Volume 36, Issue 2 (Full Volume)

 

THIS IS OUR SPECIAL ISSUE :
COMPUTER GRAPHICS AND SCIENTIFIC VISUALIZATION.

ORIGINAL ARTICLES
Autonomous Tawaf Crowd Simulation
Ahmad Zakwan Azizul Fata, Mohd Shafry Mohd Rahim, Sarudin Kari (p.1)

Fuzzy Soft Shadow in Augmented Reality System
- Hoshang Kolivand, Mohd Shahrizal Sunar, Ismahafezi Ismail & Mahyar Kolivand (p.8)
Primitives Penetration Depth Computation using Dynamic Pivot Point Technique
Hamzah Asyrani Sulaiman & Abdullah Bade (p.19)
Hybrid Federated Data Warehouse Integration Model: Implementation in Mud Crabs Case Study
- Mustafa Man, W. Aezwani W.A. Bakar, Noraida Hj. Ali & Masita Abd. Jalil (p.28)

Part-Body Detection Framework for People Detection using Sliced HOG Descriptors
- Ahmad Sani, Mohd Daud Kasmuni, Mahardhika Candra Prasetyahadi, Mohd Shafry Mohd Rahim & Mohd Shahrizal Sunar (p.39)

 

Originally Submitted in 2015. Published Online in 2016.

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AUTONOMOUS TAWAF CROWD SIMULATION

Ahmad Zakwan Azizul Fata, Mohd Shafry Mohd Rahim, Sarudin Kari

MaGIC-X (Media and Games Innonovation Centre of Excellence
UTM-IRDA Digital Media Centre
Universiti Teknologi Malaysia
Johor, Malaysia
Zakwan.fata@gmail.com, shafryr@utm.my, sarudin@utm.my

ABSTRACT. One of the most famous approaches to simulate a large density crowd is by applying the social force model. This model can be successfully used to simulate agents’ movement in real-world scenarios realistically. Nevertheless, this is very simple and not suitable to simulate a complex pedestrian flow movement. Hence, this research proposes a new novel model for simulating the pilgrims’ movements circling the Kaabah (Tawaf). These rituals are complex yet unique, due to its capacity, density, and various demographics backgrounds of the agents (pilgrims). It also had a certain set of rules and regulations that must be followed by the agents. Due to these rules, the Tawafcan introduce irregularities in the motion flow around the Kaabah. In order to make the simulation realistically, each agent will be assigned with different attributes such as; age, gender and intention outlook. The three parameters mentioned above, are the main problems that need to be solved in this research in order to simulate a better crowd simulation than previous studies. The findings of this research will contribute greatly for Hajj management in term of controlling and optimizing the flow of pilgrims during Tawaf especially in the Hajj season.

KEYWORDS. Autonomous Agents; Crowd Simulation; Hajj.

 

REFERENCES

  • Curtis S., Zafar B., Guy S. J. & Manocha D. 2011. Virtual Tawaf: A Case Study in Simulating the Behavior of Dense, Heterogeneous Crowds. IEEE International Conference on Computer Vision Workshops (ICCV Workshops) 2011.
  • Hughes, R., Ondrej, J. & Dingliana, J. 2014. Holonomic Collision Avoidance for Virtual Crowds. Proceedings of the Eurographics/ACM SIGGRAPH Symposium on Computer Animation 2014, pp. 1–8.
  • Sarmady S., Haron F. & Talib A. Z. 2011. A cellular automata model for circular movements of pedestrians during Tawaf. Simulation Modelling Practice and Theory. Elsevier.
  • Zainuddin Z., Thinakaran K. & Abu-Sulyman I. M. 2010. Simulating the Circumambulation of the Ka’aba using SimWalk. European Journal of Scientific Research, 38(3): 454-464.

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FUZZY SOFT SHADOW IN AUGMENTED REALITY SYSTEMS

Hoshang Kolivand, Mohd Shahrizal Sunar, Ismahafezi Ismail, Mahyar Kolivand

MaGIC-X (Media and Games Innovation Centre of Excellence)
UTM-IRDA Digital Media Centre
Universiti Teknologi Malaysia
81310 Skudai, Johor, Malaysia.

ABSTRACT. Realistic soft shadows in Augmented Reality (AR) is a fascinating topic in computer graphics. Many researchers are involved to have a significant improvement on this demand. In this paper, we have presented a new technique to produce soft shadows using one of the well-known methods in mathematics called Fuzzy Logic. Fuzzy logic is taken into account to generate the realistic soft shadows in AR. The wide light source is split into some parts that each of them plays the rule of a single light source. The desired soft shadow is generated by splitting the wide light source into multiple parts and considering each part as a single light source. The method which we called Fuzzy Soft Shadow is employed in AR to enhance the quality of semi-soft shadows and soft shadows.

KEYWORDS. Soft Shadows, Augmented Reality, Fuzzy logic

 

REFERENCES

  • Aittala, M. 2010. Inverse lighting and photorealistic rendering for augmented reality. The Visual Computer, 26(6-8):669–678.
  • Annen, T., Dong, A., Mertens, T., Bekaert, P., Seidel, H-P. & Kautz, J. 2008. Real-time, allfrequency shadows in dynamic scenes. ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH 2008), 27(3):1–34.
  • Boulanger, K. 2008. Real-time realistic rendering of nature scenes with dynamic lighting. Ph.D Thesis, University of Central Florida.
  • Crown. F. 1977. Shadow algorithms for computer graphics. Computer Graphics, 11(2):242–247.
  • Debevec, P. 2004. Image-based lighting. IEEE Computer Graphics and Applications, 22:26–34.
  • Haller, M., Drab, S. & Hartmann, W. 2003. A real-time shadow approach for an augmented reality application using shadow volumes. In Proceedings of VRST 2003, pp. 56–65.
  • Hensley, J., Scheuermann, T., Coombe, G., Singh, M. & Lastra, A. 2005. Fast summed-area table generation and its applications. Comput. Graph. Forum, 24(3):547–555.
  • Jacobs, K. & Loscos, C. 2004. Classification of illumination methods for mixed reality. In Eurographics, State-of-the-Art Report.
  • Jacobs, K., Nahmias, J-D., Angus, C., Reche, A., Loscos, C. & Steed, A.2005. Automatic generation of consistent shadows for augmented reality. Proceedings of Graphics Interface 2005, pp. 113–120, 2005.
  • Jensen, B. F., Laursen, J. S., Madsen, J. B. & Pedersen, T. W. 2009. Simplifying real time light source tracking and credible shadow generation for augmented reality. Institute for Media Technology, Aalborg University.
  • Kolivand, H. & Sunar, M. 2013a. A survey of shadow volume algorithms in computer graphics. IETE Technical Review, 30(1):38-46.
  • Kolivand, H. & Sunar, M. 2013b. Covering photometric properties of outdoor components with the effects of sky color in mixed reality. Multimedia Tools and Applications, pp.1–20.
  • Kolivand, H. & Sunar, M. S. 2014. Realistic Real-Time Outdoor Rendering in Augmented Reality. PLoS ONE, 9(9): e108334. doi:10.1371/journal.pone.0108334
  • Madsen, C. B. & Lal, B. B. 2013. Estimating outdoor illumination conditions based on detection of dynamic shadows. Computer Vision, Imaging and Computer Graphics. Theory and Applications, Springer.
  • Madsen, C. B. & Nielsen, M. 2008. Towards probe-less augmented reality. A Position Paper, Computer Vision and Media Technology Lab. Aalborg University, Aalborg, Denmark.
  • Nowrouzezahrai, D., Geiger, S., Mitchell, K., Sumner, R., Jarosz, W. & Gross, M. 2011. Light factorization for mixed-frequency shadows in augmented reality. 10th IEEE International Symposium on Mixed and Augmented Reality (ISMAR), pp. 173–179.
  • Ro ̈nnberg, S. 2004. Real-time rendering of natural illumination. Citeseer.
  • Williams, L. 1978. Casting curved shadows on curved surfaces. SIGGRAPH ’78, 12(3): 270- 274 1978.
  • Xing, G. Y., Zhou, X. H., Liu, Y. L., Qin, X. Y. & Peng. Q.S. 2013. Online illumination estimation of outdoor scenes based on videos containing no shadow area. Science China Information Sciences, 56(3):1–11.
  • Yan, F. 2008. Estimation of light source environment for illumination consistency of augmented reality. In First International Congress on Image and Signal Processing, 3:771–775.
  • Zadeh, L. A. 1965. Fuzzy sets. Information and control, 8(3):338–353.

 

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PRIMITIVES PENETRATION DEPTH COMPUTATION USING DYNAMIC PIVOT POINT TECHNIQUE

Hamzah Asyrani Sulaiman1*, Abdullah Bade2

1Universiti Teknikal Malaysia Melaka,
Durian Tunggal, Melaka, Malaysia
2Faculty of Science and Natural Resources,
Universiti Malaysia Sabah,
Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia.
*Email: h.a.sulaiman@ieee.org

ABSTRACT. Computing penetration depth between two or more polygons commonly described by most researchers as one of the high computational cost process. Major implementation required numbers of pre-processing function just to find the minimum penetrating depth between those penetrated objects or polygons. In this paper, we proposed a technique that manipulates the advantages of Dynamic Pivot Point into computing penetration depth between two or more objects. Comparing our proposed technique (DyOP-PD) with the well-known Lin-Canny technique, the conducted experiments proved that our proposed technique has achieved better efficiency. Overall time for DyOP-PD technique to compute penetration depth was significantly faster than the Lin-Canny PD technique (refer Figure 6.9). Our technique was faster than the prominent technique where the computational time significantly reduced, solved a larger fraction of problems, and produced better paths of penetration depth. The lowest results recorded from our simulation was in average at 10.22 milliseconds for DyOP PD and 21.33 milliseconds for Lin-Canny PD technique. The findings proved that DyOP-PD technique is robust to handle efficient, nearly accurate, and fast penetration depth detection compared to Lin-Canny-PD technique.

KEYWORDS. Collision detection, penetration depth, virtual environment

 

REFERENCES

  • Bergen, G. V D. 2001. Proximity Queries and Penetration Depth Computation on 3D Game Objects, in Game Developers Conference.
  • Kim,Y. J., Otaduy, M. A., M. C. Lin & D. Manocha. 2003. Fast Penetration Depth Estimation Using Rasterization Hardware And Hierarchical Refinement. Presented at the Proceedings of The Nineteenth Annual Symposium On Computational Geometry, San Diego, California, USA.
  • Redon, S., Kheddar, A. & Coquillart. S., 2002. Fast Continuous Collision Detection between Rigid Bodies. Computer Graphics Forum, 21: 279-287.
  • Shengzheng, W. & Jie, Y. 2009. Efficient Collision Detection for Soft Tissue Simulation In A Surgical Planning System. Computer-Aided Design and Computer Graphics, 2009. CAD/Graphics ’09. 11th IEEE International Conference on, 49-53.
  • Stephane, R. & Lin, M. C. 2006. A Fast Method for Local Penetration Depth Computation. Journal of Graphics Tools.
  • Sulaiman, H. A., Othman, M. A., Ismail, M. M, Misran, M. H., Said, M. A., B. M., Ramlee, R. A. 2013. Quad Separation Algorithm for Bounding-Volume Hierarchies Construction In Virtual
  • Environment Application. Journal of Next Generation Information Technology, 4: 63-73
  • Zhang, L., Kim Y. J., Varadhan, G. & Manocha, D. 2007. Generalized Penetration Depth Computation. Computer-Aided Design, 39(8): 625-638.
  • Zhang, X., Kim, Y. J. & Manocha, D. 2014. Continuous Penetration Depth. Computer-Aided Design, 46: 3-13

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HYBRID FEDERATED DATA WAREHOUSE INTEGRATION MODEL: IMPLEMENTATION IN MUD CRABS CASE STUDY

Mustafa Man, W. Aezwani W.A. Bakar, Noraida Hj. Ali and Masita Abd. Jalil

Department of Computer Science
School of Informatics and Applied Mathematics
Universiti Malaysia Terengganu
21030 Kuala Terengganu, Terengganu.
mustafaman@umt.edu.my, beny2194@yahoo.com, aida@umt.edu.my, masita@umt.edu.my

ABSTRACT. Data integration is considered as one of the hot issues to be solved especially in integrating unstructured data with multiple types and formats. This paper introduces a new model for integrating multiple types of heterogeneous data applying to mud crabs case study in Setiu Wetland (SW). The Hybrid Federated Data Warehouse (HyFeDWare) model combines two approaches which are Data Warehouse and Federated Database. Simulation result shows that the processing time for integration of unstructured biodiversity data of mud crabs are lesser than 2 seconds for 12 rows of 7 MB data. This model generally could be used to integrate any types and format of data in distributed environment.

KEYWORDS. Data Integration, Data Warehouse, Federated database, Distributed Environment.

 

REFERENCES

  • Aezwani, W.A.B. et al., 2010,”SIDIF: Location based technique as a determinant of effectiveness and efficiency in artificial reefs development project.”Information Technology (ITSim), 2010 International Symposium in. Vol. 2. IEEE,.
  • Bowen, J. (2012). Getting Started with Talend Open Studio for Data Integration. Packt Publishing Ltd.
  • Catriel, B. & Milo, T. 1999. Schemas for Integration and Translation of Structured and SemiStructured Data. Database Theory—ICDT’99. Springer Berlin Heidelberg, 296-313.
  • Christine, P. and Spaccapietra. S., 1998, “Issues and approaches of database integration.” Communications of the ACM 41.5es : 166-178.
  • Greenwald, R., Stackowiak, R. & Stern, J. (2013). Oracle Essentials: Oracle Database 12c. “O’Reilly Media, Inc.”.
  • Haider, S., Ballester, B., Smedley, D., Zhang, J., Rice, P. & Kasprzyk, A. (2009). BioMart Central Portal—unified access to biological data. Nucleic acids research, 37(suppl 2), W23-W27.
  • Hossain, M., Harari, N., Semere, D., Mårtensson, P., Ng, A. & Andersson, M. (2012). Integrated modeling and application of standardized data schema. In5th Swedish Production Symposium,(SPS12), 6-8 November, 2012, Linköping, Sweden. The Swedish Production Academy.
  • Ikhwanuddin, M. et al., 2012, “Improved hatchery‐rearing techniques for juvenile production of blue swimming crab, Portunus pelagicus (Linnaeus, 1758).”Aquaculture Research 43.9 : 1251 -1259.
  • Joan Bader, C. H., Razo, J., Madnick, S. & Siegel, M. (1999). An analysis of data standardization across a capital markets/financial services firm.
  • Jose, Z., Pardillo, J. & Trujillo, J. 2009. A UML Profile for the Conceptual Modeling Of DataMining With Time-Series In Data Warehouses. Information and Software Technology 51, 6: 977-992.
  • Kasprzyk, A. (2011). BioMart: driving a paradigm change in biological data management. Database, 2011, bar049.
  • Ming Shuai, W. and Fu. X. F., 2014, “A Method of Heterogeneous Data Integration Based on SOA.” Applied Mechanics and Materials 536 : 494-498.
  • Mustafa, M. et al. 2011, “Designing multiple types of spatial and non spatial databases integration model using formal specification approach.” Software Engineering (MySEC), 2011 5th Malaysian Conference in. IEEE,.
  • Mustafa, M. et al. 2012, “Integration Model for Multiple Types of Spatial and Non Spatial Databases.” Signal Processing and Information Technology. Springer Berlin Heidelberg,. 95-101.
  • Oracle (2013). Unstructured Data Management with Oracle Database 12c. Retrieved October 29, 2013 from http://www.oracle.com/technetwork/database/informationmanagement/unstructured-data-management-wp-12c-1896121.pdf
  • Roth, M. A. et al., 2002, “Information integration: A new generation of information technology.” IBM Systems Journal 41.4: 563-577.
  • Stehr, H., Duarte, J. M., Lappe, M., Bhak, J. & Bolser, D. M. (2010). PDBWiki: added value through community annotation of the Protein Data Bank.Database, 2010, baq009.

 

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PART-BODY DETECTION FRAMEWORK FOR PEOPLE DETECTION USING SLICED HOG DESCRIPTORS

Ahmad Sani, Mohd Daud Kasmuni, Mahardhika Candra Prasetyahadi, Mohd Shafry Mohd Rahim and Mohd Shahrizal Sunar

UTM-IRDA Digital Media Centre
Faculty of Computing
Universiti Teknologi Malaysia,
81310 Skudai, Johor-Malaysia

ABSTRACT. We investigate the possibility for using portions of Histograms of Oriented Gradients (HOG) descriptors in a part- based people detection framework. Instead of extracting descriptors from isolated or pre-cropped human parts, we slice the extracted HOG descriptor from whole windows into four, one slice per one human part. Support Vector Machines (SVMs) are used for classifying the slices and the outcome detections are handled by a finite-state machine where three detected parts means that one assumed person is in the window being scanned. Experiments were conducted for our detection framework and another conventional one that uses whole HOG descriptors using images from the INRIA Person Dataset, in which our framework achieved better; detecting 46/50 of occluded people comparing to 36/50 for the conventional framework. Moreover, we achieved less false positive detections of 80 windows comparing to 289 for the conventional framework.

KEYWORDS. People detection; object detection; histograms of oriented gradients; partbased detection framework

 

REFERENCES

  • Azizpour, H and Laptev, I, 2012 “Object Detection Using Strongly- Supervised Deformable Part Models,” in Computer Vision. vol. 7572, A. Fitzgibbon, S. Lazebnik, P. Perona, Y. Sato, and C.
  • Schmid, Eds., ed Berlin: Springer Berlin Heidelberg, pp. 836-849.
  • Dalal, N. and Triggs. B, 2005 “Histograms of oriented gradients for human detection,” in Conference on Computer Vision and Pattern Recognition San Diego, CA, pp. 886-893.
  • Ahmad Sani, Mohd Daud Kasmuni, Mahardhika Candra Prasetyahadi, Mohd Shafry Mohd Rahim and Mohd Shahrizal Sunar Felzenszwalb, F., McAllester, D., and Ramanan, D., 2008 “A discriminatively trained,
    multiscale, deformable part model,” in Computer Vision and Pattern Recognition, Anchorage, AKpp. 1 -8.
  • Linh, D., Buu, B., Vo, P. D., Tran, T. N. and Le, B. H., “Improved HOG Descriptors,” in 3rd International Conference on Knowledge and Systems Engineering, Hanoi, 2011, pp. 186-189.
  • Marin, J., Vazquez, D., Lopez, A. M., Amores, J and Kuncheva, L. I., 2014 “Occlusion Handling via Random Subspace Classifiers for Human Detection,” Transactions on Cybernetics, vol. 44, pp.342-354.
  • Mikolajczyk, K., Schmid, C., and Zisserman, A., 2004 “Human Detection Based on a Probabilistic Assembly of Robust Part Detectors,” in Computer Vision – ECCV 2004. vol. 3021, T. Pajdla and
  • J. Matas, Eds., ed Berlin: Springer, pp. 69-82.
  • Mikolajczyk, K., and Schmid, C., 2005 “A performance evaluation of local descriptors,” Pattern Analysis and Machine Intelligence, vol. 27, pp. 1615-1630.
  • Mohan, A., Papageorgiou, C., and Poggio, T., 2001 “Example-based object detection in images by components,” Transactions on Pattern Analysis and Machine Intelligence, vol. 23, pp. 349-361.
  • Oren, M., Papageorgiou, C., Sinha, P., Osuna, E., and Poggio, T., 1997 “Pedestrian detection using wavelet templates,” in Conference on Computer Vision and Pattern Recognition, San Juan, pp. 193-199.
  • Tang, S., Andriluka, M., and Schiele, B., 2013 “Detection and Tracking of Occluded People,” International Journal of Computer Vision, vol. 11263, pp. 1-12.
  • Viola, P. and Jones, m., 2001 “Rapid object detection using a boosted cascade of simple features,” in Conference on Computer Vision and Pattern Recognition, Kauai, pp. 511 -518.
  • Wang, X., Han, T. X., and Yan, S., 2009 “An HOG-LBP human detector with partial occlusion handling,” in 12th International Conference on Computer Vision, Kyoto, pp. 32-39.

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Volume 36, Issue 1 (Full Volume)

ORIGINAL ARTICLES

Assesment of Toxicity Level in Selected Heavy Metal in Volcanic Soils from Tawau, Sabah
– Mohamed Ali Yusof Mohd Husin, Hennie Fitria W. Soehady Erfen & Baba Musta (p.1)

Geomechanical Classification Scheme for Heterogeneous Crocker Formation in Kota Kinabalu, Sabah, Malaysia
– Ismail Abd Rahim (p.12)

Morphologies Changes during Pre- and Post- Southwest Season in Mantanani Besar Island, Kota Belud, Sabah
– Russsel Felix Koiting, Ejria Saleh, John Madin, Than Aung & Fazliana Mustajap (p. 21)

The Fruit Bats (Megachiroptera, Pteropodidae) From Bawakareng Mountain, South Sulawesi
– Ellena Yusti, Ibnu Maryanto & Bambang Suryobroto (p.33)

Classification and Quantification of Marine Debris at Teluk Likas, Sabah
– Farrah Anis Fazliatul Adnan, Rudy Kilip, Dazvieo Keniin & Carolyn Payus (p.44)

Originally Submitted in 2015. Published Online in 2016.

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ASSESSMENT OF TOXICITY LEVEL IN SELECTED HEAVY METAL IN VOLCANIC SOILS FROM TAWAU, SABAH.

Mohamed Ali Yusof Mohd Husin*, Hennie Fitria W. Soehady Erfen & Baba Musta

Faculty of Science & Natural Resources, Universiti Malaysia Sabah,
Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia.
*E-mail address: mohamedaliyusof@yahoo.com

ABSTRACT. Heavy metals are one of the serious pollutants in environment because its toxicity. Severe concentration of heavy metals can harm the plants, animals and even human. During the pedogenesis process, heavy metals from the parent rock are mobilized in soils and redistribute in to the environment. The objective of this paper is to study the concentration and toxicity level of selected heavy metals in volcanic soils around Tawau, Sabah. In this study 10 soil samples were collected from different sampling stations. The selection of soil
samples were based on the different type of volcanic rocks in the study area. The determination of concentration of heavy metals in soil samples were carried out using X-Ray Fluorescence (XRF) analysis. The result shows, the highest concentration is chromium with the average of 141 ppm followed by zinc with 112 ppm. The concentration of copper is 49 ppm, nickel 15 ppm, lead 8 ppm and arsenic 7 ppm. The soil samples is identified as polluted due to the elevated concentration of certain heavy metals when compared with the Sediment Quality Guidelines of US EPA. Chromium is regarded as heavily polluted agent while zinc, copper and arsenic indicated that the area is moderately polluted. Nickel and lead average concentration show no indication of pollution in the area. It is concluded that the combined source of heavy metals in the study area would be the parent materials of the soils and other anthropogenic effluent. From the study also, it is found out that pH value, organic matter and clay percentage has influenced the heavy metal concentration in volcanic soil in the study area.

KEYWORDS.  Heavy Metals, Tawau, Volcanic Soils, XRF.

 

REFERENCES

  • Alloway, B.J. 1995. Heavy Metals in Soils 2nd Edition. Chapman and Hall.
  • Alloway, B.J. 2008. Zinc in Soils and Crop Nutrition. International Zinc Association (IZA) & International Fertilizer Industry Association (IFA). BS 1377-1990. Methods of Test for Soils for Civil Engineering Purposes. London : British Standard Institution.
  • Baba, M., Hennie F.W.S.E. & Sanudin, T. 2008. Geochemical Characterization of Volcanic Soils From Tawau, Sabah. Geological Society of Malaysia, Bulletin 54.
  • Backer, D.E. & Chesnin, L. 1975. Chemical Monitoring of Soils For Environment Quality and Animal and Human Health. Adv. Agron. 27, 305–374.
  • Baker, D.E. & Senft, J.P. 1995. Copper. In Alloway B.J. (ed.) Heavy Metals in Soils 2nd Edition, pp. 179-205. Glasgow: Chapman and Hall.
  • Chen, Y.Y., Wang, J., Gao, W., Sun X.J. & Xu, S.Y. 2012. Comprehensive Analysis of Heavy Metals in Soils From Boashan District, Shanghai: a heavily industrialized area in China. Environmental Earth Science, Springer-Verlag.
  • Islam, M.R., Stuart, R., Risto, A.,Vesa, P. 2001. Mineralogical changes during intense chemical weathering of sedimentary rocks in Bangladesh. Journal of Earth Sciences
    20 (2002) 889-901.
  • Jenny, H. 1994. Factors of Soil Formation: A System of Quantitative Pedology. Dovers Publication, Inc.
  • Kirk, H.J.C. 1962. The Geology and Mineral Resources of Semporna Peninsula. North Borneo Geology Survey Department British Territories in Borneo 14. Sarawak Government Printing Office.
  • Kirk, H.J.C. 1968. The Igneous Rocks of Sarawak and Sabah. Geological Survey of Malaysia, Bulletin 5.
  • McGarth, S.P. 1995. Chromium and Nickel. In Alloway B.J. (ed.) Heavy Metals in Soils 2nd Edition, pp. 152-178. Glasgow: Chapman and Hall.
  • Matera, V., Le Hécho, I., Laboudigue, A., Thomas, P., Tellier, S. & Astruc, M. 2003. A Methodological Approach for The Identification of Arsenic Bearing Phases in Polluted Soils. Environmental Pollution 126 (2003) 51-64.
  • Mason, B. 1958. Principles of Geochemistry, 2nd Edition. Wiley.
  • Myung, C.J. 2008. Heavy Metal Concentrations in Soils and Factors Affecting Metal Uptake by Plants in The Vicinity of A Korean Cu-W Mine. Sensors 2008, 8, 2413-2423.
  • Norrish, K. & Hutton, J.T. 1969. An Accurate X-Ray Spectographic Method For The Analysis of A Wide Range of Geological Samples. Geochem. Et Cosmochim. Acta, 33, 431 -453.
  • Olade, M.A. 1987. Dispersion of Cadmium, Lead and Zinc in Soils and Sediments of a Humid Tropical Ecosystem in Nigeria. Lead, Mercury, Cadmium and Arsenic in The Environment, Scope. John Wiley & Sons Ltd.
  • Pekey, H. 2006. Heavy Metal Pollution Assessment in Sediments of The Izmit Bay, Turkey. Environmental Monitoring and Assessment, Springer 123:219-231.
    Perin, G., Bonardi, M., Fabris, R., Simoncini, B., Manente, S., Tosi, L. & Scotto, S. 1997. Heavy Metal Pollution in Central Venice Lagoon Bottom Sediments: Evaluation of Metal Bioavailability by Geochemical Speciation Procedure. Environmental Technology 18 593-604.
  • Prego, R. & Cobelo-Garcia, A. 2003. Twientieth Century Overview of Heavy Metals in The Galician Rias (NW Iberian Peninsular). Environmental Pollution, 121:425-425.
  • Sabri, A.W., Rasheed, K.A. & Kassim, T.I. 1993. Heavy Metal in The Water, Suspended Solids and Sediment of The River Tigris Impoundment At Samarra. Journal of Water Research, 27:1099-1103.
  • Saria, L., Takayuki, S. & Kentaro, M. 2006. Leaching of Heavy Metals in Acid Mine Drainage. Waste Management & Research, Vol. 24 No.2 134-140.
  • Sanudin, T. & Baba, M. 2007. Pengenalan Kepada Stratigrafi. Penerbit UMS, Kota Kinabalu, Sabah.
  • Schlotz, R. & Uhlig, S. 2006. Introduction to X-ray Flourescence Analysis (XRF). Bruker AXS GmbH, Karlruhe, West Germany.
  • Shan, W., Xinghui X., Chunye L., Xi, C. & Chuanhui, Z. 2010. Levels of Arsenic and Heavy Metals in The Rural Soils of Beijing and Their Changes Ove The Last Two Decades (1985-2008). Journal of Hazardous Materials, 179:860-868.
  • Sipos, P. 2004. Factors Affecting Heavy Metal Distribution in Forest Soils: Inherited Pedogenic Characteristics. Eurosoil 2004. Alvert-Ludwigs-Universitat Freiburg.

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GEOMECHANICAL CLASSIFICATION SCHEME FOR HETEROGENEOUS CROCKER FORMATION IN KOTA KINABALU, SABAH, MALAYSIA

Ismail Abd Rahim
Natural Disasters Research Centre, Faculty of Science and Natural Resources, Universiti
Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia
Phone: 088 320000 (5734/5999)
Fax: 088 435324
arismail@ums.edu.my


ABSTRACT
. Geomechanical classification scheme for heterogeneous Crocker Formation in Kota Kinabalu, Sabah has been proposed in 2009 and known as Modified Slope Mass Rating (M-SMR). M-SMR was used to characterize and to propose preliminary rock cut slope design such as slope stabilization and protection measures and recommendation levels for design model review and slope remapping by suitable engineering geologist or geotechnical
engineers. The ‘Lithological unit thickness’ approach, RQD method, weighted average of discontinuity set spacing, weighted average, statistical mode and new approach of adjustment factor (NAAF) methods were used to evaluate the parameters in M-SMR. The classes in MSMR scheme consists of class I (very good) to class VI (extremely bad). Local trimming, slope re-profiling, weep hole, horizontal drainage, concrete dentition or buttress, rock bolting or dowel, wire mesh or rope nets, reinforce shotcrete and benching are proposed slope stabilization and protection measures. Normal to detailed Design Model Review (DMR) and slope remapping are recommended to highly recommended by engineering geologist or geotechnical engineers to expert engineering geologist or geotechnical engineers for class I to class VI, respectively.

KEYWORDS: Geomechanical classification, Modified Slope Mass Rating (M-SMR), Crocker Formation, Kota Kinabalu, slope design.

REFERENCES

  • Anbalagan, R., Sharma, S. & Tarun, R. 1992. Rock mass stability evaluation using modified SMR approach. Proceeding of the Sixth National Symposium on Rock Mechanics, Bangalore, India, pp. 258-268.
  • Bieniawski, Z. T. 1989. Engineering Rock Mass Classifications. Wiley, New York, 248 p.
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  • Ismail Abd Rahim, Sanudin Tahir, Baba Musta & Shariff A. K. Omang. 2009b. Lithological unit thickness approach for determining Intact Rock Strength of slope forming rock material of Crocker Formation. Borneo Science, 25, pp. 23-31. ISSN 1394-4339.
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MORPHOLOGIES CHANGES DURING PRE- AND POST- SOUTHWEST SEASON IN MANTANANI BESAR ISLAND, KOTA BELUD, SABAH

Russel Felix Koiting*, Ejria Saleh, John Madin, Than Aung & Fazliana Mustajap

Borneo Marine Research Institute,
Universiti Malaysia Sabah, Jalan UMS, 88400 Kota Kinabalu, Sabah, Malaysia.
*Contact person: Emai: rfk_moon_2509@yahoo.com

ABSTRACT. Mantanani Besar Island is one of the community and tourism islands in the west coast of Sabah. It is inhabited by local Ubian people which stated that the island receiving major problem of erosion around the island. Ocean motion (waves and currents) and winds causes the erosion and together with seasonal monsoons change the intensity and formation of waves, winds and the periodic storms. These combinations intensified the geomorphic processes of erosion and accretion along the shoreline. Therefore, the objectives of this study are to determine the beach morphologies (beach profile, volume and angle) and sediment parameters during pre- and post- southwest monsoon (SWM). This study was conducted on May and November 2013 in order to see the beach changes done before and after the peak 2013 SWM (May to September). Beach profiles were measured at 5 stations around the island. Further measurements on beach volume and angle were calculated based on the beach profile readings. Sediment samples were collected at mid tide and analyzed the sediment parameters (mean, sorting, skewness and kurtosis). Results show most of the beach profile increase in post-SWM than in pre-SWM. Significant changes of the beach elevation were found at northern part of the island (st 4 and st 5). Beach volume increases in most of the station with a range from 2.71 to 9.19 while only st 3 experienced sediment loss with -0.75 Beach angle are also increase at most of the station (1 o) but significantly increase at st 5 (4.62o). Based on the sediment size analysis, mean values are decreasing shows the increase of energy condition. Most of the sediment are moderately sorted and positively skewness. The kurtosis value are vary indicates the presence of other source of sorting. The information gathered on this study is useful for the development along the beach and future management plan of the island.

KEYWORDS: beach profile and angle, sediment characteristics, shoreline changes, Mantanani Besar Island

REFERENCES

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  • Morphologies Changes during Pre- and Post- Southwest Season in Mantanani Besar Island, Kota Belud
  • Dora, G. U. Kumar, V. S. Johnson, G. Philip C. S. Vinayaraj, P. & Gowthaman, R. 2011. Textural characteristics of foreshore sediments along Karnataka shoreline, west coast of India. International Journal of Sediment Restoration, 26: 364 – 377.
  • Dora, G. U. Kumar, V. S. Johnson, G. Philip C. S. & Vinayaraj, P. 2012. Short-Term Observation ofBeach Dynamics Using Cross-Shore Profiles and Foreshore Sediment. Journal of Ocean Coastal Management, 67: 101 – 112.
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  • Friedman, G. M. 1962. On Sorting, Sorting Coefficients and the Log Normality of The Grain-Size Distribution of Sandstones. Journal of Geology, 70: 737 – 753.
  • Ganesh, B. Naidu, A. G. S. S. Rao, M. J. Karuna, T. K. & Avatharam, P. 2013. Studies on textural charateristics of sediments from Gosthani River Estuary-Bheemunipatnam, A. P., East Coast of India. Journal of Ind. Geophys. Union, 17: 139 – 151.
  • Jamil, T. Norsila, D. & Ashraf, A. 2009. Distribution of Sediment Characteristic in Kilim River Estuary During the Non-Moonsoon and Monsoon Season. pp 381-387. http://www.academia.edu/797941/Distribution_of_Sediment_Characteristic_in_Kilim_River_Estuary_during_the_Non-Monsoon_and_Monsoon_Season (Accessed on 16 November, 2013).
  • Kumar, G. AL.Ramanathan, & Rajkumar, K. 2010. Textural characteristics of the surface sediments of a Tropical mangrove ecosystem Gulf of Kachchh, Gujarat, India. Journal of Marine Science, 39: 415 – 422.
  • Malaysian Meteorological Department (MetMalaysia). 2013. Monsoon.
    http://www.met.gov.my/index.php?option=com_content&task=view&id=69&Itemid=160&lang =english (Accessed on 17 November 2013).
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THE FRUIT BATS (MEGACHIROPTERA, PTEROPODIDAE) FROM BAWAKARAENG MOUNTAIN, SOUTH SULAWESI

Ellena Yusti¹*, Ibnu Maryanto², Bambang Suryobroto³
¹Master Program in Animal Bioscience, Graduate School of Bogor Agricultural University,
Kampus IPB Darmaga, Bogor 16680, West Java, Indonesia
²Museum Zoologicum Bogoriense, Research Center for Biology, Indonesian Institute of
Sciences (LIPI), Jl.Raya Cibinong KM 47, Cibinong, Bogor, Indonesia
³Department of Animal Bioscience, Faculty of Mathematic and Natural Science Bogor
Agricultural University, Kampus IPB Darmaga, Bogor 16680, West Java, Indonesia
Corresponding author: yuellena@gmail.com

ABSTRACT. A study of fruit bats (Pteropodidae) was conducted in the mountain region of Bawakaraeng, Gowa and Sinjai, South Sulawesi from September to December 2013. This study aims to determine the fruit bats composition and diversity, habitat preferences and relation between bats individual captured with the moon phases. Ten species (265 individuals) of fruit bats were captured using standardized mist netting in five habitat types and elevations. Shannon-Wiener indices were highest in mixed garden (1453 m asl) and lowest in pine forest (1545 m asl), with the highest evenness in mixed garden and pine forest. Principal Component Analysis (PCA) shows that the habitat preferences were found in the mixed garden (1453 m asl) and primary forest with a river stream (2000 m asl), while at moon phases, number of individual bats captured in the dark moon phase was higher than full moon phases. This study shows that the abundance of fruit bats tightly associated with food availibility.

KEYWORDS. Fruit bats, distribution, habitat preferences, moon phases\

REFERENCES

  • Barlow, K. 1999. Bats: Expedition Field Tehniques. London : Royal Geographic Society. Bergmans, W. & Rozendaal FG. 1988. Notes on colections of fruit bats from Sulawesi and
    some off-lying islands (Mammalia, Megachiroptera). Amsterdam :Universiteit van Amsterdam.
  • Bork, SK. 2006. Lunar phobia in the greater fishing bat Noctilio leporinus (Chiroptera: Noctilionidae). Revista de Bioogial Tropical : 54(4): 1117-1123.
  • Cristian, D. & Helversen, V. 2005. Illustrated identification key to the bats of Europe. Tuebingen and Erlangen, German : Electronic Publication. Corbet, GB. & Hill, JE. 1992. The Mammals of the Indomalayan Region. A Systematics Review. Oxford : Oxford Press.
  • Esselstyn, JA. 2007. A new species of stripe-faced fruit bat (Chiroptera: Pteropodidae: Styloctenium) from the Philippines. Mammalogy : 88(4):951-958.
  • Gotelli, NJ. & Colwell, RK. 2011. Estimating Species Richness. In Magguran AE. & McGill BJ, editors. Frontiers In Measuring Biodiversity. New York (US): Malden Blackwell Publishing : 39-54.
  • Hasnawir, OH. & Kubota, T. 2006. Landslide Disaster at Mt. Bawakaraeng Caldera, South Sulawesi, Indonesia. Forest Research : 59:269-272.
  • Heideman, PD. & Heaney, LR. 1989. Population biology and estimates of abundance of fruit bats (Pteropodidae) in Philippine submontane rainforest. Zoology : 218: 565-586.
  • Larsen, JR. Begler, KA. Genoways, HH. Masefield, WP. Kirsch, RA. & Pedersen, SC. 2007. Mist netting bias, species accumulation curves and the rediscovery of two bats on Montserrat (Lesser Antiles). Acta Chiropterologica : 9(2): 423-435.
  • Lang, AB. Weise, CD. Kalko, EKV. & Roemer, H. 2004. The bias of bat netting. Bat Research News : 45: 235–236.
  • Lang, AB. Elizabeth, K. Kalko, V. & Romer, H. 2005. Activity levels of bats and katydids in relation to the lunar cycle. Oecologia.
  • Maguran, AE. 2004. Measuring Biological Diversity. United Kingdom (Inggris): Malden Blackwell Publishing
  • Maryanto, I. & Yani, M. 2003. The new species of the Rousettus bat from Lore Lindu National Park Central Sulawesi, Indonesia. Mammal Study : 28: 111-120.
  • Maryanto, I. Yani, M. Priyono, SN. & Wiantoro, S. 2011. Altitudinal distribution of fruit bats in Lore Lindu National Park, Central Sulawesi, Indonesia. Mammal : 22(1): 167-177.
  • Maryanto, I. Yani, M. Priyono, SN. & Wiantoro, S. 2012. A new species of fruit bat (Megachiroptera:Pteropodidae: Thoopterus) from Sulawesi and adjacent islands, Indonesia. Records Of The Western Australian Museum : 068–084.
  • The Fruit Bats (Megachiroptera, Pteroppodedae) From Bawakaraeng Moutain, South Sulawesi Mello, MAR. Kalko, EKV. & Silva, WR. 2013. Effect of moonlight on the capturability of frugivorous phyllostomid bats (Chiroptera: Phyllostomidae) at different time scales. Zoologia : 30 (4) :397-402.
  • Medellin RA. Equihua AM. & Amin MA. 2000. Bats diversity and abundance as indicators of disturbance in Neotropical rainforest. Conservation Biology. 14: 1666-1675.
  • Mickleburgh PS, Anthony MH, & Paul AR. 1992. Old world fruit bats. Switzerland(CH):IUCN/SSC Chiroptera Specialist Group.
  • Racey, PA. 1988. Reproductive Assessment In Bats. In Ecological and Behavioural Methods for Study of Bats. Washington DC (US): Smithsonian Institution Press.
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    including methodological and conservation considerations. Studies on Neotropical Fauna and Environment : 38 : 17-31.
  • Storz, JF. Bhat, H. & Kunz, TH. 2000. Social structure of a polygonous tent-making bat Cynopterus sphinx (Megachiroptera). Zoology : 251(2): 151–165. Sumaryono, Dasa YT. 2011. Simulasi aliran bahan rombakan di Gunung Bawakaraeng, Sulawesi Selatan. Lingkungan dan Bencana Geologi, 2: 191 – 202.
  • Suyanto, A. 2001. Kelelawar di Indonesia. Bogor (ID) : LIPI.
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  • Wiantoro, S. & Achamadi, AS. 2011. Keanekaragaman mamalia kecil di Pulau Moti. Ekologi Ternate : 55-68.

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CLASSIFICATION AND QUANTIFICATION OF MARINE DEBRIS AT TELUK LIKAS, SABAH

Farrah Anis Fazliatul Adnan*, Rudy Kilip, Dezvieo Keniin & Carolyn Payus

Faculty of Science and Natural Resources, Universiti Malaysia Sabah,
88400 Kota Kinabalu, Sabah, Malaysia.
Email: f_anis@ums.edu.my

ABSTRACT.Marine debris is a well-known issue faced by the public today and the problem is becoming serious day by day. In this study, quantification and classification of marine debris for plastic, fabric, paper, metal, glass and rubber was conducted to evaluate the marine littering of contamination level at Likas Bay. This study also aims to identify the sources of the marine debris whether it was from the land or was brought in from the sea. By selecting 10m x 10m transects randomly, the marine litters that were collected along the bay were rinsed, dried, weighted and classified according to categories. Total of 3396 items/100m2 of marine debris with the weight of 14499.36g/100m2 were collected throughout the study. From the result, it shows that plastic dominated the overall numbers and weight percentage of marine debris with 94.38% in numbers and 65.29% in weight. The study also indicates that the occurrence of marine debris at Likas Bay was not mainly caused from recreational activities at the area, but was brought in from the sea. This may due to the physical condition and the bay position which has the tendency to trap the marine debris from the sea. Therefore, further investigation should be undergoing to overcome and reduce the impact to the marine debris.

KEYWORDS: Marine debris, Littering, Transects, Bay

REFERENCES

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  • Gudger, E. W. & Hoffman, W. H. 1931 . A shark encircled with a rubber automobile tire. Scientific Monthly, 33:275–277.
  • Hidalgo-Ruz, V. & Thiel, M. 2013. Distribution and abundance of small plastic debris on beaches in the SE Pacific (Chile): a study supported by a citizen science project. Marine environmental research, 87-88:12–8.
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  • Classification and Quantification of Marine Debris at Teluk Likas, Sabah Moore, S.L. & Allen, M.J. 2000. Distribution of Anthropogenic and Natural Debris on the Mainland Shelf of the Southern California Bight. Marine Pollution Bulletin, 40(1):83–88.
  • Moore, S.L., Gregorio, D., Carreon, M., Weisberg, S.B. & Leecaster, M.K. 2001. Composition and distribution of beach debris in Orange County, California. Marine pollution
    bulletin, 42(3):241 –5 Rees, G. & Pond, K. 1995. Marine litter monitoring programmes—A review of methods with special reference to national surveys. Marine Pollution Bulletin, 30(2):103–108.
  • Rosevelt, C.,Huertos, M.L., Garza, C. & Nevins, H.M. 2013. Marine debris in central California: quantifying type and abundance of beach litter in Monterey Bay, CA. Marine pollution bulletin, 71(1-2):299–306.
  • Slavin, C., Grage, A. & Campbell, M.L. 2012. Linking social drivers of marine debris with actual marine debris on beaches. Marine pollution bulletin, 64(8):1580–1588.
  • Somerville, S.E., Miller, K.L. & Mair, J.M. 2003. Assessment of the aesthetic quality of a selection of beaches in the Firth of Forth, Scotland. Marine pollution bulletin, 46(9):1184–90.
  • Topçu, E.N., Tonay, A.M., Dede, A., Öztürk, A.A. & Öztürk, B. 2013. Origin and abundance of marine litter along sandy beaches of the Turkish Western Black Sea Coast. Marine environmental research, 85:21–8.
  • Van Cauwenberghe, L.,Claessens, M., Vandegehuchte, M.B., Mees, J. & Janssen, C.R. 2013. Assessment of marine debris on the Belgian Continental Shelf. Marine pollution bulletin, 73(1):161 –9.
  • Zhou, P., Huang, C., Fang, H., Cai, W., Li, D., Li, X. & Yu, H. 2011. The abundance, composition and sources of marine debris in coastal seawaters or beaches around the northern South China Sea (China). Marine pollution bulletin, 62(9):1998–2007.

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