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Commuting additive maps and some related maps on triangular matrices / Tan Li Yin
No full textLet F be a ring with identity and let n ⩾ 2 be an integer. Denote by Tn(F) the ring of n_n
upper triangular matrices over F with centre Z(Tn(F)) and unity In. Let 1 ⩽ i ⩽ j ⩽ n
be integers and let Eij 2 Tn(F) denote the standard matrix unit whose (i, j)th entry is one
and zero elsewhere. In this thesis, the following results have been obtained:
Let 1 < k ⩽ n be an integer and let F be a field. We characterise commuting additive maps
ψ : Tn(F) ! Tn(F) on rank k matrices, i.e., additive maps ψ satisfying ψ(A)A = Aψ(A)
for all rank k matrices A 2 Tn(F) and show that
• when either k < n or jFj ⩾ 3, there exist λ, α 2 F and an additive map μ : Tn(F) !
F such that
ψ(A) = λA + μ(A)In + α(a11 + ann)E1n
for all A = (aij) 2 Tn(F), where α 6= 0 only if k = n and jFj = 3,
• when k = n ⩾ 4 and jFj = 2, there exist λ, α, β1, β2 2 F, H,K 2 Tn(F) and
X1, . . . ,Xn 2 Tn(F) satisfying X1 + _ _ _ + Xn = 0 such that
ψ(A) = λA + tr (HtA)In + tr (KtA)E1n + Ψα,β1,β2(A) +
Σn
i=1
aiiXi
for all A = (aij) 2 Tn(F), where tr (A) and At are the trace and the transpose of A
respectively, and Ψα,β1,β2 : Tn(F) ! Tn(F) is the additive map defined by
Ψα,β1,β2(A) = (αa12 + β1(an−1,n + ann))E1,n−1 + (αan−1,n + β2(a11 + a12))E2n
for all A = (aij) 2 Tn(F),
iii
• when k = n = 3 and jFj = 2, there exist λ, α, β, γ 2 F, H,K 2 T3(F) and
X1,X2,X3 2 T3(F) satisfying X1 + X2 + X3 = 0 such that
ψ(A) = λA + tr (HtA)I3 + tr (KtA)E13 + Ψα,β(A) + Φγ(A) +
Σ3
i=1
aiiXi
for all A = (aij) 2 T3(F), where Ψα,β : T3(F) ! T3(F) and Φγ : T3(F) ! T3(F)
are the additive maps defined by
Ψα,β(A) = α(a23 + a33)E12 + β(a11 + a12)E23,
Φγ(A) = γ((a12 + a22)E22 + (a11 + a12 + a23 + a33)E33 + a13(E12 + E23))
for all A = (aij) 2 T3(F), and
• when k = n = 2 and jFj = 2, there exist λ1, λ2 2 F and X1,X2 2 T2(F) such that
ψ(A) = (a11 + a12)X1 + (a22 + a12)X2 + λ1a12I2 + λ2a12E12
for all A = (aij) 2 T2(F).
Let F be a division ring. We classify centralizing additive maps ψ : Tn(F) ! Tn(F) on rank one matrices, i.e., additive maps ψ satisfying ψ(A)
Synthesis of palm oil-derived biocompatible polymeric surfactants for natural rubber latex application / Yvonne Ling Tze Qzian
No full textSurfactant is important for NR latex applications. It serves as latex preservative to preserve latex and promote good NR film formation. However, some surfactants are toxic and skin irritant. Hence, this study aims to develop alternative green, specifically bio-based surfactant from palm oil for natural rubber latex applications. The objectives of this study are to (i) synthesize a series of biocompatible palm oil-derived polymeric surfactants and characterize the physicochemical properties of the surfactants, (ii) evaluate the in vitro cytotoxic and antimicrobial properties of surfactants, (iii) compound surfactants into natural rubber (NR) latex and investigate the rheological properties of the latex, and (iv) study the mechanical properties of NR latex films incorporated with the synthesized palm oil-derived polymeric surfactants. Four palm oil-derived polymeric surfactants, namely palmitic acid anionic surfactant (PAS), stearic acid anionic surfactant (SAS), oleic acid anionic surfactant (OAS) and oleic acid non-ionic surfactant (ONS), were synthesized using polyesterification method. The chemical structures of the surfactants were then confirmed using FT-IR and 1H-NMR. ONS experienced the highest extent of polyesterification, followed by PAS, SAS and OAS. Consistent with the extent of reaction completion, ONS exhibited the highest Mn and Mw values among all four surfactants. One of the highlights of this project is to develop a polymeric surfactant which is biocompatible for NR latex application. It is therefore crucial to evaluate the cytotoxicity of the developed product. All four surfactants, PAS, SAS, OAS, and ONS were subjected to cytotoxicity study using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays. SDS and Tween 80 were included in the study as controls. The cytotoxicity of these four surfactants were evaluated in terms of cell viability against four cell lines, including human keratinocytes (HaCaT), mouse fibroblasts (3T3), mouse hepatocytes (H2.35) and canine kidney cells (MDCK). Comparative cytotoxicity test revealed that the cell viability of these four surfactants were well above 80 %, except for SAS which exhibited low cytotoxicity on fibroblasts after prolonged exposure at high concentration. Antimicrobial test was conducted on OAS and ONS using minimum bactericidal concentration (MBC) assay against bacterial strains methicillin-sensitive S. aureus (MSSA), methicillin-resistant S. aureus (MRSA), K. pneumoniae, and A. baumannii. Subsequent results revealed that OAS is the most effective surfactant in inhibiting the growth of those tested bacteria. The synthesized OAS and ONS were also compounded into NR latex at five various concentrations and subjected into rheological study. From the study, OAS exhibited better outcome with longer linear viscoelastic region (LVR), signifying its potential usage for long term latex stabilization. Mechanical properties of unaged and aged NR films compounded with OAS and ONS in five varies concentrations were also evaluated. Based on the results obtained, it is suggested that NR films incorporated with OAS could form softer films and exhibited anti-aging properties
Preparation, characterization and application of activated carbon from agricultural solid wastes / Norli Umar
No full textThe purpose of this study was to prepare activated carbon (AC) from palm kernel shells (PKS) and coconut shells (CS) as soot adsorbents. The proximate, ultimate, and lignocellulosic background study was conducted to determine the composition of the starting material. Thermogravimetric analysis (TGA) was used to verify the lignocellulosic content and thermal stability of the biomass. Following this, an optimization study was conducted to produce AC with the desired properties. Fourier Transform Infra-red (FTIR) analysis was conducted as validation of the optimization study. Carbonization was followed by chemical activation (H3PO4, KOH and ZnCl2) and finally microwave radiation treatment. The percentage yield was calculated to determine the efficiency of AC production. The surface area was determined using the Brunauer-Emmett-Teller (BET) method, and the surface acidity and basicity were determined using Boehm titration. Field Emission Scanning Electron Microscope (FESEM) was used to gain insight into the morphology of the AC. Energy Dispersive X – Ray analysis (EDX) was conducted to identify soot presence on the AC surface. The composition analysis reveals that despite the starting materials being from different plant species, both PKS and CS have similar chemical compositions except ash content. In this work, the ash content is found to be 2.16% and 0.24% for PKS and CS, respectively. In addition, PKS primarily comprised of lignin (40.7%) while CS mainly comprised of hemicellulose (38.9%). The optimal carbonization temperature used for preparation of biochar was 650°C and 600°C for PKS and CS, respectively. Each biochar or carbonized biomass was activated at a 1:1 w/w ratio of carbonized biomass and activating agent for 30 minutes at room temperature followed by 4 minutes of microwave radiation. After the optimized method was implemented, CS and PKS activated with ZnCl2 and microwave radiation (MZCS and MZPKS) has the most suitable characteristic to be applied as a soot adsorbent. This is due to the BET surface area collected being the highest at 391.26 m2/g for MZCS and 367.12 m2/g for MZPKS. In addition, the percentage yield of both AC is acceptable and the morphology shown in FESEM images showed the most uniform pores. Through Boehm titration, it was discovered that the MZCS and MZPKS surface was predominantly acidic. After MZCS and MZPKS were exposed to soot emitted from paddy straw burning, MZCS shows the most visible physical adsorption and an even distribution of soot on the surface and within the pores. The MZCS maximum capacity was 30 minutes for approximately 23 g of paddy straw burning using 0.1 g of AC. Economic feasibility studies have been conducted and it has been determined that the laboratory scale price of AC is 4.78 USD / kg
Interpretable deep learning radiomics with synthetic data augmentation for breast cancer diagnosis / Pang Ting
No full textBreast cancer is one of the most frequent cancers among women. The capability of Deep Learning Radiomics (DLR) to extract high-level medical imaging features has promoted the use of Computer-aided Diagnosis (CAD) for breast cancer. However, current DLR for breast cancer diagnosis faces some problems, for instance, (i) limited datasets, (ii) a very simple diagnosis classification (i.e. binary classification) and (iii) incomprehensible deep learning architectures. To address the aforementioned issues, the main objective of this research is to establish an interpretable DLR framework with synthetic data augmentation for a better clinical application of CAD in breast cancer. First, this thesis introduces a data augmentation architecture using the Generative Adversarial Network (GAN) to address the issue of limited datasets. That is, the GAN model is employed to synthesize data in a semi-supervised manner, thereby alleviating the laborious task of manual labelling of medical images. Then secondly, a deep learning network based on a multi-category classifier is proposed to classify breast cancer according to the Breast Imaging Reporting and Data System (BI-RADS). Herein, it employs the Convolutional Neural Network (CNN) with transfer learning using the generated synthetic data to extract visual features as radiomics for multi-category classification. Finally, this thesis presents a novel reporting model with text attention (RRTA-Net) to achieve explainable DLR in breast cancer diagnosis. That is, it maps the visual features extracted from the CNN to the textual features extracted by Recurrent Neural Network (RNN) to generate a diagnostic report. Extensive experiments were conducted on both the breast ultrasound mass and mammographic calcifications, which are the two most important characteristics of breast cancer. First, it shows that introducing a data augmentation model can generate high-quality and interpretable breast ultrasound mass and mammographic calcification. The correct judgement ratio for the generated data was about 80%, provided by experienced radiologists from the Universiti Malaya Medical Center (UMMC). Secondly, the proposed classification model successfully classified each BI-RADS category with above 95% probability by grasping the standardized features for breast ultrasound mass (shape and margin) and mammographic calcification (morphology and distribution). As such, it improves the diagnostic performance compared to hand-crafted radiomics. Besides that, the transfer learning and synthetic data augmentation strategies also improve breast cancer classification performance compared with other state-of-the-art deep learning approaches. Finally, the report generation model with 87.3% average precision has shown the capability to reduce the labors of writing diagnostic reports and semantically promote the interpretability of DLR. Moreover, it also improves the readability of generated breast cancer reports
Kajian kes stres kerjaya dalam kalangan guru Muslim sekolah rendah / Azizah Abdul Majid
No full textMendepani suasana pandemik COVID-19 yang mengancam nyawa dan keselamatan, seluruh komuniti, termasuk jutaan pelajar dan guru di seluruh dunia berlindung di tempat masing-masing, stres menjadi isu yang amat ketara. Situasi ini telah menyebabkan berlakunya stres dan tekanan di semua peringkat. Keadaan ini menjadi semakin meruncing apabila semakin ramai orang yang tertekan dan mengambil jalan mudah dengan membunuh diri akibat depresi atau kemurungan. Stres yang tidak terkawal dan berpanjangan merupakan titik permulaan sebelum seseorang itu mengalami masalah kebimbangan (anxiety) dan depresi. Guru sekolah rendah juga amat terkesan dengan suasana pandemik dan Perintah Kawalan Pergerakan (PKP) ini malahan cabaran dan stres yang dihadapi oleh golongan pendidik ialah sesuatu yang tidak pernah berlaku dalam skala sebesar ini sebelumnya. Kajian terhadap gejala stres guru serta cara menanganinya telah dijalankan sebelum pandemik bermula lagi. Kajian lepas menunjukkan bahawa tanggungjawab dan beban kerja guru yang semakin bertambah menyebabkan guru perlu melakukan pelbagai fungsi dalam satu masa yang menyebabkan stres dalam kalangan guru. Masalah yang dihadapi oleh guru ini seterusnya mengurangkan masa pembelajaran yang berkualiti dengan murid. Bebanan tugas menyebabkan guru semakin tertekan dan mengalami stres dan tekanan emosi, burnout dan ramai juga guru yang memilih untuk bersara awal. Jika perkara ini dibiarkan berterusan tidak mustahil semakin ramai guru akan mengalami stres pada tahap yang kritikal. Oleh hal yang demikian itu, objektif kajian ini adalah untuk menganalisis faktor dan kesan stres kerjaya dalam kalangan guru Muslim sekolah rendah serta kaedah yang digunakan oleh mereka untuk menangani stres yang dihadapi. Dengan menggunakan pendekatan kualitatif, kajian telah memilih reka bentuk kajian kes dan menjalankan temu bual secara mendalam terhadap 6 orang guru yang mengalami stres dengan menggunakan persampelan mudah, persampelan bola salji dan persampelan bertujuan. Kaedah pengekodan NVivo dan teoritikal tematik yang melibatkan beberapa peringkat telah digunakan sebagai kaedah analisis. Dapatan kajian ini mendapati bahawa kesemua informan mempunyai tahap stres yang tinggi dan terdapat enam faktor penyebab stres mereka. Enam faktor tersebut ialah masalah komunikasi interpersonal, struktur dan iklim organisasi, komitmen yang pelbagai, kepuasan, penghargaan, sokongan dan pembelaan, masalah kesihatan dan perubahan peranan guru disebabkan perubahan mod pembelajaran semasa pandemik Covid19. Kesan stres yang dialami oleh setiap informan pula adalah berbeza-beza mengikut ketahanan diri dan mekanisme menangani yang diamalkan oleh setiap informan. Di samping itu, kajian ini telah mencadangkan satu model stres kerjaya menurut perspektif Islam untuk guru secara khusus dan umat Islam secara amnya. Hasil kajian ini diharapkan dapat menemukan kaedah terbaik bagi mengatasi stres guru, meningkatkan pemahaman tentang tahap stres, sumbernya, dan seterusnya menerapkan strategi mengatasi stres dan tindakan yang harus diambil oleh pihak berkaitan untuk mengurangkan stres dalam kalangan guru terutamanya guru Muslim di sekolah rendah
Aliran kritik hadith terhadap isu-isu dalam Muqaddimah Sahih Muslim: Kajian perbandingan antara Rabiʻ al Madkhali dan Hamzah al-Malyabari / Ibrahim Adham Mohd Rokhibi
No full textWacana kritik hadith semakin rancak dibahaskan dalam kalangan pengkaji semasa pada masa kini melalui kajian terhadap pelbagai kitab dalam bidang hadith. Situasi ini menunjukkan reaksi positif para pengkaji terhadap perkembangan berkaitan ilmu hadith. Antara sarjana yang turut terlibat dalam wacana ini ialah Rabīʻ al-Madkhalī dan Ḥamzah al-Malyabārī yang merupakan di antara tokoh-tokoh Islam yang berpengaruh. Kedua-dua tokoh pernah saling berbahas berkenaan isu-isu yang berlaku dalam Muqaddimah Ṣaḥīḥ Muslim di mana mereka mempunyai manhaj yang berbeza dalam memahami teks Imam Muslim. Perbezaan yang jelas dapat dilihat apabila berlaku pertembungan pemahaman metode Ṣaḥīḥ Muslim antara kedua tokoh termasuk polemik terhadap isu penerimaan hadith ḍaʻīf menurut Imam Muslim. Seterusnya, isu berkaitan keberadaan hadith-hadith berillat dalam sahihnya, isu metode penerangan hadith berillat dan isu perbezaan penetapan status hadith. Lantaran itu, timbul beberapa persoalan yang perlu dikaji antaranya latar belakang pendidikan kedua tokoh, idea penulisan Ṣaḥīḥ Muslim, tujuan hadith berʻillah dimasukkan ke dalam Ṣaḥīḥ Muslim dan aliran kritik hadith kedua tokoh terhadap isu-isu dalam muqaddimah Ṣaḥīḥ Muslim. Persoalan-persoalan ini telah melahirkan empat objektif yang memandu kajian ini. [Pertama] menjelaskan aliran kritik hadith semasa dan idea penulisan Ṣaḥīḥ Muslim. [Kedua] menghuraikan latar belakang kehidupan Rabīʻ al-Madkhalī dan aliran pemikirannya dalam wacana hadith. [Ketiga] mendedahkan latar belakang kehidupan Ḥamzah al-Malyabārī dan aliran pemikirannya dalam wacana hadith. [Keempat] menganalisis aliran kritik hadith Rabīʻ al-Madkhalī dan Ḥamzah al-Malyabārī terhadap isu-isu dalam muqaddimah Ṣaḥīḥ Muslim. Bagi menyelesaikan objektif tersebut, kajian dilakukan berasaskan kajian kepustakaan (library research) bagi membincangkan isu-isu yang menjadi polemik dan perbincangan antara kedua-dua tokoh tersebut. Kemudian, keseluruhan data tersebut dianalisis menggunakan metode induktif, deduktif, analisis kandungan dan komparatif. Hasil kajian mendapati bahawa kedua-dua tokoh mempunyai kepakaran dalam perbahasan manāhij muḥaddithīn dan ʻilal. Namun, terdapat perbezaan pendekatan metodologi kritik hadith antara kedua-dua tokoh iaitu pemahaman terhadap konsep ʻillah, penerimaan hadith daʻif di sisi Imam Muslim, keberadaan ʻillah serta metode penerangan ʻillah dalam Ṣaḥīḥ Muslim dan penetapan status hadith. Berdasarkan kepada perbezaan tersebut, kajian mendapati bahawa setiap tokoh mempunyai hujah dalam melakukan kritikan terhadap hadith-hadith dalam Ṣaḥīḥ Muslim. Dalam hal ini, kajian merumuskan bahawa pendekatan Rabīʻ al-Madkhalī sesuai digunakan untuk pemula dalam bidang hadith, manakala pendekatan Ḥamzah al-Malyabārī pula lebih sesuai diterapkan dalam kalangan pengkaji semasa atau ahli akademik
Konsep logik Muhammad bin Yusuf al-Sanusi: Kajian terhadap Mukhtasar fi ‘Ilm al-Mantiq /Nurfarzana Nizam
No full textLogic which is also known as “ilmu mantik” in Islamic tradition of knowledge is an intellect rule of thinking. Muḥammad bin Yūsuf al-Sanūsī (m.895H), an Ashāʻirah theological figure has used argumentation via naqlī and ‘aqlī as the source of evidence in the study of 20 attributes of Allah (Sifat 20). Thus, the burhān argumentation in Islamic creed is the proof of al-Sanūsī’s mastery in science of logic. Therefore, this study was conducted to analyse the logic work by al-Sanūsī, which is Mukhtaṣar fi ʻIlm al-Manṭiq. This study has focused on Mukhtaṣar because this work has the potential in the tradition of Islamic logical thinking and this study has started with going through al-Sanūsī’s background and his contributions in knowledge, especially in logical thinking. As for the data collection, it has been done using documentation methods and analysed through textual content analysis and historical methods based on the qualitative research design. As the result, this study has identified five main theories, which are the reference theory (al-dalālah), the utterance theory (al-lafẓ), the definitions theory (al-taʻrīfāt), the proposition theory (qaḍāyā) and the syllogism theory (al-qiyās). These theories which had formed al-Sanūsī logical concept is analysed based on the basic epistemology contemporary Islamic logical thinking that encompassed the inclusion of the subject (al-maddah) and format (al-ṣūrah). Finally, this study has discussed about the aspect of application and concept practicality according to al-Sanūsī’s logic with a few prospects and the challenges towards contemporary Islamic logical thinking. Lastly, this study also found that it is crucial to update the structure and the content of Mukhtaṣar to fulfil the need of contemporary Islamic logical thinking in facing the false thoughts. Meanwhile for the enrichment of terminological science of logic, this study has listed the al-Sanūsī logical terms in Mukhtaṣar fi ʻIlm al-Manṭiq
Pembangunan model perlindungan hak-hak warga emas dari pengabaian menurut perundangan Islam di Malaysia / Hasiah Mat Salleh
No full textSituasi pengurangan kadar kelahiran dan peningkatan tahap kesihatan penduduk merupakan
antara faktor utama yang menjadikan Malaysia bakal menuju ke arah sebuah negara menua
menjelang tahun 2035. Walau bagaimanapun, pelbagai isu berkaitan pengabaian dan penderaan warga emas kerap dihebahkan di media massa dan media cetak. Bagi mengatasi cabaran ini, kajian ini dijalankan untuk membina Model Perlindungan Hak-Hak Warga Emas dari Pengabaian Menurut Perundangan Islam di Malaysia (Model ERIsP). Pendekatan kajian reka bentuk dan pembangunan diterapkan dalam kajian ini. Berdasarkan pendekatan yang digunakan,
kajian ini dikelaskan kepada tiga [3] fasa utama. Fasa pertama kajian ini merupakan analisis
keperluan dengan melaksanakan pendekatan kajian literatur bersistematik dan sesi temu bual
bersama warga emas yang dipilih. Keperluan pembinaan model ini dianalisis dengan
menggunakan teknik analisis kandungan terhadap data kajian literatur dan teknik tematik
terhadap data dan transkrip temu bual. Fasa seterusnya menggunakan Kaedah Fuzzy Delphi
(FDM) bagi membina komponen dan elemen model menurut persepsi dan keputusan pakar.
Fasa ketiga iaitu fasa terakhir kajian ialah penilaian kebolehgunaan model berasaskan temu bual
bersama pakar. Penilaian ini dianalisis menggunakan Teknik Kumpulan Nominal (NGT). Hasil
kajian yang diperoleh membuktikan bahawa Model ERIsP amat penting kepada golongan ini.
Lima [5] komponen utama dan elemen-elemen komponen utama juga dipersetujui oleh kesemua
pakar dalam kajian ini bagi memberikan perlindungan yang baik kepada warga emas.
Pembangunan Model ERIsP juga dilihat amat signifikan untuk dijadikan sebagai panduan
dalam memelihara hak-hak warga emas bagi mengatasi isu pengabaian golongan ini
Progressive kernel extreme learning machine for food image analysis via optimal features / Ghalib Ahmed Tahir
No full textFood recognition systems recently garnered much research attention in the relevant field due
to their ability to obtain objective measurements for dietary intake. The goal is to improve
food diaries by addressing challenges faced by existing methodologies. In addition to the
classical challenge of the absence of rigid food structure and intra-class variations, food
diaries employing deep networks trained with pristine samples are susceptible to quality
variations during image acquisition and transmission. Similarly, most deep learning models
and other hybrid frameworks using visual features from the convolutional neural network
(CNN) do not progressively learn new food categories and their ingredients. Finally, many
existing frameworks integrated with dietary assessment apps are non-comprehensive, as
they can not recognize food ingredients or filter non-food images from the users. This
thesis tackled these challenges, aiming to provide food image analysis frameworks that use
computational resources on edge devices (offline accessibility) and cloud servers (online
accessibility). A framework with offline accessibility performs food image analysis on
edge devices by employing efficient neural networks and a novel online data augmentation
strategy random iterative mixup (RIMixUp). RIMixUp generates synthetic images during
fine-tuning to train ensembles models, resilient to various quality distortions in test images.
Then to increase the trust of the involved parties, this thesis proposed a user-centered
explainable artificial intelligence (AI) framework by inferencing and rationalizing the
results according to needs and user profile. The framework with online accessibility
extracts and selects the optimal subset of quality resilient features from CNNs and
subsequently incorporates the parallel type of classification. The first progressive classifier recognizes food categories, and its multilabel extension detects food ingredients. Following
this idea, after extracting quality resilient features from category CNN and ingredient
CNN model by fine-tuning it on synthetic images generated using the novel online data
augmentation method random iterative mixup, the feature selection strategy uses SHAP
scores from gradient explainer to select the reliable features. Then novel progressive
kernel extreme learning machine (PKELM) is exploited to tackle domain variations due
to quality distortions, intra-class variations, etc., by remodeling the network structure
based on activity value with the nodes. PKELM extension for multilabel classification
detects ingredients by employing bipolar step function to process test output and then
selecting the column labels of the resulting matrix with value one. Moreover, during online
learning, PKELM is equipped with a mechanism to label unlabeled instances and detect
noisy samples. Experimental results showed superior performance of the frameworks
on an integrated set of measures over other methodologies on publically available food
datasets and a newly introduced dataset of Malaysian foods
A rooting detection system and risk assessment for android mobile devices / Wael Farouk Mohamed Elsersy
No full textWith the proliferation of mobile banking and e-commerce applications with online payment capability, it has become a lucrative target for attackers to make revenue by gaining root access to mobile devices. For Android devices, root access is accessible via a special application such as the rooting application which are publicly downloadable from third-party stores and websites. There are many solutions proposed by previous studies, such as rule-based detection and machine learning to overcome the security problem and the installation from the third-party store. Rules-based simply checks the ability to execute Android superuser command and the presence of root applications. At the same time, machine learning builds a root detection model by training and testing a set of rooting applications, aims to identify similar characteristics and features. However, the detection accuracy of such approaches is less effective and ignores the device risk assessment. Meanwhile, the lack of risk assessment affects the support for deciding the security and threat level of the device. Therefore, this thesis work aims to propose an assessment framework for the Android devices, named AndRoRAS, and it works to detect and evaluate the rooting level of an Android device. The assessment framework contains two modules: a) rooting detection (Rootector) and b) risk assessment (ARAS). The rooting detection module introduced a data crawler (RootCrawler) that extracts static analysis group features. The second module, the risk assessment model, adopts a risk scoring system to determine the risk level of Android devices based on three risk criteria. To demonstrate the assessment framework, this thesis work undertakes four evaluation phases: a) the testing of the detection performance using thirteen thousand physical and virtual Android devices, b) investigating the impact of different feature extraction techniques, c) cross-validation with varying techniques of sampling, and d) benchmarking with the results of previous root detection studies outcomes. In contrast, this thesis work demonstrates the risk levels assessment by applying the proposed scoring model to the rooted devices dataset. The results show that the rooting detection module improves the root detection accuracy to 98 % total accuracy compared to moderate 90% in other previous studies. In addition, the risk assessment module introduced four risk levels: low, medium, and high risk levels