Search results for: Krylov subspace methods

Authors: Gizem Eser Erdek

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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

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Authors: Adandé Belarmain Fandohan

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Climate change has become a major concern globally, particularly in rural communities that have to find rapid coping solutions. Several vulnerability assessment approaches have been developed in the last decades. This comes along with a higher risk for different methods to result in different conclusions, thereby making comparisons difficult and decision-making non-consistent across areas. The effect of methods and computational approaches on estimates of people’s vulnerability was assessed using data collected from the Gambia. Twenty-four indicators reflecting vulnerability components: (exposure, sensitivity, and adaptive capacity) were selected for this purpose. Data were collected through household surveys and key informant interviews. One hundred and fifteen respondents were surveyed across six communities and two administrative districts. Results were compared over three computational approaches: the maximum value transformation normalization, the z-score transformation normalization, and simple averaging. Regardless of the approaches used, communities that have high exposure to climate change and extreme events were the most vulnerable. Furthermore, the vulnerability was strongly related to the socio-economic characteristics of farmers. The survey evidenced variability in vulnerability among communities and administrative districts. Comparing output across approaches, overall, people in the study area were found to be highly vulnerable using the simple average and maximum value transformation, whereas they were only moderately vulnerable using the z-score transformation approach. It is suggested that assessment approach-induced discrepancies be accounted for in international debates to harmonize/standardize assessment approaches to the end of making outputs comparable across regions. This will also likely increase the relevance of decision-making for adaptation policies.

Keywords: maximum value transformation, simple averaging, vulnerability assessment, West Africa, z-score transformation

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Authors: Miroslava Cuperlovic-Culf, Lipu Wang, Ketty Boyle, Nadine Makley, Ian Burton, Anissa Belkaid, Mohamed Touaibia, Marc E. Surrette

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Metabolic changes are one of the major factors in the development of a variety of diseases in various species. Metabolism of agricultural plants is altered the following infection with pathogens sometimes contributing to resistance. At the same time, pathogens use metabolites for infection and progression. In humans, metabolism is a hallmark of cancer development for example. Quantified metabolomics data combined with other omics or clinical data and analyzed using various unsupervised and supervised methods can lead to better diagnosis and prognosis. It can also provide information about resistance as well as contribute knowledge of compounds significant for disease progression or prevention. In this work, different methods for metabolomics quantification and analysis from Nuclear Magnetic Resonance (NMR) measurements that are used for investigation of disease development in wheat and human cells will be presented. One-dimensional 1H NMR spectra are used extensively for metabolic profiling due to their high reliability, wide range of applicability, speed, trivial sample preparation and low cost. This presentation will describe a new method for metabolite quantification from NMR data that combines alignment of spectra of standards to sample spectra followed by multivariate linear regression optimization of spectra of assigned metabolites to samples’ spectra. Several different alignment methods were tested and multivariate linear regression result has been compared with other quantification methods. Quantified metabolomics data can be analyzed in the variety of ways and we will present different clustering methods used for phenotype determination, network analysis providing knowledge about the relationships between metabolites through metabolic network as well as biomarker selection providing novel markers. These analysis methods have been utilized for the investigation of fusarium head blight resistance in wheat cultivars as well as analysis of the effect of estrogen receptor and carbonic anhydrase activation and inhibition on breast cancer cell metabolism. Metabolic changes in spikelet’s of wheat cultivars FL62R1, Stettler, MuchMore and Sumai3 following fusarium graminearum infection were explored. Extensive 1D 1H and 2D NMR measurements provided information for detailed metabolite assignment and quantification leading to possible metabolic markers discriminating resistance level in wheat subtypes. Quantification data is compared to results obtained using other published methods. Fusarium infection induced metabolic changes in different wheat varieties are discussed in the context of metabolic network and resistance. Quantitative metabolomics has been used for the investigation of the effect of targeted enzyme inhibition in cancer. In this work, the effect of 17 β -estradiol and ferulic acid on metabolism of ER+ breast cancer cells has been compared to their effect on ER- control cells. The effect of the inhibitors of carbonic anhydrase on the observed metabolic changes resulting from ER activation has also been determined. Metabolic profiles were studied using 1D and 2D metabolomic NMR experiments, combined with the identification and quantification of metabolites, and the annotation of the results is provided in the context of biochemical pathways.

Keywords: metabolic biomarkers, metabolic network, metabolomics, multivariate linear regression, NMR quantification, quantified metabolomics, spectral alignment

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Authors: Ines Gasmi, Salima Smiti, Makram Soui, Khaled Ghedira

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Credit risk is considered as one of the important issues for financial institutions. It provokes great losses for banks. To this objective, numerous methods for credit risk evaluation have been proposed. Many evaluation methods are black box models that cannot adequately reveal information hidden in the data. However, several works have focused on building transparent rules-based models. For credit risk assessment, generated rules must be not only highly accurate, but also highly interpretable. In this paper, we aim to build both, an accurate and transparent credit risk evaluation model which proposes a set of classification rules. In fact, we consider the credit risk evaluation as an optimization problem which uses a genetic programming (GP) algorithm, where the goal is to maximize the accuracy of generated rules. We evaluate our proposed approach on the base of German and Australian credit datasets. We compared our finding with some existing works; the result shows that the proposed GP outperforms the other models.

Keywords: credit risk assessment, rule generation, genetic programming, feature selection

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Authors: S. V. Ncube, A. I. O. Jideani, E. T. Gwata

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The plight of food insecurity in developing countries has led to renewed interest in underutilized legumes. Their nutritional versatility, desirable functionality, pharmaceutical value and inherent bioactive compounds have drawn the attention of researchers. This has provoked the development of value added products with the aim of commercially exploiting their full potential. However processing of these legumes leads to changes in nutritional composition as affected by processing variables like pH, temperature and pressure. There is therefore a need for process control and quality assurance during production of the value added products. However, conventional methods for microbiological and biochemical identification are labour intensive and time-consuming. Biosensors offer rapid and affordable methods to assure the quality of the products. They may be used to quantify nutrients and anti-nutrients in the products while manipulating and monitoring variables such as pH, temperature, pressure and oxygen that affect the quality of the final product. This review gives an overview of the types of biosensors used in the food industry, their advantages and disadvantages and their possible application in processing of legumes.

Keywords: legume processing, biosensors, quality control, nutritional versatility

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Authors: Yamkela Zitwana

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Soil erosion along the roads and/or road riparian areas has become a norm in the Eastern Cape. Soil erosion refers to the detachment and transportation of soil from one area (onsite) to another (offsite). This displacement or removal of soil can be caused by water, air and sometimes gravity. This will focus on accelerated soil erosion which is the result of human interference with the environment. Engcobo local municipality falls within the Eastern Cape Province in the eastern side of CHRIS HANI District municipality. The focus road is R61 protruding from the Engcobo town outskirts along the Nyanga SSS on the way to Umtata although it will cover few Kilometers away from Engcobo. This research aims at looking at the contribution made by road construction to soil erosion. Steps to achieve the result will involve revisiting the phases of road construction through unstructured interviews, identifying the types of soil erosion evident in the area by doing a checklist, checking the material, utensils and equipment used for road construction and the contribution of road construction through stratified random sampling checking the soil color and texture. This research will use a pragmatic approach which combines related methods and consider the flaws of each method so as to ensure validity, precision and accuracy. Both qualitative and quantitative methods will be used. Statistical methods and GIS analysis will be used to analyze the collected data.

Keywords: soil erosion, road riparian, accelerated soil erosion, road construction, sampling, universal soil loss model, GIS analysis, focus groups, qualitative, quantitative method, research, checklist questionnaires, unstructured interviews, pragmatic approach

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Authors: Samba Raju, Chiluveru, Manoj Tripathy

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Intelligibility is an essential characteristic of a speech signal, which is used to help in the understanding of information in speech signal. Background noise in the environment can deteriorate the intelligibility of a recorded speech. In this paper, we presented a simple variance subtracted - variable level discrete wavelet transform, which improve the intelligibility of speech. The proposed algorithm does not require an explicit estimation of noise, i.e., prior knowledge of the noise; hence, it is easy to implement, and it reduces the computational burden. The proposed algorithm decides a separate decomposition level for each frame based on signal dominant and dominant noise criteria. The performance of the proposed algorithm is evaluated with speech intelligibility measure (STOI), and results obtained are compared with Universal Discrete Wavelet Transform (DWT) thresholding and Minimum Mean Square Error (MMSE) methods. The experimental results revealed that the proposed scheme outperformed competing methods

Keywords: discrete wavelet transform, speech intelligibility, STOI, standard deviation

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Authors: Petr Květon, Martin Jelínek

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We try to identify the role of various aspects of parenting style in the phenomenon of videogame playing addiction. Relevant self-report questionnaires were part of a wider set of methods focused on the constructs related to videogame playing. The battery of methods was administered in school settings in paper and pencil form. The research sample consisted of 333 (166 males, 167 females) elementary and high school students at the age between 10 and 19 years (m=14.98, sd=1.77). Using stepwise regression analysis, we assessed the influence of demographic variables (gender and age) and parenting styles. Age and gender together explained 26.3% of game addiction variance (F(2,330)=58.81, p<.01). By adding four aspect of parenting styles (inconsistency, involvement, control, and warmth) another 10.2% of variance was explained (∆F(4,326)=13.09, p<.01). The significant predictor was gender of the respondent, where males scored higher on game addiction scale (B=0.70, p<.01), age (β=-0.18, p<.01), where younger children showed higher level of addiction, and parental inconsistency (β=0.30, p<.01), where the higher the inconsistency in upbringing, the more developed game playing addiction.

Keywords: gender, parenting styles, video games, addiction

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Authors: Fadwa Chtioui

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The field of endodontics has witnessed constant advancements in treatment methods and instrument design, particularly for nickel-titanium (NiTi) files. Despite these developments, it remains crucial for clinicians to have a thorough understanding of their characteristics and behavior to choose the appropriate instruments for different clinical and anatomical situations. Research Aim: The aim of this work is to study and discuss the impact of heat treatment developments on the properties of endodontic NiTi files, with the ultimate goal of providing ways to adapt these files to the anatomical features of dental roots. Methodology: This study involves both clinical cases and extensive bibliographic research. Findings: The study highlights the importance of heat treatment in the design and manufacture of NiTi files, as it significantly affects their physical and mechanical properties. It also provides insights into the ways in which NiTi files can be adapted to the complex geometries of dental roots for more effective endodontic treatments. Theoretical Importance: Theoretical implications of this study include a better understanding of the relationship between heat treatment and the properties of NiTi files, leading to improvements in both their manufacturing methods and clinical applications. Data Collection and Analysis Procedures: The data for this study was collected through clinical cases and an extensive review of relevant literature. Analysis was performed through qualitative and quantitative methods, examining the impact of heat treatment on the physical and mechanical properties of NiTi files. Questions Addressed: This study aims to answer questions concerning the properties of NiTi files and the impact of heat treatment on their behavior. It also seeks to examine ways in which these files can be adapted to complex dental root geometries for more effective endodontic treatments. Conclusion: In conclusion, this study emphasizes the importance of heat treatment in the design and manufacture of NiTi files, as it significantly impacts their physical and mechanical properties. Further research is necessary to explore additional methods for adapting NiTi files to the unique anatomies of dental roots to improve endodontic treatments further. Ultimately, this study provides valuable insights into the continued evolution of endodontic treatment and instrument design.

Keywords: endodontic files, nickel-titanium, tooth anatomy, heat treatment

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Authors: Ramona-Niculina Jurcau, Ioana-Marieta Jurcau

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Background: Preparing in the stress field (SF) is, increasingly, a concern for doctors of different specialties. Aims: The aim was to evaluate the importance of an e-learning program for doctors postgraduate courses, in SF. Methods: Doctors (n= 40 male, 40 female) of different specialties and ages (31-71 years), who attended postgraduate courses in SF, voluntarily responded to a questionnaire that included the following themes: Importance of SF courses for specialty practiced by each respondent doctor (using visual analogue scale, VAS); What SF themes would be indicated as e-learning (EL); Preferred form of SF information assimilation: Classical lectures (CL), EL or a combination of these methods (CL+EL); Which information on the SF course are facilitated by EL model versus CL; In their view which are the first four advantages and the first four disadvantages of EL compared to CL, for SF. Results: To most respondents, the SF courses are important for the specialty they practiced (VAS by an average of 4). The SF themes suggested to be done as EL were: Stress mechanisms; stress factor models for different medical specialties; stress assessment methods; primary stress management methods for different specialties. Preferred form of information assimilation was CL+EL. Aspects of the course facilitated by EL versus CL model: Active reading of theoretical information, with fast access to keywords details; watching documentaries in everyone's favorite order; practice through tests and the rapid control of results. The first four EL advantages, mentioned for SF were: Autonomy in managing the time allocated to the study; saving time for traveling to the venue; the ability to read information in various contexts of time and space; communication with colleagues, in good times for everyone. The first three EL disadvantages, mentioned for SF were: It decreases capabilities for group discussion and mobilization for active participation; EL information accession may depend on electrical source or/and Internet; learning slowdown can appear, by temptation of postponing the implementation. Answering questions was partially influenced by the respondent's age and genre. Conclusions: 1) Post-graduate courses in SF are of interest to doctors of different specialties. 2) The majority of participating doctors preferred EL, but combined with CL (CL+EL). 3) Preference for EL was manifested mainly by young or middle age men doctors. 4) It is important to balance the proper formula for chosen EL, to be the most efficient, interesting, useful and agreeable.

Keywords: stress field, doctors’ postgraduate courses, classical lectures, e-learning lecture

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Authors: Mohamed Korany, Azza Gazy, Essam Khamis, Marwa Adel, Miranda Fawzy

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Background: Two new, simple and specific methods; First, a Zero-crossing first-derivative technique and second, a chemometric-assisted spectrophotometric artificial neural network (ANN) were developed and validated in accordance with ICH guidelines. Both methods were used for the simultaneous estimation of the two closely related antioxidant nutraceuticals ; Coenzyme Q10 (Q) ; also known as Ubidecarenone or Ubiquinone-10, and Vitamin E (E); alpha-tocopherol acetate, in their pharmaceutical binary mixture. Results: For first method: By applying the first derivative, both Q and E were alternatively determined; each at the zero-crossing of the other. The D1 amplitudes of Q and E, at 285 nm and 235 nm respectively, were recorded and correlated to their concentrations. The calibration curve is linear over the concentration range of 10-60 and 5.6-70 μg mL-1 for Q and E, respectively. For second method: ANN (as a multivariate calibration method) was developed and applied for the simultaneous determination of both analytes. A training set (or a concentration set) of 90 different synthetic mixtures containing Q and E, in wide concentration ranges between 0-100 µg/mL and 0-556 µg/mL respectively, were prepared in ethanol. The absorption spectra of the training sets were recorded in the spectral region of 230–300 nm. A Gradient Descend Back Propagation ANN chemometric calibration was computed by relating the concentration sets (x-block) to their corresponding absorption data (y-block). Another set of 45 synthetic mixtures of the two drugs, in defined range, was used to validate the proposed network. Neither chemical separation, preparation stage nor mathematical graphical treatment were required. Conclusions: The proposed methods were successfully applied for the assay of Q and E in laboratory prepared mixtures and combined pharmaceutical tablet with excellent recoveries. The ANN method was superior over the derivative technique as the former determined both drugs in the non-linear experimental conditions. It also offers rapidity, high accuracy, effort and money saving. Moreover, no need for an analyst for its application. Although the ANN technique needed a large training set, it is the method of choice in the routine analysis of Q and E tablet. No interference was observed from common pharmaceutical additives. The results of the two methods were compared together

Keywords: coenzyme Q10, vitamin E, chemometry, quantitative analysis, first derivative spectrophotometry, artificial neural network

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Authors: Li Zhang, Yuehong Su

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Lightpipe as a mature solar light tube technique has been employed worldwide. Accurately assessing the performance of lightpipe and evaluate daylighting available has been a challenging topic. Previous research had used regression model and computational simulation methods to estimate the performance of lightpipe. However, due to the nonlinear nature of solar light transferring in lightpipe, the methods mentioned above express inaccurate and time-costing issues. In the present study, a neural network model as an alternative method is investigated to predict the transmittance of lightpipe. Four types of commercial lightpipe with bended angle 0°, 30°, 45° and 60° are discussed under clear, intermediate and overcast sky conditions respectively. The neural network is generated in MATLAB by using the outcomes of an optical software Photopia simulations as targets for networks training and testing. The coefficient of determination (R²) for each model is higher than 0.98, and the mean square error (MSE) is less than 0.0019, which indicate the neural network strong predictive ability and the use of the neural network method could be an efficient technique for determining the performance of lightpipe.

Keywords: neural network, bended lightpipe, transmittance, Photopia

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Authors: Zandi Ahmad, Sokhanguei Yahya, Saboonchi Reza

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Objective: The new and modern lifestyle, especially in the twenty-first century and lack of movement in spinal structure have made patients and the physicians in the field of health and also other insurance companies in the developed and developing countries worry more than before about the abnormalities of spinal column- this great healthcare problem. The high prevalence of spinal column in all age groups -from children to adults- and in all professions have led the researchers to the idea of giving an opportunity to all those who worry about the dangers threatening the spinal column. Therefore, one of the corrective methods for these patients is using SEAS exercises. Materials and Methods: This study aims at investigating the effect of one-period of SEAS exercises on some spinal biomechanical and postural parameters in the students with idiopathic scoliosis. According to the nature of the study and research objectives as well as the data collection methods, the current research is a semi-empirical survey. The research population is comprised of students with idiopathic scoliosis. A total number of 30 students were selected using available sampling and divided into two groups of control and SEAS exercises. Scoliometer was used for data collection. Descriptive statistics were used to categorize the findings. Kolmogorov-Smirnov statistical models were used to confirm that the distribution of the data is normal and T-test was used for effectiveness. Hypothesis testing was done using SPSS21. Conclusion: Results show that SEAS exercises have a significant effect in Adam’s Test. Therefore, according to the obtained results, SEAS exercises can be used to recover idiopathic scoliosis among the students. Further studies in larger samples and treatment, periods as well as more follow-up investigations appear to be essential to prove these effects.

Keywords: SEAS exercises, idiopathic scoliosis, Adam’s test, exercise

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Authors: Hamed Sarbazy, Zohre Gholipour Haftkhani, Ali Safari, Pejman Hosseiniun

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Scientific and industrial progress in the past two decades has resulted in energy distribution systems based on power electronics, as an enabling technology in various industries and building management systems can be considered. Grading and standardization module power electronics systems and its use in a distributed control system, a strategy for overcoming the limitations of using this system. The purpose of this paper is to investigate strategies for scheduling and control structure of standard modules is a power electronic systems. This paper introduces the classical control methods and disadvantages of these methods will be discussed, The hierarchical control as a mechanism for distributed control structure of the classification module explains. The different levels of control and communication between these levels are fully introduced. Also continue to standardize software distribution system control structure is discussed. Finally, as an example, the control structure will be presented in a DC distribution system.

Keywords: application management, hardware management, power electronics, building blocks

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Authors: Mohammad Ali Badri, Pouya Molana, Amin Rezvanpour

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In this paper, planning catamaran and mono-hull vessels resistance and trim in calm waters were considered. Hydrodynamic analysis of fast mono-hull planning vessel was also investigated. In order to hull form geometry optimization, numerical methods of different parameters were used for this type of vessels. Hull material was selected in carbon fiber composite. Exact architectural aspects were specified and stability calculations were performed as well. Hydrodynamic calculations to extract the resistance force using semi-analytical methods and numerical modeling were carried out. Free surface numerical analysis of vessel in designed draft using finite volume method and double phase were evaluated and verified by experimental tests.

Keywords: fast vessel, hydrostatic and hydrodynamic optimization, free surface flow, computational fluid dynamics

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Authors: Faizah Almalki, Simeon Gill, Steve G. Hayes, Lisa Taylor

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A core element of cultural identity is the traditional costumes that provide insight into the heritage that has been acquired over time. This heritage is apparent in the use of colour, the styles and the functions of the clothing and it also reflects the skills of those who created the items and the time taken to produce them. Modern flat pattern drafting methods for making garment patterns are simple in comparison to the relatively laborious traditional approaches that would require personal interaction with the wearer throughout the production process. The current study reflects on the main elements of the pattern cutting system and how this has evolved in Saudi Arabia to affect the design of the Sawan garment. Analysis of the traditional methods for constructing Sawan garments was undertaken through observation of the practice and the garments and consulting documented guidance. This provided a foundation through which to explore how modern technology can be applied to improve the process. In this research, modern methods are proposed for producing traditional Saudi garments more efficiently while retaining elements of the conventional style and design. The current study has documented the vital aspects of Sawan garment style. The result showed that the method had been used to take the body measurements and pattern making was elementary and offered simple geometric shape and the Sawan garment is composed of four pieces. Consequently, this research allows for classical pattern shapes to be embedded in garments now worn in Saudi Arabia and for the continuation of cultural heritage.

Keywords: traditional Sawan garment technique, modern pattern cutting technique, the shape of the garment and software, Lectra Modaris

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Authors: Aladdin Al-Tarawneh

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The Quran, as it is the sacred book of Islam and considered the literal word of God (Allah) in Arabic, is highly translated into many languages; however, the foreignising or the literal approach excessively stains the quality and discredits the final product in the eyes of its receptors. Such an approach fails to capture the intended meaning of the Quran and to communicate it in any language. Therefore, this study is conducted to propose a different approach that seeks involving other ones according to a hybrid model. Indeed, this study challenges the binary adherence that is highly used in Translation Studies (TS) in general and in the translation of the Quran in particular. Drawing on the genuine fact that the Quran can be communicated in any language in terms of meaning, and the translation is not sacred; this paper approaches the translation of the Quran by blending different methods like domestication or foreignisation in a systematic way, avoiding the binary choice made by many translators. To reach this aim, the paper has a conceptual part that seeks to elucidate and clarify the main methods employed in TS, and criticise and modify them to propose the new hybrid approach (the hybrid model) for translating the Quran – that is, the deductive method. To support and validate the outcome of the previous part, a comparative model is employed in order to highlight the differences between the suggested translation and other widely used ones – that is, the inductive method. By applying this methodology, the paper proves that there is a deficiency of communicating the original meaning of the Quran in light of the foreignising approach. In conclusion, the paper suggests producing a Quran translation has to take into account the adoption of many techniques to express the meaning of the Quran as understood in the original, and to offer this understanding in English in the most native-like manner to serve the intended target readers.

Keywords: Quran translation, hybrid approach, domestication, foreignization, hybrid model

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Authors: Ada Adoga James

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This paper discussed the concept of community participation and identified tertiary education problems; strategies and methods communities could be involved to reduce conflict witnessed in our tertiary institutions of learning due to government inability to fund education. The paper pointed out that community participation through the use of Parent Teachers Association (PTA), age grade, traditional leaders, village based associations, religious and political organs could be sensitized to raise financial resources. The paper identified different sources of conflicts, the outcome of which causes prolonged academic activities, destruction of lives and properties and in some cased render school environment completely insecure for serious academic activities. It recommends involvement of community participation in assisting government, proper handling of tertiary institutions in management, and more democratic procedure in conflict resolution like cordial relationship between staff, students and trade unions in decision making process.

Keywords: community, conflict resolution, tertiary education, psychology, psychiatry

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Authors: Belkacem Laimouche

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With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

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Authors: Seyed Mehran Kazemi, Bahare Fatemi

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Sudoku is a logic-based combinatorial puzzle game which is popular among people of different ages. Due to this popularity, computer softwares are being developed to generate and solve Sudoku puzzles with different levels of difficulty. Several methods and algorithms have been proposed and used in different softwares to efficiently solve Sudoku puzzles. Various search methods such as stochastic local search have been applied to this problem. Genetic Algorithm (GA) is one of the algorithms which have been applied to this problem in different forms and in several works in the literature. In these works, chromosomes with little or no information were considered and obtained results were not promising. In this paper, we propose a new way of applying GA to this problem which uses more-informed chromosomes than other works in the literature. We optimize the parameters of our GA using puzzles with different levels of difficulty. Then we use the optimized values of the parameters to solve various puzzles and compare our results to another GA-based method for solving Sudoku puzzles.

Keywords: genetic algorithm, optimization, solving Sudoku puzzles, stochastic local search

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Authors: Sajedeh Salehi, Marco Giacalone

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This paper examines the role of existing online dispute resolution (ODR) mechanisms and their effects on ameliorating access to justice – as a protected right by Art. 47 of the EU Charter of Fundamental Rights – for consumers in EU. The major focus of this study will be on evaluating ODR as the means of dispute resolution for Business-to-Consumer (B2C) cross-border small claims raised in e-commerce transactions. The authors will elaborate the consequences of implementing ODR methods in the context of recent developments in EU regulatory safeguards on promoting consumer protection. In this analysis, both non-judiciary and judiciary ODR redress mechanisms are considered, however, the significant consideration is given to – obligatory and non-obligatory – judiciary ODR methods. For that purpose, this paper will particularly investigate the impact of the EU ODR platform as well as the European Small Claims Procedure (ESCP) Regulation 861/2007 and their role on accelerating the access to justice for consumers in B2C e-disputes. Although, considerable volume of research has been carried out on ODR for consumer claims, rather less (or no-) attention has been paid to provide a combined doctrinal and empirical evaluation of ODR’s potential in resolving cross-border small e-disputes, in EU. Hence, the methodological approach taken in this study is a mixed methodology based on qualitative (interviews) and quantitative (surveys) research methods which will be mainly based on the data acquired through the findings of the Small Claims Analysis Net (SCAN) project. This project contributes towards examining the ESCP Regulation implementation and efficiency in providing consumers with a legal watershed through using the ODR for their transnational small claims. The outcomes of this research may benefit both academia and policymakers at national and international level.

Keywords: access to justice, consumers, e-commerce, small e-Disputes

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

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

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

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Authors: Yoftahe Nigussie Worku

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This research focuses on advancing fire tube boiler technology by systematically optimizing design parameters to achieve efficient saturated steam production. The main objective is to design a high-performance boiler with a production capacity of 2000kg/h at a 12-bar design pressure while minimizing costs. The methodology employs iterative analysis, utilizing relevant formulas, and considers material selection and production methods. The study successfully results in a boiler operating at 85.25% efficiency, with a fuel consumption rate of 140.37kg/hr and a heat output of 1610kW. Theoretical importance lies in balancing efficiency, safety considerations, and cost minimization. The research addresses key questions on parameter optimization, material choices, and safety-efficiency balance, contributing valuable insights to fire tube boiler design.

Keywords: safety consideration, efficiency, production methods, material selection

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Authors: Mokhtar Nikgoo

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Definition of bridge: A bridge is a structure that allows people to pass through the communication road with two points. There are many different types of bridges, each of which is designed to perform a specific function. This article introduces the concept, history, components, uses, types, construction methods, selected factors, damage factors and principles of bridge maintenance. A bridge is a structure to cross a passage such as a water, valley or road without blocking another path underneath. This structure makes it possible to pass obstacles that are difficult or impossible to pass. There are different designs for bridge construction, each of which is used for a particular function and condition. In the old definition, a bridge is an arch over a river, valley, or any type of passage that makes traffic possible. But today, in the topic of urban management, the bridge is considered as a structure to cross physical barriers, so that while using space (not just the surface of the earth), it can facilitate the passage and access to places. The useful life of bridges may be between 30 and 80 years depending on the location and the materials used. But with proper maintenance and improvement, their life may last for hundreds of years.

Keywords: bridge, road construction, surveying, transportation

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Authors: Adnan M. Al Assaf

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This research project aims to assess the methods of enhancing tolerant thinking and behavior among Muslim societies. This is in addition to spreading the anti-terrorist approach in their communities. The critical assessment for the Islamic major texts in question is the selected way for convincing, as Muslims adopt these sources as the authentic references for their lives and cultures. Moreover, this research devotes a special room to the analysis of the royal ‘Amman Message’ as a contemporary Islamic approach for enhancing tolerance and anti-terrorism from an Islamic perspective. The paper includes the study of the related concepts, texts, practical applications, with some reference to the history of Islam in human interaction, accepting the others, mercy with minorities, protecting human rights. Furthermore, it assesses the methods of enhancing tolerance and minimizing the terrorist thinking and behavior practically, in the view of Amman message, as well.

Keywords: Islam, tolerance, anti-terrorism, coexistence, Amman Message

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Authors: Frederik Calsius, Mirela Popa, Alexia Briassouli

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In the field of machine learning, it is common practice to use benchmark datasets to prove the working of a method. The domain of action recognition in videos often uses datasets like Kinet-ics, Something-Something, UCF-101 and HMDB-51 to report results. Considering the properties of the datasets, there are no datasets that focus solely on very short clips (2 to 3 seconds), and on highly-similar fine-grained actions within one specific domain. This paper researches how current state-of-the-art action recognition methods perform on a dataset that consists of highly similar, fine-grained actions. To do so, a dataset of skateboarding tricks was created. The performed analysis highlights both benefits and limitations of state-of-the-art methods, while proposing future research directions in the activity recognition domain. The conducted research shows that the best results are obtained by fusing RGB data with OpenPose data for the Temporal Shift Module.

Keywords: activity recognition, fused deep representations, fine-grained dataset, temporal modeling

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Authors: Maxwell Henderson, Tristan Cook, Justin Chan Jin Le, Mark Hodson, YoungJung Chang, John Novak, Daniel Padilha, Nishan Kulatilaka, Ansu Bagchi, Sanjoy Ray, John Kelly

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We present a method of using adiabatic quantum optimization (AQO) to solve a mixed integer nonlinear programming (MINLP) problem instance. The MINLP problem is a general form of a set of NP-hard optimization problems that are critical to many business applications. It requires optimizing a set of discrete and continuous variables with nonlinear and potentially nonconvex constraints. Obtaining an exact, optimal solution for MINLP problem instances of non-trivial size using classical computation methods is currently intractable. Current leading algorithms leverage heuristic and divide-and-conquer methods to determine approximate solutions. Creating more accurate and efficient algorithms is an active area of research. Quantum computing (QC) has several theoretical benefits compared to classical computing, through which QC algorithms could obtain MINLP solutions that are superior to current algorithms. AQO is a particular form of QC that could offer more near-term benefits compared to other forms of QC, as hardware development is in a more mature state and devices are currently commercially available from D-Wave Systems Inc. It is also designed for optimization problems: it uses an effect called quantum tunneling to explore all lowest points of an energy landscape where classical approaches could become stuck in local minima. Our work used a novel algorithm formulated for AQO to solve a special type of MINLP problem. The research focused on determining: 1) if the problem is possible to solve using AQO, 2) if it can be solved by current hardware, 3) what the currently achievable performance is, 4) what the performance will be on projected future hardware, and 5) when AQO is likely to provide a benefit over classical computing methods. Two different methods, integer range and 1-hot encoding, were investigated for transforming the MINLP problem instance constraints into a mathematical structure that can be embedded directly onto the current D-Wave architecture. For testing and validation a D-Wave 2X device was used, as well as QxBranch’s QxLib software library, which includes a QC simulator based on simulated annealing. Our results indicate that it is mathematically possible to formulate the MINLP problem for AQO, but that currently available hardware is unable to solve problems of useful size. Classical general-purpose simulated annealing is currently able to solve larger problem sizes, but does not scale well and such methods would likely be outperformed in the future by improved AQO hardware with higher qubit connectivity and lower temperatures. If larger AQO devices are able to show improvements that trend in this direction, commercially viable solutions to the MINLP for particular applications could be implemented on hardware projected to be available in 5-10 years. Continued investigation into optimal AQO hardware architectures and novel methods for embedding MINLP problem constraints on to those architectures is needed to realize those commercial benefits.

Keywords: adiabatic quantum optimization, mixed integer nonlinear programming, quantum computing, NP-hard

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Authors: Weichen Chang

Abstract:

To create a guided teaching method for AI generative drawing design, this paper develops a set of teaching models for AI generative drawing (DCAI), which combines learning modes such as problem-solving, thematic inquiry, phenomenon-based, task-oriented, and DFC . Through the information security AI picture book learning guided programs and content, the application of participatory action research (PAR) and interview methods to explore the dual knowledge of Context and ChatGPT (DCAI) for AI to guide the development of students' AI learning skills. In the interviews, the students highlighted five main learning outcomes (self-study, critical thinking, knowledge generation, cognitive development, and presentation of work) as well as the challenges of implementing the model. Through the use of DCAI, students will enhance their consensus awareness of generative mapping analysis and group cooperation, and they will have knowledge that can enhance AI capabilities in DCAI inquiry and future life. From this paper, it is found that the conclusions are (1) The good use of DCAI can assist students in exploring the value of their knowledge through the power of stories and finding the meaning of knowledge communication; (2) Analyze the transformation power of the integrity and coherence of the story through the context so as to achieve the tension of ‘starting and ending’; (3) Use ChatGPT to extract inspiration, arrange story compositions, and make prompts that can communicate with people and convey emotions. Therefore, new knowledge construction methods will be one of the effective methods for AI learning in the face of artificial intelligence, providing new thinking and new expressions for interdisciplinary design and design education practice.

Keywords: artificial intelligence, task-oriented, contextualization, design education

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Authors: Michal Friedrich

Abstract:

Cross-border investment has never been easier than in today’s global economy. Despite recent initiatives tightening the international tax landscape, profit shifting and tax optimization by multinational entities (MNEs) in the context of cross-border M&A remain persistent and complex phenomena that warrant in-depth exploration. By synthesizing the outcomes of existing research, this study aims to first provide a methodological framework for identifying MNEs’ profit-shifting behavior and quantifying its fiscal impacts via various macroeconomic and microeconomic approaches. The study also proposes additional methods and qualitative/quantitative measures for extracting insight into the profit shifting behavior of MNEs in the context of their M&A activities at industry and entity levels. To develop the proposed methods, this study applies the knowledge of international tax laws and known profit shifting conduits (incl. dividends, interest, and royalties) on several model cases/types of cross-border acquisitions and post-acquisition integration activities by MNEs and highlights important factors that encourage or discourage tax optimization. Follow-up research is envisaged to apply the methods outlined in this study on published data on real-world M&A transactions to gain practical country-by-country, industry and entity-level insights. In conclusion, this study seeks to contribute to the ongoing discourse on profit shifting by providing a methodological toolkit for exploring profit shifting tendencies MNEs in connection with their M&A activities and to serve as a backbone for further research. The study is expected to provide valuable insight to policymakers, tax authorities, and tax professionals alike.

Keywords: BEPS, cross-border M&A, international taxation, profit shifting, tax optimization

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Authors: Kamel Agroui, George Collins, Rydha Yaiche

Abstract:

The objective of this study is to better understand the thermal characteristics and molecular behaviour of cured EVA before and after outdoor exposure. Thermal analysis methods as DSC, TSC and DMTA studies were conducted on EVA material. DSC experiments on EVA show a glass transition at about -33.1° C which is characteristic of crystalline phase and an endothermic peak at temperature of 55 °C characteristic of amorphous phase. The magnitude of the integrated temperature DSC peak for EVA is 14.4 J/g. The basic results by TSC technique is that there are two relaxations that are reproducibly observed in cured EVA encapsulant material. At temperature polarization 85°C, a low temperature relaxation occurs at –24.4°C and a high temperature relaxation occurs at +30.4ºC. DMTA results exhibit two tan peaks located at -14.9°C and +66.6°C. After outdoor exposure cured EVA by DSC analysis revealed two endothermic peaks due to post crystallization phenomenon and TSC suggests that prolonged exposure selectively effects the poly(vinyl acetate)-rich phase, with much less impact on the polyethylene-rich phase.

Keywords: EVA, encapsulation process, PV module, thermal analysis, quality control

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