Search results for: state machine

Authors: Stephanie Guerra-Arias, Stephani Nevarez, Calvin Stewart, Rachel Grodsky, Denis Eichorst

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The objective of this study is to describe the framework for optimizing the heat treatment of alkali silicate glasses, to enhance the performance of hermetic seals in extreme environments. When connectors are exposed to elevated temperatures, residual stresses develop due to the mismatch of thermal expansions between the glass, metal pin, and metal shell. Excessive thermal expansion mismatch compromises the reliability of hermetic seals. In this study, a series of heat treatment schedules will be performed on two commercial sealing glasses (one conventional sealing glass and one crystallizable sealing glass) using a design of experiments (DOE) approach. The coefficient of thermal expansion (CTE) will be measured pre- and post-heat treatment using thermomechanical analysis (TMA). Afterwards, the flexural strength of the specimen will be measured using a four-point bend fixture mounted in a static universal testing machine. The measured material properties will be statistically analyzed using MiniTab software to determine which factors of the heat treatment process have a strong correlation to the coefficient of thermal expansion and/or flexural strength. Finally, a heat-treatment will be designed and tested to ensure the optimal performance of the hermetic seals in connectors.

Keywords: glass-ceramics, design of experiment, hermetic connectors, material characterization

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Authors: Mikhail O. Eremin

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Seismic activity around the world is clearly a threat to people's lives, as well as infrastructure and capital construction. It is the instability of the latter to powerful earthquakes that most often causes human casualties. Therefore, during construction it is necessary to take into account the risks of large-scale natural disasters. The task of assessing the risks of natural disasters is one of the most urgent at the present time. The final goal of any study of earthquakes is forecasting. This is especially important for seismically active regions of the planet where earthquakes occur frequently. Gorni Altai is one of such regions. In work, we developed the physical-mathematical model of stress-strain state evolution of loaded geomedium with the purpose of numerical simulation of seismic process accompanying the formation of Chuya-Kuray fault zone Gorni Altay, Russia. We build a structural model on the base of seismotectonic and paleoseismogeological investigations, as well as SRTM-data. Base of mathematical model is the system of equations of solid mechanics which includes the fundamental conservation laws and constitutive equations for elastic (Hooke's law) and inelastic deformation (modified model of Drucker-Prager-Nikolaevskii). An initial stress state of the model correspond to gravitational. Then we simulate an activation of a buried dextral strike-slip paleo-fault located in the basement of the model. We obtain the stages of formation and the structure of Chuya-Kuray fault zone. It is shown that results of numerical simulation are in good agreement with field observations in statistical sense. Simulated seismic process is strongly bound to the faults - lineaments with high degree of inelastic strain localization. Fault zone represents en-echelon system of dextral strike-slips according to the Riedel model. The system of surface lineaments is represented with R-, R'-shear bands, X- and Y-shears, T-fractures. Simulated seismic process obeys the laws of Gutenberg-Richter and Omori. Thus, the model describes a self-similar character of deformation and fracture of rocks and geomedia. We also modified the algorithm of determination of separate slip events in the model due to the features of strain rates dependence vs time.

Keywords: Drucker-Prager model, fault zone, numerical simulation, Riedel bands, seismic process, strike-slip fault

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Authors: M. Jamil Ahmad

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In this paper, the heating/cooling potential of a passive building (mosque) of Prof. K. A. Nizami center for Quranic studies at AMU Aligarh, has been evaluated on the basis of energy balance under quasi-steady state condition by incorporating the effect of ventilation. The study has been carried out for composite climate of Aligarh. The performance of the above mentioned building has been presented in this study. It is observed that the premises of the mosque are cooler than the outside ambient temperature by an average of 2°C and 4°C during the month of March and April respectively. Provision of excellent ventilation, high amount of thermal mass, high ceilings and circulation of cool natural air helps in maintaining an optimal thermal comfort temperature in the passive building.

Keywords: heating/cooling potential, passive building, ambient temperatures

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Authors: Natalia Fontes De Oliveira

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The Canadian author Margaret Atwood deconstructs the tainted dichotomies between women and men by embracing the disorder throughout her dystopias. In Atwood’s The Testaments, nature can be seen as a background to the story as well as a metaphorical expression of the characters’ state of mind, nevertheless, the protagonists’ nature writing portrays conveys a curiosity to the pre-established sanctions of a docile garden, viewing nature as an autonomous entity, especially when they are away from the confinements of Gilead’s regime. The three narrating protagonists, Agnes, Aunt Lydia, and Nicole, use nature writing subversively as a form of rebellion. This paper investigates how the three protagonists narrate nature through an intimist point of view, with sensibility to observe the multiple relationships among humanity, nature, and the impositions of a theocratic ultra conservative patriarchal society.

Keywords: contemporary literature, dystopias, feminism, women’s writing

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Authors: Railly Hugo, Igor Aguilar-Alonso

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Software visualization is a powerful tool for understanding complex software systems. However, current visualization tools often lack features or are difficult to use, limiting their effectiveness. In this paper, we present next-viz, a proposed web-based visualization tool that addresses these challenges. We provide a literature review of existing software visualization techniques and tools and describe the architecture of next-viz in detail. Our proposed tool incorporates state-of-the-art visualization techniques and is designed to be user-friendly and intuitive. We believe next-viz has the potential to advance the field of software visualization significantly.

Keywords: software visualization, literature review, tool proposal, next-viz, web-based, architecture, visualization techniques, user-friendly, intuitive

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Authors: F. Garousi, S. Veres, É. Bódi, S. Várallyay, B. Kovács

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Extracting and determining chlorophyll pigments (chlorophyll a and b) in green leaves are the procedures based on the solvent extraction of pigments in samples using N,N-dimethylformamide as the extractant. In this study, two species of soluble inorganic selenium forms, selenite (Se( IV)) and selenate (Se( VI)) at different concentrations were investigated on maize plants that were growing in nutrient solutions during 2 weeks and at the end of the experiment, amounts of chlorophyll a and b for first and second leaves of maize were measured. In accordance with the results we observed that our regarded Se concentrations in both forms of Se( IV) and Se( VI) were not effective on maize plants’ chlorophyll a and b significantly although high level of 3 mg.kg-1 Se( IV) had negative affect on growth of the samples that had been treated by it but about Se( VI) samples we did not observe this state and our different considered Se( VI) concentrations were not toxic for maize plants.

Keywords: maize, sodium selenate, sodium selenite, chlorophyll a and b

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Authors: Shan Jiang

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China is a country with a distinct cultural system. The Chinese Communist Party (CCP) is the central factor for everything, which naturally includes culture. There are quite a lot of cultural policies in China. The same goes for TV dramas. This paper traces the evolution of Chinese TV drama policy since 1986, examines the realistic situation behind the changes, and explores the structure and role of the government in shaping the process. Using historical documents and media reports, it first analyzes four key time nodes: 1986, 2003, 2012, and 2022. It shows how the policy shifts from restricting private production to opening up to public participation, from imposing one censorship to another, and from promoting some content to restricting some other area. It finds that the policy process is not simply rectilinear but rather wandering between deregulation and strengthening control. Secondly, it divides the policies into "basic" policies that establish the overall layout and more refined "strategic" policies that respond to more refined needs. It argues that the "basic" policy process is caused by China's political, economic, and cultural system reform, and then the "strategic" policy process is affected by more environmental factors, such as the government's follow-up development strategy, industrial development, technological innovation, and specific situations. Thirdly, it analysis the main body of the 104 policies from 2000 to 2021 and puts these subjects into China's power structure and cultural system, revealing that the policy issuers are all under the highest leadership of the Chinese Central Committee. Further, the paper challenges the typical description of Chinese cultural policy, which focuses on state control exclusively, identifies the forces within and outside the system that participate in or affect the policy-making process, and reveals the inter-subjective mechanism of policy change. In conclusion, the paper reveals that China's TV drama policy is under the unified leadership of the Party and the government, which greatly guarantees the consistency of the overall direction of cultural policy, that is, the right to speak firmly in the hands. The forces within the system can sometimes promote policy changes due to common development needs. However, folk discourse is only the object of control: when it breeds a certain amount of industrial space, the government will strengthen control over this space, suppress its potential "adverse effects", and instead provide protection and create conditions for the cultivation and growth of its mainstream discourse. However, the policy combination of basic policy and strategic policy, while having a strong effect and emergency capacity, also inhibits the innovation and diversification of the TV drama market. However, the state's substantial regulation will continue to exist in the future.

Keywords: TV Policy, China, policy process, cultural policy, culture management

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Authors: Gagandeep Kaur, Yadwinder Singh Brar, D. P. Kothari

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The paper has an aggregate analysis of animal dung for converting it into renewable biomass fuel source that could be used to help the Indian state Punjab to meet rising power demand. In Punjab district Bathinda produces over 4567 tonnes of animal dung daily on a renewable basis. The biogas energy potential has been calculated using values for the daily per head animal dung production and total no. of large animals in Bathinda of Punjab. The 379540 no. of animals in district could produce nearly 116918 m3 /day of biogas as renewable energy. By converting this biogas into electric energy could produce 89.8 Gwh energy annually.

Keywords: livestock, animal dung, biogas, renewable energy

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Authors: Mohammed Mesrar, Hamza El Malki, Hamza Mesrar

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In this study, ceramics of (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3 were synthesized through a conventional calcination process (solid-state method) at 1000°C for 4 hours, with x(%) values ranging from 0.0 to 100. Room temperature XRD patterns confirmed the phase formation of the samples. The Rietveld refinement method was employed to verify the morphotropic phase boundary (MPB) at x(%)=16-20. We investigated the average crystallite size and lattice strain using Scherrer's formula and Williamson-Hall (W-H) analysis. SEM image analyses provided additional evidence of the impact of doping on structural growth under low temperatures. Relaxation time extracted from Z″(f) and M″(f) spectra for x(%) = 0.0, 12, 16, 20, and 30 followed the Arrhenius law, revealing the presence of three distinct relaxation mechanisms with varying activation energies. The shoulder response in M″(f) indirectly indicated the existence of highly polarizable entities in the samples, serving as a signature of polar nanoregions (PNRs) within the grains.In this study, ceramics of (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3 were synthesized through a conventional calcination process (solid-state method) at 1000°C for 4 hours, with x(%) values ranging from 0.0 to 100. Room temperature XRD patterns confirmed the phase formation of the samples. The Rietveld refinement method was employed to verify the morphotropic phase boundary (MPB) at x(%)=16-20. We investigated the average crystallite size and lattice strain using Scherrer's formula and Williamson-Hall (W-H) analysis. SEM image analyses provided additional evidence of the impact of doping on structural growth under low temperatures. Relaxation time extracted from Z″(f) and M″(f) spectra for x(%) = 0.0, 12, 16, 20, and 30 followed the Arrhenius law, revealing the presence of three distinct relaxation mechanisms with varying activation energies. The shoulder response in M″(f) indirectly indicated the existence of highly polarizable entities in the samples, serving as a signature of polar nanoregions (PNRs) within the grains.

Keywords: (1-x)(Na0.5Bi0.5)TiO3 x(K0.5 Bi0.5)TiO3, Rietveld refinement, Scanning electron microscopy (SEM), Williamson-Hall plots, charge density distribution, dielectric properties

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Authors: Kunihisa Kakumoto

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“Purpose”: Global environmental issues are now being raised in a global dimension. By predicting sprawl phenomena beyond the limits of nature with algorithms, we can expect to protect our social life within the limits of nature. It turns out that the sustainable state of the planet now consists in maintaining a balance between the capabilities of nature and the possibilities of our social life. The amount of water on earth is finite. Sustainability is therefore highly dependent on water capacity. A certain amount of water is stored in the forest by planting and green space, and the amount of water can be considered in relation to the green space. CO2 is also absorbed by green plants. "Possible measurements and methods": The concept of the solar community has been introduced in technical papers on the occasion of many international conferences. The solar community concept is based on data collected from one solar model house. This algorithmic study simulates the amount of water stored by lush green vegetation. In addition, we calculated and compared the amount of CO2 emissions from the Taiyo Community and the amount of CO2 reduction from greening. Based on the trial calculation results of these solar communities, we are simulating the sustainable state of the earth as an algorithm trial calculation result. We believe that we should also consider the composition of this solar community group using digital technology as control technology. "Conclusion": We consider the solar community as a prototype for finding sustainable conditions for the planet. The role of water is very important as the supply capacity of water is limited. However, the circulation of social life is not constructed according to the mechanism of nature. This simulation trial calculation is explained using the total water supply volume as an example. According to this process, algorithmic calculations consider the total capacity of the water supply and the population and habitable numbers of the area. Green vegetated land is very important to keep enough water. Green vegetation is also very important to maintain CO2 balance. A simulation trial calculation is possible from the relationship between the CO2 emissions of the solar community and the amount of CO2 reduction due to greening. In order to find this total balance and sustainable conditions, the algorithmic simulation calculation takes into account lush vegetation and total water supply. Research to find sustainable conditions is done by simulating an algorithmic model of the solar community as a prototype. In this one prototype example, it's balanced. The activities of our social life must take place within the permissive limits of natural mechanisms. Of course, we aim for a more ideal balance by utilizing auxiliary digital control technology such as AI.

Keywords: solar community, sustainability, prototype, algorithmic simulation

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Authors: Rafał Kamiński, Joel Rech, Philippe Bertrand, Christophe Desrayaud

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Titanium alloys are among the most important material in the aircraft industry, due to its low density, high strength, and corrosion resistance. However, these alloys are considered as difficult to machine because they have poor thermal properties and high reactivity with cutting tools. The Selective Laser Melting (SLM) process becomes even more popular through industry since it enables the design of new complex components, that cannot be manufactured by standard processes. However, the high temperature reached during the melting phase as well as the several rapid heating and cooling phases, due to the movement of the laser, induce complex microstructures. These microstructures differ from conventional equiaxed ones obtained by casting+forging. Parts obtained by SLM have to be machined in order calibrate the dimensions and the surface roughness of functional surfaces. The ball milling technique is widely applied to finish complex shapes. However, the machinability of titanium is strongly influenced by the microstructure. So the objective of this work is to investigate the influence of the SLM process, i.e. microstructure, on the machinability of titanium, compared to conventional forming processes. The machinability is analyzed by measuring surface roughness, cutting forces, cutting tool wear for a range of cutting conditions (depth of cut ap, feed per tooth fz, spindle speed N) in accordance with industrial practices.

Keywords: ball milling, microstructure, surface roughness, titanium

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Authors: Khadija Raissi, Bechir Ben Gouissem

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In this paper, we perform the investigation of some routing protocols in Vehicular Ad-Hoc Network (VANET) context. Indeed, we study the efficiency of protocols like Dynamic Source Routing (DSR), Ad hoc On-demand Distance Vector Routing (AODV), Destination Sequenced Distance Vector (DSDV), Optimized Link State Routing convention (OLSR) and Vehicular Multi-hop algorithm for Stable Clustering (VMASC) in terms of packet delivery ratio (PDR) and throughput. The performance evaluation and comparison between the studied protocols shows that the VMASC is the best protocols regarding fast data transmission and link stability in VANETs. The validation of all results is done by the NS3 simulator.

Keywords: VANET, smart city, AODV, OLSR, DSR, OLSR, VMASC, routing protocols, NS3

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Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

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Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: Matthew C. Best

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Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

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Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using Six Sigma methodologies to improve the surface roughness of a manufactured part produced by the CNC milling machine. It presents a case study where the surface roughness of milled aluminum is required to reduce or eliminate defects and to improve the process capability index C_p and C_pk for a CNC milling process. The six sigma methodology, DMAIC (design, measure, analyze, improve, and control) approach, was applied in this study to improve the process, reduce defects, and ultimately reduce costs. The Taguchi-based six sigma approach was applied to identify the optimized processing parameters that led to the targeted surface roughness specified by our customer. A L₉ orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of feed rate, depth of cut, spindle speed, and surface roughness. The noise factor is the difference between the old cutting tool and the new cutting tool. The confirmation run with the optimal parameters confirmed that the new parameter settings are correct. The new settings also improved the process capability index. The purpose of this study is that the Taguchi–based six sigma approach can be efficiently used to phase out defects and improve the process capability index of the CNC milling process.

Keywords: CNC machining, six sigma, surface roughness, Taguchi methodology

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Authors: Krasimir Ivanov, Dimitar Dimitrov, Tatyana Tabakova, Stefka Kirkova, Anna Stoilova, Violina Angelova

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It has been suggested that nicotine, CO and tar in mainstream smoke are the most important substances and have been judged as the most harmful compounds, responsible for the health hazards of smoking. As nicotine is extremely important for smoking qualities of cigarettes and the tar yield in the tobacco smoke is significantly reduced due to the use of filters with various content and design, the main efforts of cigarettes researchers and manufacturers are related to the search of opportunities for CO content reduction. Highly active ceria supported gold catalyst was prepared by the deposition-precipitation method, and the possibilities for CO oxidation in the synthetic gaseous mixture were evaluated using continuous flow equipment with fixed bed glass reactor at atmospheric pressure. The efficiently of the catalyst in CO oxidation in the real cigarette smoke was examined by a single port, puf-by-puff smoking machine. Quality assessment of smoking using cigarette holder containing catalyst was carried out. It was established that the catalytic activity toward CO oxidation in cigarette smoke rapidly decreases from 70% for the first cigarette to nearly zero for the twentieth cigarette. The present study shows that there are two critical factors which do not permit the successful use of catalysts to reduce the CO content in the mainstream cigarette smoke: (i) significant influence of the processes of adsorption and oxidation on the main characteristics of tobacco products and (ii) rapid deactivation of the catalyst due to the covering of the catalyst’s grains with condensate.

Keywords: cigarette smoke, CO oxidation, gold catalyst, mainstream

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Authors: Ammar Neshati, Elham Hamidi Shishavan

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Statement of Problem: The increase in the use of metal-ceramic restorations and a high prevalence of porcelain chipping entails introducing an alloy which is more compatible with porcelain and which causes a stronger bond between the two. This study is to compare shear bond strength of three base-metal alloys and one noble alloy with the common VMK Master Porcelain. Materials and Method: Three different groups of base-metal alloys (Ni-cr-T3, Super Cast, Verabond) and one group of noble alloy (x-33) were selected. The number of alloys in each group was 15. All the groups went through the casting process and change from wax pattern into metal disks. Then, VMK Master Porcelain was fired on each group. All the specimens were put in the UTM and a shear force was loaded until a fracture occurred. The fracture force was then recorded by the machine. The data was subjected to SPSS Version 16 and One-Way ANOVA was run to compare shear strength between the groups. Furthermore, the groups were compared two by two through running Tukey test. Results: The findings of this study revealed that shear bond strength of Ni-Cr-T3 alloy was higher than the three other alloys (94 Mpa or 330 N). Super Cast alloy had the second greatest shear bond strength (80. 87 Mpa or 283.87 N). Both Verabond (69.66 Mpa or 245 N) and x-33 alloys (66.53 Mpa or 234 N) took the third place. Conclusion: Ni-Cr-T3 with VMK Master Porcelain has the greatest shear bond strength. Therefore, the use of this low-cost alloy is recommended in metal-ceramic restorations.

Keywords: shear bond, base-metal alloy, noble alloy, porcelain

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Authors: P. W. Tsai, W. L. Hong, C. W. Chen, C. Y. Chen

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In this paper, we present a neural network (NN) based approach represent a nonlinear Tagagi-Sugeno (T-S) system. A linear differential inclusion (LDI) state-space representation is utilized to deal with the NN models. Taking advantage of the LDI representation, the stability conditions and controller design are derived for a class of nonlinear structural systems. Moreover, the concept of utilizing the Parallel Particle Swarm Optimization (PPSO) algorithm to solve the common P matrix under the stability criteria is given in this paper.

Keywords: Lyapunov stability, parallel particle swarm optimization, linear differential inclusion, artificial intelligence

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Authors: Sarah Mohammed, Huda Allagany, Ayah Barakat, Muna Elyas

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This paper delves into the history and development of ChatGPT, tracing its evolution from its inception by OpenAI to its current state, and emphasizing its design improvements and strategic partnerships. It also explores the performance and applicability of ChatGPT versions 3.5 and 4 in various contexts, examining its capabilities and limitations in producing accurate and relevant responses. Utilizing a quantitative approach, user satisfaction, speed of response, learning capabilities, and overall utility in academic performance were assessed through surveys and analysis tools. Findings indicate that while ChatGPT generally delivers high accuracy and speed in responses, the need for clarification and more specific user instructions persists. The study highlights the tool's increasing integration across different sectors, showcasing its potential in educational and professional settings.

Keywords: artificial intelligence, chat GPT, analysis, education

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Authors: Okanlawon Simon Ayorinde, Odunjo Oluronke Omolola, Fadamiro Joseph Akinlabi, Adedibu Afolabi Adebgite

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A road is a path established over land, especially prepared way between places for the use of pedestrian, riders, and vehicles: a hard surface built for vehicles to travel on. The social, economic and health importance of roads in any community and nation cannot be underestimated. Roads provide access to properties and they also provide mobility which is ability to transport goods and services from one place to another. In the residential zones of many indigenous cities in Nigeria, roads are usually blocked for social ceremonies. Road blocked for ceremonies as used in this study are a temporary barrier across a road, used to stop or hinder traffic from passing through to the other side. Social ceremonies that could warrant road blockage include marriage, child naming, funeral, celebration of life’s achievement, birthday anniversary etc. These activities are likely to generate environmental hazards and their attendant risks. The assessment of these hazards and risks in residential zones of indigenous cities in Nigeria becomes imperative. The study is focused on Ogbomoso, Oyo State, Nigeria. The town has two local government councils namely Ogbomoso North and Ogbomoso South. Urban tracts that are easy to identify are political wards in the absence of land use segregation, houses numbering and street naming. The wards that had residential having a minimum of 60% of their land use components were surveyed and fifteen out of twenty wards identified in the town were surveyed. The study utilized primary data collected through questionnaire administration The three major road categories (Trunk A-Federal; Trunk B- State; Trunk C-Local) were identified and trunk C-Local roads were purposively selected being the concern of this study because they are the ones often blocked for social activities. The major stakeholders interviewed and the respective sampling methods are residents (random and systematic), social ceremony organizers (purposive), government officials (purposive) and road users namely commercial motorists and commercial motor cyclists (random and incidental). Data analysis was mainly descriptive. Two indices to measure respondents’ perception were developed. These are ‘Hazard Severity Index’ (HSI) and ‘Relative Awareness Index’ (RAI).Thereafter, policy implications and recommendations were provided.

Keywords: road, residential zones, indigenous cities, blocked, social ceremonies

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Authors: Xiaoyan Dai, Hsieh Yisan

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Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.

Keywords: barcode detection, data augmentation, deep learning, image-based processing

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Authors: Parameshwaran Nair

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Filling and packaging lines for bottling of beverages into glass, PET or aluminum containers require specialized expertise and a different configuration of equipment like – Filler, Warmer, Labeller, Crater/Recrater, Shrink Packer, Carton Erector, Carton Sealer, Date Coder, Palletizer, etc. Over the period of time, the packaging industry has evolved from manually operated single station machines to highly automized high-speed lines. Human factor and ergonomics have gained significant consideration in this course of transformation. A pre-requisite for such bottling lines, irrespective of the container type and size, is to be suitable for multi-format applications. It should also be able to handle format changeovers with minimal adjustment. It should have variable capacity and speeds, for providing great flexibility of use in managing accumulation times as a function of production characteristics. In terms of layout as well, it should demonstrate flexibility for operator movement and access to machine areas for maintenance. Packaging technology during the past few decades has risen to these challenges by a series of major breakthroughs interspersed with periods of refinement and improvement. The milestones are many and varied and are described briefly in this paper. In order to have a brief understanding of the human factor and ergonomics in the modern packaging lines, this paper, highlights the various technologies, design considerations and statutory requirements in packaging equipment for different types of containers used in India.

Keywords: human-factor, ergonomics, bottling lines, automized high-speed lines

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Authors: Wajid Mumtaz, Aamir Saeed Malik, Syed Saad Azhar Ali, Mohd Azhar Mohd Yasin

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In this paper, a technique based on electroencephalogram (EEG) analysis is presented, aiming for diagnosing major depressive disorder (MDD) among a potential population of MDD patients and healthy controls. EEG is recognized as a clinical modality during applications such as seizure diagnosis, index for anesthesia, detection of brain death or stroke. However, its usability for psychiatric illnesses such as MDD is less studied. Therefore, in this study, for the sake of diagnosis, 2 groups of study participants were recruited, 1) MDD patients, 2) healthy people as controls. EEG data acquired from both groups were analyzed involving inter-hemispheric asymmetry and composite permutation entropy index (CPEI). To automate the process, derived quantities from EEG were utilized as inputs to classifier such as logistic regression (LR) and support vector machine (SVM). The learning of these classification models was tested with a test dataset. Their learning efficiency is provided as accuracy of classifying MDD patients from controls, their sensitivities and specificities were reported, accordingly (LR =81.7 % and SVM =81.5 %). Based on the results, it is concluded that the derived measures are indicators for diagnosing MDD from a potential population of normal controls. In addition, the results motivate further exploring other measures for the same purpose.

Keywords: major depressive disorder, diagnosis based on EEG, EEG derived features, CPEI, inter-hemispheric asymmetry

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Authors: Mohammadhossein Moghimi, Robert Stone, Pia Rotshtein

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Recording psychological and physiological correlates of human performance within virtual environments and interpreting their impacts on human engagement, ‘immersion’ and related emotional or ‘effective’ states is both academically and technologically challenging. By exposing participants to an effective, real-time (game-like) virtual environment, designed and evaluated in an earlier study, a psychophysiological database containing the EEG, GSR and Heart Rate of 30 male and female gamers, exposed to 10 games, was constructed. Some 174 features were subsequently identified and extracted from a number of windows, with 28 different timing lengths (e.g. 2, 3, 5, etc. seconds). After reducing the number of features to 30, using a feature selection technique, K-Nearest Neighbour (KNN) and Support Vector Machine (SVM) methods were subsequently employed for the classification process. The classifiers categorised the psychophysiological database into four effective clusters (defined based on a 3-dimensional space – valence, arousal and dominance) and eight emotion labels (relaxed, content, happy, excited, angry, afraid, sad, and bored). The KNN and SVM classifiers achieved average cross-validation accuracies of 97.01% (±1.3%) and 92.84% (±3.67%), respectively. However, no significant differences were found in the classification process based on effective clusters or emotion labels.

Keywords: virtual reality, effective computing, effective VR, emotion-based effective physiological database

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Authors: Patricia Jiménez, Rafael Corchuelo

Abstract:

Nowadays the World Wide Web is the most popular source of information that relies on billions of on-line documents. Web mining is used to crawl through these documents, collect the information of interest and process it by applying data mining tools in order to use the gathered information in the best interest of a business, what enables companies to promote theirs. Unfortunately, it is not easy to extract the information a web site provides automatically when it lacks an API that allows to transform the user-friendly data provided in web documents into a structured format that is machine-readable. Rule-based information extractors are the tools intended to extract the information of interest automatically and offer it in a structured format that allow mining tools to process it. However, the performance of an information extractor strongly depends on the search heuristic employed since bad choices regarding how to learn a rule may easily result in loss of effectiveness and/or efficiency. Improving search heuristics regarding efficiency is of uttermost importance in the field of Web Information Extraction since typical datasets are very large. In this paper, we employ an information extractor based on a classical top-down algorithm that uses the so-called Information Gain heuristic introduced by Quinlan and Cameron-Jones. Unfortunately, the Information Gain relies on some well-known problems so we analyse an intuitive alternative, Termini, that is clearly more efficient; we also analyse other proposals in the literature and conclude that none of them outperforms the previous alternative.

Keywords: information extraction, search heuristics, semi-structured documents, web mining.

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Authors: Udaykumar R., M. S. Ganachari

Abstract:

In order to engage community pharmacies in Tuberculosis care, a survey has been conducted in Belgaum city, Karnataka state, India. After the survey divided into two groups one is control group and another one is intervention group. One is dispensing of anti-tuberculosis drugs, and another one is non-availability of anti-tuberculosis drugs. Those community pharmacists who are voluntarily interesting for becoming DOTS (Directly observed treatment short course) provider and RNTCP (Revised national tuberculosis control programme) objectives. Structured training is conducted for community pharmacist who are dispensing anti-tuberculosis drugs. The training module includes record maintaining, reporting to the RNTCP, Medication adherence etc. In case of non-availability of anti-tuberculosis drugs, the district RNTCP has been given training for community pharmacist by providing free of drugs to the community pharmacies. So, community pharmacies can dispense anti-tuberculosis drugs to the patients. The target of this study is Private community pharmacies. A simple random sampling method is used and 550 private community pharmacy shops has been involved in Belgaum city of Karnataka state, India. Significance of the Study: This study mainly focused on training of DOTS (Directly observed treatment short course) to the private community pharmacist. Indian Govt. Considers Private Providers as Assets for TB Control and Care to Achieve National Strategic Plan for TB Elimination 2017-2025. The Govt. has not fully tapped the Potential of Private Pharmacies to Fight TB. Providing DOTS as per patient’s convenience through community DOT Providers with periodic monitoring may reduce the treatment Default. We explore RNTCP objectives interventions that can have directly managed by private community pharmacy shop. Objectives: Survey of anti-tuberculosis drugs in Community pharmacy shop in Belgaum city. Interested community pharmacist who are willing to become DOTS (Directly observed treatment short course) Provider. Major Findings:Most of the community pharmacist are dispensing anti-tuberculosis drugs without having knowledge of DOTS therapy and RNTCP objectives. No community pharmacist is aware of RNTCP and Tuberculosis burden in India. Most of the Pharmacist agreed to come for RNTCP Training module for the community pharmacist. Some of the community pharmacist not dispensing anti-tuberculosis drugs and they agreed to become official DOTS provider. Concluding Statement: Awareness of role of community pharmacist on tuberculosis control and care has been neglected. More than 50% of tuberculosis patients seeking treatments from privatesector. In this study finds the major gap between government and private sector on tuberculosis treatment.

Keywords: community pharmacist, directly observed treatment short course(DOTS), revised national tuberculosis control programme (RNTCP), private pharmacies, anti-tuberculosis drugs

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Authors: Tarek Fatouh, Chehab Elbelehy, Alaa Abdelsalam, Eman Elakkad, Alaa Abdelshafie

Abstract:

This paper aims to explore the possibility of time compression in Engineer to Order production networks. A case study research method is used in a Norwegian shipbuilding project by implementing a value stream mapping lean tool with total cycle time as a unit of analysis. The analysis resulted in demonstrating the time deviations for the planned tasks in one of the processes in the shipbuilding project. So, authors developed a future state map by removing time wastes from value stream process.

Keywords: engineer to order, total cycle time, value stream mapping, shipbuilding

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Authors: Emmanuel Barrantes Chaves, Ernesto Rivera Alvarado

Abstract:

This paper presents a method to enable agents for the Terraria game to evaluate algorithms commonly used in general video game artificial intelligence competitions. The usage of the ‘You Only Look Once’ model in the first layer of the process obtains information from the screen, translating this information into a video game description language known as “Video Game Description Language”; the agents take that as input to make decisions. For this, the state-of-the-art algorithms were tested and compared; Monte Carlo Tree Search and Rolling Horizon Evolutionary; in this case, Rolling Horizon Evolutionary shows a better performance. This approach’s main advantage is that a VGDL beforehand is unnecessary. It will be built on the fly and opens the road for using more games as a framework for AI.

Keywords: AI, MCTS, RHEA, Terraria, VGDL, YOLOv5

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Authors: David Jurado, Carlos Ávila

Abstract:

Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

Procedia PDF Downloads 64