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Development of a semi-automated impact device based on human behaviour recognition for in service modal analysis of structures / Fahad Zahid
No full textCurrent Impact Synchronous Modal Analysis (ISMA), an operational modal analysis technique incorporated with either manual impact hammer or Automated Phase Controlled Impact Device (APCID) faces challenges on its effectiveness and practicality in real industrial applications. Studies show that the manual operation of this technique is laborious and time intensive due to the lack of control and knowledge of the impact with respect to phase angle of disturbance. APCID solves this problem as it provides knowledge and control of impact with respect to phase angle of disturbance. However, its large size and heavy weight makes it unsuitable for real world applications. As automated impact application makes APCID bulky, automated impacts can be replaced with manual impacts while still using APCID control. However, the randomness in human behaviour significantly reduces the effectiveness of APCID control due to the lack of control of impact with respect to phase angle of disturbance. Studies show that human behaviours can be recognized using devices like Inertial Measurement Unit (IMU) and Electroencephalogram (EEG) in conjunction with machine learning. In this study, machine learning models are developed using IMU and EEG to recognize physical and cognitive human behaviours respectively, to replace APCID with semi-automated impact device (IMU-ISMA/EEG-ISMA) while still using APCID control. For physical human behaviour recognition, impact classification model was developed to classify 13 different impact types using orientation data from IMU and then used with reaction time and impact speed (measured through IMU), to predict impact time and adjust APCID control accordingly. Impact time was predicted with 5.2% mean prediction error. For improved practicality, EEG was used for cognitive human behaviour recognition. Machine learning model was developed for predicting impact time before the impact and make adjustment in APCID control accordingly. Impact time was predicted with 8.3% mean prediction error. The IMU and EEG based time prediction models were integrated with APCID control to perform ISMA. Using both IMU-ISMA and EEG-ISMA, the cyclic load components at 20 Hz and 30 Hz running frequencies were reduced by over 80%. For both the devices, the extracted modal parameters were in very good correlation with the benchmark, Experimental Modal Analysis (EMA) data and all the modes were identified with less than 3% and 6% difference in natural frequencies and damping respectively, and Modal Assurance Criterion (MAC) values greater than 0.9 for all modes. Using IMU-ISMA and EEG-ISMA, on average, it took 24-26 impacts and 18-19 impacts, respectively, to complete one test. Manual ISMA, (i.e., Random ISMA) was also performed at 20 Hz and 30 Hz and results show that IMU-ISMA and EEG-ISMA were able to extract more modes with better accuracy compared to Random ISMA. Additionally, IMU-ISMA took 12-20% less number of impacts and EEG-ISMA took 35-40% less number of impacts to get better results. Both variations of semi-automated impact device present a portable and practical solution for in-service modal analysis with comparable accuracy however, EEG-ISMA is a less labour intensive and user-friendly solution as it takes around 24-27% smaller number of impacts to complete a test
A stacked ensemble deep learning model for water quality prediction / Wong Wen Yee
No full textWater quality management is crucial to ensure water security for the sustainability of health, productivity, and livelihoods. Contamination of water sources often occurs due to illegal waste dumping, sewage, and industrial discharge. This causes hazardous substances such as pesticides, heavy metals, and pathogens to seep into waterways. Therefore, the use of water quality indicators to detect the presence of pollutants is very important. Conventional water quality index (WQI) assessment methods are limited to features such as water acidity or basicity (pH), dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), ammoniacal nitrogen (NH3N), and suspended solids (SS). These features are too common and insufficient to represent the true nature of water quality. Other significant parameters including fecal coliform, heavy metals, and nutrients were not part of the WQI formula. Hence, this study aims to bridge the research gap of using different water quality parameters in water quality assessment through artificial intelligence. In this work, the potential of other water quality parameters as input variables is investigated and discussed. There are 17 input features, namely conductivity (COND), salinity (SAL), turbidity (TUR), dissolved solids (DS), nitrate (NO3), chloride (Cl), phosphate (PO4), arsenic (As), chromium (Cr), zinc (Zn), calcium (Ca), iron (Fe), potassium (K), magnesium (Mg), sodium (Na), E. coli, and total coliform, analyzed using five regression algorithms: random forest (RF), AdaBoost, support vector regression (SVR), decision tree regression (DTR), and multilayer perceptron (MLP) for preliminary model selection. The results show that the RF algorithm exhibits better prediction performance, with R2 of 0.798. The dataset is then validated with the RF classifier, and results are then improved by applying the synthetic minority oversampling technique (SMOTE) to tackle imbalanced datasets. The proposed method is shown to achieve 78.13%, 72.99%, 63.51%, and 66.85% accuracy, precision, recall, and F1 score, respectively. The results and analysis obtained from this study have proven the possibility of predicting WQI using other input features. In addition, the research extended its study to understanding imbalanced data in water quality datasets. Classifiers often perform poorly in skewed data due to a bias in the majority class. Therefore, this paper aims to explore the use of ensemble and deep learning techniques to simplify the classification process of imbalanced data. The study then proposes a stacked ensemble deep learning framework for a faster and more efficient water quality analysis. The stacked ensemble deep learning method applied was proven robust with a performance accuracy, precision, recall, and F1 score at 95.69%, 94.96%, 92.92%, and 93.88% respectively. The proposed deep learning model renders faster without the use of SMOTE. Any resampling algorithm is not a necessity in the case of this proposed algorithm
Isu-isu terpilih dalam pelaksanaan hukuman mati mandatori di Malaysia menurut perspektif syariah / Muhammad Hafizuddin Samat
No full textHukuman mati mandatori telah lama dilaksanakan di Malaysia. Pelaksanaannya dalam sistem perundangan jenayah adalah sebagai satu langkah kerajaan dalam menjamin keadilan dan keamanan dalam kehidupan bermasyarakat. Namun, dalam pelaksanaan hukuman mati mandatori di Malaysia, terdapat isu-isu dan masalah yang berlaku yang menimbulkan gesaan untuk memansuhkannya. Rentetan daripada itu, kerajaan telah menyatakan hasrat untuk memansuhkan hukuman mati mandatori pada tahun 2018 dan bersetuju untuk memansuhkan hukuman mati mandatori dan menggantikannya dengan hukuman mati dengan kuasa budi bicara mahkamah pada tahun 2022. Oleh itu, kajian ini bertujuan membincangkan isu-isu terpilih dalam pelaksanaan hukuman mati mandatori di Malaysia menurut perspektif syariah. Kajian memfokuskan kepada beberapa aspek iaitu perbandingan hukuman mati mandatori berdasarkan undangundang negara dan perundangan syariah, isu dan permasalahan dalam pelaksanaan hukuman mati mandatori dan kewajaran pelaksanaannya di Malaysia dari perspektif syariah dan isu-isu teknikal undang-undang dalam pelaksanaan hukuman mati mandatori di Malaysia dari perspektif syariah. Metode kepustakaan dan temu bual semi struktur dengan persampelan purposif telah digunakan untuk mengumpulkan data kajian. Seterusnya, data ini dianalisis menggunakan metode deduktif, induktif, tematik dan komparatif. Hasil kajian mendapati bahawa hukuman mati mandatori wajar dikekalkan untuk kesalahan melibatkan aktiviti keganasan dan kesalahan terhadap Yang di-Pertuan Agong. Manakala, hukuman mati mandatori bagi kesalahan membunuh dengan sengaja dan kesalahan yang melibatkan senjata api wajar dipinda dan digantikan dengan hukuman mati dengan kuasa budi bicara mahkamah. Selain itu kajian mendapati, hukuman mati mandatori perlu disegerakan bagi pesalah yang telah didapati bersalah dan tahap pembuktian bagi kesalahan hukuman mati mandatori mestilah pada kadar melampaui sebarang keraguan. Akhirnya, kajian menyimpulkan bahawa konsep dalam perundangan jenayah Islam mesti diterapkan secara menyeluruh agar isu-isu dalam pelaksanaan hukuman mati mandatori dapat diselesaikan
The Qur’anic approach in rehabilitation of the behavioural disorders and criminal tendencies: Applied study on rehabilitation centre for repentant in Kuwait / Abdullah A S A AlMutairi
No full textA lot of societies suffer from the problem of behavioral disorder and criminal propensity
among many individuals. This led to an increase in crime and the need for rehabilitation
and treatment. Rehabilitation centers for people with behavioral disorders and criminal
tendencies were established in many countries to integrate this group into society and make
them useful people for themselves and society. The study discussed the Holy Qur’an’s
approach in evaluating behavioral disorders and criminal propensities, showed the causes
and types of behavioral disorders and criminal propensities in the Holy Qur’an, and focused
on the Holy Qur’an’s properties in evaluating behavioral disorders and criminal
propensities and the evaluation tools and standards of the Holy Qur’an. In addition, this
study presented glimpses from the life of Allah’s Messenger (May Allah grant him
blessings and peace) in dealing with behavioral disorders to demonstrate the prophetic
methods and styles in treating behavioral disorders and criminal propensities. The study
depended on a number of methodologies appropriate to the study’s subject and objectives,
namely: the descriptive, analytical, inductive, and deductive methodologies, and the applied
descriptive methodology for this study is applied on the Repentant Rehabilitation Center in
Kuwait. The researcher prepared questionnaires and then distributed them on the center’s
dwellers, then interviewed a group of the teachers, and finally attempted the statistical
analysis of the applied study. The study aimed to clarify the means and methods that can be
used in evaluating the behavioral disorders and criminal propensities, documenting the
applications of the Qur’anic approach in treating the behaviorally disordered people and
those with criminal tendencies, and highlighting the effect of applying the means and methods of the Holy Qur’an in evaluating behavioral disorders and criminal propensities
among those enrolled in the Repentant Rehabilitation Center in the State of Kuwait, in
order to circulate them to centers similar to the center in this study in order to lessen the
crime rates. The study found the following results. the Holy Qur’an used many tools in
evaluating the behavioral disorders and criminal propensities. There are standards that must
be adhered to while using the Qur’anic approach in the evaluation process, so that the
process proceeds in a correct manner and become fruitful. The Sunnah of Allah’s
Messenger (May Allah grant him blessings and peace) represents the practical application
of the Holy Qur’an in correcting behavioral disorders and criminal propensities. The
researcher recommended the need to carry out encyclopedic studies that include the
Qur’anic and Prophetic approaches in dealing with behaviorally disturbed people and those
with criminal propensities. This encyclopedia includes the Qur’anic approach and its
practical applications (the Prophet’s Sunnah), in order to reach a useful educational
approach for this group
Pengurusan kawalan Islam terhadap aktiviti perniagaan: Kajian kes bazar jumaat di Masjid Jamek Sultan Abdul Aziz Petaling Jaya / Muhammad Ezmir Kushairy Roslee
No full textPenganjuran perniagaan di masjid telah menimbulkan polemik di kalangan masyarakat. Segelintir berpandangan bahawa penganjuran perniagaan di masjid telah menimbulkan pelbagai masalah yang mencemarkan kesucian masjid sebagai pusat ibadah. Antara isu yang berlaku ialah isu hukum berniaga di masjid, kebersihan kawasan masjid, adab di masjid, serta pengunjung masih berjual beli dan tidak masuk ke masjid sedangkan azan sudah berkumandang. Tujuan kajian ini dijalankan bagi membina suatu parameter perniagaan di masjid berdasarkan pandangan fiqh. Di samping menjelaskan konsep pengurusan kawalan Islam terhadap perniagaan di kawasan masjid, kajian ini juga menganalisis pengurusan kawalan Islam yang dilaksanakan oleh pihak pengurusan masjid dan operasi perniagaan Bazar Jumaat di Masjid Jamek Sultan Abdul Aziz. Data-data dikumpul melalui temu bual terhadap responden yang terdiri daripada pentadbir masjid, penduduk, dan para penjual. Selain itu juga, bagi mengukuhkan lagi data dan maklumat yang diterima, pengkaji melakukan pemerhatian terhadap operasi Bazar Jumaat yang berlangsung. Kemudian, data-data yang diterima dianalisis melalui analisis tematik. Hasil daripada pembinaan parameter perniagaan di masjid, kajian ini akan menyumbang kepada suatu panduan kepada pihak pengurusan masjid di dalam menjalankan aktiviti perniagaan di masjid. Pada masa yang sama memberi kesedaran kepada masyarakat kepentingan memelihara kesucian institusi masjid sebagai tempat yang suci dan mulia. Bagi memastikan parameter aktiviti perniagaan di masjid dapat dipatuhi, maka pengurusan kawalan Islam adalah penting supaya matlamat dan objektif yang ditetapkan dapat dicapai
Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altarturi
No full textThe escalating concern revolves around cybersecurity for children, given the unprecedented internet access that potentially exposes them to objectionable content. Recent data highlight the problem's severity, revealing a 97% surge in children's online exploitation and a 28% rise in reported minor sexual abuse material online. This problem has motivated academia and industry to develop frameworks for cyber parental control. Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. Most existing studies adopt one classifying approach, resulting in an ineffective and unreliable classification of objectionable content. In terms of content, only a few studies address a wide range of objectionable content topics, whereas most studies primarily focus on pornography topics. Furthermore, studies on classifying objectionable contents use conventional topic models, such as the Latent Dirichlet Allocation (LDA) and its variants. These models are built to work on generic fields and conventional documents, ignoring the structure of web content in the HTML documents and insufficiently performing when applied to web content data. Neglecting the unique structure of web content leads to missing the otherwise interpretable topics and, therefore, to low topic quality and classification accuracy. Moreover, the lack of publicly accessible objectionable web content ground-truth datasets has prevented a fair, coherent comparison of the various frameworks. This research aims to propose an effective and accurate framework for classifying objectionable web content. The Cyber Parental Control Framework (CPCF) employs a multistep approach and a novel web mining technique. It uses the URL blacklist and whitelist methods as the first and second filter layers. A final classification layer is then applied in which an HTML Topic Model (HTM) developed by this study analyses HTML tags to understand the structure of the webpages. The HTM is an enhancement of the LDA model. This study creates a ground-truth objectionable web content dataset to achieve the aim. The ground-truth dataset contains 8,000 labelled websites, split equally between objectionable and unobjectionable websites and comprising over 2 million pages. The study conducted four series of experiments to examine the CPCF. The first experiment’s results demonstrate the reliability of the ground-truth dataset using the existing state-of-the-art classifiers. The results of the second experiment demonstrate the limitations of the existing topic models web applied to web content. The third experiment then evaluates the effectiveness of the HTM in discovering interpretable topics and term patterns compared to the widely used LDA model. The final experiment investigates the performance and accuracy of the CPCF using the HTM model. The CPCF demonstrates effectiveness in web content classification and the ability to overcome the limitations of the existing methods. Finally, a web-based functional prototype was developed to facilitate the CPCF’s applicability and to offer a valuable reference for future research and prospects in this domain. The contribution of this study is a framework to produce an objectionable web content classification for cyber parental control, which was proposed, designed, evaluated, and simulated
A multi-method inquiry into the cognitive effort in human translation and neural machine translation post-editing processes / Wang Yu
No full textDue to the inaccuracies of Machine Translation (MT), Post-editing (PE) by human translators is inevitable. While most studies have reviewed HT and PE as end products, questions concerning whether the effort made by the human to polish an MT is worth it and which texts would be more efficient to be post-edited remain unanswered in the area of the cognitive translation process, especially from an empirical perspective. This study, therefore, adopts a multi-method approach, incorporating quantitative data derived from keystroke-logging and eye-tracking, with qualitative data from retrospective interviews to examine a) the differences in cognitive effort between HT and PE in terms of the whole process and the sub-phases (orientation, drafting, and revision); b) the differences in the cognitive effort between HT and PE according to text types; c) the underlying reasons for the different cognitive effort in HT and PE as well as in different text types in Chinese to English translation. A total of 25 participants from two different groups, a non-experienced group (15 students) and an experienced group (10 professional translators) were recruited to manually translate and to post-edit six texts of three text types (2 informative texts, 2 expressive texts, and 2 operative texts). Total task time, total fixation duration, fixation count, pause, and the number of keyboard activities were used as the indicators of cognitive effort. R language software was performed for statistical analysis. T-test and Liner Mixed-effect Model were used to test the significant difference and interaction between the variables. Thematic analysis was used for the qualitative data gathered from the retrospective interview. Through the comparison of the effort between HT and PE, this study concluded that PE emancipates significantly reduces human effort temporally, cognitively, and technically. The comparison of the three phases shows that translators tend to spend a long time reading the source texts before they carry out the PE works while spending a shorter time on drafting. Translators are also aware of the importance of revision after the HT and PE drafting work. The investigation of the influence of the text types on cognitive effort reveals that texts with different types bring an obvious change to translators’ time investment, mental process, and technical input in the translation process, and this change is also affected by the task type (HT and PE). Generally, in translating operative texts, translators benefit most from the “MT plus PE” mode from the perspective of effort saving. The interview data further confirmed that in translating expressive texts, the transfer of the mode is challenging, which requires translators to adopt a free translation, while in translating informative text type, the difficulty lies in the transfer of field, a literal translation method is thus adopted. Translators with different translation experiences also demonstrate different behavioural tendencies in HT and PE. Overall, student translators are more careful in carrying out the demanding task of HT while professional translators are more careful in carrying out the less demanding PE task.
The study has practical implications for both translators and translator training
Effects of teacher-led collaborative modeling on Chinese EFL learners’ writing development / Li Yang
No full textAmong the four language skills (i.e., listening, speaking, reading and writing), writing
has been recognized as the most challenging skill to master. In order to excel in academic
learning, one of the pressing goals for EFL (English as a foreign language) university
students is to develop an effective proficiency in writing, including the writing of
academic texts in their relevant fields of study. Recently, there has been an increased
awareness of the need to better understand the trajectory of EFL students’ writing
development and the role of writing instruction in assisting the students’ efforts to develop
their academic writing skills. However, empirical, detailed and well-designed research on
investigating the efficacy of L2 writing instruction in the Chinese EFL writing classroom
is lacking. Hence, this study aims to address this gap. It examines the effects of teacherled
collaborative modeling, a recent innovation in L2 writing instruction, on Chinese EFL
university students’ L2 writing. This study measures the development of a number of
linguistic features, including syntactic complexity, lexical complexity and language
accuracy, which will be the study’s main contribution. This study also investigates the
EFL students’ perceptions of the new teaching method. In realizing this research aim, this
longitudinal quasi-experimental study adopted an explanatory mixed-methods research
design (QUANàqual). The participants were 60 (N=60) Chinese EFL university students
from two intact English classes. One experimental group received the teacher-led
collaborative modeling approach as pedagogical intervention and one control group did
not receive this type of intervention but follow the regular teaching instruction. In total,
360 written essays produced by the participants were collected at six-time points during
one semester (16 weeks). A post-experiment questionnaire was distributed to the students
in the experimental group to elicit their opinions and perceptions of the novel teaching
method. A semi-structured interview was also conducted to triangulate the findings and deepen the understanding of the students’ perspectives. The data collected from students’
written texts were analyzed quantitatively. Analytical tools such as L2SCA (L2 Syntactic
Complexity Analyzer), Stanford parser, Stanford Tregex, LCA (Lexical Complexity
Analyzer) and Louvain error tagging software were employed to measure the
development of syntactic complexity, lexical complexity and language accuracy in the
students’ written texts. Different statistical analysis tests were conducted to assess the
variance between the two groups. Following this, the data from the post-experiment
questionnaire and semi-structured interviews were analyzed quantitatively and
qualitatively. The findings revealed that the students from the experimental group showed
considerable progress in terms of two, namely, syntactic complexity and language
accuracy, of the three linguistic features assessed in this study. This suggested that the
application of the novel teacher-led collaborative modeling approach might be an
effective teaching approach in the L2 writing classroom. Findings from the postexperiment
survey and semi-structured interviews indicated that, overall, the students had
positive perceptions of the newly introduced pedagogical approach. There are several
other implications regarding the methodological and pedagogical aspects that stem from
the findings
A study on the photodegradation of organic pollutants using visible light-active Cu2O/WO3/TiO2nanocomposite photocatalyst / Jenny Chau Hui Foong
No full textTextile dyeing wastewater becomes one of the root causes of environmental pollution. Photodegradation is considered the most promising approach due to its advantages, such as energy-saving, high performance, thorough degradation of organic compounds, and production of environment-friendly end products. Titanium dioxide (TiO2) is one of the photocatalysts that shows high photodegradation performance. However, the effectiveness of TiO2 is limited by the requirement of ultraviolet light excitation, wide band gap energy, and fast recombination of electron-hole pairs. In this study, a solar-responsive cuprous oxide (Cu2O)/tungsten oxide (WO3)/titanium dioxide (TiO2) ternary composite was successfully synthesized through an ultrasonic-assisted hydrothermal technique with varying weight% (wt.%) of WO3 and Cu2O and calcination temperature. Characterization techniques such as thermal gravimetric analysis (TGA), Raman, X-ray diffraction (XRD), field emission scanning electron microscope (FESEM), transmission electron microscope (TEM), Brunauer-Emmett-Teller (BET), X-ray photoelectron spectroscopy (XPS), UV-Vis, and zeta potential were used to study the morphological and crystalline structure of the synthesized Cu2O/WO3/TiO2 (CWT) composite. Next, a photoelectrochemical (PEC) study including electrochemical impedance spectrum (EIS), Mott-Schottky (MS), transient photocurrent, transient photovoltage, and linear sweep voltammetry (LSV) was used to explore the charge carrier characteristics. The formation of CWT ternary composite was proved to reduce the band gap of TiO2 effectively. The prepared 0.50CWT-500 composite exhibited the highest photodegradation activity (2.29 × 10−2 min−1) compared to the TiO2 (1.59 × 10−2 min−1) and 0.50WT composite (2.13 × 10−2 min−1) and 0.50CWT-500 showed complete mineralization in chemical oxygen demand (COD) reading towards 30 ppm of Reactive Black 5 (RB5) dye under 120 min of light irradiation. Effects of large surface area, small crystallite size, high pore volume and size, and low electron-hole pair recombination rate attributed to the superiority of 0.50CWT-500. Besides, 0.50CWT-500 could be reused, showing 80.51% of RB5 photodegradation in the fifth cycle. Scavenger study demonstrated that photogenerated hole (h+) was the main active species of 0.50CWT-500 to initiate the RB5 photodegradation and a direct Z-scheme heterojunction was proposed for the n-p-n junction of 0.50CWT-500 heterostructure. Cytotoxicity assessment determined the readings of half-maximal inhibitory concentration (IC50) were 1 ppm and 0.61 ppm (24 and 72 h of incubations) for the 0.50WT composite. The phytotoxicity study proved the safety of the treated RB5 dye solution. Last but not least, the prepared 0.50CWT-500 composite displayed a 92.50% acetaminophen (AMP) photodegradation % towards 1 ppm of AMP under 60 min of solar irradiation
Adaptability of online teaching during the COVID-19 pandemic among teachers in Qianling township rural primary schools / Sun Shuangshuang
No full textWith the pandemic of the COVID-19, online teaching has temporarily replaced traditional face-to-face teaching as an important teaching method. However, it exists many issues when implementing online teaching in rural areas. It is the first time that online courses has been wide-ranging implemented in rural districts, and it remains to be seen whether primary schools teachers can adapt to online teaching. Therefore, this research aims to understand the teachers’ adaptation of online courses during the COVID-19 pandemic in primary schools focusing in rural district. The research method is a quantitative data analysis through online questionnaire surveys. It will use descriptive analysis to analyze the adaptation of teachers to online teaching. This study will choose one-way ANOVA to analyze the effects of different teaching ages or degree levels on the teachers' adaptability to online teaching. Also it will use correlation analysis to analyze the correlation between the TPACK Adaptation. This study chose 113 primary schools teachers at Qianling Township as the sample by random sampling. This study shows that during the COVID-19 pandemic, the teachers of Qianling Township primary schools were qualified to adapt to online courses and were at a moderate level. And teaching age and degree level show no effect on the teachers' adaptability to online teaching. Meanwhile, it has a positive correlation between the four dimensions of TPACK Adaptation, and each dimension influences each other. Through the findings, this research found that primary schools teachers' adaptability on online courses is useful for teachers who may in a special situation similar to the COVID-19 pandemic to improve online teaching adaptability and institutes to optimize online teaching platform. This study gives the recommendation the future researcher to expand the sample size to other rural primary schools teachers in China, add qualitative data and use the experiments in the study on different educational groups