Many residential areas of Kuala Lumpur are susceptible to landslides; this is seen in the frequency of landslide occurences in these areas. The objective of this study is to delineate landslide risk areas in support of development planning, monitoring and control of unstable areas. In this study, five landslide causative factors were extracted from satellite imagery and maps provided by the Geological Survey Department of Malaysia. Factors included in the study including land use, river density and lineament derived from Landsat ETM image, precipitation amount from rain gauge stations and lithology, were extracted from the geological map of the study area. Layers were analyzed and divided into subclasses. An average weightage score was applied to calculate the subclasses into percentage weights of influence on landslide. Overlay, geo-processing and geo-statistic techniques in GIS were used to discriminate these weighted subclasses into landslide susceptibility at low, medium and high levels of risk areas. Results showed very high susceptible areas covering 0.21% of Kuala Lumpur of which 5.02% were found in the highly urbanized areas. Meanwhile, a landslide susceptibility map was generated to show low, medium and high susceptible areas in Kuala Lumpur. Results were verified using recorded cases of landslides in Kuala Lumpur which showed a 77% agreement with the study.
MeSH terms: Geology; Malaysia; Surveys and Questionnaires; Rain; Risk; Social Planning; Urbanization; Rivers; Landslides; Satellite Imagery
Conducting polypyrrole (PPy) nanoparticles were synthesized by chemical oxidative polymerization of pyrrole in aqueous solution containing ferric sulfate (Fe2(SO4)3), anionic surfactants (sodium dodecylbenzene-sulfonate (NaDBS) or sodium dodecyl sulfate (SDS)), 1-pentanol as the oxidant, dopant and co-emulsifier, respectively. The polymerization was carried out at 0 ºC and 25 ºC. Fourier transform infrared spectroscopy (FTIR) and elemental analysis indicated that anionic surfactants were successfully incorporated into the PPy backbone. Incorporation of anionic surfactants caused enhanced electrical conductivity, increased yield, decreased the size of particles as well as improved the thermal stability of the resultant PPy. The presence of anionic surfactant seems to inhibit undesirable side reactions so as to improve the regularity of the PPy backbone. Globular PPy particles were obtained with diameter ranged from 40 to 118 nm as revealed by field emission scanning electron microscopy (FE-SEM) and conductivity of 7.89×10-4 –2.35×10-2 S cm-1, as measured using impedance analyzer. It was found that polymerization at low temperature (0 ºC) produced PPy particles with smaller size and higher conductivity. The sodium dodecyl sulfate-doped PPy (SDS-doped PPy) exhibited higher conductivity than that of the sodium dodecylbenzenesulfonate-doped PPy (NaDBS-doped PPy), due to the bulkiness of NaDBS as compared to SDS.
This paper investigates and determines the solutions for the Diophantine equation x2 + 4.7b = y2r, where
x, y, b are all positive intergers and r > 1. By substituting the values of r and b respectively, generators of
x and yr can be determined and classified into different categories. Then, by using geometric progression
method, a general formula for each category can be obtained. The necessary conditions to obtain the
integral solutions of x and y are also investigated.
Detecting semantic events in sports video is crucial for video indexing and retrieval. Most existing works have exclusively relied on video content features, namely, directly available and extractable data from the visual and/or aural channels. Sole reliance on such data however, can be problematic due to the high-level semantic nature of video and the difficulty to properly align detected events with their exact time of occurrences. This paper proposes a framework for soccer goal event detection through collaborative analysis of multimodal features. Unlike previous approaches, the visual and aural contents are not directly scrutinized. Instead, an external textual source (i.e., minute-by-minute reports from sports websites) is used to initially localize the event search space. This step is vital as the event search space can significantly be reduced. This also makes further visual and aural analysis more efficient since excessive and unnecessary non-eventful segments are discarded, culminating in the accurate identification of the actual goal event segment. Experiments conducted on thirteen soccer matches are very promising with high accuracy rates being reported.
The objective of this study was to investigate the capabilities of low-cost digital cameras in volume determination. Low-cost digital cameras are capable of many applications including aerial photogrammetry and close-range photogrammetry. Low-cost digital cameras have the potential to be used in landslide monitoring and mapping. In this study, a low-cost digital camera was used as a tool to acquire digital images of a model of a simulated landslide. The model was constructed using cement and sand with the dimensions of 3m in length and 1m width. Digital images of the simulated model were acquired using the technique of aerial photogrammetry and were subsequently processed using digital photogrammetric software. A portion of the simulated model was excavated to simulate a landslide and volume determination was carried out for the excavated sand. The results showed that low-cost digital cameras can be used in photogrammetric application including volume determination.
The process of etching is the most crucial part of the work of manufacturing printed circuit boards (PCB). In the etching process by nitric acid, a spent etching waste solution of composition 250 g/L HNO3, 30-40 g/L Cu, 30-40 g/L Sn, 30-40 g/L Pb and 20-25 g/L Fe is produced. High metal concentrations in the spent etching waste solution make it a viable candidate for the recovery of metals. Recovery of metals from spent etching waste solution is a significant concern as the recent growth in production of printed circuit boards has generated a drastic increase of spent etching waste solution each year. This study concerns itself with the recovery of metals from spent etching waste. In this study a dilution was made in order to increase the pH of the solution as spent etching waste solution has high acidity, and the electrowinning method was performed to recover metals from the spent etching waste solution. Glassy carbon and platinum were used as cathode and anode in order to investigate the electrodeposition of metals and cyclic voltammetry investigation suggests that the deposition of metals on glassy carbon electrodes occurs at four different overpotentials mainly at -0.15 V, -0.35 V, -0.45 V and -0.75 V. Microscopy observation demonstrates that there is a deposition of metals by applying the potentials in a set of current-time transient study for a duration of 60 seconds and the metals recovered formed as aggregates.
Vapour pressure deficit (VPD) analysis introduces an approach to develop a better basis for the control of the environment of lowland greenhouses in Malaysia. The study of vapour pressure deficit (VPD) is to show air moisture conditions for plant production while taking into account different temperature levels. The purpose of this project is to develop a real-time automatic temperature and relative humidity control system in the lowland tropical greenhouse using a PIC16f876A microcontroller. The controller will then be used to monitor the temperature, relative humidity and VPD in the planting of Chili Kulai (Titisan 15). The fertigation system was introduced to the greenhouse to fertilize and irrigate the plant as well as to provide moisture to the environment. A swamp cooler was used to bring down the temperature and increase moisture content in the greenhouse. Ventilators were installed to remove the heat in the greenhouse. The study was carried out in an experimental greenhouse located at the Institute of Advanced Technology, Universiti Putra Malaysia (UPM).
Tailing sand is the residue mineral from tin extraction that contains between 94% and 99.5% silica, which can be used as moulding sand. It is found in abundance in the Kinta Valley in the state of Perak, Malaysia. Adequate water content and clay in moulding sand are important factors for better strength and
casting quality of products made from tailing sand. Samples of tailing sand were investigated according
to the American Foundrymen Society (AFS) standard. Cylindrical test pieces of Ø50 mm×50 mm in height from various sand-water ratios were compacted by applying three ramming blows of 6666g each using a Ridsdale-Dietert metric standard rammer. The specimens were tested for green compression strength using a Ridsdale-Dietert universal sand strength machine. Before the tests were conducted, moisture content of the tailing sand was measured using a moisture analyser. A mixture bonded with 8% clay possesses higher green compression strength compared to samples bonded with 4% clay. The results also show that in order to achieve maximum green compression strength, the optimum allowable moisture content for mixtures bonded with 8% clay is ranged between 3.75 and 6.5% and for mixtures bonded with 4% clay is 3-5.5%.
MeSH terms: Aluminum Silicates; Environment; Malaysia; Minerals; Pressure; Silicon Dioxide; Tin; United States; Water
The present investigation deals with the development of ethanol-vapour-sensing materials coated with the semiconducting oxide TiO2. Thick films of anatase TiO2 were deposited using the sol-gel dip-coating technique on alumina substrates by conventional alkoxide sol and modified sol added with Degussa P-25 as the sensing medium. It was shown that crystallised TiO2 anatase was obtained at the annealing temperature of 500oC. The fabricated TiO2 sensors exhibited highest sensitivity at the sensing temperature of 350 ºC. Sensitivity towards the ethanol vapour was further increased with UV light effect. The enhancement of the sensitivity of the modified catalytic pellet can be explained by the crystallite of anatase TiO2 and the effect of the photocatalytic of TiO2. The high sensitivity of the TiO2 film deposited with modified sol revealed that the modified sol could be a new alternative in the development of a TiO2 ethanol sensor.
Academic and corporate interest in sustainable product and process development has risen considerably
in recent years. This can be seen by the number of papers published and in particular by special issued of journals. This paper reports the results of a review of published peer-reviewed literature from 1987 to 2012 to provide an up-to-date picture of sustainability and sustainable assessment. A structured methodology is followed to narrow down the search from around 3500 papers to 111. A variety of different sustainability assessment methodologies are reviewed in two classified research areas: product sustainability assessment and process sustainability assessment. In presenting a detailed taxonomy of product and process sustainability assessment methods, the paper also outlines the advantages and weaknesses of the sustainability assessment methods. The review sheds light on the weak points of current research in this area. The paper also highlights several key issues which have to be taken into account in attempting to develop a product or process sustainability assessment research paradigm for future applications in manufacturing systems.
Clostridium difficile can cause severe diseases with significant morbidity and mortality in infected patients.
The rate of Clostridium difficile infection is high in North America and European countries. Metronidazole
and vancomycin have been recommended as the treatments of choice since 1990s. Recurrent infection
due to Clostridium difficile is common after several days of antibiotic administration. Probiotics have
been used in these patients as an adjunct treatment with some successful findings. However, a detailed
investigation on the use of probiotic for infected patients is still needed, particularly for its real efficacy.
The term halal refers to what ispermitted by Islamic law. It is a basic need for Muslims and encompasses all materials used in everyday life including cosmetics.Muslims want to be assured that the ingredients,handling, processing, distribution, transportation and types of cosmetic used are halal compliant. The halal aspects of cosmetic and personal care products cover ingredients, all the processes involved in production right up to delivery to consumers, safety and product efficacy evaluations. In order to verify halal compliance of cosmetic products, a method of detecting halal and non-halal ingredients is very important and critically needed. Halal cosmetic standards, halal certification and the halal logo can be used as benchmarks for halal compliance. In view of the importance of cosmetic and personal care products from the halal perspective, this review will cover the halal principles, halal cosmetic and personal care products, ingredients, standard and certification as well as safety. The development of the process of detecting non-halal ingredients and authenticating halal ingredients for potential cosmetic applications in recent years are included in this paper.
Similarity measurement is a critical component in any case-based reasoning (CBR) system. CBR is
a superior technique for solving new problems based on previous experiences. Main assumption in
CBR relies on the hypothesis that states similar problems should have similar solutions. This paper
describes a comparative analysis on several commonly used similarity measures (Canberra, Clark, and Normalized Euclidean distance) in retrieving phase of the case-based reasoning approach to facilitate supplier selection. In addition, the proposed agent-based supplier selection framework was designed to use customer’s defined weights to evaluate the price, volume, quality grade, and delivery date of supply materials, and also provide them with alternative products which are closest to their first order if it was out of stock. Finally, based on the proposed framework, a numerical example of the used approach is illustrated.
MeSH terms: Problem Solving; Thinking; Resin Cements
Heuristic Evaluation (HE) is used as a basis in developing a new technique to evaluate usability or
educational computer games known as Playability Heuristic Evaluation for Educational Computer Game (PHEG). PHEG was developed to identify usability problems that accommodate five heuristics, namely, interface, educational elements, content, playability and multimedia. In HE process, usability problems are rated based on severity score and this is followed by presentation of a mean value. The mean value is used to determine the level of usability problems; however, in some cases, this value may not accurate because it will ignore the most critical problems found in a specific part. In developing PHEG, a new quantitative approach was proposed in analyzing usability problems data. Numbers of sub-heuristics for each heuristic involved were taken into account in calculating percentage for each heuristic. Functions to calculate critical problems were also introduced. Evaluation for one educational game that was still in development process was conducted and the results showed that most of the critical problems were found in educational elements and content heuristics (57.14%), while the least usability problems were found in playability heuristic. In particular, the mean value in this analysis can be used as an indicator in identifying critical problems for educational computer games.
MeSH terms: Heuristics; Video Games; Multimedia; Biological Processes; Physiological Processes
Cross-document Structure Theory (CST) has recently been proposed to facilitate tasks related to multidocument analysis. Classifying and identifying the CST relationships between sentences across topically related documents have since been proven as necessary. However, there have not been sufficient studies presented in literature to automatically identify these CST relationships. In this study, a supervised machine learning technique, i.e. Support Vector Machines (SVMs), was applied to identify four types of CST relationships, namely “Identity”, “Overlap”, “Subsumption”, and “Description” on the datasets obtained from CSTBank corpus. The performance of the SVMs classification was measured using Precision, Recall and F-measure. In addition, the results obtained using SVMs were also compared with those from the previous literature using boosting classification algorithm. It was found that SVMs yielded better results in classifying the four CST relationships.
MeSH terms: Supervised Machine Learning; Algorithms; Publications; Support Vector Machine
Mobile users have the capability of accessing information anywhere at any time with the introduction of mobile browsers and mobile web search. However, the current mobile browsers are implemented without considering the characteristics of mobile searches. As a result, mobile users need to devote time and effort in order to retrieve relevant information from the web in mobile devices. On the other hand, mobile users often request information related to their surroundings, which is also known as context. This recognizes the importance of including context in information retrieval. Besides, the availability of the embedded sensors in mobile devices has supported the recognition of context. In this study, the context acquisition and utilization for mobile information retrieval are proposed. The “just-in-time” approach is exploited in which the information that is relevant to a user is retrieved without the user requesting it. This will reduce the mobile user’s effort, time and interaction when retrieving information in mobile devices. In this paper, the context dimensions and context model are presented. Simple experiments are shown where user context is predicted using the context model.
MeSH terms: Paper; Information Storage and Retrieval; Access to Information
Finding relevant disaster data from a huge metadata overhead often results in frustrating search
experiences caused by unclear access points, ambiguous search methods, unsuitable metadata, and long response times. More frequently, semantic relation between the retrieved objects is neglected. This paper presents a system architecture that makes use of ontologies in order to enable semantic metadata descriptions for gathering and integrating multi-format documents in the context of disaster management. After a brief discussion on the challenges of the integration process, the Multi-format Information Retrieval, Integration and Presentation (MIRIP) architecture is presented. A specific approach for ontology development and mapping process is introduced in order to semantically associate user’s query and documents metadata. An ontology model approach was designed to follow inspirational and collaborative approaches with top-down to bottom-up implementation. A prototype of the integrated disaster management information system is currently under development, based on the architecture that is presented in this paper.
MeSH terms: Cooperative Behavior; Database Management Systems; Disasters; Reaction Time; Research Personnel; Semantics; Information Storage and Retrieval
As the amount of document increases, automation of classification that aids the analysis and management of documents receive focal attention. Classification, based on association rules that are generated from a collection of documents, is a recent data mining approach that integrates association rule mining and classification. The existing approaches produces either high accuracy with large number of rules or a small number of association rules that generate low accuracy. This work presents an association rule mining that employs a new item production algorithm that generates a small number of rules and produces an acceptable accuracy rate. The proposed method is evaluated on UCI datasets and measured based on prediction accuracy and the number of generated association rules. Comparison is later made against an existing classifier, Multi-class Classification based on Association Rule (MCAR). From the undertaken experiments, it is learned that the proposed method produces similar accuracy rate as MCAR but yet uses lesser number of rules.
MeSH terms: Algorithms; Attention; Automation; Work; Data Mining
Natural language interfaces to ontologies allow users to query the system using natural language queries.
These systems take natural language query as input and transform it to formal query language equivalent
to retrieve the desired information from ontologies. The existing natural language interfaces to ontologies
offer support for handling negation queries; however, they offer limited support for dealing with them.
This paper proposes a negation query handling engine which can handle relatively complex natural
language queries than the existing systems. The proposed engine effectively understands the intent of
the user query on the basis of a sophisticated algorithm, which is governed by a set of techniques and
transformation rules. The proposed engine was evaluated using the Mooney data set and AquaLog dataset,
and it manifested encouraging results.
MeSH terms: Algorithms; Language; Information Storage and Retrieval; Intention