Search results for: bare machine computing

Authors: Rupesh S. Gundewar, Kanchan C. Khare

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Runoff contribution from urban areas is generally from manmade structures and few natural contributors. The manmade structures are buildings; roads and other paved areas whereas natural contributors are groundwater and overland flows etc. Runoff alleviation is done by manmade as well as natural storages. Manmade storages are storage tanks or other storage structures such as soakways or soak pits which are more common in western and European countries. Natural storages are catchment slope, infiltration, catchment length, channel rerouting, drainage density, depression storage etc. A literature survey on the manmade and natural storages/inflow has presented percentage contribution of each individually. Sanders et.al. in their research have reported that a vegetation canopy reduces runoff by 7% to 12%. Nassif et el in their research have reported that catchment slope has an impact of 16% on bare standard soil and 24% on grassed soil on rainfall runoff. Infiltration being a pervious/impervious ratio dependent parameter is catchment specific. But a literature survey has presented a range of 15% to 30% loss of rainfall runoff in various catchment study areas. Catchment length and channel rerouting too play a considerable role in reduction of rainfall runoff. Ground infiltration inflow adds to the runoff where the groundwater table is very shallow and soil saturates even in a lower intensity storm. An approximate percent contribution through this inflow and surface inflow contributes to about 2% of total runoff volume. Considering the various contributing factors in runoff it has been observed during a literature survey that integrated modelling approach needs to be considered. The traditional storm water network models are able to predict to a fair/acceptable degree of accuracy provided no interaction with receiving water (river, sea, canal etc), ground infiltration, treatment works etc. are assumed. When such interactions are significant then it becomes difficult to reproduce the actual flood extent using the traditional discrete modelling approach. As a result the correct flooding situation is very rarely addressed accurately. Since the development of spatially distributed hydrologic model the predictions have become more accurate at the cost of requiring more accurate spatial information.The integrated approach provides a greater understanding of performance of the entire catchment. It enables to identify the source of flow in the system, understand how it is conveyed and also its impact on the receiving body. It also confirms important pain points, hydraulic controls and the source of flooding which could not be easily understood with discrete modelling approach. This also enables the decision makers to identify solutions which can be spread throughout the catchment rather than being concentrated at single point where the problem exists. Thus it can be concluded from the literature survey that the representation of urban details can be a key differentiator to the successful understanding of flooding issue. The intent of this study is to accurately predict the runoff from impermeable areas from urban area in India. A representative area has been selected for which data was available and predictions have been made which are corroborated with the actual measured data.

Keywords: runoff, urbanization, impermeable response, flooding

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Authors: Apirak Sombat, Teerapol Saleewong, Poom Kumam, Parin Chaipunya, Wiyada Kumam, Anantachai Padcharoen, Yeol Je Cho, Thana Sutthibutpong

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This research is aimed to study a two-step iteration process defined over a finite family of σ-asymptotically quasi-nonexpansive nonself-mappings. The strong convergence is guaranteed under the framework of Banach spaces with some additional structural properties including strict and uniform convexity, reflexivity, and smoothness assumptions. With similar projection technique for nonself-mapping in Hilbert spaces, we hereby use the generalized projection to construct a point within the corresponding domain. Moreover, we have to introduce the use of duality mapping and its inverse to overcome the unavailability of duality representation that is exploit by Hilbert space theorists. We then apply our results for σ-asymptotically quasi-nonexpansive nonself-mappings to solve for ideal efficiency of vector optimization problems composed of finitely many objective functions. We also showed that the obtained solution from our process is the closest to the origin. Moreover, we also give an illustrative numerical example to support our results.

Keywords: asymptotically quasi-nonexpansive nonself-mapping, strong convergence, fixed point, uniformly convex and uniformly smooth Banach space

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Authors: Ramanpreet Kaur, Upasana Sharma

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The purpose of this paper is to address the challenges facing the water supply for the Machine Learning Database (MLDB) system at the piston foundry plant. In the MLDB system, one main unit, i.e., robotic, is connected by two sub-units. The functioning of the system depends on the robotic and water supply. Lack of water supply causes system failure. The system operates at full capacity with the help of two sub-units. If one sub-unit fails, the system runs at a low capacity. Reliability modeling is performed using semi-Markov processes and regenerative point techniques. Several system effects such as mean time to system failure, availability at full capacity, availability at reduced capacity, busy period for repair and expected number of visits have been achieved. Benefits have been analyzed. The graphical study is designed for a specific case using programming in C++ and MS Excel.

Keywords: MLDB system, robotic, semi-Markov process, regenerative point technique

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Authors: Mehmet Kale, Ramazan Sencan, Sibel Yavru, Ahmet Ak, Nuri Mamak, Sibel Hasırcıoglu, Mesih Kocamuftuoglu, Yakup Yıldırım, Hasbi Sait Saltık

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Bovine Papilloma Virus (BPV)-induced warts can cause mastitis, teat blindness, reduction of milk yield, udder deformities, and a difficulty in getting the teats into the milking machine. Especially, surgical operations cannot be performed in BPV-induced teat warts because of the increased sensitivity of the breast region and small-sized papillomas. Thus, there is a need to find new topical treatment methods. We have developed a pomade for treatment of BPV in cattle. The pomade is consists of lanoline, snakeskin (two special kind of snake), alcohol, vaseline, and ether. Firstly, we determined 46 cattle with teat warts. In the study, BPV antigen was detected in 28 cattle blood samples (61%) by ELISA. The pomade was applied to all BPV infected animals. The regression and recovery of warts were 100% in all animals. We advised using the pomade for treatment of BPV-induced warts in teats.

Keywords: bovine papilloma virus, pomade, teat, udder

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Authors: Sajad Shokohuyar, Mahsa Zomorrodi Anbaji, Saghar Pouyan Shad

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According to fast technology growth, modern banking tries to decrease going to banks’ branches and increase customers’ consent. One of the problems which banks face is securing customer’s password. The banks’ solution is one time password creation system. In this research by adapting from acceptance of technology model theory, assesses factors that are effective on banking in Iran especially in using one time password machine by one of the private banks of Iran customers. The statistical population is all of this bank’s customers who use electronic banking service and one time password technology and the questionnaires were distributed among members of statistical population in 5 selected groups of north, south, center, east and west of Tehran. Findings show that confidential preservation, education, ease of utilization and advertising and informing has positive relations and distinct hardware and age has negative relations.

Keywords: security, electronic banking, one time password, information technology

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Authors: Khenfer-Koummich Fatma, Hendel Fatiha, Mesbahi Larbi

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this paper presents an approach based on Hidden Markov Models (HMM: Hidden Markov Model) using HTK tools. The goal is to create a man-machine interface with a voice recognition system that allows the operator to tele-operate a mentor robot to execute specific tasks as rotate, raise, close, etc. This system should take into account different levels of environmental noise. This approach has been applied to isolated words representing the robot commands spoken in two languages: French and Arabic. The recognition rate obtained is the same in both speeches, Arabic and French in the neutral words. However, there is a slight difference in favor of the Arabic speech when Gaussian white noise is added with a Signal to Noise Ratio (SNR) equal to 30 db, the Arabic speech recognition rate is 69% and 80% for French speech recognition rate. This can be explained by the ability of phonetic context of each speech when the noise is added.

Keywords: voice command, HMM, TIMIT, noise, HTK, Arabic, speech recognition

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Authors: Pavel Zlabek, Vaclav Mentl

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The fatigue crack growth rate evaluation is a basic experimental characteristic when assessment o f the remaining lifetime is needed. Within the repair welding technology project, the crack growth rate at cyclic loading was measured in base and weld metals and in the situation when cracks were initiated in base metal and grew into the weld metal through heat-affected zone and back to the base metal. Two welding technologies were applied and specimens in as-welded state and after heat treatment were tested. Fatigue crack growth rate measurement was performed on CrMoV pressure vessel steel and the tests were performed at room temperature. The crack growth rate was measured on CCT test specimens (see figure) for both the base and weld metals and also in the case of crack subsequent transition through all the weld zones. A 500 kN MTS controlled electro-hydraulic testing machine and Model 632.13C-20 MTS extensometer were used to perform the tests.

Keywords: cracks, fatigue, steels, weldments

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Authors: José Neves, M. Rosário Martins, Fátima Candeias, Diana Ferreira, Sílvia Arantes, Júlio Cruz-Morais, Guida Gomes, Joaquim Macedo, António Abelha, Henrique Vicente

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Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Keywords: artificial neuronal networks, essential oils, knowledge representation and reasoning, logic programming, Schinus molle L., Schinus terebinthifolius Raddi

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Authors: F. L. Bernardo, R. A. S. Zacarias

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The ways to translate are manifold since textual genres undergoing translations are diverse. In this essay, our goal is to give special attention to the literary genre and to the online translation tool Google Translate (GT), widely used either by nonprofessionals or by scholars, in order to show evidence of the indispensability of human wit in a good translation. Our study has its basis on a literary review of prominent authors, with emphasis on translation categories. Also highlighting the issue of polysemous literary translation, we aim to shed light on the translator’s craft and the fallible nature of online translation. To better illustrate these principles, the methodology consisted on performing a comparative analysis involving the original text Moll Flanders by Daniel Defoe in English to its online translation given by GT and to a translation into Brazilian Portuguese performed by a human. We proceeded to identifying and analyzing the degrees of textual equivalence according to the following categories: volume, levels and order. The results have attested the unsuitability in a translation done by a computer connected to the World Wide Web.

Keywords: Google Translator, human translation, literary translation, Moll Flanders

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Authors: LuoJiaoyang, Yu Hongyang

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In this paper, we experimented with a new approach to multimodal identification using RGB, RGB-D and voice data. The multimodal combination of RGB and voice data has been applied in tasks such as emotion recognition and has shown good results and stability, and it is also the same in identity recognition tasks. We believe that the data of different modalities can enhance the effect of the model through mutual reinforcement. We try to increase the three modalities on the basis of the dual modalities and try to improve the effectiveness of the network by increasing the number of modalities. We also implemented the single-modal identification system separately, tested the data of these different modalities under clean and noisy conditions, and compared the performance with the multimodal model. In the process of designing the multimodal model, we tried a variety of different fusion strategies and finally chose the fusion method with the best performance. The experimental results show that the performance of the multimodal system is better than that of the single modality, especially in dealing with noise, and the multimodal system can achieve an average improvement of 5%.

Keywords: multimodal, three modalities, RGB-D, identity verification

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Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

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Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

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Authors: Hikmet Cicek

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Transition metal nitrides are widely used as protective coatings on machine parts and cutting tools to protect the surfaces from abrasion and corrosion for decades. In this study, the ternary TiNbVN thin coatings were produced with closed field unbalanced magnetron sputtering system and their structural, mechanical and fatigue-like (multi-pass scratch test) properties were investigated. Two different substrates (M2 and H13 steels) were used to explore substrates effects. X-Ray diffractometer, scanning electron microscope, and energy dispersive spectroscopy were used for the structural and chemical analysis of the coatings. Nanohardness tests were proceed for mechanical properties. The fatigue-like properties of the coatings obtained from the multi-scratch test under three different cycle passes. The results showed that TiNbVN films have excellent fatigue resistance and the coatings deposited on M2 steel substrate have higher hardness and better fatigue resistance.

Keywords: physical vapor deposition, fatigue, metal nitride, multipass scratch test

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Authors: Shuge Lei, Haonan Hu, Dasheng Sun, Huabin Zhang, Kehong Yuan, Jian Dai, Yan Tong

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It remains challenging to measure reliability from classification results from different machine learning models. This paper proposes a reliable soup optimization algorithm based on the model weight fusion algorithm Model Soup, aiming to improve reliability by using dual-channel reliability as the objective function to fuse a series of weights in the breast ultrasound classification models. Experimental results on breast ultrasound clinical datasets demonstrate that reliable soup significantly enhances the reliability of breast ultrasound image classification tasks. The effectiveness of the proposed approach was verified via multicenter trials. The results from five centers indicate that the reliability optimization algorithm can enhance the reliability of the breast ultrasound image classification model and exhibit low multicenter correlation.

Keywords: breast ultrasound image classification, feature attribution, reliability assessment, reliability optimization

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Authors: Soha A. Bahanshal, Byung G. Kim

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Identification of patients at high risk for hospital readmission is of crucial importance for quality health care and cost reduction. Predicting hospital readmissions among diabetic patients has been of great interest to many researchers and health decision makers. We build a prediction model to predict hospital readmission for diabetic patients within 30 days of discharge. The core of the prediction model is a modified k Nearest Neighbor called Hybrid Fuzzy Weighted k Nearest Neighbor algorithm. The prediction is performed on a patient dataset which consists of more than 70,000 patients with 50 attributes. We applied data preprocessing using different techniques in order to handle data imbalance and to fuzzify the data to suit the prediction algorithm. The model so far achieved classification accuracy of 80% compared to other models that only use k Nearest Neighbor.

Keywords: machine learning, prediction, classification, hybrid fuzzy weighted k-nearest neighbor, diabetic hospital readmission

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Authors: R. B. Patil, B. S. Kothavale, L. Y. Waghmode

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Today, the CNC turning center becomes an important machine tool for manufacturing industry worldwide. However, as the breakdown of a single CNC turning center may result in the production of an entire plant being halted. For this reason, operations and preventive maintenance have to be minimized to ensure availability of the system. Indeed, improving the availability of the CNC turning center as a whole, objectively leads to a substantial reduction in production loss, operating, maintenance and support cost. In this paper, fault tree analysis (FTA) method is used for reliability analysis of CNC turning center. The major faults associated with the system and the causes for the faults are presented graphically. Boolean algebra is used for evaluating fault tree (FT) diagram and for deriving governing reliability model for CNC turning center. Failure data over a period of six years has been collected and used for evaluating the model. Qualitative and quantitative analysis is also carried out to identify critical sub-systems and components of CNC turning center. It is found that, at the end of the warranty period (one year), the reliability of the CNC turning center as a whole is around 0.61628.

Keywords: fault tree analysis (FTA), reliability analysis, risk assessment, hazard analysis

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Authors: Adnan Baig, Ishteeaq Naeem, Saad Mansoor

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The Internet of Things (IoT) gadgets have advanced quickly in recent years, and their use is steadily rising daily. However, cyber-attackers can target these gadgets due to their distributed nature. Additionally, many IoT devices have significant security flaws in their implementation and design, making them vulnerable to security threats. Hence, these threats can cause important data security and privacy loss from a single attack on network devices or systems. Botnets are a significant security risk that can harm the IoT network; hence, sophisticated techniques are required to mitigate the risk. This work uses a machine learning-based method to identify IoT orchestrated by botnets. The proposed technique identifies the net attack by distinguishing between legitimate and malicious traffic. This article proposes a hyperparameter tuning model to improvise the method to improve the accuracy of existing processes. The results demonstrated an improved and more accurate indication of botnet-based cyber-attacks.

Keywords: Internet of Things, Botnet, BoT-IoT dataset, ML techniques

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Authors: Joseph Thomas Eghwerido, Julian I. Mbegbu

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In modelling environment processes, we apply multidisciplinary knowledge to explain, explore and predict the Earth's response to natural human-induced environmental changes. Thus, the analysis of spatial-time ecological and environmental studies, the spatial parameters of interest are always heterogeneous. This often negates the assumption of stationarity. Hence, the dispersion of the transportation of atmospheric pollutants, landscape or topographic effect, weather patterns depends on a good estimate of spatial covariance. The generalized linear mixed model, although linear in the expected value parameters, its likelihood varies nonlinearly as a function of the covariance parameters. As a consequence, computing estimates for a linear mixed model requires the iterative solution of a system of simultaneous nonlinear equations. In other to predict the variables at unsampled locations, we need to know the estimate of the present sampled variables. The geostatistical methods for solving this spatial problem assume covariance stationarity (locally defined covariance) and uniform in space; which is not apparently valid because spatial processes often exhibit nonstationary covariance. Hence, they have globally defined covariance. We shall consider different existing methods of solutions of spatial covariance of a space-time processes at unsampled locations. This stationary covariance changes with locations for multiple time set with some asymptotic properties.

Keywords: parametric, nonstationary, Kernel, Kriging

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Authors: Amarnath M., Ramachandra C. G., H. Chelladurai, P..Sateesh Kumar, K. Santhosh Kumar

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Journal bearings are extensively used sliding contact machine elements to support radial/axial loaded rotors used in various applications viz. automobile crankshaft, turbine propeller shaft, rope conveyer, heavy duty electric motors. The primary reasons for the failures of these bearings include unstable lubricant film, oil degradation, misalignment, etc. This paper describes the results of experimental investigations carried out to detect surface fatigue wear developed on load bearing the contact surfaces of journal bearing. The test bearing was subjected to fatigue load cycles over a period of 600 hours. The vibration signals were acquired from the journal bearing at regular intervals of 100 hrs. These signals were post-processed by using the vibration analysis technique to obtain diagnostic information of wear propagated in the journal-bearing system.

Keywords: fatigue, journal bearing, sound signals, vibration signals, wear

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Authors: Glaoui Hachemi

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In this paper, a scheme based on multi-input multi output Fuzzy Sliding Mode control (MIMO-FSMC) for linear speed regulation of winding system is proposed. Once the uncoupled model of the winding system was obtained, a smooth control function with a threshold was selected to indicate how far away the case was from the sliding surface. nevertheless, this control function depends closely on the higher bound of the uncertainties, which generates overlap. So, this size has to be chosen with broad care to obtain high performances. Usually, the upper bound of uncertainties is difficult to know before motor operation, so, a Fuzzy Sliding Mode controller is investigated to resolve this problem, a simple Fuzzy inference mechanism is used to decrease the chattering phenomenon by simple adjustments. A simulation study is achieved and that the indicate fuzzy sliding mode controllers have great potential for use as an alternative to the conventional sliding mode control.

Keywords: Winding system, induction machine, Mechanical tension, Proportional-integral (PI), sliding mode control, Fuzzy logic

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Authors: B. G. Patel, A. K. Desai, S. G. Shah

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The main of objective of this paper is to develop new measurement technique without touching the object. DIC is advance measurement technique use to measure displacement of particle with very high accuracy. This powerful innovative technique which is used to correlate two image segments to determine the similarity between them. For this study, nine geometrically similar beam specimens of different sizes with (steel fibers and glass fibers) and without fibers were tested under three-point bending in a closed loop servo-controlled machine with crack mouth opening displacement control with a rate of opening of 0.0005 mm/sec. Digital images were captured before loading (unreformed state) and at different instances of loading and were analyzed using correlation techniques to compute the surface displacements, crack opening and sliding displacements, load-point displacement, crack length and crack tip location. It was seen that the CMOD and vertical load-point displacement computed using DIC analysis matches well with those measured experimentally.

Keywords: Digital Image Correlation, fibres, self compacting concrete, size effect

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Authors: Leila Goosen

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The research problem reported on in this paper relates to improving success in Computer Science and Information Technology subjects where students are learning applications, especially when teaching occurs in a distance education context. An investigation was launched in order to address students’ struggles with applications, and improve their assessment in such subjects. Some of the main arguments presented centre on formulating and situating significant concepts within an appropriate conceptual framework. The paper explores the experiences and perceptions of computing instructors, teaching assistants, students and higher education institutions on how they are empowered by using technologies such as myITLab. They also share how they are working with the available features to successfully teach applications to their students. The data collection methodology used is then described. The paper includes discussions on how myITLab empowers instructors, teaching assistants, students and higher education institutions. Conclusions are presented on the way in which this paper could make an original and significant contribution to the promotion and development of knowledge in fields related to successfully teaching applications for student learning, including in a distance education context. The paper thus provides a forum for practitioners to highlight and discuss insights and successes, as well as identify new technical and organisational challenges, lessons and concerns regarding practical activities related to myITLab as an implementation instance of distance education technologies.

Keywords: distance, education, myITLab, technologies

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Authors: Boughedaoui Rachid, Belaidi Idir, Ouali Mohamed

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The formatting by removal of material remains an indispensable means for obtaining different forms of pieces. The objective of this work is to study the influence of parameters of the vibratory regime of the system PTM 'Piece-Tool-Machine, in the case of the machining of the thin pieces on the surface finish. As a first step, an analytical study of essential dynamic models 2D slice will be presented. The stability lobes will be thus obtained. In a second step, a characterization of PTM system will be realized. This system will be instrumented with accelerometric sensors but also a laser vibrometer so as to have the information closer to the cutting area. Dynamometers three components will be used for the analysis of cutting forces. Surface states will be measured and the condition of the cutting edge will be visualized thanks to a binocular microscope coupled to a data acquisition system. This information will allow quantifying the influence of chatter on the dimensional quality of the parts. From lobes stabilities previously determined experimental validation allow for the development a method for detecting of the phenomenon of chatter and so an approach will be proposed.

Keywords: chatter, dynamic, milling, lobe stability

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Authors: Daniel Benson, Yundan Gong, Hannah Kirk

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Advancement in national language processing techniques has led to increased data processing speeds, and reduced the need for cumbersome, manual data processing that is often required when processing data from multilateral organizations for specific purposes. As such, using named entity recognition (NER) modeling and the Organisation of Economically Developed Countries (OECD) Creditor Reporting System database, we present the first geotagged dataset of OECD donor Official Development Assistance (ODA) projects on a global, subnational basis. Our resulting data contains 52,086 ODA projects geocoded to subnational locations across 115 countries, worth a combined $87.9bn. This represents the first global, OECD donor ODA project database with geocoded projects. We use this new data to revisit old questions of how ‘well’ donors allocate ODA to the developing world. This understanding is imperative for policymakers seeking to improve ODA effectiveness.

Keywords: international aid, geocoding, subnational data, natural language processing, machine learning

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Authors: Hussein Moselhy, Islam Salam

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There have been some challenges and problems which hinder the implementation of the e-marketing systems such as the high cost of information systems infrastructure and maintenance as well as their unavailability within the institution. Also, there is no system which supports all programming languages and different platforms. Another problem is the lack of integration between these systems on one hand and the operating systems and different web browsers on the other hand. No system for customer relationship management is established which recognizes their desires and puts them in consideration while performing e-marketing functions is available. Therefore, the service-oriented architecture emerged as one of the most important techniques and methodologies to build systems that integrate with various operating systems and different platforms and other technologies. This technology allows realizing the data exchange among different applications. The service-oriented architecture represents distributed computing concepts to demonstrate its success in achieving the requirements of systems through web services. It also reflects the appropriate design for the services to use different web services in supporting the requirements of business processes and software users. In a service-oriented environment, web services are deployed on the web in the form of independent services to be accessed without knowledge of the nature of the programs and systems with in. This Paper presents a proposal for a new model which contributes to the application of methods and means of e-marketing with the integration of marketing mix elements to improve marketing efficiency (E-MSOA). And apply it in the educational city of one of the Egyptian sector.

Keywords: service-oriented architecture, electronic commerce, virtual retailing, unified modeling language

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Authors: Andrey Khalov

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The rapid proliferation of unstructured data in IT infrastructure management demands innovative approaches for extracting actionable knowledge. This paper presents a framework for ontology-based knowledge extraction that combines relational graph neural networks (R-GNN) with large language models (LLMs). The proposed method leverages the DOLCE framework as the foundational ontology, extending it with concepts from ITSMO for domain-specific applications in IT service management and outsourcing. A key component of this research is the use of transformer-based models, such as DeBERTa-v3-large, for automatic entity and relationship extraction from unstructured texts. Furthermore, the paper explores how transfer learning techniques can be applied to fine-tune large language models (LLaMA) for using to generate synthetic datasets to improve precision in BERT-based entity recognition and ontology alignment. The resulting IT Ontology (ITO) serves as a comprehensive knowledge base that integrates domain-specific insights from ITIL processes, enabling more efficient decision-making. Experimental results demonstrate significant improvements in knowledge extraction and relationship mapping, offering a cutting-edge solution for enhancing cognitive computing in IT service environments.

Keywords: ontology mapping, R-GNN, knowledge extraction, large language models, NER, knowlege graph

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Authors: Kevin Smith

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Publicly traded company in the US are legally obligated to host earnings calls that discuss their most recent financial reports. During these calls, investors are able to ask these companies questions about these financial reports and on the future direction of the company. This paper examines whether common institutional owners use these calls as a way to indirectly signal to companies in their portfolio to not take actions that could hurt the common owner's interests. This paper uses transcripts taken from the earnings calls of the six largest health insurance companies in the US from 2014 to 2019. This data is analyzed using text analysis and sentiment analysis to look for patterns in the statements made by common owners. The analysis found that common owners where more likely to recommend against direct price competition and instead redirect the insurance companies towards more passive actions, like investing in new technologies. This result indicates a mechanism that common owners use to reduce competition in the health insurance market.

Keywords: common ownership, text analysis, sentiment analysis, machine learning

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Authors: Sungyani Tripathy, Atul Desai

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Turbo machinery Frame Foundation is very important for power generation, gas, steam, hydro, geothermal and nuclear power plants. The Turbo machinery Foundation system was simulated in SAP: 2000 software and dynamic response of foundation was analysed. In this paper, the detailed study of turbo machinery foundation with different running speed has considered. The different revolution per minute considered in this study is 4000 rpm, 6000 rpm, 8000 rpm, 1000 rpm and 12000 rpm. The above analysis has been carried out considering Winkler spring soil model, solid finite element modelling and dynamic analysis of Turbo machinery foundations. The comparison of frequency and time periods at various mode shapes are addressed in this study. Current work investigates the effect of damping on the response spectra curve at the foundation top deck, considering the dynamic machine load. It has been found that turbo generator foundation with haunches remains more elastic during seismic action for different running speeds.

Keywords: turbo machinery, SAP: 2000, response spectra, running speeds

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Authors: Aliasghar Baziar, Hassan Masoumi, Alireza Ale Saadi

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The control of the response of electric motors plays a significant role in the damping of transient responses. In this regard, this paper presents a static VAR compensator (SVC) based on a fuzzy logic which is applied to an industrial power network consisting of three phase synchronous, asynchronous and DC motor loads. The speed and acceleration variations of a specific machine are the inputs of the proposed fuzzy logic controller (FLC). In order to verify the effectiveness and proficiency of the proposed Fuzzy Logic based SVC (FLSVC), several non-linear time-domain digital simulation tests are performed. The proposed fuzzy model can properly control the response of electric motors. The results show that the FLSVC is successful to improve the voltage profile significantly over a wide range of operating conditions and disturbances thus improving the overall dynamic performance of the network.

Keywords: fuzzy logic controller, VAR compensator, single cage asynchronous motor, DC motor

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Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

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In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

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Authors: Arezou Javadi

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The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

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