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Syed Sharizman Syed Abdul Rahim,Mohd Fazeli Sazali,Ahmad Hazim Mohammad,Fairrul Kadir,Alvin Oliver Payus,Richard Avoi,Mohammad Saffree Jeffree,Azizan Omar,Mohd Yusof Ibrahim,Azman Atil,Nooralisa Moh 대한결핵및호흡기학회 2023 Tuberculosis and Respiratory Diseases Vol.86 No.2
Tuberculosis (TB) is a significant public health concern. Globally, TB is among the top 10 and the leading cause of death due to a single infectious agent. Providing standard anti-TB therapy for at least 6 months is recommended as one of the crucial strategies to control the TB epidemic. However, the long duration of TB treatment raised the issue of non-adherence. Non-adherence to TB therapy could negatively affect clinical and public health outcomes. Thus, directly observed therapy (DOT) has been introduced as a standard strategy to improve anti-TB medication adherence. Nonetheless, the DOT approach has been criticized due to inconvenience, stigma, reduced economic productivity, and reduced quality of life, which ultimately could complicate adherence issues. Apart from that, its effectiveness in improving anti-TB adherence is debatable. Therefore, digital technology could be an essential tool to enhance the implementation of DOT. Incorporating the health belief model (HBM) into digital technology can further increase its effectiveness in changing behavior and improving medication adherence. This article aimed to review the latest evidence regarding TB medication non-adherence, its associated factors, DOT’s efficacy and its alternatives, and the use of digital technology and HBM in improving medication adherence. This paper used the narrative review methodology to analyze related articles to address the study objectives. Conventional DOT has several disadvantages in TB management. Integrating HBM in digital technology development is potentially effective in improving medication adherence. Digital technology provides an opportunity to improve medication adherence to overcome various issues related to DOT implementation.
Syed Shatir Asghrar Syed-Hassan,Mohd Saufi Md Zaini 한국화학공학회 2016 Korean Journal of Chemical Engineering Vol.33 No.8
The preparation of activated carbon from palm kernel shell for methane adsorption was studied. Taguchi orthogonal array design was employed to optimize the preparation of activated carbon. The statistical results show that the optimized conditions are the impregnation ratio of 0.55, the activation temperature of 900 oC and the activation time of 150min. The impregnation ratio has the most influence on methane adsorption based on S/N ratio analysis. The mathematical model was developed using regression analysis as a function of independent variables. The results of experiment using optimum conditions fall within the predicted value obtained from the developed model. Activated carbon prepared at optimum conditions which have the highest BET surface area of 1,548.0m2/g and the total pore volume of 1.0 cm3/g recorded the highest methane uptake compared to other conditions. The equilibrium data of the adsorption characteristic fitted favourably to the Freundlich isotherm.
Syed Muhammad Raza,Soo Young Shin,Syed Ghazi Hassan,Syed Ali Hassan 한국정보통신학회 2024 Journal of information and communication convergen Vol.22 No.2
Trash or garbage is one of the most dangerous health and environmental problems that affect pollution. Pollution affects nature,human life, and wildlife. In this paper, we propose modern solutions for cleaning the environment of trash pollution by enforcingstrict action against people who dump trash inappropriately on streets, outside the home, and in unnecessary places. ArtificialIntelligence (AI), especially Deep Learning (DL), has been used to automate and solve issues in the world. We availed this as anexcellent opportunity to develop a system that identifies trash using a deep convolutional neural network (CNN). This paperproposes a real-time garbage identification system based on a deep CNN architecture with eight distinct classes for the trainingdataset. After identifying the garbage, the CCTV camera captures a video of the individual placing the trash in the incorrectlocation and sends an alert notice to the relevant authority.
Rahman Syed Ahmad Fadhli Syed Abdul,Maulud Khairul Nizam Abdul,Pradhan Biswajeet,Mustorpha Sharifah Nurul Ain Syed 한국CDE학회 2021 Journal of computational design and engineering Vol.8 No.6
Navigation, also known as discovering one’s direction, is a complex human activity. To produce effective routes, it relies on knowledge of the surroundings’ precise geometry and semantic information. Complex geometrical data can be precisely delineated with the improvement of 3D geometric models. A precise 3D geometric model containing a specifically built-in Building Information Modelling (BIM) environment can be integrated into the Geographical Information System platform for indoor path generation to satisfy the requirements of indoor location-based services. Therefore, this paper proposes an approach to evaluate a 3D indoor topology network called a lattice topology data model (LTDM) for the floor-level paths in a 3D multipatch-based model. The LTDM requires the geometric information of the integrated BIM model to identify the indoor space and bounding lines for indoor network generation. The novelty of this study is in the application of the replacement of cell values into vector length for pathfinding through a combination of the Poincaré duality theorem and Dijkstra’s algorithm. The Campus Infrastructure Building model was chosen to validate the proposed method. Multiple space centroid pairs within the floor level were randomly selected to identify the shortest path using the LTDM principle. Paths drawn from the Medial Axis Transformation were compared with LTDM-generated paths for availability testing. The average floor-level path availability was 112% due to the generation of extra paths reflecting real-life situations. The LTDM paths were compared with on-site measurements for accuracy tests, and the average error rate was 3.18%. The results show that the implementation of the LTDM generates an excellent topology data network.
MicroRNA and Their Potential Role in Conjunctival Disorders
Nazmul Huda Syed(Nazmul Huda Syed ),Embong Zunaina(Embong Zunaina ),Shahidan Wan-Nazatul Shima(Shahidan Wan-Nazatul Shima ),Malvika Sharma(Malvika Sharma ),Ismail Shatriah(Ismail Shatriah ) 대한안과학회 2022 Korean Journal of Ophthalmology Vol.36 No.5
MicroRNAs (miRNAs) are the small noncoding RNA molecules which regulate target gene expression posttranscriptionally. They are known to regulate key cellular processes like inflammation, cell differentiation, cell proliferation, and cell apoptosis across various ocular diseases. Due to their easier access, recent focus has been laid on the investigation of miRNA expression and their involvement in several conjunctival diseases. The aim of this narrative review is to provide understanding of the miRNAs and describe the current role of miRNAs as the mediators of the various conjunctival diseases. A literature search was made using PubMed, Scopus, and Web of Science databases for studies involving miRNAs in the conjunctival pathological conditions. Original articles in the last 10 years involving both human and animal models were included. Literature search retrieved 27 studies matching our criteria. Pertaining to the numerous literatures, there is a strong correlation between miRNA and the various pathological conditions that occur in the conjunctiva. miRNAs are involved in various physiological processes such as cell differentiation, proliferation, apoptosis, development, and inflammation by regulating various signaling pathways, genes, proteins, and mediators. Pterygium was the most studied conjunctival disease for miRNA involvement, whereas miRNA research in allergic conjunctivitis is still in its early stages. Our review provides deep insights into the various miRNAs playing an important role in the various conjunctival diseases. miRNAs do have the potential to serve as noninvasive biomarkers with diagnostic, prognostic, and therapeutic implications. However, multitudinous studies are required to validate miRNAs as the reliable biomarkers in conjunctival pathologies and its targeted therapy.
End-Group Alkylation of Diarylethene to Enhance Photo-Switchability of Organic Transistors
Syed Zahid Hassan,유성훈,소찬,문도현,정대성 한국고분자학회 2021 한국고분자학회 학술대회 연구논문 초록집 Vol.46 No.2
A molecular and synthetic approach to strengthen switching performance of diarylethene (DAE)-based organic transistor is proposed. From photophysical, structural and morphological analyses, we found that longer alkyl chains inhibit intermolecular aggregation between DAEs and allow more hydrophobic surface property of DAEs, thus improving molecular miscibility with ITIC. In addition, it is found that the improved molecular compatibility of DAEs with ITIC makes the overall bulk heterojunction (BHJ) film amorphous, allowing more free volume for reversible photoisomerization. As a result, DAE_C6 exhibits the maximum quantum yield for both photocyclization and photocycloreversion, enabling high light-controlled on/off ratios when employed as a photoswitch of ITIC transistor. Furthermore, exceptionally high quantum yield of DAE_C6 enables robust fatigue resistance under repeated photoswitching of the transistor with only 30% decrease of on/off ratio after 100 cycles.
Performance Improvement of QoS-Enabled WLANs Using Adaptive Contention Window Backoff Algorithm
Syed, Ikram,Shin, Seung-hun,Roh, Byeong-hee,Adnan, Muhammad IEEE 2018 IEEE systems journal Vol.12 No.4
<P>Quality of service (QoS) is one of the critical aspects for real-time applications in wireless local area networks (WLANs). To provide QoS, WLANs use the enhanced distributed channel access (EDCA) with a fixed backoff range without considering the network load for estimating the backoff time. When the number of stations (STAs) increases in each access category (AC), the collision among STAs also increases; this leads to increased delay and decreased network throughput. In this paper, we aim to improve the QoS for WLANs and achieve better network performance in terms of high throughput, low collision rate, and small mean frame delay in delay-sensitive applications. To achieve this objective, we propose an adaptive contention window backoff mechanism that improves the QoS by adjusting the backoff time according to the active STAs in each AC. First, we estimate the number of STAs in each AC and then calculate the optimal contention window size based on the estimated STAs in each AC. We derived an analytical model for the proposed scheme and then conducted simulations to validate analytical model results. The simulation results show that the proposed scheme outperforms EDCA in terms of throughput and delay in different traffic scenarios.</P>
Haptic Guided Optimized Aircraft Maintenance Assembly Disassembly Path Planning Scheme
Syed Hassan,Jungwon Yoon 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10
The virtual aircraft manufacturing environment the most difficult phase so far considered is the automated A/D process (Assembly / Disassembly). The effectiveness of the maintenance scheme depends on the time taken to complete the A/D process. When dealing with complex 3D environment that simulates realistic models, the assembly path planning of the parts becomes more complex because of the factors like complex geometry computations, obstacles, orientation and initial/final position of the part. Therefore, In a 3D environment the path planning of the parts becomes an important factor affecting the overall efficiency of the maintenance process. To address this problem an intelligent assembly path planner is developed with an approach based on Ant colony algorithm and potential field path planning concepts. Furthermore, haptic-assisted feature is implemented for user support for realistic 3D path planning simulations and training.