Search results for: publication performance

Authors: Anjela Koblischka-Veneva, Michael R. Koblischka

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To increase the flux pinning performance of bulk YBa2Cu3O7-δ (YBCO or Y-123) superconductors, it is common to employ secondary phase particles, either Y2BaCuO5 (Y-211) particles created during the growth of the samples or additionally added (nano)particles of various types, embedded in the superconducting Y-123 matrix. As the crystallographic parameters of all the particles indicate a misfit to Y-123, there will be residual strain within the Y-123 matrix around such particles. With a dedicated analysis of electron backscatter diffraction (EBSD) data obtained on various bulk, Y-123 superconductor samples, the strain distribution around such embedded secondary phase particles can be revealed. The results obtained are presented in form of Kernel Average Misorientation (KAM) mappings. Around large Y-211 particles, the strain can be so large that YBCO subgrains are formed. Therefore, it is essential to properly control the particle size as well as their distribution within the bulk sample to obtain the best performance. The impact of the strain distribution on the flux pinning properties is discussed.

Keywords: Bulk superconductors, EBSD, Strain, YBa2Cu3Oy

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Authors: Saru Arora, Anurag Sharma, Harsukhpreet Singh

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To meet the growing need of high data rate and bandwidth, various efforts has been made nowadays for the efficient communication systems. Optical Code Division Multiple Access over Free space optics communication system seems an effective role for providing transmission at high data rate with low bit error rate and low amount of multiple access interference. This paper demonstrates the OCDMA over FSO communication system up to the range of 7000 m at a data rate of 5 Gbps. Initially, the 8 user OCDMA-FSO system is simulated and pseudo orthogonal codes are used for encoding. Also, the simulative analysis of various performance parameters like power and core effective area that are having an effect on the Bit error rate (BER) of the system is carried out. The simulative analysis reveals that the length of the transmission is limited by the multi-access interference (MAI) effect which arises when the number of users increases in the system.

Keywords: FSO, PSO, bit error rate (BER), opti system simulation, multiple access interference (MAI), q-factor

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Authors: Zayar Phyo, Ei Chaw Htoon

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In a New-LSB based Steganography method, the Fisher-Yates algorithm is used to permute an existing array randomly. However, that algorithm performance became slower and occurred memory overflow problem while processing the large dimension of images. Therefore, the Text-Based Shuffling algorithm aimed to select only necessary pixels as hiding characters at the specific position of an image according to the length of the input text. In this paper, the enhanced text-based shuffling algorithm is presented with the powered of GPU to improve more excellent performance. The proposed algorithm employs the OpenCL Aparapi framework, along with XORShift Kernel including the Pseudo-Random Number Generator (PRNG) Kernel. PRNG is applied to produce random numbers inside the kernel of OpenCL. The experiment of the proposed algorithm is carried out by practicing GPU that it can perform faster-processing speed and better efficiency without getting the disruption of unnecessary operating system tasks.

Keywords: LSB based steganography, Fisher-Yates algorithm, text-based shuffling algorithm, OpenCL, XORShiftKernel

Procedia PDF Downloads 154

Authors: Sadegh Torfi

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Realization of anticipated energy efficiency from recuperative run-around energy recovery (RER) systems requires identification of the system components influential parameters. Because simulation modeling is considered as an integral part of the design and economic evaluation of RER systems, it is essential to calibrate the developed models and validate the performance predictions by means of comparison with data from experimental measurements. Several theoretical and numerical analyses on RER systems by researchers have been done, but generally the effect of distance between hot and cold flow is ignored. The objective of this study is to develop a thermohydroulic model for a typical RER system that accounts for energy loss from the interconnecting piping and effects of interconnecting pipes length performance of run-around energy recovery systems. Numerical simulation shows that energy loss from the interconnecting piping is change linear with pipes length and if pipes are properly isolated, maximum reduction of effectiveness of RER systems is 2% in typical piping systems.

Keywords: combined heat and power, heat recovery, effectiveness, CGS

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Authors: Siti Nurkhamidah, Yeni Rahmawati, Fadlilatul Taufany, Eamor M. Woo, I Made P. A. Merta, Deffry D. A. Putra, Pitsyah Alifiyanti, Krisna D. Priambodo

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Cellulose acetate/polyethylene glycol (CA/PEG) membrane was modified with varying amount of silica and carbon nanotube (CNT) to enhance its separation performance in the desalination process. These composite membranes were characterized for their hydrophilicity, morphology and permeation properties. The experiment results show that hydrophilicity of CA/PEG/Silica membranes increases with the increasing of silica concentration and the decreasing particle size of silica. From Scanning Electron Microscopy (SEM) image, it shows that pore structure of CA/PEG membranes increases with the addition of silica. Membrane performance analysis shows that permeate flux, salt rejection, and permeability of membranes increase with the increasing of silica concentrations. The effect of CNT on the hydrophylicity, morphology, and permeation properties was also discussed.

Keywords: carbon nanotube, cellulose acetate, desalination, membrane, PEG

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Authors: Charmaine Lamiel, Van Hoa Nguyen, Jae-Jin Shim

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Supercapacitors are energy storage devices capable of storing more energy than conventional capacitors and have higher power density than batteries. The advantages of this method include the non-use of reducing agents and acidic medium, and no further use of a post-heat treatment unlike the conventional processes, in which calcination is generally employed after obtaining the initial product. Furthermore, it also offers a shorter reaction time at low temperatures and low power requirements, which allows low fabrication and energy cost. In this study, microwave irradiation was used for the facile and rapid synthesis of mesoporous RGO@(Co,Mn)3O4 nanosheets as an electrode material. The as-prepared electrode exhibited a high capacitance of 953 F•g^−1 at 1 A•g^−1 in a 6 M KOH electrolyte solution. Moreover, the electrode exhibited a high energy density of 76.2 Wh•kg^−1 at a power density of 720 W•kg^−1, and a high power density of 7200 W•kg^−1 at an energy density of 38 Wh•kg^−1. The successful methodology was considered to be efficient and cost-effective, thereby providing an active electrode material with very promising electrochemical performance.

Keywords: cobalt-manganese oxide, electrochemical, graphene, microwave synthesis, supercapacitor

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Authors: Chia-Chia Chang, Jhen-Ting Huang, Hu-Cheng Weng, An-Ya Lo

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This study developed a simple hierarchical porous carbon (HPC) synthesis process and used for supercapacitor application. In which, mesopore provides huge specific surface area, meanwhile, macropore provides excellent mass transfer. Thus the hierarchical porous electrode improves the charge-discharge performance. On the other hand, cerium oxide (CeO2) have also got a lot research attention owing to its rich in content, low in price, environmentally friendly, good catalytic properties, and easy preparation. Besides, a rapid redox reaction occurs between trivalent cerium and tetravalent cerium releases oxygen atom and increase the conductivity. In order to prevent CeO2 from disintegration under long-term charge-discharge operation, the CeO2 carbon porous materials were was integrated as composite material in this study. For in the ex-situ analysis, scanning electron microscope (SEM), X-ray diffraction (XRD), transmission electron microscope (TEM) analysis were adopted to identify the surface morphology, crystal structure, and microstructure of the composite. 77K Nitrogen adsorption-desorption analysis was used to analyze the porosity of each specimen. For the in-situ test, cyclic voltammetry (CV) and chronopotentiometry (CP) were conducted by potentiostat to understand the charge and discharge properties. Ragone plot was drawn to further analyze the resistance properties. Based on above analyses, the effect of macropores/mespores and the CeO2/HPC ratios on charge-discharge performance were investigated. As a result, the capacitance can be greatly enhanced by 2.6 times higher than pristine mesoporous carbon electrode.

Keywords: hierarchical porous carbon, cerium oxide, supercapacitor

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Authors: Yulan Wu

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The spread of fake news on social media has posed significant societal harm to the public and the nation, with its threats spanning various domains, including politics, economics, health, and more. News on social media often covers multiple domains, and existing models studied by researchers and relevant organizations often perform well on datasets from a single domain. However, when these methods are applied to social platforms with news spanning multiple domains, their performance significantly deteriorates. Existing research has attempted to enhance the detection performance of multi-domain datasets by adding single-domain labels to the data. However, these methods overlook the fact that a news article typically belongs to multiple domains, leading to the loss of domain knowledge information contained within the news text. To address this issue, research has found that news records in different domains often use different vocabularies to describe their content. In this paper, we propose a fake news detection framework that combines domain knowledge and expert knowledge. Firstly, it utilizes an unsupervised domain discovery module to generate a low-dimensional vector for each news article, representing domain embeddings, which can retain multi-domain knowledge of the news content. Then, a feature extraction module uses the domain embeddings discovered through unsupervised domain knowledge to guide multiple experts in extracting news knowledge for the total feature representation. Finally, a classifier is used to determine whether the news is fake or not. Experiments show that this approach can improve multi-domain fake news detection performance while reducing the cost of manually labeling domain labels.

Keywords: fake news, deep learning, natural language processing, multiple domains

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Authors: Ibrahim Cicek, Melike Nikbay

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Electrically propelled vehicles, either road or aerial vehicles are studied on contemporarily for their robust maneuvers and cost-efficient transport operations. The main power generating systems of such vehicles electrified by selecting proper components and assembled as e-powertrain. Generally, e-powertrain components selected considering the target performance requirements. Since the main component of propulsion is the drive unit, e-motor control system is subjected to achieve the performance targets. In this paper, the optimization of e-motor control parameters studied by Integral Squared Method (ISE). The overall aim is to minimize power consumption of such vehicles depending on mission profile and maintaining smooth maneuvers for passenger comfort. The sought-after values of control parameters are computed using the Optimal Control Theory. The system is modeled as a closed-loop linear control system with calibratable parameters.

Keywords: optimization, e-powertrain, optimal control, electric vehicles

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Authors: Mohammed A. Elhaj, Jamal S. Yassin

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Owing to the lack of synchronization between the solar energy availability and the heat demands in a specific application, the energy storing sub-system is necessary to maintain the continuity of thermal process. The present work is dealing with an active solar heating storing system in which an air solar collector is connected to storing unit where this energy is distributed and provided to the heated space in a controlled manner. The solar collector is a box type absorber where the air flows between a number of vanes attached between the collector absorber and the bottom plate. This design can improve the efficiency due to increasing the heat transfer area exposed to the flowing air, as well as the heat conduction through the metal vanes from the top absorbing surface. The storing unit is a packed bed type where the air is coming from the air collector and circulated through the bed in order to add/remove the energy through the charging / discharging processes, respectively. The major advantage of the packed bed storage is its high degree of thermal stratification. Numerical solution of the packed bed energy storage is considered through dividing the bed into a number of equal segments for the bed particles and solved the energy equation for each segment depending on the neighbor ones. The studied design and performance parameters in the developed simulation model including, particle size, void fraction, etc. The final results showed that the collector efficiency was fluctuated between 55%-61% in winter season (January) under the climatic conditions of Misurata in Libya. Maximum temperature of 52ºC is attained at the top of the bed while the lower one is 25ºC at the end of the charging process of hot air into the bed. This distribution can satisfy the required load for the most house heating in Libya.

Keywords: solar energy, thermal process, performance, collector, packed bed, numerical analysis, simulation

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Authors: Sogol Zarafshan

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The present study aimed to identify important factors affecting the effectiveness of quality control circles in a hospital, as well as rank them using a combination of fuzzy VIKOR and Grey Relational Analysis (GRA). The study population consisted of five academic members and five experts in the field of nursing working in a hospital, who were selected using a purposive sampling method. Also, a sample of 107 nurses was selected through a simple random sampling method using their employee codes and the random-number table. The required data were collected using a researcher-made questionnaire which consisted of 12 factors. The validity of this questionnaire was confirmed through giving the opinions of experts and academic members who participated in the present study, as well as performing confirmatory factor analysis. Its reliability also was verified (α=0.796). The collected data were analyzed using SPSS 22.0 and LISREL 8.8, as well as VIKOR–GRA and IPA methods. The results of ranking the factors affecting the effectiveness of quality control circles showed that the highest and lowest ranks were related to ‘Managers’ and supervisors’ support’ and ‘Group leadership’. Also, the highest hospital performance was for factors such as ‘Clear goals and objectives’ and ‘Group cohesiveness and homogeneity’, and the lowest for ‘Reward system’ and ‘Feedback system’, respectively. The results showed that although ‘Training the members’, ‘Using the right tools’ and ‘Reward system’ were factors that were of great importance, the organization’s performance for these factors was poor. Therefore, these factors should be paid more attention by the studied hospital managers and should be improved as soon as possible.

Keywords: Quality control circles, Fuzzy VIKOR, Grey Relational Analysis, Importance–Performance Analysis

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Authors: Khader S. Al-Aidmat, Venus W. Samawi

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Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

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Authors: Veronica Diaz Quezada

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In this article, the performance and errors are featured and analysed in the limit problems solving of a real-valued function, in correspondence to competency-based education in engineering careers, in the south of Chile. The methodological component is contextualised in a qualitative research, with a descriptive and explorative design, with elaboration, content validation and application of quantitative instruments, consisting of two parallel forms of open answer tests, based on limit application problems. The mathematical competences and errors made by students from five engineering careers from a public University are identified and characterized. Results show better performance only to solve routine-context problem-solving competence, thus they are oriented towards a rational solution or they use a suitable problem-solving method, achieving the correct solution. Regarding errors, most of them are related to techniques and the incorrect use of theorems and definitions of real-valued function limits of real variable.

Keywords: engineering education, errors, limits, mathematics competences, problem solving

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Authors: Domenico Panno, Antonino D’amico, Hamed Jafargholi

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This paper presents an experimental analysis of the performance of a system for freezing fish products equipped with a modulating vapour injection scroll compressor operating with R448A refrigerant. Freezing is a critical process for the preservation of seafood products, as it influences quality, food safety, and environmental sustainability. The use of a modulating scroll compressor with vapour injection, associated with the R448A refrigerant, is proposed as a solution to optimize the performance of the system, reducing energy consumption and mitigating the environmental impact. The stream injection modulating scroll compressor represents an advanced technology that allows you to adjust the compressor capacity based on the actual cooling needs of the system. Vapour injection allows the optimization of the refrigeration cycle, reducing the evaporation temperature and improving the overall efficiency of the system. The use of R448A refrigerant, with a low Global Warming Potential (GWP), is part of an environmental sustainability perspective, helping to reduce the climate impact of the system. The aim of this research was to evaluate the performance of the system through a series of experiments conducted on a pilot plant for the freezing of fish products. Several operational variables were monitored and recorded, including evaporation temperature, condensation temperature, energy consumption, and freezing time of seafood products. The results of the experimental analysis highlighted the benefits deriving from the use of the modulating vapour injection scroll compressor with the R448A refrigerant. In particular, a significant reduction in energy consumption was recorded compared to conventional systems. The modulating capacity of the compressor made it possible to adapt the cold production to variations in the thermal load, ensuring optimal operation of the system and reducing energy waste. Furthermore, the use of an electronic expansion valve highlighted greater precision in the control of the evaporation temperature, with minimal deviation from the desired set point. This helped ensure better quality of the final product, reducing the risk of damage due to temperature changes and ensuring uniform freezing of the fish products. The freezing time of seafood has been significantly reduced thanks to the configuration of the entire system, allowing for faster production and greater production capacity of the plant. In conclusion, the use of a modulating vapour injection scroll compressor operating with R448A has proven effective in improving the performance of a system for freezing fish products. This technology offers an optimal balance between energy efficiency, temperature control, and environmental sustainability, making it an advantageous choice for food industries.

Keywords: scroll compressor, vapor injection, refrigeration system, EER

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Authors: Nur Bella Octoria Bella, Ayomi Dita Rarasati

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DKI Jakarta is Indonesia's capital city with the 10th highest congestion rate in the world based on the 2019 traffic index. Other than that based on World Air Quality Report in 2019 showed DKI Jakarta's air pollutant concentrate 49.4 µg and the 5th highest air pollutant in the world. In the urban city nowadays, the mobility rate is high enough and the efficiency for sustainability assessment in transport infrastructure development is needed. This efficiency is the important key for sustainable infrastructure development. DKI Jakarta is nowadays in the process of constructing the railway infrastructure to support the transportation system. The problems appearing are the railway infrastructure networks and the service in DKI Jakarta already planned based on sustainability factors or not. Therefore, the aim of this research is to make the evaluation of railways infrastructure networks performance and services in DKI Jakarta regards on the railway sustainability key factors. Further, this evaluation will be used to make the railway sustainability assessment framework and to offer some of the alternative solutions to improve railway transportation sustainability in DKI Jakarta. Firstly a very detailed literature review of papers that have focused on railway sustainability factors and their improvements of railway sustainability, published in the scientific journal in the period 2011 until 2021. Regarding the sustainability factors from the literature review, further, it is used to assess the current condition of railway infrastructure in DKI Jakarta. The evaluation will be using a Likert rate questionnaire and directed to the transportation railway expert and the passenger. Furthermore, the mapping and evaluation rate based on the sustainability factors will be compared to the effect factors using the Analytical Hierarchical Process (AHP). This research offers the network's performance and service rate impact on the sustainability aspect and the passenger willingness for using the rail public transportation in DKI Jakarta.

Keywords: transportation sustainability, railway transportation, sustainability, DKI Jakarta

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Authors: Karima Chaabna, Sohaila Cheema, Amit Abraham, Hekmat Alrouh, Ravinder Mamtani, Javaid I. Sheikh

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We aimed to assess the production of systematic reviews (SRs) that synthesize observational studies discussing population health issues in the Middle East and North Africa (MENA). Two independent reviewers systematically searched MEDLINE through PubMed. Between 2008-2016, 5,747 articles (reviews, systematic reviews, and meta-analyses) were identified. Following a multi-stage screening process, 387 SRs (with or without meta-analysis) on population health issues in the MENA were included in our overview. Citation numbers for each SR were retrieved from Google Scholar. Impact factor of the journal during the publication year for the included SRs was retrieved from the Institute of Scientific Information’s Journal Citation Report. We conducted linear regression analysis to assess time trends of number of publications according to SRs’ characteristics. We characterized a linear statistically significant increase in the annual numbers of SRs that summarize observational studies on the MENA population health (p-value<0.0001, R2=0.95), from 15 in 2008 to 81 in 2016. Our analysis reveals also linear statistically significant increases in numbers of SRs published by authors affiliated to institutions located inside MENA and/or neighboring countries (N=113, p-value < 0.0001, R²=0.90), by authors located outside MENA (N=155, p-value=0.0007, R²=0.82), and by collaborating authors affiliated to institutions located outside MENA and inside the region and/or in MENA’s neighboring countries (total number of SRs (N)= 119, p-value=0.0004, R²=0.85). Furthermore, these SRs were published in journals with an IF ranging from 0 to 47.8 (median=2.1). Linear statistically significant increases in numbers of published SRs were demonstrated in journals’ impact factor (IF) categories (IF=[0-2[: R²=0.79, p-value=0.0012; IF=[2-4[:R²=0.86, p-value=0.0003; and IF=[4-6[:R²=0.53, p-value=0.026). Additionally, annual numbers of citations to the SRs varied between 0 and 471 (median=7). While each year, a couple of SRs were getting more than 50 annual citations, there were linear statistically significant increases in numbers of published SRs with an annual number of citations at [0-10[(R²=0.89, p-value=0.00014) and at [10-50[ (R²=0.76, p-value=0.0021). Between 2008-2016, increasingly SRs that summarize observational studies on population health issues in the MENA were published. Authors of these SRs were located inside and/or outside the MENA region and an increasing number of collaborations were seen. Increasing numbers of SRs were predominantly observed in journals with an IF between zero and six. Interestingly, SRs covering MENA region countries were being increasingly cited, indicating an escalation of interest in this region’s population health issues.

Keywords: bibliometric, citation, impact factor, Middle East and North Africa, population health, systematic review

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Authors: Hyun-Woo Cho

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Earlier detection of incipient abnormal operations in terms of plant-wide process management is quite necessary in order to improve product quality and process safety. And generating warning signals or alarms for operating personnel plays an important role in process automation and intelligent plant health monitoring. Various methodologies have been developed and utilized in this area such as expert systems, mathematical model-based approaches, multivariate statistical approaches, and so on. This work presents a nonlinear empirical monitoring methodology based on the real-time analysis of massive process data. Unfortunately, the big data includes measurement noises and unwanted variations unrelated to true process behavior. Thus the elimination of such unnecessary patterns of the data is executed in data processing step to enhance detection speed and accuracy. The performance of the methodology was demonstrated using simulated process data. The case study showed that the detection speed and performance was improved significantly irrespective of the size and the location of abnormal events.

Keywords: detection, monitoring, process data, noise

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Authors: Debarag Banerjee, Pooja Singh, Arjun Avadhanam, Saksham Srivastava

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Autonomous conversational agents, i.e., chatbots, are becoming an increasingly common mechanism for enterprises to provide support to customers and partners. In order to rate chatbots, especially ones powered by Generative AI tools like Large Language Models (LLMs), we need to be able to accurately assess their performance. This is where chatbot benchmarking becomes important. In this paper, authors propose the use of a benchmark that they call the E2E (End to End) benchmark and show how the E2E benchmark can be used to evaluate the accuracy and usefulness of the answers provided by chatbots, especially ones powered by LLMs. The authors evaluate an example chatbot at different levels of sophistication based on both our E2E benchmark as well as other available metrics commonly used in the state of the art and observe that the proposed benchmark shows better results compared to others. In addition, while some metrics proved to be unpredictable, the metric associated with the E2E benchmark, which uses cosine similarity, performed well in evaluating chatbots. The performance of our best models shows that there are several benefits of using the cosine similarity score as a metric in the E2E benchmark.

Keywords: chatbot benchmarking, end-to-end (E2E) benchmarking, large language model, user centric evaluation.

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Authors: Vithaya Intaraphimol

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This research investigates the effect of financial accounting information and non-financial accounting reports on corporate credibility via strength of board of directors and market environment volatility as moderating effect. Data in this research is collected by questionnaire form non-financial companies listed on the Stock Exchange of Thailand. Multiple regression statistic technique is chosen for analyzing the data. The empirical results find that firms with greater financial accounting information reports and non-financial accounting information reports will gain greater corporate credibility. Therefore, the corporate reporting has the value for the firms. Moreover, the strength of board of directors will positively moderate the financial and non-financial accounting information reports and corporate credibility relationship. Whereas, market environment volatility will negatively moderate the financial and nonfinancial accounting information reports and corporate credibility relationship.

Keywords: corporate credibility, financial and non-financial reports, firms performance, economics

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Authors: Mahmoud Khamaira, Ahmed Abu-Siada, Yasser Alharbi

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Doubly Fed Induction Generators (DFIGs) are currently extensively used in variable speed wind power plants due to their superior advantages that include reduced converter rating, low cost, reduced losses, easy implementation of power factor correction schemes, variable speed operation and four quadrants active and reactive power control capabilities. On the other hand, DFIG sensitivity to grid disturbances, especially for voltage sags represents the main disadvantage of the equipment. In this paper, a coil is proposed to be integrated within the DFIG converters to improve the overall performance of a DFIG-based wind energy conversion system (WECS). The charging and discharging of the coil are controlled by controlling the duty cycle of the switches of the dc-dc chopper. Simulation results reveal the effectiveness of the proposed topology in improving the overall performance of the WECS system under study.

Keywords: doubly fed induction generator, coil, wind energy conversion system, converter topology

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Authors: Mehmet Savsar

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One of the most important factors affecting power plant performance is the reliability of the turbine units operated under different conditions. Reliability directly affects plant availability and performance. Therefore, it is very important to be able to analyze turbine units, as well as power plant system reliability and availability under various operational conditions. In this paper, data related to power station failures are collected and analyzed in detail for all power stations in the state of Kuwait. Failures are characterized and categorized. Reliabilities of various power plants are analyzed and availabilities are quantified. Based on calculated availabilities of all installed power plants, actual power output is estimated. Furthermore, based on the past 15 years of data, power consumption trend is determined and the demand for power in the future is forecasted. Estimated power output is compared to the forecasted demand in order to determine the need for future capacity expansion.

Keywords: power plants, reliability, availability, capacity, preventive maintenance, forecasting

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Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini

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In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.

Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor

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Authors: A. Lovascio, A. D’Orazio, V. Centonze

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From several years till now the aerospace industry is developing more and more small satellites for Low-Earth Orbit (LEO) missions. Such satellites have a low cost of making and launching since they have a size and weight smaller than other types of satellites. However, because of size limitations, small satellites need integrated electronic equipment based on digital logic. Moreover, the LEOs require telecommunication modules with high throughput to transmit to earth a big amount of data in a short time. In order to meet such requirements, in this paper we propose a Telemetry, Tracking & Command module optimized through the use of the Commercial Off-The-Shelf components. The proposed approach exploits the major flexibility offered by these components in reducing costs and optimizing the performance. The method has been applied in detail for the design of the front-end receiver, which has a low noise figure (1.5 dB) and DC power consumption (smaller than 2 W). Such a performance is particularly attractive since it allows fulfilling the energy budget stringent constraints that are typical for LEO small platforms.

Keywords: COTS, LEO, small-satellite, TT&C

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Authors: Yang Liu

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Reinforced concrete (RC) shear wall structures are one of the most popular and efficient structural forms for medium- and high-rise buildings to resist the action of earthquake loading. Thus, it is of great significance to evaluate the seismic demands of the RC shear walls. In this paper, the application of the extend spectrum-based pushover analysis (ESPA) method on the seismic evaluation of the shear wall structure is presented. The ESPA method includes a nonlinear consecutive pushover analysis procedure and a linear elastic modal response analysis procedure to consider the combination of modes in both elastic and inelastic cases. It is found from the results of case study that the ESPA method can predict the seismic performance of shear wall structures, including internal forces and deformations very well.

Keywords: reinforced concrete shear wall, seismic performance, high mode effect, nonlinear analysis

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Authors: Umit Duru

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The Soil and Water Assessment Tool (SWAT) was tested for prediction of water balance and sediment yield in the Ankara gauged basin, Turkey. The overall objective of this study was to evaluate the performance and applicability of the SWAT in this region of Turkey. Thirteen years of monthly stream flow, and suspended sediment, data were used for calibration and validation. This research assessed model performance based on differences between observed and predicted suspended sediment yield during calibration (1987-1996) and validation (1982-1984) periods. Statistical comparisons of suspended sediment produced values for NSE (Nash Sutcliffe efficiency), RE (relative error), and R² (coefficient of determination), of 0.81, -1.55, and 0.93, respectively, during the calibration period, and NSE, RE (%), and R² of 0.77, -2.61, and 0.87, respectively, during the validation period. Based on the analyses, SWAT satisfactorily simulated observed hydrology and sediment yields and can be used as a tool in decision making for water resources planning and management in the basin.

Keywords: calibration, GIS, sediment yield, SWAT, validation

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Authors: Vinh Duy Cao, Shima Pilehvar, Anna M. Szczotok, Anna-Lena Kjøniksen

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The total energy consumption is dramatically increasing on over the world, especially for building energy consumption where a significant proportion of energy is used for heating and cooling purposes. One of the solutions to reduce the energy consumption for the building is to improve construction techniques and enhance material technology. Recently, microcapsulated phase change materials (MPCM) with high energy storage capacity within the phase transition temperature of the materials is a potential method to conserve and save energy. A new composite materials with high energy storage capacity by mixing MPCM into concrete for passive building technology is the promising candidate to reduce the energy consumption. One of the most untilized building materials for mixing with MPCM is Portland cement concrete. However, the emission of carbon dioxide (CO2) due to producing cement which plays the important role in the global warming is the main drawback of PCC. Accordingly, an environmentally friendly building material, geopolymer, which is synthesized by the reaction between the industrial waste material (aluminosilicate) and a strong alkali activator, is a potential materials to mixing with MPCM. Especially, the effect of MPCM on the thermal and mechanical properties of geopolymer concrete (GPC) is very limited. In this study, high thermal energy storage capacity materials were fabricated by mixing MPCM into geopolymer concrete. This article would investigate the effect of MPCM concentration on thermal and mechanical properties of GPC. The target is to balance the effect of MPCM on improving the thermal performance and maintaining the compressive strength of the geopolymer concrete at an acceptable level for building application.

Keywords: microencapsulated phase change materials, geopolymer concrete, energy storage capacity, thermal performance

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Authors: Ch. Sridevi, S. P. Shailender Kumar, B. Gurudayal, A. Chalapathi Rao, K. Koteswara Rao, P. Srinivasulu

Abstract:

System reliability and system availability evaluation plays a crucial role in ensuring the seamless operation of complex satellite data reception system with consistent performance for longer periods. This paper presents a novel approach for the same using a case study on one of the antenna systems at satellite data reception ground station in India. The methodology involves analyzing system's components, their failure rates, system's architecture, generation of logical reliability block diagram model and estimating the reliability of the system using the component level mean time between failures considering exponential distribution to derive a baseline estimate of the system's reliability. The model is then validated with collected system level field failure data from the operational satellite data reception systems that includes failure occurred, failure time, criticality of the failure and repair times by using statistical techniques like median rank, regression and Weibull analysis to extract meaningful insights regarding failure patterns and practical reliability of the system and to assess the accuracy of the developed reliability model. The study mainly focused on identification of critical units within the system, which are prone to failures and have a significant impact on overall performance and brought out a reliability model of the identified critical unit. This model takes into account the interdependencies among system components and their impact on overall system reliability and provides valuable insights into the performance of the system to understand the Improvement or degradation of the system over a period of time and will be the vital input to arrive at the optimized design for future development. It also provides a plug and play framework to understand the effect on performance of the system in case of any up gradations or new designs of the unit. It helps in effective planning and formulating contingency plans to address potential system failures, ensuring the continuity of operations. Furthermore, to instill confidence in system users, the duration for which the system can operate continuously with the desired level of 3 sigma reliability was estimated that turned out to be a vital input to maintenance plan. System availability and station availability was also assessed by considering scenarios of clash and non-clash to determine the overall system performance and potential bottlenecks. Overall, this paper establishes a comprehensive methodology for reliability and availability analysis of complex satellite data reception systems. The results derived from this approach facilitate effective planning contingency measures, and provide users with confidence in system performance and enables decision-makers to make informed choices about system maintenance, upgrades and replacements. It also aids in identifying critical units and assessing system availability in various scenarios and helps in minimizing downtime and optimizing resource allocation.

Keywords: exponential distribution, reliability modeling, reliability block diagram, satellite data reception system, system availability, weibull analysis

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Authors: Henar Martín-Sanz García, Eleni Chatzi, Eugen Brühwiler

Abstract:

Located on the shore of Geneva Lake, in Switzerland, the Chillon Viaducts are two parallel structures consisted of post-tensioned concrete box girders, with a total length of 2 kilometers and 100m spans. Built in 1969, the bridges currently accommodate a traffic load of 50.000 vehicles per day, thereby holding a key role both in terms of historic value as well as socio-economic significance. Although several improvements have been carried out in the past two decades, recent inspections demonstrate an Alkali-Aggregate reaction in the concrete deck and piers reducing the concrete strength. In order to prevent further expansion of this issue, a layer of 40 mm of Ultra High Performance Fiber Reinforced cement-based Composite (UHPFRC) (incorporating rebars) was casted over the slabs, acting as a waterproof membrane and providing significant increase in resistance of the bridge structure by composite UHPFRC – RC composite action in particular of the deck slab. After completing the rehabilitation works, a Structural Monitoring campaign was installed on the deck slab in one representative span, based on accelerometers, strain gauges, thermal and humidity sensors. This campaign seeks to reveal information on the behavior of UHPFRC-concrete composite systems, such as increase in stiffness, fatigue strength, durability and long-term performance. Consequently, the structural monitoring is expected to last for at least three years. A first insight of the analyzed results from the initial months of measurements is presented herein, along with future improvements or necessary changes on the deployment.

Keywords: composite materials, rehabilitation, structural health monitoring, UHPFRC

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Authors: Luis C. Parra

Abstract:

The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.

Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms

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Authors: Sasitharan Ambicapathy, J. Vignesh, P. Sivaraj, Godfrey Derek Sams, K. Sabarinath, V. R. Sanal Kumar

Abstract:

The external flow simulation of a flying car at take off phase is a daunting task owing to the fact that the prediction of the transient unsteady flow features during its deployment phase is very complex. In this paper 3D numerical simulations of external flow of Ferrari F430 proposed flying car with different NACA 9618 rectangular wings have been carried. Additionally, the aerodynamics characteristics have been generated for optimizing its geometry for achieving the minimum take off velocity with better overall performance in both road and air. The three-dimensional standard k-omega turbulence model has been used for capturing the intrinsic flow physics during the take off phase. In the numerical study, a fully implicit finite volume scheme of the compressible, Reynolds-Averaged, Navier-Stokes equations is employed. Through the detailed parametric analytical studies we have conjectured that Ferrari F430 flying car facilitated with high wings having three different deployment histories during the take off phase is the best choice for accomplishing its better performance for the commercial applications.

Keywords: aerodynamics of flying car, air taxi, negative lift, roadable airplane

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