Search results for: marketing communication tools internet

Authors: S. Jagadeesh Kumar

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This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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Authors: Mehdi Naserian, Mohammad Jooshaki, Mahmud Fotuhi-Firuzabad, Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee

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In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a recent solution is presented to uncover consumers with high air conditioner demand among large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.

Keywords: communication infrastructure, smart meters, power systems, HVAC system, residential HVAC systems

Procedia PDF Downloads 44

Authors: A. El Hamdouni, J. Zbitou, A. Tajmouati, L. El Abdellaoui, A. Errkik, A. Tribak, M. Latrach

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This paper presents a novel fractal antenna structure proposed for UWB (Ultra – Wideband) applications. The frequency band 3.1-10.6 GHz released by FCC (Federal Communication Commission) as the commercial operation of UWB has been chosen as frequency range for this antenna based on coplanar waveguide (CPW) feed and circular shapes fulfilled according to fractal geometry. The proposed antenna is validated and designed by using an FR4 substrate with overall area of 34 x 43 mm2. The simulated results performed by CST-Microwave Studio and compared by ADS (Advanced Design System) show good matching input impedance with return loss less than -10 dB between 2.9 GHz and 11 GHz.

Keywords: Fractal antenna, Fractal Geometry, CPW Feed, UWB, FCC

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Authors: Jin Ho Kim, Yujeong Shin, Seong-Jin Cho, Dong-Jin Kim, U-Syn Ha

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Due to the development of the information industry and technologies, cellular phones have must not only function to communicate, but also have functions such as the Internet, e-banking, entertainment, etc. These phones are called smartphones. The performance of smartphones has improved, because of the various functions of smartphones, and the capacity of the battery has been increased gradually. Recently, linear generators have been embedded in smartphones in order to recharge the smartphone's battery. In this study, optimization is performed and an array change of permanent magnets is examined in order to increase efficiency. We propose an optimal design using design of experiments (DOE) to maximize the generated induced voltage. The thickness of the poleshoe and permanent magnet (PM), the height of the poleshoe and PM, and the thickness of the coil are determined to be design variables. We made 25 sampling points using an orthogonal array according to four design variables. We performed electromagnetic finite element analysis to predict the generated induced voltage using the commercial electromagnetic analysis software ANSYS Maxwell. Then, we made an approximate model using the Kriging algorithm, and derived optimal values of the design variables using an evolutionary algorithm. The commercial optimization software PIAnO (Process Integration, Automation, and Optimization) was used with these algorithms. The result of the optimization shows that the generated induced voltage is improved.

Keywords: smartphone, linear generator, design of experiment, approximate model, optimal design

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Authors: E. L. Elghazy, A. M. Sanad, M. G. Ghoneim

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Over the past two decades research has shown that fiber reinforced polymers can be efficiently, economically and safely used for strengthening and rehabilitation of reinforced concrete (RC) structures. Designing FRP confined concrete columns requires reliable analytical tools that predict the level of performance and ductility enhancement. A numerical procedure is developed aiming at determining the type and thickness of FRP jacket needed to achieve a certain level of ductility enhancement. The procedure starts with defining the stress strain curve, which is used to obtain moment curvature relationship then displacement ductility ratio of reinforced concrete cross-sections subjected to bending moment and axial force. Three sets of published experimental tests were used to validate the numerical procedure. Comparisons between predicted results obtained by using the proposed procedure and actual results of experimental tests proved the reliability of the proposed procedure.

Keywords: columns, confinement, ductility, FRP, numerical

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Authors: Chuencheewin Yimfuang

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The WIPO copyright treaty (WCT) was established by the World Intellectual Property Organisation (WIPO). This agreement required the contracting nations to provide adequate protection to technological measures to prevent massive copyright infringement in the internet system. Thailand had to implement the anti-circumvention rules into domestic legislation to comply with this international obligation. The purpose of this paper is to critically discuss the legislative standard under the WCT. It also aims to examine the legal development of technological protection measures in Thailand and demonstrate that the scope of prohibitions under the copyright Act 2022 (NO.5) is similar to the Digital Millennium Copyright Act 1998 (DMCA) of the United States (US). It could be found that the anti-circumvention laws of Thailand prohibit the circumvention of access-control technologies, and the regulation on trafficking circumvention devices has been added to the latest version of the Thai Copyright Act. These legislative evolutions have revealed the attempt to reinforce the legal protection of technological measures and copyright holders in order to be in line with global practices. However, the amendment has problems concerning the legal definitions of effective technological measure and the prohibited act of circumvention. The vagueness might affect the scope of protection and the boundary of prohibition. With this aspect, the DMCA will be evaluated and compared to gain guidelines for interpretation and enforcement in Thailand. The lessons and experiences learned from this study might be useful to correct the flaws or at least clarify the ambiguities embodied in Thai copyright legislation.

Keywords: legal development, technological protection measure, circumvention, Thailand

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Moomen Chaari, Wolfgang Ecker, Thomas Kruse, Bogdan-Andrei Tabacaru

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In our daily life, we frequently interact with complex systems which facilitate our mobility, enhance our access to information, and sometimes help us recover from illnesses or diseases. The reliance on these systems is motivated by the established evaluation and assessment procedures which are performed during the different phases of the design and manufacturing flow. Such procedures are aimed to qualify the system’s delivered services with respect to their availability, reliability, safety, and other properties generally referred to as dependability attributes. In this paper, we propose a metamodel based generic characterization of dependability concepts and describe an automation methodology to customize this characterization to different standards and contexts. When integrated in concrete design and verification environments, the proposed methodology promotes the reuse of already available dependability assessment tools and reduces the costs and the efforts required to create consistent and efficient artefacts for fault injection or error simulation.

Keywords: dependability analysis, model-driven development, metamodeling, code generation

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Authors: Penn P. Wu, Jeannie Jo

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Blockchain technology has rapidly gained popularity in industry. This paper attempts to assist academia to answer four questions. First, should community colleges begin offering education to nurture blockchain-literate students for the job market? Second, what are the appropriate topical areas to cover? Third, should it be an individual course? And forth, should it be a technical or management course? This paper starts with identifying the knowledge domains of blockchain technology and the topical areas each domain has, and continues with placing them in appropriate academic territories (Computer Sciences vs. Business) and subjects (programming, management, marketing, and laws), and then develops an evaluation model to determine the appropriate topical area for community colleges to teach. The evaluation is based on seven factors: maturity of technology, impacts on management, real-world applications, subject classification, knowledge prerequisites, textbook readiness, and recommended pedagogies. The evaluation results point to an interesting direction that offering an introductory course is an ideal option to guide students through the learning journey of what blockchain is and how it applies to business. Such an introductory course does not need to engage students in the discussions of mathematics and sciences that make blockchain technologies possible. While it is inevitable to brief technical topics to help students build a solid knowledge foundation of blockchain technologies, community colleges should avoid offering students a course centered on the discussion of developing blockchain applications.

Keywords: blockchain, pedagogies, blockchain technologies, blockchain course, blockchain pedagogies

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Authors: Dung Nguyen, Yu Wei, Eric Henderson

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Analytical tools have been used for decades to assist in the development of forest plans. In 2016, a new decision support system, PRISM, was jointly developed by United States Forest Service (USFS) Northern Region and Colorado State University to support the forest planning process. Prism has a friendly user interface with functionality for database management, model development, data visualization, and sensitivity analysis. The software is tailored for USFS planning, but it is flexible enough to support planning efforts by other forestland owners and managers. Here, the core capability of PRISM and its applications in developing plans for several United States national forests are presented. The strengths of PRISM are also discussed to show its potential of being a preferable tool for managers and experts in the domain of forest management and planning.

Keywords: decision support, forest management, forest plan, graphical user interface, software

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Authors: Yu-Ming Wang, Jia-Hong Jian

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The Internet and digital publication technologies have brought dramatic impacts on how people collect, organize, disseminate, access, store, and use information. More and more governments, schools, and organizations spent huge funds to develop digital libraries. A digital library can be regarded as a web extension of traditional physically libraries. People can search diverse publications, find out the position of knowledge resources, and borrow or buy publications through digital libraries. People can gain knowledge and students or employees can finish their reports by using digital libraries. Since the considerable funds and energy have been invested in implementing digital libraries, it is important to understand the evaluative criteria from the users’ viewpoint in order to enhance user acceptance. This study develops a list of user acceptance criteria for digital libraries. An initial criteria list was developed based on some previously validated instruments related to digital libraries. Data were collected from user experiences of digital libraries. The exploratory factor analysis and confirmatory factor analysis were adopted to purify the criteria list. The reliabilities and validities were tested. After validating the criteria list, a user survey was conducted to collect the comparative importance of criteria. The analytic hierarchy process (AHP) method was utilized to derive the importance of each criterion. The results of this study contribute to an e understanding of the criteria and relative importance that users evaluate for digital libraries.

Keywords: digital library, user acceptance, analytic hierarchy process, factor analysis

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Authors: Josephine K. Mule, Levi Obonyo

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Technology has changed human life over time. The COVID-19 pandemic has altered the work set-up, the school system, the shopping experience, church attendance, and even the way athletes train in Kenya. Although the use of technology to communicate and maintain interactions has been on the rise in the last 30 years, the uptake during the COVID-19 pandemic has been unprecedented. Traditionally, ‘paid’ work has been considered to take place outside the “home house” but COVID-19 has resulted in what is now being referred to as “the world’s largest work-from-home experiment” with up to 43 percent of employees working at least some of the time remotely. This study was conducted on 90 respondents from across remote work set-ups, school systems, merchants and customers of online shopping, church leaders and congregants and athletes, and their coaches. Data were collected by questionnaires and interviews that were conducted online. The data is based on the first three months since the first case of coronavirus was reported in Kenya. This study found that the use of technology is in the center of working remotely with work interactions being propelled on various online platforms including, Zoom, Microsoft Teams, and Google Meet, among others. The school system has also integrated the use of technology, including students defending their thesis/dissertations online and university graduations being conducted virtually. Kenya is known for its long-distance runners, due to the directives to reduce interactions; coaches have taken to providing their athletes with guidance on training on social media using applications such as WhatsApp. More local stores are now offering the shopping online option to their customers. Churches have also felt the brunt of the situation, especially because of the restrictions on crowds resulting in online services becoming more popular in 2020 than ever before. Artists, innovatively have started online musical concerts. The findings indicate that one of the outcomes in the Kenyan society that is evident as a result of the COVID-19 period is a population that is using technology more to communicate and get work done. Vices that have thrived in this season where the use of technology has increased, include the spreading of rumors on social media and cyberbullying. The place of technology seems to have been cemented by demand during this period.

Keywords: communication, coronavirus, COVID-19, Kenya, technology

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Authors: Martina Holenko Dlab, Natasa Hoic-Bozic

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This paper presents an original approach to student and group activity level assessment that relies on certainty factors theory. Activity level is used to represent quantity and continuity of student’s contributions in individual and collaborative e‑learning activities (e‑tivities) and is calculated to assist teachers in assessing quantitative aspects of student's achievements. Calculated activity levels are also used to raise awareness and provide recommendations during the learning process. The proposed approach was implemented within the educational recommender system ELARS and validated using data obtained from e‑tivity realized during a blended learning course. The results showed that the proposed approach can be used to estimate activity level in the context of e-tivities realized using Web 2.0 tools as well as to facilitate the assessment of quantitative aspect of students’ participation in e‑tivities.

Keywords: assessment, ELARS, e-learning, recommender systems, student model

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Authors: Jorge Duarte de Sá

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The appearance of the new media technologies has opened new fields of intervention in architecture creating a new dynamic communication in the relationship between public and space, where are present technological devices that enable a new sensory experience, aesthetic and even spiritual. This connection makes relevant the idea of rehabilitate architectonic spaces with new media technologies such as sacred spaces. This research aims to create a media project integrated in sacred spaces that combine Architecture, Art and New Technologies, exploring new perspectives and different dynamics in space.

Keywords: media, architecture, religious spaces, projections, contemplation

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Authors: Zeradam Yeshiwas, A. Krishnaia

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The aim of this study is to verify the resulting surface roughness of parts formed by the Single-Point Incremental Forming (SPIF) process for an ISO 3574 Drawing Quality Cold Rolled CR2 Steel. The chemical composition of drawing quality Cold Rolled CR2 steel is comprised of 0.12 percent of carbon, 0.5 percent of manganese, 0.035 percent of sulfur, 0.04 percent phosphorous, and the remaining percentage is iron with negligible impurities. The experiments were performed on a 3-axis vertical CNC milling machining center equipped with a tool setup comprising a fixture and forming tools specifically designed and fabricated for the process. The CNC milling machine was used to transfer the tool path code generated in Mastercam 2017 environment into three-dimensional motions by the linear incremental progress of the spindle. The blanks of Drawing Quality Cold Rolled CR2 steel sheets of 1 mm of thickness have been fixed along their periphery by a fixture and hardened high-speed steel (HSS) tools with a hemispherical tip of 8, 10 and 12mm of diameter were employed to fabricate sample parts. To investigate the surface roughness, hyperbolic-cone shape specimens were fabricated based on the chosen experimental design. The effect of process parameters on the surface roughness was studied using three important process parameters, i.e., tool diameter, feed rate, and step depth. In this study, the Taylor-Hobson Surtronic 3+ surface roughness tester profilometer was used to determine the surface roughness of the parts fabricated using the arithmetic mean deviation (Rₐ). In this instrument, a small tip is dragged across a surface while its deflection is recorded. Finally, the optimum process parameters and the main factor affecting surface roughness were found using the Taguchi design of the experiment and ANOVA. A Taguchi experiment design with three factors and three levels for each factor, the standard orthogonal array L9 (3³) was selected for the study using the array selection table. The lowest value of surface roughness is significant for surface roughness improvement. For this objective, the ‘‘smaller-the-better’’ equation was used for the calculation of the S/N ratio. The finishing roughness parameter Ra has been measured for the different process combinations. The arithmetic means deviation (Rₐ) was measured via the experimental design for each combination of the control factors by using Taguchi experimental design. Four roughness measurements were taken for a single component and the average roughness was taken to optimize the surface roughness. The lowest value of Rₐ is very important for surface roughness improvement. For this reason, the ‘‘smaller-the-better’’ Equation was used for the calculation of the S/N ratio. Analysis of the effect of each control factor on the surface roughness was performed with a ‘‘S/N response table’’. Optimum surface roughness was obtained at a feed rate of 1500 mm/min, with a tool radius of 12 mm, and with a step depth of 0.5 mm. The ANOVA result shows that step depth is an essential factor affecting surface roughness (91.1 %).

Keywords: incremental forming, SPIF, drawing quality steel, surface roughness, roughness behavior

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Authors: Kazumasa Kawasaki, Katsuya Fukazawa

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Nickel-based superalloys are an important class of engineering material within the aerospace and power generation, due to their excellent combination of corrosion resistance and mechanical properties, including high-temperature applications Inconel 625 is one of such superalloys and difficult-to-machine material. In cutting of Inconel 625 superalloy with a ball end mill, the problem of adhesive wear often occurs. However, the proper cutting conditions are not known so much because of lack of study examples. In this study, the experiments using ball end mills made of carbide tools were tried to find the best cutting conditions out following qualifications. Using Inconel 625 superalloy as a work material, three kinds of experiment, with the revolution speed of 5000 rpm, 8000 rpm, and 10000 rpm, were performed under dry cutting conditions in feed speed per tooth of 0.045 mm/ tooth, depth of cut of 0.1 mm. As a result, in the case of 8000 rpm, it was successful to cut longest with the least wear.

Keywords: Inconel 625, ball end mill, carbide tool, high speed cutting, tool wear

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Authors: Jamaluddin Abd Rashid, Aris Abdul Rahman

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Mobile phones have become the most popular way to communicate with other individuals and it has created an unspoken social dependency. Making phone calls, instant messaging, playing online games and accessing the Internet are among the features added to a mobile phone, attracting teenagers to spend more hours fixated on their gadgets. As such, this study attempted to examine the frequency of time spent on mobile phones and how this influenced academic performance. A quantitative methodology was applied in this study, where face to face survey through the distribution of questionnaires was facilitated onto a group of 200 secondary school students from the Shah Alam community in Selangor,Malaysia. Both genders, male and females were assessed equally to find out if there exists a correlation between genders when measuring higher or lower frequency of attachment to mobile phones. It can also be seen that 100% correspondents have a mobile phone in their possession. The adolescents uses mobile phones daily, which shows students being somewhat addicted, as they tend to feel that it is necessary to use a mobile phone. The main findings of this research found out that, students that are mobile phone addictive received a lower grade in schools. Mobile phone addiction does affect academic performance negatively. As this study discusses the modern-day phenomenon, it is hoped that the findings and discussion could add to present literary works and help future researchers understand the relationship between mobile phone addiction and academic performance.

Keywords: academic performance, mobile phone addiction, social media, student

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Authors: Matias Micheletto, Rodrigo Santos, Sergio F. Ochoa

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In developing countries, the most roads in rural areas are dirt road. They require frequent maintenance since are affected by erosive events, such as rain or wind, and the transit of heavy-weight trucks and machinery. Early detection of damages on the road condition is a key aspect, since it allows to reduce the main-tenance time and cost, and also the limitations for other vehicles to travel through. Most proposals that help address this problem require the explicit participation of drivers, a permanent internet connection, or important instrumentation in vehicles or roads. These constraints limit the suitability of these proposals when applied into developing regions, like in Latin America. This paper proposes an alternative method, based on unattended crowdsensing, to determine the quality of dirt roads in rural areas. This method involves the use of a mobile application that complements the road condition surveys carried out by organizations in charge of the road network maintenance, giving them early warnings about road areas that could be requiring maintenance. Drivers can also take advantage of the early warnings while they move through these roads. The method was evaluated using information from a public dataset. Although they are preliminary, the results indicate the proposal is potentially suitable to provide awareness about dirt roads condition to drivers, transportation authority and road maintenance companies.

Keywords: dirt roads automatic quality assessment, collaborative system, unattended crowdsensing method, roads quality awareness provision

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Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

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Authors: Lukholo Raxangana

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Fourth Industrial Revolution (4IR)-era teaching offers in-service mathematics teachers opportunities to use blended approaches to engage learners while teaching mathematics. This study explores in-service high school teachers' experiences with a blended teaching approach to mathematics. This qualitative case study involved eight pre-service teachers from four selected schools in the Sedibeng West District of the Gauteng Province. The study used the community of inquiry model as its analytical framework for data analysis. Data collection was through semi-structured interviews and focus-group discussions to explore in-service teachers' experiences with the influence of blended teaching (BT) on learning mathematics. The study results are the impact of load-shedding, benefits of BT, and perceptions of in-service and hindrances of BT. Based on these findings, the study recommends that further research should focus on developing data-free BT tools to assist during load-shedding, regardless of location.

Keywords: bended teaching, teachers, in-service, and mathematics

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Authors: Tasawar Nawaz

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Promotion of socioeconomic justice through redistribution of wealth is one of the most salient features of Islamic economic system. Islamic financial institutions known as Islamic banks are used to implement this in practice under the guidelines of Islamic Shariah law. Islamic banking systems strive to promote and achieve financial inclusion among the society by offering interest-free banking and risk-sharing financing solutions. Shariah-compliant micro finance is one of the most popular financial instruments used by Islamic banks to enhance access to finance. Benevolent loan (or Qard-al-Hassanah) is one of the popular financial tools used by the Islamic banks to promote financial inclusion. This aspect of Islamic banking is empirically examined in this paper with specific reference to firm’s resources, largely defined here as intellectual capital. The paper finds that Islamic banks promote financial inclusion by exploiting available resources especially, the human intellectual capital.

Keywords: financial inclusion, intellectual capital, Qard-al-Hassanah, Islamic banking

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Authors: Lipsa Dash, Gyanendra Sahu

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Intelligence is the cornerstone of humans, and now they have created a counterpart of themselves artificially. Our understanding of the word intelligence is a very perspective based and mostly superior understanding of what we read, write, perceive and understand the adversities around better. A wide range of industrial sectors have also started involving the technology to perceive, reason and act. Similarly, intellectual property is the product of human intelligence and creativity. The World Intellectual Property Organisation is currently working on technology trends across the globe, and AI tops the list in the digital frontier that will have a profound impact on the world, transforming the way we live and work. Coming to Intellectual Property, patents and creations of the AI’s itself have constantly been in question. This paper explores whether AI’s can fit in the flexibilities of Trade Related Intellectual Property Studies and gaps in the existing IP laws or rthere is a need of amendment to include them in the ambit. The researcher also explores the right of AI’s who create things out of their intelligence and whether they could qualify to be legal persons making the other laws applicable on them. Differentiation between AI creations and human creations are explored in the paper, and the need of amendments to determine authorship, ownership, inventorship, protection, and identification of beneficiary for remuneration or even for determining liability. The humans and humanoids are all indulged in matters related to Privacy, and that attracts another constitutional legal issue to be addressed. The authors will be focusing on the legal conundrums of AI, transhumanism, and the Internet of things.

Keywords: artificial intelligence, humanoids, healthcare, privacy, legal conundrums, transhumanism

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Authors: Steven Latré, Frederik Desplentere, Ilya Straumit, Stepan V. Lomov

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A method is proposed in order to create a three-dimensional finite element model representing fibre reinforced insulation materials for the simulation software Siemens NX. VoxTex software, a tool for quantification of µCT images of fibrous materials, is used for the transformation of microtomography images of random fibre reinforced composites into finite element models. An automatic tool was developed to execute the import of the models to the thermal solver module of Siemens NX. The paper describes the numerical tools used for the image quantification and the transformation and illustrates them on several thermal simulations of fibre reinforced insulation blankets filled with low thermal conductive fillers. The calculation of thermal conductivity is validated by comparison with the experimental data.

Keywords: analysis, modelling, thermal, voxel

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Authors: Kai Warsoenke, Maik Mackiewicz

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To achieve a high quality of assembled car body structures, tolerancing is used to ensure a geometric accuracy of the single car body parts. There are two main techniques to determine the required tolerances. The first is tolerance analysis which describes the influence of individually tolerated input values on a required target value. Second is tolerance synthesis to determine the location of individual tolerances to achieve a target value. Both techniques are based on classical statistical methods, which assume certain probability distributions. To ensure competitiveness in both saturated and dynamic markets, production processes in vehicle manufacturing must be flexible and efficient. The dimensional specifications selected for the individual body components and the resulting assemblies have a major influence of the quality of the process. For example, in the manufacturing of forming tools as operating equipment or in the higher level of car body assembly. As part of the metrological process monitoring, manufactured individual parts and assemblies are recorded and the measurement results are stored in databases. They serve as information for the temporary adjustment of the production processes and are interpreted by experts in order to derive suitable adjustments measures. In the production of forming tools, this means that time-consuming and costly changes of the tool surface have to be made, while in the body shop, uncertainties that are difficult to control result in cost-intensive rework. The stored measurement results are not used to intelligently design tolerances in future processes or to support temporary decisions based on real-world geometric data. They offer potential to extend the tolerancing methods through data analysis and machine learning models. The purpose of this paper is to examine real-world measurement data from individual car body components, as well as assemblies, in order to develop an approach for using the data in short-term actions and future projects. For this reason, the measurement data will be analyzed descriptively in the first step in order to characterize their behavior and to determine possible correlations. In the following, a database is created that is suitable for developing machine learning models. The objective is to create an intelligent way to determine the position and number of measurement points as well as the local tolerance range. For this a number of different model types are compared and evaluated. The models with the best result are used to optimize equally distributed measuring points on unknown car body part geometries and to assign tolerance ranges to them. The current results of this investigation are still in progress. However, there are areas of the car body parts which behave more sensitively compared to the overall part and indicate that intelligent tolerancing is useful here in order to design and control preceding and succeeding processes more efficiently.

Keywords: automotive production, machine learning, process optimization, smart tolerancing

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Authors: Vahid Bairami Rad

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Extracting knowledge from spatial data like GIS data is important to reduce the data and extract information. Therefore, the development of new techniques and tools that support the human in transforming data into useful knowledge has been the focus of the relatively new and interdisciplinary research area ‘knowledge discovery in databases’. Thus, we introduce a set of database primitives or basic operations for spatial data mining which are sufficient to express most of the spatial data mining algorithms from the literature. This approach has several advantages. Similar to the relational standard language SQL, the use of standard primitives will speed-up the development of new data mining algorithms and will also make them more portable. We introduced a database-oriented framework for spatial data mining which is based on the concepts of neighborhood graphs and paths. A small set of basic operations on these graphs and paths were defined as database primitives for spatial data mining. Furthermore, techniques to efficiently support the database primitives by a commercial DBMS were presented.

Keywords: spatial data base, knowledge discovery database, data mining, spatial relationship, predictive data mining

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Authors: El Miloudi Djelloul

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The computer network play an important position for practical implementations of the differently system. To implement a system into network above all is needed to know all the configurations, which is responsible to be a part of the system, and to give adequate information and solution in realtime. So if want to implement this system for example in the school or relevant institutions, the first step is to analyze the types of model which is needed to be configured and another important step is to organize the works in the context of devices, as a part of the general system. Often before configuration, as important point is descriptions and documentations from all the works into the respective process, and then to organize in the aspect of problem-solving. The computer network as critic infrastructure is very specific so the paper present the effectiveness solutions in the structured aspect viewed from one side, and another side is, than the paper reflect the positive aspect in the context of modeling and block schema presentations as an better alternative to solve the specific problem because of continually distortions of the system from the line of devices, programs and signals or packed collisions, which are in movement from one computer node to another nodes.

Keywords: local area networks, LANs, block schema presentations, computer network system, computer node, critical infrastructure packed collisions, structural control system representations, computer network, implementations, modeling structural representations, companies, computers, context, control systems, internet, software

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Authors: Melliti Rihab, Zaeid Sonia, Khechine Wiem, Daldoul Amira

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Introduction: Lung cancer is the leading cause of cancer death. Its incidence is increasing, and its prognosis remains pejorative. We present the clinical, pathological, and therapeutic characteristics of bronchopulmonary cancer (BPC) in Tunisia. Methods: Retrospective study including patients followed in the oncology department of the University Hospital of Monastir between April 2014 and December 2021 suffering from lung cancer. Results: These are 117 patients, including 86.3% men and 13.7% women (sex ratio 6.3). The average age was 64 years ± 9 (37-83), with 95.7% being over 50 years old. Patients were smokers in 82% of cases. The clinical signs were dominated by chest pain (27.5%) and dyspnea in 21.1% of cases. In 6 patients, an episode of COVID-19 infection revealed the diagnosis. Half of the patients had a PS between 0 and 1. Small cell lung cancer was present in 18 patients (15.4%). The majority of non small cell lung cancer was of the adenocarcinoma type (68.7%). The diagnosis was late (stage IV) in 62.4% of cases. BPC was metastatic to bone (52%), contralateral lung (25.9%), and brain (27.3%). Patients were oligometastatic in 26% of cases. Surgery and radiotherapy were performed respectively in 14.5% and 23.1% of cases. Three-quarters of the patients had had nutrition (75.2%). The ROS1 mutation was present in 1 patient. PDL-1 expression was >40% in 2 patients. Survival was mean eight months ± 7.4. Conclusion: Lung cancer is diagnosed at a late stage in Tunisia. The lack of molecular study for non-small cell PBC and the lack of marketing authorization for tyrosine kinase inhibitors in Tunisia make the management incomplete.

Keywords: SCLC, NCSLC, ROS1, PDL1

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Authors: Dylan Santos De Pinho, Nabil Ouerhani

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Energy consumption of machine-tools is becoming critical for machine-tool builders and end-users because of economic, ecological and legislation-related reasons. Many machine-tool builders are seeking for solutions that allow the reduction of energy consumption of machine-tools while preserving the same productivity rate and the same quality of machined parts. In this paper, we present the first results of a project conducted jointly by academic and industrial partners to reduce the energy consumption of a Swiss-Type lathe. We employ genetic algorithms to find optimal machining parameters – the set of parameters that lead to the best trade-off between energy consumption, part quality and tool lifetime. Three main machining process parameters are considered in our optimization technique, namely depth of cut, spindle rotation speed and material feed rate. These machining process parameters have been identified as the most influential ones in the configuration of the Swiss-type machining process. A state-of-the-art multi-objective genetic algorithm has been used. The algorithm combines three fitness functions, which are objective functions that permit to evaluate a set of parameters against the three objectives: energy consumption, quality of the machined parts, and tool lifetime. In this paper, we focus on the investigation of the fitness function related to energy consumption. Four different energy consumption related fitness functions have been investigated and compared. The first fitness function refers to the Kienzle cutting force model. The second fitness function uses the Material Removal Rate (RMM) as an indicator of energy consumption. The two other fitness functions are non-deterministic, learning-based functions. One fitness function uses a simple Neural Network to learn the relation between the process parameters and the energy consumption from experimental data. Another fitness function uses Lasso regression to determine the same relation. The goal is, then, to find out which fitness functions predict best the energy consumption of a Swiss-Type machining process for the given set of machining process parameters. Once determined, these functions may be used for optimization purposes – determine the optimal machining process parameters leading to minimum energy consumption. The performance of the four fitness functions has been evaluated. The Tornos DT13 Swiss-Type Lathe has been used to carry out the experiments. A mechanical part including various Swiss-Type machining operations has been selected for the experiments. The evaluation process starts with generating a set of CNC (Computer Numerical Control) programs for machining the part at hand. Each CNC program considers a different set of machining process parameters. During the machining process, the power consumption of the spindle is measured. All collected data are assigned to the appropriate CNC program and thus to the set of machining process parameters. The evaluation approach consists in calculating the correlation between the normalized measured power consumption and the normalized power consumption prediction for each of the four fitness functions. The evaluation shows that the Lasso and Neural Network fitness functions have the highest correlation coefficient with 97%. The fitness function “Material Removal Rate” (MRR) has a correlation coefficient of 90%, whereas the Kienzle-based fitness function has a correlation coefficient of 80%.

Keywords: adaptive machining, genetic algorithms, smart manufacturing, parameters optimization

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Authors: Inayat Ur Rehman, Georgia Sakellari

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Cloud computing has evolved into a vital technology for businesses, offering scalability, flexibility, and cost-effectiveness. However, maintaining high availability and optimal performance in the cloud is crucial for reliable services. This paper explores the significance of cloud monitoring and performance optimization in sustaining the high availability of cloud-based systems. It discusses diverse monitoring tools, techniques, and best practices for continually assessing the health and performance of cloud resources. The paper also delves into performance optimization strategies, including resource allocation, load balancing, and auto-scaling, to ensure efficient resource utilization and responsiveness. Addressing potential challenges in cloud monitoring and optimization, the paper offers insights into data security and privacy considerations. Through this thorough analysis, the paper aims to underscore the importance of cloud monitoring and performance optimization for ensuring a seamless and highly available cloud computing environment.

Keywords: cloud computing, cloud monitoring, performance optimization, high availability

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Authors: Mubeshera Tufail

Abstract:

The purpose of the study was to explore the experiences and challenges faced by teachers and students with Flipped Classroom Instruction (FCI) for an undergraduate course at university level. The Flipped Classroom lesson plan consisted of two components: one was out-of-class component consisting of learning material for reading for students and other was within-class component involving a class quiz, class activity and the feedback/further reading task. Besides, experiences, the research study also covered the adaptations made to improve their experiences with Flipped Classroom during the study. The phenomenological research strategy was used for this research study. The data consisted of weekly reflective journals documented by class teacher and students. The reflective journals were recorded by teacher and students while working in Flipped Classroom for an undergraduate course at university level. The main challenges highlighted by teacher were related to effort and time required for planning, time management and students' guidance for shift of their role from passive to independent learner. The main challenges found in reflective journals of students were personal computers issue, electricity and internet speed issue. It is recommended to adapt to some locally useful lesson planning and classroom management techniques to enhance the effectiveness of Flipped Classroom Instruction in an undergraduate university level course.

Keywords: flipped classroom instruction, undergraduate students, independent learner, technology-integrated classroom

Procedia PDF Downloads 145