The walking of a humanoid robot needs to be robust enough in order to maintain balance in a dynamic environment especially on uneven terrain. A walking model based on multi-sensor is proposed for a Robotis DARwIn-OP robot named as Leman. Two force sensitive resistor (FSRs) on both feet equipped to Leman to estimate the zero moment point (ZMP) alongside with accelerometer and gyrosensor embedded in the body for body state estimation. The results show that the FSRs can successfully detect the unbalanced walking event if the protuberance exists on the floor surface and the accelerometer and gyrosensor (Inertial Measurement Unit, IMU) data are recorded to tune the balancing parameter in the model.
This paper deals with the analysis of different Fuzzy membership type performance for Extended Kalman Filter (EKF) based mobile robot navigation. EKF is known to be incompetent in non-Gaussian noise condition and therefore the technique alone is not sufficient to provide solution. Motivated by this shortcoming, a Fuzzy based EKF is proposed in this paper. Three membership types are considered which includes the triangular, trapezoidal and Gaussian membership types to determine the best estimation results for mobile robot and landmarks locations. Minimal rule design and configuration are also other aspects being considered for analysis purposes. The simulation results suggest that the Gaussian memberships surpassed other membership type in providing the best solution in mobile robot navigation.
The water flow-like algorithm (WFA) is a relatively new metaheuristic algorithm, which has shown good solution for the Travelling Salesman Problem (TSP) and is comparable to state of the art results. The basic WFA for TSP uses a 2-opt searching method to decide a water flow splitting decision. Previous algorithms, such as the Ant Colony System for the TSP, has shown that using k-opt (k>2) improves the solution, but increases its complexity exponentially. Therefore, this paper aims to present the performance of the WFA-TSP using 3-opt and 4-opt, respectively, compare them with the basic WFA-TSP using 2-opt and the state of the art algorithms. The algorithms are evaluated using 16 benchmarks TSP datasets. The experimental results show that the proposed WFA-TSP-4opt outperforms in solution quality compare with others, due to its capacity of more exploration and less convergence.
K-Means is an unsupervised method partitions the input space into clusters. K-Means algorithm has a weakness of detecting outliers, which have it available in many variations research fields. A decade ago, Rough Sets Theory (RST) has been used to solve the problem of clustering partition. Specifically, Rough K-Means (RKM) is a one of the powerful hybrid algorithm, which has it, has various extension versions. However, with respect of the ideas of existing rough clustering algorithms, a suitable method to detect outliers is much needed now. In this paper, we propose an effective method to detect local outliers in rough clustering. The Local Outlier Factor (LOF) method in rough clustering improves the quality of the cluster partition. The improved algorithm increased the level of clusters quality. An existing algorithm version, the π Rough K-Means (π RKM) tested in the study. Finally, the effectiveness of the algorithm performance is demonstrated based on synthetic and real datasets.
Blood cancer is an umbrella term for cancers that affect the blood, bone marrow and lymphatic system. There are three main groups of blood cancer: leukemia, lymphoma and myeloma. Some types are more common than others. In this paper, a new image transform based on geometric mean properties of integral values in both horizontal and vertical image directions is proposed for leukemia cancer cell classification. Available classification methods using the classical feature extraction methods which are sensitive to rotation and deformation of the blood cells. The new transform is based on geometric mean projection, which —unlike other image transforms, such as Radon transform— is not considered all signals in an image with the same signal acquisition rate. Instead, it is general and thus applicable to all capturing signal functions to achieve sufficient invariant features. The geometric mean projection transforms (GMPT) guarantees that the detector only extracts the highly informative information from the object to achieve an invariant feature vector for an accurate classification process. This method has been used as cancer cell identification using microscopic Imagery analysis in this study. Dissimilarity metric calculation and shape analysis by using image transform has been used to extract the feature vectors of the imagery. Then, the accumulated feature vectors have been classified to different classes by using artificial neural network (ANN). The proposed technique has been evaluated in the standard images sourced from USIM, Malaysia. The evaluation results indicate the robustness of the technique in different types of images available in the dataset.
Visual Simultaneous Localization and Mapping (vSLAM) system is widely used by autonomous mobile robots. Most vSLAM systems use cameras to analyze surrounding environment and to build maps for autonomous navigation. For a robot to perform intelligent tasks, the built map should be accurate. Landmark features are crucial elements for mapping and path planning. In the vSLAM literature, loop closure detection is a very important process for enhancing the robustness of the vSLAM algorithms. The most widely used algorithms for loop closure detection use a single descriptor. However, the performance of the single descriptors appears to worsen as the map keeps growing. One possible solution to this problem is to use multiple descriptors and combine them as in Naive and linear combinations. These approaches, however, have weaknesses in recognizing the correct locations due to overfitting and highbias, which hinder the generalization performance. This paper proposes the usage of ensemble learning to combine the predictions of multiple Bayesian filter models which make more accurate prediction than individual models. The proposed approach is validated on three public datasets; namely, Lip6 Indoor, Lip6 Outdoor and City Centre. The results show that the proposed ensemble algorithm significantly outperforms the single approaches with a recall of 80%, 97% and 87%, with 100% precision on the three datasets, and outperforms the Naive approach and the existing loop closure detection algorithms.
In this study, oil palm fruit bunch fiber (OPEFB) was used as a secondary filler in HDPE/clay nanocomposites. The composites were prepared by melt compounding, containing high density polyethylene (HDPE), OPEFB fibers, Maleic anhydride grafted polyethylene (MAPE) and four different clay loading (3, 5, 7 and 10 PE nanoclay masterbatch pellets per hundred HDPE pellets). Four OPEFB sizes (180 μm, 250 μm, 300 μm and 355 μm) were added in the composites to investigate its effects on the fracture toughness and impact strength. Fracture toughness of the composites was determined according to ASTM D5045 and single edge notch bending (SENB) was employed during the test while impact tests were performed according to ASTM D256. The effects of alkali treatment were also investigated in this study. The result indicates that the fracture toughness slightly increased as clay loading increased. The highest value of fracture toughness was 0.47 and 1.06 MPa.m1/2 at 5 phr for both types of composites. The presence of OPEFB fiber as a secondary filler in the matrix indicates significant enhancement of fracture toughness up to 133%. However, its impact strength seems to deteriorate with the presence of OPEFB fiber.
This study focuses on examining the influence of post weld impact treatment (PWIT) using Pneumatic Impact Treatment (PIT) for spot welded joint on mechanical properties and fatigue failure. PWIT is one of the methods for improving mechanical properties and fatigue strength of welded joints. One of the versatile techniques of PWIT used for this study is PIT. The material investigated in this study was carbon steel with welded single lap shear joint with the constant thickness of 1.2mm. All the welded samples were later performing the tensile shear test, hardness test, and fatigue test. The tensile shear test was conducted on the spot welded both treated and untreated samples using crosshead speed of 2 mm/ min, while hardness test was performed using 1kgf load via Vickers hardness indenter. Fatigue test was conducted using R=0.1 and frequency of 10 Hz. The effects of PIT on tensile-shear properties, hardness, and fatigue failure were evaluated. It was found that the implementation of PIT has increased tensile shear and hardness significantly and prolonged lifetime of spot welded joint.
Post Weld Impact Treatment (PWIT) is necessary in order to improve the tensile shear and hardness strengths on the welded joints of spot welding process. PWIT can be performed via Low Blow Impact Treatment (LBIT), which is the main focus in this research. In this present study, two plates of low carbon steel (LCS) with dimensions of 110 mm × 45 mm × 1.2 mm underwent a resistance spot welding. All welded samples were later tested for their mechanical properties by performing the tensile-shear, hardness test and qualitative analysis. Tensile shear test was conducted on the spot welded area for both treated and untreated samples using crosshead speed of 2 mm/min, while hardness test was performed using 1 kgf load Vickers hardness indenter. The effects of LBIT on tensile-shear properties, hardness and fatigue strength were evaluated and it was found that the implementation of LBIT increased the tensile shear strength, fatigue strength and hardness on the welded joint significantly.
High uncertainties in aerosol radiative forcing (ARF) arise from inaccurate estimation for aerosol optical depth (AOD) as an input parameter into Santa Barbara Discrete Ordinate Radiative Transfer (SBDART) model. Influence of AOD in ARF at the top of atmosphere (TOA) and surface over Kuching from 2011 until 2015 was investigated using Moderate Resolution Imaging Spectroradiometer (MODIS). Multi plane regression technique was used to retrieve AOD from MODIS (AODMODIS) by using different statistics (mean and standard deviation (MODISµ±σ) and relative absolute error (MODISRAE) for accuracy assessment in spatial averaging and compared with Aerosol Robotic Network (AERONET). The relationship between AODMODIS and AOD from AERONET (AODAERONET) showed R2 value for MODISµ±σ and MODISRAE is 0.906 and 0.932, respectively. AODMODIS over Kuching tends to underestimate AOD during low variations and overestimate AOD when aerosol loading is higher. The retrieval of AODMODIS was used as an input parameter into SBDART for ARF estimation and compared with ARF from AERONET. When using AODMODIS from MODISµ±σ, the ARF at TOA was between -5.95 Wm-2 and 0.89 Wm-2 and at the surface was from -389.7 Wm-2 and -31.4 Wm-2 while for MODISRAE, ARF value at the surface was from -392.3 Wm-2 and -27.3 Wm-2 while at TOA was between -5.89 Wm-2 and 0.98 Wm-2. Average ARF value within the atmosphere for both MODISµ±σ and MODISRAE were 151.6 Wm-2 and 130.4 Wm-2, respectively. There is a poor relationship between the SBDART and AERONET for MODISµ±σ, where R2 is 0.33, while strong relationship is observed for MODISRAE with R2 value at 0.724.
Crowdsourcing introduces new perspectives in innovation, allowing for new products and services to shift away from the traditional manufacture-centric model to a more user-centric one. In order for businesses to reap the benefits of open innovation, it is necessary to understand the factors that motivate ideators to contribute valuable ideas. Equally, there is an urgency to identify the challenges faced by ideators in crowdsourcing for open innovation to retain the participants of crowdsourcing communities. This paper presents a structured review to address the aforementioned issues. Our findings reveal that the intrinsic factors that drive participation in open innovation are related to the learning experience that results from sharing ideas. Extrinsic factors like social motivation are frequently mentioned in different studies. This study also highlights the need for organisations to develop strategies for interacting with their contributors in order to sustain their participation and idea contribution. In conclusion, this paper can serve as a guideline for practitioners to improve crowdsourcing platforms with the inclusion of important motivational features. It can also serve as reference for organisations for formulating policies to regulate idea contribution.
The increasing adoption of social media is a viable means in crowdsourcing. It can facilitate the connectivity of collaboration between different organisations, people and society to produce innovative and cost-effective solutions to many problems. Social media have opened up unprecedented new possibilities of engaging the public in meaningful ways through crowdsourcing. However, the growing number of security and privacy issues in social media may weaken the efficacy of crowdsourcing. This study aims to provide a basic understanding of security and privacy issues in line with the growth of crowdsourcing using social media platforms. This study also illustrates how crowdsourcing and social media data can lead to security and privacy issues in different environments. Lastly, this study proposes future works that may serve as direction for scholars to explore security and privacy in crowdsourcing through social media platforms. Secondary sources obtained from journals, conference papers, industry reports and books were reviewed to gather information.
Crowdsourcing has changed the way people conduct business. It provides access to work, and employers can source for the best talent, at the best price, with the shortest turnaround time. Research so far has focussed on crowdsourcing implementation. Hence, there is a need to conduct research that can contribute towards crowdsourcing sustainability. Thus, the objectives of this paper are to identify current practices of crowdsourcing in Malaysia and the challenges that face it. A conceptual model for crowdsourcing sustainability ecosystem is then proposed. This study adopted the case-study approach. Two crowdsourcing platforms were examined in the case study. Two techniques were used to obtain the data: observation and interview. Observation was carried out to observe how the crowdsourcing platforms worked. The interviews helped to uncover current practices, challenges in using crowdsourcing and identification of sustainability factors. It is hoped that the proposed conceptual model will facilitate better planning of the ecosystem supporting crowdsourcing and ensure sustainable growth for crowdsourcing. Future research into crowdsourcing can test the proposed conceptual model to validate its components.
Crowdsourcing is an initiative implemented by the Malaysian government to support its National Key Result Area (NKRA) agenda to improve the lives of citizens with low household income in the B40 group. Crowdsourcing activities are done on mobile crowdsourcing platforms that enable workers to perform micro tasks at any time for a fixed payment. However, without active and constant participation from the crowd, this initiative might not be successful. This paper describes a preliminary study in identifying motivation factors for participating in mobile crowdsourcing platforms. This study identified intrinsic and extrinsic motivation factors that can attract crowds to participate in mobile crowdsourcing platforms. Technology efficacy factors that interlink with motivation factors were also identified in this study. The preliminary study employed the qualitative method where in-depth interviews were conducted among 30 crowdsourcing participants in Peninsular Malaysia. The findings of this study are the basis for a motivation model that can attract crowdworkers from among the B40 group of household-income earners to participate in crowdsourcing to procure and perform available micro-tasks. The findings will also help improvise mobile platforms for crowdsourcing.
A full description of a new reading chart in Malay language, the Buari-Chen Malay Reading Chart (BCMRC) is described. Internal and external comparisons of BCMRC are also reported. BCMRC comprised four reading sets with contextual sentence (CS1 and CS2) and random words (RW1 and RW2) designs. A total of 14 prints, ranging from 1.3LogMAR to 0.0LogMAR in 0.1LogMAR steps (equivalent to 8 M to 0.4 M) were printed in high contrast Arial font. CS1, CS2, RW1 and RW2 were presented in random order to the participants for internal comparison. The reading was evaluated aloud with clear pronunciation (errors were recorded). Maximum reading speed (MRS) was reported in words per minute. The external comparison involved two standard English reading charts [MNread acuity chart (MNread) and Bailey-Lovie words reading chart (Bailey-Lovie)]. The internal and external comparisons were analysed using the intra-class correlation coefficient (ICC) and Cronbach’s alpha (α) respectively. Contextual sentence set (ICC=0.82) and random word set (ICC=0.85) exhibited good reliability in our internal comparison. The external comparison showed acceptable reliability for both MNread (α=0.76) and Bailey-Lovie (α=0.80). BCMRC sets with similar features could be used interchangeably to monitor clinical progress in visual rehabilitation. BCMRC was comparable with MNread and Bailey-Lovie reading charts.
This article aims to quantify the colour discrimination ability by using Total error scores (TES) to categorise colour discrimination level into superior, average or inferior levels under three different types of light sources, with different spectral power distribution. Colour discrimination was investigated using Farnsworth-Munsell 100 hues and compared upon three light sources: compact fluorescent light (CFL), fluorescent light (FL) and light emitting diode (LED). Total error score calculated and pattern of colour caps misplacement plotted used the web-based scoring method (http://www.torok.info/colorvision/fm100. htm). Total error score (TES) for three types of light sources (TES for LED 58.00 ± 18.67, FL 80.00 ± 19.27 and CFL 127.25 ± 28.02) were significantly different [One-way ANOVA (F=9.98, P
The purpose of this study was to develop a simple, economical but efficient procedure to collect illuminance data in quantifying interior lighting. This study was carried out in 3.8 m × 2.9 m × 3.0 m controlled experimental room. Three approaches to measure illuminance level were examined: (1) rowto-row; (2) column-to-column; and (3) zig-zag direction. A pre-determined 34 measurement points was used for all the three approaches. The duration required to complete the illuminance data measurement was recorded in minutes. There was a statistically significant difference in the total time measured to complete the illuminance data measurement in three different approaches (F(2, 4) = 23266.81, p
This study was conducted to investigate mitochondrial, nuclear chromatin and cytoskeletal organisation of vitrified embryos based on timing of the first zygotic cleavage. Embryos were retrieved from superovulated ICR mice, 28 hours after hCG injection. Two-cell stage embryos were categorised as earlycleaving (EC), while zygotes with 2-pronuclei as late-cleaving (LC) embryos. Embryos were cultured overnight in M16 medium supplemented with 3% bovine serum albumin (BSA) in carbon dioxide incubator. After 20 hours, the embryos were vitrified for one hour and warmed to room temperature. They were then fixed and immunostained to visualise distribution and intensity of mitochondria, nuclear chromatin and cytoskeleton. Finally, the embryos were mounted on glass slides and examined under a Confocal Laser Scanning Microscope (CLSM). Fluorescence intensities were analysed using LAS-AF-Lite Software. Results showed that EC embryos had significantly higher mitochondria (39.22 ± 12.50 versus 35.42 ± 14.61 pixel, p
Cryopreservation by vitrification has been widely used in Assisted Reproductive Technology (ART) to preserve embryos for an extended period of time. However, the effect of vitrification on development of the embryos is lacking. Therefore, understanding on vitrification effects on embryonic proteins, especially those involved in preimplantation development is crucial to provide high quality embryos for further usage. In this study, XIAP and S6K1 protein expressions following vitrification was investigated, since they have been implicated in diverse cellular processes including cell growth, migration, proliferation, differentiation, survival and development of preimplantation embryos via the PI3K pathway. Embryos were obtained from superovulated female ICR mice which were mated with fertile males. The embryos were harvested at the 2-cell stage and cultured until blastocyst stage. Blastocysts were then vitrified in ESF40 cryoprotectant. Western blot was carried out to determine the expression of XIAP and S6K1 proteins. The results showed the expression of XIAP and S6K1 significantly decreased in vitrified blastocyst compared to the control. This indicates that blastocyst vitrification may impact developmental competence through the activation of apoptotic pathways.
Kenaf fibre is one of the natural fibers that has received much attention of many researchers because of its good properties and flexible use. Kenaf fibre composites have been proposed as interior building materials. In this study, the recycling effect on the kenaf PVC wall panel is focused. The main objective of this study is to determine the mechanical properties of different types of kenaf PVC wall panels. The samples were formulated based on the first and third recycling process. The specimens were subjected to several types of tests, namely, tensile, izod impact, flexural and hardness based on ASTM D3039, ASTM D256, ASTM D7264 and ASTM D785, respectively. The results indicate that the mechanical properties of the third recycled kenaf PVC wall panel product is better than the virgin and first recycled specimen. This shows that the recycling process enhances the mechanical properties of the product. On the other hand, the hardness of the specimen decreases after first recycling due to the reheating effect.