Search results for: auditory processing delays

Authors: Atabak Rahimzadeh Ilkhch

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Friction stir processing (FSP) has promised for application of thermo-mechanical processing techniques where aims to change the micro structural and mechanical properties of materials in order to obtain high performance and reducing the production time and cost. There are lots of studies focused on the microstructure of friction stir welded aluminum alloys. The main focus of this research is on the grain size obtained in the weld zone. Moreover in second part focused on temperature distribution effect over the entire weld zone and its effects on the microstructure. Also, there is a need to have more efforts on investigating to obtain the optimal value of effective parameters such as rotational speed on microstructure and to use the optimum tool designing method. the final results of this study will be present the variation of structural and mechanical properties of materials in the base of applying Friction stir processing and effect of (FSP) processing and tensile testing on surface quality. in the hand, this research addresses the FSP f AA-7020 aluminum and variation f ration of rotation and translational speeds.

Keywords: friction stir processing, AA-7020, thermo-mechanical, microstructure, temperature

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Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

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In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

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Authors: L. Kučerová, M. Bystrianský, V. Kotěšovec

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Thermo-mechanical processing with various processing parameters was applied to 0.2%C-0.6%Mn-2S%i-0.8%Cr low alloyed high strength steel. The aim of the processing was to achieve the microstructures typical for transformation induced plasticity (TRIP) steels. Thermo-mechanical processing used in this work incorporated two or three deformation steps. The deformations were in all the cases carried out during the cooling from soaking temperatures to various bainite hold temperatures. In this way, 4-10% of retained austenite were retained in the final microstructures, consisting further of ferrite, bainite, martensite and pearlite. The complex character of TRIP steel microstructure is responsible for its good strength and ductility. The strengths achieved in this work were in the range of 740 MPa – 836 MPa with ductility A_5mm of 31-41%.

Keywords: pearlite, retained austenite, thermo-mechanical treatment, TRIP steel

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Authors: Reham K. El Sawah, N. S. M. El-Tayeb

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This study aims to produce a polymer matrix composite reinforced with Al₂O₃ nanoparticles in order to enhance the mechanical properties of PMMA. The composite was fabricated via Friction stir processing to ensure homogenous dispersion of Al₂O₃ nanoparticles in the polymer, and the processing was submerged to prevent the sputtering of nanoparticles. The surface quality, microstructure, impact energy and hardness of the prepared samples were investigated. Good surface quality and dispersion of nanoparticles were attained through employing sufficient processing conditions. The experimental results indicated that as the percentage of nanoparticles increased, the impact energy and hardness increased, reaching 2 kJ/m2 and 14.7 HV at a nanoparticle concentration of 25%, which means that the toughness and the hardness of the polymer-ceramic produced composite is higher than unprocessed PMMA by 66% and 33% respectively.

Keywords: friction stir processing, polymer matrix nanocomposite, mechanical properties, microstructure

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Authors: Bruno Di Pace, Roxanne H. Padley

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Aims: The recent increase in remote video interaction has increased the number of requests for teleconsultations with plastic surgeons in private practice (70% in the UK and 64% in the USA). This study investigated the motivations for such an increase and the underlying psychological impact on patients. Method: An anonymous web-based poll of 8 questions was designed and distributed to patients seeking cosmetic surgery through social networks in both Italy and the UK. The questions gathered responses regarding 1. Reasons for pursuing cosmetic surgery; 2. The effects of delays caused by the SARS-COV-2 pandemic; 3. The effects on mood; 4. The influence of video conferencing on body-image perception. Results: 85 respondents completed the online poll. Overall, 68% of respondents stated that seeing themselves more frequently online had influenced their decision to seek cosmetic surgery. The types of surgeries indicated were predominantly to the upper body and face (82%). Delays and access to surgeons during the pandemic were perceived as negatively impacting patients' moods (95%). Body-image perception and self-esteem were lower than in the pre-pandemic, particularly during lockdown (72%). Patients were more inclined to undergo cosmetic surgery during the pandemic, both due to the wish to improve their “lockdown face” for video conferencing (77%) and also due to the benefits of home recovery while in smart working (58%). Conclusions: Overall, findings suggest that video conferencing has led to a significant increase in requests for cosmetic surgery and the so-called “Zoom Boom” effect.

Keywords: cosmetic surgery, remote communication, telehealth, zoom boom

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

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

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

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Authors: Hooman Torabifard

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In the last few years, with the progress of technology and computers and artificial intelligence entry into all kinds of scientific and industrial fields, the lifestyles of human life have changed and in general, the way of humans live on earth has many changes and development. Until now, some of the changes has occurred in the context of digital images and image processing and still continues. However, besides all the benefits, there have been disadvantages. One of these disadvantages is the multiplicity of images with high volume and data; the focus of this paper is on improving and developing a method for summarizing and enhancing the productivity of these images. The general method used for this purpose in this paper consists of a set of methods based on data obtained from image processing and using the PSO (Particle swarm optimization) algorithm. In the remainder of this paper, the method used is elaborated in detail.

Keywords: image summarization, particle swarm optimization, image threshold, image processing

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Authors: NeisaKuonuo Tungoe

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Tenyidie, also known as Angami, is spoken by the Angami tribe of Nagaland, North-East India, bordering Myanmar (Burma). It belongs to the Tibeto-Burman language group, falling under the Kuki-Chin-Naga sub-family. Tenyidie studies have seen random attempts at explaining the phonemic inventory of Tenyidie. Different scholars have variously emphasized the grammar or the history of Tenyidie. Many of these claims have been stimulating, but they were often based on a small amount of merely suggestive data or on auditory perception only. The principal objective of this paper is to analyse the affricate segments of Tenyidie as an acoustic study. There are seven categories to the inventory of Tenyidie; Plosives, Nasals, Affricates, Laterals, Rhotics, Fricatives, Semi vowels and Vowels. In all, there are sixty phonemes in the inventory. As mentioned above, the only prominent readings on Tenyidie or affricates in particular are only reflected through auditory perception. As noted above, this study aims to lay out the affricate segments based only on acoustic conclusions. There are seven affricates found in Tenyidie. They are: 1) Voiceless Labiodental Affricate - / pf /, 2) Voiceless Aspirated Labiodental Affricate- / pfh /, 3) Voiceless Alveolar Affricate - / ts /, 4) Voiceless Aspirated Alveolar Affricate - / tsh /, 5) Voiced Alveolar Affricate - / dz /, 6) Voiceless Post-Alveolar Affricate / tʃ / and 7) Voiced Post- Alveolar Affricate- / dʒ /. Since the study is based on acoustic features of affricates, five informants were asked to record their voice with Tenyidie phonemes and English phonemes. Throughout the study of the recorded data, PRAAT, a scientific software program that has made itself indispensible for the analyses of speech in phonetics, have been used as the main software. This data was then used as a comparative study between Tenyidie and English affricates. Comparisons have also been drawn between this study and the work of another author who has stated that there are only six affricates in Tenyidie. The study has been quite detailed regarding the specifics of the data. Detailed accounts of the duration and acoustic cues have been noted. The data will be presented in the form of spectrograms. Since there aren’t any other acoustic related data done on Tenyidie, this study will be the first in the long line of acoustic researches on Tenyidie.

Keywords: tenyidie, affricates, praat, phonemic inventory

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Authors: Mile Vuković, Lana Jerkić Rajić

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Introduction: Broca's aphasia is a non-fluent type of aphasic syndrome, which is primarily manifested by impairment of language production. In connected speech, patients with this type of aphasia produce short sentences in which they often omit function words and morphemes or choose inadequate forms. Aim: This research was conducted to examine the morphosyntactic abilities of people with Broca's aphasia, comparing them with neurologically healthy subjects without a language disorder. Method: The sample included 15 patients with Broca's post-stroke aphasia, who had the relatively intact ability of auditory comprehension. The diagnosis of aphasia was based on the Boston Diagnostic Aphasia Examination. The control group comprised 16 neurologically healthy subjects without data on the presence of disorders in speech and language development. The patients' mother tongue was Serbian. The new Serbian Morphosyntactic Abilities Test (SMAT) was used. Descriptive (frequency, percentage, mean, SD, min, max) and inferential (Mann-Whitney U-test) statistics were used in data processing. Results: We noticed statistically significant differences between people with Broca's aphasia and neurotypical subjects on the SMAT (U = 1.500, z = -4.982, p = 0.000). The results showed that people with Broca's aphasia had achieved low scores on the SMAT, regardless of age (ρ = -0.045, p = 0.873) and time post onset (ρ = 0.330, p = 0.229). Conclusion: Preliminary results show that the SMAT has the potential to detect morphosyntactic deficits in Serbian speakers with Broca's aphasia.

Keywords: Broca’s aphasia, morphosyntactic abilities, agrammatism, Serbian language

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Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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Authors: Laila Akbarali

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In the small scale study, an attempt is made to explore the structure and administrative relationships adopted by Multi Campus Universities [MCU] in UK and Pakistan and how these universities deal with some selected issues with respect to student related functions. For this study, literature on multi-site, divisionalized and other complex organizations related to business and Industry was consulted and an attempt was made to empirically test the normative models in the literature with respect to centralized , deconcentrated and decentralized structures. A questionnaire was used to gather data for this study. Purposive sampling was used. The findings of this study are somewhat different for UK and Pakistan. Contrary to a substantial body of organization theory, the results show that deconcentrated and decentralized universities in the UK are prone to delays in decision making and tend not to sensitive to local needs. In Pakistan on the other hand, deconcentrated and decentralized universities are more sensitive to local needs and there are less delays in decision making. The findings suggest that distance and reporting relationships could perhaps be responsible for the contradiction. The results also suggest that there is better coordination when the subsidiary campus sub-registrar reports to the registrar. The findings also highlight, that in both contexts, leadership at the campus level remains an issue. The results suggest that there may be factors other than structure that allow universities to keep their identity intact. The study highlights that MCU are inclined to use Information Technology and develop broad policies within which they allow their campuses to operate.

Keywords: administrative relationships, Multi-Campus, organization structure, registrar

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Authors: Yasser F. Hassan

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The reduction or removal of noise in a color image is an essential part of image processing, whether the final information is used for human perception or for an automatic inspection and analysis. This paper describes the modeling system based on the rough neural network model to adaptive cellular automata for various image processing tasks and noise remover. In this paper, we consider the problem of object processing in colored image using rough neural networks to help deriving the rules which will be used in cellular automata for noise image. The proposed method is compared with some classical and recent methods. The results demonstrate that the new model is capable of being trained to perform many different tasks, and that the quality of these results is comparable or better than established specialized algorithms.

Keywords: rough sets, rough neural networks, cellular automata, image processing

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Authors: Muhammet Dursun Kaya, Hasan Asil

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In recent years, different methods have been proposed to optimize question processing in database. Although different methods have been proposed to optimize the query, but the problem which exists here is that most of these methods destroy the query execution plan after executing the query. This research attempts to solve the above problem by using a combination of methods of communicating with the database (the present questions in the programming code and using store procedures) and making query processing adaptive in database, and proposing a new approach for optimization of query processing by introducing the idea of dynamic store procedures. This research creates dynamic store procedures in the database according to the proposed algorithm. This method has been tested on applied software and results shows a significant improvement in reducing the query processing time and also reducing the workload of DBMS. Other advantages of this algorithm include: making the programming environment a single environment, eliminating the parametric limitations of the stored procedures in the database, making the stored procedures in the database dynamic, etc.

Keywords: relational database, agent, query processing, adaptable, communication with the database

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Authors: Reza Rezaeipour Honarmandzad

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Wavelet analysis is an exciting method for solving difficult problems in mathematics, physics, and engineering, with modern applications as diverse as wave propagation, data compression, signal processing, image processing, pattern recognition, etc. Wavelets allow complex information such as signals, images and patterns to be decomposed into elementary forms at different positions and scales and subsequently reconstructed with high precision. In this paper a wavelet-based signal processing algorithm for airplane cable fault location is proposed. An orthogonal discrete wavelet decomposition and reconstruction algorithm is used to eliminate the noise in the aircraft cable fault signal. The experiment result has shown that the character of emission pulse and reflect pulse used to test the aircraft cable fault point are reserved and the high-frequency noise are eliminated by means of the proposed algorithm in this paper.

Keywords: wavelet analysis, signal processing, orthogonal discrete wavelet, noise, aircraft cable fault signal

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Authors: M. Kustyawati, F. Pratama, D. Saputra, A. Wijaya

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Tempe composes of not only molds but also bacteria and yeasts. The structure of microorganisms needs to be in balance number in order the tempe to be an acceptable quality for an extended time. Sub supercritical carbon dioxide can be a promising preservation method for tempe as it induces microbial inactivation avoiding alterations of its quality attributes. Fresh tempe were processed using supercritical and sub supercritical CO2 for a defined holding times, then the growth ability of molds and bacteria were analyzed. The results showed that the supercritical CO2 processing for 5 minutes reduced the number of bacteria and molds to 0.30 log cycle and 1.17 log cycles, respectively. In addition, sub supercritical CO2 processing for 20 minutes had fungicidal effect against mold tempe; whereas, the sub supercritical CO2 for 10 minutes had reducing effect against bacteria tempe, and had fungistatic affect against mold tempe. It suggested that sub-supercritical CO2 processing for 10 min could be useful alternative technique for preservation of tempe.

Keywords: tempe, sub supercritical CO2, fungistatic effect, preservation

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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: Ana Paula Soares, Alexandrina Lages, Helena Oliveira, Francisco-Javier Gutiérrez-Domínguez, Marisa Lousada

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From an early age, exposure to a spoken language allows us to implicitly capture the structure underlying the succession of the speech sounds in that language and to segment it into meaningful units (words). Statistical learning (SL), i.e., the ability to pick up patterns in the sensory environment even without intention or consciousness of doing it, is thus assumed to play a central role in the acquisition of the rule-governed aspects of language and possibly to lie behind the language difficulties exhibited by children with development language disorder (DLD). The research conducted so far has, however, led to inconsistent results, which might stem from the behavioral tasks used to test SL. In a classic SL experiment, participants are first exposed to a continuous stream (e.g., syllables) in which, unbeknownst to the participants, stimuli are grouped into triplets that always appear together in the stream (e.g., ‘tokibu’, ‘tipolu’), with no pauses between each other (e.g., ‘tokibutipolugopilatokibu’) and without any information regarding the task or the stimuli. Following exposure, SL is assessed by asking participants to discriminate between triplets previously presented (‘tokibu’) from new sequences never presented together during exposure (‘kipopi’), i.e., to perform a two-alternative-forced-choice (2-AFC) task. Despite the widespread use of the 2-AFC to test SL, it has come under increasing criticism as it is an offline post-learning task that only assesses the result of the learning that had occurred during the previous exposure phase and that might be affected by other factors beyond the computation of regularities embedded in the input, typically the likelihood two syllables occurring together, a statistic known as transitional probability (TP). One solution to overcome these limitations is to assess SL as exposure to the stream unfolds using online techniques such as event-related potentials (ERP) that is highly sensitive to the time-course of the learning in the brain. Here we collected ERPs to examine the neurofunctional correlates of SL in preschool children with DLD, and chronological-age typical language development (TLD) controls who were exposed to an auditory stream in which eight three-syllable nonsense words, four of which presenting high-TPs and the other four low-TPs, to further analyze whether the ability of DLD and TLD children to extract-word-like units from the steam was modulated by words’ predictability. Moreover, to ascertain if the previous knowledge of the to-be-learned-regularities affected the neural responses to high- and low-TP words, children performed the auditory SL task, firstly, under implicit, and, subsequently, under explicit conditions. Although behavioral evidence of SL was not obtained in either group, the neural responses elicited during the exposure phases of the SL tasks differentiated children with DLD from children with TLD. Specifically, the results indicated that only children from the TDL group showed neural evidence of SL, particularly in the SL task performed under explicit conditions, firstly, for the low-TP, and, subsequently, for the high-TP ‘words’. Taken together, these findings support the view that children with DLD showed deficits in the extraction of the regularities embedded in the auditory input which might underlie the language difficulties.

Keywords: development language disorder, statistical learning, transitional probabilities, word segmentation

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Authors: Jonathan Bolduc

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Studies have demonstrated the effectiveness of music training approaches to help children with language disabilities. Because music is closely associated with a number of cognitive functions, including language, it has been hypothesized that musical skills transfer to other domains. Research suggests that music training strengthens basic auditory processing skills in dyslexic children and may ameliorate phonological deficits. Furthermore, music instruction has the particular advantage of being non-literacy-based, thus removing the frustrations that can be associated with reading and writing activities among children with specific learning disabilities. In this study, we assessed the effect of implementing an intensive music program on the development of language skills (phonological and reading) in 4- to 9-year-old children. Seventeen children (N=17) participated in the study. The experiment took place over 6 weeks in a controlled environment. Eighteen lessons of 40 minutes were offered during this period by two music specialists. The Dalcroze, Orff, and Kodaly approaches were used. A series of qualitative measures were implemented to document the contribution of music training to this population. Currently, the data is being analyzed. The first results show that learning music seems to significantly improve verbal memory. We already know that language disabilities are considered one of the main causes of school dropout as well as later professional and social failure. We aim to corroborate that an integrated music education program can provide children with language disabilities with the same opportunities to develop and succeed in school as their classmates. Scientifically, the results will contribute to advance the knowledge by identifying the more effective music education strategies to improve the overall development of children worldwide.

Keywords: music education, music, art education, language diasabilities

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Authors: Puti F. Marzuki, Adrianto Oktavianus, Almerinda Regina

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Interface problems among interacting parties in Indonesian construction projects have most often led to low productivity and completion delay. In the midst of this country’s needs to accelerate construction of public infrastructure providing connectivity among regions and supporting economic growth as well as better living quality, project delays have to be seriously addressed. This paper identifies potential causes factors of interface problems experienced by construction projects in Indonesia. Data are collected through a survey involving the main actors of six important public infrastructure construction projects including railway, LRT, sports stadiums, apartment, and education building construction projects. Five of these projects adopt the design-build project delivery method and one applies the design-bid-build scheme. Interface problems’ potential causes are categorized into contract, management, technical experience, coordination, financial, and environmental factors. Research results reveal that, especially in railway and LRT projects, potential causes of interface problems are mainly technical and managerial in nature. These relate to complex construction execution in highly congested areas. Meanwhile, coordination cause factors are mainly found in the education building construction project with loan from a foreign donor. All of the six projects have to resolve interface problems caused by incomplete or low-quality contract documents. This research also shows that the design-bid-build delivery method involving more parties in construction projects tends to induce more interface problem cause factors than the design-build scheme.

Keywords: cause factors, construction delays, project delivery method, contract documents

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Authors: Keiko Sakai

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In Japan, all stages of public education aim to foster a zest for life. ‘Zest’ implies solving problems by oneself, using acquired knowledge and skills. It is related to the self-regulation of metacognition. To enhance this, establishing good learning habits is important. Tardiness in undergraduate students should be examined based on self-regulation. Accordingly, we focussed on self-monitoring and self-planning strategies among self-regulated learning factors to examine the causes of tardiness. This study examines the impact of self-monitoring and self-planning learning skills on the degree and reason for tardiness in undergraduate students. A questionnaire survey was conducted, targeted to undergraduate students in University X in the autumn semester of 2018. Participants were 247 (average age 19.7, SD 1.9; 144 males, 101 females, 2 no answers). The survey contained the following items and measures: school year, the number of classes in the semester, degree of tardiness in the semester (subjective degree and objective times), active participation in and action toward schoolwork, self-planning and self-monitoring learning skills, and reason for tardiness (open-ended question). First, the relation between strategies and tardiness was examined by multiple regressions. A statistically significant relationship between a self-monitoring learning strategy and the degree of subjective and objective tardiness was revealed, after statistically controlling the school year and the number of classes. There was no significant relationship between a self-planning learning strategy and the degree of tardiness. These results suggest that self-monitoring skills reduce tardiness. Secondly, the relation between a self-monitoring learning strategy and the reason of tardiness was analysed, after classifying the reason for tardiness into one of seven categories: ‘overslept’, ‘illness’, ‘poor time management’, ‘traffic delays’, ‘carelessness’, ‘low motivation’, and ‘stuff to do’. Chi-square tests and Fisher’s exact tests showed a statistically significant relationship between a self-monitoring learning strategy and the frequency of ‘traffic delays’. This result implies that self-monitoring skills prevent tardiness because of traffic delays. Furthermore, there was a weak relationship between a self-monitoring learning strategy score and the reason-for-tardiness categories. When self-monitoring skill is higher, a decrease in ‘overslept’ and ‘illness’, and an increase in ‘poor time management’, ‘carelessness’, and ‘low motivation’ are indicated. It is suggested that a self-monitoring learning strategy is related to an internal causal attribution of failure and self-management for how to prevent tardiness. From these findings, the effectiveness of a self-monitoring learning skill strategy for reducing tardiness in undergraduate students is indicated.

Keywords: higher-education, self-monitoring, self-regulation, tardiness

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Authors: Imtiaz Ali, Imam Mansoor

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Investigations as a part of the academic study were undertaken to identify and evaluate the significant risks associated with the construction of K-span buildings in the region of UAE. Primary field data was collected through questionnaires obtaining specific open and close-ended questions from carefully selected construction firms, civil engineers and, construction manager regarding risks associated to K-span building construction. Historical data available for other regions of the same construction technique was available which was compared for identifying various non-critical and critical risk parameters by comparative evaluation techniques to come up with important risks and potential sources for their control and minimization in K-Span buildings that is increasing in the region. The associated risks have been determined with their Relative Importance Index (RII) values of which Risk involved in Change of Design required by Owners carries the highest value (RII=0.79) whereas, Delayed Payment by Owner to Contractor is one of the least (RII=0.42) value. The overall findings suggest that most relative risks as quantified originate or associated with the contractors. It may be concluded that project proponents undertaking K-span projects in planning and budgeting the cost and delays should take into account of risks on high account if changes in design are also required any delays in the material by the supplier would then be a major risk in K-span project delay. Since projects are, less costly, so owners have limited budgets, then they hire small contractors, which are not highly competent contractors. So study suggests that owner should be aware of these types of risks associated with the construction of K-span buildings in order to make it cost effective.

Keywords: k-span buildings, k-span construction, risk management, relative improvement index (RII)

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Authors: Niyongabo Elyse

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Prefabricated building construction is a pioneering approach that combines design, production, and assembly to attain energy efficiency, environmental sustainability, and economic feasibility. Despite continuous development in the industry in China, the low technical maturity of standardized design, factory production, and construction assembly introduces uncertainties affecting prefabricated component production and on-site assembly processes. This research focuses on enhancing project management performance under uncertainty to help enterprises navigate these challenges and optimize project resources. The study introduces a perspective on how uncertain factors influence the implementation of prefabricated building construction projects. It proposes a theoretical model considering project process management ability, adaptability to uncertain environments, and collaboration ability of project participants. The impact of uncertain factors is demonstrated through case studies and quantitative analysis, revealing constraints on implementation time, cost, quality, and safety. To address uncertainties in prefabricated component production scheduling, a fuzzy model is presented, expressing processing times in interval values. The model utilizes a cooperative co-evolution evolution algorithm (CCEA) to optimize scheduling, demonstrated through a real case study showcasing reduced project duration and minimized effects of processing time disturbances. Additionally, the research addresses on-site assembly construction scheduling, considering the relationship between task processing times and assigned resources. A multi-objective model with fuzzy activity durations is proposed, employing a hybrid cooperative co-evolution evolution algorithm (HCCEA) to optimize project scheduling. Results from real case studies indicate improved project performance in terms of duration, cost, and resilience to processing time delays and resource changes. The study also introduces a multistage dynamic process control model, utilizing IoT technology for real-time monitoring during component production and construction assembly. This approach dynamically adjusts schedules when constraints arise, leading to enhanced project management performance, as demonstrated in a real prefabricated housing project. Key contributions include a fuzzy prefabricated components production scheduling model, a multi-objective multi-mode resource-constrained construction project scheduling model with fuzzy activity durations, a multi-stage dynamic process control model, and a cooperative co-evolution evolution algorithm. The integrated mathematical model addresses the complexity of prefabricated building construction project management, providing a theoretical foundation for practical decision-making in the field.

Keywords: prefabricated construction, project management performance, uncertainty, fuzzy scheduling

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Authors: Mst Shapna Akter, Hossain Shahriar

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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

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Authors: Ayo Osisanya, Promise Ebuka Okonkwo

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Reduced hearing sensitivity among the elderly has been attributed to some risk factors and influence of age-related degenerative conditions such as diabetes, cardiovascular disease, Alzheimer’s disease, bipolar disorder, and hypertension. Hearing loss; especially the age-related type (presbycusis), has been reported as one of the global burden affecting the general well-being and quality of life of the elderly with hypertension. Thus, hearing loss has been observed to be associated with hypertension and functional decline in elderly, as this condition makes them experience poor communication, fatigue, reduced social functions, mood-swing, and withdrawal syndrome. Emerging research outcomes indicate a strong relationship between hypertension and reduced auditory performance among the elderly. Therefore, this study determined the prevalence, types, and patterns of hearing loss associated with hypertension, with a bid to suggesting comprehensive management strategies and a model of creating awareness towards promoting good healthy living among the elderly in Nigeria. One hundred and seventy-two elderly, aged 65–85 with hypertension were purposively selected from patients undergoing treatment for hypertension in some tertiary hospitals in southwest Nigeria for the study. Participants were suggested to Pure-Tone Audiometry (PTA) through the use of Maico 53 Diagnostic Audiometer to determine the degree, types ad patterns of hearing loss among the elderly with hypertension. Results showed that 148 (86.05%) elderly with hypertension presented with different degrees, types, and patterns of hearing loss. Out of this number, 123 (83.11%) presented with bilateral hearing loss, while 25 (16.89%) had unilateral hearing loss. Degree of hearing loss, 74 moderate hearing loss, 118 moderately severe and 50 severe hearing loss. 36% of the hearing loss appeared as flat audiometric configuration, 24% were slopping, 19% were rising, while 21% were tough-shaped audiometric configurations. The findings showed high prevalence of hearing loss among the elderly with hypertension in Southwest, Nigeria. Based on the findings, management of elderly with hypertension should include regular audiological rehabilitation and total adherence to hearing conservation principles, otological management, regulation of blood pressure and adequate counselling / follow-up services.

Keywords: auditory performance, elderly, hearing loss, hypertension

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Authors: Hanaa M. Abdelgawad, Mona Safar, Ayman M. Wahba

Abstract:

Real-time image and video processing is a demand in many computer vision applications, e.g. video surveillance, traffic management and medical imaging. The processing of those video applications requires high computational power. Therefore, the optimal solution is the collaboration of CPU and hardware accelerators. In this paper, a Canny edge detection hardware accelerator is proposed. Canny edge detection is one of the common blocks in the pre-processing phase of image and video processing pipeline. Our presented approach targets offloading the Canny edge detection algorithm from processing system (PS) to programmable logic (PL) taking the advantage of High Level Synthesis (HLS) tool flow to accelerate the implementation on Zynq platform. The resulting implementation enables up to a 100x performance improvement through hardware acceleration. The CPU utilization drops down and the frame rate jumps to 60 fps of 1080p full HD input video stream.

Keywords: high level synthesis, canny edge detection, hardware accelerators, computer vision

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Authors: Khaled M. Alhawiti

Abstract:

This paper investigates the future of medicine and the use of Natural language processing. The importance of having correct clinical information available online is remarkable; improving patient care at affordable costs could be achieved using automated applications to use the online clinical information. The major challenge towards the retrieval of such vital information is to have it appropriately coded. Majority of the online patient reports are not found to be coded and not accessible as its recorded in natural language text. The use of Natural Language processing provides a feasible solution by retrieving and organizing clinical information, available in text and transforming clinical data that is available for use. Systems used in NLP are rather complex to construct, as they entail considerable knowledge, however significant development has been made. Newly formed NLP systems have been tested and have established performance that is promising and considered as practical clinical applications.

Keywords: clinical information, information retrieval, natural language processing, automated applications

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Authors: H. S. Sathish, H. S. Jagadeesh, Skanda Kumar

Abstract:

Journey time and delay study is used to evaluate the quality of service, the travel time and study can also be used to evaluate the quality of traffic movement along the route and to determine the location types and extent of traffic delays. Components of delay are boarding and alighting, issue of tickets, other causes and distance between each stops. This study investigates the total journey time required to travel along the stretch and the influence the delays. The route starts from Kempegowda Bus Station to Yelahanka Satellite Station of Bangalore City. The length of the stretch is 16.5 km. Modal split analysis has been done for this stretch. This stretch has elevated highway connecting to Bangalore International Airport and the extension of metro transit stretch. From the regression analysis of total journey time it is affected by delay due to boarding and alighting moderately, Delay due to issue of tickets affects the journey time to a higher extent. Some of the delay factors affecting significantly the journey time are evident from F-test at 10 percent level of confidence. Along this stretch work trips are more prevalent as indicated by O-D study. Modal shift analysis indicates about 70 percent of commuters are ready to shift from current system to Metro Rail System. Metro Rail System carries maximum number of trips compared to private mode. Hence Metro is a highly viable choice of mode for Bangalore Metropolitan City.

Keywords: delay, journey time, modal choice, regression analysis

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Authors: Sanjay Singh, Sushil Kumar, Rashmi Jain

Abstract:

Quantum registering is another pattern in computational hypothesis and a quantum mechanical framework has a few helpful properties like Entanglement. We plan to store data concerning the structure and substance of a basic picture in a quantum framework. Consider a variety of n qubits which we propose to use as our memory stockpiling. In recent years classical processing is switched to quantum image processing. Quantum image processing is an elegant approach to overcome the problems of its classical counter parts. Image storage, retrieval and its processing on quantum machines is an emerging area. Although quantum machines do not exist in physical reality but theoretical algorithms developed based on quantum entangled states gives new insights to process the classical images in quantum domain. Here in the present work, we give the brief overview, such that how entangled states can be useful for quantum image storage and retrieval. We discuss the properties of tripartite Greenberger-Horne-Zeilinger and W states and their usefulness to store the shapes which may consist three vertices. We also propose the techniques to store shapes having more than three vertices.

Keywords: Greenberger-Horne-Zeilinger, image storage and retrieval, quantum entanglement, W states

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Authors: Dong Liu

Abstract:

By sending a high-frequency probe wave and a low-frequency pump wave to a specimen, the vibroacoustic method evaluates the defect’s severity according to the modulation index of the received signal. Many studies experimentally proved the significant sensitivity of the modulation index to the tiny contact type defect. However, it has also been found that the modulation index was highly affected by the frequency of probe or pump waves. Therefore, the chirp signal has been introduced to the VAM method since it can assess multiple frequencies in a relatively short time duration, so the robustness of the VAM method could be enhanced. Consequently, the signal processing method needs to be modified accordingly. Various studies utilized different algorithms or combinations of algorithms for processing the VAM signal method by chirp excitation. These signal process methods were compared and used for processing a VAM signal acquired from the steel samples.

Keywords: vibroacoustic modulation, nonlinear acoustic modulation, nonlinear acoustic NDT&E, signal processing, structural health monitoring

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Authors: Seongsoo Lee

Abstract:

Motion estimation occupies the heaviest computation in HEVC (high efficiency video coding). Many fast algorithms such as TZS (test zone search) have been proposed to reduce the computation. Still the huge computation of the motion estimation is a critical issue in the implementation of HEVC video codec. In this paper, motion estimator architecture with optimized number of PEs (processing element) is presented by exploiting early termination. It also reduces hardware size by exploiting parallel processing. The presented motion estimator architecture has 8 PEs, and it can efficiently perform TZS with very high utilization of PEs.

Keywords: motion estimation, test zone search, high efficiency video coding, processing element, optimization

Procedia PDF Downloads 337