Search results for: input shaping

Authors: Ricky A. J. Syngkon, Santi Gopal Maji

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Decent work and inclusive economic growth, social development, environmental protection, eradication of poverty and hunger as well as clean water and sanitation are the rudiments of 2030 agenda of sustainable development goals of the United Nations. On the other hand, spirituality is deeply entwined in the fabric of daily lives that helps in shaping attitudes, opinions, and behaviors of common people and ensuring quality of lives and overall sustainable development through protection of environment and natural resources. Mawlynnong, a small village in North-Eastern part of India, is a vivid example of how spirituality influences the development of sense of community leading to upliftment of the economic conditions of the people. Mawlynnong as a small hamlet has been in existence for a couple of centuries and it was acknowledged as the cleanest village of Asia in 2004 by BBC and National Geographic and subsequently endorsed by UNESCO in 2006. Consequently, it has attracted large number of tourists over the years from India and other parts of the world. This paper tries to explore how spirituality leads to a sense of community and the economic benefits for the people. Further, this paper also tries to find out the answer whether such an informal collective effort is sustainable or not for achieving solidarity economy. The study is based on both primary and secondary data collected from the local people and the State Government records. The findings of the study indicate that over the last one and a half decade the tourist footfall has increased to a great extent in Mawlynnong and this has brought about a paradigm shift in the occupational structure of its inhabitants from plantation to service sector particularly tourism and tourism related activities. As a result, from the economic standpoint, it is observed that life is much better off now as compared to before. But from the socio-cultural standpoint, the study finds a drift in terms of the cohesiveness and community bonding which was the hallmark of this village. This drift puts a question mark about the sustainability of such practices and consequently the development of solidarity economy.

Keywords: spirituality, sense of community, economic welfare, solidarity economy, Mawlynnong village

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Authors: Kyugneun Lee, Ikjin Lee

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Parameter estimation with inverse problem often suffers from unfavorable conditions in the real world. Useless data and many input parameters make the problem complicated or insoluble. Data refinement and reformulation of the problem can solve that kind of difficulties. In this research, a method to solve the rank deficient inverse problem is suggested. A multi-physics system which has rank deficiency caused by response correlation is treated. Impeditive information is removed and the problem is reformulated to sequential estimations using Bayesian network (BN) and subset groups. At first, subset grouping of the responses is performed. Feature selection with singular value decomposition (SVD) is used for the grouping. Next, BN inference is used for sequential conditional estimation according to the group hierarchy. Directed acyclic graph (DAG) structure is organized to maximize the estimation ability. Variance ratio of response to noise is used to pairing the estimable parameters by each response.

Keywords: Bayesian network, feature selection, rank deficiency, statistical inverse analysis

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Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

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Authors: Ritesh Joshi, Kishan Fuse, Gopal Zinzala, Nishit Nirmal

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Ti-6Al-4V is a titanium alloy having high strength, low weight and corrosion resistant which is a required characteristic for a material to be used in aerospace industry. Titanium, being a hard alloy is difficult to the machine via conventional methods, so it is a call to use non-conventional processes. In present work, the effects on Ti-6Al-4V by drilling a hole of Ø 6 mm using copper (99%) electrode in Electric Discharge Machining (EDM) process is analyzed. Effect of various input parameters like peak current, pulse-on time and pulse-off time on output parameters viz material removal rate (MRR) and electrode wear rate (EWR) is studied. Multi-objective optimization technique Grey relational analysis is used for process optimization. Experiments are designed using an L9 orthogonal array. ANOVA is used for finding most contributing parameter followed by confirmation tests for validating the results. Improvement of 7.45% in gray relational grade is observed.

Keywords: ANOVA, electric discharge machining, grey relational analysis, Ti-6Al-4V

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Authors: Hong Mengdi, Li Jianan, Ji Fei, Chen Aiting, Wang Qian

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Objective: To overcome the communication barriers that audiologists encounter during cochlear implant mapping, particularly the challenge of eliciting subjective feedback from recipients regarding electrical stimulation, and to enhance the capabilities of existing technologies, we teamed up with software engineers to design an interactive approach for patient-audiologist communication. This approach employs a tablet (PAD) as the interface for a communication and feedback system between patients and audiologists during the mapping process, known as the Cochlear Implant Mapping Assistance System. Methods: Capitalizing on the touchscreen functionality of the PAD, the recipients' subjective feedback during cochlear implant mapping is instantly transmitted to the audiologist's mapping computer. The system acts as a platform for auditory assessment instruments, facilitating immediate evaluation of recipients' post-mapping hearing and speech discrimination capabilities. Furthermore, the system is designed to augment the visual reinforcement audiometry (VRA) process. The system consists of six modules, including three testing projects: loudness testing, hearing threshold testing, and loudness balance testing; two assessment projects: warble tone testing and digit speech testing; and one VRA animation project. It also incorporates speech-to-text and text input display functions tailored to accommodate speech communication difficulties in hearing-impaired individuals, with pre-installed common exchange content between audiologists and recipients. Audiologists can input sentences by selecting options. The system supports switching between Chinese and English versions, suitable for audiologists and recipients who use English, facilitating international application of the system. Results: The Cochlear Implant Mapping Assistance System has been in use for over a year in the Auditory Implant Center of the Department of Otology and Neurotology, Medical Center of Otology and Head & Neck Surgery, Chinese PLA General Hospital, with more than 300 recipients using this mapping system. Currently, the system operates stably, with both audiologists and recipients providing positive feedback, indicating a significant improvement over previous methods. It is particularly well-received by pediatric recipients, significantly enhancing the work efficiency of audiologists and improving the feedback efficiency and accuracy of recipients. The system enhances the comprehensibility for cochlear implant recipients, improves wearing comfort and user experience, facilitates cochlear implant auditory mapping, and increases the collection of previously challenging-to-obtain data during the existing assisted mapping process, such as loudness testing data, electrical stimulation testing data, warble tone testing data, loudness balance testing data, digit speech testing data, and visual reinforcement audiometry testing data. Real-time data recording improves the accuracy of assisted mapping. The interface design is meticulously crafted to accommodate patients of varying ages and cognitive abilities, featuring an intuitive design that allows for effortless, guidance-free use by patients.

Keywords: audiologist, subjective feedback, mapping, cochlear implant

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Authors: M.J. Seddighi, Moradchelleh, M. Keyvan

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The ultimate goal in building a city is to provide pleasant, comfortable and nurturing environment as a context of public life. City environment establishes strong connection with people and their surrounding habitant, acting as relevance in social interactions between citizens itself. Urban environment and appropriate municipal facilities are the only way for proper communication between city and citizens and also citizens themselves.There is a need for complement elements between buildings and constructions to settling city life through which the move, comfort, reactions and anxiety will adjust and reflect the spirit to the city. In the surging development of society, urban’ spaces are encountered evolution, sometimes causing the symbols to fade and waste, and as a result, leading to destroy belongs among humans and their physical liquidate. Houses and living spaces exhibit materialistic reflection of life style. In the other words, way of life makes the symbolic essence of living spaces. In addition, it is of sociocultural factor of lifestyle, consisting the concepts and culture, morality, worldview, and national character. Culture is responsible for some crucial meaningful needs which can be wide because they depend on various causes such as perception and interpretation of believes, philosophy of life, interaction with neighbors and protection against climate and enemies. The bi-lateral relationship between human and nature is the main factor that needs to be properly addressed. It is because of the fact that the approach which is taken against landscape and nature has a pertinent influence on creation and shaping the structure of a house. The first response of human in tackling the environment is to build a “shelter” and place as dwelling. This has been a crucial factor in all time periods. In the proposed study, dwelling in Khorasgan’ Stream, as an area located in one of the important historical city of Iran, has been studied. Khorasgan’ Stream is the basic constituent elements of the present architectural form of Isfahan. The influence of Islamic spiritual culture and neighborhood with the historical elements on the dwelling of the selected location, subsequently on other regions of the town are presented.

Keywords: dwelling, neighborhood, historical, Islamic, architectural elements

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Authors: Kaarthik K., Harshini S., Karthika M., Kripanandhini T.

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Water is an essential part of living organisms. Major water pollution is caused due to contamination of industrial wastewater in the river. The most important step in bringing wastewater contaminants down to levels that are safe for nature is wastewater treatment. The contamination of river water harms both humans who consume it and the aquatic life that lives there. We introduce a new cloud-based industrial IoT paradigm in this work for real-time control and monitoring of wastewater. The proposed system prevents prohibited entry of industrial wastewater into the plant by monitoring temperature, hydrogen power (pH), CO₂ and turbidity factors from the wastewater input that the wastewater treatment facility will process. Real-time sensor values are collected and uploaded to the cloud by the system using an IoT Wi-Fi Module. By doing so, we can prevent the contamination of industrial wastewater entering the river earlier, and the necessary actions will be taken by the users. The proposed system's results are 90% efficient, preventing water pollution due to industry and protecting human lives.

Keywords: sensors, pH, CO₂, temperature, turbidity

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Authors: Saeed Saffar-Heidari

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This article aims to study the recent Iranian national uprising of “Women, Life, Freedom” as a site of memory which renders the political possibility of imagining the post-Islamic futures in Iran. “Women, Life, Freedom” movement in Iran has been arguably the most pervasive social movement since the Islamic Revolution (1979) as it has posed serious issues and conflicts for the present Islamic state in Iran. The core argument of this article, however, is oriented toward the critical role of collective memory as a means of political transition and revolutionary mobilization. “Women, Life, Freedom” movement, among other things, has revitalized the popular binary opposition of pre-1979 and post-1979 Iran through which the Ancien Régime or the pre-1979 era is likely to be interpreted, read, and remembered in terms of present post-1979 cultural and political demands. As remembering involves everyday participation in shaping and reshaping the past through new codes, criteria, and values, it is argued that the presentist refashioning and remembering of the pre-1979 monarchical era has been one of the major facilitatory forces for the on-going revolutionary mobilization in Iran. The construction of the pre-1979 memory and the return of the dynastic specter has played a significant role in revolutionary mobilization as it has provided the protesters with the possible perspectives of post-Islamic regime in Iran. Additionally, the question of compulsory “Hijab” (veiling) as the prime mover of "Women, Life, Freedom” movement in Iran has strongly contributed to the everyday comparative discourse of pre/post 1979 memory. According to this presentist remembering of pre-1979, the Pahlavi dynasty would be conceived as a symbol of modernization, westernization, secularization, and non-compulsory Hijab. While the memory of the pre-revolutionary Iran is genuinely an imaginative as well as a constructed entity that finally culminates in the public condemnation of the very Islamic revolution (1979), it serves the enrichment of the Iranian political imagination as it paves the ways for the revolutionary mobilization and then the overthrowing of the Islamic regime in Iran. This article makes a case for the ways that the public narrative and discourse around the Islamic regime (especially the Islamic Hijab) led to the refashioning of the memory of pre-1979 era and inspired he revolutionary mobilization in Iran.

Keywords: post-islamic, utopias, memory, revolutionary, mobilization, Iran

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Authors: Zayar Phyo, Ei Chaw Htoon

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

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

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Authors: Martha Ndeley, John Ikome

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In this paper, we expand the scope of constraint-directed techniques to deal with the case of transportation schedule with capacity restrictions where the scheduling problem includes alternative activities. That is, not only does the scheduling problem consist of determining when an activity is to be executed, but also determining which set of alternative activities is to be executed at all level of transportation from input to output. Such problems encompass both alternative resource problems and alternative process plan problems. We formulate a constraint-based representation of alternative activities to model problems containing such choices. We then extend existing constraint-directed scheduling heuristic commitment techniques and propagators to reason directly about the fact that an activity does not necessarily have to exist in a final transportation schedule without being completed. Tentative results show that an algorithm using a novel texture-based heuristic commitment technique propagators achieves the best overall performance of the techniques tested.

Keywords: production, transportation, scheduling, integrated

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Authors: Salim Ouchtati, Aissa Belmeguenai, Mouldi Bedda

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In this study, we propose an offline system for the recognition of the fragmented handwritten numeric chains. Firstly, we realized a recognition system of the isolated handwritten digits, in this part; the study is based mainly on the evaluation of neural network performances, trained with the gradient backpropagation algorithm. The used parameters to form the input vector of the neural network are extracted from the binary images of the isolated handwritten digit by several methods: the distribution sequence, sondes application, the Barr features, and the centered moments of the different projections and profiles. Secondly, the study is extended for the reading of the fragmented handwritten numeric chains constituted of a variable number of digits. The vertical projection was used to segment the numeric chain at isolated digits and every digit (or segment) was presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits).

Keywords: features extraction, handwritten numeric chains, image processing, neural networks

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Authors: Nisful Laila, Fatin Fadhilah Hasib, Puji Sucia Sukmaningrum, Achsania Hendratmi

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The purpose of this study is to determine and comparing the level of efficiency of Islamic Banks in Indonesia and United Kingdom during eurozone sovereign debt crisis. This study using a quantitative non-parametric approach with Data Envelopment Analysis (DEA) VRS assumption, and a statistical tool Mann-Whitney U-Test. The samples are 11 Islamic Banks in Indonesia and 4 Islamic Banks in England. This research used mediating approach. Input variable consists of total deposit, asset, and the cost of labour. Output variable consists of financing and profit/loss. This study shows that the efficiency of Islamic Bank in Indonesia and United Kingdom are varied and fluctuated during the observation period. There is no significant different the efficiency performance of Islamic Banks in Indonesia and United Kingdom.

Keywords: data envelopment analysis, efficiency, eurozone crisis, islamic bank

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Authors: M. Karimpour, N. Elkhoury, L. Hitihamillage, S. Moridpour, R. Hesami

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There is a necessity among rail transportation authorities for a superior understanding of the rail track degradation overtime and the factors influencing rail degradation. They need an accurate technique to identify the time when rail tracks fail or need maintenance. In turn, this will help to increase the level of safety and comfort of the passengers and the vehicles as well as improve the cost effectiveness of maintenance activities. An accurate model can play a key role in prediction of the long-term behaviour of railroad tracks. An accurate model can decrease the cost of maintenance. In this research, the rail track degradation is predicted using an autoregressive moving average with exogenous input (ARMAX). An ARMAX has been implemented on Melbourne tram data to estimate the values for the tram track degradation. Gauge values and rail usage in Million Gross Tone (MGT) are the main parameters used in the model. The developed model can accurately predict the future status of the tram tracks.

Keywords: ARMAX, dynamic systems, MGT, prediction, rail degradation

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Authors: Chin-Ho Lin

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This study explores the impact of technical barriers to trade(TBT) on the import value and weight of 54 types of waste products between ASEAN+6 countries and 200 trading partners from 1999–to 2018. By using disaggregated detailed product data and the gravity model, we obtained results demonstrating that implementation of TBT by importing countries is likely to enhance waste trade. After controlling for three combinations of fixed effects, the results remain robust. We consider the quality of waste products by dividing waste products into recyclable and nonrecyclable materials, revealing that imported recyclable waste is more likely to be imported than nonrecyclable waste. When waste trade isregulated by importing countries through TBT implementation, the exporting countries may export relatively valuable waste products, and recyclable waste is of greater economic value because it can be used as an input in other production processes. Finally, developed countries are more likely than developing countries to export waste to the ASEAN+6countries, a finding that supports the waste haven hypothesis.

Keywords: waste trade, ASEAN+6, technical barriers to trade, gravity model, waste haven hypothesis

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

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Authors: Avrokomi Zavitsanou, Spiros Papadopoulos, Theofanis Alexandridis

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This paper presents the research project ‘Colour & Travel’, which is co-funded by the European Union and national resources through the Operational Programme “Competitiveness, Entrepreneurship and Innovation” 2014-2020, under the Single RTDI State Aid Action "RESEARCH - CREATE - INNOVATE". The research project proposes the design of an innovative, playful framework for exploring a variety of travel destinations and creating personalised travel narratives, aiming to entertain, educate, and promote culture and tourism. Gamification of the cultural and touristic environment can enhance its experiential, multi-sensory aspects and broaden the perception of the traveler. The latter's involvement in creating and shaping his personal travel narrations and the possibility of sharing it with others can offer him an alternative, more binding way of getting acquainted with a place. In particular, the paper presents the design of an infrastructure: (a) for the development of interactive travel guides for mobile devices, where sites with specific points of interest will be recommended, with which the user can interact in playful ways and then create his personal travel narratives, (b) for the development of innovative games within virtual reality environment, where the interaction will be offered while the user is moving within the virtual environment; and (c) for an online application where the content will be offered through the browser and the modern 3D imaging technologies (WebGL). The technological products that will be developed within the proposed project can strengthen important sectors of economic and social life, such as trade, tourism, exploitation and promotion of the cultural environment, creative industries, etc. The final applications delivered at the end of the project will guarantee an improved level of service for visitors and will be a useful tool for content creators with increased adaptability, expansibility, and applicability in many regions of Greece and abroad. This paper aims to present the research project by referencing the state of the art and the methodological scheme, ending with a brief reflection on the expected outcome in terms of results.

Keywords: gamification, culture, tourism, AR, VR, applications

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Authors: Huiwu Yu, Xiangyou Li, Xiaoyan Zeng

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Porous spheres have been widely used in many fields due to their attractive features. In this work, an approach for fabricating porous spheres of nanoparticles was presented, in which the nanoparticles were welded together to form micro spheres by simply irradiating the nanoparticles in liquid medium by a picosecond laser. As an example, anatase titanium dioxide was chosen as a typical material on account of its metastability. The structure and morphologies of the products were characterised by X-ray diffraction (XRD), scanning electron microscope (SEM), Raman, and high-resolution transmission electron microscopy (HRTEM), respectively. The results showed that, anatase titanium dioxide micro spheres (2-10 μm) with macroporous (10-100 nm) were prepared from nano-anatase titanium dioxide nanoparticles (10-100 nm). The formation process of polycrystalline anatase titanium dioxide microspheres was investigated with different liquid mediums and the input laser fluences. Thus, this facile laser irradiation approach might provide a way for the fabrication of porous microspheres without phase-transition.

Keywords: titanium dioxide, porous microspheres, picosecond laser, nano-welding

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Authors: Taiwo Hassanat Bawa-Muhammad, Opeoluwa Hope Adegoke

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Introduction: This study aims to examine the knowledge and perceptions of preconception care among healthcare workers in Nigeria, recognizing its crucial role in ensuring safe pregnancies. Despite its significance, awareness of preconception care remains low in the country. The study seeks to assess the understanding of preconception services and identify the barriers that hinder their efficacy. Methods: Through semi-structured interviews, 129 healthcare workers across six states in Nigeria were interviewed between January and March 2023. The interviews explored the healthcare workers' knowledge of preconception care practices, the socio-cultural influences shaping decision-making, and the challenges that limit accessibility and utilization of preconception care services. Results: The findings reveal a limited knowledge of preconception care among healthcare workers, primarily due to inadequate information dissemination within the healthcare system. Additionally, cultural beliefs significantly influence perceptions surrounding preconception care. Furthermore, financial constraints, distance to healthcare facilities, and poor health infrastructure disproportionately restrict access to preconception services, particularly for vulnerable populations. The study also highlights insufficient skills and outdated training among healthcare workers regarding preconception guidance, primarily attributed to limited opportunities for professional development. Discussion: To improve preconception care in Nigeria, comprehensive education programs must be implemented, taking into account the societal influences that shape perceptions and behaviors. These programs should aim to dispel myths and promote evidence-based practices. Additionally, training healthcare workers and integrating preconception care services into primary care settings, with support from religious and community leaders, can help overcome barriers to access. Strategies should prioritize affordability while emphasizing the broader benefits of preconception care beyond fertility concerns alone. Lastly, widespread literacy campaigns utilizing trusted channels are crucial for effectively disseminating information and promoting the adoption of preconception practices in Nigeria.

Keywords: preconception care, knowledge, healthcare workers, Nigeria, barriers, education, training

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Authors: Mary Josephine

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Waste of certain process can be the input source of other sectors in order to reduce environmental pollution. Today there are more and more solid wastes are generated, but only very small amount of those are recycled. So, the threatening of environmental pressure to public health is very serious. The methods considered for the treatment of solid waste are biogas tanks or processing to make animal feed and fertilizer, however, they did not perform well. An alternative approach is growing mushrooms on waste residues. This is regarded as an environmental friendly solution with potential economic benefit. The substrate producers do their best to produce quality substrate at low cost. Apart from other methods, this can be achieved by employing biologically degradable wastes used as the resource material component of the substrate. Mushroom growing is a significant tool for the restoration, replenishment and remediation of Earth’s overburdened ecosphere. One of the rational methods of waste utilization involves locally available wastes. The present study aims to find out the yield of mushroom grown on locally available waste for free and to conserve our environment by recycling wastes.

Keywords: biodegradable, environment, mushroom, remediation

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Authors: A. T. Kuda, J. J. Dayya, A. Jimoh

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This paper investigates the fault detection and Isolation technique of measurement data sets from a three tank system using analytical model-based temporal redundancy which is based on residual generation using parity equations/space approach. It further briefly outlines other approaches of model-based residual generation. The basic idea of parity space residual generation in temporal redundancy is dynamic relationship between sensor outputs and actuator inputs (input-output model). These residuals where then used to detect whether or not the system is faulty and indicate the location of the fault when it is faulty. The method obtains good results by detecting and isolating faults from the considered data sets measurements generated from the system.

Keywords: fault detection, fault isolation, disturbing influences, system failure, parity equation/relation, structured parity equations

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Authors: Mimi Mohaffyza Mohamad, Yee Mei Heong, Nurfirdawati Muhammad Hanafi, Tee Tze Kiong

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This study is conducted to investigate the disparity of between learning styles and cognitive abilities specifically in Vocational Education. Felder and Silverman Learning Styles Model (FSLSM) was applied to measure the students’ learning styles while the content in Building Construction Subject consists; knowledge, skills and problem solving were taken into account in constructing the elements of cognitive abilities. There are four dimension of learning styles proposed by Felder and Silverman intended to capture student learning preferences with regards to processing either active or reflective, perception based on sensing or intuitive, input of information used visual or verbal and understanding information represent with sequential or global learner. The study discovered that students are tending to be visual learners and each type of learner having significant difference whereas cognitive abilities. The finding may help teachers to facilitate students more effectively and to boost the student’s cognitive abilities.

Keywords: learning styles, cognitive abilities, dimension of learning styles, learning preferences

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Authors: Tobias Beyer, Christoph Friedrich

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Modern simulation methodology using finite element models is nowadays a recognized tool for product design/optimization. Likewise, manufacturing process design is increasingly becoming the focus of simulation methodology in order to enable sustainable results based on reduced real-life tests here as well. In this article, two process simulations -radial riveting and roller burnishing- used for mechanical joining of components are explained. In the first step, the required boundary conditions are developed and implemented in the respective simulation models. This is followed by process space validation. With the help of the validated models, the interdependencies of the input parameters are investigated and evaluated by means of sensitivity analyses. Limit case investigations are carried out and evaluated with the aid of the process simulations. Likewise, a comparison of the two joining methods to each other becomes possible.

Keywords: FEM, model-based process development, process simulation, radial riveting, roller burnishing, sensitivity analysis

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Authors: Seyed Hossein Hosseini, Seyed Majid Hashemzadeh

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Solar energy is one of the remarkable renewable energy sources that have particular characteristics such as unlimited, no environmental pollution, and free access. Generally, solar energy can be used in thermal and photovoltaic (PV) types. The cost of installation of the PV system is very high. Additionally, due to dependence on environmental situations such as solar radiation and ambient temperature, electrical power generation of this system is unpredictable and without power electronics devices, there is no guarantee to maximum power delivery at the output of this system. Maximum power point tracking (MPPT) should be used to achieve the maximum power of a PV string. MPPT is one of the essential parts of the PV system which without this section, it would be impossible to reach the maximum amount of the PV string power and high losses are caused in the PV system. One of the noticeable challenges in the problem of MPPT is the partial shading conditions (PSC). In PSC, the output photocurrent of the PV module under the shadow is less than the PV string current. The difference between the mentioned currents passes from the module's internal parallel resistance and creates a large negative voltage across shaded modules. This significant negative voltage damages the PV module under the shadow. This condition is called hot-spot phenomenon. An anti-paralleled diode is inserted across the PV module to prevent the happening of this phenomenon. This diode is known as the bypass diode. Due to the performance of the bypass diode under PSC, the P-V curve of the PV string has several peaks. One of the P-V curve peaks that makes the maximum available power is the global peak. Model-based Global MPPT (GMPPT) methods can estimate the optimal point with higher speed than other GMPPT approaches. Centralized, modular, and interleaved DC-DC converter topologies are the significant structures that can be used for GMPPT at a PV string. there are some problems in the centralized structure such as current mismatch losses at PV sting, loss of power of the shaded modules because of bypassing by bypass diodes under PSC, needing to series connection of many PV modules to reach the desired voltage level. In the modular structure, each PV module is connected to a DC-DC converter. In this structure, by increasing the amount of demanded power from the PV string, the number of DC-DC converters that are used at the PV system will increase. As a result, the cost of the modular structure is very high. We can implement the model-based GMPPT through the multi-input interleaved boost DC-DC converter to increase the power extraction from the PV string and reduce hot-spot and current mismatch error in a PV string under different environmental condition and variable load circumstances. The interleaved boost DC-DC converter has many privileges than other mentioned structures, such as high reliability and efficiency, better regulation of DC voltage at DC link, overcome the notable errors such as module's current mismatch and hot spot phenomenon, and power switches voltage stress reduction.

Keywords: solar energy, photovoltaic systems, interleaved boost converter, maximum power point tracking, model-based method, partial shading conditions

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Authors: Ana Maghfiroh

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Learning a foreign language needs a big effort from the learner itself to make their language ability grows better day by day. Among those, they also need a support from all around them including teacher, friends, as well as activities which support them to speak the language. When those activities developed well as a habit which are done regularly, it will help improving the students’ language competence. It was a qualitative research which aimed to find out and describe some activities implemented in Pesantren Al Mawaddah, Ponorogo, in order to teach the students a foreign language. In collecting the data, the researcher used interview, questionnaire, and documentation. From the study, it was found that Pesantren Al Mawaddah had successfully built the language habit on the students to speak the target language. More than 15 hours a day students were compelled to speak foreign language, Arabic or English, in turn. It aimed to habituate the students to keep in touch with the target language. The habit was developed through daily language activities, such as dawn vocabs giving, dictionary handling, daily language use, speech training and language intensive course, daily language input, and night vocabs memorizing. That habit then developed the students awareness towards the language learned as well as promoted their language mastery.

Keywords: habit, communicative competence, daily language activities, Pesantren

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Authors: Fatih Frank Alparslan

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The aviation industry is at a crucial turning point due to modern technologies, environmental concerns, and changing ways of transporting people and goods globally. The paper examines these challenges and opportunities comprehensively. It emphasizes the role of innovative management and advanced technology in shaping the future of air travel. This study begins with an overview of the current state of the aviation industry, identifying key areas where innovation and technology could be highly beneficial. It explores the latest advancements in airplane design, propulsion, and materials. These technological advancements are shown to enhance aircraft performance and environmental sustainability. The paper also discusses the use of artificial intelligence and machine learning in improving air traffic control, enhancing safety, and making flight operations more efficient. The management of these technologies is critically important. Therefore, the research delves into necessary changes in organization, culture, and operations to support innovation. It proposes a management approach that aligns with these modern technologies, underlining the importance of forward-thinking leaders who collaborate across disciplines and embrace innovative ideas. The paper addresses challenges in adopting these innovations, such as regulatory barriers, the need for industry-wide standards, and the impact of technological changes on jobs and society. It recommends that governments, aviation businesses, and educational institutions collaborate to address these challenges effectively, paving the way for a more innovative and eco-friendly aviation industry. In conclusion, the paper argues that the future of aviation relies on integrating new management practices with innovative technologies. It urges a collective effort to push beyond current capabilities, envisioning an aviation industry that is safer, more efficient, and environmentally responsible. By adopting a broad approach, this research contributes to the ongoing discussion about resolving the complex issues facing today's aviation sector, offering insights and guidance to prepare for future advancements.

Keywords: aviation innovation, technology integration, environmental sustainability, management strategies, multidisciplinary approach

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Authors: Anas H. Aljemely, Jianping Xuan

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Rolling bearing fault diagnosis plays a pivotal issue in the rotating machinery of modern manufacturing. In this research, a raw vibration signal and improved deep learning method for bearing fault diagnosis are proposed. The multi-dimensional scales of raw vibration signals are selected for evaluation condition monitoring system, and the deep learning process has shown its effectiveness in fault diagnosis. In the proposed method, employing an Exponential linear unit (ELU) layer in a convolutional neural network (CNN) that conducts the identical function on positive data, an exponential nonlinearity on negative inputs, and a particular convolutional operation to extract valuable features. The identification results show the improved method has achieved the highest accuracy with a 100-dimensional scale and increase the training and testing speed.

Keywords: bearing fault prognostics, developed CNN model, multiple-scale evaluation, deep learning features

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Authors: Rodrigo S. Fonseca, Antônio C. P. Veiga

Abstract:

Aiming at helping people with some movement limitation that makes typing and communication difficult, there is a need to customize an assistive tool with a learning environment that helps the user in order to optimize text input, identifying the error and providing the correction and possibilities of choice in the Portuguese language. The work presents an Orthographic and Grammatical System that can be incorporated into writing environments, improving and facilitating the use of an alphanumeric keyboard, using a prototype built using a genetic algorithm in addition to carrying out the prediction, which can occur based on the quantity and position of the inserted letters and even placement in the sentence, ensuring the sequence of ideas using a Long Short Term Memory (LSTM) neural network. The prototype optimizes data entry, being a component of assistive technology for the textual formulation, detecting errors, seeking solutions and informing the user of accurate predictions quickly and effectively through machine learning.

Keywords: genetic algorithm, neural networks, word prediction, machine learning

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Authors: Hamed Saremi, Shahla Saremi

Abstract:

In this study, control and management of construction projects is evaluated through developing a dynamic model in which some means are used in order to evaluating planning assumptions and reviewing the effectiveness of some project control policies based on previous researches about time, cost, project schedule pressure management, source management, project control, adding elements and sub-systems from cost management such as estimating consumption budget from budget due to costs, budget shortage effects and etc. using sensitivity analysis, researcher has evaluated introduced model that during model simulation by VENSIM software and assuming optimistic times and adding information about doing job and changes rate and project is forecasted with 373 days (2 days sooner than forecasted) and final profit $ 1,960,670 (23% amount of contract) assuming 15% inflation rate in year and costs rate accordance with planned amounts and other input information and final profit.

Keywords: dynamic planning, cost, time, performance, project management

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Authors: Aadityaa Singla

Abstract:

The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

Procedia PDF Downloads 147

Authors: Ammar Alali, Mahmoud Abughaban

Abstract:

Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

Procedia PDF Downloads 232