KEBUTUHAN RTH UNTUK MENYERAP EMISI CO2 KENDARAAN BERMOTOR PADA KAWASAN JEMBATAN TELUK KENDARI

Emisi karbon dioksida (CO2) yang dihasilkan akibat aktivitas kendaraan bermotor pada kawasan Jembatan Teluk Kendari (JTK) perlu diimbangi dengan ketersediaan ruang terbuka hijau (RTH). Tujuan dari penelitian ini adalah: (a) mengetahui jumlah kendaraan bermotor yang melintasi Jembatan Teluk Kendari, (b) menganalisis konsentrasi emisi CO2 yang dihasilkan oleh kendaraan bermotor di Jembatan Teluk Kendari, dan (c) menganalisis kebutuhan RTH untuk menyerap emisi CO2 yang dihasilkan oleh kendaraan bermotor pada Jembatan Teluk Kendari. Metode yang digunakan pada penelitian ini adalah observasi lapangan, studi literatur, serta survei instansional. Hasil penelitian menunjukkan bahwa selama waktu pengamatan traffic counting dilakukan, tercatat 10476 unit kendaraan melintas pada ruas Jl. Wr. Soepratman (JTK), 11007 unit kendaraan pada Jl.Insinyur Soekarno, 7172 unit kendaraan Jl. Tinumbu-Jl. Beringin III-Jl. Gajah Mada, dan 8677 unit kendaraan pada Jl. Sukowati. Total konsentrasi emisi CO2 yang dihasilkan dari aktivitas kendaraan bermotor adalah 337,09 kg/jam, dan kebutuhan RTH untuk menyerap seluruh emisi dilakukan dengan mengoptimalkan RTH eksisting menjadi RTH berdaya serap 165,995 kg/jam dan mendesainRTH baru berdaya serap 172,943 kg/jam. RTH baru memanfaatkan lahan potensial yang berada pada kawasan Jembatan Teluk Kendari seluas 1,172 ha dengan komposisi 80% dari total luasan tersebut atau 0,937 ha terdiri atas komponen softscape (vegetasi), sedangkan sisanya sebesar 20% atau 0,234 ha terdiri atas komponen hardscape (benda mati)

Off the Beaten Path: Let's Replace Term-Based Retrieval with k-NN Search

Retrieval pipelines commonly rely on a term-based search to obtain candidate records, which are subsequently re-ranked. Some candidates are missed by this approach, e.g., due to a vocabulary mismatch. We address this issue by replacing the term-based search with a generic k-NN retrieval algorithm, where a similarity function can take into account subtle term associations. While an exact brute-force k-NN search using this similarity function is slow, we demonstrate that an approximate algorithm can be nearly two orders of magnitude faster at the expense of only a small loss in accuracy. A retrieval pipeline using an approximate k-NN search can be more effective and efficient than the term-based pipeline. This opens up new possibilities for designing effective retrieval pipelines. Our software (including data-generating code) and derivative data based on the Stack Overflow collection is available online

Transactional Support for Visual Instance Search

International audienceThis article addresses the issue of dynamicity and durability for scalable indexing of very large and rapidly growing collections of local features for visual instance retrieval. By extending the NV-tree, a scalable disk-based high-dimensional index, we show how to implement the ACID properties of transactions which ensure both dynamicity and durability. We present a detailed performance evaluation of the transactional NV-tree, showing that the insertion throughput is excellent despite the effort to enforce the ACID properties

H∞ LIDAR odometry for spacecraft relative navigation

Current light detection and ranging (LIDAR) based odometry solutions that are used for spacecraft relative navigation suffer from quite a few deficiencies. These include an off-line training requirement and relying on the iterative closest point (ICP) that does not guarantee a globally optimum solution. To encounter this, the authors suggest a robust architecture that overcomes the problems of current proposals by combining the concepts of 3D local feature matching with an adaptive variant of the H∞ recursive filtering process. Trials on real laser scans of an EnviSat model demonstrate that the proposed architecture affords at least one order of magnitude better accuracy compared to ICP

Exploring Spatial Correlation for Visual Object Retrieval

2013-2014 > Academic research: refereed > Publication in refereed journa