Search results for: learning design

Authors: Venkata Ramanaiah, Shabina Khanam

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Enormous potential for saving energy is available in coal-based sponge iron plants as these are associated with the high percentage of energy wastage per unit sponge iron production. An energy integration option is proposed, in the present paper, to a coal based sponge iron plant of 100 tonnes per day production capacity, being operated in India using SL/RN (Stelco-Lurgi/Republic Steel-National Lead) process. It consists of the rotary kiln, rotary cooler, dust settling chamber, after burning chamber, evaporating cooler, electrostatic precipitator (ESP), wet scrapper and chimney as important equipment. Principles of process integration are used in the proposed option. It accounts for preheating kiln inlet streams like kiln feed and slinger coal up to 170ᴼC using waste gas exiting ESP. Further, kiln outlet stream is cooled from 1020ᴼC to 110ᴼC using kiln air. The working areas in the plant where energy is being lost and can be conserved are identified. Detailed material and energy balances are carried out around the sponge iron plant, and a modified model is developed, to find coal requirement of proposed option, based on hot utility, heat of reactions, kiln feed and air preheating, radiation losses, dolomite decomposition, the heat required to vaporize the coal volatiles, etc. As coal is used as utility and process stream, an iterative approach is used in solution methodology to compute coal consumption. Further, water consumption, operating cost, capital investment, waste gas generation, profit, and payback period of the modification are computed. Along with these, operational aspects of the proposed design are also discussed. To recover and integrate waste heat available in the plant, three gas-solid heat exchangers and four insulated ducts with one FD fan for each are installed additionally. Thus, the proposed option requires total capital investment of $0.84 million. Preheating of kiln feed, slinger coal and kiln air streams reduce coal consumption by 24.63% which in turn reduces waste gas generation by 25.2% in comparison to the existing process. Moreover, 96% reduction in water is also observed, which is the added advantage of the modification. Consequently, total profit is found as $2.06 million/year with payback period of 4.97 months only. The energy efficient factor (EEF), which is the % of the maximum energy that can be saved through design, is found to be 56.7%. Results of the proposed option are also compared with literature and found in good agreement.

Keywords: coal consumption, energy conservation, process integration, sponge iron plant

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Authors: Noor Azwa Azreen Binti Abd. Aziz, Muhamad Zaim Bin Mohd Rozi

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Moving towards the 4th Industrial Revolution, artificial intelligence (AI) is now more popular than ever. This subject is gaining significance every day and is continually expanding, often merging with other fields. Instead of merely being passive observers, there are benefits to understanding modern technology by delving into its inner workings. However, in a world teeming with digital information, the impact of AI on the spread of disinformation has garnered significant attention. The dissemination of inaccurate or misleading information is referred to as misinformation, posing a serious threat to democratic society, public debate, and individual decision-making. This article delves deep into the connection between AI and the dissemination of false information, exploring its potential, risks, and ethical issues as AI technology advances. The rise of AI has ushered in a new era in the dissemination of misinformation as AI-driven technologies are increasingly responsible for curating, recommending, and amplifying information on online platforms. While AI holds the potential to enhance the detection and mitigation of misinformation through natural language processing and machine learning, it also raises concerns about the amplification and propagation of false information. AI-powered deepfake technology, for instance, can generate hyper-realistic videos and audio recordings, making it increasingly challenging to discern fact from fiction.

Keywords: artificial intelligence, digital information, disinformation, ethical issues, misinformation

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Authors: Danilsa Lorduy, Liliana Valle

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Assessment and evaluation are inextricable parts of the teaching learning process. Evaluation practices concerns are gaining popularity among curriculum developers an educational researchers, particularly in Colombian regions where English language is taught as a foreign language EFL. This study addressed one of those issues, which are the unbalanced in –services’ evaluation practices perceived in school classes. They present predominance on the written test among the procedures they use to evaluate; therefore, the purpose of this case study was to explore in-service teachers’ evaluation practices, their beliefs about evaluation and to establish an eventual connection between practices and beliefs. To this end, classroom observations, questionnaires, and a semi structured interview were applied to three in-service English teachers from different schools in a city in Colombia. The findings suggested that teachers’ beliefs indicate a formative inclination and they actually are using a variety of procedures different from test but they seem to have some issues regarding their appropriateness for application Moreover, it was found that teachers’ practices are being influenced by external factors such as school requirements and national policies. It could be concluded that the predominance in using tests is not only elicited by teachers’ beliefs but also by national test results 'Pruebas Saber' and law 115 demanding. It was also suggested that further quantitative research is needed to demonstrate connections between overuse of testing procedures and 'Pruebas Saber' national test.

Keywords: beliefs, evaluation, external factors, national test

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Authors: Mathias Marquardt, Peter Dünow, Sandra Baßler

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The paper describes the use of subspace based identification methods for auto tuning of a state space control system. The plant is an unstable but self balancing transport robot. Because of the unstable character of the process it has to be identified from closed loop input-output data. Based on the identified model a state space controller combined with an observer is calculated. The subspace identification algorithm and the controller design procedure is combined to a auto tuning method. The capability of the approach was verified in a simulation experiments under different process conditions.

Keywords: auto tuning, balanced robot, closed loop identification, subspace identification

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Authors: Nihed Bahria El Asghar, Imen Jouili, Mounir Frikha

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Inter-datacenter transport network is very bandwidth and delay demanding. The data transferred over such a network is also highly QoS-exigent mostly because a huge volume of data should be transported transparently with regard to the application user. To avoid the data transfer failure, a backup path should be reserved. No re-routing delay should be observed. A dedicated 1+1 protection is however not applicable in inter-datacenter transport network because of the huge spare capacity. In this context, we propose a survivable virtual network with minimal backup based on network coding (1 ⊕ 1) and solve it using a modified Dijkstra-based heuristic.

Keywords: network coding, dedicated protection, spare capacity, inter-datacenters transport network

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Authors: Ammar Nimer Natsheh

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Chaos control is used to design a controller that is able to eliminate the chaotic behaviour of nonlinear dynamic systems that experience such phenomena. The paper describes the control of the bifurcation behaviour of a parallel-connected DC-DC buck-boost converter used to provide an interface between energy storage batteries and photovoltaic (PV) arrays as renewable energy sources. The paper presents a delayed feedback control scheme in a module converter comprises two identical buck-boost circuits and operates in the continuous-current conduction mode (CCM). MATLAB/SIMULINK simulation results show the effectiveness and robustness of the scheme.

Keywords: chaos, bifurcation, DC-DC Buck-Boost Converter, Delayed Feedback Control

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Authors: Ben Clapperton, Daniel Stahl, Kimberley Goldsmith, Trudie Chalder

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Chronic fatigue syndrome (CFS) is a condition characterised by chronic disabling fatigue and other symptoms that currently can't be explained by any underlying medical condition. Although clinical trials support the effectiveness of cognitive behaviour therapy (CBT), the success rate for individual patients is modest. Patients vary in their response and little is known which factors predict or moderate treatment outcomes. The aim of the project is to develop a prediction model from baseline characteristics of patients, such as demographics, clinical and psychological variables, which may predict likely treatment outcome and provide guidance for clinical decision making and help clinicians to recommend the best treatment. The project is aimed at identifying subgroups of patients with similar baseline characteristics that are predictive of treatment effects using modern cluster analyses and data mining machine learning algorithms. The characteristics of these groups will then be used to inform the types of individuals who benefit from a specific treatment. In addition, results will provide a better understanding of for whom the treatment works. The suitability of different clustering methods to identify subgroups and their response to different treatments of CFS patients is compared.

Keywords: chronic fatigue syndrome, latent class analysis, prediction modelling, self-organizing maps

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Authors: Raphael Rehmet, Armin Lohrengel, Prof Dr-Ing

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In terms of making machines more silent and convenient, it is necessary to analyze the transmission path of mechanical vibrations and structure-bone noise. A typical solution for the elimination of structure-bone noise would be to simply add stiffeners or additional masses to change the transmission behavior and, thereby, avoid the propagation of vibrations. Another solution could be to use materials with a different damping behavior, such as elastomers, to isolate the machine dynamically. This research approach investigates the damping behavior of additive printed components made from structural steel or titanium, which have been manufactured in the “Laser Powder Bed Fusion“-process. By using the design flexibility which this process comes with, it will be investigated how a local impedance difference will affect the transmission behavior of the specimens.

Keywords: 3D-printed, acoustics, dynamics, impedance

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Authors: H. Pasternak, T. Krausche

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The Porsche Pavilion is an innovative stainless steel construction using the principle, often used in ship and car design, as an advantage for building a light but stiff structure. The Pavilion is a one of a kind and outstanding construction that you can find. It fits right in the existing parts of the Autostadt within the lagoon landscape and was built in only eight months. With its curving lines and exiting bends the structure is an extraordinary work which was designed by Henn architects, Munich. The monocoque has a good balance between material and support structure. The stiffness is achieved by the upper and lower side sheathing plates and the intermediate formers. Also the roof shell has no joints and a smooth surface. The assembling of the structure requires a large time and effort cost due to many welds which are necessary to connect all section to one large shell.

Keywords: construction welding, exhibition building, light steel construction, monocoque

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Authors: Imene Medfouni

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In the context of postcolonial Algeria, language policy, language planning as well as language attitudes have recently stirred up contested debates in higher education system. This linguistic and politically-oriented conflict have constantly created a complex environment for learning. In the light of this observation, English language situates itself at the core of this debate with respects to its international status and potential influences. This presentation is based on ongoing research that aims to gain a better understanding of the introduction of English as a medium of instruction (EMI) in a postcolonial context, marked by multilingualism and language conflict. This research offers interesting insights to critically explore EMI from different perspectives: policy, practices, and attitudes. By means of methodological triangulation, this research integrates a mixed approach, whereby the sources of data triangulation will be elicited from the following methods: classroom observations, document analysis, focus groups, questionnaires and interviews. Preliminary findings suggest that English language might not replace French status in Algerian universities because of the latter strong presence and diffusion within Algerian linguistic landscape.

Keywords: English as a lingua franca, English as a medium of instruction, language policy and planning, multilingualism, postcolonial contexts, World Englishes

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Authors: Kurt S. Candilas

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This expressive critical study is an effort to bring in light new interpretation of Robert Frost poem 'The Road Not Taken' as a reflection of his indecisiveness in life. Specifically, it aims at examining Frost’s inner being, emphasizing his own self and experiences in the poem or text. The study employs the qualitative research design which made use of discourse analysis using the critical theory of expressivism as the main guide. In acquiring the data of the study, the art of historiography is used such as autobiographical and/or biographical notes, sources documents, and web information. In executing the methods involved in this study, it is observed that the poem shows a naturalist implicatures, expressing Frost’s strong feelings and emotions being devoid of free will and a narrow bit of confusions and ambiguities with his indecisions in life.

Keywords: The Road Not Taken, expressivism, indecisiveness, naturalist implicatures

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Authors: Jao Jo-Chi, Chen Yen-Ku, Jaw Twei-Shiun, Chen Po-Chou

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This study aimed to investigate the magnetic resonance (MR) signal enhancement ratio (ER) of contrast-enhanced MR angiography (CE-MRA) in normal rats with gadobenate dimeglumine (Gd-BOPTA) using a clinical 3T scanner and an extremity coil. The relaxivities of Gd-BOPTA with saline only and with 4.5 % human serum albumin (HSA) were also measured. Compared with Gadolinium diethylenetriamine pentaacetic acid (Gd-DTPA), Gd-BOPTA had higher relaxivities. The maximum ER of Aorta (ERa), kidney, liver and muscle with Gd-BOPTA were higher than those with Gd-DTPA. The maximum ERa appeared at 1.2 min and decayed to half at 10 min after Gd-BOPTA injection. This information is helpful for the design of CE-MRA study of rats.

Keywords: contrast-enhanced magnetic resonance angiography, Gd-BOPTA, Gd-DTPA, rat

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Authors: Sy-Wei Lo, Chi-Heng Yu

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A new design of aerostatic thrust bearing is proposed for high static stiffness. The bearing body, which is mead of polymer covered with metallic membrane, is held by a circular ring. Such a support helps form a concave air gap to grasp the air pressure. The polymer body, which can be made rapidly by either injection or molding is able to provide extra damping under dynamic loading. The smooth membrane not only serves as the bearing surface but also protects the polymer body. The restrictor is a capillary inside a silicone tube. It can passively compensate the variation of load by expanding the capillary diameter for more air flux. In the present example, the stiffness soars from 15.85 N/µm of typical bearing to 349.85 N/µm at bearing elevation 9.5 µm; meanwhile the load capacity also enhances from 346.86 N to 704.18 N.

Keywords: aerostatic, bearing, polymer, static stiffness

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Authors: Heba Abdelmotaal, Magdy Abdel-Kader

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Purpose: This study explores whether a firm’s effective political risk management is preventing real and accrual earnings management . Design/methodology/approach: Based on a sample of 130 firms operating in Egypt during the period 2008-2013, two hypotheses are tested using the panel data regression models. Findings: The empirical findings indicate a significant relation between real and accrual earnings management and political risk. Originality/value: This paper provides a statistically evidence on the effects of the political risk management failure on the mangers’ engagement in the real and accrual earnings management practices, and its impact on the firm’s performance.

Keywords: political risk, risk management failure, real activities manipulation, accrual earnings management

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Authors: Mohammad R. Rahim, Shagil Akhtar, Prem K. Bharti, Syed Muneeb Iqbal

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Deformation and energy absorption studies with corrugated tubes where corrugation is perpendicular to the line of action which coincides exactly with the unstrained axis of the tubes. In the present study, several specimens with various geometric parameters are prepared and compressed quasi-statistically in ANSYS Workbench. It is observed that tubes with perpendicular corrugation alters the deformation condition considerably and culminates in a substantial escalation in energy absorption scope in juxtaposed with the tubes having a circular cross-section. This study will help automotive, aerospace and various other industries to design superior components with perpendicular corrugated tubes and will reduce the experimental trials by conducting the numerical simulations.

Keywords: ANSYS Workbench, deformation and energy absorption, corrugated tubes, quasi-static compression

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Authors: K. Biswas, U. H. Armin, S. M. J. Prodhan, J. A. Prithul, S. Sarker, F. Afrin

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Alzheimer’s disease (AD) (a progressive neurodegenerative disorder) is mostly predominant cause of dementia in the elderly. Prolonging the function of acetylcholine by inhibiting both acetylcholinesterase and butyrylcholinesterase is most effective treatment therapy of AD. Traditionally Pterocarpus santalinus L. is widely known for its medicinal use. In this study, in vitro acetylcholinesterase inhibitory activity was investigated and methanolic extract of the plant showed significant activity. To confirm this activity (in vivo), learning and memory enhancing effects were tested in mice. For the test, memory impairment was induced by scopolamine (cholinergic muscarinic receptor antagonist). Anti-amnesic effect of the extract was investigated by the passive avoidance task in mice. The study also includes brain acetylcholinesterase activity. Results proved that scopolamine induced cognitive dysfunction was significantly decreased by administration of the extract solution, in the passive avoidance task and inhibited brain acetylcholinesterase activity. These results suggest that bark extract of Pterocarpus santalinus can be better option for further studies on AD via their acetylcholinesterase inhibitory actions.

Keywords: Pterocarpus santalinus, cholinesterase inhibitor, passive avoidance, Alzheimer’s disease

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Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

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The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: agent, network backup system, three architecture model, NSBS

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Authors: Lucian Vasile Bagiu, Paraschiva Bagiu

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The study is a contrastive essay on language acquisition and learning and follows the outcomes of teaching Romanian language to foreign students both at Lund University, Sweden (from 2014 to 2017) and at '1 Decembrie 1918' University in Alba Iulia, Romania (2017-2018). Having employed the same teaching methodology (on campus, same curricula) for the same level of study (beginners’ level: A1-A2), the essay focuses on the written exam at the end of the semester. The study argues on grammar exercises concerned with: the indefinite and the definite article; the conjugation of verbs in the present indicative; the possessive; verbs in the past tense; the subjunctive; the degrees of comparison for adjectives. Identifying similar errors when solving identical grammar exercises by different groups of foreign students is an opportunity to emphasize the major challenges any foreigner has to face and overcome when trying to acquire Romanian language. The conclusion draws attention to the complexity of the morphology of Romanian language in several key elements which may be insurmountable for a foreign speaker no matter if the language acquisition takes place in a foreign country or a Romanian university.

Keywords: Arab students, morphological errors, Romanian language, Swedish students, written exam

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Authors: Stuti Modi, Aditi Kambli

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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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Authors: Amir Ngah, Masita Abdul Jalil, Zailani Abdullah

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The aim of software maintenance is to maintain the software system in accordance with advancement in software and hardware technology. One of the early works on software maintenance is to extract information at higher level of abstraction. In this paper, we present the process of how to design an information extraction tool for software maintenance. The tool can extract the basic information from old program such as about variables, based classes, derived classes, objects of classes, and functions. The tool have two main part; the lexical analyzer module that can read the input file character by character, and the searching module which is user can get the basic information from existing program. We implemented this tool for a patterned sub-C++ language as an input file.

Keywords: extraction tool, software maintenance, reverse engineering, C++

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Authors: Rudranil Das

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Wrapping is a basic textile technique; it is having a great quality of decorative view. Since long back it has been embellishing life of people and their culture in different forms. It links cultures, beliefs, thoughts, technology, and above all, people. Through etymology we can study the movement of the word power of wrapping undoubtedly but in depth analyze it could provide many concepts of structural ability. Only in India, more than 105 different processes exist in the way of saree [a type of women attire] wrapping. Then many more other clothing we found in allover world which connects this technique and construction too. One of the main objectives of this study is to enrich wrapping explanation and come up with surfaces by this technique. The deliberate more fragile and stretchable structural framework makes it more appropriate in different users according to their necessity. Developments of design and technology could create new industry segment and generate a marginalized employment for the people too.

Keywords: concept, existence, philosophical attachment, technological advancement

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Authors: S. Ghasemi, K. Khorasani

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In this paper, the problem of fault detection and isolation in the attitude control subsystem of spacecraft formation flying is considered. In order to design the fault detection method, an extended Kalman filter is utilized which is a nonlinear stochastic state estimation method. Three fault detection architectures, namely, centralized, decentralized, and semi-decentralized are designed based on the extended Kalman filters. Moreover, the residual generation and threshold selection techniques are proposed for these architectures.

Keywords: component, formation flight of satellites, extended Kalman filter, fault detection and isolation, actuator fault

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Authors: Mazharuddin Syed Ahmed

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This research presents a framework used to develop The Ara Polytechnic College of Architecture Studies building “Kahukura” which is Green Building certified. This framework integrates the development of a smart building digital twin by utilizing Building Information Modelling (BIM) and its BIM maturity levels, including Levels of Development (LOD), eight dimensions of BIM, Heritage-BIM (H-BIM) and Facility Management BIM (FM BIM). The research also outlines a structured approach to building performance analysis and integration with the circular economy, encapsulated within a five-level digital twin framework. Starting with Level 1, the Descriptive Twin provides a live, editable visual replica of the built asset, allowing for specific data inclusion and extraction. Advancing to Level 2, the Informative Twin integrates operational and sensory data, enhancing data verification and system integration. At Level 3, the Predictive Twin utilizes operational data to generate insights and proactive management suggestions. Progressing to Level 4, the Comprehensive Twin simulates future scenarios, enabling robust “what-if” analyses. Finally, Level 5, the Autonomous Twin, represents the pinnacle of digital twin evolution, capable of learning and autonomously acting on behalf of users.

Keywords: building information modelling, circular economy integration, digital twin, predictive analytics

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Authors: Anwar Jarndal

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In this paper, a genetic-neural-network (GNN) based large-signal model for GaN HEMTs is presented along with its parameters extraction procedure. The model is easy to construct and implement in CAD software and requires only DC and S-parameter measurements. An improved decomposition technique is used to model self-heating effect. Two GNN models are constructed to simulate isothermal drain current and power dissipation, respectively. The two model are then composed to simulate the drain current. The modeling procedure was applied to a packaged GaN-on-Si HEMT and the developed model is validated by comparing its large-signal simulation with measured data. A very good agreement between the simulation and measurement is obtained.

Keywords: GaN HEMT, computer-aided design and modeling, neural networks, genetic optimization

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Authors: Hamida Qumber Ali, Waseem Muhammad Arain, Shama Siddiqui, Sayeed Ghani

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We present an implementing of RMAC in TinyOS 1.x. RMAC is a cross layer and Duty-cycle MAC protocols that was proposed to provide energy efficient transmission services for wireless sensor networks. The protocol has a unique and efficient packet transmission scheduling mechanism that enables it to overcome delivery latency and overcome traffic congestion. Design details and implementation challenges are divulged. Experiments are conducted to show the correctness of our implementation with numerous assumptions. Simulations are performed to compare the performance of RMAC and SMAC. Our results show that RMAC outperforms SMAC in energy efficiency and delay.

Keywords: MAC protocol, performance, RMAC, wireless sensor networks

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Authors: M. Chen, S-Q. Zhang, X. Wang, D. Tate

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This paper presents a numerical solution, namely limit and shakedown analysis, to predict the safety state of smart structures made of heterogeneous materials under unknown cyclic loadings, for instance, the flexure hinge in the micro-positioning stage driven by piezoelectric actuator. In combination of homogenization theory and finite-element method (FEM), the safety evaluation problem is converted to a large-scale nonlinear optimization programming for an acceptable bounded loading as the design reference. Furthermore, a general numerical scheme integrated with the FEM and interior-point-algorithm based optimization tool is developed, which makes the practical application possible.

Keywords: limit state, shakedown analysis, homogenization, heterogeneous structure

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Authors: Turkyh Alotibi, Ghadah Obeid Alrasheed, Afaf Saad Alshaibani, Moneerah Obeid Alrasheed

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This study explores factors that influence MBA enrolment and investigates strategic prerequisites for developing a viable online MBA program at Alfaisal University in the Kingdom of Saudi Arabia. It compares students’ perspectives about online MBA against the face-to-face on-site MBA program. With the self-administered online survey tool, we collected data from 52 first- and second-year MBA students enrolled at Alfaisal University for the 2021 Fall Semester. The data from the survey questionnaire, distributed at the university’s College of Business, reports that approximately 60% of MBA students prefer face-to-face, in-person courses. Their preference for considering an online MBA, primarily rests on two factors, the university’s ranking (68% would enroll for an online MBA program offered by Harvard Business School) and 34.07% for the program timing (timetable). Alfaisal University’s outstanding ranking makes it viable to offer an online MBA either independently or in collaboration with other internationally reputed business schools. The paper contains useful insights to set “the strategic agenda for Online MBA program” in no accredited University but with a good reputation. The information from the case study could be useful for supporting the strategic intent to start an Online MBA program in Saudi Arabia.

Keywords: online MBA, online education demand, university management, course evaluation, blended learning

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Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi

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Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.

Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics

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Authors: Muhammad Atif, Cang Yan

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The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on convolutional neural networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an autoencoder-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the PIX to PIX GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: low light image enhancement, deep learning, convolutional neural network, image processing

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.

Keywords: deep learning, optical Soliton, neural network, partial differential equation

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