ awareness of learners’ reticence can help them choose more appropriate activities and provide a friendly environment enhancing hopefully more effective participation of EFL learners. The findings can have implications for EFL teachers, learners and policy makers.

Keywords: anxiety, Iranian EFL learners, reticence, reticence scale-12

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Authors: Hesamaddin Khoshnoodi, Ahmad Rahbar Ranji

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Corrosion in steel structures is one of the most important issues that should be considered in designing and constructing. Corrosion reduces the cross section and load capacity of element and leads to costly damage of structures. In this paper, the corrosion has been modeled for moment stresses. Moreover, the steel beam has been modeled using ABAQUS advanced finite element software. The conclusions of this study demonstrated that the displacement of the analyzed composite steel girder bridge might increase.

Keywords: Abaqus, Corrosion, deformation, Steel Beam

Procedia PDF Downloads 354

Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

Procedia PDF Downloads 143

Authors: Jacob Seddlemeyer, Tahar Messadi, Hongmei Gu, Mahboobeh Hemmati

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The main purpose of this first tier of the study is to quantify and compare the embodied environmental impacts associated with alternative materials applied to Adohi Hall, a residence building at the University of Arkansas campus, Fayetteville, AR. This 200,000square foot building has5 stories builtwith mass timber and is compared to another scenario where the same edifice is built with a steel frame. Based on the defined goal and scope of the project, the materials respectivetothe respective to the two building options are compared in terms of Global Warming Potential (GWP), starting from cradle to the construction site, which includes the material manufacturing stage (raw material extract, process, supply, transport, and manufacture) plus transportation to the site (module A1-A4, based on standard EN 15804 definition). The consumedfossil fuels and emitted CO2 associated with the buildings are the major reason for the environmental impacts of climate change. In this study, GWP is primarily assessed to the exclusion of other environmental factors. The second tier of this work is to evaluate Tally’s performance in the decision-making process through the design phases, as well as determine its strengths and weaknesses. Tally is a Life Cycle Assessment (LCA) tool capable of conducting a cradle-to-grave analysis. As opposed to other software applications, Tally is specifically targeted at buildings LCA. As a peripheral application, this software tool is directly run within the core modeling application platform called Revit. This unique functionality causes Tally to stand out from other similar tools in the building sector LCA analysis. The results of this study also provide insights for making more environmentally efficient decisions in the building environment and help in the move forward to reduce Green House Gases (GHGs) emissions and GWP mitigation.

Keywords: comparison, GWP, LCA, materials, tally

Procedia PDF Downloads 226

Authors: Sh. Khoshemehry, M. E. Bahram, M. J. Pourvaghar

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Sport has found a special place as an effective phenomenon in all societies of the contemporary world. The relationship between physical activity and exercise with different sciences has provided new fields for human study. The range of issues related to exercise and physical education is such that it requires specialized sciences and special studies. In this article, the psychological and social sections of exercise have been investigated for children and adults. It can be used for anyone in different age groups. Exercise and regular physical movements have a great impact on the mental and social health of the individual in addition to body health. It affects the individual's adaptability in society and his/her personality. Exercise affects the treatment of diseases such as depression, anxiety, stress, body image, and memory. Exercise is a safe haven for young people to achieve the optimum human development in its shelter. The effects of sensorimotor skills on mental actions and mental development are such a way that many psychologists and sports science experts believe these activities should be included in training programs in the first place. Familiarity of students and scholars with different programs and methods of sensorimotor activities not only causes their mental actions; but also increases mental health and vitality, enhances self-confidence and, therefore, mental health.

Keywords: anxiety, mental health, physical activity, serotonin

Procedia PDF Downloads 207

Authors: Nicolás Rudas

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Sociologists have brought to light the fascination of contemporary societies with numbers but fall short of explaining it. In their accounts, people generally misunderstand the technical intricacies of statistical knowledge and therefore accept numbers as unassailable “facts”. It is due to such pervasive fascination, furthermore, that both old and new forms of social control find fertile ground. By focusing on the process whereby the fetishization of numbers reaches its zenith, i.e., when specific statistics become emblematic of an entire society, it is asserted that numbers primarily function as moral symbols with immense potential for galvanizing collective action. Their “facticity” is not solely a cognitive problem but one that is deeply rooted in myth and connected with social experiences of epiphany and ritual. Evidence from Colombia is used to illustrate how certain quantifications become canonical. In 2021, Colombia’s Peace Court revealed that the national army had executed 6,402 innocent civilians to later report them as members of illegal armed groups. Rapidly, “6,402” transformed into a prominent item in the country’s political landscape. This article reconstructs such a process by following the first six months of the figure’s circulation, both in traditional and social media. In doing so, it is developed a new cultural-sociological conceptualization of numbers as “fact-icons” that departs from traditional understandings of statistics as “technical” objects. Numbers are icons whose appropriation is less rational than aesthetic.

Keywords: culture, statistics, collective memory, social movements

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Authors: Chris Phan, Yong Seok Park

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The Toyota Camry is one of the best-selling cars in America. It is economical, reliable, and most importantly, safe. These attributes allowed the Camry to be the trustworthy choice when choosing dependable vehicle. However, a new finding brought question to the Camry’s safety. Since 1997, the Camry received a “good” rating on its moderate overlap front crash test through the Insurance Institute of Highway Safety. In 2012, the Insurance Institute of Highway Safety introduced a frontal small overlap crash test into the overall evaluation of vehicle occupant safety test. The 2012 Camry received a “poor” rating on this new test, while the 2015 Camry redeemed itself with a “good” rating once again. This study aims to find a possible solution that Toyota implemented to reduce the severity of a frontal small overlap crash in the Camry during a mid-cycle update. The purpose of this study is to analyze and evaluate the performance of various A-pillar shapes as energy absorbing structures in improving passenger safety in a frontal crash. First, A-pillar structures of the 2012 and 2015 Camry were modeled using CAD software, namely SolidWorks. Then, a crash test simulation using ANSYS software, was applied to the A-pillars to analyze the behavior of the structures in similar conditions. Finally, the results were compared to safety values of cabin intrusion to determine the crashworthy behaviors of both A-pillar structures by measuring total deformation. This study highlights that it is possible that Toyota improved the shape of the A-pillar in the 2015 Camry in order to receive a “good” rating from the IIHS safety evaluation once again. These findings can possibly be used to increase safety performance in future vehicles to decrease passenger injury or fatality.

Keywords: A-pillar, Crashworthiness, Design Synthesis, Finite Element Analysis

Procedia PDF Downloads 119