Showing papers in "Scientific Programming in 2016"

Adolescent Development (Perkembangan Remaja)

Abstract: Adolescent atau remaja merupakan periode kritis peralihan dari anak menjadi dewasa. Pada remaja terjadi perubahan hormonal, fisik, psikologis maupun sosial yang berlangsung secara sekuensial. Pada anak perempuan awitan pubertas terjadi pada usia 8 tahun sedangkan anak laki-laki terjadi pada usia 9 tahun. Faktor genetik, nutrisi, dan faktor lingkungan lainnya dianggap berperan dalam awitan pubertas. Perubahan fisik yang terjadi pada periode pubertas ini juga diikuti oleh maturasi emosi dan psikis. Secara psikososial, pertumbuhan pada masa remaja (adolescent) dibagi dalam 3 tahap yaitu early, middle, dan late adolescent. Masing-masing tahapan memiliki karakteristik tersendiri. Segala sesuatu yang mengganggu proses maturasi fisik dan hormonal pada masa remaja ini dapat mempengaruhi perkembangan psikis dan emosi sehingga diperlukan pemahaman yang baik tentang proses perubahan yang terjadi pada remaja dari segala aspek.

Virtual Machine Placement Algorithm for Both Energy-Awareness and SLA Violation Reduction in Cloud Data Centers

Abstract: The problem of high energy consumption is becoming more and more serious due to the construction of large-scale cloud data centers. In order to reduce the energy consumption and SLA violation, a new virtual machine VM placement algorithm named ATEA adaptive three-threshold energy-aware algorithm, which takes good use of the historical data from resource usage by VMs, is presented. In ATEA, according to the load handled, data center hosts are divided into four classes: hosts with little load, hosts with light load, hosts with moderate load, and hosts with heavy load. ATEA migrates VMs on heavily loaded or little-loaded hosts to lightly loaded hosts, while the VMs on lightly loaded and moderately loaded hosts remain unchanged. Then, on the basis of ATEA, two kinds of adaptive three-threshold algorithm and three kinds of VMs selection policies are proposed. Finally, we verify the effectiveness of the proposed algorithms by CloudSim toolkit utilizing real-world workload. The experimental results show that the proposed algorithms efficiently reduce energy consumption and SLA violation.

A Hybrid Programming Framework for Modeling and Solving Constraint Satisfaction and Optimization Problems

Abstract: This paper proposes a hybrid programming framework for modeling and solving of constraint satisfaction problems (CSPs) and constraint optimization problems (COPs). Two paradigms, CLP (constraint logic programming) and MP (mathematical programming), are integrated in the framework. The integration is supplemented with the original method of problem transformation, used in the framework as a presolving method. The transformation substantially reduces the feasible solution space. The framework automatically generates CSP and COP models based on current values of data instances, questions asked by a user, and set of predicates and facts of the problem being modeled, which altogether constitute a knowledge database for the given problem. This dynamic generation of dedicated models, based on the knowledge base, together with the parameters changing externally, for example, the user?s questions, is the implementation of the autonomous search concept. The models are solved using the internal or external solvers integrated with the framework. The architecture of the framework as well as its implementation outline is also included in the paper. The effectiveness of the framework regarding the modeling and solution search is assessed through the illustrative examples relating to scheduling problems with additional constrained resources.

Pernikahan Usia Dini dan Permasalahannya

Abstract: Kasus pernikahan usia dini banyak terjadi di berbagai penjuru dunia dengan berbagai latarbelakang. Telah menjadi perhatian komunitas internasional mengingat risiko yang timbul akibat pernikahan yang dipaksakan, hubungan seksual pada usia dini, kehamilan pada usia muda, dan infeksi penyakit menular seksual. Kemiskinan bukanlah satu-satunya faktor penting yang berperan dalam pernikahan usia dini. Hal lain yang perlu diperhatikan yaitu risiko komplikasi yang terjadi di saat kehamilan dan saat persalinan pada usia muda, sehingga berperan meningkatkan angka kematian ibu dan bayi. Selain itu, pernikahan di usia dini juga dapat menyebabkan gangguan perkembangan kepribadian dan menempatkan anak yang dilahirkan berisiko terhadap kejadian kekerasan dan keterlantaran. Masalah pernikahan usia dini ini merupakan kegagalan dalam perlindungan hak anak. Dengan demikian diharapkan semua pihak termasuk dokter anak, akan meningkatkan kepedulian dalam menghentikan praktek pernikahan usia dini

HSIP: A Novel Task Scheduling Algorithm for Heterogeneous Computing

Abstract: High-performance heterogeneous computing systems are achieved by the use of efficient application scheduling algorithms. However, most of the current algorithms have low efficiency in scheduling. Aiming at solving this problem, we propose a novel task scheduling algorithm for heterogeneous computing named HSIP (heterogeneous scheduling algorithm with improved task priority) whose functionality relies on three pillars: () an improved task priority strategy based on standard deviation with improved magnitude as computation weight and communication cost weight to make scheduling priority more reasonable; () an entry task duplication selection policy to make the makespan shorter; and () an improved idle time slots (ITS) insertion-based optimizing policy to make the task scheduling more efficient. We evaluate our proposed algorithm on randomly generated DAGs, using some real application DAGs by comparison with some classical scheduling algorithms. According to the experimental results, our proposed algorithm appears to perform better than other algorithms in terms of schedule length ratio, efficiency, and frequency of best results.

RVLBPNN: A Workload Forecasting Model for Smart Cloud Computing

Abstract: Given the increasing deployments of Cloud datacentres and the excessive usage of server resources, their associated energy and environmental implications are also increasing at an alarming rate. Cloud service providers are under immense pressure to significantly reduce both such implications for promoting green computing. Maintaining the desired level of Quality of Service (QoS) without violating the Service Level Agreement (SLA), whilst attempting to reduce the usage of the datacentre resources is an obvious challenge for the Cloud service providers. Scaling the level of active server resources in accordance with the predicted incoming workloads is one possible way of reducing the undesirable energy consumption of the active resources without affecting the performance quality. To this end, this paper analyzes the dynamic characteristics of the Cloud workloads and defines a hierarchy for the latency sensitivity levels of the Cloud workloads. Further, a novel workload prediction model for energy efficient Cloud Computing is proposed, named RVLBPNN (Rand Variable Learning Rate Backpropagation Neural Network) based on BPNN (Backpropagation Neural Network) algorithm. Experiments evaluating the prediction accuracy of the proposed prediction model demonstrate that RVLBPNN achieves an improved prediction accuracy compared to the HMM and Naive Bayes Classifier models by a considerable margin.

A Parallel Genetic Algorithm Based Feature Selection and Parameter Optimization for Support Vector Machine

Abstract: The extensive applications of support vector machines (SVMs) require efficient method of constructing a SVM classifier with high classification ability. The performance of SVM crucially depends on whether optimal feature subset and parameter of SVM can be efficiently obtained. In this paper, a coarse-grained parallel genetic algorithm (CGPGA) is used to simultaneously optimize the feature subset and parameters for SVM. The distributed topology and migration policy of CGPGA can help find optimal feature subset and parameters for SVM in significantly shorter time, so as to increase the quality of solution found. In addition, a new fitness function, which combines the classification accuracy obtained from bootstrap method, the number of chosen features, and the number of support vectors, is proposed to lead the search of CGPGA to the direction of optimal generalization error. Experiment results on 12 benchmark datasets show that our proposed approach outperforms genetic algorithm (GA) based method and grid search method in terms of classification accuracy, number of chosen features, number of support vectors, and running time.

Modified Bat Algorithm Based on Lévy Flight and Opposition Based Learning

Abstract: Bat Algorithm BA is a swarm intelligence algorithm which has been intensively applied to solve academic and real life optimization problems. However, due to the lack of good balance between exploration and exploitation, BA sometimes fails at finding global optimum and is easily trapped into local optima. In order to overcome the premature problem and improve the local searching ability of Bat Algorithm for optimization problems, we propose an improved BA called OBMLBA. In the proposed algorithm, a modified search equation with more useful information from the search experiences is introduced to generate a candidate solution, and Levy Flight random walk is incorporated with BA in order to avoid being trapped into local optima. Furthermore, the concept of opposition based learning OBL is embedded to BA to enhance the diversity and convergence capability. To evaluate the performance of the proposed approach, 16 benchmark functions have been employed. The results obtained by the experiments demonstrate the effectiveness and efficiency of OBMLBA for global optimization problems. Comparisons with some other BA variants and other state-of-the-art algorithms have shown the proposed approach significantly improves the performance of BA. Performances of the proposed algorithm on large scale optimization problems and real world optimization problems are not discussed in the paper, and it will be studied in the future work.

Research on Healthy Anomaly Detection Model Based on Deep Learning from Multiple Time-Series Physiological Signals

Abstract: Health is vital to every human being. To further improve its already respectable medical technology, the medical community is transitioning towards a proactive approach which anticipates and mitigates risks before getting ill. This approach requires measuring the physiological signals of human and analyzes these data at regular intervals. In this paper, we present a novel approach to apply deep learning in physiological signals analysis that allows doctor to identify latent risks. However, extracting high level information from physiological time-series data is a hard problem faced by the machine learning communities. Therefore, in this approach, we apply model based on convolutional neural network that can automatically learn features from raw physiological signals in an unsupervised manner and then based on the learned features use multivariate Gauss distribution anomaly detection method to detect anomaly data. Our experiment is shown to have a significant performance in physiological signals anomaly detection. So it is a promising tool for doctor to identify early signs of illness even if the criteria are unknown a priori.

Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time

Abstract: A parallel machine scheduling problem in plastic production is studied in this paper. In this problem, the processing time and arrival time are uncertain but lie in their respective intervals. In addition, each job must be processed together with a mold while jobs which belong to one family can share the same mold. Therefore, time changing mold is required for two consecutive jobs that belong to different families, which is known as sequence-dependent setup time. This paper aims to identify a robust schedule by min–max regret criterion. It is proved that the scenario incurring maximal regret for each feasible solution lies in finite extreme scenarios. A mixed integer linear programming formulation and an exact algorithm are proposed to solve the problem. Moreover, a modified artificial bee colony algorithm is developed to solve large-scale problems. The performance of the presented algorithm is evaluated through extensive computational experiments and the results show that the proposed algorithm surpasses the exact method in terms of objective value and computational time.

Masalah Emosi dan Perilaku pada Anak dan Remaja di Poliklinik Jiwa Anak dan Remaja RSUPN dr. Ciptomangunkusumo (RSCM), Jakarta

Abstract: Latar belakang. Anak dengan masalah emosi dan perilaku mempunyai kerentanan untuk mengalami hendaya dalam fungsi kehidupan sehari-hari, terutama dalam fungsi belajar dan sosialisasi. Masalah tersebut seringkali sulit dikenali oleh orangtua sehingga anak dengan masalah ini datang berobat dalam kondisi yang cukup berat. Tujuan. Untuk mengetahui persepsi orangtua terhadap perubahan emosi dan perilaku pada anak mereka pada saat berkonsultasi di Poliklinik Jiwa Anak dan Remaja RSCM Jakarta selama periode November 2009–Mei 2010. Metode. Penelitian deskriptif dengan menggunakan data sekunder dari catatan medik anak dan remaja di Poliklinik Anak dan Remaja RSCM, selama periode November 2009 – Mei 2010. Kriteria inklusi adalah, catatan medik lengkap mengenai data anak beserta orangtuanya, dan kuesioner Strength and Difficulties Questionaire (SDQ) diisi dengan lengkap. Hasil. Selama periode enam bulan didapatkan 161 subjek penelitian yang memenuhi kriteria yang sudah ditentukan. Enam puluh lima koma sembilan puluh persen dari seluruh subjek penelitian berada pada usia kurang dari 12 tahun dan mempunyai tingkat pendidikan setara dengan sekolah dasar. Proporsi terbesar adalah masalah hubungan dengan teman sebaya 54,81%, dan masalah emosional 42,2%. Kesimpulan. Masalah teman sebaya dan emosi merupakan masalah yang terbesar yang dijumpai pada pasien anak dan remaja yang datang berobat ke Poliklinik Jiwa Anak dan Remaja RSCM. Perlu dipertimbangkan untuk menerapkan suatu program keterampilan sosial di masyarakat atau sekolah sehingga diharapkan dapat menurunkan masalah ini di kemudian hari.

Hubungan Status Gizi dan Perkembangan Anak Usia 1 - 2 Tahun

Abstract: Latar belakang. Pada umumnya usia 1-2 tahun pertama kehidupan akan menentukan kualitas hidup anak di kemudian hari. Tujuan. Mengetahui gambaran perkembangan anak usia 1-2 tahun dan status gizi. Metode. Penelitian dilakukan di tiga Puskesmas Garuda, Ibrahim Aji, dan Puter yang terdiri dari 24 Posyandu di Kabupaten Bandung. Penelitian dilakukan dilakukan secara cross sectionaldengan subjek anak usia 1-2 tahun yang sehat dan kooperatif pada saat pemeriksaan, serta orang tua menyetujui ikut dalam penelitian. Tes perkembangan dilakukan oleh satu dokter anak dan dua dokter (residen) dengan menggunakan KPSP (Kuesioner Pra Skrening Perkembangan). Empat aspek perkembangan yang dinilai yaitu motorik kasar, motorik halus, bicara dan bahasa, sosial dan kemandirian. Penelitian dilakukan dari tanggal 15 November 2010 sampai 30 November 2010. Hasil. Jumlah subjek 321 anak usia 1–2 tahun dan yang memenuhi kriteria inklusi 308 anak, terdiri dari 164 laki-laki (53,2%) dan 144 perempuan (46,8%). Anak yang mengalami perkembangan normal 278 anak (90,22%) dan meragukan 30 anak (9,78%). Sedangkan status gizi dinilai berdasarkan BB/PB, hasil normal 277 anak (89,9%) dan kurus 31 anak (10,10%). Dari 31 anak dengan status gizi kurang, di antara 2 anak di antaranya mengalami perkembangan meragukan dan dari 28 anak dengan perkembangan meragukan mempunyai status gizi normal. Kesimpulan .Tidak terdapat hubungan antara gangguan perkembangan dengan status gizi (p=0,394) begitu juga dengan status gizi dengan kondisi ekonomi (p=2,500) dan perkembangan dengan status ekonomi (p=0,336). Dari perkembangan dengan nilai meragukan adalah motorik kasar (6,17%), motorik halus (0,65%), bicara dan bahasa (4,54%), serta sosialisasi dan kemandirian (2,92%). Faktor-faktor yang berhubungkan dengan status perkembangan adalah umur anak (p=0,009). Perlu upaya untuk mengevaluasi perkembangan yang meragukan dan perlu penelitian lanjut dengan pembanding.

Perubahan Epidemiologi Demam Berdarah Dengue Di Indonesia

Abstract: Dengue berdarah dengue yang ditularkan melalui vektor nyamuk Aedes aegypty masih merupakan masalah kesehatan penting di dunia. Di Indonesia, demam berdarah dengue mulai dikenal pertama kali pada tahun 1968 di DKI Jakarta dan Surabaya, dan terus menyebar ke seluruh tiga puluh tiga propinsi di Indonesia. Pola epidemiologi infeksi dengue mengalami perubahan dari tahun ke tahun, jumlah kasus memuncak setiap siklus 10 tahunan. Dari tahun 1968-2008 angka kesakitan demam berdarah dengue terus meningkat. Pada tahun 2008 didapatkanangka kesakitan 58,85/ 100.000 penduduk. Angka kematian menurun dengan stabil dari 41% pada tahun 1968 menjadi kurang dari 2% sejak tahun 2000, dan pada tahun 2008 angka kematian menurun menjadi 0,86%.Semua serotipe virus dengue ditemukan di Indonesia, namun serotipe virus den-3 masih dominan menyebabkan kasus dengue yang berat dan fatal. Surveilans epidemiologi, dukungan edukasi masyarakat dan program pengendalian vektor diperlukan untuk mencegah transmisi. Pengembangan vaksin dengue merupakan salah satu upaya mencegah penyakit dengue.

Kecerdasan Majemuk pada Anak

Abstract: Kecerdasan majemuk pertama kali diperkenalkan tahun 1983 oleh Howard Gardner di Harvard School of Education and Harvard Project Zero. Teori ini membantah tes seperti contoh Stanford Binet Test yang dikatakan sebagai hitungan tradisional yang tidak adekuat menilai kecerdasan. Menurut Gardner, kecerdasan melebihi dari hanya sekedar IQ (Intelligence Quotient) karena IQ yang tinggi tanpa ada produktifitas bukan merupakan kecerdasan yang baik. Anak harus dinilai berdasarkan apa yang mereka dapat kerjakan bukan apa yang tidak dapat mereka kerjakan. Kecerdasan didefinisikan sebagai kemampuan untuk memecahkan masalah dan memiliki nilai lebih dalam sebuah kultur masyarakat. Kecerdasan adalah potensi biopsikologikal untuk mengolah informasi sehingga dapat memecahkan masalah, menciptakan hasil baru yang menambah nilainilai budaya setempat. Pandangan baru ini sangat berbeda dengan pandangan lama yang selalu mengandalkan dua penilaian yaitu verbal dan komputasional. Delapan macam kecerdasan itu antara lain, (1) Kecerdasan linguistik, (2) Kecerdasan logika-matematika, (3) Kecerdasan gerak tubuh, (4) Kecerdasan musikal, (5) Kecerdasan visual-spasial, (6) Kecerdasan interpersonal, (7) Kecerdasan intrapersonal, dan (8) Kecerdasan naturalis.

Task Classification Based Energy-Aware Consolidation in Clouds

Abstract: We consider a cloud data center, in which the service provider supplies virtual machines (VMs) on hosts or physical machines (PMs) to its subscribers for computation in an on-demand fashion. For the cloud data center, we propose a task consolidation algorithm based on task classification (i.e., computation-intensive and data-intensive) and resource utilization (e.g., CPU and RAM). Furthermore, we design a VM consolidation algorithm to balance task execution time and energy consumption without violating a predefined service level agreement (SLA). Unlike the existing research on VM consolidation or scheduling that applies none or single threshold schemes, we focus on a double threshold (upper and lower) scheme, which is used for VM consolidation. More specifically, when a host operates with resource utilization below the lower threshold, all the VMs on the host will be scheduled to be migrated to other hosts and then the host will be powered down, while when a host operates with resource utilization above the upper threshold, a VM will be migrated to avoid using 100% of resource utilization. Based on experimental performance evaluations with real-world traces, we prove that our task classification based energy-aware consolidation algorithm (TCEA) achieves a significant energy reduction without incurring predefined SLA violations.

Prevalensi Gangguan Tidur pada Remaja Usia 12-15 Tahun di Sekolah Lanjutan Tingkat Pertama

Abstract: Latar belakang. Gangguan tidur dinilai dari gangguan dalam jumlah, kualitas, atau waktu tidur. Gangguan tidur banyak ditemukan pada remaja (73,4%), namun belum banyak dilakukan di Indonesia. Tujuan. Mengetahui prevalensi gangguan tidur pada remaja usia 12-15 tahun di SLTP “X”, Kelurahan Jati, Jakarta Timur. Metode. Studi potong lintang dilakukan terhadap 140 pelajar SLTPN 92 di Kelurahan Jati, Jakarta Timur pada bulan Mei 2009, dengan teknik stratified purposive sampling. Pengambilan data dilakukan menggunakan kuesioner Sleep Disturbance Scale for Children (SDSC) yang diisi secara self-administered oleh orang tua beserta anak di rumah. Hasil. Prevalensi gangguan tidur didapatkan 62,9%, dengan gangguan transisi bangun-tidur sebagai jenis gangguan yang paling sering ditemui. Separuh subjek memiliki perbedaan waktu bangun antara hari sekolah dengan hari libur, 72,9% memiliki perbedaan waktu tidur yang tidak signifikan. Separuh subjek tidur cukup selama hari sekolah, dan 65% di hari libur. Aktivitas yang menenangkan sebelum tidur dilakukan oleh 73,6% subjek. Uji kemaknaan menunjukkan hubungan antara gangguan tidur dengan durasi tidur di hari sekolah dan aktivitas di tempat tidur (p<0,05). Tidak ada hubungan antara perbedaan waktu bangun atau tidur hari sekolah dengan hari libur, durasi tidur di hari libur, kebiasaan konsumsi minuman berkafein, dan lingkungan dengan gangguan tidur (p<0,05). Kesimpulan. Gangguan tidur banyak ditemukan pada remaja usia 12-15 tahun. Sleep Disturbance Scale for Children dapat digunakan sebagai uji tapis dalam mendeteksi gangguan tidur pada remaja

Hipertensi pada Remaja

Abstract: Pengukuran tekanan darah saat pemeriksaan kesehatan rutin terhadap remaja akan memungkinkan ditemukannya hipertensi asimptomatik yang signifikan oleh karena penyakit yang tidak diketahui, dan memperkuat pernyataan bahwa sering terjadi kenaikan tekanan darah yang ringan pada remaja. Penyebab hipertensi pada remaja (usia 13-18 tahun) yang paling sering adalah hipertensi esensial (80%), diikuti penyakit ginjal. Hipertensi esensial pada remaja dapat merupakan lanjutan dari masa kanak-kanak dan berlanjut ke masa dewasa. Remaja dengan tekanan darah di atas persentil ke-90 menurut umur memerlukan pemeriksaan berkala. Remaja dengan hipertensi ringan yang asimptomatik hanya memerlukan pemeriksaan yang sederhana. Tujuan tata laksana hipertensi pada remaja, untuk menurunkan tekanan darah di bawah persentil ke-95 dan mencegah komplikasi. Tata laksana ini mencakup non farmakologik dan farmakologik

Pengaruh Perkembangan Bahasa Terhadap Perkembangan Kognitif Anak Usia 1-3 Tahun

Abstract: Latar belakang .Kemampuan bahasa merupakan salah satu indikator perkembangan kognitif anak. Deteksi dini masalah perkembangan anak sangat menentukan keberhasilan dalam memaksimalkan plastisitas otak pada kompensasi penyimpangan perkembangan. Tujuan .Mengetahui pengaruh perkembangan bahasa terhadap perkembangan kognitif anak usia 1-3 tahun. Metode. Penelitian potong lintang pada kunjungan pasien Poliklinik Tumbuh Kembang Anak RS Dr. Kariadi Semarang, usia subjek 1-3 tahun. Kriteria inklusi keterlambatan bicara, gizi baik, tidak memiliki kelainan kongenital, gangguan neurologi, dan gangguan pendengaran. Dilakukan pemeriksaan kemampuan bahasa dengan Denver II kemudian ditentukan DQ (developmental quotients)menggunakan CAPUTE scale. Untuk menentukan gangguan pendengaran dilakukan konsultasi dengan Bagian THT dan pemeriksaan BERA. Datadianalisissecara statistik dengan uji-t. Hasil. Didapatkan kasus (n=36) dan kontrol (n=36), jumlah sampel laki-laki pada kasus 77.8%. Pada kelompok kontrol rerata DQ CAT(cognitive adaptive test)91,4 (SD+5,6),CLAMS (clinical linguistic & auditory milestone scale)90,1 (SD+6,1) sedangkan pada kasus rerata DQCAT82,7 (SD+6,7),CLAMS57,9 (SD+11,2). Hasil Uji-tdidapatadjustedR 2 0,415 (p=0,000). Kesimpulan. Terdapat pengaruh perkembangan bahasa terhadap perkembangan kognitif pada anak usia 1-3 tahun

Kuesioner Praskrining Perkembangan (KPSP) Anak

Abstract: Latar belakang. Masalah perkembangan anak seperti gangguan berbahasa, perilaku, autisme, saat ini makin meningkat dan sebagai upaya untuk menurunkan angka kejadiannya diperlukan deteksi dini. Skrining merupakan cara deteksi dini yang efektif, namun hal ini masih jarang dilakukan oleh dokter mungkin karena keterbatasan waktu dan biaya. Tujuan. Untuk mengetahui efektivitas KPSP sebagai alat praskrining perkembangan anak. Metoda. Merupakan penelitian cross sectional yang dilakukan pada Desember 2003 sampai Februari 2004 terhadap orang tua yang mempunyai anak umur 15-18 bulan di daerah kumuh wilayah kerja Puskesmas Padasuka, Kiaracondong dan Garuda Kota Bandung. Kuesioner yang digunakan adalah KPSP dan Denver II, yang dilakukan oleh tenaga terlatih. Hasil. Diantara 494 anak, diduga mengalami gangguan perkembangan 73 anak (15%) menurut KPSP dan 57 anak (12%) menurut Denver II. Sensitivitas dan spesifisitas KPSP masing-masing 60% dan 92%. Kesimpulan. Penggunaan KPSP dapat menimbulkan underdetection. Sebaiknya dilakukan revisi terhadap KPSP yang disesuaikan dengan Parent Developmental Questions (PDQ) II yang merupakan pengembangan Denver II. Penelitian sebaiknya dilakukan tidak hanya di daerah kumuh.

WSF2: a novel framework for filtering web spam

Abstract: Over the last years, research on web spam filtering has gained interest from both academia and industry. In this context, although there are a good number of successful antispam techniques available (i.e., content-based, link-based, and hiding), an adequate combination of different algorithms supported by an advanced web spam filtering platform would offer more promising results. To this end, we propose the WSF2 framework, a new platform particularly suitable for filtering spam content on web pages. Currently, our framework allows the easy combination of different filtering techniques including, but not limited to, regular expressions and well-known classifiers (i.e., Naive Bayes, Support Vector Machines, and C5.0). Applying our WSF2 framework over the publicly available WEBSPAM-UK2007 corpus, we have been able to demonstrate that a simple combination of different techniques is able to improve the accuracy of single classifiers on web spam detection. As a result, we conclude that the proposed filtering platform is a powerful tool for boosting applied research in this area.

Hubungan antara Curah Hujan dan Peningkatan Kasus Demam Berdarah Dengue Anak di Kota Palembang

Abstract: Latar belakang. Dampak curah hujan terhadap prevalensi dengue sangat penting untuk diteliti sebagai alat untuk meramalkan variasi insidens dan risiko yang berhubungan dengan dampak perubahan iklim. Tujuan. Untuk menilai apakah peningkatan curah hujan di Palembang, setelah selang waktu tertentu, berhubungan dengan peningkatan jumlah kasus DBD anak yang dirawat di tiga rumah sakit di Palembang. Kedua, menilai hubungan puncak curah hujan dengan puncak kasus DBD yang dirawat. Jumlah kasus DBD yang dirawat di tiga rumah sakit tersebut diasumsikan mencerminkan tingkat kejadian DBD di Kota Palembang. Metode .Data curah hujan didapat dari Badan Meteorologi Klimatologi dan Geofisika kota Palembang. Prevalensi DBD yang dirawat dikompilasikan dari buku/Data Register. Hubungan peningkatan curah hujan dengan peningkatan jumlah kasus DBD ditelusuri melalui olah statistik. Hubungan puncak curah hujan dengan puncak kasus DBD yang dirawat dinilai berdasarkan selang waktu antara puncak curah hujan dan puncak prevalensi perawatan kasus. Hasil .Terdapat korelasi antara curah hujan dan peningkatan jumlah kasus DBD yang dirawat. Korelasi mulai terjadi satu bulan sebelum puncak curah hujan (r=0,332; p=0,001), meningkat saat puncak curah hujan (r=0,353; p=0,000), dan menurun satu bulan sesudahnya (r=0,262; p=0,008). Bulan serta tanggal curah hujan berhimpitan dengan prevalensi kasus yang DBD yang dirawat. Anomali bulan puncak hujan diikuti perubahan puncak prevalensi DBD. Kesimpulan. 1) Curah hujan berkorelasi dengan kejadian DBD, korelasi paling kuat terjadi dengan kasus DBD pada puncak curah hujan; 2) Puncak curah hujan bulanan berhimpitan dengan bulan puncak kasus DBD dan perubahan puncak curah hujan sejalan dengan perubahan puncak kasus DBD

Cloud Model Approach for Lateral Control of Intelligent Vehicle Systems

Abstract: Studies on intelligent vehicles, among which the controlling method of intelligent vehicles is a key technique, have drawn the attention of industry and the academe. This study focuses on designing an intelligent lateral control algorithm for vehicles at various speeds, formulating a strategy, introducing the Gauss cloud model and the cloud reasoning algorithm, and proposing a cloud control algorithm for calculating intelligent vehicle lateral offsets. A real vehicle test is applied to explain the implementation of the algorithm. Empirical results show that if the Gauss cloud model and the cloud reasoning algorithm are applied to calculate the lateral control offset and the vehicles drive at different speeds within a direction control area of ±7°, a stable control effect is achieved.

On Elasticity Measurement in Cloud Computing

Abstract: Elasticity is the foundation of cloud performance and can be considered as a great advantage and a key benefit of cloud computing. However, there is no clear, concise, and formal definition of elasticity measurement, and thus no effective approach to elasticity quantification has been developed so far. Existing work on elasticity lack of solid and technical way of defining elasticity measurement and definitions of elasticity metrics have not been accurate enough to capture the essence of elasticity measurement. In this paper, we present a new definition of elasticity measurement and propose a quantifying and measuring method using a continuous-time Markov chain (CTMC) model, which is easy to use for precise calculation of elasticity value of a cloud computing platform. Our numerical results demonstrate the basic parameters affecting elasticity as measured by the proposed measurement approach. Furthermore, our simulation and experimental results validate that the proposed measurement approach is not only correct but also robust and is effective in computing and comparing the elasticity of cloud platforms. Our research in this paper makes significant contribution to quantitative measurement of elasticity in cloud computing.

A Multiple Classifier Fusion Algorithm Using Weighted Decision Templates

Abstract: Fusing classifiers’ decisions can improve the performance of a pattern recognition system. Many applications areas have adopted the methods of multiple classifier fusion to increase the classification accuracy in the recognition process. From fully considering the classifier performance differences and the training sample information, a multiple classifier fusion algorithm using weighted decision templates is proposed in this paper. The algorithm uses a statistical vector to measure the classifier’s performance and makes a weighed transform on each classifier according to the reliability of its output. To make a decision, the information in the training samples around an input sample is used by the k-nearest-neighbor rule if the algorithm evaluates the sample as being highly likely to be misclassified. An experimental comparison was performed on 15 data sets from the KDD’99, UCI, and ELENA databases. The experimental results indicate that the algorithm can achieve better classification performance. Next, the algorithm was applied to cataract grading in the cataract ultrasonic phacoemulsification operation. The application result indicates that the proposed algorithm is effective and can meet the practical requirements of the operation.

Two-Phase Algorithm for Optimal Camera Placement

Abstract: As markers for visual sensor networks have become larger, interest in the optimal camera placement problem has continued to increase. The most featured solution for the optimal camera placement problem is based on binary integer programming (BIP). Due to the NP-hard characteristic of the optimal camera placement problem, however, it is difficult to find a solution for a complex, real-world problem using BIP. Many approximation algorithms have been developed to solve this problem. In this paper, a two-phase algorithm is proposed as an approximation algorithm based on BIP that can solve the optimal camera placement problem for a placement space larger than in current studies. This study solves the problem in three-dimensional space for a real-world structure.

A Dynamic Pricing Reverse Auction-Based Resource Allocation Mechanism in Cloud Workflow Systems

Abstract: Market-oriented reverse auction is an efficient and cost-effective method for resource allocation in cloud workflow systems since it can dynamically allocate resources depending on the supply-demand relationship of the cloud market However, during the auction the price of cloud resource is usually fixed, and the current resource allocation mechanisms cannot adapt to the changeable market properly which results in the low efficiency of resource utilization To address such a problem, a dynamic pricing reverse auction-based resource allocation mechanism is proposed During the auction, resource providers can change prices according to the trading situation so that our novel mechanism can increase the chances of making a deal and improve efficiency of resource utilization In addition, resource providers can improve their competitiveness in the market by lowering prices, and thus users can obtain cheaper resources in shorter time which would decrease monetary cost and completion time for workflow execution Experiments with different situations and problem sizes are conducted for dynamic pricing-based allocation mechanism DPAM on resource utilization and the measurement of Time⁎Cost TC The results show that our DPAM can outperform its representative in resource utilization, monetary cost, and completion time and also obtain the optimal price reduction rates

Robust Optimization on Regional WCO-for-Biodiesel Supply Chain under Supply and Demand Uncertainties

Abstract: This paper aims to design a robust waste cooking oil- WCO- for-biodiesel supply chain under WCO supply and price as well as biodiesel demand and price uncertainties, so as to improve biorefineries’ ability to cope with the poor environment. A regional supply chain is firstly introduced based on the biggest WCO-for-biodiesel company in Changzhou, Jiangsu province, and it comprises three components: WCO supplier, biorefinery, and demand zone. And then a robust mixed integer linear model with multiple objectives economic, environmental, and social objectives is proposed for both biorefinery location and transportation plans. After that, a heuristic algorithm based on genetic algorithm is proposed to solve this model. Finally, the 27 cities in Yangtze River delta are adopted to verify the proposed models and methods, and the sustainability and robustness of biodiesel supply are discussed.

A Heuristic Task Scheduling Algorithm for Heterogeneous Virtual Clusters

Abstract: Cloud computing provides on-demand computing and storage services with high performance and high scalability. However, the rising energy consumption of cloud data centers has become a prominent problem. In this paper, we first introduce an energy-aware framework for task scheduling in virtual clusters. The framework consists of a task resource requirements prediction module, an energy estimate module, and a scheduler with a task buffer. Secondly, based on this framework, we propose a virtual machine power efficiency-aware greedy scheduling algorithm (VPEGS). As a heuristic algorithm, VPEGS estimates task energy by considering factors including task resource demands, VM power efficiency, and server workload before scheduling tasks in a greedy manner. We simulated a heterogeneous VM cluster and conducted experiment to evaluate the effectiveness of VPEGS. Simulation results show that VPEGS effectively reduced total energy consumption by more than 20% without producing large scheduling overheads. With the similar heuristic ideology, it outperformed Min-Min and RASA with respect to energy saving by about 29% and 28%, respectively.

Qu'est-ce que l'éditorialisation ?

Abstract: Cet article presente les resultats de huit ans de travail sur le concept d'editorialisation, realises dans le cadre du seminaire international « Ecritures numeriques et editorialisation » que j'ai coorganise avec Nicolas Sauret depuis 2008. Je propose de definir l'editorialisation comme l'ensemble des dynamiques qui produisent l'espace numerique. Ces dynamiques peuvent etre comprises comme les interactions d'actions individuelles et collectives avec un environnement numerique. A partir de cette definition, je propose de decrire le fonctionnement des instances d'autorite dans l'espace numerique.

Faktor Risiko yang Berperan pada Mortalitas Sepsis

Abstract: Latar belakang. Sepsis merupakan penyebab utama kematian bayi dan anak. Status imun pejamu dan malnutrisi merupakan faktor penting yang menentukan luaran pada sepsis. Skor pediatric logistic organ dysfunction (PELOD) adalah sistem skoring disfungsi organ pada sakit kritis, untuk memprediksi mortalitas pasien sepsis. Tujuan. Mengetahui faktor risiko usia, status gizi, dan skor PELOD terhadap mortalitas sepsis. Metode . Retrospektif analitik berupa data rekam medis pasien berusia 1 bulan – 18 tahun di PICU RSCM bulan Apri1- Agustus 2011 dengan diagnosis sepsis menurut kriteria konsensus sepsis internasional. Hasil. Sembilanpuluh dua dari 209 pasien mengalami sepsis, 22 (23,9%) di antaranya meninggal. Median usia subjek 15 (rentang 2-192) bulan dengan sebaran terbanyak pada kelompok usia 1 bulan – 1 tahun (62%). Sebagian besar subjek (57,61%) memiliki status gizi kurang. Fokus infeksi tersering adalah infeksi saraf pusat dan gastrointestinal, masing-masing 32 (34,77%) subjek. Gizi buruk (p<0,001; OR 26,88;IK95% 4,74-152,61) dan skor PELOD ≥20 (p<0,001; OR 78,8;IK95%14,23-436,36) merupakan faktor risiko yang secara independen berperan terhadap mortalitas sepsis pada anak. Kesimpulan. Gizi buruk dan skor PELOD ≥20 berperan terhadap mortalitas sepsis pada anak. Usia <5 tahun tidak terbukti sebagai faktor risiko mortalitas sepsis pada anak.