Search results for: automated cad drawing

Authors: Faris Algahtani

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Every child has a right to education. This is one of the laws in the constitution and it empowers every child to access knowledge but it does not, however, allocate special interest to the rights of education for children with disabilities. It also does not address the challenges that teachers of such children face while trying to educate them. This study was conducted at government schools of Saudi Arabia. As the teaching profession is the most valuable profession and deserves to have its challenges tackled. This paper explores the challenges that teachers face as they try to teach students who have intellectual disabilities (ID). It looks at the daily challenges of a teacher who has to teach both children with disabilities and those without. The literature review shed light on the various aspects of mainstream education from the classroom to the outside environment to the teachers involved in mainstream education. The study employed qualitative methods in which Focus Group Discussions were utilized and Twenty (N=20) special education teachers were randomly sampled from primary schools through 6 groups of teachers from 6 different schools were interviewed through semi-structured interviews with the aim of drawing collective perceptions rather than personal perceptions about the challenges. The study found that most teachers had similar perceptions about the challenges that teachers face as they educate students with intellectual disabilities. The study recommends that The Ministry of Education should consider increasing the availability of special needs courses, workshops and conference for special education teachers.

Keywords: intellectual disabilities, inclusion, mainstream schools, disabilities, special education teachers

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Authors: Mohammad Afghari

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Since the inception of intellectual movements in Iran, Iranian thinkers have perennially found themselves at the crossroads of indigenous traditionalism and Western orientation. On the one hand, supporters of indigenous thinking have emphasized the defense of cultural, national, and religious values. On the other hand, Western-leaning intellectuals, often derogatorily labeled as ‘Westoxication’ by their indigenous counterparts, have been inclined towards embracing non-indigenous ideas and ideologies, primarily of Western origin. In this historical context, the dualistic nature of Iranian intellectuals, evolving amidst the era of globalization and its swift advancements in communication, has not only retained its inherent character but has evolved into a broader duality that can identified as ‘Iranian-Cosmopolitan’. In this duality, both in its classical form of indigenous-Western and its contemporary manifestation as Iranian-Cosmopolitan, the Iranian national identity has consistently been a significant part of intellectual discussions. While critically examining this dualism through a historical lens and drawing upon the theories of Anthony Smith, a historical sociologist and British theorist of nationalism, this article delves into the importance of aligning national identity with the prevailing societal transformations, especially globalization. It underscores that Iranian intellectuals, to national identity reconstruction in the present age, will find no solution other than discarding this dualism and reconstructing national identity within a global framework.

Keywords: Iran, Iranian intellectuals, globalization, localism, national identity, cosmopolitan

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Authors: Laurence Picard, André Bégin-Drolet, Pierre Blanchet

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The prefabricated construction industry has been operating in North America for several years now and differs from traditional construction by its much shorter project timelines, lower costs, and increased build quality. Faced with the global housing crisis, prefabrication should be the first choice for erecting buildings quickly and at a low cost. However, the reality is quite different; manufacturers focus their operations mainly on single-home construction. This is explained by the lack of a suitable and efficient assembly solution for erecting large-scale buildings. Indeed, it is difficult to maintain the coveted advantages of prefabrication with a laborious on-site assembly and a colossal load of additional operations such as the installation of fasteners and the internal finishing. In the desire to maximize the benefits of prefabrication and make it a smart choice even for large buildings, an automated connection solution is developed. The plug-in self-locking device was developed accordingly to the product design phases: on-site observations, the definition of the problem and product requirements, solution generation, prototyping, fabricating and testing.

Keywords: assembly solution, automation, construction productivity, modular connection, modular buildings, plug-in device, self-lock mechanism

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Authors: Souvik Das, Janak Lal, Arthita Dey, Goutam Mukhopadhyay, Sandip Bhattacharya

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Telescopic Front Fork (TFF) used in two wheelers, mainly motorcycle, is made from high strength steel, and is manufactured by high frequency induction welding process wherein hot rolled and pickled coils are used as input raw material for rolling of hollow tubes followed by heat treatment, surface treatment, cold drawing, tempering, etc. The final application demands superior quality TFF tubes w.r.t. surface finish and dimensional tolerances. This paper presents the investigation of two different types of failure of fork during operation. The investigation consists of visual inspection, chemical analysis, characterization of microstructure, and energy dispersive spectroscopy. In this paper, comprehensive investigations of two failed tube samples were investigated. In case of Sample #1, the result revealed that there was a pre-existing crack, known as hook crack, which leads to the cracking of the tube. Metallographic examination exhibited that during field operation the pre-existing hook crack was surfaced out leading to crack in the pipe. In case of Sample #2, presence of internal oxidation with decarburised grains inside the material indicates origin of the defect from slab stage.

Keywords: telescopic front fork, induction welding, hook crack, internal oxidation

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Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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Authors: Alireza Changizi, Arash Rezaei, Jamal Muhammad, Jyrki Latokartano, Minna Lanz

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Offline programming (OLP) is a new method in robot programming which is used widely in the industry nowadays which is a simulation base method that can produce the robot codes for motion according to virtual world in the simulation software. In this project Delmia v5 is used as simulation software. First the work cell component was modelled by Catia v5 and all of them was imported to a process file in Delmia and placed roughly to form the virtual work cell. Then robot was added to the work cell from the Delmia library. Work cell was calibrated corresponding to real world work cell to have accurate code. Tool calibration is the first step of calibration scheme and then work cell equipment can be calibrated using 6 point calibration method. Finally generated code needs to be reformed to match related controller code instruction. At the last stage IO were set to accomplish robots cooperation and make their motion synchronized. The pros and cons also will be discussed to clarify the presented results show the feasibility of the method and its effect on production line efficiency. Finally the positive and negative points of the implementation will be discussed.

Keywords: robotic, automated, production, offline programming, CAD

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: Clinton Chidiebere Anyanwu

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Secondary education is a vital part of a virtuous circle of economic growth within the context of a globalised knowledge economy. The teaching of Business Education entails teaching learners the essentials, rudiments, assumptions, and methods of business. Hence, it was deemed necessary for the study to investigate technology integration in Business Education. Drawing from the theoretical frameworks of technological pedagogical content knowledge (TPACK), and unified theory of acceptance and use of technology (UTAUT), the study observes teachers’ level of technology use in Business Education classrooms. Using a mixed-methods sequential explanatory design, probability, and purposive sampling, the majority of participants were found to be not integrating technology to an acceptable level and a small percentage was. After an analysis of constructs from UTAUT, some of this could be attributed to the lack of facilitating conditions in the teaching and learning of Business Education. The implication of the study findings is that poor investment in technology integration in secondary schools in Nigeria affects pedagogical implementations and effective teaching and learning of Business Education subjects. The study concludes that if facilitating conditions and professional development are considered to address the shortfalls in terms of TPACK, technology integration will become a reality in secondary schools in Nigeria.

Keywords: business education, secondary education, technology integration, TPACK, UTAUT

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Authors: J. Bernasovská, R. Lohajová Behulová, E. Petrejčiková, I. Boroňová, I. Bernasovský

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Y chromosome microdeletions are the most common genetic cause of male infertility and screening for these microdeletions in azoospermic or severely oligospermic men is now standard practice. Analysis of the Y chromosome in men with azoospermia or severe oligozoospermia has resulted in the identification of three regions in the euchromatic part of the long arm of the human Y chromosome (Yq11) that are frequently deleted in men with otherwise unexplained spermatogenic failure. PCR analysis of microdeletions in the AZFa, AZFb and AZFc regions of the human Y chromosome is an important screening tool. The aim of this study was to analyse the type of microdeletions in men with fertility disorders in Slovakia. We evaluated 227 patients with azoospermia and with normal karyotype. All patient samples were analyzed cytogenetically. For PCR amplification of sequence-tagged sites (STS) of the AZFa, AZFb and AZFc regions of the Y chromosome was used Devyser AZF set. Fluorescently labeled primers for all markers in one multiplex PCR reaction were used and for automated visualization and identification of the STS markers we used genetic analyzer ABi 3500xl (Life Technologies). We reported 13 cases of deletions in the AZF region 5,73%. Particular types of deletions were recorded in each region AZFa,b,c .The presence of microdeletions in the AZFc region was the most frequent. The study confirmed that percentage of microdeletions in the AZF region is low in Slovak azoospermic patients, but important from a prognostic view.

Keywords: AZF, male infertility, microdeletions, Y chromosome

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Authors: Yuan-Hsiang Chang, Zhong-Xian Peng, Li-Der Jeng

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Music has always been an integral part of human’s daily lives. But, for the most people, reading musical score and turning it into melody is not easy. This study aims to develop an Automatic music score recognition system using digital image processing, which can be used to read and analyze musical score images automatically. The technical approaches included: (1) staff region segmentation; (2) image preprocessing; (3) note recognition; and (4) accidental and rest recognition. Digital image processing techniques (e.g., horizontal /vertical projections, connected component labeling, morphological processing, template matching, etc.) were applied according to musical notes, accidents, and rests in staff notations. Preliminary results showed that our system could achieve detection and recognition rates of 96.3% and 91.7%, respectively. In conclusion, we presented an effective automated musical score recognition system that could be integrated in a system with a media player to play music/songs given input images of musical score. Ultimately, this system could also be incorporated in applications for mobile devices as a learning tool, such that a music player could learn to play music/songs.

Keywords: connected component labeling, image processing, morphological processing, optical musical recognition

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Authors: Angelis P. Barlampas

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Target: The (SARS-CoV-2) is still a threat. AI software could be useful, categorizing the disease into different severities and indicate the extent of the lesions. Materials and methods: AI is a new revolutionary technique, which uses powered computerized systems, to do what a human being does more rapidly, more easily, as accurate and diagnostically safe as the original medical report and, in certain circumstances, even better, saving time and helping the health system to overcome problems, such as work overload and human fatigue. Results: It will be given an effort to describe to the inexperienced reader (see figures), as simple as possible, how an artificial intelligence system diagnoses computed tomography pictures. First, the computerized machine learns the physiologic motives of lung parenchyma by being feeded with normal structured images of the lung tissue. Having being used to recognizing normal structures, it can then easily indentify the pathologic ones, as their images do not fit to known normal picture motives. It is the same way as when someone spends his free time in reading magazines with quizzes, such as <> and <>. General conclusion: The AI mimics the physiological processes of the human mind, but it does that more efficiently and rapidly and provides results in a few seconds, whereas an experienced radiologist needs many days to do that, or even worse, he is unable to accomplish such a huge task.

Keywords: covid-19, artificial intelligence, automated imaging, CT, chest imaging

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Authors: Safa Safdar

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Breast cancer is a type of cancer which is developed by the formation of a tumor on the breast. This tumor invades and causes different electrolyte imbalance. The present study was designed to measure the serum calcium and inorganic phosphorous levels and to check the frequency of hypercalcemia and hypophosphatemia in breast cancer patients. Serum calcium and phosphorous levels of fifty breast cancer women of 18-70 years of age group and fifty healthy women of same age group were measured by using semi-automated chemistry analyzer ( Humalyzer 3000, Human, Germany ). Significant variation in these levels was observed. The mean calcium value in BC patients was higher 9.398 mg/dl as compared to controls which were 8.694 mg/dl. Whereas the mean value of inorganic phosphorus level was lower 4.060 mg/dl in BC patients as compared to controls having 4.456 mg/dl. In this study, the frequency of hypercalcemia in Breast cancer patients was 10% i.e. only 10 out of 50 Breast cancer patients were suffering from hypercalcemia. Whereas the frequency of hypophosphatemia in this study was only 2 % i.e. only 1 out of 50 patients was suffering from hypophosphatemia. Thus it is concluded that there is a significant change in serum calcium and inorganic phosphorous levels in Breast cancer patients as the disease progresses. So, this study will be helpful for the clinicians to maintain serum calcium and phosphorous levels in Breast cancer patients and also preventing them from further complications.

Keywords: serum analysis, calcium, inorganic phosphorus, hpercalcemia hypophosphatemia

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Authors: Mitra Mesgar

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Online learning environment is becoming more popular among learners because of their multiple information representations. Despite the growing importance of online reading strategies among adult learners, little attention has been carried out to postgraduate EFL learners. This study is quantitative research designed and aimed to investigate metacognitive reading strategies employed by Iranian postgraduate learners to read online academic texts. This study is conducted by over 50 Iranian postgraduate students studying in different Malaysian universities. This study used two different survey questionnaires, namely, 1) background questionnaire and 2) OSORS questionnaire. The collected data were analyzed using SPSS. The findings of the study emphasized metacognitive reading strategies used by different aged adult learners. The results of the survey questionnaires revealed that adult learners use global reading strategies as well as problem-solving strategies and support reading strategies. Also, through one-way analysis of variance toward age factor revealed that it has no meaningful changes on metacognitive reading strategy usage. This means that metacognitive reading strategies used by adult learners are independent of age variable. Drawing from findings, adult learners have learning goals, and since they have more exposure to online academic texts, they are able to use different metacognitive online reading strategies that affect their understanding of academic texts.

Keywords: online reading strategies, metacognitive strategies, online learning, independent students, locus of control

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Authors: R. A. Moronfolu, I. M. Ndaks, O. E. Ifekoya

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This study investigated Gender Stereotypes in Leadership Behaviour and its consequent effect on Job Performance of Sports Council Personnel in Lagos State. The descriptive research method was adapted in conducting the study, while eighty sports personnel of Lagos State sports council, Lagos, Nigeria were drawn as respondents using the stratified random sampling technique. A self-structured questionnaire titled “ Gender- Leader Performance Questionnaire (GLPQ) ”was used for data collection. The GLPQ was face validated by three experts in sports management and was subjected to a pilot test using the test retest method for reliability. A total of eighty copies of the validated GLPQ were administered on selected respondents and retrieved on the spot. The descriptive statistics of frequency counts and percentages were used in describing the demographic data collected, while the inferential statistics of Chi-square (X2) and Analysis of Variance (ANOVA) were used in drawing inferences at a level of significance of 0.05. It was observed that gender stereotypes and behaviours of leaders in Lagos State Sports Council, significantly differ. In addition, gender stereotypes and leadership behavior were observed to significantly influence the job performance of sports council personnel in Lagos State.

Keywords: gender, leadership, stereotype, performance

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Authors: Diana Pombo, Maria Loaiza, Mauricio Quijano, Alberto Cadena, Juan Pablo Tello

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In this paper, we present a semi-automatic tool for calculating ejection fraction from an echocardiographic video signal which is derived from a database in DICOM format, of Clinica de la Costa - Barranquilla. Described in this paper are each of the steps and methods used to find the respective calculation that includes acquisition and formation of the test samples, processing and finally the calculation of the parameters to obtain the ejection fraction. Two imaging segmentation methods were compared following a methodological framework that is similar only in the initial stages of processing (process of filtering and image enhancement) and differ in the end when algorithms are implemented (Active Contour and Region Growing Algorithms). The results were compared with the measurements obtained by two different medical specialists in cardiology who calculated the ejection fraction of the study samples using the traditional method, which consists of drawing the region of interest directly from the computer using echocardiography equipment and a simple equation to calculate the desired value. The results showed that if the quality of video samples are good (i.e., after the pre-processing there is evidence of an improvement in the contrast), the values provided by the tool are substantially close to those reported by physicians; also the correlation between physicians does not vary significantly.

Keywords: echocardiography, DICOM, processing, segmentation, EDV, ESV, ejection fraction

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Authors: George Kamil Kamal Abdelnor

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Every major educational institution has incorporated diversity, equity, and inclusion (DEI) principles into its administrative, hiring, and pedagogical practices. Yet these DEI principles rarely incorporate explicit language or critical thinking about disability. Despite the fact that according to the World Health Organization, one in five people worldwide is disabled, making disabled people the larger minority group in the world, disability remains the neglected stepchild of DEI. Drawing on disability studies and crip theory frameworks, the underlying causes of this exclusion of disability from DEI, such as stigma, shame, invisible disabilities, institutionalization/segregation/delineation from family, and competing models and definitions of disability are examined. This paper explores both the ideological and practical shifts necessary to include disability in university DEI initiatives. It offers positive examples as well as conceptual frameworks such as 'divers ability' for so doing. Using Georgetown University’s 2020-2022 DEI initiatives as a case study, this paper describes how curricular infusion, accessibility, identity, community, and diversity administration infused one university’s DEI initiatives with concrete disability-inclusive measures. It concludes with a consideration of how the very framework of DEI itself might be challenged and transformed if disability were to be included.

Keywords: cognitive disability, cognitive diversity, disability, higher education disability, Standardized Index of Diversity of Disability (SIDD), differential and diversity in disability, 60+ population diversity, equity, inclusion, crip theory, accessibility

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Authors: T. Heikkinen, J. Oksman, T. Bragge, A. Nurmi, O. Kontkanen, T. Ahtoniemi

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Motor impairment is an inherent phenotypic feature of several chronic neurodegenerative diseases, and pharmacological therapies aimed to counterbalance the motor disability have a great market potential. Animal models of chronic neurodegenerative diseases display a number deteriorating motor phenotype during the disease progression. There is a wide array of behavioral tools to evaluate motor functions in rodents. However, currently existing methods to study motor functions in rodents are often limited to evaluate gross motor functions only at advanced stages of the disease phenotype. The most commonly applied traditional motor assays used in CNS rodent models, lack the sensitivity to capture fine motor impairments or improvements. Fine motor skill characterization in rodents provides a more sensitive tool to capture more subtle motor dysfunctions and therapeutic effects. Importantly, similar approach, kinematic movement analysis, is also used in clinic, and applied both in diagnosis and determination of therapeutic response to pharmacological interventions. The aim of this study was to apply kinematic gait analysis, a novel and automated high precision movement analysis system, to characterize phenotypic deficits in three different chronic neurodegenerative animal models, a transgenic mouse model (SOD1 G93A) for amyotrophic lateral sclerosis (ALS), and R6/2 and Q175KI mouse models for Huntington’s disease (HD). The readouts from walking behavior included gait properties with kinematic data, and body movement trajectories including analysis of various points of interest such as movement and position of landmarks in the torso, tail and joints. Mice (transgenic and wild-type) from each model were analyzed for the fine motor kinematic properties at young ages, prior to the age when gross motor deficits are clearly pronounced. Fine motor kinematic Evaluation was continued in the same animals until clear motor dysfunction with conventional motor assays was evident. Time course analysis revealed clear fine motor skill impairments in each transgenic model earlier than what is seen with conventional gross motor tests. Motor changes were quantitatively analyzed for up to ~80 parameters, and the largest data sets of HD models were further processed with principal component analysis (PCA) to transform the pool of individual parameters into a smaller and focused set of mutually uncorrelated gait parameters showing strong genotype difference. Kinematic fine motor analysis of transgenic animal models described in this presentation show that this method isa sensitive, objective and fully automated tool that allows earlier and more sensitive detection of progressive neuromuscular and CNS disease phenotypes. As a result of the analysis a comprehensive set of fine motor parameters for each model is created, and these parameters provide better understanding of the disease progression and enhanced sensitivity of this assay for therapeutic testing compared to classical motor behavior tests. In SOD1 G93A, R6/2, and Q175KI mice, the alterations in gait were evident already several weeks earlier than with traditional gross motor assays. Kinematic testing can be applied to a wider set of motor readouts beyond gait in order to study whole body movement patterns such as with relation to joints and various body parts longitudinally, providing a sophisticated and translatable method for disseminating motor components in rodent disease models and evaluating therapeutic interventions.

Keywords: Gait analysis, kinematic, motor impairment, inherent feature

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Authors: Abe Degale D., Cheng Jian

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When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: Khaled M. Alhawiti

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

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

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Authors: Linus O. Asuquo

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Mining in Nigeria and development effort of metallurgical technologies at National Metallurgical Development Centre Jos has been addressed in this paper. The paper has looked at the history of mining in Nigeria, the impact of mining on social and industrial development, and the contribution of the mining sector to Nigeria’s Gross Domestic Product (GDP). The paper clearly stated that Nigeria’s mining sector only contributes 0.5% to the nation’s GDP unlike Botswana that the mining sector contributes 38% to the nation’s GDP. Nigeria Bureau of Statistics has it on record that Nigeria has about 44 solid minerals awaiting to be exploited. Clearly highlighted by this paper is the abundant potentials that exist in the mining sector for investment. The paper made an exposition on the extensive efforts made at National Metallurgical Development Center (NMDC) to develop metallurgical technologies in various areas of the metals sector; like mineral processing, foundry development, nonferrous metals extraction, materials testing, lime calcination, ANO (Trade name for powder lubricant) wire drawing lubricant, refractories and many others. The paper went ahead to draw a conclusion that there is a need to develop the mining sector in Nigeria and to give a sustainable support to the efforts currently made at NMDC to develop metallurgical technologies which are capable of transforming the metals sector in Nigeria, which will lead to industrialization. Finally the paper made some recommendations which traverse the topic for the best expectation.

Keywords: mining, minerals, technologies, value addition

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Authors: Fatemeh Modirzare

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Smart interior design represents a transformative approach to creating living spaces that integrate technology seamlessly into our daily lives, enhancing comfort, convenience, and sustainability. This paper explores the concept of smart interior design, its principles, benefits, challenges, and future prospects. It also highlights various examples and applications of smart interior design to illustrate its potential in shaping the way we live and interact with our surroundings. In an increasingly digitized world, the boundaries between technology and interior design are blurring. Smart interior design, also known as intelligent or connected interior design, involves the incorporation of advanced technologies and automation systems into residential and commercial spaces. This innovative approach aims to make living environments more efficient, comfortable, and adaptable while promoting sustainability and user well-being. Smart interior design seamlessly integrates technology into the aesthetics and functionality of a space, ensuring that devices and systems do not disrupt the overall design. Sustainable materials, energy-efficient systems, and eco-friendly practices are central to smart interior design, reducing environmental impact. Spaces are designed to be adaptable, allowing for reconfiguration to suit changing needs and preferences. Smart homes and spaces offer greater comfort through features like automated climate control, adjustable lighting, and customizable ambiance. Smart interior design can significantly reduce energy consumption through optimized heating, cooling, and lighting systems. Smart interior design integrates security systems, fire detection, and emergency response mechanisms for enhanced safety. Sustainable materials, energy-efficient appliances, and waste reduction practices contribute to a greener living environment. Implementing smart interior design can be expensive, particularly when retrofitting existing spaces with smart technologies. The increased connectivity raises concerns about data privacy and cybersecurity, requiring robust measures to protect user information. Rapid advancements in technology may lead to obsolescence, necessitating updates and replacements. Users must be familiar with smart systems to fully benefit from them, requiring education and ongoing support. Residential spaces incorporate features like voice-activated assistants, automated lighting, and energy management systems. Intelligent office design enhances productivity and employee well-being through smart lighting, climate control, and meeting room booking systems. Hospitals and healthcare facilities use smart interior design for patient monitoring, wayfinding, and energy conservation. Smart retail design includes interactive displays, personalized shopping experiences, and inventory management systems. The future of smart interior design holds exciting possibilities, including AI-powered design tools that create personalized spaces based on user preferences. Smart interior design will increasingly prioritize factors that improve physical and mental health, such as air quality monitoring and mood-enhancing lighting. Smart interior design is revolutionizing the way we interact with our living and working spaces. By embracing technology, sustainability, and user-centric design principles, smart interior design offers numerous benefits, from increased comfort and convenience to energy efficiency and sustainability. Despite challenges, the future holds tremendous potential for further innovation in this field, promising a more connected, efficient, and harmonious way of living and working.

Keywords: smart interior design, home automation, sustainable living spaces, technological integration, user-centric design

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Authors: Tripti Singh

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Digital tools are merging boundaries of different mediums as endeavoured artists exploring new areas. Digital fabric printing has motivated artists to create prints by combining images acquired by photograph, scanned images, computer graphics and microscopic imaginary etc to name few, with traditional media such as hand drawing, weaving, hand printed patterns, printing making techniques and so on. It opened whole new world of possibilities for artists to search, research and combine old and contemporary mediums for their unique art prints. As artistic medium digital art fabrics have aesthetic values which have impact and influence on not only on a personality but also interiors of a living or work space. In this way it can be worn, as fashion statement and also an interior decoration. Digital art fabric prints gives opportunity to print almost everything on any fabric with long lasting prints quality. Single edition and limited editions are possible for maintaining scarcity and uniqueness of an art form. These fabric prints fulfill today’s need, as they are eco-friendly in nature and they produce less wastage compared to traditional fabric printing techniques. These prints can be used to make unique and customized curtains, quilts, clothes, bags, furniture, dolls, pillows, framed artwork, costumes, banners and much, much more. This paper will explore the procedure, process, and progress techniques of digital art fabric printing in depth with suitable pictorial examples.

Keywords: digital art, fabric prints, digital fabric prints, new media

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Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

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Authors: Nik Azmah Nik Yusuff, Faridah Hassan Basri, Rosnidar Mansor

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The purpose of the study is to find out the effectiveness of using Graphic calculators (GC) with Calculator Based Laboratory 2 (CBL2) in teaching and learning of form four biology for these topics: Nutrition, Respiration and Dynamic Ecosystem. Sixty form four science stream students were the participants of this study. The participants were divided equally into the treatment and control groups. The treatment group used GC with CBL2 during experiments while the control group used the ordinary conventional laboratory apparatus without using GC with CBL2. Instruments in this study were a set of pre-test and post-test and a questionnaire. T-Test was used to compare the student’s biology achievement while a descriptive statistic was used to analyze the outcome of the questionnaire. The findings of this study indicated the use of GC with CBL2 in biology had significant positive effect. The highest mean was 4.43 for item stating the use of GC with CBL2 had saved collecting experiment result’s time. The second highest mean was 4.10 for item stating GC with CBL2 had saved drawing and labelling graphs. The outcome from the questionnaire also showed that GC with CBL2 were easy to use and save time. Thus, teachers should use GC with CBL2 in support of efforts by Malaysia Ministry of Education in encouraging technology-enhanced lessons.

Keywords: biology experiments, Calculator-Based Laboratory 2 (CBL2), graphic calculators, Malaysia Secondary School, teaching/learning

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Authors: Omar M. Al Aufi, Abdulwahab Noorwali, Ahmed Al Abd, Safia Alattas, Fathya Zahran, Fahd Almutairi

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Cisplatin (CDDP) is a potent anticancer agent used for several tumor types. Thymoquinone (TQ) is a naturally occurring compound drawing great attention as an anticancer and chemomodulator for chemotherapies. Herein, we studied the potential cytotoxicity of thymoquinone, CDDP and their combination against human oral squamous cell carcinoma cells in contrast to normal oral epithelial cells. CDDP similarly killed both head and neck squamous cell carcinoma cells (UMSCC-14C) and normal oral epithelial cells (OEC). TQ alone exerted considerable cytotoxicity against UMSCC-14C cells, while it induced a weaker killing effect against normal oral epithelial cells (OEC). The equitoxic combination of TQ and CDDP showed additive to synergistic interaction against both UMSCC-14C and OEC cells. TQ alone increased apoptotic cell fraction in UMSCC-14C cells as early as after 6 hours. In addition, prolonged exposure of UMSCC-14C to TQ alone resulted in 96.7±1.6% total apoptosis, which was increased after combination with CDDP to 99.3±1.2% in UMSCC-14C cells. On the other hand, TQ induced a marginal increase in the apoptosis in OEC and even decreased the apoptosis induced by CDDP alone. Finally, apoptosis induction results were confirmed by the change in the expression levels of p53, Bcl-2 and Caspase-9 proteins in both UMSCC-14c and OEC cells.

Keywords: thymoquinone, cisplatin, apoptosis, oral squamous cell carcinoma, P53, Caspase-9, Bcl-2

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Authors: Rudolf Egger

Abstract:

This paper explores the relationships between the basic learning processes of leading trade union workers and their methods for coping with the changes in the life-courses of societies today. It will discuss the fragile discourse on lifelong learning in trade unions and the “production of self-techniques” to get in touch with the new economic forms. On the basis of an empirical project, different processes of the socialization of leading trade union workers will be analysed to discover the consequences of the lifelong learning discourse. The results show what competences they need to develop for the “wider benefits of negotiations”. The main challenge remains to make visible how deeply intertwined trade union learning and education are with development in an ongoing dynamic economic process, rather than a quick-fix injection of skills and information. There is a complex relationship existing between the three ‘partners’, work, learning and society forming. The author suggests that contemporary trade unions could be trendsetters who make their own learning agendas by drawing less on formal education and more on informal and non-formal learning contexts. This is in parallel with growing political and scientific consciousness of the need to arrive at new educational/vocational policies and practices.

Keywords: trade union workers, educational leadership, learning societies, social acting

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Authors: Mona Nikidehaghani, Freda Hui

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In Australia, one-third of mental health carers provide 40 hours or more of unpaid care per week. These hidden workers contribute significantly to the Australian mental health workforce by providing unpaid services both direct and indirect to people in their care. However, carers are often neglected in the healthcare system because Government services focus on those with a mental health condition rather than those supporting them. The aim of this study is to evaluate the perceptions of mental health carers on the effectiveness of community services designed for carers and how these services could be improved. We collaborated with One Door Mental Health, a community organisation that supports mental health carers. Through semi-structured interviews with 27 mental health carers residing in the Illawarra region (NSW), we documented their daily challenges and evaluated outcomes of the current programs for carers. Our findings demonstrate that services such as education programs enable capacity building and improve the social life and mental health of carers. Drawing on the perceptions of mental health carers, this study maps pathways for making meaningful changes in the lives of carers and proposes an outcome framework to evaluate the impact of a community organisation on the lives of their clients. The framework prepared by this project would be replicable, allowing other community organisations to measure the outcomes and improve their services.

Keywords: capacity building, community development, community service, mental health carers

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Authors: Hussain Ali Bekhet, Nor Salwati Othman

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Malaysia has achieved remarkable economic growth since 1957, moving toward modernization from a predominantly agriculture base to manufacturing and—now—modern services. The development policies (i.e., New Economic Policy [1970–1990], the National Development Policy [1990–2000], and Vision 2020) have been recognized as the most important drivers of this transformation. The transformation of the economic structure has moved along with rapid gross domestic product (GDP) growth, urbanization growth, and greater demand for energy from mainly fossil fuel resources, which in turn, increase CO2 emissions. Malaysia faced a great challenge to bring down the CO2 emissions without compromising economic development. Solid policies and a strategy to reduce dependencies on fossil fuel resources and reduce CO2 emissions are needed in order to achieve sustainable development. This study provides an overview of the Malaysian economic, energy, and environmental situation, and explores the existing policies and strategies related to energy and the environment. The significance is to grasp a clear picture on what types of policies and strategies Malaysia has in hand. In the future, this examination should be extended by drawing a comparison with other developed countries and highlighting several options for sustainable development.

Keywords: energy policies, energy efficiency, renewable energy, green building, Malaysia, sustainable development

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Authors: Neda Mozaffari

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This study represents an investigation into the poetics of space within Annie Ernaux's autobiographical work La honte, highlighting the intricate interplay among space, the individual, and society. The research aims to dissect the spatial dimension of the town Yvetot, the referential locale of the author's childhood, drawing upon the frameworks of geocriticism and geopoetics. Our analysis exposes a profound dialectical tension fundamentally predicated on the binaries of "interior/exterior" and "here/there," emphasizing how space and its occupants may reciprocally influence each other. This endeavor aspires to attribute meaning to space in Ernaux's writing in La honte and to forge a connection between spatial elements and the author's autobiographical perspective, heavily imprinted by social dynamics. Ernaux's approach fluctuates between certain binaries that segment space according to the collective perception of social hierarchy, thus unveiling the author's preoccupation with social distancing. Consequently, space transforms into a structured milieu that transfers fear and insecurity to the child, where spatial and architectural segregation further cements class divisions in terms of the language employed by its inhabitants. Ernaux's depiction of space serves both as a repository of collective memory and an instrument of social distinction, where her autobiographical perception echoes within a collective geography marked by class determinism and culture.

Keywords: geocriticism, literary study, social class, social space, spatial analysis

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Authors: Thomas Roche, Erica Wilson, Elizabeth Goode

Abstract:

Universities across the globe are considering how to effect meaningful change in their higher education (HE) delivery in the face of increasingly diverse student cohorts and shifting student learning preferences. This paper reports on a descriptive case study of whole-of-institution curriculum reform at one regional Australian university, where more traditional 13-week semesters were replaced with a 6-week immersive block model drawing on active learning pedagogy. Based on a synthesis of literature in best practice HE pedagogy and principles, the case study draws on student performance data and senior management staff interviews (N = 5) to outline the key changes necessary for successful HE transformation to deliver increased student pass rates and retention. The findings from this case study indicate that an institutional transformation to an immersive block model requires both a considered change in institutional policy and process as well as the appropriate resourcing of roles, governance committees, technical solutions, and, importantly, communities of practice. Implications for practice at higher education institutions considering reforming their curriculum model are also discussed.

Keywords: student retention, immersive scheduling, block model, curriculum reform, active learning, higher education pedagogy, higher education policy

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