Search results for: supervised machine learning algorithm

Authors: Michael Danilov, Sergei Iskakov, Vladimir Mazurenko

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The present paper describes a high-performance parallel realization of an exact diagonalization solver for quantum-electron models in a shared memory computing system. The proposed algorithm contains a storage format for efficient computing eigenvalues and eigenvectors of a quantum electron Hamiltonian matrix. The results of the test calculations carried out for 15 sites Hubbard model demonstrate reduction in the required memory and good multiprocessor scalability, while maintaining performance of the same order as compressed row storage.

Keywords: sparse matrix, compressed format, Hubbard model, Anderson model

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Authors: Aarnav Singh, Jayesh Ghatate, Tarush Pandey

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Non-Governmental Organizations (NGOs) play a crucial role in addressing societal challenges, relying heavily on financial transactions to fund their impactful initiatives. However, traditional financial systems can be cumbersome and lack transparency, hindering the efficiency and trustworthiness of NGO operations. The Ethereum main-net, while pioneering the decentralized finance landscape, grapples with inherent scalability challenges, restricting its transaction throughput to a range of 15-45 transactions per second (TPS). This limitation poses substantial obstacles for NGOs engaging in swift and dynamic financial transactions critical to their operational efficiency. This research is a comprehensive exploration of the intricacies of these scalability challenges and delves into the design and implementation of a purpose-built blockchain system explicitly crafted to surmount these constraints.

Keywords: non-governmental organizations, decentralized system, zero knowledge Ethereum virtual machine, decentralized application

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Authors: Zdenek Silar, Martin Dobrovolny

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This article deals with the obstacle detection on a railway crossing (clearance detection). Detection is based on the optical flow estimation and classification of the flow vectors by K-means clustering algorithm. For classification of passing vehicles is used optical flow direction determination. The optical flow estimation is based on a modified Lucas-Kanade method.

Keywords: background estimation, direction of optical flow, K-means clustering, objects detection, railway crossing monitoring, velocity vectors

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Authors: Dembele Dembele, Philippe

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Several Second Language Acquisition (SLA) studies have stressed the benefits of Content and Language Integrated Learning (CLIL) and shown how CLIL students outperformed their non-CLIL counterparts in many L2 skills. However, numerous experimental CLIL programs seem to have mainly targeted above-average and rather highly motivated language learners. The need to understand the impact of the student’s language proficiency on code-switching in CLIL instruction motivated this study. Therefore, determining the implications of the students’ low-language proficiency for CLIL methodology, as well as the frequency with which CLIL teachers use the main pedagogical functions of code-switching, seemed crucial for a Spanish CLIL instruction on a large scale. In the mixed-method approach adopted, ten face-to-face interviews were conducted in nine Valencian public secondary education schools, while over 30 CLIL teachers also contributed with their experience in two online survey questionnaires. The results showed the crucial role language proficiency plays in the Valencian CLIL/Plurilingual selection criteria. The presence of a substantial number of low-language proficient students in CLIL groups, which in turn implied important methodological consequences, was another finding of the study. Indeed, though the pedagogical use of L1 was confirmed as an extended practice among CLIL teachers, more than half of the participants perceived that code-switching impaired attaining their CLIL lesson objectives. Therein, the dissertation highlights the need for more extensive empirical research on how code-switching could prove beneficial in CLIL instruction involving low-language proficient students while maintaining the maximum possible exposure to the target language.

Keywords: CLIL methodology, low language proficiency, code switching, selection criteria, code-switching functions

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Authors: Farzad Hosseini Hossein Abadi, Cristina Prieto Sierra, Cesar Álvarez Díaz

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Predicting streamflow accurately in flashy catchments prone to floods is a major research and operational challenge in hydrological modeling. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have shown to be promising in achieving accurate hydrological predictions at daily and hourly time scales. In this work, a multi-timescale LSTM (MTS-LSTM) network was applied to the context of regional hydrological predictions at an hourly time scale in flashy catchments. The case study includes 40 catchments allocated in the Basque Country, north of Spain. We explore the impact of hyperparameters on the performance of streamflow predictions given by regional deep learning models through systematic hyperparameter tuning - where optimal regional values for different catchments are identified. The results show that predictions are highly accurate, with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) metrics values as high as 0.98 and 0.97, respectively. A principal component analysis reveals that a hyperparameter related to the length of the input sequence contributes most significantly to the prediction performance. The findings suggest that input sequence lengths have a crucial impact on the model prediction performance. Moreover, employing catchment-scale analysis reveals distinct sequence lengths for individual basins, highlighting the necessity of customizing this hyperparameter based on each catchment’s characteristics. This aligns with well known “uniqueness of the place” paradigm. In prior research, tuning the length of the input sequence of LSTMs has received limited focus in the field of streamflow prediction. Initially it was set to 365 days to capture a full annual water cycle. Later, performing limited systematic hyper-tuning using grid search, revealed a modification to 270 days. However, despite the significance of this hyperparameter in hydrological predictions, usually studies have overlooked its tuning and fixed it to 365 days. This study, employing a simultaneous systematic hyperparameter tuning approach, emphasizes the critical role of input sequence length as an influential hyperparameter in configuring LSTMs for regional streamflow prediction. Proper tuning of this hyperparameter is essential for achieving accurate hourly predictions using deep learning models.

Keywords: LSTMs, streamflow, hyperparameters, hydrology

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Authors: Ismail Haddad, Djamel Herbadji, Aissa Belmeguenai, Selma Boumerdassi

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in this paper, we provide a novel approach for image encryption that employs the Fibonacci matrix and an enhanced fractional order chaotic map. The enhanced map overcomes the drawbacks of the classical map, especially the limited chaotic range and non-uniform distribution of chaotic sequences, resulting in a larger encryption key space. As a result, this strategy improves the encryption system's security. Our experimental results demonstrate that our proposed algorithm effectively encrypts grayscale images with exceptional efficiency. Furthermore, our technique is resistant to a wide range of potential attacks, including statistical and entropy attacks.

Keywords: image encryption, logistic map, fibonacci matrix, grayscale images

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Authors: Joselito Medina-Marin, Alexandr Karelin, Ana Tarasenko, Juan Carlos Seck-Tuoh-Mora, Norberto Hernandez-Romero, Eva Selene Hernandez-Gress

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A production line designer faces with several challenges in manufacturing system design. One of them is the assignment of buffer slots in between every machine of the production line in order to maximize the throughput of the whole line, which is known as the Buffer Allocation Problem (BAP). The BAP is a combinatorial problem that depends on the number of machines and the total number of slots to be distributed on the production line. In this paper, we are proposing a Petri Net (PN) Model to obtain the throughput in unreliable production lines, based on PN mathematical tools and the decomposition method. The results obtained by this methodology are similar to those presented in previous works, and the number of machines is not a hard restriction.

Keywords: buffer allocation problem, Petri Nets, throughput, production lines

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Authors: D. F. Carvalho, A. O. Uscamayta, J. C. Guerrero, H. F. Oliveira, P. M. Azevedo-Marques

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The creation of vector contours slices (ROIs) on body silhouettes in oncologic patients is an important step during the radiotherapy planning in clinic and hospitals to ensure the accuracy of oncologic treatment. The radiotherapy planning of patients is performed by complex softwares focused on analysis of tumor regions, protection of organs at risk (OARs) and calculation of radiation doses for anomalies (tumors). These softwares are supplied for a few manufacturers and run over sophisticated workstations with vector processing presenting a cost of approximately twenty thousand dollars. The Brazilian project SIPRAD (Radiotherapy Planning System) presents a proposal adapted to the emerging countries reality that generally does not have the monetary conditions to acquire some radiotherapy planning workstations, resulting in waiting queues for new patients treatment. The SIPRAD project is composed by a set of integrated and interoperabilities softwares that are able to execute all stages of radiotherapy planning on simple personal computers (PCs) in replace to the workstations. The goal of this work is to present an image processing technique, computationally feasible, that is able to perform an automatic contour delineation in patient body silhouettes (SIPRAD-Body). The SIPRAD-Body technique is performed in tomography slices under grayscale images, extending their use with a greedy algorithm in three dimensions. SIPRAD-Body creates an irregular polyhedron with the Canny Edge adapted algorithm without the use of preprocessing filters, as contrast and brightness. In addition, comparing the technique SIPRAD-Body with existing current solutions is reached a contours similarity at least 78%. For this comparison is used four criteria: contour area, contour length, difference between the mass centers and Jaccard index technique. SIPRAD-Body was tested in a set of oncologic exams provided by the Clinical Hospital of the University of Sao Paulo (HCRP-USP). The exams were applied in patients with different conditions of ethnology, ages, tumor severities and body regions. Even in case of services that have already workstations, it is possible to have SIPRAD working together PCs because of the interoperability of communication between both systems through the DICOM protocol that provides an increase of workflow. Therefore, the conclusion is that SIPRAD-Body technique is feasible because of its degree of similarity in both new radiotherapy planning services and existing services.

Keywords: radiotherapy, image processing, DICOM RT, Treatment Planning System (TPS)

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Authors: Johanna Lundqvist

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Third cycle supervision is a multifaceted and complex task for supervisors in higher education. It progresses over several years and is affected by several proximal and distal factors. It can result in positive learning outcomes for doctoral students and high-quality publications. However, not all doctoral students thrive during their doctoral studies; nor do they all complete their studies. This is problematic for both the individuals themselves as well as society at large: doctoral students are valuable and important in current research, future research and higher education. The aim of this literature review is to elucidate what responsible third cycle supervision can include and be in practice. The question posed is as follows: according to recent literature, what is it that characterises responsible third cycle supervision in which doctoral students can thrive and develop their research knowledge and skills? A literature review was conducted, and the data gathered from the literature regarding responsible third cycle supervision was analysed by means of a thematic analysis. The analysis was inspired by the notion of responsible inclusion outlined by David Mitchell. In this study, the term literature refers to research articles and regulations. The results (preliminary) show that responsible third cycle supervision is associated with a number of interplaying factors (themes). These are as follows: committed supervisors and doctoral students; a clear vision and research problem; an individual study plan; adequate resources; interaction processes and constructive feedback; creativity; cultural awareness; respect and research ethics; systematic quality work and improvement efforts; focus on overall third cycle learning goals; and focus on research presentations and publications. Thus, responsible third cycle supervision can occur if these factors are realized in practice. This literature review is of relevance to evaluators, researchers, and management in higher education, as well as third cycle supervisors.

Keywords: doctoral student, higher education, third cycle supervisors, third cycle programmes

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Authors: Tala Toonsi, Marah Alagha, Lina Alnowaiser, Hala Rajab

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This report is about the Photomath app, which is an AI application that uses image recognition technology, specifically optical character recognition (OCR) algorithms. The (OCR) algorithm translates the images into a mathematical equation, and the app automatically provides a step-by-step solution. The application supports decimals, basic arithmetic, fractions, linear equations, and multiple functions such as logarithms. Testing was conducted to examine the usage of this app, and results were collected by surveying ten participants. Later, the results were analyzed. This paper seeks to answer the question: To what level the artificial intelligence features are accurate and the speed of process in this app. It is hoped this study will inform about the efficiency of AI in Photomath to the users.

Keywords: photomath, image recognition, app, OCR, artificial intelligence, mathematical equations.

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Authors: Min Bao

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The teacher is at the core of the three fundamental factors in international Chinese language teaching, the other two being the textbook and the method. Professional development of the teacher comprises a self-renewing process that is characterized by knowledge impartment and self-reflection, in which individual agency plays a significant role. Agency makes a positive contribution to teachers’ teaching practice and their life-long learning. This study, taking Chinese teaching and learning in Minsk State Linguistic University of Belarus as an example, attempts to understand agency by investigating the teacher’s strategic adaptation of textbooks to meet local needs. Firstly, through in-depth interviews, teachers’ comments on textbooks are collected and analyzed to disclose their strategies of adapting and localizing textbooks. Then, drawing on the theory of 'The chordal triad of agency', the paper reveals the process in which teacher agency is exercised as well as its rationale. The results verify the theory, that is, given its temporal relationality, teacher agency is constructed through a combination of experiences, purposes and aims, and context, i.e., projectivity, iteration and practice-evaluation as mentioned in the theory. Evidence also suggests that the three dimensions effect differently; It is usually one or two dimensions that are of greater effects on the construction of teacher agency. Finally, the paper provides four specific insights to teacher development in international Chinese language teaching: 1) when recruiting teachers, priority be given on candidates majoring in Chinese language or international Chinese language teaching; 2) measures be taken to assure educational quality of the two said majors at various levels; 3) pre-service teacher training program be tailored for improved quality, and 4) management of overseas Confucius Institutions be enhanced.

Keywords: international Chinese language teaching, teacher agency, textbooks, localization

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Authors: Reza Hedayati, Meysam Jahanbakhshi

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Elastic energy absorbers which consist of a ring-liked plate and springs can be a good choice for increasing the impact duration during an accident. In the current project, an energy absorber system is optimized using four optimizing methods Kuhn-Tucker, Sequential Linear Programming (SLP), Concurrent Subspace Design (CSD), and Pshenichny-Lim-Belegundu-Arora (PLBA). Time solution, convergence, Programming Length and accuracy of the results were considered to find the best solution algorithm. Results showed the superiority of PLBA over the other algorithms.

Keywords: Concurrent Subspace Design (CSD), Kuhn-Tucker, Pshenichny-Lim-Belegundu-Arora (PLBA), Sequential Linear Programming (SLP)

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Authors: Huai-Cong Liu, Tae Chul Jeong, Ju Lee

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The aim of this study was to develop an electric circuit method (ECM) to ascertain the core loss influence on a Synchronous Reluctance Motor (SynRM) in the condition of the maximum torque per ampere (MTPA). SynRM for fan usually operates on the constant torque region, at synchronous speed the MTPA control is adopted due to current vector. However, finite element analysis (FEA) program is not sufficient exactly to reflect how the core loss influenced on the current vector. This paper proposed a method to calculate the current vector with consideration of core loss. The precision of current vector by ECM is useful for MTPA control. The result shows that ECM analysis is closer to the actual motor’s characteristics by testing with a 7.5kW SynRM drive System.

Keywords: core loss, SynRM, current vector, magnetic saturation, maximum torque per ampere (MTPA)

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Authors: Chung To Kong, Siu Ming Yiu

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Rubik's cube was invented in 1974. Since then, speedcubers all over the world try their best to break the world record again and again. The newest record is 3.47 seconds. There are many factors that affect the timing, including turns per second (tps), algorithm, finger trick, hardware of the cube. In this paper, the lower bound of the cube solving time will be discussed using convex optimization. Extended analysis of the world records will be used to understand how to improve the timing. With the understanding of each part of the solving step, the paper suggests a list of speed improvement techniques. Based on the analysis of the world record, there is a high possibility that the 3 seconds mark will be broken soon.

Keywords: Rubik's Cube, speed, finger trick, optimization

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Authors: Soyon Kim, Edward Kim

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In order to retrieve information from the massive stream of songs in the music industry, music search by title, lyrics, artist, mood, and genre has become more important. Despite the subjectivity and controversy over the definition of music genres across different nations and cultures, automatic genre classification systems that facilitate the process of music categorization have been developed. Manual genre selection by music producers is being provided as statistical data for designing automatic genre classification systems. In this paper, an automatic music genre classification system utilizing non-negative matrix factorization (NMF) is proposed. Short-term characteristics of the music signal can be captured based on the timbre features such as mel-frequency cepstral coefficient (MFCC), decorrelated filter bank (DFB), octave-based spectral contrast (OSC), and octave band sum (OBS). Long-term time-varying characteristics of the music signal can be summarized with (1) the statistical features such as mean, variance, minimum, and maximum of the timbre features and (2) the modulation spectrum features such as spectral flatness measure, spectral crest measure, spectral peak, spectral valley, and spectral contrast of the timbre features. Not only these conventional basic long-term feature vectors, but also NMF based feature vectors are proposed to be used together for genre classification. In the training stage, NMF basis vectors were extracted for each genre class. The NMF features were calculated in the log spectral magnitude domain (NMF-LSM) as well as in the basic feature vector domain (NMF-BFV). For NMF-LSM, an entire full band spectrum was used. However, for NMF-BFV, only low band spectrum was used since high frequency modulation spectrum of the basic feature vectors did not contain important information for genre classification. In the test stage, using the set of pre-trained NMF basis vectors, the genre classification system extracted the NMF weighting values of each genre as the NMF feature vectors. A support vector machine (SVM) was used as a classifier. The GTZAN multi-genre music database was used for training and testing. It is composed of 10 genres and 100 songs for each genre. To increase the reliability of the experiments, 10-fold cross validation was used. For a given input song, an extracted NMF-LSM feature vector was composed of 10 weighting values that corresponded to the classification probabilities for 10 genres. An NMF-BFV feature vector also had a dimensionality of 10. Combined with the basic long-term features such as statistical features and modulation spectrum features, the NMF features provided the increased accuracy with a slight increase in feature dimensionality. The conventional basic features by themselves yielded 84.0% accuracy, but the basic features with NMF-LSM and NMF-BFV provided 85.1% and 84.2% accuracy, respectively. The basic features required dimensionality of 460, but NMF-LSM and NMF-BFV required dimensionalities of 10 and 10, respectively. Combining the basic features, NMF-LSM and NMF-BFV together with the SVM with a radial basis function (RBF) kernel produced the significantly higher classification accuracy of 88.3% with a feature dimensionality of 480.

Keywords: mel-frequency cepstral coefficient (MFCC), music genre classification, non-negative matrix factorization (NMF), support vector machine (SVM)

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Authors: Mirriam M. Moleko, Sekanse A. Ntsala

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Language in mathematics instruction enables the teacher to communicate mathematical knowledge to the learners with precision. It also enables the learner to deal with mathematical activities effectively. This scholarly piece was motivated by the fact that mathematics performance in the South African primary classrooms has not been satisfactory, and English, which is a Language of Learning and Teaching (LoLT) for the majority of the learners, has been singled out as one of the major impediments. This is not only on the part of the learners, but also on the part of the teachers as well. The study thus focused on the lack of competency in English among the primary school teachers as one of the possible causes of poor performance in mathematics in primary classrooms. The qualitative processes, which were premised on the social interaction theory as a lens, sourced the narratives of 10 newly qualified primary school mathematics teachers from the disadvantaged schools on the matter. This was achieved through the use of semi-structured interviews and focus group discussions. The data, which were analyzed thematically, highlighted the actuality that the challenges cut across the pre-service stage to the in-service stage. The findings revealed that the undergraduate mathematics courses in the number of the institutions neglect the importance of language. The study further revealed that the in-service mathematics teachers lack adequate linguistic command, thereby finding it difficult to successfully teach some mathematical concepts, or even to outline instructions clearly. The study thus suggests the need for training institutions to focus on improving the teachers’ English language competency. The need for intensive in-service training targeting the problem areas was also highlighted. The study thus contributes to the body of knowledge by providing suggestions on how the mathematics teachers’ language incompetency can be mitigated.

Keywords: Competency, English language proficiency, language of learning and teaching, primary mathematics teachers

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Authors: Noriyoshi Yamauchi, Etsuo Horikawa, Takunori Tsuji

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Training by exoskeleton robot is drawing attention as a rehabilitation method for body paralysis seen in many cases, and there are many forms that assist with the myoelectric signal generated by exercise commands from the brain. Rehabilitation requires more frequent training, but it is one of the reasons that the technology is required for the identification of the myoelectric potential derivation site and attachment of the device is preventing the spread of paralysis. In this research, we focus on improving the efficiency of gait training by exoskeleton type robots, improvement of myoelectric acquisition and analysis method using active matrix sensing method, and improvement of walking rehabilitation and walking by optimization of robot control.

Keywords: active matrix sensing, brain machine interface (BMI), the central pattern generator (CPG), myoelectric signal processing, robot rehabilitation

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Authors: A. Javorova, M. Matusova, K. Velisek

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The article summarizes the experience of laboratory technical subjects teaching methodologies using a number of software products. The main aim is to modernize the teaching process in accordance with the requirements of today - based on information technology. Increasing of the study attractiveness and effectiveness is due to the introduction of CA technologies in the learning process. This paper discussed the areas where individual CA system used. Environment using CA systems are briefly presented in each chapter.

Keywords: education, CA systems, simulation, technology

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Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

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There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

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Authors: Samia Dardouri, Ridha Bouallegue

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Scheduling is the process of dynamically allocating physical resources to User Equipment (UE) based on scheduling algorithms implemented at the LTE base station. Various algorithms have been proposed by network researchers as the implementation of scheduling algorithm which represents an open issue in Long Term Evolution (LTE) standard. This paper makes an attempt to study and compare the performance of PF, MLWDF and EXP/PF scheduling algorithms. The evaluation is considered for a single cell with interference scenario for different flows such as Best effort, Video and VoIP in a pedestrian and vehicular environment using the LTE-Sim network simulator. The comparative study is conducted in terms of system throughput, fairness index, delay, packet loss ratio (PLR) and total cell spectral efficiency.

Keywords: LTE, multimedia flows, scheduling algorithms, mobile computing

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Authors: Elizabeth Hoyos, Hernán Alvarez, Diana Lopez, Yesid Montoya

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The main goal of this research relates to the modeling of FSW from a different or unusual perspective coming from mechanical engineering, particularly looking for a way to establish process windows by assessing soundness of the joints as a priority and with the added advantage of lower computational time. This paper presents the use of a previously developed model applied to specific aspects of soundness evaluation of AA7075 FSW welds. EMSO software (Environment for Modeling, Simulation, and Optimization) was used for simulation and an adapted CNC machine was used for actual welding. This model based approach showed good agreement with the experimental data, from which it is possible to set a window of operation for commercial aluminum alloy AA7075, all with low computational costs and employing simple quality indicators that can be used by non-specialized users in process modeling.

Keywords: aluminum AA7075, friction stir welding, phenomenological based semiphysical model, processing map

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Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

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Authors: Jumazulhisham Abdul Shukor, Mohd. Sazali Said, Roshanizah Harun, Shuib Husin, Ahmad Razlee Ab Kadir

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This paper applies Taguchi Optimization Method in determining the best machining parameters for pocket milling process on Polypropylene (PP) using CNC milling machine where the surface roughness is considered and the Carbide inserts cutting tool are used. Three machining parameters; speed, feed rate and depth of cut are investigated along three levels; low, medium and high of each parameter (Taguchi Orthogonal Arrays). The setting of machining parameters were determined by using Taguchi Method and the Signal-to-Noise (S/N) ratio are assessed to define the optimal levels and to predict the effect of surface roughness with assigned parameters based on L9. The final experimental outcomes are presented to prove the optimization parameters recommended by manufacturer are accurate.

Keywords: inserts, milling process, signal-to-noise (S/N) ratio, surface roughness, Taguchi Optimization Method

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Authors: Bussabamintra Chalauisaeng

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The creative writing skill of Thai fourth year university learners majoring in English at Khon Kaen University, Thailand has been enhanced in an English creative writing course through the implementation of creative thinking process. The creative writing assignments cover writing a variety of short poems and a short story, bibliography and short play scripts. However, this study focuses mainly on writing short poems and short stories through the implementation of creative thinking process via action research design with on-going needs analysis and feedbacks to meet their learning needs for 45 hours. At the end of the course, forty two learners’ creative writing skill appeared to be significantly improved. Through the research instruments such as the tasks assigned both inside and outside the class as self –study including class observation, semi-conversational interviews and teacher feedback both in persons and on line including peer feedbacks. The research findings show that the target learners could produce better short poems and short story assessed by the set of criteria such as the creative and innovative short poems and short stories with complete and interesting elements of a short story like plot, theme, setting, symbolism and so on. This includes a higher level of the awareness of the pragmatic use of English writing in terms of word choices, grammar rules and writing styles. All of these outcomes reflect positive trends of success in terms of the learners’ improved creative writing skill as well as better attitudes to and motivation for learning to write English for pleasure. More interestingly, many learners claimed that this innovative teaching method through the implementation of creative thinking process integrated with creative writing help stretch their imaginations and inspire them to become a writer in the future.

Keywords: creative thinking process, creative writing skill, enhancing, implementing

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Authors: Neha Toppo

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Plans and programs for successful secondary education are incomplete without the inclusion of teaching English as an important area. Even after sixteen years of the formation of Jharkhand as a separate state, the students are still struggling to achieve quality education of English. This paper intends to account the present condition of teaching English in Jharkhand board secondary level schools through discussion on various issues of English language teaching, language need and learning challenges of its students. The study is to analyze whether the learning environment, teaching methods and materials, teaching resources, goals of language curriculum are appropriately convincing for the students of the board or require to be reanalyzed and also to provide appropriate suggestions for improvement. Immediate attention must be drawn towards the problem for benefitting those students, who despite their knowledge and talent are lagging behind in numerous fields only due to the lack of proficiency in English. The data and discussion provided are on the basis of a survey, in which semi structured interview with teachers, students and administrators in several schools including both rural and urban area has been taken. Questionnaire, observation and testing were used as important tools. The survey has been conducted in Ranchi district, as it covers large geographical area which includes number of villages and at the same time several towns. The district primarily possesses tribes as well as different class of people including immigrants from all over and outside Jharkhand with their social, economical strata. The observation makes it clear that the English language teaching at the state board is not complementing its context and the whole language teaching system should be re-examined to establish learner oriented environment.

Keywords: material, method, secondary level, teaching resources

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Authors: Khadija Rafi, Neha Jamil, Laiba Khalid, Meerub Nawaz, Mahwish Farooq

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Speech articulation is a complex process to produce intelligible sounds with the help of precise movements of various structures within the vocal tract. All these structures in the vocal tract are named as articulators, which comprise lips, teeth, tongue, and palate. These articulators work together to produce a range of distinct phonemes, which happen to be the basis of language. It starts with the airstream from the lungs passing through the trachea and into oral and nasal cavities. When the air passes through the mouth, the tongue and the muscles around it form such coordination it creates certain sounds. It can be seen when the tongue is placed in different positions- sometimes near the alveolar ridge, soft palate, roof of the mouth or the back of the teeth which end up creating unique qualities of each phoneme. We can articulate vowels with open vocal tracts, but the height and position of the tongue is different every time depending upon each vowel, while consonants can be pronounced when we create obstructions in the airflow. For instance, the alphabet ‘b’ is a plosive and can be produced only by briefly closing the lips. Articulation disorders can not only affect communication but can also be a hurdle in speech production. To improve articulation skills for such individuals, doctors often recommend speech therapy, which involves various kinds of exercises like jaw exercises and tongue twisters. However, this disorder is more common in children who are going through developmental articulation issues right after birth, but in adults, it can be caused by injury, neurological conditions, or other speech-related disorders. In short, speech articulation is an essential aspect of productive communication, which also includes coordination of the specific articulators to produce different intelligible sounds, which are a vital part of spoken language.

Keywords: linguistics, speech articulation, speech therapy, language learning

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Authors: R. Ouafi, F. Ouafi

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We study the problem of cutting a rectangular material entity into smaller sub-entities of trapezoidal forms with minimum waste of the material. This problem will be denoted TCP (Trapezoidal Cutting Problem). The TCP has many applications in manufacturing processes of various industries: pipe line design (petro chemistry), the design of airfoil (aeronautical) or cuts of the components of textile products. We introduce an orthogonal build to provide the optimal horizontal and vertical homogeneous strips. In this paper we develop a general heuristic search based upon orthogonal build. By solving two one-dimensional knapsack problems, we combine the horizontal and vertical homogeneous strips to give a non orthogonal cutting pattern.

Keywords: combinatorial optimization, cutting problem, heuristic

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Authors: Omer Shujat Bhatti, Afshan Huma

Abstract:

Online educational system were considered a great opportunity for distance learning. In recent days of COVID19 pandemic, it enable the continuation of educational activities at all levels of education, from primary school to the top level universities. One of the key considered element in supporting the online educational system is video lectures. The current research explored the usefulness of the video lectures delivered to technical students of masters level with a focus on MSc Sustainable Environmental design students who have diverse backgrounds in the formal educational system. Hence they were unable to cope right away with the online system and faced communication and understanding issues in the lecture session due to internet and allied connectivity issues. Researcher used self prepared video lectures for respective subjects and provided them to the students using Youtube channel and subject based Whatsapp groups. Later, students were asked about the usefulness of the lectures towards a better understanding of the subject and an overall enhanced learning experience. More than 80% of the students appreciated the effort and requested it to be part of the overall system. Data collection was done using an online questionnaire which was prior briefed to the students with the purpose of research. It was concluded that video lectures should be considered an integral part of the lecture sessions and must be provided prior to the lecture session, ensuring a better quality of delivery. It was also recommended that the existing system must be upgraded to support the availability of these video lectures through the portal. Teachers training must be provided to help develop quality video content ensuring that is able to cover the content and courses taught.

Keywords: video lectures, online distance education, synchronous instruction, asynchronous communication

Procedia PDF Downloads 99

Authors: Mary Cheptanui Sambu

Abstract:

Teaching practice is an integral component of students who are training to be teachers, as it provides them with an opportunity to gain experience in an actual teaching and learning environment. This study explored the experiences of trainee teachers from a local university in Kenya, undergoing a three-month teaching practice in Special Secondary schools in the country. The main aim of the study was to understand the trainees’ experiences, their expectations, and the realities encountered during the teaching practice period. The study focused on special secondary schools for learners with hearing impairment. A descriptive survey design was employed and a sample size of forty-four respondents from special secondary schools for learners with hearing impairment was purposively selected. A questionnaire was administered to the respondents and the data obtained analysed using the Statistical Package for the Social Sciences (SPSS). Preliminary analysis shows that challenges facing special secondary schools include inadequate teaching and learning facilities and resources, low academic performance among learners with hearing impairment, an overloaded curriculum and inadequate number of teachers for the learners. The study findings suggest that the Kenyan government should invest more in the education of special needs children, particularly focusing on increasing the number of trained teachers. In addition, the education curriculum offered in special secondary schools should be tailored towards the needs and interest of learners. These research findings will be useful to policymakers and curriculum developers, and will provide information that can be used to enhance the education of learners with hearing impairment; this will lead to improved academic performance, consequently resulting in better transitions and the realization of Vision 2030.

Keywords: hearing impairment, special secondary schools, trainee, teaching practice

Procedia PDF Downloads 148

Authors: Aleksander Mendoza

Abstract:

Glushkov's construction has many interesting properties, and they become even more evident when applied to transducers. This article strives to show the vast range of possible extensions and optimisations for this algorithm. Special flavour of regular expressions is introduced, which can be efficiently converted to e-free functional subsequential weighted finite state transducers. Produced automata are very compact, as they contain only one state for each symbol (from input alphabet) of original expression and only one transition for each range of symbols, no matter how large. Such compactified ranges of transitions allow for efficient binary search lookup during automaton evaluation. All the methods and algorithms presented here were used to implement open-source compiler of regular expressions for multitape transducers.

Keywords: weighted automata, transducers, Glushkov, follow automata, regular expressions

Procedia PDF Downloads 143