1,720,955 research outputs found
Diagram Kendali Max-XbarS^tn Dan EWMA-Max^tn Untuk Memonitor Mean Dan Variabilitas Proses
No full textDiagram kendali merupakan teknik yang paling sering digunakan dalam bidang industri untuk memonitor proses sebagai dasar perbaikan kualitas. Penelitian ini mengembangkan diagram kendali variabel berdasarkan inspeksi atribut, yaitu Max-XbarS^tn dan EWMA-Max^tn untuk mengevaluasi stabilitas mean dan variabilitas proses dalam satu diagram. Manfaat utama dari inspeksi atribut adalah kemudahan dan biaya yang relatif lebih murah dibandingkan tipe inspeksi variabel yang menggunakan nilai aktual. Selain itu, memonitor mean dan variabilitas proses dalam satu diagram dinilai efisien. Karakteristik kualitas diinspeksi menggunakan alat go/no go dengan menggunakan lima kategori. Dalam praktiknya, sebuah sampel berukuran n diambil secara periodik dan setiap item dialokasikan ke dalam salah satu kategori dengan batas-batas go/no go yang telah disesuaikan, selanjutnya sebuah nilai dibangkitkan secara random untuk setiap item berdasarkan distribusi normal truncated dengan batas atas dan batas bawah truncated sesuai dengan dimensi dari alat go/no go. Evaluasi kinerja dilakukan dengan menggunakan simulasi Monte Carlo. Diagram kendali Max-XbarS^tn memiliki performa yang baik dalam mendeteksi pergeseran proses yang besar dan efisiensinya terkonfirmasi dengan menambahkan ukuran sampel. Sementara, diagram kendali EWMA-Max^tn memiliki performa yang baik dalam mendeteksi pergeseran proses yang kecil maupun besar. Oleh karena itu, diagram kendali Max-XbarS^tn dan EWMA-Max^tn dapat dipertimbangkan sebagai alternatif yang kompetitif untuk diagram kendali variabel dengan tipe inspeksi variabel atau pengukuran secara langsung. Penerapan diagram kendali Max-XbarS^tn dan EWMA-Max^tn pada data lebar celah ends cincin piston di PT X menunjukkan bahwa proses tidak terkendali secara statistik yang umumnya disebabkan oleh peningkatan mean proses.
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Control charts are the most often technique used in the industry to continuously monitor a process for quality improvement. This study proposes a variable control chart based on attribute inspection, denoted as Max-XbarS^tn and EWMA-Max^tn, to evaluate the stability of mean and variability process using a single chart. The main advantage of using the attribute inspection is its ease of use and lower costs required compared to the variable-type inspection that using the actual value. In addition, monitoring mean and variability process using a single chart is considered efficient. Quality characteristics are monitored using a go/no go gauge with five categories. In practice, a sample with the size of n is taken periodically and each item is allocated to one of five categories with adjusted go/no go boundaries, then a value is generated randomly for each item based on a truncated normal distribution with an upper and a lower truncated limit according to the dimensions of go/no go gauge. The performance evaluation is carried out using the Monte Carlo simulation. The Max-XbarS^tn chart excels at detecting large process shifts and its efficiency is confirmed by adding the sample size. Meanwhile, the EWMA-Max^tn chart excels in detecting small and large process shifts. Therefore, the proposed Max-XbarS^tn and EWMA-Max^tn charts can be considered as a competitive alternative to the variable control charts with variable-type inspection or direct measurement. The application of Max-XbarS^tn and EWMA-Max^tn charts on the width of ends gap of piston ring at PT X shows that the process is not statistically controlled generally caused by an increase in the process mean
Klasifikasi Ictal dan Interictal Berdasarkan Rekaman EEG pada Pasien Epilepsi di Rumah Sakit Universitas Airlangga Menggunakan Smooth Support Vector Machine
No full textEpilepsi merupakan salah satu gangguan neurologi yang ditandai dengan serangan kejang berulang. Peningkatan risiko serangan epilepsi dapat digambarkan dengan menggunakan EEG (electroencephalogram), yaitu rekaman aktivitas listrik sepanjang kulit kepala yang dihasilkan oleh penembakan neuron dalam otak selama periode tertentu. Klinis dengan kejang (ictal) dan klinis tanpa kejang (interictal) berdasarkan rekaman EEG perlu diklasifikasikan untuk mempermudah tenaga medis dalam memberikan treatment kepada pasien epilepsi. Namun, hasil analisa rekaman EEG secara visual antar tenaga medis dapat menghasilkan diagnosa yang berbeda akibat dari subjektivitas dan pengalaman tenaga medis yang berbeda, sehingga diperlukan metode klasifikasi yang cepat dan tepat. Metode pre-processing data rekaman EEG yang digunakan adalah Discrete Wavelet Transform untuk mendekomposisikan sinyal sehingga didapatkan gelombang theta, alpha, dan beta. Gelombang tersebut diekstraksi ke dalam fitur energy, deviasi standar, maksimum, minimum, dan entropy. Selanjutnya, pada tahap klasifikasi ictal dan interictal berdasarkan rekaman EEG menggunakan SVM dan SSVM didapatkan AUC masing-masing sebesar 97.83% dan 100%, sehingga metode SSVM lebih baik dibandingkan metode SVM.
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Epilepsy is a neurological disorder characterized by recurrent seizures. The increased risk of epileptic seizures can be described using EEG (electroencephalogram), which is a record of electrical activity along the scalp produced by the firing of neurons in the brain over a period of time. Clinically with seizures (ictal) and clinical without seizures (interictal) based on EEG recordings need to be classified to facilitate medical personnel in providing treatment to epilepsy patients. However, the results of analyzing EEG recordings visually between medical personnel can produce different diagnoses as a result of subjectivity and experience of different medical personnel, so a fast and precise classification method is needed. The pre-processing method of EEG recording data used is Discrete Wavelet Transform to decompose signals so that theta, alpha, and beta waves are obtained. The wave is extracted into the energy feature, standard deviation, maximum, minimum and entropy. Furthermore, at the ictal and interictal classification stages based on EEG recordings using SVM and SSVM, the AUC was 97.83% and 100% respectively, so the SSVM method was better than the SVM
Evaluation of Distance Measurement Using Complete Linkage Method
Full text linkCluster analysis is the process of grouping a number of objects based on information obtained from data that explains the relationship between objects with the principle of maximizing similarities between members of one cluster and minimizing similarities between clusters. Cluster analysis is useful for identifying objects (recognition), supporting decision-making systems, and data mining. Cluster analysis consists of hierarchical (Average Linkage, Single Linkage, Complete Linkage, Ward's, and Centroid) and non-hierarchical (K-Means) methods. Each method generally has advantages and disadvantages. Apart from that, there are several distance measures that are commonly used in the grouping process, such as Euclidean, Canberra Metric, Czekanowski Coefficient, and others. In general, researchers will choose one or several cluster analysis methods as a comparison and a certain distance measure to be applied to the data in order to group objects based on certain criteria. In this research, a study and evaluation of Euclidean distance measures, Canberra Metric, and Czekanowski Coefficient were carried out using the Complete Linkage method based on simulated data. The conclusion obtained from evaluating measures of object similarity, namely Euclidean distance, Canberra Metric, and Czekanowski Coefficient by applying the Complete Linkage method, concluded that Euclidean distance is better used as a measure of object similarity in grouping cases compared to Canberra Metric and Czekanowski Coefficient.Analisis cluster merupakan proses pengelompokkan sejumlah objek berdasarkan informasi yang diperoleh dari data yang menjelaskan hubungan antar objek dengan prinsip untuk memaksimalkan kesamaan antar anggota satu cluster dan meminimumkan kesamaan antar cluster. Analisis cluster bermanfaat untuk mengidentifikasi objek-objek (rekognisi), mendukung sistem pengambilan keputusan, dan data mining. Analisis cluster terdiri atas metode hirarki (Average Linkage, Single Linkage, Complete Linkage, Ward’s, Centroid) dan non hirarki (K-Means). Setiap metode umumnya memiliki kelebihan dan kekurangan. Selain itu, terdapat beberapa ukuran jarak yang biasa digunakan dalam proses pengelompokkan, seperti Eucliean, Canberra Metric, Czekanowski Coefficient, dan lain-lain. Pada umumnya peneliti akan memilih salah satu metode atau beberapa metode analisis cluster sebagai komparasi dan ukuran jarak tertentu untuk diaplikasikan pada data guna mendapatkan pengelompokkan objek berdasarkan suatu kriteria tertentu. Pada penelitian ini dilakukan kajian dan evaluasi ukuran jarak Euclidean, Canberra Metric, dan Czekanowski Coefficient menggunakan metode Complete Linkage berdasarkan data simulasi. Kesimpulan yang diperoleh dari evaluasi ukuran kemiripan objek, yaitu jarak Euclidean, Canberra Metric, dan Czekanowsi Coefficient dengan menerapakan metode Complete Linkage diperoleh kesimpulan bahwa jarak Euclidean lebih baik digunakan sebagai ukuran kemiripan objek pada kasus pengelompokan dibandingkan Canberra Metric dan Czekanowsi Coefficient
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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