13474 research outputs found
Sort by
Deep learning-based breast cancer detection and classification using histopathology images / Ghulam Murtaza
No full textCancer disease is drastically increasing worldwide over the past few years. Among all types of cancers in women, breast cancer (BrC) is the main cause of abnormal deaths. For a confident diagnosis of BrC, histopathology (Hp) images are usually suggested by the doctors. BrC detection is a diagnostic test for benign (non-cancerous) and malignant (cancerous) breast tumors (BrT). Once the BrT is diagnosed, then it needs to be classified for subtypes of benign and malignant to start specific treatment. Several studies developed BrC detection and classification models using Hp images. However, the existing models required high computational resources, long training time, and their performance is compromised due to a higher misclassification rate. Thus, this research is aimed to develop two models. First, the BrC detection model is developed to diagnose BrT basic types like benign and malignant. Second, the BrT classification model is developed to diagnose subtypes of benign and malignant tumors. To perform overall experiments, Hp images of the BreakHis dataset are utilized. BreakHis is a large and complex dataset (i.e., four subtypes of each benign and malignant BrTs) that publicly available. For BrC detection, an efficient and reliable model namely Ensemble BrC Detection Network (EBrC-Net) and three misclassification reduction (McR) algorithms are developed. The proposed EBrC-Net model is based on deep learning (DL) based approach. EBrC-Net architecture is designed to require less training time and computational resources like a normal desktop computer. The trained EBrC-Net is used to extract discriminative features. The extracted features are evaluated through six machine learning (ML) classifiers namely softmax, k-nearest neighbor (kNN), support vector machine, linear discriminant analysis, decision tree, and naive Bayes. Experimentally, it has been observed that kNN outperformed the rest of the five ML classifiers. Furthermore, three McR algorithms are developed and implemented in a cascaded manner to reduce the false predictions (i.e., misclassification) of the aforementioned six ML classifiers. The proposed BrC detection model for five folds of features achieved mean accuracy, sensitivity, and patient recognition rate by 97.78%, 97.28%, and 97.92% respectively. On the other hand, BrT classification is aimed to develop an efficient and reliable model namely Biopsy Microscopic Image Cancer Network (BMIC-Net) to classify Hp images into eight subtypes of BrT through a DL-based hierarchical classification approach. BMIC-Net model can be trained using less computational resources in less time. The trained BMIC-Net is used to extract discriminative features from Hp images. To reduce the misclassification, a feature selection algorithm (using information gain and principal component analysis schemes) is developed to elicit the most discriminative feature subset. Finally, the aforementioned six ML classifiers are analyzed to acquire the best performing classifier. The experimental results revealed that BMIC-Net outperformed for five folds of features by obtaining a mean accuracy of 95.33% for first-level hierarchical classifier and 94.70%, 92.53% for second-level hierarchical classifiers. Moreover, the performances of both BrC detection and BrT classification are compared with existing state-of-art baseline studies. Findings discovered that the proposed models are efficient (i.e., consume less computational resources and training time) and reliable (i.e., reduce misclassification to show better and unbiased results even using a complex dataset) in comparison with the existing SoA baseline studies. Thus, the proposed BrC detection and classification models can assist doctors to serve on the basis of the second opinion for early diagnosis of BrC
Scholarly communication in open science: A study of cognitive, conative and affective readiness of researchers in Malaysia / Wusu, Oluwaseyi Hodonu
No full textThe study aims to investigate the readiness of Malaysian academic researchers’ open scholarly communication focusing on the three most important pillars of Open Science i.e., Open Access, Open Data and Open Peer Review. The study answered the extent of Malaysian academic researchers’ cognitive, conative, and affective readiness as regards to Open Access, Open Data and Open Peer Review, as well as finding out significant differences between gender, types of researchers, and research discipline. A survey instrument of 75 questions about open scholarly communication was sent to academic researchers in five research universities in Malaysia between February and August 2018. A total of 135 responses from the questionnaire were analyzed via simple percentage. The sample size was determined as 370 (confidence level=95%, margin of error=2.5%) however, oversampling was carried out to be 400 from a population of 9,299. A total of 135 were returned for a response rate of 33.75%. The results showed the researchers’ cognitive, conative, and affective readiness of Open Access, Open Data and Open Peer Review. From the study, it was revealed Malaysian researchers are generally aware of Open Access; but have low levels of awareness of Open Data and Open Peer Review. Practices of open scholarly communication are still low as reflected in the mean scores, especially on open data sharing and open peer reviewing, probably because they do not want to be associated with bad comments syndrome in science, as well as the fear of losing publication rights. Lack of incentives and misuse of data are part of disincentives for data sharing. It is widely believed that Open Peer Review will ensure transparent, provide honest feedback, increased motivation and improve science, but the issue of timing in reviewing and fear of negative comments are concerns to many respondents. The study concludes in terms of readiness that Malaysian academic scholars are somewhat ready and grouped as strollers, they are moving ahead with the trend of open scholarly communication. Future studies should investigate the importance or rewards for openness, especially in data sharing among scholars’ institutions, and studies bridging the gap between policy and practices of open science should be examined
Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq
No full textDifferent teaching approaches for programming are widespread but what is essential for students is being able to computationally formulate an algorithmic solution at first and then transfer to code. A number of factors such as inefficient teaching approaches and lack of problem-solving skills are factors making this knowledge procedure difficult. This study aims to investigate teaching issues in solving programming problems and find the right approach to teach programming using a suitable problem solving approach method. Sorting algorithm as a concept for solving problems have been utilized to understand the effectiveness of the model in different teaching methods. After carrying out a thorough literature review on core concepts of the study, a pilot study was conducted, and it identified some difficulties faced in teaching programming and motivated the search for an approach to overcome the issues and design the workshops for the feasibility study. A problem-solving approach (PSA) model was formulated using computational thinking concepts based on the sorting problems. An experimental study was designed to evaluate the PSA model. The syntax-based programming workshop was the control group. The problem-based and the game-based programming workshops utilizing our problem-solving model using sorting algorithms were the experimental groups.
A one-way ANOVA test indicated that the mean score for syntax-based workshop post test scores (M=6.99, SD=1.92) was significantly different than the post test scores of activity-based workshop (M=8.05, SD=1.96) and the post test scores of game-based workshop (M=8.62, SD=1.90). However, the post test scores of activity-based workshop (M=8.05, SD=1.96) did not significantly differ from the post test scores of game-based workshop (M=8.62, SD=1.90). The results suggested that students had improved their programming skills in all the workshops. However, participants had better acquisition of problem-solving skills and a better understanding of programming concepts with both the active learning skills compared to the syntax-based approach. Even though there was no significant difference between the scores of the active learning methods, a comparison between both the approaches from a teaching perspective suggested that game-based learning was more suitable due to its interactivity
A lightweight host-based intrusion detection system using N-gram and perceptron model for internet of things / Belal Sudqi Abed Saleh Khater
No full textA Host-Based Intrusion Detection System (HIDS) is a system that monitors and analyses internal or external data to detect intrusion. It is installed in a host capable of monitoring users’ activities, which is not possible in a network-based system. In this thesis, a HIDS using Modified Vector Space Representation (MVSR) N-gram and Multilayer Perceptron (MLP) model for securing Internet of Things (IoT) devices were proposed. The HIDS utilizes fog computing paradigm to address the inherent challenges of the cloud such as latency, lack of mobility support and location-awareness. Since the fog and IoT devices are resource constraint, a lightweight HIDS is highly desirable. Therefore, detailed analysis and evaluation were conducted to fulfil the lightweight criteria. The Australian Defence Force Academy Linux Dataset (ADFA-LD), which is a new generation system that calls datasets containing exploits and attacks on various applications, was employed for the analysis. The proposed method was divided into feature extraction stage, feature selection stage and classification modelling. To maintain the lightweight criteria, feature extraction stage considered a combination of 1-gram and 2-gram for the system call encoding. In addition, Sparse Matrix was used to reduce the space by keeping only the weight of the feature that appeared in the trace, thus ignoring the zero weights. Subsequently, Linear Correlation Coefficient (LCC) was utilized to compensate any missing N-gram in the test data. In the feature selection stage, Mutual Information (MI) method and Principle Component Analysis (PCA) were utilized and then compared to reduce the number of input features. Following the feature selection stage, the modelling and performance evaluation of various Machine Learning classifiers were conducted by using a Raspberry Pi IoT device. Further analysis on the effect of MLP parameters such as number of nodes, number of features, activation, solver, regularization parameters were also conducted. From the simulation, it could be seen that, different parameters affect the accuracy and lightweight evaluation. By using a single hidden layer and four nodes, the proposed method with MI could achieve 96% accuracy, 97% recall, 96% F1-Measure, 5% False Positive Rate (FPR), highest curve of Receiver Operating Characteristic (ROC) and 96% Area Under the Curve (AUC). It also achieved low CPU time usage of 4.43 [ms] millisecond and low energy consumption of 8.87 [mJ] millijoule
Measuring aircraft altimetry system error using automatic dependent surveillance-broadcast data / Kalyani Bahskaran
No full textThe International Civil Aviation Organization (ICAO) introduced Reduced Vertical
Separation Minima (RVSM) globally to support increasing traffic volumes on congested
airspace. RVSM focused on reducing vertical separation minimum from 2000 feet to 1000
feet between flight level FL290 and FL410. Implementation of RVSM stresses the accuracy
of aircraft avionics that report altitude and requires the Regional Monitoring Agency (RMA)
to monitor the aircraft's Height Keeping Performance (HKP) to ensure the aviation safety of
their airspace. Presently, air traffic and navigation are controlled by an air traffic controller
on the ground based on the pressure altitude value, also known as a flight level (FL) measured
with barometric altimeter. The pressure altitude was subjected to errors due to various factors
including instrument defect, obstructed airflow, presence of foreign materials into the system,
variations of temperature and humidity. Altimetry System Error (ASE) is the difference
between the actual altitude based on SI units and the pressure altitude displayed. ASE
possesses risk to the aviation industry as it is an invisible to the pilots during the flight.
According to ICAO, ASE value must be less than 245 feet to ensure the safety of the aircraft.
Currently, some of the airspace operators that implement RVSM in their airspace installs
Height Monitoring Unit (HMU) on the ground to monitor the aircraft HKP in their airspace.
However, HMU methods are disposed to drawbacks. It requires high implementation and
maintenance costs, low scalability, and the requirement to have professionals on board to
operate the equipment. Alternatively, this research aims to measure the ASE using geometric height data derived from Automatic Dependent Surveillance-Broadcast (ADS-B) message,
which is transmitted to the Air Traffic Control (ATC) in the ground. Aircrafts in different
regions has been instructed to be equipped with transponders by their authorities. Hence, the
ready availability of ADS-B data can be utilized to study the HKP of the aircrafts. This
research identifies a process to measure the ASE values using ADS-B data. Subsequently, a
computer algorithm and interfacing tool is developed. The tool enables any personal with
basic computer literacy and access to the tool and data file to process the data and asses the
HKP of the flight at ease. The algorithm reads inputs of the ADS-B data file, stores all the
required fields for processing either all or a single flight, and finally the ASE will be
calculated. ASE value is calculated by subtracting Flight Level from the Orthometric Height
of the aircraft. Orthometric height is calculated using the Geoid Height derived using the
EGM96 Geopotential Model. A scatter graph is outputted displaying the FL, Datetime, and
ASE values to visualize the ASE pattern and compliance throughout the flight duration. The
algorithms’ accuracy is evaluated against the method adopted by China RMA comparing the
Mean ASE values returned 98.84% accuracy using the same dataset. Further studies require
incorporating the algorithm into the real-time Air Traffic Controller System and can be
further improved with the Big Data Analytics approach in the future when it comes to
processing more volume and variety of data
Modified guar gum-based hydrogels: Synthesis, characterisations and swelling behaviour / Mazrina Mazlan
No full textThe growing concern for synthetic materials that are primarily derived from petroleum and coal as raw materials for the manufacture of hydrogel has opened a field of research focused on nature-based products. Massive efforts are being taken on biopolymer-based hydrogels due to their abundance, renewability, biodegradability and biocompatibility. Modification of biopolymer by grafting as alternative hydrogels is a promising strategy for imparting beneficial properties on them. Guar gum has solubility in water, possesses uncontrolled and enormous swelling that restricts its potential to be used in diverse applications. Thus, in this study, native guar gum (Native GG) was modified into guar gum acetate (GGA) and phthaloyl guar gum (PHGG) by transesterification and phthaloylation, respectively. These two modified guar gums have better solubility in organic solvents such as dimethylsulfoxide and dimethylformamide. The success of these modifications was confirmed through Fourier-transform infrared spectroscopy with new characteristic peaks at 1733 cm-1 for GGA and 1709 cm-1 for PHGG. The degree of substitution of GGA was 5.65 meanwhile PHGG was 1.04 as determined from proton nuclear magnetic resonance spectroscopy. X-ray diffractometry results revealed that both GGA and PHGG are less crystalline compared to Native GG. GGA was found to be thermally more stable than Native GG while PHGG was slightly less thermally stable in comparison with Native GG. The swelling behaviour revealed that Native GG had the highest swelling equilibrium with 918.4 ± 46.6%, followed by PHGG with 537.0 ± 2.9% and GGA with 393.0 ± 13.4% in distilled water. These hydrogels (Native GG, GGA and PHGG) were found to be stimuli sensitive towards pH and ionic salt solution. The samples responded to simulated normal saline isotonic solution, showing lower swelling compared to swelling in distilled water. For simulated gastric fluid (SGF) medium, GGA showed higher swelling while Native GG and PHGG showed higher swelling in simulated intestinal fluid (SIF) medium. Therefore, these guar gum hydrogels have potential to be used in biomedical fields such as tissue engineering and drug-delivery
Keberkesanan modul pendidikan kesihatan reproduktif dan sosial menerusi drama kreatif (PEERS-DK) terhadap pengetahuan dan kemahiran preventif pencabulan seksual dalam kalangan kanak-kanak prasekolah / Haneem Said
No full textPencabulan seksual terhadap kanak-kanak merupakan jenayah berat yang kian berleluasa di Malaysia. Isu yang semakin tular di media sosial dan mencetuskan kegusaran banyak pihak ini mampu ditangani sekiranya kanak-kanak diperkasa dengan pengetahuan dan kemahiran preventif pencabulan seksual. Justeru, menerusi kajian ini, sebuah modul keselamatan seksualiti berasaskan Drama Kreatif yang dinamakan sebagai Modul PEERS-DK telah dibina khusus untuk kanak-kanak prasekolah berusia lima dan enam tahun. Pengumpulan data dilaksanakan menerusi beberapa kaedah mengikut tiga fasa kajian yang berbeza. 72 kanak-kanak prasekolah yang dilibatkan dalam kajian ini dibahagikan kepada kumpulan eksperimen dan kumpulan kawalan di mana kumpulan eksperimen telah menjalani sesi pengajaran dan pembelajaran Pendidikan Kesihatan Reprodukif dan Sosial (PEERS) menerusi Modul PEERS-DK manakala kumpulan kawalan tidak menerima rawatan terbabit. Ujian pra, ujian pasca dan ujian pasca lanjutan ditadbir untuk ke dua-dua kumpulan. Hasil kajian fasa pertama menerusi temu bual terhadap 17 guru prasekolah mendapati bahawa terdapat beberapa kekangan yang dihadapi oleh guru-guru prasekolah dalam pengajaran dan pembelajaran PEERS iaitu topik mencabar, guru malu, guru bimbang, kanak-kanak malu dan tingkah laku disruptif kanak-kanak. Selain itu, dapatan kajian juga mendedahkan bahawa kaedah pengajaran yang menarik, menyeronokkan dan aktiviti yang disukai kanak-kanak prasekolah merupakan faktor-faktor penting yang perlu dititikberatkan bagi merangsang fokus dan mengekalkan daya tumpu mereka dalam pengajaran dan pembelajaran PEERS. Di samping itu, dapatan kajian turut mencungkil cadangan-cadangan daripada para guru di mana mereka menyarankan penggunaan dramatisasi cerita, pantomim, boneka dan lakonan cerita sebagai strategi pengajaran dan pembelajaran PEERS yang efektif untuk kanak-kanak prasekolah. Dapatan kajian fasa ke dua yang diperoleh berdasarkan penilaian pakar mendedahkan bahawa semua aktiviti mencecah lebih 70% aras kesahan kandungan. Sementara itu, nilai α keempat-empat sesi dengan 16 aktiviti berada antara julat 0.64 hingga 0.92. Analisis U Mann-Whitney yang ditadbir pada fasa ke tiga kajian membuktikan bahawa min skor ujian pasca bagi pencapaian pengetahuan pencabulan seksual kumpulan eksperimen adalah lebih tinggi secara signifikan dan statistik berbanding kumpulan kawalan dengan nilai U= 20.50
In-situ electrochemical generation of superoxide ion for the conversion of CO2 and chlorinated compounds in ionic liquid and nanohybrid-ionic liquid media / Ahmed Halilu
No full textPollution remediation is one of the 21st-century global environmental concerns that need to be sustainable. As such, the conversion of pollutants such as CO2 or chlorinated organics to useful products is a judicious strategy to achieve sustainability of their remediation processes as it provides an opportunity to generate economic profit. Conversion of pollutants can be achieved using superoxide ions (O2●−) as demonstrated in this research in the case of CO2 and selected chlorinated organics. The conversion of pollutants using O2●− relies heavily on media with low nucleophilic susceptibility. This study successfully generated stable O2●− at –±1.0 V vs Ag/AgCl in ammonium [Amm+], pyrrolidinium [Pyrr+], piperidinium [Pip+] and morpholinium [Mor+] based ILs that satisfy the low nucleophilic criterion. The study further pioneered the development of IL-nanofluid media using fully characterized novel pseudocapacitive Fe/Ru-SiMWCNT nanohybrid. The nanofluid has low nucleophilic susceptibility and suitable as media for stable O2●− generation at – 0.445 V vs Ag/AgCl. Moreover, the interfacial and mass transfer parameters therein were determined using cyclic voltammetry (CV), chronoamperometry (CA) and electrochemical impedance spectroscopy (EIS) analysis. Long-term stability of the O2●− was determined in ILs and the nanofluid media using UV/Vis spectrometry. The kinetic parameter indicated that O2●− stays longer in some ILs; [MOEMPyrr+][PFTP−] (3.82 % decay, 0.34×10−5 s−1), [MOEMMor+][TFSI−] (4.81 % decay, 1.71×10−5 s−1), [BTMAmm+][TFSI−] (8.38 % decay, 0.82×10−5 s−1). Second, O2●− decayed by only 2.24 % in Fe/Ru-SiMWCNT-[MOEMPyrr+][PFTP−] nanofluid with a rate constant of 0.423×10−5 s−1 after at least 1 day. These long-term stability results validated the media for at least 60 min in-situ O2●− mediated electrolysis. The CV technique was used in the second part of the analysis to investigate selective CO2 conversion to peroxy-dicarbonate anion (C2O62–) by O2●− at – 0.54 V vs Ag/AgCl. The C2O62– was identified by O-O (proxy-bridge) symmetric stretching harmonic at 853 cm-1 using DFT-IR and ATR-IR spectroscopy. The energy efficiency of C2O62– production in the nanofluid was 97.6 %, higher than that in [MOEMPyrr+][PFTP−] (50 %). This study postulated that the pseudocapacitance of Fe3O4 and RuO2 phase of the nanofluid implicated a low overpotential required for CO2 conversion by O2●− unlike ordinary ILs. Moreover, the CO2 conversion mechanism followed direct nucleophilic addition of O2●− to CO2 since the charge transfer resistance of the CO2 saturated media is extremely high (6.86×1018 kΩ). In the third part of the study, in-situ C2O62– further carboxylated diethanolamine to produce methyl (2-hydroxyethyl) (methyl) carbamate. In the fourth part of this research, dechlorination of CH2Cl2 and C6H5Cl by O2●− was investigated in [BMPip+][TFSI−]. The dechlorination process produced non-dioxin product distribution, achieving 100 % dechlorination after 2 h of electrolysis. In all these accomplishments, quantum chemical calculations were conducted to support the results. The final part of the research entailed analysis of product distribution from the electrolysis of either CO2 or CH2Cl2 and C6H5Cl using GCMS, 1D (1H and 13C), 2D (COSY, HSQC and HMBC) nuclear magnetic resonance analysis. Overall, this research contributed by conceptualizing the development of stable nanofluid media for reactive oxygen species, energy storage and conversion applications
The influence of conventional and Islamic microfinance on Bangladeshi women empowerment / Sajeda Pervin
No full textMicrofinance has favourable outcomes in socio economic perspectives in terms of poverty alleviation, women empowerment, employment, entrepreneurship, financial innovation and financial inclusion. However, there is no consensus on the role of microfinance on women empowerment. Whether microfinance is good or bad for women empowerment is an ongoing academic and policymaking debate. On the other hand, as an alternative microfinance model, empirical evidence on the role of Islamic microfinance on women empowerment is very rare in the literature. Therefore, the main objective of this study is to investigate the influence of conventional and Islamic microfinance on women empowerment in Bangladesh. The study additionally studied whether there is any difference between conventional and Islamic microfinance in influencing women empowerment. The empowerment framework considered are resources, agency, and achievement. Resources refer to education, involvement in income generating activities, access to media and access to politics; agency includes decision making agency, freedom of movement, voice with husband and family members; and achievement includes economic security, control over loan use and management, participation in public protest and social support and self-efficacy. This study uses case study method in the investigation process. The lenders investigated are Grameen Bank and Rural Development Scheme of Islami Bank Bangladesh Limited. Data on borrowers were obtained from 40 individuals (20 from each institution) from the four villages in Chittagong, Bangladesh. Data were also obtained from key informants’ interviews, focus group discussions, participant observations and documentary evidence. Data were analyzed using a 7-steps framework method. Pattern matching, thematic analysis and cross case analysis were employed as analytical framework for interpretation using CAQDAS NVivo 10 software. The results indicate that conventional microfinance is influential in terms of access to media and phone, and political and legal awareness of resource dimension. In terms of agency, this study found that conventional microfinance has more influences only on ability to make large purchase decision, involvement in major decisions and relative freedom from the domination by the family. This study also found that conventional microfinance has limited influence in terms of achievement dimension. Islamic microfinance is more influential in terms of access to media and phone, and political and legal awareness of resource dimension. However, among the seven indicators of agency dimension this study found that Islamic microfinance has more influences only on ability to make large purchase decision, and involvement in major decisions. In addition, this study found that Islamic microfinance has more influence on the self- efficacy among the four indicators of achievement dimension. Finally, this study also found some other factors which influence the microfinance role on women empowerment such as microfinance borrower’s life tragedies, husband’s profession and absence, social context, active involvement in income generating activities, higher education and training and self- determination
Biopolymer based carbon nanocomposite for the electrochemical determination of selected painkiller drugs / Md.Shalauddin
No full textBiopolymers are naturally occurring polymers which have attained profound interest and are investigated widely due to their outstanding characteristics and several advantages such as cost efficiency, excellent hydrophilicity, film formation capability, chemical inertness, non-toxicity, high mechanical integrity and biocompatibility. Cellulose and chitosan are the two most abundant biopolymers in the world. Recently, the incorporation of nanocellulose and chitosan into electroconductive platform i.e nanostructured carbon such as- multiwall carbon nanotube (MWCNT) and nitrogen doped graphene (NDG) is the focus of this thesis for the fabrication of modified electrodes as electrochemical sensor for the detection of some common painkiller drugs. Nanocellulose (NC) and chitosan (CTS) possess excellent properties such as biocompatibility, non-toxicity, biodegradability, film formability, dispersion of nanomaterials and preventing leaching of nanomaterials. These biopolymers enhance the electrocatalytic activity of the carbon-based nanoparticles for the sensitive determination of commonly administered painkillers. Multiwall carbon nanotubes and nitrogen doped graphene both are nanostructured carbons and possess excellent features such as high dispersion, chemical and mechanical stability, high electrical conductivity, high surface area etc. These two nanomaterials are conducting scaffold in the presence of biopolymers for the homogenous dispersion of nanomaterials and ultimately enhances the electrons transfer process. A hybrid nanocomposite of NC and MWCNT was prepared, where NC was synthesized while the MWCNT was functionalized by acid hydrolysis method to afford the f-MWCNTs/NC/GCE for the electrochemical determination of widely used painkiller drug, iv
diclofenac sodium. The assimilation of NC and f-MWCNTs enhances the active surface area by proper dispersion of the nanomaterials which enhances the electrical conductivity, accelerates the electrons transfer rate and ultimately amplifies the electrochemical response towards the determination of the targeted analyte. While a nanocomposite comprising of nitrogen doped graphene (NDG), nanocellulose (NC) and sodium dodecyl sulphate (SDS) i.e (NDG-NC)-SDS was prepared for the simultaneous determination of two common painkillers paracetamol (PCT) and naproxen (NPX) in the presence of another painkiller, diclofenac sodium (DCF). Due to binding property of NC, the junction of NC with NDG establishes a good bonding with each other and could be embedded into the graphene nanosheets. Another nanocomposite composed of MWCNT, CTS and copper (Cu), f-MWCNTs/CTS-Cu was prepared for the determination of DCF. The excellent catalytic effect of f-MWCNTs, adsorption capacity and film formation ability of CTS and the incorporation of Cu by immobilization technique enhances the catalytic effect of CTS-Cu complex. The fabricated f-MWCNTs/CTS-Cu nanocomposite is a potential candidate for the analytical detection of DCF. While another conductive biopolymer nanocomposite containing NC and conductive polymer polypyrrole (PPY) was prepared for the simultaneous determination of paracetamol (PCT) and ciprofloxacin (CPR) in commercial dosage forms, biological media and water sample. It should be mentioned that the synthesized biopolymer based nanostructured carbon nanocomposite have been fabricated for the first time for the detection of some common used painkiller drugs in commercial dosage forms and biological fluids