3,744 research outputs found
Innovative Green Technology for Sustainable Industrial Estate Development
Sustainable industrial development requires a balance between economic growth, equity and environment. Two major components of industrial development are energy and raw materials. To minimize the environmental impacts of energy and raw materials, important steps are required to deal with the green economy and global warming issues. The use of innovation technology to industrial gas emission is a preventive solution facing global warming. A research has been done in Industrial Estate in Cilegon (IEC) Banten province, Indonesia, to see how to reduce energy demand and encourage uses of more environmentally-friendly energy in the estate. Fossil energy needs in the industrial estate were analyzed to see the opportunities of energy saving and renewable energy development. The target to be achieved is to reduce the greenhouse gas emissions and improve the energy efficiency in the industrial park
Kebenaran dan Metodologi Penelitian Filsafat: sebuah Tinjauan Epistemologis
Di dalam makalah ini, perhatian akan difokuskan pada masalah "kebenaran" yang ditinjau secara epistemologis, dan "metodologi penelitian filsafat". Karena "kebenaran" tersebut dibicarakan di dalam kerangka epistemologis, maka di dalam pendahuluan ini akan disajikan pengertian "epistemologi" dan "metodologi" secara singkat, agar pembicaraan kita menemukan fokus yang jelas
Evaluasi Kinerja Forum Bina Lingkungan (Bilik) Dalam Pengawasan dan Pengendalian Pencemaran Air Sungai di Kecamatan Cikarang Barat Kabupaten Bekasi
Forum Bina Lingkungan (Forum Bilik) sebagai manifestasi partisipasi stakeholder dalam pengelolaan lingkungan hidup merupakan salah satu strategi pengawasan dan pengendalian pencemaran air dalam pengelolaan sungai. Forum Bilik dibentuk di sekitar sub daerah aliran sungai dengan keanggotaan terdiri dari masyarakat (tokoh-tokoh masyarakat, pemerhati lingkungan) dan pengusaha/ industriawan. Melalui penelitian studi kasus terhadap partisipasi masyarakat dalam pengelolaan lingkungan hidup akan dikaji kinerja forum bina lingkungan (bilik) dalam pengawasan pencemaran air sungai. Fokus penelitian yaitu mendeskripsikan realita yang terjadi di wilayah studi atas kinerja forum bilik dalam pengawasan dan pengendalian pencemaran air sungai. Pengumpulan data dalam penelitian ini dilakukan melalui observasi langsung, wawancara, dan diskusi kelompok kecil
A Learning-based Stochastic MPC Design for Cooperative Adaptive Cruise Control to Handle Interfering Vehicles
Vehicle to Vehicle (V2V) communication has a great potential to improve
reaction accuracy of different driver assistance systems in critical driving
situations. Cooperative Adaptive Cruise Control (CACC), which is an automated
application, provides drivers with extra benefits such as traffic throughput
maximization and collision avoidance. CACC systems must be designed in a way
that are sufficiently robust against all special maneuvers such as cutting-into
the CACC platoons by interfering vehicles or hard braking by leading cars. To
address this problem, a Neural- Network (NN)-based cut-in detection and
trajectory prediction scheme is proposed in the first part of this paper. Next,
a probabilistic framework is developed in which the cut-in probability is
calculated based on the output of the mentioned cut-in prediction block.
Finally, a specific Stochastic Model Predictive Controller (SMPC) is designed
which incorporates this cut-in probability to enhance its reaction against the
detected dangerous cut-in maneuver. The overall system is implemented and its
performance is evaluated using realistic driving scenarios from Safety Pilot
Model Deployment (SPMD).Comment: 10 pages, Submitted as a journal paper at T-I
Perancangan Aplikasi Informasi Multimedia Tanaman Buah Kebun Raya Bogor dengan Augmented Reality
Kebun Raya Bogor adalah salah satu tempat wisata botani, Selain sebagai tempat untuk mempelajari atau mendalami ilmu pengetahuan alam, Kebun Raya Indonesia merupakan salah satu lembaga yang bertanggung jawab terhadap konservasi ex-situ flora asli Indonesia mempunyai perananpenting dalam mempertahankan dan mengembangkan potensi tanaman buah yang ada. Terdapat tidak kurang dari 102 jenis tanaman buah. Media informasi yang terletak pada area perkebunan sudah tersedia namun untuk mencari informasi lebih lengkap tentang tumbuhan atau tanaman buah tersebut,pengunjung tidak bisa mendapatkannya secara langsung. Kurang lengkapnya informasi yang lebih detail pada area koleksi Kebun Raya Bogor membuat pengunjung tidak mengetahui manfaat lebih daritubuhan tersebut. Pengungjung harus mencari sendiri di perpustakaan atau informasi dari internet. Tanaman buah mempunyai rentang waktu dalam berbuah, pengujung akan sulit membayangkan jika pohon nya sedang tidak berbuah. Informasi lebih detail seperti ukuran, daun, bunga, buah secaramendetail tidak didapatkan di lokasi tumbuhan tersebut. karena media informasi yang ada hanya memaparkan informasi umum. Informasi multimedia dengan menerapkan teknologi augmented reality dapat menjadi solusi. Perancangan multimedia informasi ini mengunakan Metode Interactive Multimedia System Design Development (IMSDD) dengan penekanan bidang keilmuan desain antarmuka pengguna. Multimedia Informasi dengan memanfaatkan Augmented reality sebagai simulasi dari objek buah dapat memberikan informasi yang lengkap sesuai kebutuhan pengunjung. Informasi multimedia nantinya akan memanfaatkan aplikasi mobile sehingga pengunjung dapat melihat informasitersebut pada lokasi tubuhan buah dikebun yang sangat luas
A Learning-Based Framework for Two-Dimensional Vehicle Maneuver Prediction over V2V Networks
Situational awareness in vehicular networks could be substantially improved
utilizing reliable trajectory prediction methods. More precise situational
awareness, in turn, results in notably better performance of critical safety
applications, such as Forward Collision Warning (FCW), as well as comfort
applications like Cooperative Adaptive Cruise Control (CACC). Therefore,
vehicle trajectory prediction problem needs to be deeply investigated in order
to come up with an end to end framework with enough precision required by the
safety applications' controllers. This problem has been tackled in the
literature using different methods. However, machine learning, which is a
promising and emerging field with remarkable potential for time series
prediction, has not been explored enough for this purpose. In this paper, a
two-layer neural network-based system is developed which predicts the future
values of vehicle parameters, such as velocity, acceleration, and yaw rate, in
the first layer and then predicts the two-dimensional, i.e. longitudinal and
lateral, trajectory points based on the first layer's outputs. The performance
of the proposed framework has been evaluated in realistic cut-in scenarios from
Safety Pilot Model Deployment (SPMD) dataset and the results show a noticeable
improvement in the prediction accuracy in comparison with the kinematics model
which is the dominant employed model by the automotive industry. Both ideal and
nonideal communication circumstances have been investigated for our system
evaluation. For non-ideal case, an estimation step is included in the framework
before the parameter prediction block to handle the drawbacks of packet drops
or sensor failures and reconstruct the time series of vehicle parameters at a
desirable frequency
Outlier Detection Using Nonconvex Penalized Regression
This paper studies the outlier detection problem from the point of view of
penalized regressions. Our regression model adds one mean shift parameter for
each of the data points. We then apply a regularization favoring a sparse
vector of mean shift parameters. The usual penalty yields a convex
criterion, but we find that it fails to deliver a robust estimator. The
penalty corresponds to soft thresholding. We introduce a thresholding (denoted
by ) based iterative procedure for outlier detection (-IPOD). A
version based on hard thresholding correctly identifies outliers on some hard
test problems. We find that -IPOD is much faster than iteratively
reweighted least squares for large data because each iteration costs at most
(and sometimes much less) avoiding an least squares estimate.
We describe the connection between -IPOD and -estimators. Our
proposed method has one tuning parameter with which to both identify outliers
and estimate regression coefficients. A data-dependent choice can be made based
on BIC. The tuned -IPOD shows outstanding performance in identifying
outliers in various situations in comparison to other existing approaches. This
methodology extends to high-dimensional modeling with , if both the
coefficient vector and the outlier pattern are sparse
Analisa Finansial Pendirian Pabrik Pengolahan Kopi
IndonesianMau tidak mau, ekspor kopi Indonesia harus ditingkatkan karena ia merupakan salah satu komoditi ekspor non-migas penting. Tetapi mutunya masih rendah, sehingga harganya di pasar dunia masih rendah. Membuka kesempatan bagi pengusaha swasta untuk menanamkan modalnya di bidang pengolahan kopi adalah salah satu kemungkinan untuk mengatasi masalah mutu kopi Indonesia. Penelitian ini bertujuan untuk menilai kelayakan finansial investasi di bidang pengolahan kopi oleh swasta berbentuk Perseroan Terbatas berdasarkan kriteria NPV dan IRR. Hasil analisa menunjukkan bahwa investasi tersebut di daerah kopi Boja, Jawa Tengah adalah menguntungkan dengan NPV sebesar Rp. 124,9 juta dan IRR 27,1% dengan umur proyek 10 tahun. Namun proyek ini sangat sensitif terhadap Perubahan harga kopi dan tersedianya bahan baku kopi
- …