Search results for: Mohd Yusri Idorus

Authors: Mohd. Noor Md. Sap, A. Majid Awan

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Intelligent systems based on machine learning techniques, such as classification, clustering, are gaining wide spread popularity in real world applications. This paper presents work on developing a software system for predicting crop yield, for example oil-palm yield, from climate and plantation data. At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data. This work gets inspiration from the notion that a non-linear data transformation into some high dimensional feature space increases the possibility of linear separability of the patterns in the transformed space. Therefore, it simplifies exploration of the associated structure in the data. Kernel methods implicitly perform a non-linear mapping of the input data into a high dimensional feature space by replacing the inner products with an appropriate positive definite function. In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering the data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.

Keywords: Pattern analysis, clustering, kernel methods, spatial data, crop yield

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Authors: Noor Zuhaira Abd Aziz, Rahmah Mohamed, Mohd Muizz Fahimi M.

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Rice husk and kenaf filled with calcium carbonate (CaCO3) and high density polyethylene (HDPE) composite were prepared separately using twin-screw extruder at 50rpm. Different filler loading up to 30 parts of rice husk particulate and kenaf fiber were mixed with the fixed 30% amount of CaCO3 mineral filler to produce rice husk/CaCO3/HDPE and kenaf/CaCO3/HDPE hybrid composites. In this study, the effects of natural fiber for both rice husk and kenaf in CaCO3/HDPE composite on physical, mechanical and morphology properties were investigated. Field Emission Scanning Microscope (FeSEM) was used to investigate the impact fracture surfaces of the hybrid composite. The property analyses showed that water absorption increased with the presence of kenaf and rice husk fillers. Natural fibers in composite significantly influence water absorption properties due to natural characters of fibers which contain cellulose, hemicellulose and lignin structures. The result showed that 10% of additional natural fibers into hybrid composite had caused decreased flexural strength, however additional of high natural fiber (>10%) filler loading has proved to increase its flexural strength.

Keywords: Hybrid composites, Water absorption, Mechanical properties.

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Authors: H. Mansor, S. B. Mohd Noor

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This paper presents a design method of self-tuning Quantitative Feedback Theory (QFT) by using improved deadbeat control algorithm. QFT is a technique to achieve robust control with pre-defined specifications whereas deadbeat is an algorithm that could bring the output to steady state with minimum step size. Nevertheless, usually there are large peaks in the deadbeat response. By integrating QFT specifications into deadbeat algorithm, the large peaks could be tolerated. On the other hand, emerging QFT with adaptive element will produce a robust controller with wider coverage of uncertainty. By combining QFT-based deadbeat algorithm and adaptive element, superior controller that is called selftuning QFT-based deadbeat controller could be achieved. The output response that is fast, robust and adaptive is expected. Using a grain dryer plant model as a pilot case-study, the performance of the proposed method has been evaluated and analyzed. Grain drying process is very complex with highly nonlinear behaviour, long delay, affected by environmental changes and affected by disturbances. Performance comparisons have been performed between the proposed self-tuning QFT-based deadbeat, standard QFT and standard dead-beat controllers. The efficiency of the self-tuning QFTbased dead-beat controller has been proven from the tests results in terms of controller’s parameters are updated online, less percentage of overshoot and settling time especially when there are variations in the plant.

Keywords: Deadbeat control, quantitative feedback theory (QFT), robust control, self-tuning control.

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Authors: Zety Shakila Binti Mohd Yusof, Muhammad Adib Bin Ishak, Hajah Fatimah Binti Hussein

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The international shipping business is related to numerous controls or regulations of export and import shipments. It is costly and time consuming, and when something goes wrong or when the buyer or seller fails to comply with the regulations, it can result in penalties, delays, and unexpected costs etc. For the focus of this study, the researchers have selected a local forwarder that provides forwarding and clearance services, Nexus Zone Logistics. It was identified that this company currently has many extra costs to be paid including local and detention charges, which negatively impacts the flow of income and reduces overall stability. Two variables have been identified as factors of extra charges; loaded containers entering the port by exceeded closing time and late delivery of empty containers to the container yard. This study is a qualitative in nature and the secondary data collected was analyzed using self-administered observation. The findings of this study were covered by one selected case for each export and import shipment between July and December 2014. The data were analyzed using frequency analysis based on tables and graphs. The researcher recommends Nexus Zone Logistics impose a 1% deposit payment per container for each shipment (export and import) to its customers.

Keywords: International shipping, export and import, detention charges, container shipment.

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Authors: Mohd Hasmadi Ismail, Kamaruzaman Jusoff

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In order to develop forest management strategies in tropical forest in Malaysia, surveying the forest resources and monitoring the forest area affected by logging activities is essential. There are tremendous effort has been done in classification of land cover related to forest resource management in this country as it is a priority in all aspects of forest mapping using remote sensing and related technology such as GIS. In fact classification process is a compulsory step in any remote sensing research. Therefore, the main objective of this paper is to assess classification accuracy of classified forest map on Landsat TM data from difference number of reference data (200 and 388 reference data). This comparison was made through observation (200 reference data), and interpretation and observation approaches (388 reference data). Five land cover classes namely primary forest, logged over forest, water bodies, bare land and agricultural crop/mixed horticultural can be identified by the differences in spectral wavelength. Result showed that an overall accuracy from 200 reference data was 83.5 % (kappa value 0.7502459; kappa variance 0.002871), which was considered acceptable or good for optical data. However, when 200 reference data was increased to 388 in the confusion matrix, the accuracy slightly improved from 83.5% to 89.17%, with Kappa statistic increased from 0.7502459 to 0.8026135, respectively. The accuracy in this classification suggested that this strategy for the selection of training area, interpretation approaches and number of reference data used were importance to perform better classification result.

Keywords: Image Classification, Reference Data, Accuracy Assessment, Kappa Statistic, Forest Land Cover

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Authors: Mohd Afif Md Nasir, Faizal Amin NurYunus, Jamaluddin Hashim, Abd Samad Hassan Basari, A. Halim Sahelan

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The aim of this study is to identify the suitability of Virtual Learning Environment (VLE) in welding simulator application towards Computer-Based Training (CBT) in developing skills upon new students at the Advanced Technology Training Center (ADTEC) Batu Pahat, Johor, Malaysia and GIATMARA, Batu Pahat, Johor, Malaysia. The significance of the study is to create a computer-based skills development approach in welding technology among new students in ADTEC and GIATMARA as well as to cultivate the elements of general skills among them. This study is also important in elevating the number of individual knowledge workers (K-workers) working in manufacturing industry in order to achieve a national vision which is to be an industrial nation in the year of 2020. The design of the study is a survey type of research which using questionnaires as the instruments and some 136 students from ADTEC and GIATMARA were interviewed. Descriptive analysis is used to identify the frequency and mean values. The findings of the study show that the welding technology has developed skills in the students because of the application of VLE simulated at a high level and the respondents agreed that the skills could be embedded through the application of the VLE simulator. In summary, the VLE simulator is suitable in welding skills development training in terms of exposing new students with the relevant characteristics of welding skills and at the same time spurring the students’ interest towards learning more about the skills.

Keywords: Computer-Based Training (CBT), knowledge workers (K-workers), virtual learning environment, welding simulator, welding technology.

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Authors: Mohd. A. M. Rahim, Yahaya Hassan, Mathumalar L. Fahrni

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Second line antiretroviral therapy (ART) regimen is used when patients fail their first line regimen. There are many factors such as non-adherence, drug resistance as well as virological and immunological failure that lead to second line highly active antiretroviral therapy (HAART) regimen treatment failure. This study was aimed at determining predictor factors to treatment failure with second line HAART and analyzing median survival time. An observational, retrospective study was conducted in Sungai Buloh Hospital (HSB) to assess current status of HIV patients treated with second line HAART regimen. Convenience sampling was used and 104 patients were included based on the study’s inclusion and exclusion criteria. Data was collected for six months i.e. from July until December 2013. Data was then analysed using SPSS version 18. Kaplan-Meier and Cox regression analyses were used to measure median survival times and predictor factors for treatment failure. The study population consisted mainly of male subjects, aged 30- 45 years, who were heterosexual, and had HIV infection for less than 6 years. The most common second line HAART regimen given was lopinavir/ritonavir (LPV/r)-based combination. Kaplan-Meier analysis showed that patients on LPV/r demonstrated longer median survival times than patients on indinavir/ritonavir (IDV/r) based combination (p<0.001). The commonest reason for a treatment to fail with second line HAART was non-adherence. Based on Cox regression analysis, other predictor factors for treatment failure with second line HAART regimen were age and mode of HIV transmission.

Keywords: Adherence, antiretroviral therapy, second line, treatment failure.

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Authors: Juhi Faridi, Mohd. Ajmal Kafeel

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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS.  Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.

Keywords: Analog circuits, digital circuits, memristors, neuromorphic computing systems.

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Authors: Noor Zainab Habib, Ibrahim Kamaruddin, Madzalan Napiah, Isa Mohd Tan

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This paper presents a research conducted to investigate the effect of mixing process on polypropylene (PP) modified bitumen mixed with well graded aggregate to form modified bituminous concrete mix. Two mode of mixing, namely dry and wet with different concentration of polymer polypropylene was used with 80/100 pen bitumen, to evaluate the bituminous concrete mix properties. Three percentages of polymer varying from 1-3% by the weight of bitumen was used in this study. Three mixes namely control mix, wet mix and dry mix were prepared. Optimum binder content was calculated considering Marshall Stability, flow, air voids and Marshall Quotient at different bitumen content varying from 4% - 6.5% for control, dry and wet mix. Engineering properties thus obtained at the calculated optimum bitumen content revealed that wet mixing process is advantageous in comparison to dry mixing as it increases the stiffness of the mixture with the increase in polymer content in bitumen. Stiffness value for wet mix increases with the increase in polymer content which is beneficial in terms of rutting. 1% PP dry mix also shows enhanced stiffness, with the air void content limited to 4%.The flow behaviour of dry mix doesn't indicate any major difference with the increase in polymer content revealing that polymer acting as an aggregate only without affecting the viscosity of the binder in the mix. Polypropylene (PP) when interacted with 80 pen base bitumen enhances its performance characteristics which were brought about by altered rheological properties of the modified bitumen. The decrease in flow with the increase in binder content reflects the increase in viscosity of binder which induces the plastic flow in the mix. Workability index indicates that wet mix were easy to compact up to desired void ratio in comparison to dry mix samples.

Keywords: Marshall Flow, Marshall Stability, Polymer modified bitumen, Polypropylene, Stiffness.

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Authors: Y. S. Liew, K. A. Puteh Ariffin, M. A. Mohd Nor

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One of the Best Management Practices (BMPs) promoted in Urban Stormwater Management Manual for Malaysia (MSMA) published by the Department of Irrigation and Drainage (DID) in 2001 is through the construction of wet ponds in new development projects for water quantity and quality control. Therefore, this paper aims to demonstrate a case study on evaluation of a constructed mini wet pond located at Sekolah Rendah Kebangsaan Seksyen 2, Puchong, Selangor, Malaysia in both stormwater quantity and quality aspect particularly to reduce the peak discharge by temporary storing and gradual release of stormwater runoff from an outlet structure or other release mechanism. The evaluation technique will be using InfoWorks Collection System (CS) as the numerical modeling approach for water quantity aspect. Statistical test by comparing the correlation coefficient (R²), mean error (ME), mean absolute error (MAE) and root mean square error (RMSE) were used to evaluate the model in simulating the peak discharge changes. Results demonstrated that there will be a reduction in peak flow at 11 % to 15% and time to peak flow is slower by 5 minutes through a wet pond. For water quality aspect, a survey on biological indicator of water quality carried out depicts that the pond is within the range of rather clean to clean water with the score of 5.3. This study indicates that a constructed wet pond with wetland facilities is able to help in managing water quantity and stormwater generated pollution at source, towards achieving ecologically sustainable development in urban areas.

Keywords: Wet pond, Retention Facilities, Best Management Practices (BMP), Urban Stormwater Management Manual for Malaysia (MSMA).

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Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Sharul T. Tajuddin, Hartiny Md Azmi

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Taking into consideration the real time situation specifically the higher academic institutions, small, medium to large companies, public to private sectors and the remaining sectors, do experience the inventory or asset shrinkages due to theft, loss or even inventory tracking errors. This happening is due to a zero or poor security systems and measures being taken and implemented in their organizations. Henceforth, implementing the Radio Frequency Identification (RFID) technology into any manual or existing web-based system or web application can simply deter and will eventually solve certain major issues to serve better data retrieval and data access. Having said, this manual or existing system can be enhanced into a mobile-based system or application. In addition to that, the availability of internet connections can aid better services of the system. Such involvement of various technologies resulting various privileges to individuals or organizations in terms of accessibility, availability, mobility, efficiency, effectiveness, real-time information and also security. This paper will look deeper into the integration of mobile devices with RFID technologies with the purpose of asset tracking and control. Next, it is to be followed by the development and utilization of MongoDB as the main database to store data and its association with RFID technology. Finally, the development of a web based system which can be viewed in a mobile based formation with the aid of Hypertext Preprocessor (PHP), MongoDB, Hyper-Text Markup Language 5 (HTML5), Android, JavaScript and AJAX programming language.

Keywords: RFID, asset tracking system, MongoDB, NoSQL.

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Authors: Mina Najafi, Mustafa Kamal Bin Mohd Shariff

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Religious place attachment is an affective bond that develops between people and their religious settings. The published literature shows that although religion has a significant impact on the public ‘place attachment’, the architectural features and attributes of the places could still play an influencing role in strengthening this attachment. However, the role of architectural characteristics and features of the religious places, as the components that give them meaning(s), has not been adequately explored. This paper reports the impacts of factors influencing the physical and ambience quality of different styles of Malaysian mosques from the Muslim public perspective. Thereby, a survey was conducted to investigate Malaysian public attachment to selected five Malaysian state mosques with respect to their architectural characteristics and features. The survey employed the results of series of interviews as its theoretical basis. The finding proved that Malaysian ‘Muslim’ society has equally strong attachment to all selected mosques in spite of their different architectural styles. The findings also confirmed that the emotional attachment to the impressive aspects of architectural features (e.g. dome, minaret etc.) and the unique identity of the studied mosques is irrespective of the architectural styles, e.g. Modern vs. Postmodern. The paper also argued that religious activities and pleasant architectural characteristic of the studied places including the functional facilities are equally important factors in forming place attachment. This is a new approach to the study of physical and ambience quality of mosques, hence providing sufficient theoretical basis for further investigations and improvements.

Keywords: Place Attachment, Place Identity, Physical Features, Malaysian Mosques.

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Authors: Noor Azlina Mohd Salleh, Salmiah Kasolang, Ahmed Jaffar

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Green Lean Total Quality Management (LTQM) Human Resource Management (HRM) System is a system comprises of HRM in Environmental Management System (EMS) practices which is integrated to TQM with Lean Manufacturing (LM) principles. HRM is essential especially in dealing with low motivation and less productive employees. The ultimate goal of this system is to focus on achieving total human resource development that is motivated and capable to optimize their creativity to be a part of Green and Lean TQM organization. A survey questionnaire was developed and distributed to 30 highly active automotive vendors in Malaysia and analyzed by Minitab v16 and SPSS v17. It was found out companies that are practicing Green LTQM HRM practices have generated more revenue and have RND capability. However, years of company establishment do not affect the openness of the company to adapt new initiatives that can help to improve the effectiveness of the operations. It was also found out the importance of training, communication and rewards for employees. The Green LTQM HRM practices framework model established in this study hopefully will give preliminary insight especially to companies that are still looking for system that can improve their productivity from managing human resource. This is preliminary study that combined 4 awards practices, ISO/TS16949, Toyota Production System SAEJ4000, MAJAICO Lean Production System and EMS focusing on highly active companies that have been involved in MAJAICO Program and Proton Vendor Development Program. Future study can be conducted to know the status at other industry as well as case study pertaining to this system.

Keywords: Automotive Industry, Lean Manufacturing, Operational Engineering Management, Total Quality Management. Environmental Management System.

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Authors: M. Z. Bin Mohd Ghazali, N. C. Wilson, A. F. Bin Ahmad Fuad, M. A. H. B. Musa, M. U. Mohamad Sani, F. Zulkifli, M. S. Zainal Abidin

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Physical activity levels are low in Malaysia and this study was undertaken to determine if a four week work-based intervention program would be effective in changing physical activity levels. The study was conducted in a Malaysian Government Department and had three stages: baseline data collection, four-week intervention and two-month post intervention data collection. During the intervention and two-month post intervention phases, physical activity levels (determined by a pedometer) and basic health profiles (BMI, abdominal obesity, blood pressure) were measured. Staff (58 males, 47 females) with an average age of 33 years completed baseline data collection. Pedometer steps averaged 7,102 steps/day at baseline, although male step counts were significantly higher than females (7,861 vs. 6114). Health profiles were poor: over 50% were overweight/obese (males 66%, females 40%); hypertension (males 23%, females 6%); excess waist circumference (males 52%, females 17%). While 86 staff participated in the intervention, only 49 regularly reported their steps. There was a significant increase (17%) in average daily steps from 8,965 (week 1) to 10,436 (week 4). Unfortunately, participation in the intervention program was avoided by the less healthy staff. Two months after the intervention there was no significant difference in average steps/day, despite the fact that 89% of staff reporting they planned to make long-term changes to their lifestyle. An unexpected average increase of 2kg in body weight occurred in participants, although this was less than the 5.6kg in non-participants. A number of recommendations are made for future interventions, including the conclusion that pedometers were a useful tool and popular with participants.

Keywords: Pedometers, walking, health, intervention.

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Authors: Siti Nor Hafizah binti Mohd Zaid, Mohamed Abdel-Maguid, Abdel-Hamid Soliman

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An Advance Driver Assistance System (ADAS) is a computer system on board a vehicle which is used to reduce the risk of vehicular accidents by monitoring factors relating to the driver, vehicle and environment and taking some action when a risk is identified. Much work has been done on assessing vehicle and environmental state but there is still comparatively little published work that tackles the problem of driver state. Visual attention is one such driver state. In fact, some researchers claim that lack of attention is the main cause of accidents as factors such as fatigue, alcohol or drug use, distraction and speeding all impair the driver-s capacity to pay attention to the vehicle and road conditions [1]. This seems to imply that the main cause of accidents is inappropriate driver behaviour in cases where the driver is not giving full attention while driving. The work presented in this paper proposes an ADAS system which uses an image based template matching algorithm to detect if a driver is failing to observe particular windscreen cells. This is achieved by dividing the windscreen into 24 uniform cells (4 rows of 6 columns) and matching video images of the driver-s left eye with eye-gesture templates drawn from images of the driver looking at the centre of each windscreen cell. The main contribution of this paper is to assess the accuracy of this approach using Receiver Operating Characteristic analysis. The results of our evaluation give a sensitivity value of 84.3% and a specificity value of 85.0% for the eye-gesture template approach indicating that it may be useful for driver point of regard determinations.

Keywords: Advanced Driver Assistance Systems, Eye-Tracking, Hazard Detection.

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Authors: N. A. Samat, S. H. Mohd Imam Ma’arof

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Dengue disease is an infectious vector-borne viral disease that is commonly found in tropical and sub-tropical regions, especially in urban and semi-urban areas, around the world and including Malaysia. There is no currently available vaccine or chemotherapy for the prevention or treatment of dengue disease. Therefore prevention and treatment of the disease depend on vector surveillance and control measures. Disease risk mapping has been recognized as an important tool in the prevention and control strategies for diseases. The choice of statistical model used for relative risk estimation is important as a good model will subsequently produce a good disease risk map. Therefore, the aim of this study is to estimate the relative risk for dengue disease based initially on the most common statistic used in disease mapping called Standardized Morbidity Ratio (SMR) and one of the earliest applications of Bayesian methodology called Poisson-gamma model. This paper begins by providing a review of the SMR method, which we then apply to dengue data of Perak, Malaysia. We then fit an extension of the SMR method, which is the Poisson-gamma model. Both results are displayed and compared using graph, tables and maps. Results of the analysis shows that the latter method gives a better relative risk estimates compared with using the SMR. The Poisson-gamma model has been demonstrated can overcome the problem of SMR when there is no observed dengue cases in certain regions. However, covariate adjustment in this model is difficult and there is no possibility for allowing spatial correlation between risks in adjacent areas. The drawbacks of this model have motivated many researchers to propose other alternative methods for estimating the risk.

Keywords: Dengue disease, Disease mapping, Standardized Morbidity Ratio, Poisson-gamma model, Relative risk.

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Authors: Sarina Md Yusof, Suhana Aiman, Mohd Khairi Zawi, Hosni Hasan, Azila Azreen Md Radzi

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Failure in mastery of motor skills proficiency during childhood has been seen as a detrimental factor for children to be physically active. Lack of motor skills proficiency tends to reduce children’s competency and confidence level to participate in physical activity. As a consequence of less participation in physical activity, children will turn to be overweight and obese. It has been suggested that children who master motor skill proficiency will be more involved in physical activity thus preventing them from being overweight. Obesity has become a serious childhood health issues worldwide. Previous studies have found that children who were overweight and obese were generally less active however these studies focused on one gender. This study aims to compare motor skill proficiency of underweight, normal-weight, overweight and obese young boys as well as to determine the relationship between motor skills proficiency and body composition. 112 boys aged between 8 to 10 years old participated in this study. Participants were assigned to four groups; underweight, normal-weight, overweight and obese using BMI-age percentile chart for children. Bruininks- Oseretsky Test Second Edition-Short Form was administered to assess their motor skill proficiency. Meanwhile, body composition was determined by the skinfold thickness measurement. Result indicated that underweight and normal children were superior in motor skills proficiency compared to overweight and obese children (p < 0.05). A significant strong inverse correlation between motor skills proficiency and body composition (r = -0.849) is noted. The findings of this study could be explained by non-contributory mass that carried by overweight and obese children leads to biomechanical movement inefficiency which will become detrimental to motor skills proficiency. It can be concluded that motor skills proficiency is inversely correlated with body composition.

Keywords: Motor skills proficiency, body composition, obesity.

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Authors: M.H. Ahmad Fadzil, Esa Prakasa, Hurriyatul Fitriyah, Hermawan Nugroho, Azura Mohd Affandi, S.H. Hussein

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Psoriasis is a widespread skin disease affecting up to 2% population with plaque psoriasis accounting to about 80%. It can be identified as a red lesion and for the higher severity the lesion is usually covered with rough scale. Psoriasis Area Severity Index (PASI) scoring is the gold standard method for measuring psoriasis severity. Scaliness is one of PASI parameter that needs to be quantified in PASI scoring. Surface roughness of lesion can be used as a scaliness feature, since existing scale on lesion surface makes the lesion rougher. The dermatologist usually assesses the severity through their tactile sense, therefore direct contact between doctor and patient is required. The problem is the doctor may not assess the lesion objectively. In this paper, a digital image analysis technique is developed to objectively determine the scaliness of the psoriasis lesion and provide the PASI scaliness score. Psoriasis lesion is modelled by a rough surface. The rough surface is created by superimposing a smooth average (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate average surface followed by a subtraction between rough and average surface to give elevation surface (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 444 lesion models. From roughness validation result, only 6 models can not be accepted (percentage error is greater than 10%). These errors occur due the scanned image quality. Roughness algorithm is validated for roughness measurement on abrasive papers at flat surface. The Pearson-s correlation coefficient of grade value (G) of abrasive paper and Ra is -0.9488, its shows there is a strong relation between G and Ra. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data.

Keywords: psoriasis, roughness algorithm, polynomial surfacefitting.

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Authors: Yehia A. Eldrainy, Mohammad Nazri Mohd. Jaafar, Tholudin Mat Lazim

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This paper presents a cold flow simulation study of a small gas turbine combustor performed using laboratory scale test rig. The main objective of this investigation is to obtain physical insight of the main vortex, responsible for the efficient mixing of fuel and air. Such models are necessary for predictions and optimization of real gas turbine combustors. Air swirler can control the combustor performance by assisting in the fuel-air mixing process and by producing recirculation region which can act as flame holders and influences residence time. Thus, proper selection of a swirler is needed to enhance combustor performance and to reduce NOx emissions. Three different axial air swirlers were used based on their vane angles i.e., 30°, 45°, and 60°. Three-dimensional, viscous, turbulent, isothermal flow characteristics of the combustor model operating at room temperature were simulated via Reynolds- Averaged Navier-Stokes (RANS) code. The model geometry has been created using solid model, and the meshing has been done using GAMBIT preprocessing package. Finally, the solution and analysis were carried out in a FLUENT solver. This serves to demonstrate the capability of the code for design and analysis of real combustor. The effects of swirlers and mass flow rate were examined. Details of the complex flow structure such as vortices and recirculation zones were obtained by the simulation model. The computational model predicts a major recirculation zone in the central region immediately downstream of the fuel nozzle and a second recirculation zone in the upstream corner of the combustion chamber. It is also shown that swirler angles changes have significant effects on the combustor flowfield as well as pressure losses.

Keywords: cold flow, numerical simulation, combustor;turbulence, axial swirler.

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Authors: Siti Aisyah Zakaria, Nor Azrita Mohd Amin, Noor Fadhilah Ahmad Radi, Nasrul Hamidin

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Higher ground-level ozone (GLO) concentration adversely affects human health, vegetations as well as activities in the ecosystem. In Malaysia, most of the analysis on GLO concentration are carried out using the average value of GLO concentration, which refers to the centre of distribution to make a prediction or estimation. However, analysis which focuses on the higher value or extreme value in GLO concentration is rarely explored. Hence, the objective of this study is to classify the tail behaviour of GLO using generalized extreme value (GEV) distribution estimation the return level using the corresponding modelling (Gumbel, Weibull, and Frechet) of GEV distribution. The results show that Weibull distribution which is also known as short tail distribution and considered as having less extreme behaviour is the best-fitted distribution for four selected air monitoring stations in Peninsular Malaysia, namely Larkin, Pelabuhan Kelang, Shah Alam, and Tanjung Malim; while Gumbel distribution which is considered as a medium tail distribution is the best-fitted distribution for Nilai station. The return level of GLO concentration in Shah Alam station is comparatively higher than other stations. Overall, return levels increase with increasing return periods but the increment depends on the type of the tail of GEV distribution’s tail. We conduct this study by using maximum likelihood estimation (MLE) method to estimate the parameters at four selected stations in Peninsular Malaysia. Next, the validation for the fitted block maxima series to GEV distribution is performed using probability plot, quantile plot and likelihood ratio test. Profile likelihood confidence interval is tested to verify the type of GEV distribution. These results are important as a guide for early notification on future extreme ozone events.

Keywords: Extreme value theory, generalized extreme value distribution, ground-level ozone, return level.

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Authors: Syahril Ridzuan Ab Rahim, Ibrahim Ahmad, Mohd Azizi Chik, Ahmad Zafir Md. Rejab, and U. Hashim

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This research presents the development of simulation modeling for WIP management in semiconductor fabrication. Manufacturing simulation modeling is needed for productivity optimization analysis due to the complex process flows involved more than 35 percent re-entrance processing steps more than 15 times at same equipment. Furthermore, semiconductor fabrication required to produce high product mixed with total processing steps varies from 300 to 800 steps and cycle time between 30 to 70 days. Besides the complexity, expansive wafer cost that potentially impact the company profits margin once miss due date is another motivation to explore options to experiment any analysis using simulation modeling. In this paper, the simulation model is developed using existing commercial software platform AutoSched AP, with customized integration with Manufacturing Execution Systems (MES) and Advanced Productivity Family (APF) for data collections used to configure the model parameters and data source. Model parameters such as processing steps cycle time, equipment performance, handling time, efficiency of operator are collected through this customization. Once the parameters are validated, few customizations are made to ensure the prior model is executed. The accuracy for the simulation model is validated with the actual output per day for all equipments. The comparison analysis from result of the simulation model compared to actual for achieved 95 percent accuracy for 30 days. This model later was used to perform various what if analysis to understand impacts on cycle time and overall output. By using this simulation model, complex manufacturing environment like semiconductor fabrication (fab) now have alternative source of validation for any new requirements impact analysis.

Keywords: Advanced Productivity Family (APF), Complementary Metal Oxide Semiconductor (CMOS), Manufacturing Execution Systems (MES), Work In Progress (WIP).

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Authors: Adilah Shariff, Nurhidayah Mohamed Noor, Alexander Lau, Muhammad Azwan Mohd Ali

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Biomass such as corn and cassava wastes if left to decay will release significant quantities of greenhouse gases (GHG) including carbon dioxide and methane. The biomass wastes can be converted into biochar via thermochemical process such as slow pyrolysis. This approach can reduce the biomass wastes as well as preserve its carbon content. Biochar has the potential to be used as a carbon sequester and soil amendment. The aim of this study is to investigate the characteristics of the corn cob, cassava stem, and cassava rhizome in order to identify their potential as pyrolysis feedstocks for biochar production. This was achieved by using the proximate and elemental analyses as well as calorific value and lignocellulosic determination. The second objective is to investigate the effect of pyrolysis temperature on the biochar produced. A fixed bed slow pyrolysis reactor was used to pyrolyze the corn cob, cassava stem, and cassava rhizome. The pyrolysis temperatures were varied between 400 °C and 600 °C, while the heating rate and the holding time were fixed at 5 °C/min and 1 hour, respectively. Corn cob, cassava stem, and cassava rhizome were found to be suitable feedstocks for pyrolysis process because they contained a high percentage of volatile matter more than 80 mf wt.%. All the three feedstocks contained low nitrogen and sulphur content less than 1 mf wt.%. Therefore, during the pyrolysis process, the feedstocks give off very low rate of GHG such as nitrogen oxides and sulphur oxides. Independent of the types of biomass, the percentage of biochar yield is inversely proportional to the pyrolysis temperature. The highest biochar yield for each studied temperature is from slow pyrolysis of cassava rhizome as the feedstock contained the highest percentage of ash compared to the other two feedstocks. The percentage of fixed carbon in all the biochars increased as the pyrolysis temperature increased. The increment of pyrolysis temperature from 400 °C to 600 °C increased the fixed carbon of corn cob biochar, cassava stem biochar and cassava rhizome biochar by 26.35%, 10.98%, and 6.20% respectively. Irrespective of the pyrolysis temperature, all the biochars produced were found to contain more than 60 mf wt.% fixed carbon content, much higher than its feedstocks.

Keywords: Biochar, biomass, cassava wastes, corn cob, pyrolysis.

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Authors: Duong Vannak, Mohd Shahir Liew, Guo Zheng Yew

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Data of wave height and wind speed were collected from three existing oil fields in South China Sea – offshore Peninsular Malaysia, Sarawak and Sabah regions. Extreme values and other significant data were employed for analysis. The data were recorded from 1999 until 2008. The results show that offshore structures are susceptible to unacceptable motions initiated by wind and waves with worst structural impacts caused by extreme wave heights. To protect offshore structures from damage, there is a need to quantify descriptive statistics and determine spectra envelope of wind speed and wave height, and to ascertain the frequency content of each spectrum for offshore structures in the South China Sea shallow waters using measured time series. The results indicate that the process is nonstationary; it is converted to stationary process by first differencing the time series. For descriptive statistical analysis, both wind speed and wave height have significant influence on the offshore structure during the northeast monsoon with high mean wind speed of 13.5195 knots (
= 6.3566 knots) and the high mean wave height of 2.3597 m (
= 0.8690 m). Through observation of the spectra, there is no clear dominant peak and the peaks fluctuate randomly. Each wind speed spectrum and wave height spectrum has its individual identifiable pattern. The wind speed spectrum tends to grow gradually at the lower frequency range and increasing till it doubles at the higher frequency range with the mean peak frequency range of 0.4104 Hz to 0.4721 Hz, while the wave height tends to grow drastically at the low frequency range, which then fluctuates and decreases slightly at the high frequency range with the mean peak frequency range of 0.2911 Hz to 0.3425 Hz.

Keywords: Metocean, Offshore Engineering, Time Series, Descriptive Statistics, Autospectral Density Function, Wind, Wave.

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Authors: Mohd.F.Shabir, P. Tamilporai, B. Rajendra Prasath

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The fundamental aim of extended expansion concept is to achieve higher work done which in turn leads to higher thermal efficiency. This concept is compatible with the application of turbocharger and LHR engine. The Low Heat Rejection engine was developed by coating the piston crown, cylinder head inside with valves and cylinder liner with partially stabilized zirconia coating of 0.5 mm thickness. Extended expansion in diesel engines is termed as Miller cycle in which the expansion ratio is increased by reducing the compression ratio by modifying the inlet cam for late inlet valve closing. The specific fuel consumption reduces to an appreciable level and the thermal efficiency of the extended expansion turbocharged LHR engine is improved. In this work, a thermodynamic model was formulated and developed to simulate the LHR based extended expansion turbocharged direct injection diesel engine. It includes a gas flow model, a heat transfer model, and a two zone combustion model. Gas exchange model is modified by incorporating the Miller cycle, by delaying inlet valve closing timing which had resulted in considerable improvement in thermal efficiency of turbocharged LHR engines. The heat transfer model, calculates the convective and radiative heat transfer between the gas and wall by taking into account of the combustion chamber surface temperature swings. Using the two-zone combustion model, the combustion parameters and the chemical equilibrium compositions were determined. The chemical equilibrium compositions were used to calculate the Nitric oxide formation rate by assuming a modified Zeldovich mechanism. The accuracy of this model is scrutinized against actual test results from the engine. The factors which affect thermal efficiency and exhaust emissions were deduced and their influences were discussed. In the final analysis it is seen that there is an excellent agreement in all of these evaluations.

Keywords: Low Heat Rejection, Miller cycle.

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Authors: Saleh Abduallah Saleh, Mohammad Basir Bin Saud, Mohd Azwardi Md Isa

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It is very important for a developing nation to developing their infrastructure on the prime priority because their infrastructure particularly their roads and transportation functions as a blood in the system. Almost 1.1 billion populations share the travel and transportation industry in India. On the other hand, the Pakistan transportation industry is also extensive and elevating about 170 million users of transportation. Indian and Pakistani specifically within bus industry are well connected within and between the urban and rural areas. The transportation industry is radically helping the economic alleviation of both countries. Due to high economic instability, unemployment and poverty rate both countries governments are very serious and committed to help for boosting their economy. They believe that any form of transportation development would play a vital role in the development of land, infrastructure which could indirectly support many other industries’ developments, such as tourism, freighting and shipping businesses, just to mention a few. However, it seems that their previous transportation planning in the due course has failed to meet the fast growing demand. As with the span of time, both the countries are looking forward to a long-term, and economical solutions, because the demand is from time to time keep appreciating and reacting according to other key economic drivers. Content analysis method and case study approach is used in this paper and secondary data from the bureau of statistic is used for case analysis. The paper focused on the mobility concerns of the lower and middle-income people in India and Pakistan. The paper is aimed to highlight the weaknesses, opportunities and limitations resulting from low priority industry for a government, which is making the either country's public suffer. The paper has concluded that the main issue is identified as the slow, inappropriate, and unfavorable decisions which are not in favor of long-term country’s economic development and public interest. The paper also recommends to future research avenues for public and private transportation, which is continuously failing to meet the public expectations.

Keywords: Bus transportation industries, transportation demand, government parallel initiatives, road and traffic congestions.

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Authors: M. Izzat Md. Nor, N. Jaffar, N. Zaitulakma Md. Zain, N. Izyanti Mohd Suppian, S. Balakrishnan, G. Kandavello

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During the Coronavirus (COVID-19) pandemic, Malaysia has been focusing on building herd immunity by introducing vaccination programs into the community. Hospital Standard Operating Procedures (SOP) were developed to prevent inpatient transmission. In this study, we focus on the positivity rate of inpatient Person Under Surveillance (PUS) becoming COVID-19 positive and compare this to the national rate in order to see the outcomes of the patient who becomes COVID-19 positive in relation to their vaccination status. This is a retrospective observational study carried out from 1 January until 30 March 2022 in Institut Jantung Negara (IJN). There were 5,255 patients admitted during the time of this study. Pre-admission Polymerase Chain Reaction (PCR) swab was done for all patients. Patients with positive PCR on pre-admission screening were excluded. The patients who had exposure to COVID-19-positive staff or patients during hospitalization were defined as PUS and were quarantined and monitored for potential COVID-19 infection. Their frequency and risk of exposure (WHO definition) were recorded. On the final day of quarantine, a second PCR swab was performed on PUS patients who exhibit clinical deterioration, whether or not they exhibit COVID-19 symptoms. The severity of COVID-19 infection was defined as category 1-5A. All patients' vaccination status was recorded, and they were divided into three groups: fully immunised, partially immunised, and unvaccinated. We analysed the positivity rate of PUS patients becoming COVID-positive, outcomes, and correlation with the vaccination status. The ratio of positive inpatient PUS to the total inpatient PUS is 492; only 13 became positive, giving a positivity rate of 2.6%. Eight (62%) had multiple exposures. The majority, 8/13(72.7%), had a high-risk exposure, and the remaining 5 had medium-risk exposure. Four (30.8%) were boosted, 7(53.8%) were fully vaccinated, and 2(15.4%) were partial/unvaccinated. Eight patients were in categories 1-2, whilst 38% were in categories 3-5. Vaccination status did not correlate with COVID-19 Category (P = 0.641). One (7.7%) patient died due to COVID-19 complications and sepsis. Within the first quarter of 2022, our institution's positivity rate (2.6%) is significantly lower than the country's (14.4%). High-risk exposure and multiple exposures to positive COVID-19 cases increased the risk of PUS becoming COVID-19 positive despite their underlying vaccination status.

Keywords: COVID-19, boosted, high risk, Malaysia, quarantine, vaccination status.

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Authors: Mohd Fikri Azli bin Abdullah, Khairul Anwar bin Kamarul Hatta, Esther Jeganathan

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WiFi has become an essential technology that is widely used nowadays. It is famous due to its convenience to be used with mobile devices. This is especially true for Internet users worldwide that use WiFi connections. There are many location based services that are available nowadays which uses Wireless Fidelity (WiFi) signal fingerprinting. A common example that is gaining popularity in this era would be Foursquare. In this work, the WiFi signal would be used to estimate the user or client’s location. Similar to GPS, fingerprinting method needs a floor plan to increase the accuracy of location estimation. Still, the factor of inconsistent WiFi signal makes the estimation defer at different time intervals. Given so, an adaptive method is needed to obtain the most accurate signal at all times. WiFi signals are heavily distorted by external factors such as physical objects, radio frequency interference, electrical interference, and environmental factors to name a few. Due to these factors, this work uses a method of reducing the signal noise and estimation using the Nearest Neighbour based on past activities of the signal to increase the signal accuracy up to more than 80%. The repository yet increases the accuracy by using Artificial Neural Network (ANN) pattern matching. The repository acts as the server cum support of the client side application decision. Numerous previous works has adapted the methods of collecting signal strengths in the repository over the years, but mostly were just static. In this work, proposed solutions on how the adaptive method is done to match the signal received to the data in the repository are highlighted. With the said approach, location estimation can be done more accurately. Adaptive update allows the latest location fingerprint to be stored in the repository. Furthermore, any redundant location fingerprints are removed and only the updated version of the fingerprint is stored in the repository. How the location estimation of the user can be predicted would be highlighted more in the proposed solution section. After some studies on previous works, it is found that the Artificial Neural Network is the most feasible method to deploy in updating the repository and making it adaptive. The Artificial Neural Network functions are to do the pattern matching of the WiFi signal to the existing data available in the repository.

Keywords: Adaptive Repository, Artificial Neural Network, Location Estimation, Nearest Neighbour Euclidean Distance, WiFi RSSI Fingerprinting.

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Authors: Wisam H. Muragaa, Kamaruzzaman Seman, Mohd Fadzli Marhusin

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Software Defined Networking (SDN) is a new norm of networks. It is designed to facilitate the way of managing, measuring, debugging and controlling the network dynamically, and to make it suitable for the modern applications. Generally, measurement methods can be divided into two categories: Active and passive methods. Active measurement method is employed to inject test packets into the network in order to monitor their behaviour (ping tool as an example). Meanwhile the passive measurement method is used to monitor the traffic for the purpose of deriving measurement values. The measurement methods, both active and passive, are useful for the collection of traffic statistics, and monitoring of the network traffic. Although there has been a work focusing on measuring traffic statistics in SDN environment, it was only meant for measuring packets and bytes rates for non-web traffic. In this study, a feasible method will be designed to measure the number of packets and bytes in a certain time, and facilitate obtaining statistics for both web traffic and non-web traffic. Web traffic refers to HTTP requests that use application layer; while non-web traffic refers to ICMP and TCP requests. Thus, this work is going to be more comprehensive than previous works. With a developed module on POX OpenFlow controller, information will be collected from each active flow in the OpenFlow switch, and presented on Command Line Interface (CLI) and wireshark interface. Obviously, statistics that will be displayed on CLI and on wireshark interfaces include type of protocol, number of bytes and number of packets, among others. Besides, this module will show the number of flows added to the switch whenever traffic is generated from and to hosts in the same statistics list. In order to carry out this work effectively, our Python module will send a statistics request message to the switch requesting its current ports and flows statistics in every five seconds; while the switch will reply with the required information in a message called statistics reply message. Thus, POX controller will be notified and updated with any changes could happen in the entire network in a very short time. Therefore, our aim of this study is to prepare a list for the important statistics elements that are collected from the whole network, to be used for any further researches; particularly, those that are dealing with the detection of the network attacks that cause a sudden rise in the number of packets and bytes like Distributed Denial of Service (DDoS).

Keywords: Mininet, OpenFlow, POX controller, SDN.

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Authors: Abtehal Y. Anaas, Mohd. Nazmi Bin Abd. Manap

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Meat Tenderness is one of the most important factors affecting consumers' assessment of meat quality. Variation in meat tenderness is genetically controlled and varies among breeds, and it is also influenced by environmental factors that can affect its creation during rigor mortis and postmortem. The final postmortem meat tenderization relies on the extent of proteolysis of myofibrillar proteins caused by the endogenous activity of the proteolytic calpain system. This calpain system includes different calcium-dependent cysteine proteases, and an inhibitor, calpastatin. It is widely accepted that in farm animals including chickens, the μ-calpain gene (CAPN1) is a physiological candidate gene for meat tenderness. This study aimed to identify the association of single nucleotide polymorphism (SNP) markers in the CAPN1 gene with the tenderness of chicken breast meat from two Malaysian native and commercial broiler breed crosses. Ten, five months old native chickens and ten, 42 days commercial broilers were collected from the local market and breast muscles were removed two hours after slaughter, packed separately in plastic bags and kept at -20ºC for 24 h. The tenderness phenotype for all chickens’ breast meats was determined by Warner-Bratzler Shear Force (WBSF). Thawing and cooking losses were also measured in the same breast samples before using in WBSF determination. Polymerase chain reaction (PCR) was used to identify the previously reported C7198A and G9950A SNPs in the CAPN1 gene and assess their associations with meat tenderness in the two breeds. The broiler breast meat showed lower shear force values and lower thawing loss rates than the native chickens (p<0.05), whereas there were similar in the rates of cooking loss. The study confirms some previous results that the markers CAPN1 C7198A and G9950A were not significantly associated with the variation in meat tenderness in chickens. Therefore, further study is needed to confirm the functional molecular mechanism of these SNPs and evaluate their associations in different chicken populations.

Keywords: CAPNl, chicken, meat tenderness, meat quality, SNPs.

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Authors: Cherry Dhiman, Ayushi Paliwal, Mohd. Shahid Khan, M. N. Reddy, Vinay Gupta, Monika Tomar

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The laser based high resolution spectroscopic experimental techniques such as Laser Induced Breakdown Spectroscopy (LIBS), Rotating Disk Electrode Optical Emission spectroscopy (RDE-OES) and Surface Plasmon Resonance (SPR) have been used for the study of composition and degradation analysis of used engine oils. Engine oils are mainly composed of aliphatic and aromatics compounds and its soot contains hazardous components in the form of fine, coarse and ultrafine particles consisting of wear metal elements. Such coarse particulates matter (PM) and toxic elements are extremely dangerous for human health that can cause respiratory and genetic disorder in humans. The combustible soot from thermal power plants, industry, aircrafts, ships and vehicles can lead to the environmental and climate destabilization. It contributes towards global pollution for land, water, air and global warming for environment. The detection of such toxicants in the form of elemental analysis is a very serious issue for the waste material management of various organic, inorganic hydrocarbons and radioactive waste elements. In view of such important points, the current study on used engine oils was performed. The fundamental characterization of engine oils was conducted by measuring water content and kinematic viscosity test that proves the crude analysis of the degradation of used engine oils samples. The microscopic quantitative and qualitative analysis was presented by RDE-OES technique which confirms the presence of elemental impurities of Pb, Al, Cu, Si, Fe, Cr, Na and Ba lines for used waste engine oil samples in few ppm. The presence of such elemental impurities was confirmed by LIBS spectral analysis at various transition levels of atomic line. The recorded transition line of Pb confirms the maximum degradation which was found in used engine oil sample no. 3 and 4. Apart from the basic tests, the calculations for dielectric constants and refractive index of the engine oils were performed via SPR analysis.

Keywords: Laser induced breakdown spectroscopy, rotating disk electrode optical emission spectroscopy, surface plasmon resonance, ICCD spectrometer, Nd:YAG laser, engine oil.

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