Search results for: traditional and modern architecture

Authors: Satish Y. Deodhar

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Science without history is like a man without memory. The colossal history of India stores many ideas on economic ethics and public policy, which have been forgotten in the course of time. This paper is an attempt to bring to the fore contributions from ancient Indian treatises. In this context, the paper briefly summarizes alternative economic ideas such as communism, capitalism, and the holistic approach of ancient Indian writings. Thereafter, the idea of a welfare brick for an individual consisting of three dimensions -Purusharthas, Ashramas, and Varnas is discussed. Given the contours of the welfare brick, the concept of the state, its economic policies, markets, prices, interest rates, and credit are covered next. This is followed by delving into the treatment of land, property rights, guilds, and labour relations. The penultimate section summarises the economic advice offered to the head of a household in the treatise Shukranitisara. Finally, in concluding comments, the relevance of ancient Indian writings for modern times is discussed -both for pedagogy and economic policies.

Keywords: ancient Indian treatises, history of economic thought, science of political economy, Sanskrit

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Authors: Narmina Mammadova

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In modern linguistics, the comparative study of languages is becoming increasingly popular, the typology and comparison of languages that have different structures is expanding and deepening. Of particular interest is the study of phraseological units, which makes it possible to identify the specific features of the compared languages in all their national identity. This paper gives a brief analysis of the comparative study of somatic phraseological units (SFU) of the Spanish and Turkish languages with the component "hand" in the semantic aspect; identification of equivalents, analogs and non-equivalent units, as well as a description of methods of translation of non-equivalent somatic phraseological units. Comparative study of the phraseology of unrelated languages is of particular relevance since it allows us to identify both general, universal features and differential and specific features characteristic of a particular language. Based on the results of the generalization of the study, it can be assumed that phraseological units containing a somatic component have a high interlingual phraseological activity, which contributes to an increase in the degree of interlingual equivalence.

Keywords: Linguoculturology, Turkish, Spanish, language picture of the world, phraseological units, semantic microfield

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Authors: Anas H. Aljemely, Jianping Xuan

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

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

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Authors: Ahmad Al Aboudi

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The Department of Archaeology at King Saud University conduct a long Term excavations since 2004 at the archaeological site of (Qurh) in Al-Ula area. The history of the site goes back to the eighth century AD. The main aim of the excavations is the training of the students on the archaeological field work associated with the scientific skills of exploring, surveying, classifying, documentations and other necessary in the field archaeology. During the 12th Season of Excavations, an area of 20 × 40 m2 of the site was excavated. The depth of the excavating the site was reached to 2-3 m. Many of the architectural features of a residential area in the northern part of the site were excavated this season. Circular walls made of mud-brick and a brick column drums and tiles made of clay were revealed this season. Additionally, lots of findings such as Gemstones, jars, ceramic plates, metal, glass, and fabric, as well as some jewelers and coins were discovered. This paper will deal with the main results of this field project including the architectural features and phenomena and their interpretations, the classification of excavated material culture remains and stratigraphy.

Keywords: Islamic architecture, Islamic art, excavations, early Islamic city

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Authors: N. Majouri, J. Sghaier, M. El Mankibi

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The history of brick manufacturing in south-west Tunisia dates back 1000 years. Most of the bricks are made at local workshops near to the clay supply site. This experimental study aims at studying and comparing the chemical, mineralogical and physical characterization of ancient and recent clay bricks in south-western Tunisia. This was done by collecting a large sample of clay brick specimens from four sites. There was much variability in the properties. The results revealed that there is a difference of up to 50% between old and new bricks; in chemical composition, mineralogy composition and porosity, which are much lower in recent clay bricks.

Keywords: clay bricks, chemical properties, mineralogical properties, physical properties

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Authors: Adil K. Tamimi, Tarig Ali, Rawan Anoohi, Ahmed Rajput, Kaltham Alkamali

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3D concrete printing is one of the most innovative and modern techniques in the field of construction that achieved several milestones in that field for the following advantages: saving project’s time, ability to execute complicated shapes, reduce waste and low cost. However, the concept of 3D printing in UAE is relatively new where construction teams, including clients, consultants, and contractors, do not have the required knowledge and experience in the field. This is the most significant obstacle for the construction parties, which make them refrained from using 3D concrete printing compared to conventional concreting methods. This study shows the historical development of the 3D concrete printing, its advantages, and the challenges facing this innovation. Concrete mixes and materials have been proposed and evaluated to select the best combination for successful 3D concrete printing. The main characteristics of the 3D concrete printing in the fresh and hardened states are considered, such as slump test, flow table, compressive strength, tensile, and flexural strengths. There is need to assess the structural stability of the 3D concrete by testing the bond between interlayers of the concrete.  

Keywords: 3D printing, workability, compressive strength, robots, dimensions

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Authors: Riki Panchal, Debasis Sarkar

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This paper describes the work done for the GIS-based project management for different infrastructure projects. It is a review paper which gives the idea of the trends in the construction project management and various models adopted for the betterment of the project planning and execution. Traditional scheduling and progress control techniques such as bar charts and the critical path method fail to provide information pertaining to the spatial aspects of a construction project. An integrated system was developed to represent construction progress not only in terms of a CPM schedule but also in terms of a graphical representation of the construction that is synchronized with the work schedule. Hence, it is suggested to work on the common platform from where all the data can be shared and analyzed.

Keywords: GIS, project management, integrated model, infrastructure project

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: classification, data mining, spam filtering, naive bayes, decision tree

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Authors: Abiodun Ladanu Ajala, Wuyi Oke

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Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

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Authors: A. O. Mikhailov, N. I. Gerasimov, K. N. Morozov, I. V. Grachev

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The most advanced method of onboard equipment installation on the world shipbuilding practice is modular method, or modularization. The main idea of this is assembly of equipment, pipelines and hull structures in so called assembly units yet at the shopfloor. Those assembly units are thereafter loaded and installed inside the ship's hull. This allows to reduce labour intensiveness and significantly improve assembly quality, due to the fact that a good part of installation work is performed in the shops, instead of restricted onboard premises. Also, this method allows performing equipment installation at very early stages of hull erection. This practice is widely spread in naval submarines building. However, in merchant shipbuilding, equipment is installed mostly individually. To implement modular principles of equipment installation in designing and construction of civil ships and marine rigs, some new technologies are being developed in the following areas. The paper contains main principles and already achieved results in the above mentioned areas.

Keywords: assembly and installation technology, onboard equipment installation, large-scale assembly units, modular method

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Authors: Hassan Sharafuddin, Chekra Allani

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Academicians at the Arab Open University have always voiced their concern about the efficacy of the blended learning process. Based on 75% independent study and 25% face-to-face tutorial, it poses the challenge of the predisposition to adjustment. Being used to the psychology of traditional educational systems, AOU students cannot be easily weaned from being spoon-fed. Hence they lack the motivation to plunge into self-study. For better involvement of AOU students into the learning practices, it is imperative to diagnose the factors that impede or increase their motivation. This is conducted through an empirical study grounded upon observations and tested hypothesis and aimed at monitoring and optimizing the students’ learning outcome. Recommendations of the research will follow the findings.

Keywords: academic performance, blended learning, educational psychology, independent study, pedagogy

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Authors: H. Emari, Z. Emari

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The purpose of this paper is to design an applied framework for strategic thinking which can be applied in all managerial levels and all types of organizational environments. No special applied frame has been presented for this thinking. This paper presents a theoretical framework for the thinking type of a manager by making a historical research and studying the scientific documents about thinking of a strategist. In the new theoretical framework it has been tried to suggest the best type of thinking for a strategist after analyzing the environment of his decisions. So, in this framework, the traditional viewpoint about strategic thinking, which has considered it as a special type of right-brain thinking against other types of right-brain thinking and suggested it for a strategist, was put aside and suggests that the strategist should use a suitable type of thinking under different conditions.

Keywords: strategic thinking, systemic thinking, lateral thinking, intuitive thinking, hybrid thinking

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Authors: H. Gonzalez-Rivera, J. L. Palmeros-Torres

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This paper describes the application of traditional computer vision techniques as a procedure for automatic measurement of the secondary dendrite arm spacing (SDAS) from microscopic images. The algorithm is capable of finding the lineal or curve-shaped secondary column of the main microstructure, measuring its length size in a micro-meter and counting the number of spaces between dendrites. The automatic characterization was compared with a set of 1728 manually characterized images, leading to an accuracy of −0.27 µm for the length size determination and a precision of ± 2.78 counts for dendrite spacing counting, also reducing the characterization time from 7 hours to 2 minutes.

Keywords: dendrite arm spacing, microstructure inspection, pattern recognition, polynomial regression

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Authors: Ahmidah Elgali

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SCADA is the abbreviation for "Administrative Control And Data Acquisition." SCADA frameworks are generally utilized in industry for administrative control and information securing of modern cycles. Regular SCADA frameworks use PC, journal, slim client, and PDA as a client. In this paper, a Java-empowered cell phone has been utilized as a client in an example SCADA application to show and regulate the place of an example model crane. The paper presents a genuine execution of the online controlling of the model crane through a cell phone. The remote correspondence between the cell phone and the SCADA server is performed through a base station by means of general parcel radio assistance GPRS and remote application convention WAP. This application can be used in industrial sites in areas that are likely to be exposed to a security emergency (like terrorist attacks) which causes the sudden exit of the operators; however, no time to perform the shutdown procedures for the plant. Hence this application allows shutting down units and equipment remotely by mobile and so avoids damage and losses.

Keywords: control, industrial, mobile, network, remote, SCADA

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Authors: Manal E. A Elhalwagy, Nadia Amin Abdulmajeed, Hanan S. Alnahdi, Enas N. Danial

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Baron is herbicide includes (48% glyphosate) widely used in Egypt. The present study assesses the cytotoxic and genotoxic effect of baron on rats liver. Two groups of rats were treated orally with 1/10 LD 50, (275.49 mg kg -1) and 1/40 LD 50, (68.86 mg kg-1) glyphosate for 28 days compared with control group. Serum and liver tissues were taken at 14 and 28 days of treatment. An inhibition in Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities were recorded at both treatment periods and reduction in total serum protein (TP) and albumin (ALB). However, non-significant changes in serum acetylcholinesterase (AChE). Elevation in oxidative stress biomarker malondyaldehyde (MDA) and the decline in detoxification biomarker total reduced glutathione (GSH), Glutathione S-transferase (GST) and superoxide dismutase (SOD) in liver tissues led to increase in percentage of DNA damage. Destruction in liver tissue architecture was observed . Although, Baron was classified in the safe category pesticides repeated exposure to small doses has great danger effect.

Keywords: glyphosate, liver toxicity, oxidative stress, DNA damage, commet assay

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: Pedro Esteban

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Planning a hybrid power system (HPS) that integrates renewable generation sources, non-renewable generation sources and energy storage, involves determining the capacity and size of various components to be used in the system to be able to supply reliable electricity to the connected load as required. Nowadays it is very common to integrate solar photovoltaic (PV) power plants for renewable generation as part of HPS. The solar PV system is usually balanced via a second form of generation (renewable such as wind power or using fossil fuels such as a diesel generator) or an energy storage system (such as a battery bank). Hybrid power systems can also provide other forms of power such as heat for some applications. Modern hybrid power systems combine power generation and energy storage technologies together with real-time energy management and innovative power quality and energy efficiency improvement functionalities. These systems help customers achieve targets for clean energy generation, they add flexibility to the electrical grid, and they optimize the installation by improving its power quality and energy efficiency.

Keywords: microgrids, hybrid power systems, energy storage, grid code compliance

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Authors: Mohamed Derbeli, Maissa Farhat, Oscar Barambones, Lassaad Sbita

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Conventional controller (PI) applied to a DC/DC boost converter for the improvement and optimization of the Proton Exchange Membrane Fuel Cell (PEMFC) system efficiency, cannot attain a good performance effect. Thus, due to its advantages comparatively with the PI controller, this paper interest is focused on the use of the sliding mode controller (SMC), Stability of the closed loop system is analytically proved using Lyapunov approach for the proposed controller. The model and the controllers are implemented in the MATLAB and SIMULINK environment. A comparison of results indicates that the suggested approach has considerable advantages compared to the traditional controller.

Keywords: DC/DC boost converter, PEMFC, PI controller, sliding mode controller

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Authors: Alexander Hudson, Shaogang Gong

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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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Authors: Wondmnew Derebe

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Increased adoption of modern beehives improves the livelihood of smallholder farmers whose income largely depends on mixed crop-livestock farming. Improved beehives have been disseminated to farmers in many parts of Ethiopia. However, its impact on income is less investigated. Thus, this study estimates how adopting improved beehives impacts rural households' income. Survey data were collected from 350 randomly selected households' and analyzed using an endogenous switching regression model. The result revealed that the adoption of improved beehives is associated with a higher annual income. On average, improved beehive adopters earned about 6,077 (ETB) more money than their counterparts. However, the impact of adoption would have been larger for actual non-adopters, as reflected in the negative transitional heterogeneity effect of 1792 (ETB). The result also indicated that the decision to adopt or not to adopt improved beehives was subjected to individual self-selection. Improved beehive adoption can increase farmers' income and can be used as an alternative poverty reduction strategy.

Keywords: impact, adoption, endogenous switching regression, income, improved

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Authors: Ibrahim Aly, Manal Ahmed, Mahmoud M. El-Shall

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Filariasis is a parasitic disease caused by small roundworms. The filarial worms are transmitted and spread by blood-feeding black flies and mosquitoes. Lymphatic filariasis (Elephantiasis) is caused by Wuchereriabancrofti, Brugiamalayi, and Brugiatimori. Elimination of Lymphatic filariasis necessitates an increasing demand for valid, reliable, and rapid diagnostic kits. Nanodiagnostics involve the use of nanotechnology in clinical diagnosis to meet the demands for increased sensitivity, specificity, and early detection in less time. The aim of this study was to evaluate the nano-based enzymelinked immunosorbent assay (ELISA) and novel nano-chip card as a rapid test for detection of filarial antigen in serum samples of human filariasis in comparison with traditional -ELISA. Serum samples were collected from an infected human with filarial gathered across Egypt's governorates. After receiving informed consenta total of 45 blood samples of infected individuals residing in different villages in Gharbea governorate, which isa nonendemic region for bancroftianfilariasis, healthy persons living in nonendemic locations (20 persons), as well as sera from 20 other parasites, affected patients were collected. The microfilaria was checked in thick smears of 20 µl night blood samples collected during 20-22 hrs. All of these individuals underwent the following procedures: history taking, clinical examination, and laboratory investigations, which included examination of blood samples for microfilaria using thick blood film and serological tests for detection of the circulating filarial antigen using polyclonal antibody- ELISA, nano-based ELISA, and nano-chip card. In the present study, a recently reported polyoclonal antibody specific to tegumental filarial antigen was used in developing nano-chip card and nano-ELISA compared to traditional ELISA for the detection of circulating filarial antigen in sera of patients with bancroftianfilariasis. The performance of the ELISA was evaluated using 45 serum samples. The ELISA was positive with sera from microfilaremicbancroftianfilariasis patients (n = 36) with a sensitivity of 80 %. Circulating filarial antigen was detected in 39/45 patients who were positive for circulating filarial antigen using nano-ELISA with a sensitivity of 86.6 %. On the other hand, 42 out of 45 patients were positive for circulating filarial antigen using nano-chip card with a sensitivity of 93.3%.In conclusion, using a novel nano-chip assay could potentially be a promising alternative antigen detection test for bancroftianfilariasis.

Keywords: lymphatic filariasis, nanotechnology, rapid diagnosis, elisa technique

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Authors: Laura Butabayeva, Svetlana Ismagulova, Gulbarshin Nogaibayeva, Maiya Temirbayeva, Aidana Zhussip

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The article presents the main results of the study conducted within the grant project «Organizational and methodological foundations for ensuring the inclusiveness of school students’ career guidance» (2022-2024). The main aim of the project is to study the issue of the absence of developed mechanisms, coordinating the activities of all stakeholders in preparing school students for conscious career choice, taking into account their individual opportunities and special educational needs. To achieve the aim of the project, according to the implementation plan, the analysis of foreign and national literature on the studied problem, as well as the study of the state of school students’ career guidance and their socialization in the context of inclusive education were conducted, the international experience on this issue was explored. The analysis of the national literature conducted by the authors has shown the State’s annual increase in the number of students with special educational needs as well as the rapid demand of labour market, influencing their professional self-determination in modern society. The participants from 5 State’s regions, including students, their parents, general secondary schools administration and educators, as well as employers, took part in the study, taking into account the geographical location: south, north, west, centre, and the cities of republican significance. To ensure the validity of the study’s results, the triangulation method was utilised, including both qualitative and quantitative methods. The data were analysed independently and compared with each other. Ethical principles were considered during all stages of the study. The characteristics of the system of career guidance in the modern school, the role and the involvement of stakeholders in the system of career guidance, the opinions of educators on school students’ preparedness for career choice, and the factors impeding the effectiveness of career guidance in schools were examined. The problem of stakeholders’ disunity and inconsistency, causing the systemic labor market distortions, the growth of low-skilled labor, and the unemployed, including people with special educational needs, were revealed. The other issue identified by the researchers was educators’ insufficient readiness for students’ career choice preparation in the context of inclusive education. To study cutting-edge experience in organizing a system of career guidance for young people and develop mechanisms coordinating the actions of all stakeholders in preparing students for career choice, the institutions of career guidance in France, Japan, and Germany were explored by the researchers. To achieve the aim of the project, the systemic contemporary model of school students’ professional self-determination, considering their individual opportunities and special educational needs, has been developed based on the study results and international experience. The main principles of this model are consistency, accessibility, inclusiveness, openness, coherence, continuity. The perspectives of students’ career guidance development in the context of inclusive education have been suggested.

Keywords: career guidance, inclusive education, model of school students’ professional self-determination, psychological and pedagogical support, special educational needs

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Authors: Maria Christofi, George Plastiras, Rafaella Elia, Vaggelis Tsiourtis, Theocharis Theocharides, Miltiadis Katsaros

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The rapidly expanding urban areas of the world constitute a challenge of how we need to make the transition to "the next urbanization", which will be defined by new analytical tools and new sources of data. This paper is about the production of a spatial application, the ‘FUMapp’, where space and its initiative will be available literally, in meters, but also abstractly, at a sensed level. While existing spatial applications typically focus on illustrations of the urban infrastructure, the suggested application goes beyond the existing: It investigates how our environment's perception adapts to the alterations of the built environment through a dataset construction of biophysical measurements (eye-tracking, heart beating), and physical metrics (spatial characteristics, size of stimuli, rhythm of mobility). It explores the intersections between architecture, cognition, and computing where future design can be improved and identifies the flexibility and livability of the ‘available space’ of specific examined urban paths.

Keywords: biophysical data, flexibility of urban, livability, next urbanization, spatial application

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Authors: Aswathi Thrivikraman, S. Advaith

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The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.

Keywords: LSTM, autoencoder, forecasting, seq2seq model

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Authors: Arun Sanjel, Greg Speegle

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Every second, massive amounts of data are generated, and Data Intensive Scalable Computing (DISC) frameworks have evolved into effective tools for analyzing such massive amounts of data. Since the underlying architecture of these distributed computing platforms is often new to users, building a DISC application can often be time-consuming and prone to errors. The automated conversion of a sequential program to a DISC program will consequently significantly improve productivity. However, synthesizing a user’s intended program from an input specification is complex, with several important applications, such as distributed program synthesizing and code refactoring. Existing works such as Tyro and Casper rely entirely on deductive synthesis techniques or similar program synthesis approaches. Our approach is to develop a data-driven synthesis technique to identify sequential components and translate them to equivalent distributed operations. We emphasize using reinforcement learning and unit testing as feedback mechanisms to achieve our objectives.

Keywords: program synthesis, distributed computing, reinforcement learning, unit testing, DISC

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Authors: Randa M. T. Mohamed

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Spices have long been used as traditional ingredients in the kitchen for seasoning, coloring, aromatic and food preservative properties. Besides, spices are equally used for therapeutic purposes. The objective of this study was to survey and document the medicinal properties of spices commonly used in the Sudanese kitchen for different food preparations. Also, extracts from reported spices were screened for the presence of secondary metabolites as well as their antioxidant and beta-lactamase inhibitory properties. This study was conducted in the Rekabbya Quartier in Omdurman, Khartoum State, Sudan. Information was collected by carrying out semi-structured interviews. All informants (30) in the present study were women. Spices were purchased from Attareen shop in Omdurman. Essential oils from spices were extracted by hydrodistillation and ethanolic extracts by maceration. Phytochemical screening was performed by thin layer chromatography (TLC). The antioxidant capacity of essential oils and ethanolic extracts was investigated through TLC bioautography. Beta lactamase inhibitory activity was performed by the acidimetric test. Ethnobotany study showed that a total of 16 spices were found to treat 36 ailments belonging to 10 categories. The most frequently claimed medicinal uses were for the digestive system diseases treated by 14 spices and respiratory system diseases treated by 8 spices. Gynaecological problems were treated by 4 spices. Dermatological diseases were cured by 5 spices while infections caused by tapeworms and other microbes causing dysentery were treated by 3 spices. 4 spices were used to treat bad breath, bleeding gum and toothache. Headache, eyes infection, cardiac stimulation and epilepsy were treated by one spice each. Other health problem like fatigue and loss of appetite and low breast milk production were treated by 1, 3 and 2 spices respectively. The majority (69%, 11/16) of spices were exported from different countries like India, China, Indonesia, Ethiopia, Egypt and Nigeria while 31% (5/16) was cultivated in Sudan. Essential oils of all spices were rich in terpenes while ethanolic extracts contained variable classes of secondary metabolites. Both essential oils and ethanolic extracts of all spices exerted considerable antioxidant activity. Only one extract, Syzygium aromaticum, possessed beta lactamase inhibitory activity. In conclusion, this study could contribute in conserving information on traditional medicinal uses of spices in Sudan. Also, the results demonstrated the potential of some of these spices to exert beneficial antimicrobial and antioxidant effect. Detailed phytochemical and biological assays of these spices are recommended.

Keywords: spices, ethnobotany, phytoconstituents, antioxidant, beta lactamase inhibition

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Arun Prasad Jaganathan

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In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling

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Authors: Fangying Wang, Zhang Sanming, Ni Qian

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In recent years, more and more personalized sound absorbing materials have entered the Chinese room acoustical decoration market. The acoustic performance of three kinds of personalized sound-absorbing materials: Flame-retardant Flax Fiber Sound-absorbing Cotton, Eco-Friendly Sand Acoustic Panel and Transparent Micro-perforated Panel (Film) are tested by Reverberation Room Method. The sound absorption characteristic curves show that their performance match for or even exceed the traditional sound absorbing material. Through the application in the actual projects, these personalized sound-absorbing materials also proved their sound absorption ability and unique decorative effect.

Keywords: acoustic performance, application prospect personalized sound-absorbing materials

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Authors: Mostafa ‘Neo’ Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

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EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy of modern supervised methods falls rapidly as the number of users increases to a few thousand. Moreover, supervised methods require a large amount of labeled data for training which limits their applications in real-world scenarios where acquiring data for training should not take more than a few minutes. We show that using contrastive learning for pre-training, it is possible to maintain high accuracy on a dataset of 2130 subjects while only using a fraction of labels. We compare 5 different self-supervised tasks for pre-training of the encoder where our proposed method achieves the accuracy of 96.4%, improving the baseline supervised models by 22.75% and the competing self-supervised model by 3.93%. We also study the effects of the length of the signal and the number of channels on the accuracy of the user-identification models. Our results reveal that signals from temporal and frontal channels contain more identifying features compared to other channels.

Keywords: brainprint, contrastive learning, electroencephalo-gram, self-supervised learning, user identification

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