Simulation of Energy Consumption in Multi Cluster Wireless Sensor Networks

Energy conserving protocols in wireless sensor networks (WSNs), such as S-MAC, introduce multi-cluster network. The border nodes in multi cluster WSNs have more active time than the other nodes in the network; hence have more energy depletion rate. Since battery replacement in most networks is considered difficult, one or more nodes running out of energy prematurely will affect the network connectivity and decrease the overall network performance severely. This paper aims to (1) analyze the energy consumption in a multi-cluster sensor network and compare it to the single cluster scenario (2) investigate the merging time in a single cluster network. The result shows that, in average the energy needed to deliver a packet in the multi cluster networks is about 150% more than the energy needed in the single cluster networks. Moreover, the merging time in the single cluster network using schedule offset as the merging criteria in average is slightly smaller than one in the network using schedule ID as the merging criteria

SIMULATION OF ENERGY CONSUMPTION IN MULTI CLUSTER WIRELESS SENSOR NETWORKS

Energy conserving protocols in wireless sensor networks (WSNs), such as S-MAC, introduce multi-cluster network. The border nodes in multi cluster WSNs have more active time than the other nodes in the network; hence have more energy depletion rate. Since battery replacement in most networks is considered difficult, one or more nodes running out of energy prematurely will affect the network connectivity and decrease the overall network performance severely. This paper aims to (1) analyze the energy consumption in a multi-cluster sensor network and compare it to the single cluster scenario (2) investigate the merging time in a single cluster network. The result shows that, in average the energy needed to deliver a packet in the multi cluster networks is about 150% more than the energy needed in the single cluster networks. Moreover, the merging time in the single cluster network using schedule offset as the merging criteria in average is slightly smaller than one in the network using schedule ID as the merging criteria

Penentuan Prioritas pada Jaringan Back-bone Palapa Ring Menggunakan Derajat Node dan Cut Vertex

Palapa Ring is a project aiming to connect provinces and cities in Indonesia via a high data speed telecommunication path. The purpose of this  research is to identify the priority scale of each node in Palapa Ring Backbone network by considering the degree of each node and the cut vertices of the network. The result shows that the existing infrastructure in Palapa Ring comprised 48 nodes and 117 links. The nodes with the highest degree in the network were PBR, PTK, BJM, JK, SB and UP, with each of the nodes was connected to four links. Cut vertices in the network consisted of 22 nodes. The nodes in the network are classified into 4 categories. Five nodes (PBR, PTK, BJM, SB and UP) fell into the 1st priority group, two nodes (JK,MDN) fell into the 2nd priority group, 16 nodes fell into the 3rd priority group and the rest fell into the non priority group

Implementasi Deteksi dan Pengenalan Wajah pada Sistem Ujian Online Menggunakan Metode Deep Learning Berbasis Raspberry Pi

Penelitian ini bertujuan untuk mengembangkan sistem yang secara otomatis dapat mengenali peserta dalam tes berbasis online untuk efisiensi waktu dan biaya. Sistem ini terdiri dari Raspberry Pi untuk menjalankan algoritma pengenalan wajah, Kamera Pi untuk menangkap gambar peserta dan server lokal untuk menyimpan data peserta. Pada tahap awal penelitian, dibangun sebuah dataset yang berisi foto terbaru peserta dan id peserta. Dataset ini kemudian digunakan dalam proses pembelajaran menggunakan algoritma haarcascade yang merupakan bagian dari metode deep learning untuk menghasilkan sebuah model. Pada tahap pengenalan, gambar peserta dibandingkan dengan model. Peserta yang berhasil dikenali akan secara otomatis dialokasikan ke komputer yang tersedia. Pengujian menunjukkan bahwa sistem berhasil mengenali peserta tes dan yang bukan peserta tes

Emulasi Aplikasi Pemantauan Ruangan Melalui Handphone Menggunakan Webcam

This paper describes implementation of GPRS and Java 2 Micro Edition (J2ME) technology in room monitoring application via mobile phone and webcam. The webcam, which is connected to a server, captures picture periodically. A mobile phone, which has GPRS feature and supports J2ME technology, is used to access the picture. Experiments were done using Nokia 3300 emulator in a local area network. The transfer rate time for a 36 KB picture is 0.9 second.The experiment's result shows that the system is only suitable for low frame rate room monitoring

DISAIN SISTEM PENGINDERAAN LEVEL INTENSITAS CURAH HUJAN BERBASIS MINICOMPUTER

Intensitas curah hujan mempunyai peran yang penting bagi pertanian di Indonesia, terutama pada daerah-daerah potensial lahan kering. Penelitian ini bertujuan membangun sebuah sistem yang dapat memonitor curah hujan dan melaporkannya secara otomatis ke sebuah komputer server yang daoat diakses oleh setiap pihak yang membutuhkan. Protoype sistem yang dibangun terdiri dari sensor ultrasonic dan minicomputer Raspberry Pi 3 mode B+ yang terhubung ke jaringan internet. Raspberry Pi mengakses sensor ultrasonic untuk membaca level ketinggian air pada wadah penampung curah hujan secara berkala, mengolahnya untuk mendapatkan data curah hujan dan menyimpan data tersebut dalam sebuah database. Sebuah server pusat bertugas untuk mengumpulkan data curah hujan dari setiap titik pengambilan sampel. Publik dapat mengakses data sensing dari tiap wilayah menggunakan teknologi website

Integrating genetic analysis of mixed populations with a spatially explicit population dynamics model

1. Inferring the dynamics of populations in time and space is a central challenge in ecology. Intra-specific structure (for example genetically distinct sub-populations or meta-populations) may require methods that can jointly infer the dynamics of multiple populations. This is of particular importance for harvested species, for which management must balance utilization of productive populations with protection of weak ones. 2. Here we present a novel method for simultaneous learning about the spatio-temporal dynamics of multiple populations that combines genetic data with prior information about abundance and movement, akin to an integrated population modelling approach. We apply the Bayesian genetic mixed stock analysis to 17 wild and 10 hatchery-reared Baltic salmon (S. salar) stocks, quantifying uncertainty in stock composition in time and space, and in population dynamics parameters such as migration timing and speed. 3. The genetic data were informative about stock-specific movement patterns, updating priors for migration path, timing and speed. Use of a population dynamics model allowed robust interpolation of expected catch composition at areas and times with no genetic observations. Our results indicate that the commonly used "equal prior probabilities" assumption may not be appropriate for all mixed stock analyses: incorporation of prior information about stock abundance and movement resulted in more plausible and precise estimates of mixture compositions in time and space. 4. The model we present here forms the basis for optimizing the spatial and temporal allocation of harvest to support the management of mixed populations of migratory species.Peer reviewe

predicting her2 status in esophagogastric cancer development and validation of an easy to use nomogram

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