Search results for: state machine

Authors: Tunde Szecsi, Janka Szilagyi

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Students majoring in education are underrepresented in undergraduate scholarship. To enable and encourage teacher candidates to engage in scholarly activities, it is essential to infuse skills such as problem-solving, critical thinking, oral and written communication, collaboration and the utilization of information literacy, into courses in teacher preparation programs. In this empirical study, we examined two teacher education programs – one in New York State and one in Florida – in terms of the approaches of the course-based infusion of skills for undergraduate research, and the effectiveness of this infusion. First, course-related documents such as syllabi, assignment descriptions, and course activities were reviewed and analyzed. The goal of the document analysis was to identify and describe the targeted skills, and the pedagogical approaches and strategies for promoting research skills in teacher candidates. Next, a selection of teacher candidates’ scholarly products from the institution in Florida was used as a data set to examine teacher candidates’ skill development in the context of the identified assignments. This dataset was analyzed both quantitatively and qualitatively to describe the changes that occurred in teacher candidates’ critical thinking, communication, and information literacy skills, and to uncover patterns in the skill development at the two institutions. Descriptive statistics were calculated to explore the changes in these skills of teacher candidates over a period of three years. The findings based on data from the teacher education program in Florida indicated a steady gain in written communication and critical thinking and a modest increase in informational literacy. At the institution in New York, candidates’ submission and success rates on the edTPA, a New York State Teacher Certification exam, was used as a measure of scholarly skills. Overall, although different approaches were used for infusing the development of scholarly skills in the courses, the results suggest that a holistic and well-orchestrated infusion of the skills into most courses in the teacher education program might result in steadily developing scholarly skills. These results offered essential implications for teacher education programs in terms of further improvements in teacher candidates’ skills for engaging in undergraduate research and scholarship. In this presentation, our purpose is to showcase two approaches developed by two teacher education programs to demonstrate how diverse approaches toward the promotion of undergraduate scholarship activities are responsive to the context of the teacher preparation programs.

Keywords: critical thinking, pedagogical strategies, teacher education, undergraduate student research

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Authors: Melanie Schinnerl, Dorothea Greiling

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In the context of the 2020 strategy, poverty and its fight returned to the center of national political efforts. This served as motivation for an Austrian research grant-funded project to focus on the under-researched local government level with the aim to identify municipal best-practice cases and to derive policy implications for Austria. Designing effective poverty reduction strategies is a complex challenge which calls for an integrated multi-actor in approach. Cities are increasingly confronted to combat poverty, even in rich EU-member states. By doing so cities face substantial demographic, cultural, economic and social challenges as well as changing welfare state regimes. Furthermore, there is a low willingness of (right-wing) governments to support the poor. Against this background, the research questions are: 1. How do local governments define poverty? 2. Who are the main risk groups and what are the most pressing problems when fighting urban poverty? 3. What is regarded as successful anti-poverty initiatives? 4. What is the underlying welfare state concept? To address the research questions a multi-method approach was chosen, consisting of a systematic literature analysis, a comprehensive document analysis, and expert interviews. For interpreting the data the project follows the qualitative-interpretive paradigm. Municipal approaches for reducing poverty are compared based on deductive, as well as inductive identified criteria. In addition to an intensive literature analysis, interviews (40) were conducted in Austria since the project started in March 2018. From the other countries, 14 responses have been collected, providing a first insight. Regarding the definition of poverty the EU SILC-definition as well as counting the persons who receive need-based minimum social benefits, the Austrian form of social welfare, are the predominant approaches in Austria. In addition to homeless people, single-parent families, un-skilled persons, long-term unemployed persons, migrants (first and second generation), refugees and families with at least 3 children were frequently mentioned. The most pressing challenges for Austrian cities are: expected reductions of social budgets, a great insecurity of the central government's social policy reform plans, the growing number of homeless people and a lack of affordable housing. Together with affordable housing, old-age poverty will gain more importance in the future. The Austrian best practice examples, suggested by interviewees, focused primarily on homeless, children and young people (till 25). Central government’s policy changes have already negative effects on programs for refugees and elderly unemployed. Social Housing in Vienna was frequently mentioned as an international best practice case, other growing cities can learn from. The results from Austria indicate a change towards the social investment state, which primarily focuses on children and labour market integration. The first insights from the other countries indicate that affordable housing and labor market integration are cross-cutting issues. Inherited poverty and old-age poverty seems to be more pressing outside Austria.

Keywords: anti-poverty policies, European cities, empirical study, social investment

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Authors: Himani Sharma, Amit Agrawal

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Stability of the Cassie and Wenzel wetting states depends on intrinsic contact angle and geometric features on a surface that was exploited in capturing biofluids in microwells. However, the mechanism of imbibition of biofluids in the microwells is not well implied in terms of wettability of a substrate. In this work, we experimentally demonstrated filling dynamics in hydrophilic and hydrophobic microwells by protein solutions. Towards this, we utilized lotus leaf as a mold to fabricate microwells on a Polydimethylsiloxane (PDMS) surface. Lotus leaf containing micrometer-sized blunt-conical shaped pillars with a height of 8-15 µm and diameter of 3-8 µm were transferred on to PDMS. Furthermore, PDMS surface was treated with oxygen plasma to render the hydrophilic nature. A 10µL droplets containing fluorescein isothiocyanate (FITC) - labelled bovine serum albumin (BSA) were rested on both hydrophobic (θa = 108o, where θa is the apparent contact angle) and hydrophilic (θa = 60o) PDMS surfaces. A time-dependent fluorescence microscopy was conducted on these modified PDMS surfaces by recording the fluorescent intensity over a 5 minute period. It was observed that, initially (at t=1 min) FITC-BSA was accumulated on the periphery of both hydrophilic and hydrophobic microwells due to incomplete penetration of liquid-gas meniscus. This deposition of FITC-BSA on periphery of microwell was not changed with time for hydrophobic surfaces, whereas, a complete filling was occurred in hydrophilic microwells (at t=5 mins). This attributes to a gradual movement of three-phase contact line along the vertical surface of the hydrophilic microwells as compared to stable pinning in the hydrophobic microwells as confirmed by Surface Evolver simulations. In addition, if the cavities are presented on hydrophobic surfaces, air bubbles will be trapped inside the cavities once the aqueous solution is placed over these surfaces, resulting in the Cassie-Baxter wetting state. This condition hinders trapping of proteins inside the microwells. Thus, it is necessary to impart hydrophilicity to the microwell surfaces so as to induce the Wenzel state, such that, an entire solution will be fully in contact with the walls of microwells. Imbibition of microwells by protein solutions was analyzed in terms fluorescent intensity versus time. The present work underlines the importance of geometry of microwells and surface wettability of substrate in wetting and effective capturing of solid sub-phases in biofluids.

Keywords: BSA, microwells, surface evolver, wettability

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Authors: M. Benachour, N. Benachour, M. Benguediab

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In this investigation an empirical study was made on fatigue crack initiation on 7075 T6 and 7075 T71 al-alloys under constant amplitude loading. At initiation stage, local strain approach at the notch was applied. Single Edge Notch Tensile specimen with semi circular notch is used. Based on experimental results, effect of mean stress, is highlights on fatigue initiation life. Results show that fatigue life initiation is affected by notch geometry and mean stress.

Keywords: fatigue crack initiation, al-alloy, mean stress, heat treatment state

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Authors: Husam Kaid, Abdulrahman Al-Ahmari, Zhiwu Li

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This paper develops a robust deadlock control technique for shared and unreliable resources in automated manufacturing systems (AMSs) based on structural analysis and colored Petri nets, which consists of three steps. The first step involves using strict minimal siphon control to create a live (deadlock-free) system that does not consider resource failure. The second step uses an approach based on colored Petri net, in which all monitors designed in the first step are merged into a single monitor. The third step addresses the deadlock control problems caused by resource failures. For all resource failures in the Petri net model a common recovery subnet based on colored petri net is proposed. The common recovery subnet is added to the obtained system at the second step to make the system reliable. The proposed approach is evaluated using an AMS from the literature. The results show that the proposed approach can be applied to an unreliable complex Petri net model, has a simpler structure and less computational complexity, and can obtain one common recovery subnet to model all resource failures.

Keywords: automated manufacturing system, colored Petri net, deadlocks, siphon

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Authors: Deborah Eric, Abbas Ahmad Khan

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Lead halide perovskites quantum dots have attracted immense scientific and technological interest for successful photovoltaic applications because of their remarkable optoelectronic properties. In this paper, we have simulated CsMAPbI3-xBrx based quantum dots to implement their use in intermediate band solar cells (IBSC). These types of materials exhibit optical and electrical properties distinct from their bulk counterparts due to quantum confinement. The conceptual framework provides a route to analyze the electronic properties of quantum dots. This layer of quantum dots optimizes the position and bandwidth of IB that lies in the forbidden region of the conventional bandgap. A three-dimensional MAPbI3 quantum dot (QD) with geometries including spherical, cubic, and conical has been embedded in the CsPbBr3 matrix. Bound energy wavefunction gives rise to miniband, which results in the formation of IB. If there is more than one miniband, then there is a possibility of having more than one IB. The optimization of QD size results in more IBs in the forbidden region. One band time-independent Schrödinger equation using the effective mass approximation with step potential barrier is solved to compute the electronic states. Envelope function approximation with BenDaniel-Duke boundary condition is used in combination with the Schrödinger equation for the calculation of eigen energies and Eigen energies are solved for the quasi-bound states using an eigenvalue study. The transfer matrix method is used to study the quantum tunneling of MAPbI3 QD through neighbor barriers of CsPbI3. Electronic states are computed using Schrödinger equation with effective mass approximation by considering quantum dot and wetting layer assembly. Results have shown the varying the quantum dot size affects the energy pinning of QD. Changes in the ground, first, second state energies have been observed. The QD is non-zero at the center and decays exponentially to zero at boundaries. Quasi-bound states are characterized by envelope functions. It has been observed that conical quantum dots have maximum ground state energy at a small radius. Increasing the wetting layer thickness exhibits energy signatures similar to bulk material for each QD size.

Keywords: perovskite, intermediate bandgap, quantum dots, miniband formation

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Authors: Asma Ameur, Dhafer Malouche

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Hotel competitiveness research is an essential phase of the marketing strategy for any hotel. Certainly, knowing the hotels' competitors helps the hotelier to grasp its position in the market and the citizen to make the right choice in picking a hotel. Thus, competitiveness is an important indicator that can be influenced by various factors. In fact, the issue of competitiveness, this ability to cope with competition, remains a difficult and complex concept to define and to exploit. Therefore, the purpose of this article is to make an exploratory study to calculate a competitiveness indicator for hotels. Further on, this paper makes it possible to determine the criteria of direct or indirect effect on the image and the perception of a hotel. The actual research is used to look into the right model for hotel ‘competitiveness. For this reason, we exploit different theoretical contributions in the field of machine learning. Thus, we use some statistical techniques such as the Principal Component Analysis (PCA) to reduce the dimensions, as well as other techniques of statistical modeling. This paper presents a survey covering of the techniques and methods in hotel competitiveness research. Furthermore, this study allows us to deduct the significant variables that influence the determination of hotel’s competitors. Lastly, the discussed experiences in this article found that the hotel competitors are influenced by several factors with different rates.

Keywords: competitiveness, e-reputation, hotels' competitors, online hotel’ review, principal component analysis, statistical modeling

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Authors: Touila Ahmed, Elie Louis, Hamza Gharbi

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State of the art question answering models have recently shown impressive performance especially in a zero-shot setting. This approach is particularly useful when confronted with a highly diverse domain such as the legal field, in which it is increasingly difficult to have a dataset covering every notion and concept. In this work, we propose a flexible generative question answering approach to contract analysis as well as a weakly supervised procedure to leverage unannotated data and boost our models’ performance in general, and their zero-shot performance in particular.

Keywords: question answering, contract analysis, zero-shot, natural language processing, generative models, self-supervision

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Authors: Maria Lucia G. Lourenco, Keylla H. N. P. Pereira, Viviane Y. Hibaru, Fabiana F. Souza, Joao C. P. Ferreira, Simone B. Chiacchio, Luiz H. A. Machado

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Congenital malformations are organ defects due to genetic or teratogenic causes, which can lead to high mortality in dog litters. This study assessed and described the congenital malformations in newborn dogs. The study included litters attend in the São Paulo State University (UNESP) Veterinary Hospital, Botucatu, Sao Paulo, Brazil. One hundred seventy-eight litters and 803 newborns were evaluated. The occurrence of litters with malformations was 24.7%, and of newborns was 6.7%. Twenty-seven different malformations were registered: anasarca, anal atresia, cleft lip, cleft palate, duplicated right ribcage, equinovarus, exencephaly, gastroschisis, hydrocephaly, lissencephaly, macroglossia, microphthalmia, mitral valve dysplasia, omphalocele, eyelid agenesis, persistent urachus, polydactyly, pulmonary hypoplasia, pulmonary valve stenosis, rectovaginal fistula, agenesis of abdominal muscles, rib hypoplasia, scoliosis, segmental aplasia of the intestines, tricuspid valve dysplasia, unilateral kidney agenesis, and vaginal atresia. 68.7% of newborns died as a result of malformations. The pure breeds with the highest chances of manifesting malformations in contrast with mixed breeds were French Bulldog, Pug, English Bulldog, Rottweiler, German Spitz, Pinscher, Pitbull, Yorkshire Terrier, and Shih-Tzu. Significant values (P<0.05) occurred in races French Bulldogs and Pugs. The causes of congenital disabilities are possibly related to hereditary genetic factors considering that the highest incidence of malformations was observed among purebreds. There as one case of exposure to a teratogenic agent, but no other mothers were exposed to such agents during pregnancy. Two cases of consanguineal breeding between siblings were reported. The mortality rate was high. Genetic breeding programs for reproduction, avoiding consanguineous mating, care in choosing parents, and avoiding maternal exposure to teratogenic agents are of utmost importance in reducing dog malformations and consequent mortality.

Keywords: congenital defects, teratogenesis, canine neonatology, newborn puppy

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Authors: Marcela Dávalos López

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In Mexico, the distribution of hygienistarchitecture during the 20th century had different rhythms. The culmination of the urban hygiene system (from sewers to showers, passing through garbage collection) forced neighbors and citizens to participate in the common welfare. This turned the urban references and dissociated the ways of living and led to comfort and health. However, the contrast between two Mexicancities, Cuernavaca and Mexico City shows us very different cultural practices regarding the use of hygienicarchitectures: in the first, thenature of its deepravines marked the destiny of residential architecture, while in Mexico City, state participation alteredthelandscape and homogenized the architectural models of domestic and intímate spaces.

Keywords: Cultural Practices, Dissociated Ways To Comfort, Hygiene Architecture , Mexico

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Authors: Fatima Muhammad Abdulkadir, D. B. Maikaje, Y. A. Umar

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A study conducted to determine cercariae diversity and prevalence of trematode infection in freshwater snails from six freshwater bodies selected by systematic random sampling in Kaduna State was carried from January 2013 to December 2013. Freshwater snails and cercariae harvested from the study sites were morphologically identified. A total of 23,823 freshwater snails were collected from the six freshwater bodies: Bagoma dam, Gimbawa dam, Kangimi dam, Kubacha dam, Manchok water intake and Saminaka water intake. The observed freshwater snail species were: Melanoides tuberculata, Biomphalaria pfeifferi, Bulinus globosus, Lymnaea natalensis, Physa sp., Cleopatra bulimoides, Bellamya unicolor and Lanistes varicus. The freshwater snails were exposed to artificial bright light from a 100 Watt electric bulb in the laboratory to induce cercarial shedding. Of the total freshwater snails collected, 10.55% released one or more types of cercariae. Seven morphological types of cercariae were shed by six freshwater snail species namely: Brevifurcate-apharyngeate distome, Amphistome, Gymnocephalus, Longifurcate-pharyngeate monostome, Longifurcate-pharyngeate distome, Echinostome and Xiphidio cercariae. Infection was monotype in most of the freshwater snails collected; however, Physa species presented a mixed infection with Gymnocephalus and Longifurcate-pharyngeate distome cercariae. B. globosus and B. pfeifferi were the most preferred intermediate hosts with the prevalence of 13.48% and 13.46%, respectively. The diversity and prevalence of cercariae varied among the six freshwater bodies with Manchok water intake having the highest infestation (14.3%) and the least recorded in Kangimi dam (3.9%). There was a correlation trend between the number of freshwater snails and trematode infection with Manchok exhibiting the highest and Bagoma none. The highest cercarial diversity was observed in B. pfeifferi and B. globosus with four morphotypes each, and the lowest was in M. tuberculata with one morphotype. The general distribution of freshwater snails and the trematode cercariae they shed suggests the risk of human and animals to trematodiasis in Manchok community. Public health education to raise awareness on individual and communal action that may control snail breeding sites, prevent transmission and provide access to treatment should be intensified.

Keywords: Cercariae, diversity, freshwater snails, prevalence, trematodiasis

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Authors: Nassim Dennouni, Yvan Peter, Luigi Lancieri, Zohra Slama

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The objective of this article is to make a bibliographic study on the recommendation of mobile learning activities that are used as part of the field trip scenarios. Indeed, the recommendation systems are widely used in the context of mobility because they can be used to provide learning activities. These systems should take into account the history of visits and teacher pedagogy to provide adaptive learning according to the instantaneous position of the learner. To achieve this objective, we review the existing literature on field trip scenarios to recommend mobile learning activities.

Keywords: mobile learning, field trip, mobile learning activities, collaborative filtering, recommendation system, point of interest, ACO algorithm

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Authors: Ayliana Dharmawan, Heng Yong Sheng, Zhang Xiaojin, Tan Thai Lian

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To facilitate discharge planning, doctors are presently required to assign an Estimated Discharge Date (EDD) for each patient admitted to the hospital. This assignment of the EDD is largely based on the doctor’s judgment. This can be difficult for cases which are complex or relatively new to the doctor. It is hypothesized that a data-driven approach would be able to facilitate the doctors to make accurate estimations of the discharge date. Making use of routinely collected data on inpatient discharges between January 2013 and May 2016, a predictive model was developed using machine learning techniques to predict the Length of Stay (and hence the EDD) of inpatients, at the point of admission. The predictive performance of the model was compared to that of the clinicians using accuracy measures. Overall, the best performing model was found to be able to predict EDD with an accuracy improvement in Average Squared Error (ASE) by -38% as compared to the first EDD determined by the present method. It was found that important predictors of the EDD include the provisional diagnosis code, patient’s age, attending doctor at admission, medical specialty at admission, accommodation type, and the mean length of stay of the patient in the past year. The predictive model can be used as a tool to accurately predict the EDD.

Keywords: inpatient, estimated discharge date, EDD, prediction, data-driven

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Authors: Fatimah Abd Elghani, Raymonde Szargel, Vered Shani, Hazem Safory, Haya Hamza, Mor Savyon, Ruth Rott, Rina Bandopadhyay, Simone Engelender

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Background: PINK1 is a mitochondrial kinase mutated in some familial cases of Parkinson’s disease. Down regulation of PINK1 results in abnormal mitochondrial morphology and altered membrane potential. Although PINK1 has a predicted mitochondrial import sequence, it’s cellular, and submitochondrial localization remains unclear, in part because it is rapidly degraded. In this work, we investigated the mechanisms involved in PINK1 degradation and how this may affect PINK1 stability and function, with implications for mitochondrial function in PD. In addition, pharmacological inhibition of proteasome activity was shown to lead to PINK1 accumulation, indicating that PINK1 degradation depends on the ubiquitin-proteasome system (UPS). Methods: Using co-immunoprecipitation assays, we identified E3 ubiquitin ligase SIAH1 as a PINK1-interacting protein in HEK293 cells as well as on rat brain tissues. In addition, we determined the effect of SIAH 1, SIAH2 and Parkin on PINK1 steady-state levels by Western blot analysis, and checked their possibility to ubiquitinate and mediate PINK1 degradation through the proteasome carried out in vivo ubiquitination experiments. Results: We have obtained results showing that SIAH-1 interacts with and ubiquitinates PINK1. The ubiquitination promoted by SIAH-1 leads to the proteasomal degradation of PINK1. We confirmed these findings by knocking down SIAH-1 and observing important accumulation of PINK1 in cells. Besides, we found that SIAH-1 decreases PINK1 steady-state levels but not the E3 ligase Parkin. We also investigated the interaction of SIAH-1 with PINK1 disease mutants and its ability to promote their ubiquitination and degradation. Although, no clear difference in the ability of SIAH-1 to promote the degradation of PINK1 disease mutants was observed. It is possible that dysfunction of proteasomal activity in the disease may lead to the accumulation and aggregation of ubiquitinated PINK1 in patients with PINK1 mutations, with possible implications to the pathogenesis of PD. Conclusions: Here, we demonstrated that SIAH-1 ubiquitinates and promotes the degradation of PINK1. In addition, SIAH-1 represents now a target that may help the improvement of mitophagy in PD. Further investigations needed to understand how mitophagy is regulated by PINK1-SIAH-1 axis to provide targets for future therapeutics.

Keywords: PD, Parkinson's disease, PINK1, PTEN-induced kinase1, SIAH, seven in absentia homolog, SN, substantia nigra

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Authors: Derrouazin Mohammed Redhouane, Souakri Mohammed Lotfi, Henini Ghania

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This work consists, first of all, of mastering one of the powerful process simulation tools currently used in the industrial processes, which is the HYSYS sizing software, and second, of simulating a petroleum distillation column. This study is divided into two parts; where the first one consists of a dimensioning of the column with a fast approximating method using state equations, iterative calculations, and then a precise simulation method with the HYSYS software. The second part of this study is a hydrodynamic study in order to verify by obtained results the proper functioning of the plates.

Keywords: industry process engineering, water distillation, environment, HYSYS simulation tool

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Authors: Imine Zakaria, Meftah Sidi Mohamed El Amine

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One of the most vital aerodynamic organs of a flying machine is the wing, which allows it to fly in the air efficiently. The flow around the wing is very sensitive to changes in the angle of attack. Beyond a value, there is a phenomenon of the boundary layer separation on the upper surface, which causes instability and total degradation of aerodynamic performance called a stall. However, controlling flow around an airfoil has become a researcher concern in the aeronautics field. There are two techniques for controlling flow around a wing to improve its aerodynamic performance: passive and active controls. Blowing and suction are among the active techniques that control the boundary layer separation around an airfoil. Their objective is to give energy to the air particles in the boundary layer separation zones and to create vortex structures that will homogenize the velocity near the wall and allow control. Blowing and suction have long been used as flow control actuators around obstacles. In 1904 Prandtl applied a permanent blowing to a cylinder to delay the boundary layer separation. In the present study, several numerical investigations have been developed to predict a turbulent flow around an aerodynamic profile. CFD code was used for several angles of attack in order to validate the present work with that of the literature in the case of a clean profile. The variation of the lift coefficient CL with the momentum coefficient

Keywords: CFD, control flow, lift, slot

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: Bastian Vollrath, Hartwig Hubel

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In case of over-elastic and cyclic loading, strain may accumulate due to a ratcheting mechanism until the state of shakedown is possibly achieved. Load history dependent numerical investigations by a step-by-step analysis are rather costly in terms of engineering time and numerical effort. In the case of multi-parameter loading, where various independent loadings affect the final state of shakedown, the computational effort becomes an additional challenge. Therefore, direct methods like the Simplified Theory of Plastic Zones (STPZ) are developed to solve the problem with a few linear elastic analyses. Post-shakedown quantities such as strain ranges and cyclic accumulated strains are calculated approximately by disregarding the load history. The STPZ is based on estimates of a transformed internal variable, which can be used to perform modified elastic analyses, where the elastic material parameters are modified, and initial strains are applied as modified loading, resulting in residual stresses and strains. The STPZ already turned out to work well with respect to cyclic loading between two states of loading. Usually, few linear elastic analyses are sufficient to obtain a good approximation to the post-shakedown quantities. In a multi-dimensional load domain, the approximation of the transformed internal variable transforms from a plane problem into a hyperspace problem, where time-consuming approximation methods need to be applied. Therefore, a solution restricted to structures with four stress components was developed to estimate the transformed internal variable by means of three-dimensional vector algebra. This paper presents the extension to cyclic multi-parameter loading so that an unlimited number of load cases can be taken into account. The theoretical basis and basic presumptions of the Simplified Theory of Plastic Zones are outlined for the case of elastic shakedown. The extension of the method to many load cases is explained, and a workflow of the procedure is illustrated. An example, adopting the FE-implementation of the method into ANSYS and considering multilinear hardening is given which highlights the advantages of the method compared to incremental, step-by-step analysis.

Keywords: cyclic loading, direct method, elastic shakedown, multi-parameter loading, STPZ

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Authors: Sung-Bok Choi, Hyun-Jun Shin, Hyoung-Kyu Song

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This paper proposes a single relay selection scheme in cooperative communication. Decode and forward scheme is considered when a source node wants to cooperate with a single relay for data transmission. To use the proposed single relay selection scheme, the source node make a little different pattern signal which is not complex pattern and broadcasts it. The proposed scheme does not require the channel state information between the source node and candidates of the relay during the relay selection. Therefore, it is able to be used in many fields.

Keywords: relay selection, cooperative communication, df, channel codes

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Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

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Authors: Bashaiar Alsanaa

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Social media have totally converged with social life all around the globe. Using social media applications and mobile phones have become somewhat of an addiction to most people. Driving while using mobile applications falls under such addiction when usage is not of urgency. This study aims to investigate the impact of using such applications while driving in the small rich state of Kuwait, where most people juggle more than one phone for different purposes. Positive and negative effects will be explored in detail as well as causes for these effects and possible reasons. A full range of recommendations will be presented so as to give other countries a specific case study upon which to build solutions and remedies to this emerging and dangerous social phenomenon.

Keywords: social media, driving, mobile applications, communication

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Authors: Liqin Zhang, Liang Yan

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This paper addresses the speed synchronization control problem for a network-based multi-motor system from the perspective of cluster consensus theory. Each motor is considered as a single agent connected through fixed and undirected network. This paper presents an improved control protocol from three aspects. First, for the purpose of improving both tracking and synchronization performance, this paper presents a distributed leader-following method. The improved control protocol takes the importance of each motor’s speed into consideration, and all motors are divided into different groups according to speed weights. Specifically, by using control parameters optimization, the synchronization error and tracking error can be regulated and decoupled to some extent. The simulation results demonstrate the effectiveness and superiority of the proposed strategy. In practical engineering, the simplified models are unrealistic, such as single-integrator and double-integrator. And previous algorithms require the acceleration information of the leader available to all followers if the leader has a varying velocity, which is also difficult to realize. Therefore, the method focuses on an observer-based variable structure algorithm for consensus tracking, which gets rid of the leader acceleration. The presented scheme optimizes synchronization performance, as well as provides satisfactory robustness. What’s more, the existing algorithms can obtain a stable synchronous system; however, the obtained stable system may encounter some disturbances that may destroy the synchronization. Focus on this challenging technological problem, a state-dependent-switching approach is introduced. In the presence of unmeasured angular speed and unknown failures, this paper investigates a distributed fault-tolerant consensus tracking algorithm for a group non-identical motors. The failures are modeled by nonlinear functions, and the sliding mode observer is designed to estimate the angular speed and nonlinear failures. The convergence and stability of the given multi-motor system are proved. Simulation results have shown that all followers asymptotically converge to a consistent state when one follower fails to follow the virtual leader during a large enough disturbance, which illustrates the good performance of synchronization control accuracy.

Keywords: consensus control, distributed follow, fault-tolerant control, multi-motor system, speed synchronization

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Authors: Duyen Lam, Thuong Hoang, Atul Sajjanhar, Feifei Chen

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With the emerging interactive technology applications helping users connect progressively with cultural artefacts in new approaches, the cultural heritage sector gains significantly. The interactive apps’ issues can be tested via several techniques, including usability surveys and usability evaluations. The severe usability problems for museums’ interactive technologies commonly involve interactions, control, and navigation processes. This study confirms the low quality of being immersive for audio guides in navigating the exhibition and involving experience in the virtual environment, which are the most vital features of new interactive technologies such as AR and VR. In addition, our usability surveys and heuristic evaluations disclosed many usability issues of these interactive technologies relating to interaction functions. Additionally, we use the Wayback Machine to examine what interactive apps/technologies were deployed on these websites during the physical visits limited due to the COVID-19 pandemic lockdown. Based on those inputs, we propose the reflection framework to enhance the UX in the cultural heritage domain with detailed guidelines.

Keywords: framework, user experience, cultural heritage, interactive technology, museum, COVID-19 pandemic, usability survey, heuristic evaluation, guidelines

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Authors: Nyashadzashe Chiraga, Anthony Walker, Glen Bright

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The manufacturing industry is currently experiencing a paradigm shift into the Fourth Industrial Revolution in which customers are increasingly at the epicentre of production. The high degree of production customization and personalization requires a flexible manufacturing system that will rapidly respond to the dynamic and volatile changes driven by the market. They are a gap in technology that allows for the optimal flow of information and optimal manufacturing operations on the shop floor regardless of the rapid changes in the fixture and part demands. Information is the reduction of uncertainty; it gives meaning and context on the state of each cell. The amount of information needed to describe cellular manufacturing systems is investigated by two measures: the structural entropy and the operational entropy. Structural entropy is the expected amount of information needed to describe scheduled states of a manufacturing system. While operational entropy is the amount of information that describes the scheduled states of a manufacturing system, which occur during the actual manufacturing operation. Using Anylogic simulator a typical manufacturing job shop was set-up with a cellular manufacturing configuration. The cellular make-up of the configuration included; a Material handling cell, 3D Printer cell, Assembly cell, manufacturing cell and Quality control cell. The factory shop provides manufactured parts to a number of clients, and there are substantial variations in the part configurations, new part designs are continually being introduced to the system. Based on the normal expected production schedule, the schedule adherence was calculated from the structural entropy and operation entropy of varying the amounts of information communicated in simulated runs. The structural entropy denotes a system that is in control; the necessary real-time information is readily available to the decision maker at any point in time. For contractive analysis, different out of control scenarios were run, in which changes in the manufacturing environment were not effectively communicated resulting in deviations in the original predetermined schedule. The operational entropy was calculated from the actual operations. From the results obtained in the empirical study, it was seen that increasing, the efficiency of a factory communication system increases the degree of adherence of a job to the expected schedule. The performance of downstream production flow fed from the parallel upstream flow of information on the factory state was increased.

Keywords: information entropy, communication in manufacturing, mass customisation, scheduling

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Authors: Priyadarsini Samal, Rajesh Singla

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Many mobile games come with the benefits of entertainment by introducing stress to the human brain. In recognizing this mental stress, the brain-computer interface (BCI) plays an important role. It has various neuroimaging approaches which help in analyzing the brain signals. Electroencephalogram (EEG) is the most commonly used method among them as it is non-invasive, portable, and economical. Here, this paper investigates the pattern in brain signals when introduced with mental stress. Two healthy volunteers played a game whose aim was to search hidden words from the grid, and the levels were chosen randomly. The EEG signals during gameplay were recorded to investigate the impacts of stress with the changing levels from easy to medium to hard. A total of 16 features of EEG were analyzed for this experiment which includes power band features with relative powers, event-related desynchronization, along statistical features. Support vector machine was used as the classifier, which resulted in an accuracy of 93.9% for three-level stress analysis; for two levels, the accuracy of 92% and 98% are achieved. In addition to that, another game that was similar in nature was played by the volunteers. A suitable regression model was designed for prediction where the feature sets of the first and second game were used for testing and training purposes, respectively, and an accuracy of 73% was found.

Keywords: brain computer interface, electroencephalogram, regression model, stress, word search

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Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

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Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

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Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

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Authors: Diogo José Morgado Rebelo, Francisco António Carneiro Pacheco de Andrade, Paulo Jorge Freitas de Oliveira Novais

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Not everything in AI-power consumer credit scoring turns out to be a wonder. When using AI in Creditworthiness Assessment (CWA), opacity and unfairness ‘sins’ must be considered to the task be deemed Responsible. AI software is not always 100% accurate, which can lead to misclassification. Discrimination of some groups can be exponentiated. A hetero personalized identity can be imposed on the individual(s) affected. Also, autonomous CWA sometimes lacks transparency when using black box models. However, for this intended purpose, human analysts ‘on-the-loop’ might not be the best remedy consumers are looking for in credit. This study seeks to explore the legality of implementing a Multi-Agent System (MAS) framework in consumer CWA to ensure compliance with the regulation outlined in Article 14(4) of the Proposal for an Artificial Intelligence Act (AIA), dated 21 April 2021 (as per the last corrigendum by the European Parliament on 19 April 2024), Especially with the adoption of Art. 18(8)(9) of the EU Directive 2023/2225, of 18 October, which will go into effect on 20 November 2026, there should be more emphasis on the need for hybrid oversight in AI-driven scoring to ensure fairness and transparency. In fact, the range of EU regulations on AI-based consumer credit will soon impact the AI lending industry locally and globally, as shown by the broad territorial scope of AIA’s Art. 2. Consequently, engineering the law of consumer’s CWA is imperative. Generally, the proposed MAS framework consists of several layers arranged in a specific sequence, as follows: firstly, the Data Layer gathers legitimate predictor sets from traditional sources; then, the Decision Support System Layer, whose Neural Network model is trained using k-fold Cross Validation, provides recommendations based on the feeder data; the eXplainability (XAI) multi-structure comprises Three-Step-Agents; and, lastly, the Oversight Layer has a 'Bottom Stop' for analysts to intervene in a timely manner. From the analysis, one can assure a vital component of this software is the XAY layer. It appears as a transparent curtain covering the AI’s decision-making process, enabling comprehension, reflection, and further feasible oversight. Local Interpretable Model-agnostic Explanations (LIME) might act as a pillar by offering counterfactual insights. SHapley Additive exPlanation (SHAP), another agent in the XAI layer, could address potential discrimination issues, identifying the contribution of each feature to the prediction. Alternatively, for thin or no file consumers, the Suggestion Agent can promote financial inclusion. It uses lawful alternative sources such as the share of wallet, among others, to search for more advantageous solutions to incomplete evaluation appraisals based on genetic programming. Overall, this research aspires to bring the concept of Machine-Centered Anthropocentrism to the table of EU policymaking. It acknowledges that, when put into service, credit analysts no longer exert full control over the data-driven entities programmers have given ‘birth’ to. With similar explanatory agents under supervision, AI itself can become self-accountable, prioritizing human concerns and values. AI decisions should not be vilified inherently. The issue lies in how they are integrated into decision-making and whether they align with non-discrimination principles and transparency rules.

Keywords: creditworthiness assessment, hybrid oversight, machine-centered anthropocentrism, EU policymaking

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Authors: Hamza Javar Magnier, Robin Curtis

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There have been rapid advances in the upstream processing of protein therapeutics, which has shifted the bottleneck to downstream purification and formulation. Finding liquid formulations with shelf lives of up to two years is increasingly difficult for some of the newer therapeutics, which have been engineered for activity, but their formulations are often viscous, can phase separate, and have a high propensity for irreversible aggregation1. We explore means to develop improved predictive ability from a better understanding of how protein-protein interactions on formulation conditions (pH, ionic strength, buffer type, presence of excipients) and how these impact upon the initial steps in protein self-association and aggregation. In this work, we study the initial steps in the aggregation pathways using a minimal protein model based on square-well potentials and discontinuous molecular dynamics. The effect of model parameters, including range of interaction, stiffness, chain length, and chain sequence, implies that protein models fold according to various pathways. By reducing the range of interactions, the folding- and collapse- transition come together, and follow a single-step folding pathway from the denatured to the native state2. After parameterizing the model interaction-parameters, we developed an understanding of low-temperature conformational properties and fluctuations, and the correlation to the folding transition of proteins in isolation. The model fluctuations increase with temperature. We observe a low-temperature point, below which large fluctuations are frozen out. This implies that fluctuations at low-temperature can be correlated to the folding transition at the melting temperature. Because proteins “breath” at low temperatures, defining a native-state as a single structure with conserved contacts and a fixed three-dimensional structure is misleading. Rather, we introduce a new definition of a native-state ensemble based on our understanding of the core conservation, which takes into account the native fluctuations at low temperatures. This approach permits the study of a large range of length and time scales needed to link the molecular interactions to the macroscopically observed behaviour. In addition, these models studied are parameterized by fitting to experimentally observed protein-protein interactions characterized in terms of osmotic second virial coefficients.

Keywords: protein folding, native-ensemble, conformational fluctuation, aggregation

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Authors: Md Serajul Islam

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High Dose Rate (HDR) Brachytherapy is used for cancer patients. In our country’s prospect, we are using only cervices and breast cancer treatment by using HDR. The air kerma rate in air at a reference distance of less than a meter from the source is the recommended quantity for the specification of gamma ray source Ir-192 in brachytherapy. The absorbed dose for the patients is directly proportional to the air kerma rate. Therefore the air kerma rate should be determined before the first use of the source on patients by qualified medical physicist who is independent from the source manufacturer. The air kerma rate will then be applied in the calculation of the dose delivered to patients in their planning systems. In practice, high dose rate (HDR) Ir-192 afterloader machines are mostly used in brachytherapy treatment. Currently, HDR-Co-60 increasingly comes into operation too. The essential advantage of the use of Co-60 sources is its longer half-life compared to Ir-192. The use of HDRCo-60 afterloading machines is also quite interesting for developing countries. This work describes the dosimetry at HDR afterloading machines according to the protocols IAEA-TECDOC-1274 (2002) with the nuclides Ir-192 and Co-60. We have used 3 different measurement methods (with a ring chamber, with a solid phantom and in free air and with a well chamber) in dependence of each of the protocols. We have shown that the standard deviations of the measured air kerma rate for the Co-60 source are generally larger than those of the Ir-192 source. The measurements with the well chamber had the lowest deviation from the certificate value. In all protocols and methods, the deviations stood for both nuclides by a maximum of about 1% for Ir-192 and 2.5% for Co-60-Sources respectively.

Keywords: Ir-192 source, cancer, patients, cheap treatment cost

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