Search

Nigeria has an estimated TB prevalence of 219 per 100,000 population. In 2019, Nigeria diagnosed and notified 27% of the WHO-estimated cases of all forms of TB and contributed 11% of the missing TB cases globally.To assess TB underreporting by type and level of health facility (HF), and associated factors in Lagos State, Nigeria.Quantitative secondary data analysis of TB cases was conducted in 2015. χOverall, 2,064 persons with bacteriologically confirmed TB (15.5%) were not matched to patients in sampled TB registers. Treatment status was unknown for 86 cases (IQR 55-97) per LGA. LGAs with higher case-loads had higher proportions of cases with unknown TB status. Discrepant reporting of treated TB was also common (60% HFs). Primary-level TB treatment facilities and unengaged private facilities were less likely to notify.There was TB under-reporting across all types and levels of HFs and LGAs. There is a need to revise or strengthen the process of supervision and data quality assurance system at all levels.Le Nigeria a une prévalence de la TB estimée à 219 pour 100 000 habitants. En 2019, le Nigéria a diagnostiqué et notifié 27% des cas estimés par l’OMS de toutes les formes de TB et a contribué à 11% des cas de TB manquants dans le monde.Évaluer la sous-déclaration de la TB par type et niveau d’établissement de santé (HF), et les facteurs associés dans l’État de Lagos, au Nigeria.Une analyse quantitative des données secondaires des cas de TB a été réalisée en 2015. Le test χDans l’ensemble, 2 064 personnes ayant une TB confirmée par épreuve bactériologique (15,5%) n’ont pas été appariées à des patients dans les registres de TB échantillonnés. Le statut de traitement était inconnu pour 86 cas (IQR 55–97) par LGA. Les LGA ayant un plus grand nombre de cas avaient une plus grande proportion de cas dont le statut de traitement était inconnu. La déclaration discrète de la TB traitée était également fréquente (60% des HF). Les établissements de traitement de la TB de premier niveau et les établissements privés non engagés étaient moins susceptibles de faire des déclarations.Il y avait une sous-déclaration de la TB dans tous les types et niveaux d’HF et de LGA. Il est nécessaire de réviser ou de renforcer le processus de supervision et le système d’assurance qualité des données à tous les niveaux.

Water pollution always occurs in Malaysia due to industrial, construction, agriculture, and household activities. River pollution can disturb water supply that eventually affects business and household activities. Thus, water quality monitoring system is needed to detect contaminated water. We developed a water quality monitoring and filtration system controlled by Arduino. The proposed system was designed in Proteus software and ThingSpeak platform was used for real-time monitoring. The main objective of the study was to compare water quality of river, lake and tap water in terms of pH, temperature, turbidity, electrical conductivity and oxidation-reduction potential. If the water quality was not satisfied, the water sample would be filtered through filtration system. Water turbidity level, pH, temperature, electrical conductivity, and oxidation-reduction potential for filtered and nonfiltered water were compared and analyzed according to international and national water quality standard. Besides that, statistical analysis such as box plot and one-way analysis of variance test was applied to validate data from the system. The real-time water quality monitoring system was implemented through data storage, data transfer, and data processing. The system was connected to wireless fidelity whereas the output data was sent to the user and monitored by ThingSpeak. The system can be further upgraded and scaled up to be applied in the main tank at our home or factory. The outcome of this research can be used as a reference for further study on lake and river pollution monitoring system.The online version contains supplementary material available at 10.1007/s13762-022-04192-x.

Overhead cranes are widely used in industry to move extremely heavy and bulky loads through the overhead space in a facility instead of through aisles or on the floor. Unfortunately, the natural sw...

Objective The carbon, titanium, and oxygen levels on titanium implant surfaces with or without ultraviolet (UV) pretreatment were evaluated at different wavelengths through X-ray photoelectron spectroscopy (XPS). Materials and Methods This interventional experimental study was conducted on nine Dio UFII implants with hybrid sandblasted and acid-etched (SLA) surface treatments, divided equally into three groups. Control group A samples were not given UV irradiation, while groups B and C samples were given UVA (382 nm, 25 mWcm2) and UVC (260 nm, 15 mWcm2) irradiation, respectively. The atomic ratio of carbon, titanium, and oxygen was compared through XPS. Results Mean carbon-to-titanium ratio and C1 peaks considerably increased in Group A compared to those in experimental Groups B and C. The intensity of Ti2p and O1s peaks was more pronounced for group C compared to that for groups A and B. Conclusions Although the decrease in surface hydrocarbons was the same in both UV-treated groups, the peak intensity of oxygen increased in the UVC-treated group. Thus, it can be concluded that compared with UVA irradiation, UVC irradiation has the potential to induce more hydrophilicity on SLA-coated implants.

Structural failure can be prevented if the damage in the structure is detected at its onset and appropriate retrofitting carried out. Towards this end, this paper presents a vibration-based technique, using only the first vibration mode, for predicting damage and its location and severity in steel beams that are important structural components in buildings and bridges. For single damage scenarios, the modal strain energy based damage index β was capable of detecting, locating and quantifying damage. For multiple damage scenarios, Artificial Neural Network incorporating β as the input layer was used. This research used computer simulations supported by limited experiments. Damage intensity was specified as a percentage reduction in stiffness compared to that at first yield. The procedure is illustrated through several numerical examples and the results confirm the feasibility of the method and its application in preventing structural failure. Keywords: Damage prediction, Failure prevention, Vibration based technique, Modal strain energy, Artificial Neural Network, Damage location, Damage severity, Damage index, Damage scenarios.

The contribution to global CO2 emissions from concrete production is increasing. In this paper, the effect of concrete mix constituents on the properties of concrete and CO2 emissions was investigated. The tested materials used 47 mixtures, consisting of ordinary Portland cement (OPC) type I, coarse aggregate, river sand and chemical admixtures. Response surface methodology (RSM) and particle swarm optimisation (PSO) algorithms were employed to evaluate the mix constituents at different levels simultaneously. Quadratic and line models were produced to fit the experimental results. Based on these models, the concrete mixture necessary to achieve optimum engineering properties was found using RSM and PSO. The resulting mixture required to obtain the desired mechanical properties for concrete was 1.10-2.00 fine aggregate/cement, 1.90-2.90 coarse aggregate/cement, 0.30-0.4 water/cement, and 0.01-0.013 chemical admixtures/cement. Both methods had over 94% accuracy, compared to the experimental results. Finally, by employing RSM and PSO methods, the number of experimental mixtures tested could be reduced, saving time and money, as well as decreasing CO2 emissions. La contribución a las emisiones globales de CO2 debidas a la producción de hormigón está aumentando. En este trabajo, se investigó el efecto de los componentes de la mezcla de hormigón en las propiedades del mismo y las emisiones de CO2. Los materiales estudiados fueron 47 mezclas, que consistieron en cemento Portland ordinario (OPC) tipo I, árido grueso, arena de río y aditivos químicos. Se utilizaron algoritmos de metodología de respuesta de superficie (RSM) y optimización de nube de partículas (PSO) para evaluar los componentes de la mezcla a diferentes niveles simultáneamente. Se elaboraron modelos cuadráticos y lineales para ajustar los resultados experimentales. Basándose en estos modelos, utilizando RSM y PSO, la mezcla de hormigón logró propiedades óptimas de ingeniería. La mezcla resultante requerida para obtener las propiedades mecánicas deseadas para el hormigón fue de 1.10-2.00 árido fino / cemento, 1.90-2.90 árido grueso / cemento, 0.30-0.4 agua / cemento y 0.01-0.013 aditivos químicos / cemento. Ambos métodos tuvieron más del 94% de precisión, en comparación con los resultados experimentales. Finalmente, al emplear los métodos RSM y PSO, el número de mezclas experimentales probadas podría reducirse, ahorrando tiempo y dinero, así como disminuyendo las emisiones de CO2.

This paper proposes an optimized damage identification method in beam-like structures using genetic algorithm (GA) without baseline data. For this purpose, a vibration-based damage identification algorithm using a damage indicator called ‘Relative Wavelet Packet Entropy’ (RWPE) was implemented to determine the location and extent of damage. The procedure does not require vibration signals from an undamaged structure because the method of comparing signals from different locations in the existing state was found to be effective. To ameliorate the algorithm, GA was utilized to identify the best choice for “mother wavelet function” and “decomposition level” of the signals by means of the fundamental fitness function to optimize the algorithm. This resulted in the high accuracy of the damage identification algorithm. In addition, this method has eliminated the difficulties in selecting the type of mother wavelet function for damage identification purposes. To investigate the robustness and accuracy of the proposed method, numerical examples and experimental cases with different damage depths were considered and conducted. The results demonstrated that the proposed method has great potential in the identification of damage location and depth of cut in beam-like structures since it does not require the recorded data from an undamaged beam as a baseline for damage detection. Moreover, the relationship between damage location and depth of damage has been evaluated and results showed that the algorithm can be applied to actual structures.

There are several issues that present in conventional sensor including its accuracy, safety, durability and RF effect. These issues could be minimized with the implementation of fiber optic sensor. This project is to design and implement optical sensor using FBG for various temperature and liquid density sensing. The FBG sensor was submerged in liquid substances to determine the sensing conditions. The available pigtail was connected to the circulator, 1550nm laser source and optical spectrum analyzer (OSA). The data regarding temperature and density sensing captured from OSA were observed and analyzed. It is found that the relationship between the change in temperature and the change in wavelength is virtually linear in both environments making FBG a good candidate for sensing temperature.

Nearly 280 kilotons of polystyrene (PS) waste being discarded yearly in Malaysia. Banning usage of PS food packaging aims to minimize this “white pollution”. However, the existing PS waste volume remains the same despite the termination of PS production. Therefore, this study has investigated the optimization of biodegradation of PS using isolated strain Bacillus aryabhattai as an alternative solution to the biodegradation of recalcitrant plastic. The effect of pH and temperature as independent variables were studied at three levels each (pH: 6, 7.5 and 9, temperature: 25 °C, 35 °C and 45 °C) under the designation by three level-factorial and analysed using response surface methodology (RSM) by Design Expert Version 10.0. The biodegradation activity of Bacillus aryabhattai was quantified using simple colorimetric method. Bacillus aryabhattai was inoculated on the dye PS-film and incubated under designed conditions. As a result of biodegradation, the entrapped methylene blue dye was released and measured photometrically. Optimum conditions for the highest reading of blue dye absorbance were obtained at pH 9 and temperature of 25ºC with the desirability of 75.9%. This study provides significant information on the biodegradation activity of Bacillus aryabhattai for future research that can be applied in waste management.

This work examined sonocatalytic degradation of caffeine in the presence of CeO2 prepared by hydrothermal method. Several characterization techniques were used to study the CeO2 including TEM, XRD and BET method. Effects of various parameters such as pH, initial concentration of caffeine and dosage of CeO2 were investigated. This study also examined the reusability of CeO2. Results showed that the CeO2 had mixed shapes of crystallites consisting of rods and cubes with the specific surface area (Sbet) and pore volume of 126.63 m2/g and 0.4898 cm3/g, respectively. About 95.5% of caffeine degradation was achieved under the best parameter conditions i.e. at pH of 7.5, 5.0 mg/L of initial concentration of caffeine and 1.0 g/L of CeO2 dosage within 150 min. It was also revealed that the operating parameters played major roles in caffeine degradation efficiency. In addition, the CeO2 were quite stable since the efficiency of caffeine degradation achieved in the third cycle was 81.4%.

Galvanic coupling method is one of the methods introduced in intra-body communication (IBC). IBC uses human body to as the communication medium for data transmission. In this paper, the investigation focuses on signal attenuation performance across knee joint using the galvanic coupling analysis. The signal attenuation was determined by implementing the galvanic coupling analysis at specific knee flexion angle. The galvanic analysis initiated by deciding the operating frequency in between 40 to 60 MHz in order to analyze the signal attenuation between the knee flexion angles. This paper found that the lowest signal attenuation at the operating frequency was 47.25dB, while the highest one was 52.63dB where the knee flexion angle is 0o and 155o respectively. It was concluded that the signal attenuation decrease with the increasing of knee joint existence at the specific flexion angle. However, a wider experiment must be conducted for various data that will correspond to signal attenuation for various influenced human data characteristics.

Damage in a structure is defined as changes to its geometric and material properties, leading to a reduction in the structural stiffness which negatively affects the performance of the structure. Reduction in the structural stiffness produces changes in the modal parameters such as the natural frequencies and mode shapes. Artificial neural networks (ANNs) have been applied extensively in recent years due to their excellent pattern recognition ability that is useful for structural damage identification purposes. In this paper, ANNs based damage identification techniques were developed and applied for damage localization and severity identification in I-beam structures using dynamic parameters. Experimental modal analysis and numerical simulations were applied to generate dynamic parameters of the first five flexural modes of structures. In damage identification using ANNs, five individual networks corresponding to mode 1 to mode 5 were trained, and then a method based on neural network ensemble was proposed to combine the outcomes of the individual neural networks into a single network. The ensemble network has the advantages of all the individual networks from different vibrational modes. The results showed that ensemble neural networks have a strong potential for structural damage identification.

Watershed Conditions (DAS) Limboto has faced seriously problems of highly rates of erosion, sedimentation, spread of critical land, shift functions of forests and rarity quality water of river as a resutt of floods that always happen, water scarcity and the silting up of Lake Limboto. Therefore, the research has conducted as an integral part ofan effort to develop a model ofintegrated watershed management through mechanisms of payments for environment services (PES) and identify institutional forms. Through Valuation Method and Dynamic System ver.2.5 with 84 people of sample is found that preserving watershed area of Limboto will manage by integrated watershed management through the mechanisms of Payments for Environmental Services (PES) has potential to do in light of community participation and willingness to maintain the forest while maintaining the sustainability of the future of Environment and to proven society of social-and economic matters as has showed by analysis ofdynamic systems.

One of the most important requirements in the evaluation of existing structural systems and ensuring a safe performance during their service life is damage assessment. Damage can be defined as a weakening of the structure that adversely affects its current or future performance which may cause undesirable displacements, stresses or vibrations to the structure. The mass and stiffness of a structure will change due to the damage, which in turn changes the measured dynamic response of the system. Damage detection can increase safety, reduce maintenance costs and increase serviceability of the structures. Artificial Neural Networks (ANNs) are simplified models of the human brain and evolved as one of the most useful mathematical concepts used in almost all branches of science and engineering. ANNs have been applied increasingly due to its powerful computational and excellent pattern recognition ability for detecting damage in structural engineering. This paper presents and reviews the technical literature for past two decades on structural damage detection using ANNs with modal parameters such as natural frequencies and mode shapes as inputs.

This study presents and reviews the technical literature and previous studies for the past three decades on structural damage identification using ANNs and measured FRFs as inputs. Much of the previous studies have used modal parameters to ascertain the success of damage identification. However, significant information may not be properly represented through the application of modal parameters. With this in mind, the direct use of frequency domain data in terms of the Frequency Response Functions (FRFs) seems more appropriate. Recent studies indicate that ANNs can be trained on measured FRFs of healthy and damaged models of structure to assess the condition of the structure. According to this review, it is clear that there have been numerous studies which have gone on to apply the ANNs on FRF data of structures in the field of damage identification and it has been shown that ANNs using FRFs can provide several advantages over the modal parameters and damage identification has subsequently become much improved.

This study deals with a proposed mix design method for SCC utilizing different properties of coarse aggregate. The work was conducted in three phases, i.e. paste, mortar and concrete to facilitate the mix design process. Initial investigation on cement paste determined the basis for water cement ratio and superplasticizer dosage for the concrete. For the study on mortar, metakaolin (MK) as pozzolan was used at replacement levels of 5%, 10%, 15%, and 20% by weight of cement. Self compactability of mortars was obtained by adding suitable materials such as mineral admixtures and superplasticizer which provided a sufficient balance between flowability and viscosity of the mix. The optimum MK replacement level for cement was 10% from the viewpoint of workability and strength. Flowability of mortar decreased with the use of metakaolin. Moreover, strength of mortar increased when the optimum replacement level of pozzolan was used. Different fresh concrete tests were adopted. The results obtained for fresh concrete properties showed that flowability of concrete increased with increase flowability of mortar. The mixes which contained coarse aggregate with lower volume, small size, and continuous grading affected positively the fresh properties of SCC. Finally, the mix design method used was successful in producing SCC with different coarse aggregate properties.

In this paper, an explicit time integration scheme is proposed for structural vibration analysis by using wavelet functions. Initially, the differential equation of vibration governing SDOF (single-degree of freedom) systems has been solved by wavelet operators, and later the proposed approach has been generalized for MDOF (multi-degrees of freedom) systems. For this purpose, two different types of wavelet functions have been exemplified including, complex Chebyshev wavelet functions and simple Haar wavelet functions. In the proposed approach, a straightforward formulation has been derived from the numerical approximation of response through the wavelet definition. Emphasizing on frequency-domain approximation, a simple step-by-step algorithm has been implemented and improved to calculate the response of MDOF systems. Moreover, stability and accuracy of results have been evaluated. The effectiveness of the proposed approach is demonstrated using three examples compared with some of the existing numerical integration schemes such as family of Newmark-@b, Wilson-@q and central difference method. In all the procedures, computation time involved has also been considered. Finally, it is concluded that the vibration analysis of structures is improved by lesser computation time and high accuracy of proposed approach, particularly, in large-scaled systems.

This article attempts to explain the effect of composite action in reinforced concrete (RC) elements on the natural frequencies. Natural frequencies are governed by the relationship between the physical properties of RC elements and its composite action. The softening of concrete in tension, compression, and pre- and post-yielding steel behavior are considered. The bonding action between steel and concrete under loading and unloading conditions is also taken into account. The assumption of the increase in stiffness of RC elements in tension due to bond action is investigated by tests on two RC beams. Both static and modal testing were carried out after inducing different levels of damage in the beams. Results show the validity of the assumption made due to composite action. Mode 1 can be an indicator for bond action behavior and for predicting the yield state of steel in the RC beams. Mode 2 behavior is governed by the amount of steel reinforcement, where for maximum steel ratio it will be affected by con...

Humans live their lives very much depending on the environment. Humans modify the environment for their purposes and the benefits of ecosystem. In everyday routine, disposal items keep on escalating. However lack of concern towards waste container as a mediator of waste practices has indirectly affected human environment. This was the result of a survey that had been distributed to employees of several organizations in Malaysia. The survey yielded personas who were not satisfied with waste containers due to several weaknesses of the current waste container such as low level of tear resistant, short of lifespan, swarmed by small insects and does not detect trash flow. Therefore, this paper was written to conceptualize an innovated artifact based on spiritual design concept. For this artifact, we applied some hygienic features and ICT technology in a waste container called XOdorBin. This innovative product is hoped to promote spiritual element of harmony towards better quality of life.

Damage in structures often leads to failure. Thus it is very important to monitor structures for the occurrence of damage. When damage happens in a structure the consequence is a change in its modal parameters such as natural frequencies and mode shapes. Artificial Neural Networks (ANNs) are inspired by human biological neurons and have been applied for damage identification with varied success. Natural frequencies of a structure have a strong effect on damage and are applied as effective input parameters used to train the ANN in this study. The applicability of ANNs as a powerful tool for predicting the severity of damage in a model steel girder bridge is examined in this study. The data required for the ANNs which are in the form of natural frequencies were obtained from numerical modal analysis. By incorporating the training data, ANNs are capable of producing outputs in terms of damage severity using the first five natural frequencies. It has been demonstrated that an ANN trained only with natural frequency data can determine the severity of damage with a 6.8% error. The results shows that ANNs trained with numerically obtained samples have a strong potential for structural damage identification.

In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANNs) techniques are developed and applied to identify damage in a model steel girder bridge using dynamic parameters. The required data in the form of natural frequencies are obtained from experimental modal analysis. A comparative study is made using the ANNs and ANFIS techniques and results showed that both ANFIS and ANN present good predictions. However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. This paper also highlights the concept of ANNs and ANFIS followed by the detail presentation of the experimental modal analysis for natural frequencies extraction.

In this paper, fly ash and metakaolin as pozzolan while limestone powder and kaolin as filler material were used at replacement levels of 5%, 10%, 15%, and 20% by weight of cement and sand, respectively. The effects of these powders on the fresh property of mortar mixes were studied and reported. Superplasticizer dosages were determined from flow test on cement paste and mortar with different powder content. A total of 33 mixes were prepared, mixed, and tested. The mini slump cone and mini V-funnel box tests were used to assess the flowability of the fresh mortar. In addition, the effect of mineral admixture on setting time of the mixes was also evaluated. In this study, the optimum dosage of superplasticizer was determined based on the desired flowability for self compactability. Superplasticizer at higher dosages than optimum reduced the stability due to bleeding. The results confirmed the role of the mineral powders in determining the desired stability and the flowability of mortar mixes which is crucial for self compacting concrete.

In this study, an optimized damage detection using genetic algorithm (GA) in beam-like structures without using baseline data. For this purpose, a vibration-based damage detection algorithm using a damage indicator called ‘Relative Wavelet Packet Entropy’ (RWPE) was applied to determine the location and severity of damage. To improve the algorithm, GA was utilized to optimize the algorithm so as to identify the best choice of wavelet parameters. To examine the robustness and accuracy of the proposed method, numerical examples and experimental cases with different damage depths were considered and conducted.

The recent economic climate, impact of government regulation, and new market trends has impacted the catalyst designers to improve the performance of catalyst. To achieve this goal, a series of experiments were conducted to focus on the influence of Ga and Re addition on the catalytic activity of Pt–Re/Al2O3 naphtha reforming catalysts. To supported γ-Al2O3 the Ga-Re-Pt prepare by using incipient wetness impregnation method. Many characterization tests are used such as scanning electron microscopy, temperature programmed desorption, X-ray diffraction and BET surface area. The liquid product yield tested by PONA method. In this study the benzene content is used as main performance criteria throughout many experiments performed at different liquid hourly space velocity, hydrogen/ hydrocarbon ratios and different operating temperature. According to the catalyst characterization tests the coimpregnation method showed good result in term of performance and properties. The catalyst exhibited good liquid product distribution and significant minimization of benzene content.

The strengthened effectiveness and the performance capacity of repaired Reinforced Concrete (RC) structures with Carbon Fibre Reinforced Polymer (CFRP) sheets is dependent on the properties of the adhesive interface layer. Adhesive material requires a specific setting time to achieve the maximum design capacity. Adhesive producer provides technical data which demonstrates the increase with time of the capacity, up to the maximum. The aim of this study is to investigate the effect of the adhesive setting time on the modal parameters as an indication of the effectiveness of CFRP on repaired RC beams. Firstly, datum modal parameters were determined on the undamaged beam and subsequently the parameters were obtained when damaged was induced on the RC beam by application of load until the appearance of the first crack. Finally, the RC beam is repaired with externally bonded CFRP sheets, and modal parameters are once again applied after 0.5, 1, 2, 3, 5, 8, 11, 15 and 18 days. The comparison is made with the data based on half day results in order to monitor the change in the modal parameters corresponding to the adhesive setting time. The modal parameters where used as indicators for the effectiveness of CFRP are affected by the adhesive time as shown in this study. Results are compared with the adhesive technical data provided by the adhesive producer.

The performance of structures such as bridges, machine foundations and base isolated buildings are very much affected by the condition of their elastic bearing supports, which eventually deteriorate due to wear and tear or which can be damaged during the service life of the structure. In this study, the dynamic parameters, namely natural frequencies and mode shapes are used to detect the deterioration of the elastic bearing supports of a simply supported bridge girder. For this purpose, force vibration testing was conducted on a reinforced concrete bridge girder supported at the ends by rubber bearings to simulate the actual conditions in a bridge deck. Three different levels of deteriorations were investigated namely that of no deterioration, partial deterioration, and full deterioration, whereby rubber with different stiffness was used to simulate the different deterioration levels. Vibration data were obtained for two cases i.e. an undamaged girder and a damaged girder after being subjected to a load exceeding its service limit for flexure. A direct relationship was observed between the dynamic parameters and the elastic bearing stiffness. Based on the results obtained in this study, the natural frequency of mode 3 is a good indicator of the deterioration in elastic bearing support conditions while mode 1 is the most sensitive to changes in support conditions. The Modal Assurance Criteria (MAC) index can be a useful indicator to identify different causes of deterioration in the structural system. In order to confirm and verify the observations, further tests were conducted on a different beam with more deterioration levels in the elastic bearing stiffness. The results support the deductions made regarding MAC and bending frequencies.

This paper presents finite element modelling of the effects of different flow velocities on the structural behaviour of a skewed integral bridge. Flow velocities affect the scour depths at the piles of a bridge and thus affect its structural behaviour. Laboratory tests on a scaled-down hydraulic model along with numerical modelling were performed to simulate the structural behaviour of the scoured integral bridge. A finite element package was used for the numerical modelling work, and the displacements and strains corresponding to the measured locations on the physical model were extracted. The experimental and numerical results for the case of maximum scour depths were compared.

This article reports the results of an investigation on the engineering properties of concrete containing black sugar palm fiber. Three fiber lengths of 15, 25, and 35 mm in four volume fractions, namely 0.2%, 0.4%, 0.6%, and 0.8%, were utilized in this investigation. The values of compressive, flexural, toughness, first crack deflection, first crack toughness, and toughness indices are reported for ages up to 90 days. It was observed that the addition of palm fibers slightly increased the flexural strength of concrete. The incorporation of the fibers had no significant effect on the compressive strength. The mix with 0.8% volume fraction and 35 mm length fiber gave higher toughness and ductility compared to other mixes.

This study presents the potential energy saving, life cycle cost analysis and payback period of the lighting system in campus buildings of the University of Malaya, Malaysia. The survey results indicate that almost 90% of the lighting system at the University Malaya campus consists of fluorescent lamp. Cost benefit analysis of retrofitting with more efficient lighting system in terms of potential energy saving, life cycle cost analysis and payback period have been conducted. Comparison of existing and retrofitting of lighting system based on the energy consumption is presented. From the analysis, it can be concluded that by using energy efficient lighting system will save a significant amounts of energy and cost, and also indirectly reducing emission.

Self Compacting Concrete (SCC) is new type of concrete that posse's property of high flow ability, passing ability and stability. To achieve SCC, many factors must be investigated. Coarse aggregate is one of these factors that have a significant influence on SCC. This paper presents the coarse aggregate properties such as maximum size, texture and type of coarse aggregate that have a direct effect on achieving SCC. Three types of coarse aggregate are used, namely crush gravel, uncrushed gravel and crush limestone. To determine the workability, different test methods are adopted such as slump flow, V-funnel, L-box and U-box test. It was found that by increasing the maximum size of coarse aggregate, flowability and passing ability reduced. In addition it was observed that when uncrushed gravel was used in the concrete mixture, flow ability, passing ability and segregation resistance increased as compared to concrete with crushed gravel. Furthermore, the inclusion of 10% HRM as a partial replacement by weight of cement leads to reduce flow ability and increase viscosity. The compressive and flexural strengths and modulus of elasticity was measured. It was noticed that concrete mixes prepared with crushed limestone showed higher strengths and modulus of elasticity than concrete mixes prepared with crushed and uncrushed gravel. In addition, lower maximum size of coarse aggregate leads to higher strengths compared to higher maximum size of coarse aggregate in SCC mixes.

The effects of far distant earthquakes felt in regions with low and moderate seismicity has increased markedly over the last decade. Henceforth fragility curves in this study are to indicate whether buildings are safe to enter or not after an earthquake event occurring more than 300 km away. The probability of light, moderate and severe damage states occurring on two and four storey reinforced concrete buildings up to a peak ground acceleration of 0.2 g were predicted. The building models were constructed using finite element software based on eight node brick elements with three degrees of freedom at each node. The analysis was carried out using a dynamic response spectrum to calculate the peak inter-storey drift ratios. For the development of fragility curves, the results were collated following a log-normal mean distribution. The results showed that light damage is likely to occur with a probability of over 10% within a 50 year period, while the existing record is unlikely to cause structural damage. The fragility curves were comparable to those for RC moment resisting frames obtained by (Rossetto and Elnashai 2003) at a lower drift limit, with approximately 2% of inter-storey drift ratio.

Investigation of the influence of the differences in the support conditions on the dynamic parameters are presented in this study. Bridge girders are usually supported by elastic bearings and suffer deterioration during the service life of the bridge. Early stages of deterioration of the elastic bearing occur with decrease in its stiffness. Advance stages of deterioration causes total damage of the elastic bearing, whereby the bridge girder will be supported directly on the structural element below it. The deterioration can occur on one or both sides of the supports. In order to study the effect of this phenomenon, experiments were conducted on a simply supported beam supported on elastic rubber pads with different stiffness as well as on steel supports. The undamaged support condition was simulated by using new rubber pads with stiffness of 10MN/m. The damage support conditions were represented by using old rubber pads with stiffness of 3 MN/m and using steel supports to simulate the case of total deterioration of the rubber bearing pads. Natural frequencies and mode shapes were obtained from modal testing and compared using of Modal Assurance Criteria MAC. The results showed a direct relationship between the support stiffness and the natural frequencies and mode shape. The first bending mode was most sensitive to the changes in support stiffness followed by Mode 2. It was also observed that the other modes had similar but lower sensitivity to the state of deterioartion of the supports.

Sea level rise due to climate change have a profound impact on low lying coastal zones. The objective of this study is to identify the potential of coastal inundation area due to Sea Level Rise (SLR) along of Cherating to Pekan coast. The shoreline of Pahang has been undergoing severe erosion and inundated by sea water in some locations, hence affects the socio-economy and the livelihood of the coastal communities. Numerical modelling using the MIKE 21 FM software was done to predict coastal inundation for the years 2020 and 2080 along the Cherating to Pekan shoreline by using the condition for the year 2017 as the baseline. The results of the statistical analysis of this numerical model is congruous with the measured data, such as tide, current, and wave direction. The results show that about 17 to 22% of the Cherating to Pekan shoreline is at risk of being inundated due to the projected SLR for the years 2020 and 2080. The map for projected inundation shows that the infrastructure located in the 1km buffers zone from the shoreline will be affected by the sea level rise. This information could be of benefit to all parties involved in ensuring effective coastal management and making preparation and plan to and protect the coastal areas from the potential impacts of climate change and future disasters.