Search results for: natuaral language processing

Authors: Ranveet Saggu, Saad Bin Ahmed

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Cardiovascular Disease (CVD) is the leading cause of death worldwide. One of its main manifestations, myocardial infarction (commonly known as a heart attack), occurs about 750,000 times a year, caused by insufficient blood flow to a portion of the heart muscle. A quick and accurate diagnosis of a heart attack or heart failure is crucial in the treatment of the patient. The aim of this research project is to improve the prediction of cardiovascular diseases by automating risk assessment using binary classifiers. The methodology includes Exploratory Data Analysis (EDA), which helps to obtain information about the dataset with the help of visualizations and metrics. Additionally, Feature Engineering techniques is employed to address missing values, outliers, feature extraction, and normalizing the dataset. Subsequently, various classification machine learning algorithms are trained, and their accuracy along with other metrics are evaluated to identify the most efficient model in terms of processing time and predictive performance.

Keywords: cardiovascular disease, machine learning, deci- sion trees, logistic regression, k-nearest neighbor, xgboost, random forest, gradient boosting

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Authors: Ramim Tanver Rahman, Muhammad Mahbub Sobhan, M. A. Alim

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This study reports on processing of biscuits using skinned, treated and dried cassava flour. Five samples of biscuits S2, S3, S4, S5, and S6 containing 8, 16, 24, 32, and 40% cassava flour with wheat flour and a control sample (S1) containing no cassava flour were processed. The weights of all the biscuit samples were higher than that of control biscuit. The biscuit containing cassava flour was lower width than the control biscuit. The spread ratio of biscuits with 16% cassava flour was higher than other combinations of cassava flour. No remarkable changes in moisture content, peroxide value, fatty acid value, texture, and flavor were observed up to 4 months of storage in ambient conditions (27° to 35°C). A decreasing trend in color, flavor, texture and overall acceptability was observed with the increased incorporation of cassava flour. The sample S1 (no cassava flour) secured the highest overall acceptability and sample S6 (40% cassava flour) obtained the lowest overall acceptability. It is recommended that good quality cassava flour fortified biscuits may be processed in industrial-scale substituting the wheat flour by cassava flour up to 24% levels.

Keywords: cassava flour, wheat flour, shelf life, spread ratio, storage, biscuit

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Authors: Harshkumar K. Desai, Anuj K. Desai, Jay P. Patel, Snehal V. Trivedi, Yogendrasinh Parmar

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The need of continuous improvement in a product or process in this era of global competition leads to apply value engineering for functional and aesthetic improvement in consideration with economic aspect too. Solar industries located at G.I.D.C., Makarpura, Vadodara, Gujarat, India; a manufacturer of variety of CNC Machines had a challenge to analyze the structural design of column, base, carriage and table of CNC Milling Machine in the account of reduction of overall weight of a machine without affecting the rigidity and accuracy at the time of operation. The identified task is the first attempt to validate and optimize the proposed design of ribbed structure statically using advanced modeling and analysis tools in a systematic way. Results of stress and deformation obtained using analysis software are validated with theoretical analysis and found quite satisfactory. Such optimized results offer a weight reduction of the final assembly which is desired by manufacturers in favor of reduction of material cost, processing cost and handling cost finally.

Keywords: CNC milling machine, optimization, finite element analysis (FEA), weight reduction

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

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Authors: Elifcan Oztekin

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Compliment response strategies in cross-linguistic contexts have received a considerable amount of interest in sociolinguistic research in various language settings. In this respect, a common finding of these studies indicates that speakers of different languages employ different patterns in strategies to respond to compliments. This has triggered varying theoretical approaches to compliment responses within theories of politeness and the universality of speech acts. In the light of previous studies, the present study investigates compliment response strategies that Turkish-English bilingual university students use in English and Turkish response conditions through a cross-linguistic discourse completion task and interviews. Data were analyzed using Holmes’ (1988) taxonomy and the results indicate a similar pattern to what has been observed in Turkish compliments responses in previous research. Turkish-English comparisons also display noticeable similarities in macro-level strategies, while subtle differences in micro-level strategies were also observed.

Keywords: compliment response strategies, cross-cultural differences, bilingualism, sociolinguistics

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Authors: Abdel Rahman Altakhaineh, Mohamma Alaghawat, Hiba Alhendi

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This paper reports an investigation of the comprehension of English compound nouns by sixty Arabic-speaking English Foreign Language (EFL) learners majoring in English at the University of Jordan, Amman. The investigation focused on the problems that these learners may encounter in understanding certain types of compounds and their ability to use their L1 compound noun knowledge to produce the meaning of L2 compound nouns. Participants whose English proficiency level was advanced underwent a test to identify the meaning ofan underlined compound without using a dictionary. Theresponses to the three different types of compounds were analyzed usingTwo-Way repeated measures ANOVA, and the results showed that there were different endocentric and exocentric compound responses within subordinative compounds, with a statistically significant difference between the two in favor of endocentric compounds. We argue that the endocentric, especially subordinative endocentric compounds,weremore easily understood due to its representative nature, i.e., because the head represents the meaning of the whole compound. The study concludes with pedagogical implications for teaching compound nouns.

Keywords: morphology, compounding, SLA, arabic-speaking EFL learners

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Authors: A. Hamma, A. Pegoretti

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The paper focuses on the evaluation of mechanical performances and viscoelastic behaviour of starch-grafted-PP reinforced with kenaf fibres. Investigations were carried out on composites prepared by melt compounding and compression molding. Two aspects have been taken into account, the effects of various fibres loading rates (10, 20 and 30 wt.%) and the fibres aspect ratios (L/D=30 and 160). Good fibres/matrix interaction has been evidenced by SEM observations. However, processing induced variation of fibre length quantified by optical microscopy observations. Tensile modulus and ultimate properties, hardness and tensile impact stress, were found to remarkably increase with fibre loading. Moreover, short term tensile creep tests have proven that kenaf fibres improved considerably the creep stability. Modelling of creep behaviour by a four parameter Burger model was successfully used. An empirical equation involving Halpin-Tsai semi empirical model was also used to predict the elastic modulus of composites.

Keywords: mechanical properties, creep, fibres, thermoplastic composites, starch-grafted-PP

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Authors: Osiris Terry, Kenneth Hopkinson, Laura Humphrey

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Systematic resampling is the most popularly used resampling method in particle filters. This paper seeks to further the understanding of systematic resampling by defining a formula made up of variables from the sampling equation and the particle weights. The formula is then verified via SPARK, a software verification language. The verified systematic resampling formula states that the minimum/maximum number of possible samples taken of a particle is equal to the floor/ceiling value of particle weight divided by the sampling interval, respectively. This allows for the creation of a randomness spectrum that each resampling method can fall within. Methods on the lower end, e.g., systematic resampling, have less randomness and, thus, are quicker to reach an estimate. Although lower randomness allows for error by having a larger bias towards the size of the weight, having this bias creates vulnerabilities to the noise in the environment, e.g., jamming. Conclusively, this is the first step in characterizing each resampling method. This will allow target-tracking engineers to pick the best resampling method for their environment instead of choosing the most popularly used one.

Keywords: SPARK, software verification, resampling, systematic resampling, particle filter, tracking

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Authors: Miroslav Popelka, Jakub Nozicka

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The whole work is based on possibility to use Lego Mindstorms robotics systems to reduce costs. Lego Mindstorms consists of a wide variety of hardware components necessary to simulate, programme and test of robotics systems in practice. To programme algorithm, which simulates space using the ultrasonic sensor, was used development environment supplied with kit. Software Matlab was used to render values afterwards they were measured by ultrasonic sensor. The algorithm created for this paper uses theoretical knowledge from area of signal processing. Data being processed by algorithm are collected by ultrasonic sensor that scans 2D space in front of it. Ultrasonic sensor is placed on moving arm of robot which provides horizontal moving of sensor. Vertical movement of sensor is provided by wheel drive. The robot follows map in order to get correct positioning of measured data. Based on discovered facts it is possible to consider Lego Mindstorm for low-cost and capable kit for real-time modelling.

Keywords: LEGO Mindstorms, ultrasonic sensor, real-time modeling, 2D object, low-cost robotics systems, sensors, Matlab, EV3 Home Edition Software

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Authors: Muna F. Al-Sammaraie

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The aim of this research is to present a multi spectral image enhancement methods used to achieve highly real digital image populates only a small portion of the available range of digital values. Also, a quantitative measure of image enhancement is presented. This measure is related with concepts of the Webers Low of the human visual system. For decades, several image enhancement techniques have been proposed. Although most techniques require profuse amount of advance and critical steps, the result for the perceive image are not as satisfied. This study involves changing the original values so that more of the available range is used; then increases the contrast between features and their backgrounds. It consists of reading the binary image on the basis of pixels taking them byte-wise and displaying it, calculating the statistics of an image, automatically enhancing the color of the image based on statistics calculation using algorithms and working with RGB color bands. Finally, the enhanced image is displayed along with image histogram. A number of experimental results illustrated the performance of these algorithms. Particularly the quantitative measure has helped to select optimal processing parameters: the best parameters and transform.

Keywords: image enhancement, multi-spectral, RGB, histogram

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Authors: Ladan Surajo

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Nigeria as a third world country is full of people who cannot read and write, thereby constituting a stumbling block to the modern way of communication. It is a well known fact that Nigeria is a heterogeneous country with an estimated 450 or more ethnic groups communicating in divergent languages. Despite this scenario, English, Hausa, Igbo and Yoruba languages are predominantly used in the country. Apart from English language, Hausa has a wider coverage of usage among the indigenous languages in Nigeria, thereby using it in the area of social mobilization and conflict management cannot be overemphasized. Hausa Oral Singers are depicting their artistic and God endowed talents through singing to mobilize and sensitize the local communities about government programmes and the ills of other social problems of the society. It is the belief of this researcher that if used properly, the Hausa Oral Singers will assist immensely in reducing to the barest minimum some social ills of the society in Nigeria. More so that music is the food of the heart and has a resounding impact in changing the behaviour of individuals and groups.

Keywords: oral, singers, praise, social mobilization, conflict management

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

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The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

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Authors: Yu Liang, Wei Wei

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Spatial representation of numbers and numerical magnitude are important for preschoolers’ mathematical ability. Mental number line, a typical index to measure numbers spatial representation, and numerical comparison are both related to arithmetic obviously. However, they seem to rely on different mechanisms and probably influence arithmetic through different mechanisms. In line with this idea, preschool children were trained with two tasks to investigate which one is more important for approximate arithmetic. The training of numerical processing and number line estimation were proved to be effective. They both improved the ability of approximate arithmetic. When the difficulty of approximate arithmetic was taken into account, the performance in number line training group was not significantly different among three levels. However, two harder levels achieved significance in numerical comparison training group. Thus, comparing spatial representation ability, symbolic approximation arithmetic relies more on numerical magnitude. Educational implications of the study were discussed.

Keywords: approximate arithmetic, mental number line, numerical magnitude, preschooler

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Authors: Ericson O. Alieto, Aprillete C. Devanadera

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The main objective of the study is to determine the dominant speech acts in five commemorative speeches of President Duterte. This study employed Speech Act Theory and Discourse analysis to determine how the speech acts features connote the pragmatic meaning of Duterte’s speeches. Identifying the speech acts is significant in elucidating the underlying message or the pragmatic meaning of the speeches. From the 713 sentences or utterances from the speeches, assertive with 208 occurrences from the corpus or 29% is the dominant speech acts. It was followed by expressive with 177 or 25% occurrences, directive accounts for 152 or 15% occurrences. While commisive accounts for 104 or 15% occurrences and declarative got the lowest percentage of occurrences with 72 or 10% only. These sentences when uttered by Duterte carry a certain power of language to move or influence people. Thus, the present study shows the fundamental message perceived by the listeners. Moreover, the frequent use of assertive and expressive not only explains the pragmatic message of the speeches but also reflects the personality of President Duterte.

Keywords: commemorative speech, discourse analysis, duterte, pragmatics

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Authors: A. Şahinoğlu, R. Gürbüz, A. Güllü, M. Karhan

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This study in production machines, it is aimed that machine will automatically perceive cutting data and alter cutting parameters. The two most important parameters have to be checked in machine control unit are progress feed rate and speeds. These parameters are aimed to be controlled by sounds of machine. Optimum sound’s features introduced to computer. During process, real time data is received and converted by Matlab software. Data is converted into numerical values. According to them progress and speeds decreases/increases at a certain rate and thus optimum sound is acquired. Cutting process is made in respect of optimum cutting parameters. During chip remove progress, features of cutting tools, kind of cut material, cutting parameters and used machine; affects on various parameters. Instead of required parameters need to be measured such as temperature, vibration, and tool wear that emerged during cutting process; detailed analysis of the sound emerged during cutting process will provide detection of various data that included in the cutting process by the much more easy and economic way. The relation between cutting parameters and sound is being identified.

Keywords: cutting process, sound processing, intelligent late, sound analysis

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Authors: Abdessalam Hijab, Hafida Boulekbache, Eric Henry

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The objective of this article is to explain the use of geographic information system (GIS) and information and communication technologies (ICTs) in the real-time processing and analysis of data on the status of an urban sanitation network by integrating professional actors in sanitation for sustainable management in urban areas. Indeed, it is a smart geo-collaboration based on the complementarity of ICTs and GIS. This multi-actor reflection was built with the objective of contributing to the development of complementary solutions to the existing technologies to better protect the urban environment, with the help of a checklist with the spatial reference "E-Géo-LD" dedicated to the "professional/professional" actors in sanitation, for intelligent monitoring of liquid sanitation networks in urban areas. In addition, this research provides a good understanding and assimilation of liquid sanitation schemes in the "Lamkansa" sampling area of the city of Casablanca, and spatially evaluates these schemes. Downstream, it represents a guide to assess the environmental impacts of the liquid sanitation scheme.

Keywords: ICT, GIS, spatial checklist, liquid sanitation, environment

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

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

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

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Authors: Yashas Bedre Raghavendra, Pim Vullers

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This study presents the design and implementation of an abstract cryptographic coprocessor, leveraging AMBA(Advanced Microcontroller Bus Architecture) protocols - APB (Advanced Peripheral Bus) and AHB (Advanced High-performance Bus), to enable seamless integration with the main CPU(Central processing unit) and enhance the coprocessor’s algorithm flexibility. The primary objective is to create a versatile coprocessor that can execute various cryptographic algorithms, including ECC(Elliptic-curve cryptography), RSA(Rivest–Shamir–Adleman), and AES (Advanced Encryption Standard) while providing a robust and secure solution for modern secure embedded systems. To achieve this goal, the coprocessor is equipped with a tightly coupled memory (TCM) for rapid data access during cryptographic operations. The TCM is placed within the coprocessor, ensuring quick retrieval of critical data and optimizing overall performance. Additionally, the program memory is positioned outside the coprocessor, allowing for easy updates and reconfiguration, which enhances adaptability to future algorithm implementations. Direct links are employed instead of DMA(Direct memory access) for data transfer, ensuring faster communication and reducing complexity. The AMBA-based communication architecture facilitates seamless interaction between the coprocessor and the main CPU, streamlining data flow and ensuring efficient utilization of system resources. The abstract nature of the coprocessor allows for easy integration of new cryptographic algorithms in the future. As the security landscape continues to evolve, the coprocessor can adapt and incorporate emerging algorithms, making it a future-proof solution for cryptographic processing. Furthermore, this study explores the addition of custom instructions into RISC-V ISE (Instruction Set Extension) to enhance cryptographic operations. By incorporating custom instructions specifically tailored for cryptographic algorithms, the coprocessor achieves higher efficiency and reduced cycles per instruction (CPI) compared to traditional instruction sets. The adoption of RISC-V 128-bit architecture significantly reduces the total number of instructions required for complex cryptographic tasks, leading to faster execution times and improved overall performance. Comparisons are made with 32-bit and 64-bit architectures, highlighting the advantages of the 128-bit architecture in terms of reduced instruction count and CPI. In conclusion, the abstract cryptographic coprocessor presented in this study offers significant advantages in terms of algorithm flexibility, security, and integration with the main CPU. By leveraging AMBA protocols and employing direct links for data transfer, the coprocessor achieves high-performance cryptographic operations without compromising system efficiency. With its TCM and external program memory, the coprocessor is capable of securely executing a wide range of cryptographic algorithms. This versatility and adaptability, coupled with the benefits of custom instructions and the 128-bit architecture, make it an invaluable asset for secure embedded systems, meeting the demands of modern cryptographic applications.

Keywords: abstract cryptographic coprocessor, AMBA protocols, ECC, RSA, AES, tightly coupled memory, secure embedded systems, RISC-V ISE, custom instructions, instruction count, cycles per instruction

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Authors: Jungho Moon, Lae-Jeong Park

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This paper introduces a signal monitoring program developed with a view to helping electrical engineering students get familiar with sensors with digital output. Because the output of digital sensors cannot be simply monitored by a measuring instrument such as an oscilloscope, students tend to have a hard time dealing with digital sensors. The monitoring program runs on a PC and communicates with an MCU that reads the output of digital sensors via an asynchronous communication interface. Receiving the sensor data from the MCU, the monitoring program shows time and/or frequency domain plots of the data in real time. In addition, the monitoring program provides a serial terminal that enables the user to exchange text information with the MCU while the received data is plotted. The user can easily observe the output of digital sensors and configure the digital sensors in real time, which helps students who do not have enough experiences with digital sensors. Though the monitoring program was programmed in the Matlab programming language, it runs without the Matlab since it was compiled as a standalone executable.

Keywords: digital sensor, MATLAB, MCU, signal monitoring program

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Authors: Gianni Jacucci

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Epistemology traditionally finds its place within human research philosophies and methodologies. Artificial intelligence methods pose challenges, particularly given the unresolved relationship between AI and pivotal concepts in social arenas such as hermeneutics and accountability. We begin by examining the essential criteria governing scientific rigor in the human sciences. We revisit the three foundational philosophies underpinning qualitative research methods: empiricism, hermeneutics, and phenomenology. We elucidate the distinct attributes, merits, and vulnerabilities inherent in the methodologies they inspire. The integration of AI, e.g., deep learning algorithms, sparks an interest in evaluating these criteria against the diverse forms of AI architectures. For instance, Interpreted AI could be viewed as a hermeneutic approach, relying on a priori interpretations, while straight AI may be perceived as a descriptive phenomenological approach, processing original and uncontaminated data. This paper serves as groundwork for such explorations, offering preliminary reflections to lay the foundation and outline the initial landscape.

Keywords: artificial intelligence, deep learning, epistemology, qualitative research, methodology, hermeneutics, accountability

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Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

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Authors: Gloria Chen

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In the past, when we complimented someone who had a good command of English, we would say ‘She/He speaks/writes standard English,’ or ‘His/Her English is standard.’ However, with English has becoming a ‘global language,’ many scholars and English users even create a plural form for English as ‘world Englishes,’ which indicates that national/racial varieties of English not only exist, but also are accepted to a certain degree. Now, a question will be raised when it comes to English teaching and learning: ‘What variety/varieties of English should be taught?’ This presentation will first explore Braj Kachru’s well-known categorization of the inner circle, the outer circle, and the expanding circle of English users, as well as inner circle varieties such as ‘Ebonics’ and ‘cockney’. The presentation then will discuss the purposes and contexts of English learning, and apply different approaches to different purposes and contexts. Three major purposes of English teaching/learning will be emphasized and considered: (1) communicative competence, (2) academic competence, and (3) intercultural competence. This presentation will complete with the strategies of ‘code switch’ and ‘register switch’ in teaching English to non-standard English speakers in both speaking and writing.

Keywords: world Englishes, standard and non-standard English, inner, outer, expanded circle communicative, academic, intercultural competence

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Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

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Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: bioassay, machine learning, preprocessing, virtual screen

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Authors: C. G. Jinimole, A. Harsha

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One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.

Keywords: computed tomography, enhancement techniques, increasing contrast, PSNR and MSE

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Authors: Tatyana Alexandrova, Alexandr Alexandrov, Nadezhda Nikolaeva

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A problem of complex mineral resources development is urgent and priority, it is aimed at realization of the processes of their ecologically safe development, one of its components is revealing the influence of the forms of element compounds in raw materials and in the processing products. In view of depletion of the precious metal reserves at the traditional deposits in the XXI century the large-size open cast deposits, localized in black shale strata begin to play the leading role. Carbonaceous (black) shales carry a heightened metallogenic potential. Black shales with high content of carbon are widely distributed within the scope of Bureinsky massif. According to academician Hanchuk`s data black shales of Sutirskaya series contain generally PGEs native form. The presence of high absorptive towards carbonaceous matter gold and PGEs compounds in crude ore results in decrease of valuable components extraction because of their sorption into dissipated carbonaceous matter.

Keywords: сarbonaceous rocks, bitumens, precious metals, concentration, extraction

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Authors: Junjie Peng, Jinbao Chen, Shuai Kong, Danxu Liu

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On the basis of traditional resource allocation strategies, the usage of resources on physical servers in cloud data center is great uncertain. It will cause waste of resources if the assignment of tasks is not enough. On the contrary, it will cause overload if the assignment of tasks is too much. This is especially obvious when the applications are the same type because of its resource preferences. Considering CPU intensive application is one of the most common types of application in the cloud, we studied the optimization strategy for CPU intensive applications on the same server. We used resource preferences to analyze the case that multiple CPU intensive applications run simultaneously, and put forward a model which can predict the execution time for CPU intensive applications which run simultaneously. Based on the prediction model, we proposed the method to select the appropriate number of applications for a machine. Experiments show that the model can predict the execution time accurately for CPU intensive applications. To improve the execution efficiency of applications, we propose a scheduling model based on priority for CPU intensive applications. Extensive experiments verify the validity of the scheduling model.

Keywords: cloud computing, CPU intensive applications, resource optimization, strategy

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Authors: Boudersa Said Sami

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This paper aims at revealing the new role of the African translator as a progressive traveler in the thoughts and minds of both Africans and others via his/her multidimensional translations, and a particular focus will be here on literary translation. The African translator, in this respect, is a great actor in Africa’s literary, intellectual and philosophical movement through his exploration of great literary books and highly-echoed intellectual masterpieces via translation. The paper’s hypothesis revolves around the importance of the African translator in moving from one thought to another as shifting from one language to another (French to English or English to French and Arabic). Unless the African translator is alert-minded, lively and animated, the African thoughts are stagnant and Africa is a big mire of rotten ideas. African thoughts are alive, providing that translation is vivid. The findings of the paper reveal the significance of the African translator’s multidimensional roles in keeping Africa in movement. As a pertinent recommendation, translation in Africa should be fostered and its tools should be enhanced as well to keep Africa’s thoughts in continuous mobility between geographic areas as languages are in a progressive move through translation.

Keywords: African, translator, literary, globetrotter, movement

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Authors: Eleni Karasavvidou

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Social and anthropological research, parallel to Gender Studies, highlighted the relationship between social structures and symbolic forms as an important field of interaction and recording of 'social trends.' Since the study of representations can contribute to the understanding of the social functions and power relations, they encompass. This ‘mirage,’ however, has not only to do with the representations themselves but also with the ways they are received and the film or critical narratives that are established as dominant or alternative. Cinema and the criticism of its cultural products are no exception. Even in the rapidly changing media landscape of the 21st century, movies remain an integral and widespread part of popular culture, making films an extremely powerful means of 'legitimizing' or 'delegitimizing' visions of domination and commonsensical gender stereotypes throughout society. And yet it is film criticism, the 'language per se,' that legitimizes, reinforces, rewards and reproduces (or at least ignores) the stereotypical depictions of female roles that remain common in the realm of film images. This creates the need for this issue to have emerged (also) in academic research questioning gender criteria in film reviews as part of the effort for an inclusive art and society. Qualitative content analysis is used to examine female roles in selected Oscar-nominated films against their reviews from leading websites and newspapers. This method was chosen because of the complex nature of the depictions in the films and the narratives they evoke. The films were divided into basic scenes depicting social functions, such as love and work relationships, positions of power and their function, which were analyzed by content analysis, with borrowings from structuralism (Gennette) and the local/universal images of intercultural philology (Wierlacher). In addition to the measurement of the general ‘representation-time’ by gender, other qualitative characteristics were also analyzed, such as: speaking time, sayings or key actions, overall quality of the character's action in relation to the development of the scenario and social representations in general, as well as quantitatively (insufficient number of female lead roles, fewer key supporting roles, relatively few female directors and people in the production chain and how they might affect screen representations. The quantitative analysis in this study was used to complement the qualitative content analysis. Then the focus shifted to the criteria of film criticism and to the rhetorical narratives that exclude or highlight in relation to gender identities and functions. In the criteria and language of film criticism, stereotypes are often reproduced or allegedly overturned within the framework of apolitical "identity politics," which mainly addresses the surface of a self-referential cultural-consumer product without connecting it more deeply with the material and cultural life. One of the prime examples of this failure is the Bechtel Test, which tracks whether female characters speak in a film regardless of whether women's stories are represented or not in the films analyzed. If perceived unbiased male filmmakers still fail to tell truly feminist stories, the same is the case with the criteria of criticism and the related interventions.

Keywords: representations, context analysis, reviews, sexist stereotypes

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Authors: A. Hamidi, S. Khelladi, L. Illoul, A. Tcharkhtchi

Abstract:

Reactive rotational molding (RRM) is a process to manufacture hollow plastic parts with reactive material has several advantages compared to conventional roto molding of thermoplastic powders: process cycle time is shorter; raw material is less expensive because polymerization occurs during processing and high-performance polymers may be used such as thermosets, thermoplastics or blends. However, several phenomena occur during this process which makes the optimization of the process quite complex. In this study, we have used a mixture of isocyanate and polyol as a reactive system. The chemical transformation of this system to polyurethane has been studied by thermal analysis and rheology tests. Thanks to these results of the curing process and rheological measurements, the kinetic and rheokinetik of polyurethane was identified. Smoothed Particle Hydrodynamics, a Lagrangian meshless method, was chosen to simulate reactive fluid flow in 2 and 3D configurations of the polyurethane during the process taking into account the chemical, and chemiorehological results obtained experimentally in this study.

Keywords: reactive rotational molding, simulation, smoothed particle hydrodynamics, surface tension, rheology, free surface flows, viscoelastic, interpolation

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Authors: Dalia Elleuch

Abstract:

The use of machine learning in the field of healthcare has gained tremendous momentum in recent years, with the potential to revolutionize the way diseases are diagnosed and treated. In particular, the field of machine learning in the detection of degenerative diseases through language performance analysis has shown great promise and has been the subject of a growing body of research. As Alzheimer’s Disease (AD) is among the most prevalent neurodegenerative diseases, this review is designed to investigate the effectiveness of machine learning through speech analysis techniques to analyze linguistic data from patients with AD, with the goal of detecting early signs of the disease. A corpus comprising seven comparative studies with a total number of patients (n=1054) was analyzed. The finding reveals a high degree of accuracy, ranging between 83.32% and 97.18%. This systematic review sheds light on the potential of speech analysis and machine learning in the detection of AD, highlighting the need for further development and integration into clinical practice for improved patient outcomes.

Keywords: machine learning, detection, neurodegenerative diseases, Alzheimer’s disease, speech analysis

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