Pavement structural assessment using automated tools: a comparative study

Pavement distress evaluation was traditionally conducted through visual observation. Traditional practice requires a person to walk along the stretch of pavement in order to survey distresses, take photos, and measure defects occurred at the deteriorated surface. However, this approach is too subjective causes inconsistencies of information, less reliable and time-consuming. Due to these shortcomings, the practitioners in pavement maintenance sector seek for a reliable alternative tools and techniques to arrest incapability of traditional approach. This research aimed to investigate feasibility of automated tools for pavement structural assessment conducting a comparative study. Series of interviews with expert panels and comparison matrix have been conducted comparing Ground Penetrating Radar (GPR), Infrared Thermograph (IR), and Portable Seismic Pavement Analyzer (PSPA) by investigating across parameters; cost-time effectiveness, operating principle, depth of performance, method of application, and limitations of pavement evaluations. The research indicated the Ground Penetrating Radar (GPR) is highly advantageous over IR and PSPA for pavement structural assessment. The GPR, as a geophysical tool, has extensive capabilities to accommodate data in pavement assessment, geotechnical investigation and structural assessment. GPR can considerably perform at high speed and save time. It is also beneficial for long-term investment with deeper information. Notably, the interpretation of radar gram images of GPR tool needs sufficient time and skill

Ground penetrating radar imaging and its application to pavement structural assessment

Traditionally, pavement distress evaluations were carried out by visual observation. In traditional practice, it requires a person to walk along the stretch of the pavement to conduct distress survey, take photo and measure defects occurred at deteriorated surface. However, this approach is too subjective, generates inconsistencies of information, less reliable and consumes lots of time. In lieu to this situation, some of the practitioners’ in pavement maintenance sector seek for other alternative tools and techniques to arrest incapability of traditional approach. One of the tools available in the market is Ground Penetrating Radar (GPR). GPR is a geophysical tool that is known with the ability to accommodate extensive data in pavement assessment, geotechnical investigation and structural assessment. The application of GPR is new to most of the practitioners in road maintenance industry in Malaysia. Therefore, this study has been undertaken to evaluate the benefits of using GPR in assessing pavement structure. The methodology for this study includes interviews with expert panels, followed by comparison of tools and GPR survey. The significant of tools comparison is to select the most appropriate tool for evaluation. Thus, GPR is compared with Infrared Thermograph (IR) and Portable Seismic Pavement Analyzer (PSPA) using the following parameters; cost-time effectiveness, operating principle, depth of performance, method of applications and limitations in order to select the most appropriate tool for further evaluations. Subsequently, GPR survey is being applied at a proposed location within UTM campus and findings are identified and processed using REFLEX 2D simulation software. The finding of this study concluded that GPR is highly advantageous over IR and PSPA for pavement structural assessments. GPR can perform at high speed and save time. It is also beneficial for long term investment due to numerous applications and vast ability to provide extensive information at a greater depth. There are three (3) types of information obtained from GPR survey such as; identification of raw image and processed image, identification of pavement segments thickness, and identification of GPR response towards surface and subsurface conditions which illustrated in radargram images. The interpretation of radargram images consumed more time due to the low resolution image captured by GPR. In view of this issue, selection of GPR system is crucial to ensure accuracy and clarity of radar images can be obtained nevertheless, all objectives in the study were achieved and verifie

Modelling aggressive driving behaviour impact on vehicle fuel consumption and tailpipe emissions

Vehicles, the environment, and drivers are important factors in driving behavioural studies. However, previous research related to vehicle’s fuel consumption and tailpipe emissions were focused on driving behaviour while treating the driver’s behaviour with a lack of consideration. Therefore, this study aims to model the impact of aggressive driving behaviour on vehicle fuel consumption and tailpipe emissions by considering characteristic of driver in real driving behaviour. Self-reported assessment tool was used to identify aggressive and nonaggressive drivers. Both types of drivers were then invited for on-road driving assessment (ODA) under different traffic conditions over five consecutive days. During the ODA, driver behaviour (anger expressions) were evaluated by an in-car observer, while driving behaviour and driving performances were observed and recorded using video camera and GPS Logger. The recorded anger expression during ODA were then validated with self-reported anger expression and triangulated with the actual driving behaviour and driving performance. Data recorded in the GPS Logger were then extracted in order to develop driving cycles for aggressive and non-aggressive drivers. The driving cycle was developed using micro trips by eliminating idling conditions. Aggressive drive cycle (AGDC) was compared with non-aggressive drive cycle (NGDC) and the findings from previous studies based on kinematic assessment parameters. AGDC and NGDC were then simulated using a chassis dynamometer in the laboratory to measure the vehicle’s fuel consumption and tailpipe emissions. Tailpipe emissions obtained from the AGDC and NGDC were also compared based on speed variations, traffic conditions, and road sections. The results from the Driving Anger Expression Inventory (DAX) questionnaires revealed that 35 out of 330 respondents were aggressive drivers and the rest were non-aggressive drivers. Based on 10 aggressive drivers and 1 non-aggressive driver who agreed to participate in the ODA, the findings on anger expressions showed insignificant difference between recorded and self-reported anger expressions. Based on the validated data, more than 58% consistencies in vehicle and verbal aggressions were found between self rating and in-car observation. While, only 35% and 42 % of vehicle and verbal aggressions, respectively shown by aggressive drivers in the video camera observation. Aggressive drivers were found to tailgate other vehicles, performed dangerous overtaking, violated the lane-keeping and red-light signals. For driving performances, it showed that aggressive drivers had a shorter travel time, higher average speed, and higher maximum speed as compared to non-aggressive drivers. Strong negative correlations was found between aggressive drivers travel time and average speed indicating that higher choice of speed had shortened the travel time. The comparative characteristics of AGDC and NGDC showed that the AGDC had shorter driving time, higher average speed, higher positive acceleration, and lower negative acceleration and positive acceleration kinetic energy (PKE) compared to the NGDC. While the comparison of AGDC with previous studies indicated that AGDC has similar kinematic characteristics with drive cycles in China, Taiwan, Jakarta, Chennai, Hong Kong, Tehran, and Tianjin. Results for the simulated driving cycles showed that AGDC had lower fuel consumption compared to NGDC. It was found that more than 50% of CO2 and less than 2% of CO emissions from AGDC and NGDC have been emitted. As speed increases, CO and CO2 emissions have increased. CO and CO2 emissions were found slightly higher during the afternoon traffic than other traffic conditions. For interrupted and non-interrupted road sections, AGDC illustrated increasing CO emissions in contrast to NGDC. While for CO2, AGDC showed high CO2 emissions at the interrupted section during the afternoon traffic and non-interrupted section during the morning traffic. The study concluded that modelling aggressive driving behaviour impact on vehicle fuel consumption and tailpipe emissions using new methods is capable of conveying realistic results. The application of new methods in the study can be used in other driver and driving behaviour studies that benefit for the environmental management

Drivers' adaptive travel behaviors towards green transportation development: a critical review

The transportation professionals integrated the concept Green in various dimensions of transportation, such as, green vehicle, green highway. The current study has established a new dimension to green transportation, which is called Green Driver as whom substantially contributes to less emission and fuel consumption, and higher-safety. The research established the driver's Green Adaptive Travel Behaviors (GATB), in particular, that is referred to voluntary personal and lifestyle behaviors on less energy consumption and emission. The methodology was designed into two phases. Phase one was to investigate driver's GATBs through systematic literature review process and content analysis method. The second phase was to verify greenery value impact (GVI) of the finalized list of drivers' GATBs through an expert input study and Grounded Group Decision Making (GGDM) method. Total twenty six (26) GATB factors have been determined. Amongst, the factor 'F27-Dangerous overtaking' has received the highest value (97%) followed with 'F3-Slow once realizing bike lanes for cyclist crossing' (91%). In contrast, F4-Realize visual Obstacles to manage the speed' and F21 - Brake with smooth deceleration' has received the lowest value (77%) among other factors. Two of the initial factors; F5-Use traffic calming devices' (55%), and F24-Change highest possible gear' (69%) could not reach the 70% saturation; hence, they have been dropped from the list of GATB factors. Indeed, the GATB efforts are not limited to technology and practice; but also can include education and enforcement to driving regulations in order to interconnect driver, technology, environment, and vehicle. The research concluded with an innovative technique used as the decision support tool to evaluate the greenery grade of any individual driver on committing to less emission, less fuel consumption, and higher safety in traveling. As future study, the Green driver behaviour index assessment model will be developed based on this study outputs

Drivers’ adaptive travel behaviors towards green transportation development: a critical review

The transportation professionals integrated the concept Green in various dimensions of transportation, such as, green vehicle, green highway. The current study has established a new dimension to green transportation, which is called Green Driver as whom substantially contributes to less emission and fuel consumption, and higher-safety. The research established the driver's Green Adaptive Travel Behaviors (GATB), in particular, that is referred to voluntary personal and lifestyle behaviors on less energy consumption and emission. The methodology was designed into two phases. Phase one was to investigate driver's GATBs through systematic literature review process and content analysis method. The second phase was to verify greenery value impact (GVI) of the finalized list of drivers' GATBs through an expert input study and Grounded Group Decision Making (GGDM) method. Total twenty six (26) GATB factors have been determined. Amongst, the factor 'F27-Dangerous overtaking' has received the highest value (97%) followed with 'F3-Slow once realizing bike lanes for cyclist crossing' (91%). In contrast, F4-Realize visual Obstacles to manage the speed' and F21 - Brake with smooth deceleration' has received the lowest value (77%) among other factors. Two of the initial factors; F5-Use traffic calming devices' (55%), and F24-Change highest possible gear' (69%) could not reach the 70% saturation; hence, they have been dropped from the list of GATB factors. Indeed, the GATB efforts are not limited to technology and practice; but also can include education and enforcement to driving regulations in order to interconnect driver, technology, environment, and vehicle. The research concluded with an innovative technique used as the decision support tool to evaluate the greenery grade of any individual driver on committing to less emission, less fuel consumption, and higher safety in traveling. As future study, the Green driver behaviour index assessment model will be developed based on this study outputs

PELATIHAN PENGEMBANGAN USAHA DAN OPTIMALISASI KREATIVITAS DI MEDIA SOSIAL BAGI WIRA USAHA MUDA DI KOTA BANJARMASIN

Salah satu sektor yang menunjang perekonomian di indonesia berasal dari sektor UMKM, hal ini pun juga berdampak pada wilayah Kalimantan Selatan Khususnya Kota Banjarmasin karena melalui sektor inilah semua aspek berkaitan dengan pola kehidupan manusia yang bersumber, mulai dari sektor konsumsi, pangan, fashion, fotografer serta kebutuhan yang diperlukan oleh masyarakat. Permasalahan secara umum yang sedang dihadapi wirausaha muda di kota Banjarmasin tersebut diantaranya adalah apa yang harus dilakukan bagi anak muda yang ingin memulai bisnisnya, permasalahan pasar atau pemasarannya, meliputi keterbatasan pasar, distribusi maupun luas pasar yang dituju, permasalahan iklim usaha dan pengembangan usaha, permasalahan standarisasi meliputi standard produksi hingga pelayanan, masih rendahnya pemanfaatan media sosial, dan serta kurang optimalnya sisi kreativitas pemanfaatan media sosial. Tujuan dari kegiatan ini untuk memberikan pengetahuan kepada masyarakat dan organisasi bisnis khususnya kepada wirausaha muda pelaku UMKM Kota Banjarmasin tentang bagaimana mengembangankan usaha dan mengoptimalisasikan sisi kreativitas mereka dalam memanfaatkan media sosial. Tahapan dalam pelaksanaan kegiatan: (1) pembekalan daring, (2) Ramah Tamah & Focus Group discussion (FGD), dan (3) Kegiatan Kunjungan. Hasil pelasaksanaan kegiatan ini yang diprogram secara konsepsi dengan menargetkan sasaran wirausaha muda selaku pemilik UMKM yang dilihat dari sisi pengolahan bahan baku hingga ke bahan jadi, dengan menyesuaikan antara basis keilmuan dengan realitas lapangan adalah merupakan hal yang dinilai sangat baik untuk selalu dipertahankan dan ditingkatkan.Kata Kunci: Pengembangan Usaha, Optimalisasi Kreativitas, Media Sosial, UMKM

EKSPLORASI ETNOMATEMATIIKA PADA PAKAIAN DAN RUMAH ADAT DI MALUKU: SYSTEMATIC LITERATUR REVIEW

Tuntutan kurikulum pendidikan agar pembelajaran matematika harus berbasis budaya. Sehingga maraknya penelitian etnomatematika yang beragam disetiap daerah khususnya di Maluku misalnya pada objek pakaian dan rumah adat. Penelitian ini berntujuan untuk mendekripsikan hasil penelitian etnomatematika pada pakaian dan rumah adat di Maluku, sebagai upaya mengenal dan memanfaatkan budaya Maluku dalam memahami matematika. Metode yang digunakan dalam penelitian ini adalah Systematic Literatur Review (SLR).  Artikel dan proseding di ambil dari database Google Scholar dengan kata kunci “Etnomatematika di Maluku”, dipilih sesuai kriteria yang tentukan terbitan tahun 2019-2023. Hasil pelitian menjukkan pembelajaran matematika di Maluku dapat melalui budaya pakaian dan rumah adat. Konsep matematika yang ditemukan pada pakaian (Tarian cakalele dan Tarian Tnabar Ila’a ) dan rumah adat (rumah adat Desa Nuanea, Beileo, Bera, dan rumah adat Desa Lorulun) adalah operasi bilangan, pengukuran, dan geometri. Seajuh ini penelitian etnomatematika pada pakaian dan rumah adat Maluku masih sedikit. Diharapkan peneliti etnomatematika berikunya dapat menggali lebih banyak pakaian dan rumah adat Maluku pada konsep matematika lainnya sehingga budaya dapat disajikan alat dan sumber belajar

Introducing Theil-Sen estimator for sun glint correction of UAV data for coral mapping

Despite wider applications for Unmanned Aerial Vehicle (UAV) in aquatic remote sensing, frequent sun glint in UAV acquisition often results in significant data gaps. Much research exists in the development of sun glint correction methods for airborne and satellite imagery to generate accurate coral habitat maps. Conversely, little is known about an appropriate glint correction method that can also be considered as data gap in UAV. This study compared glint correction methods for filling data gaps in UAV imagery acquired from the coral-dominated Pulau Bidong island in Peninsular Malaysia. This study proposed a simple seed pixel region growing technique that can be used in glint detection and mask development. It introduces the Theil-Sen regression glint correction (TSGC) for glint correction in UAV imagery and to achieve coral composition maps with thematic details, useful for sustainable coastal management. TSGC achieved a 25.6% greater coral classification accuracy compared to the uncorrected images

Assessing optimal UAV-data pre-processing workflows for quality ortho-image generation to support coral reef mapping

Since ortho-image constructed from unmanned aerial vehicles (UAV) acquired images has significant misalignment effect, an optimized and precise workflow (WF) is proposed in this study. Based on the parameters of photo alignment, sparse point cloud model, blending and seamline refinement, the 24 combinations of ortho-image producing methods were tested. The optimal WF is evaluated from the aspects of coral mapping accuracy, geometric fidelity, completeness, and efficiency. Statistical error analysis shows that blending and seamline refinement are the most relevant WF components that influence accuracy of orthorectification and consequently coral reef classification. The optimal WF found to be when ‘highest’ photo alignment, with ‘high’ tie points in the sparse cloud model are applied, in presence of blending and seamline refinements and can achieve 87.9% overall mapping accuracy. With the available photogrammetric software packages, the proposed WF can be used in mosaicking and mapping large scale macroalgae, seagrass and seaweed