Search results for: engine performance analysis

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: Frank Kuebler, Rolf Steinhilper

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Artificial neural networks (ANN) as well as Design of Experiments (DOE) based regression analysis (RA) are mainly used for modeling of complex systems. Both methodologies are commonly applied in process and quality control of manufacturing processes. Due to the fact that resource efficiency has become a critical concern for manufacturing companies, these models needs to be extended to predict resource-consumption of manufacturing processes. This paper describes an approach to use neural networks as well as DOE based regression analysis for predicting resource consumption of manufacturing processes and gives a comparison of the achievable results based on an industrial case study of a turning process.

Keywords: artificial neural network, design of experiments, regression analysis, resource efficiency, manufacturing process

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Authors: Roberto Cabezas H

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The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

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Authors: Himanshu Pavagadhi, Maunik Jani, S. M. Vyas, Jaymin Ray, Vimal Patel, Piyush Patel, Jignesh P. Raval

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The preparation of pure and Sn-doped cadmium sulfide (CdS) pellets was carried out using a compression technique with a pelletizer. The energy dispersive X-ray (EDX) analysis is used to confirm the purity and stoichiometric ratio of Cd, S, and Sn in the prepared pellets. The surface morphology of the pellets was examined using a scanning electron microscope. Both XRD and Raman scattering spectrum analysis confirmed the doping effect in the CdS pellets. The X-ray diffraction (XRD) analysis confirmed the hexagonal structure and revealed that the grain size decreases with increasing Sn dopant concentration in the parent CdS pellet. The optical properties of the pellets were evaluated by measuring diffuse reflectance using a UV-vis spectrophotometer. The analysis indicated that as the Sn concentration increases in the parent CdS pellet, the optical band gap decreases. This implies that the optical properties of the CdS material are also affected by the Sn dopant.

Keywords: CdS, Sn dopant, UV-Spetrophotometer, XRD

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Authors: Jonardan Koner, Avinash Purandare

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In today’s globalized world international business is a very key area for the country's growth. Some of the strategic areas for holding up a country’s international business to grow are in the areas of connecting Ports, Road Network, and Rail Network. India’s International Business is booming both in Exports as well as Imports. Ports play a very central part in the growth of international trade and ensuring competitive ports is of critical importance. India has a long coastline which is a big asset for the country as it has given the opportunity for development of a large number of major and minor ports which will contribute to the maritime trades’ development. The National Economic Development of India requires a well-functioning seaport system. To know the comparative strength of Indian ports over South-east Asian similar ports, the study is considering the objectives of (I) to identify the key parameters of an international mega container port, (II) to compare the five selected container ports (JNPT, Chennai, Singapore, Dubai, and Colombo Ports) according to user of the ports and iii) to measure the growth of selected five container ports’ throughput over time and their comparison. The study is based on both primary and secondary databases. The linear time trend analysis is done to show the trend in quantum of exports, imports and total goods/services handled by individual ports over the years. The comparative trend analysis is done for the selected five ports of cargo traffic handled in terms of Tonnage (weight) and number of containers (TEU’s). The comparative trend analysis is done between containerized and non-containerized cargo traffic in the five selected five ports. The primary data analysis is done comprising of comparative analysis of factor ratings through bar diagrams, statistical inference of factor ratings for the selected five ports, consolidated comparative line charts of factor rating for the selected five ports, consolidated comparative bar charts of factor ratings of the selected five ports and the distribution of ratings (frequency terms). The linear regression model is used to forecast the container capacities required for JNPT Port and Chennai Port by the year 2030. Multiple regression analysis is carried out to measure the impact of selected 34 explanatory variables on the ‘Overall Performance of the Port’ for each of the selected five ports. The research outcome is of high significance to the stakeholders of Indian container handling ports. Indian container port of JNPT and Chennai are benchmarked against international ports such as Singapore, Dubai, and Colombo Ports which are the competing ports in the neighbouring region. The study has analysed the feedback ratings for the selected 35 factors regarding physical infrastructure and services rendered to the port users. This feedback would provide valuable data for carrying out improvements in the facilities provided to the port users. These installations would help the ports’ users to carry out their work in more efficient manner.

Keywords: throughput, twenty equivalent units, TEUs, cargo traffic, shipping lines, freight forwarders

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Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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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: K. Hema Shankari, R. Thirumalaiselvi, N. V. Balasubramanian

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The present paper addresses to the research in the area of regression testing with emphasis on automated tools as well as prioritization of test cases. The uniqueness of regression testing and its cyclic nature is pointed out. The difference in approach between industry, with business model as basis, and academia, with focus on data mining, is highlighted. Test Metrics are discussed as a prelude to our formula for prioritization; a case study is further discussed to illustrate this methodology. An industrial case study is also described in the paper, where the number of test cases is so large that they have to be grouped as Test Suites. In such situations, a genetic algorithm proposed by us can be used to reconfigure these Test Suites in each cycle of regression testing. The comparison is made between a proprietary tool and an open source tool using the above-mentioned metrics. Our approach is clarified through several tables.

Keywords: APFD metric, genetic algorithm, regression testing, RFT tool, test case prioritization, selenium tool

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Authors: Erdal Akyol, Mutlu Alkan

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Multi criteria decision analysis (MDCA) covers both data and experience. It is very common to solve the problems with many parameters and uncertainties. GIS supported solutions improve and speed up the decision process. Weighted grading as a MDCA method is employed for solving the geotechnical problems. In this study, geotechnical parameters namely soil type; SPT (N) blow number, shear wave velocity (Vs) and depth of underground water level (DUWL) have been engaged in MDCA and GIS. In terms of geotechnical aspects, the settlement suitability of the municipal area was analyzed by the method. MDCA results were compatible with the geotechnical observations and experience. The method can be employed in geotechnical oriented microzoning studies if the criteria are well evaluated.

Keywords: GIS, spatial analysis, multi criteria decision analysis, geotechnics

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Authors: Divya Juneja, Sukhjeet Kaur Matharu

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Purpose: The paper is aimed at identifying the challenging factors experienced by the women entrepreneurs in India in operating their enterprises amidst the challenges posed by the COVID-19 pandemic. Methodology: The sample for the study comprised 396 women entrepreneurs from different regions of India. A purposive sampling technique was adopted for data collection. Data was collected through a self-administered questionnaire. Analysis was performed using the SPSS package for quantitative data analysis. Findings: The results of the study state that entrepreneurial characteristics, resourcefulness, networking, adaptability, and continuity have a positive influence on the resiliency of women entrepreneurs when faced with a crisis situation. Practical Implications: The findings of the study have some important implications for women entrepreneurs, organizations, government, and other institutions extending support to entrepreneurs.

Keywords: women entrepreneurs, analysis, data analysis, positive influence, resiliency

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Authors: Syed Abdul Rehman Khan

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In today’s world, information sharing plays a vital role in successful operations of supply chain; and boost to the profitability of the organizations (end-to-end supply chains). Many researches have been completed over the role of information sharing in supply chain. In this research article, we will investigate the ‘how information sharing can boost profitability & productivity of the organization; for this purpose, we have developed one conceptual model and check to that model through collected data from companies. We sent questionnaire to 369 companies; and will filled form received from 172 firms and the response rate was almost 47%. For the data analysis, we have used Regression in (SPSS software) In the research findings, our all hypothesis has been accepted significantly and due to the information sharing between suppliers and manufacturers ‘quality of material and timely delivery’ increase and also ‘collaboration & trust’ will become more stronger and these all factors will lead to the company’s profitability directly and in-directly. But unfortunately, companies could not avail the all fruitful benefits of information sharing due to the fear of ‘compromise confidentiality or leakage of information’.

Keywords: collaboration, information sharing, risk factor, timely delivery

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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: Renata Kurpiewska-Korbut

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Making an assumption that the use and sharing of data generated in humanitarian action constitute a core function of humanitarian organizations, the paper analyzes the position of the largest Polish humanitarian non-governmental organizations in the humanitarian data ecosystem in Ukraine and their approach to non-personal and personal data management since February of 2022. Both expert interviews and document analysis of non-profit organizations providing a direct response in the Ukrainian crisis context, i.e., the Polish Humanitarian Action, Caritas, Polish Medical Mission, Polish Red Cross, and the Polish Center for International Aid and the applicability of theoretical perspective of contingency theory – with its central point that the context or specific set of conditions determining the way of behavior and the choice of methods of action – help to examine the significance of data complexity and adaptive approach to data management by relief organizations in the humanitarian supply chain network. The purpose of this study is to determine how the existence of well-established and accurate internal procedures and good practices of using and sharing data (including safeguards for sensitive data) by the surveyed organizations with comparable human and technological capabilities are implemented and adjusted to Ukrainian humanitarian settings and data infrastructure. The study also poses a fundamental question of whether this crisis experience will have a determining effect on their future performance. The obtained finding indicate that Polish humanitarian organizations in Ukraine, which have their own unique code of conduct and effective managerial data practices determined by contingencies, have limited influence on improving the situational awareness of other assistance providers in the data ecosystem despite their attempts to undertake interagency work in the area of data sharing.

Keywords: humanitarian data ecosystem, humanitarian data management, polish NGOs, Ukraine

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Authors: Djilani Kobibi Youcef Islam, Hadjeri Samir, Djehaf Mohamed Abdeldjalil

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The Flexible AC Transmission System (FACTS) technology is a new advanced solution that increases the reliability and provides more flexibility, controllability, and stability of a power system. The Unified Power Flow Controller (UPFC), as the most versatile FACTS device for regulating power flow, is able to control respectively transmission line real power, reactive power, and node voltage. The main purpose of this paper is to analyze the effect of the UPFC on the load flow, the power losses, and the voltage stability using NEPLAN software modules, Newton-Raphson load flow is used for the power flow analysis and the modal analysis is used for the study of the voltage stability. The simulation was carried out on the IEEE 14-bus test system.

Keywords: FACTS, load flow, modal analysis, UPFC, voltage stability

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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: Saima Ali, Pathamanathan Rajeev, Imteaz A. Monzur

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In this paper, a brief review of the corrosion mechanism in buried pipe and modes of failure is provided together with the available corrosion models. Moreover, the sensitivity analysis is performed to understand the influence of corrosion model parameters on the remaining life estimation. Further, the probabilistic analysis is performed to propagate the uncertainty in the corrosion model on the estimation of the renaming life of the pipe. Finally, the comparison among the corrosion models on the basis of the remaining life estimation will be provided to improve the renewal plan.

Keywords: corrosion, pit depth, sensitivity analysis, exposure period

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Authors: Chassel T. Paras, Tryxzy Q. Dela Cruz, Ma. Carmela Lousie V. Goingco, Pauline L. Tolentino, Carmela S. Dizon

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In implementing inclusive education, parental involvement is measured to be an irreplaceable contributing factor. Parental involvement is described as an indispensable aspect of the teaching-learning process and has a remarkable effect on the student's academic performance. However, there are still differences in the viewpoints, expectations, and needs of both parents and teachers that are not yet fully conveyed in their relationship; hence, the perceptions of SNED teachers are essential in their collaboration with parents. This qualitative study explored how SNED teachers perceive the roles of parental involvement in the teaching-learning process of students with special needs. To answer this question, one-on-one face-to-face semi-structured interviews with three SNED teachers in a selected public school in Angeles City, Philippines, that offer special needs education services were conducted. The gathered data are then analyzed using Interpretative Phenomenological Analysis (IPA). The results revealed four superordinate themes, which include: (1) roles of parental involvement, (2) parental involvement opportunities, (3) barriers to parental involvement, and (4) parent-teacher collaboration practices. These results indicate that SNED teachers are aware of the roles and importance of parental involvement; however, despite parent-teacher collaboration, there are still barriers that impede parental involvement. Also, SNED teachers acknowledge the big roles of parents as they serve as main figures in the teaching-learning process of their children with special needs. Lastly, these results can be used as input in developing a school-facilitated parenting involvement framework that encompasses the contribution of SNED teachers in planning, developing, and evaluating parental involvement programs, which future researchers can also use in their studies

Keywords: parental involvement, special needs education, teaching-learning process, teachers’ perceptions, special needs education teachers, interpretative phenomenological analysis

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Authors: Abenezer Nigussie

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Strategic control practice is a critical exercise, as it provides a sturdy influence towards firms or production partners to achieve the full implementation of effective predetermined plans. The importance of strategic control in a company is often measured by observing the relationship between strategic management and organizational performance. The conventional philosophy of strategic control in academia and the industry places significant emphasis on the ability to plan and execute initiatives. In contrast, the same emphasis on strategic management has received less attention in the housing industry. Although the pressures of project performance can often obscure the wider social, economic, and professional context in which strategic management is undertaken, it is these broad contextual areas that make strategic control a vital issue for construction businesses. Rapidly changing social and technological issues are creating an informed environment that will appear very different in the coming decades from what is experienced in today’s companies. Construction project activity is not adequately led by strategic management tools; projects are mostly executed through simple plans and schedules. The issues that this thesis addresses and solves involve the successful accompaniment of the construction project process through these strategic management tools. The second important aspect is an evaluation of project activity, which is mostly done through simple economic and technical valuation. However, during this research, effective strategic management tools are evaluated and suggested for the assessment of project activities. The research introduces a study of the current strategic management practices of construction companies and also presents the concept of strategic management and the areas that companies need to address to compete in the global market. A summary of an industry survey is documented along with the historical research that prompted the investigation of these topics with a focus on the implementation of tools. Strategic management is a concept that concerns making decisions and taking corrective actions to achieve the future goals and objectives of a company. The objective of this paper is to review the practice of strategic management in construction companies. Questionnaires were distributed to major construction companies listed under categories of each project capable of specifying the complete expression of strategic management tools. Findings of the research showed that the majority of development companies practice strategic management tools in the process and implementation of each tool.

Keywords: strategic management, management, analysis, project management

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Authors: Inas Kamel, Noor Z. Habib

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Utilizing construction and demolition wastes in hotmix asphalt (HMA) pavement construction can reduce the adverse environmental effect of its inadequate disposal and reduce the pressure of extracting and processing mineral aggregates (MA). This study aims to examine the viability of replacing MA by recycled construction and demolition waste aggregates (RCDWA) in the wearing course of asphaltic concrete (AC) pavements without compromising its loadbearing capacity. The Marshall Method was used to evaluate the performance of AC wearing course specimens by replacing MA by 10%, 20% and 30% RCDWA. Grade 60/70 bitumen was used in the range 3.0-5.5%, with 05% increments, to generate the optimum bitumen content (OBC). From the volumetric analysis and test property curves, the mixture containing 20% RCDWA was chosen as the preferred mix at 5.1% OBC. It possessed a 10% increase in Marshall Stability compared to the reference specimen, containing 100% MA, and a 6% increase in Marshall flow.

Keywords: aggregate, asphaltic concrete, Marshall method, optimum bitumen content, recycled construction and demolition waste

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Authors: S. Jahangir, S. H. I. Jaffery, M. Khan, Z. Zareef, A. Yar, A. Mubashir, S. Butt, L. Ali

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In this work, drilling responses and behavior of MMC was investigated in Al-Mg2Si composites. For the purpose Al-15% wt. Mg2Si, was selected from the hypereutectic region of Al- Mg2Si phase diagram. Based on hardness and tensile strength, drill bit of appropriate material and morphology was selected. The performance of different drill bits of different morphology and material was studied and analysed using experimental data. For theoretical calculations of axial thrust force and required power calculation, material factor “K” was obtained from different data charts and at the same time cutting forces (drilling forces) were practically obtained using a Peizo electric force dynamometer. These results show the role of reinforcement particles on the machinability of MMCs and provide a useful guide for a better control and optimized drilling parameters for the drilling process. Furthermore, in this work, comparison of MMC with non -reinforced Aluminum Alloy regarding drilling operation was also studied.

Keywords: drilling, metal matrix composite (MMC), cutting forces, thrust force

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Authors: Mariam Waheed Mekheimar

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Nascent research is conducted to the advancement of discourse analysis to include different modes as images, sound, and text. The focus of this study will be to elucidate how images are embedded with texts in an audio-visual medium as cinema to send political messages; it also seeks to broaden our understanding of politics beyond a relatively narrow conceptualization of the 'political' through studying non-traditional discourses as the cinematic discourse. The aim herein is to develop a systematic approach to film analysis to capture political meanings in films. The method adopted in this research is Multimodal Discourse Analysis (MDA) focusing on embedding visuals with texts. As today's era is the era of images and that necessitates analyzing images. Drawing on the writings of O'Halloran, Kress and Van Leuween, John Bateman and Janina Wildfeuer, different modalities will be studied to understand how those modes interact in the cinematic discourse. 'People at the top movie' is selected as an example to unravel the political meanings throughout film tackling the cinematic representation of the notion of social justice.

Keywords: Egyptian cinema, multimodal discourse analysis, people at the top, social justice

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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: Veronika Přivřelová

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Well-designed composite steel and concrete structures highlight the good material properties and lower the deficiencies of steel and concrete, in particular they make use of high tensile strength of steel and high stiffness of concrete. The most common composite steel and concrete structure is a simply supported beam, which concrete slab transferring the slab load to a beam is connected to the steel cross-section. The aim of this paper is to find the most adequate numerical model of a simply supported composite beam with the cross-sectional and material parameters based on the results of a processed parametric study and numerical analysis. The paper also evaluates the suitability of using compact concrete with the lightweight aggregates for composite steel and concrete beams. The most adequate numerical model will be used in the resent future to compare the results of laboratory tests.

Keywords: composite beams, high-performance concrete, high-strength steel, lightweight concrete slab, modeling

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Authors: Kriangkrai Maneerat, Chutima Prommak

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Indoor wireless localization systems have played an important role to enhance context-aware services. Determining the position of mobile objects in complex indoor environments, such as those in multi-floor buildings, is very challenging problems. This paper presents an effective floor estimation algorithm, which can accurately determine the floor where mobile objects located. The proposed algorithm is based on the confidence interval of the summation of online Received Signal Strength (RSS) obtained from the IEEE 802.15.4 Wireless Sensor Networks (WSN). We compare the performance of the proposed algorithm with those of other floor estimation algorithms in literature by conducting a real implementation of WSN in our facility. The experimental results and analysis showed that the proposed floor estimation algorithm outperformed the other algorithms and provided highest percentage of floor accuracy up to 100% with 95-percent confidence interval.

Keywords: floor estimation algorithm, floor determination, multi-floor building, indoor wireless systems

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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: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Milica Karadžić

Abstract:

The present study is based on the quantitative structure-activity relationship (QSAR) analysis of eighteen compounds with anti-prion activity. The structures and anti-prion activities (expressed in response units, RU%) of the analyzed compounds are taken from CHEMBL database. In the first step of analysis 85 molecular descriptors were calculated and based on them the hierarchical cluster analysis (HCA) and principal component analysis (PCA) were carried out in order to detect potential significant similarities or dissimilarities among the studied compounds. The calculated molecular descriptors were physicochemical, lipophilicity and ADMET (absorption, distribution, metabolism, excretion and toxicity) descriptors. The first stage of the QSAR analysis was simple linear regression modeling. It resulted in one acceptable model that correlates Henry's law constant with RU% units. The obtained 2D-QSAR model was validated by cross-validation as an internal validation method. The validation procedure confirmed the model’s quality and therefore it can be used for prediction of anti-prion activity. The next stage of the analysis of anti-prion activity will include 3D-QSAR and molecular docking approaches in order to select the most promising compounds in treatment of prion diseases. These results are the part of the project No. 114-451-268/2016-02 financially supported by the Provincial Secretariat for Science and Technological Development of AP Vojvodina.

Keywords: anti-prion activity, chemometrics, molecular modeling, QSAR

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Authors: M. Shoukath Ali, Rajendra Prasad Singh

Abstract:

Game Theory approaches and their application in improving the performance of Wireless Sensor Networks (WSNs) are discussed in this paper. The mathematical modeling and analysis of WSNs may have low success rate due to the complexity of topology, modeling, link quality, etc. However, Game Theory is a field, which can efficiently use to analyze the WSNs. Game Theory is related to applied mathematics that describes and analyzes interactive decision situations. Game theory has the ability to model independent, individual decision makers whose actions affect the surrounding decision makers. The outcome of complex interactions among rational entities can be predicted by a set of analytical tools. However, the rationality demands a stringent observance to a strategy based on measured of perceived results. Researchers are adopting game theory approaches to model and analyze leading wireless communication networking issues, which includes QoS, power control, resource sharing, etc.

Keywords: wireless sensor network, game theory, cooperative game theory, non-cooperative game theory

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