Relevant bibliographies by topics / Anomaly

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Anomaly'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 March 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Anomaly.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Anomaly"

1

Ilahude, Delyuzar. "MAGNETIC ANOMALY PATTERNS USING TREND SURFACE ANALYSIS APPLICATION (TSA) ON MARINE GEOLOGY MAPPING IN THE BALIKPAPAN WATERS." BULLETIN OF THE MARINE GEOLOGY 27, no. 1 (February 15, 2016): 19. http://dx.doi.org/10.32693/bomg.27.1.2012.42.

Full text
Abstract:
The application of Trend Surface Analysis (TSA) method an geological and geophysical research in map sheets 1813-1814, Balikpapan Waters and its surrounding, shows the significant value of residual anomaly. The magnetic disseverance of regional and total anomaly value obtained the negative anomaly between -50 nT and -350 nT and positive anomaly between +50 nT and +400 nT. The contour of total and regional anomaly shows the magnetic properties of rocks which characterizes the geological arrangements of the research areas. Residual anomaly yielded from the 2nd order value of regional anomaly might be correlated with the formation of basin structures in the central and northern parts of research area, which is interpreted as a part of Kutai Basin. Keywords : TSA method, magnetic anomaly, geology and geophisics, Balikpapan Waters. Penerapan metode TSA dalam penelitian geologi dan geofisika di Lembar Peta 1813-1814, Perairan Balikpapan dan sekitarnya menunjukkan nilai anomali sisa yang cukup signifikan. Hasil pemisahan nilai anomali magnet regional dan anomaly total diperoleh nilai anomali yaitu antara -50 nT dan –350 nT dan anomali positif antara +50 nT dan +400 nT. Kontur anomali total dan anomali regional memperlihatkan sifat kemagnitan batuan yang mencirikan tatanan geologi daerah penelitian. Anomali sisa dihasilkan dari nilai anomali regional orde ke 2, kemungkinan berkaitan dengan pembentukan struktur cekungan di bagian tengah dan utara daerah penelitian yang ditafsirkan sebagai bagian dari Cekungan Kutai. Kata kunci : metode TSA, anomali magnet, geologi dan geofisika, Perairan Balikpapan.
APA, Harvard, Vancouver, ISO, and other styles
2

Muhajirin, Muhajirin, Nazli Ismail, and Bukhari Bukhari. "The Computation of Residual and Regional Anomaly of Gravity Method Data By Polynomial Filter Using Microsoft Excel." Journal of Aceh Physics Society 9, no. 2 (May 1, 2020): 37–41. http://dx.doi.org/10.24815/jacps.v9i2.15745.

Full text
Abstract:
Eksplorasi metode gravitasi umumnya dilakukan untuk mencari objek di bawah permukaan yang dangkal sehingga perlu dilakukan pemisahan anomali residual dan regional dari anomali Bouguer lengkap. Perhitungan anomali residual biasanya menggunakan software khusus untuk pengolahan data geofisika yang berlisensi atau algoritma dengan bahasa pemrograman, sedangkan program Microsoft Excel pada PC dan notebook biasa digunakan untuk perhitungan polinomial pada pengolahan data statistik. Penelitian ini memperkenalkan cara menghitung anomali residual menggunakan Microsoft Excel dengan filter polinomial. Hasil validasi yang menggunakan model sintetik menunjukkan bahwa perhitungan tersebut dapat diaplikasikan pada data metode gravitasi. Apalikasi pada data lapangan diperoleh bahwa anomali residual berfrekuensi tinggi, sedangkan anomali regional berfrekuensi rendah. Nilai anomali residual dipengaruhi oleh trendline anomali Bouguer lengkap dalam domain jarak. Hasil ini relatif sama dengan hasil perhitungan software lainnya. Gravity method exploration was generally conducted to seek the object in shallow underground so that required residual and regional anomaly separation of complete Bouguer anomaly. The residual anomaly separation was usually used by the special softwares for geophysics that require licency or algorithm by programming language, however the program of Microsoft Excel in the PC or notebook was usually applied to compute the polynomial filter for statistic data analysis. This research introduces how to compute residual anomaly using Microsoft Excel through polynomial filter. The validation result of sintetic model shows that the computation using Microsoft Excel can be applied to gravity method data. The application of field data was obtained that residual anomaly has high frecuency, whereas residual anomaly has low frecuency. The value of residual anomaly was influenced by trendline of complete Bouguer anomaly in distance domain. This result relatively equal to the result of other softwares. Keywords: gravity method, residual anomaly, regional anomaly, polynomial filter, Microsoft Excel
APA, Harvard, Vancouver, ISO, and other styles
3

Subagio, Subagio, and Tatang Patmawidjaya. "POLA ANOMALI BOUGUER DAN ANOMALI MAGNET DAN KAITANNYA DENGAN PROSPEK SUMBER DAYA MINERAL DAN ENERGI DI PULAU LAUT, PULAU SEBUKU DAN SELAT SEBUKU, KALIMANTAN SELATAN." JURNAL GEOLOGI KELAUTAN 11, no. 3 (February 16, 2016): 115. http://dx.doi.org/10.32693/jgk.11.3.2013.236.

Full text
Abstract:
Anomali Bouguer Pulau Laut, Pulau Sebuku, dan Selat Sebuku dapat dikelompokkan menjadi dua wilayah anomali meliputi anomali berpola melingkar dengan kisaran nilai dari 40 hingga 64 mGal, dan anomali berpola lurus dengan kisaran nilai 40 hingga 50 mGal. Anomali magnet di daerah ini bervariasi dari -700 hingga 1600 nT, membentuk pola tinggian dan rendahan. Anomali Bouguer berpola melingkar dengan kisaran nilai 45-64 mGal mencerminkan batuan ultrabasa yang relatif mendekati permukaan. Batuan ultrabasa yang tersingkap di permukaan dicirikan oleh anomali magnet tinggi. Anomali Bouguer berpola kontur lurus sejajar menunjukkan sesar naik maupun sesar turun yang terdapat di daerah tersebut. Sesar naik yang berkembang di daerah penelitian umumnya terdapat di Pegunungan Meratus yang mempunyai mendala geologi sama. Anomali Bouguer dan anomali magnet rendah mencerminkan cekungan sedimen. yang diakibatkan oleh adanya gaya tarikan yang pernah ada. Batuan terobosan yang dijumpai, diduga terbentuk bersamaan dengan periode gaya tarikan ini. Serangkaian proses tektonik yang hasilnya terekam pada anomali Bouguer, anomali magnet, dan singkapan batuan memberi implikasi kemungkinan terdapatnya sumber daya energi dan mineral di daerah penelitian. Mineralisasi logam diperkirakan dapat dijumpai di sekitar daerah terobosan. Bijih besi, nikel, dan kromit kemungkinan terdapat di daerah ultra-mafik, sedangkan batubara di daerah cekungan sedimen. Kata kunci : Anomali Bouguer, anomali magnet, sumber daya energi dan mineral, sesar naik dan sesar turun. Bouguer anomaly of the Laut Island, Sebuku Island, and The Sebuku Strait can be grouped into two anomaly groups covering the circular pattern anomaly with range from 40 to 64 mGals, and the straight pattern with range of values from 40 to 50 mGals. The range of magnetic anomalies in the study area area from -700 to 1600 nT, forming high and low anomay patterns. The circular pattern of the Bouguer anomalies with range from 45 to 64 mGals reflects that the ultramafic rocks relatively close to the surface, while exposed ultrabasic rocks are indicated by high magnetic anomalies. Paralled pattern contour of Bouguer anomaly show a thrust faults and normal faults in this area. Thrust faults of commonly develop in Meratus Mountaint that has the same geological setting. The low Bouguer and magnetic anomalies reflect a sedimentary basin caused by previous tensional force. The intrusion rocks found in the study area suggest to be formed together with this tensional force period. A series of tectonic events recorded in Bougue anomaly, magnetic anomaly, and out crops gave the implication the possibility the present of energy and mineral resources in the study area. Metal mineralization suggests to be found in the intrusion area. Irons, nickels and chromites supposed can be found in the ulta-mafic area, while coal can be found in the sedimentary basin. Keywords : Bouguer anomalies, magnetic anomalies, energy and mineral resources, thrust and normal faults.
APA, Harvard, Vancouver, ISO, and other styles
4

Panjaitan, Saultan, and Subagio Subagio. "POLA ANOMALI GAYABERAT DAERAH TALIABU-MANGOLE DAN LAUT SEKITARNYA TERKAIT DENGAN PROSPEK MINYAK BUMI DAN GAS." JURNAL GEOLOGI KELAUTAN 12, no. 2 (February 16, 2016): 65. http://dx.doi.org/10.32693/jgk.12.2.2014.247.

Full text
Abstract:
Anomali gayaberat di daerah penelitian merupakan anomali tertinggi di Indonesia, secara umum dikelompokkan ke dalam 2 (dua) satuan, yaitu: kelompok anomali gayaberat 160 mGal hingga 260 mGal membentuk pola rendahan/cekungan anomali, dan kelompok anomali gayaberat 260 mGal hingga 620 mGal membentuk pola tinggian anomali. Anomali sisa 0 mGal hingga 5 mGal membentuk tinggian anomali, diduga merupakan gambaran antiklin dengan diameter 10 – 15 kilometer. Perangkap struktur migas di daerah Minaluli, Madafuhi dan Lekosula Pulau Mangole berdekatan dengan lokasi rembesan migas, sehingga diusulkan untuk dilakukan pemboran eksplorasi. Sedangkan di Pulau Taliabu, Tolong, Pena, Samuya dan Teluk Jiko masih perlu dilakukan penambahan data. Batuan reservoir terdiri dari batupasir dan batugamping Formasi Tanamu berumur Kapur Akhir, menempati daerah beranomali sisa 0 mGal hingga 5 mGal, dengan rapat massa batuan sekitar 2.65 gr/cm³. Batuan induk adalah Formasi Buya umur Jura Tengah - Jura Akhir dari serpih hitam dengan rapat massa 2.71 gr/cm³, dan dapur migas terbentuk di sekitar daerah beranomali sisa -4 mGal hingga -28 mGal yang membentuk sub-cekungan di utara lepas pantai Pulau Mangole. Kata kunci: gayaberat, dapur minyak, cekungan, migas, serpih hitam, anomali sisa, rapat massa, antiklin, batuan induk. The gravity anomaly of research area is the highest anomaly in Indonesia, generally it can be grouped into 2 (two) units, that are 160 mGal up to 260 mGal anomaly groups formed low anomaly pattern, and 260 mGal up to 620 mGal anomaly groups formed high anomaly pattern. 0 mGal to 5 mGal residual anomaly formed high anomaly pattern, it is interpreted as anticline with diameter are 10-15 kilometers. The trap oil and gas structures of this area at Minaluli, Madafuhi, and Lekosula are near the location of oil and gas seepage, that is propose to explore and drill in that area. Whereas in Taliabu Island, Tolong, Pena, Samuya, and Jiko Gulf still need increasing datas. Reservoir rocks consist of sandstones and limestones of Tanamu Formations were Late Cretaceous age, that occupied the location of 0 mGal to 5 mGal residual anomaly with density 2.65 g/cm ³. Hostrock are Buya Formation are Middle Jurassic - Late Jurassic from black shales with density 2.71 g/cm³, and kitchen oil were formed in the area - 4 mGal to -28 mGal residual anomaly that formed low anomaly in the northern offshore of Mangole Island. Keyword: gravity, oil kitchen, basin, oil and gas, black shales, recidual anomaly, density, anticline, hostrocks.
APA, Harvard, Vancouver, ISO, and other styles
5

Ilahude, Delyuzar, and Beben Rachmat. "POLA ANOMALI MAGNET LOKAL DARI APLIKASI TREND SURFACE ANALYSIS (TSA) PADA PEMETAAN GEOLOGI KELAUTAN BERSISTEM DI PERAIRAN SELAT MALAKA SUMATERA UTARA." JURNAL GEOLOGI KELAUTAN 9, no. 2 (February 16, 2016): 109. http://dx.doi.org/10.32693/jgk.9.2.2011.204.

Full text
Abstract:
Analisis intensitas magnet dari penerapan metode TSA orde ke 2 menunjukkan nilai anomali lokal yang cukup signifikan dari pemisahan nilai anomali magnet total di perairan Selat Malaka. Kontur anomali lokal yang dihasilkan diduga berkaitan dengan pola struktur geologi busur belakang Sumatera Utara. Kata kunci : anomali lokal, metode TSA Analysis of magnetic intensity using 2nd orde of the TSA method shows a significant value of local anomaly from the separation of total magnetic anomaly value in the Malaka Strait waters. Contour of the local anomaly resulted is assumed to be correlated with the geological structure pattern of back arc of North Sumatera. Keyword : local anomaly, TSA method
APA, Harvard, Vancouver, ISO, and other styles
6

Hafizhah, Luthfia, and Dwi Pujiastuti. "Perbandingan Anomali Frekuensi Kritis Lapisan F2 (Fof2) Ionosfer Pada Gempa Bumi Laut Dan Gempa Bumi Darat Pulau Sumatera." Jurnal Fisika Unand 10, no. 1 (February 17, 2021): 41–47. http://dx.doi.org/10.25077/jfu.10.1.41-47.2021.

Full text
Abstract:
Pada saat akan terjadinya gempa bumi, maka akan diikuti dengan peningkatan injeksi gas radon di daerah zona persiapan gempa. Gas radon ini akan menyebabkan perubahan terhadap lapisan ionosfer. Telah dilakukan analisis perbedaan anomali frekuensi kritis lapisan F2 ionosfer (foF2) sebelum kejadian gempa laut dan gempa darat menggunakan ionogram ionosonda FMCW (Frequency Modulation Continous Wave) untuk melihat perbedaan karakteristiknya. Terdapat 5 kejadian gempa darat dan 5 kejadian gempa laut yang dianalisis. Rentang hari pengambilan ionogram adalah 21 hari sebelum kejadian gempa bumi (analisis prekursor gempa bumi) dan 7 hari setelah kejadian gempa bumi (respon lapisan ionosfer setelah gempa bumi). Terdapat 13.440 buah ionogram yang di-scaling manual. Perbandingan intensitas anomali foF2 pada gempa laut dan gempa darat terlihat acak dan tidak memiliki karakteristik yang berbeda. Anomali foF2 sudah terlihat 21 hari sebelum gempa darat. Pada gempa laut kemunculan anomali foF2 juga sudah terlihat 21 hari sebelum gempa bumi tetapi hanya untuk gempa dengan magnitudo besar saja yaitu gempa 12 September 2007 (7,7 SR dan 7,9 SR) dan 11 April 2012 (8,4 SR). Kemunculan anomali foF2 terakhir beberapa jam sebelum gempa bumi darat berakhir lebih cepat dibandingkan dengan gempa laut. Respon lapisan ionosfer terhadap aktivitas seismik dari gempa darat lebih cepat dari pada gempa laut. Anomali foF2 dipengaruhi oleh sumber gempa bumi, kedalaman dan magnitudo. Comparing the characteristic critical frequency anomaly of the ionosphere F2 layer (foF2) concerning land earthquake and sea earthquake during 2005 – 2016 in Sumatera region has been carried out. Ionogram data from the Frequency Modulation Continous Wave (FMCW) ionosonde instrument were analyzed for each of the five earthquakes. The foF2 anomaly in sea earthquake and land earthquake looks random. The foF2 anomaly was seen 21 before the earthquake. For the land earthquake, the foF2 anomaly has also been seen 21 days before the earthquake but only with large magnitudes ( 7.7 SR). The last foF2 anomaly was observed several hours before the land earthquake, ending the anomaly sooner than sea earthquake. Thus, the ionosphere layer response to seismic activity from the land arthquake was faster than sea earthquakes. The foF2 anomaly is influenced by earthquake source, depth, and magnitude.
APA, Harvard, Vancouver, ISO, and other styles
7

Ango, Christian Imanuel, Dolfie Paulus Pandara, Ferdy Ferdy, and Seni H. J. Tongkukut. "Investigasi Anomali TEC-Ionosfer Sebelum Letusan Gunung Lokon 14 Juli 2011 Menggunakan Metode Sliding Interquartile." Jurnal MIPA 9, no. 1 (January 24, 2020): 28. http://dx.doi.org/10.35799/jmuo.9.1.2020.27677.

Full text
Abstract:
Gunung Lokon yang berada di Sulawesi Utara adalah salah satu gunung api yang sering mengalami erupsi di Indonesia. Sebelum erupsi terjadi, terdapat aktivitas pra-erupsi yang memicu munculnya anomali Total Electron Content (TEC) di ionosfer. Anomali TEC yang menandai terjadinya letusan diasumsikan sebagai prekursor erupsi yang dapat bermanfaat bagi upaya mitigasi bencana letusan. Tujuan penelitian ini adalah untuk menginvestigasi anomali TEC sebelum letusan gunung Lokon pada tanggal 14 Juli 2011. Investigasi anomali TEC menggunakan metode Sliding Interquartile diperoleh hasil yang menunjukkan adanya anomali TEC yang terjadi 3 hari menjelang letusan yaitu pada tanggal 11 Juli 2011. Hal ini mengindikasikan adanya aktivitas pra-erupsi yang berpengaruh pada kuantitas TEC di ionosfer.Mount Lokon, located in North Sulawesi is among the most active volcanoes in Indonesia. Before the eruption occurred, there was a pre-eruption activity that triggered anomaly on Total Electron Content (TEC) in the ionosphere. TEC anomaly that mark the eruption are assumed as precursors of eruption that can be useful for disaster eruption mitigation efforts. The purpose of this study was to investigate the TEC anomaly before the Lokon eruption on July 14, 2011. Investigation of TEC by using the Sliding Interquartile method, the results showed that an TEC anomaly occurred 3 days before the eruption on July 11, 2011.These indicates the presence of pre-eruptive activity that affects the quantity of TEC in the ionosphere.
APA, Harvard, Vancouver, ISO, and other styles
8

Mu’awanah, Frida Rosidatul, Bambang Priadi, Widodo Widodo, I. Gde Sukadana, and Rian Andriansyah. "Mobilitas Uranium pada Endapan Sedimen Sungai Aktif di Daerah Mamuju, Sulawesi Barat." EKSPLORIUM 39, no. 2 (January 31, 2019): 95. http://dx.doi.org/10.17146/eksplorium.2018.39.2.4953.

Full text
Abstract:
ABSTRAK Mamuju merupakan daerah yang memiliki nilai laju dosis radiasi (radioaktifitas) tinggi. Daerah penelitian terdiri dari 6 sektor yaitu Sektor Ahu, Orobatu, Takandeang, Botteng, Pangasaan, dan Taan. Variasi batuan pada daerah penelitian tidak mencerminkan distribusi uranium, sehingga diperlukan metode geokimia untuk mengetahui distribusi uranium pada sistem drainase. Penelitian ini bertujuan untuk memberikan gambaran mobilitas dan distribusi uranium pada sistem drainase dengan menggunakan sampel sedimen sungai aktif. Analisis mobilitas uranium menggunakan persen labil yang didapatkan dari perbandingan uranium total dan uranium labil. Nilai uranium total didapatkan dari pengukuran X-Ray fluorescence spectrometry dan nilai uranium labil didapatkan dari pengukuran labile fluorimetry. Pengambilan sampel dilakukan pada 4 lokasi potensial berdasarkan data radiometri. Hasil analisis menunjukkan Sektor Ahu memiliki nilai anomali uranium labil >113,44 ppm, Sektor Pangasaan dengan nilai anomali uranium labil >168,63 ppm, Sektor Takandeang dengan nilai anomali uranium labil >74,36 ppm, dan Sektor Botteng dengan nilai anomali uranium labil >84,23 ppm. Tipe anomali yang teridentifikasi pada dua sektor, yaitu anomali pada sektor Ahu berhubungan dengan presipitasi hidrolisat uranium terlarut pada endapan sungai dari lava Ahu dan breksi Tapalang, sementara anomali pada Sektor Takandeang berhubungan dengan pengayaan permukaan uranium in situ pada tanah dan batuan lava Takandeang. ABSTRACT Mamuju is an area that has a high dose rate (radioactivity) value. The research area consists of 6 sectors namely Ahu, Orobatu, Takandeang, Botteng, Pangasaan, and Taan Sector. Lithological distribution does not represent the distribution of uranium; therefore geochemical method is needed to observe the distribution of uranium in the drainage system. The aim of this research is to provide an overview of the mobility and distribution of uranium in the drainage system using stream sediment. Uranium mobility analysis uses labile percent obtained from the ratio of total uranium and labile uranium, the total uranium value obtained from the measurement of X-Ray fluorescence spectrometry and the value of labile uranium obtained from measurement of labile fluorimetry. The sample taken from 4 potential areas based on radiometric value Map. The result of analysis shows that Ahu Sector has labile uranium anomaly >113.44 ppm, Pangasaan Sector with labile uranium anomaly >168.63 ppm, Takandeang Sector with uranium labile anomaly values >74.36 ppm, and Botteng Sector with uranium labile anomaly >84.23 ppm. The anomaly types identified from two sectors, namely Ahu Sector anomaly is related to the precipitation of dissolved uranium hydrolysates in stream deposit originating from Ahu lava and Tapalang breccia, while Takandeang Sector anomaly is related to the enrichment of in situ uranium in soil and Takandeang lava.
APA, Harvard, Vancouver, ISO, and other styles
9

Rahman, Fathu, Taufik Edy Sutanto, and Nina Fitriyati. "Web Traffic Anomaly Detection using Stacked Long Short-Term Memory." InPrime: Indonesian Journal of Pure and Applied Mathematics 3, no. 2 (November 10, 2021): 112–21. http://dx.doi.org/10.15408/inprime.v3i2.21879.

Full text
Abstract:
AbstractAn example of anomaly detection is detecting behavioral deviations in internet use. This behavior can be seen from web traffic, which is the amount of data sent and received by people who visit websites. In this study, anomaly detection was carried out using stacked Long Short-Term Memory (LSTM). First, stacked LSTM is used to create forecasting models using training data. Then the error value generated from the prediction on test data is used to perform anomaly detection. We conduct hyperparameter optimization on sliding window parameter. Sliding window is a sub-sequential data of time-series data used as input in the prediction model. The case study was conducted on the real Yahoo Webscope S5 web traffic dataset, consisting of 67 datasets, each of which has three features, namely timestamp, value, and anomaly label. The result shows that the average sensitivity is 0.834 and the average Area Under ROC Curve (AUC) is 0.931. In addition, for some of the data used, the window size selection can affect the sum of the sensitivity and AUC values. In this study, anomaly detection using stacked LSTM is described in detail and can be used for anomaly detection in other similar problems.Keywords: time-series data; sliding window; web traffic; window size. AbstrakSalah satu contoh deteksi anomali adalah mendeteksi penyimpangan perilaku dalam penggunaan internet. Perilaku ini dapat dilihat dari web traffic, yaitu jumlah data yang dikirim dan diterima oleh orang-orang yang mengunjungi situs web. Pada penelitian ini, deteksi anomali dilakukan menggunakan Long Short-Term Mermory (LSTM) bertumpuk. Pertama, LSTM bertumpuk digunakan untuk membuat model peramalan menggunakan data latih. Kemudian nilai error yang dihasilkan dari prediksi pada data uji digunakan untuk melakukan deteksi anomali. Kami melakukan optimasi hyperparameter pada parameter sliding window. Sliding window adalah data sub-sekuensial dari data runtun waktu yang digunakan sebagai input pada model prediksi. Studi kasus dilakukan pada dataset web traffic Yahoo Webscope S5 yang terdiri dari 67 dataset yang masing-masing memiliki tiga fitur yaitu timestamp, value, dan anomaly label. Hasil menunjukkan bahwa rata-rata sensitivitas sebesar 0.834 dan rata-rata Area Under ROC Curve (AUC) sebesar 0.931. Selain itu, untuk beberapa data yang digunakan, pemilihan window size dapat mempengaruhi jumlah dari nilai sensitivitas dan AUC. Pada penelitian ini, deteksi anomali menggunakan LSTM bertumpuk dijelaskan secara rinci dan dapat digunakan untuk deteksi anomali pada permasalahan lainnya yang serupa.Kata kunci: data runtun waktu; sliding window; web traffic; window size.
APA, Harvard, Vancouver, ISO, and other styles
10

Alviana, Sopian, and Irfan Dwiguna Sumitra. "ANALISIS PENGUKURAN PENGGUNAAN SUMBER DAYA KOMPUTER PADA INTRUSION DETECTION SYSTEM DALAM MEMINIMALKAN SERANGAN JARINGAN." Komputa : Jurnal Ilmiah Komputer dan Informatika 7, no. 1 (March 19, 2018): 27–34. http://dx.doi.org/10.34010/komputa.v7i1.2533.

Full text
Abstract:
Pemanfaatan intrusion detection system sebagai salah satu Teknik yang dapat mendeteksi serangan lebih dini dalam jaringan komputer. Dalam mendeteksi setiap serangan intrusion detection system menggunakan dua Teknik yaitu dengan anomaly based dan signature based. Pada penelitian ini akan mengukur penggunaan sumber daya komputer yang digunakan dalam mendeteksi serangan baik oleh anomaly based maupun signature based. Teknik pengukuran menggunakan experimental metode dengan memberikan sistem dengan serangan secara terus menerus dan bervariasi dari serangan yang bersifat anomali maupun bersifat signature, kemudian mengukur penggunaan sumber daya baik memori maupun penggunaan processor, serta waktu responsi oleh signature based maupun anomaly based. Berdasarkan analisis pengukuran terhadap respon deteksi metode anomaly based mempunyai keunggulan deteksi lebih cepat dengan membutuhkan 7 detik dibandingkan dengan signature based. Sedangkan, penggunaan processor metode signature based mengkonsumsi processor lebih rendah mencapai 69% dibandingkan anomaly based 75%, dan anomaly based cenderung lebih kecil dalam penggunaan memori dengan 60% dibandingkan signature based yang mengkonsumsi memory sebesar 62%.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Anomaly"

1

Ståhl, Björn. "Online Anomaly Detection." Thesis, Blekinge Tekniska Högskola, Avdelningen för för interaktion och systemdesign, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2825.

Full text
Abstract:
Where the role of software-intensive systems has shifted from the traditional one of fulfilling isolated computational tasks, larger collaborative societies with interaction as primary resource, is gradually taking its place. This can be observed in anything from logistics to rescue operations and resource management, numerous services with key-roles in the modern infrastructure. In the light of this new collaborative order, it is imperative that the tools (compilers, debuggers, profilers) and methods (requirements, design, implementation, testing) that supported traditional software engineering values also adjust and extend towards those nurtured by the online instrumentation of software intensive systems. That is, to adjust and to help to avoid situations where limitations in technology and methodology would prevent us from ascertaining the well-being and security of systems that assists our very lives. Coupled with most perspectives on software development and maintenance is one well established member of, and complement to, the development process. Debugging; or the art of discovering, localising, and correcting undesirable behaviours in software-intensive systems, the need for which tend to far outlive development in itself. Debugging is currently performed based on a premise of the developer operating from a god-like perspective. A perspective that implies access and knowledge regarding source code, along with minute control over execution properties. However, the quality as well as accessibility of such information steadily decline with time as requirements, implementation, hardware components and their associated developers, all alike fall behind their continuously evolving surroundings. In this thesis, it is argued that the current practice of software debugging is insufficient, and as precursory action, introduce a technical platform suitable for experimenting with future methods regarding online debugging, maintenance and analysis. An initial implementation of this platform will then be used for experimenting with a simple method that is targeting online observation of software behaviour.
APA, Harvard, Vancouver, ISO, and other styles
2

Sutton, Patrick James. "The dimensional-reduction anomaly." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ59681.pdf.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Tran, Thi Minh Hanh. "Anomaly detection in video." Thesis, University of Leeds, 2018. http://etheses.whiterose.ac.uk/22443/.

Full text
Abstract:
Anomaly detection is an area of video analysis that has great importance in automated surveillance. Although it has been extensively studied, there has been little work on using deep convolutional neural networks to learn spatio-temporal feature representations. In this thesis we present novel approaches for learning motion features and modelling normal spatio-temporal dynamics for anomaly detection. The contributions are divided into two main chapters. The first introduces a method that uses a convolutional autoencoder to learn motion features from foreground optical flow patches. The autoencoder is coupled with a spatial sparsity constraint, known as Winner-Take-All, to learn shift-invariant and generic flow-features. This method solves the problem of using hand-crafted feature representations in state of the art methods. Moreover, to capture variations in scale of the patterns of motion as an object moves in depth through the scene,we also divide the image plane into regions and learn a separate normality model in each region. We compare the methods with state of the art approaches on two datasets and demonstrate improved performance. The second main chapter presents a end-to-end method that learns normal spatio-temporal dynamics from video volumes using a sequence-to-sequence encoder-decoder for prediction and reconstruction. This work is based on the intuition that the encoder-decoder learns to estimate normal sequences in a training set with low error, thus it estimates an abnormal sequence with high error. Error between the network's output and the target is used to classify a video volume as normal or abnormal. In addition to the use of reconstruction error, we also use prediction error for anomaly detection. We evaluate the second method on three datasets. The prediction models show comparable performance with state of the art methods. In comparison with the first proposed method, performance is improved in one dataset. Moreover, running time is significantly faster.
APA, Harvard, Vancouver, ISO, and other styles
4

Barone, Joshua M. "Automated Timeline Anomaly Detection." ScholarWorks@UNO, 2013. http://scholarworks.uno.edu/td/1609.

Full text
Abstract:
Digital forensics is the practice of trained investigators gathering and analyzing evidence from digital devices such as computers and smart phones. On these digital devices, it is possible to change the time on the device for a purpose other than what is intended. Currently there are no documented techniques to determine when this occurs. This research seeks to prove out a technique for determining when the time has been changed on forensic disk image by analyzing the log files found on the image. Out of this research a tool is created to perform this analysis in automated fashion. This tool is TADpole, a command line program that analyzes the log files on a disk image and determines if a timeline anomaly has occurred.
APA, Harvard, Vancouver, ISO, and other styles
5

Samuelsson, Jonas. "Anomaly Detection in ConsoleLogs." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-314514.

Full text
Abstract:
The overall purpose of this project was to find anomalies inunstructured console logs. Logs were generated from system componentsin a contact center, specifically components in an email chain. Ananomaly is behaviour that can be described as abnormal. Suchbehaviour was found by creating features of the data that later oncould be analyzed by a data mining model. The mining model involvedthe usage of normalisation methods together with different distancefunctions. The algorithms that were used in order to generate resultson the prepared data were DBSCAN, Local Outlier Factor, and k-NNGlobal Anomaly Score. Every algorithm was combined with two differentnormalisation technologies, namely Min-Max- and Z-transformationnormalisation. The six different experiments yielded three datapoints that could be considered anomalies. Further inspection on thedata showed that the anomalies could be divided into two differenttypes of anomalies; system- or user behavioural related. Two out ofthree algorithms gave an anomaly score to a data point, whereas thethird gave a binary anomaly value to a data point. All the sixexperiments in this project had a common denominator; two data pointscould be classified as anomalies in all the six experiments.
APA, Harvard, Vancouver, ISO, and other styles
6

Das, Mahashweta. "Spatio-Temporal Anomaly Detection." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1261540196.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Mazel, Johan. "Unsupervised network anomaly detection." Thesis, Toulouse, INSA, 2011. http://www.theses.fr/2011ISAT0024/document.

Full text
Abstract:
La détection d'anomalies est une tâche critique de l'administration des réseaux. L'apparition continue de nouvelles anomalies et la nature changeante du trafic réseau compliquent de fait la détection d'anomalies. Les méthodes existantes de détection d'anomalies s'appuient sur une connaissance préalable du trafic : soit via des signatures créées à partir d'anomalies connues, soit via un profil de normalité. Ces deux approches sont limitées : la première ne peut détecter les nouvelles anomalies et la seconde requiert une constante mise à jour de son profil de normalité. Ces deux aspects limitent de façon importante l'efficacité des méthodes de détection existantes.Nous présentons une approche non-supervisée qui permet de détecter et caractériser les anomalies réseaux de façon autonome. Notre approche utilise des techniques de partitionnement afin d'identifier les flux anormaux. Nous proposons également plusieurs techniques qui permettent de traiter les anomalies extraites pour faciliter la tâche des opérateurs. Nous évaluons les performances de notre système sur des traces de trafic réel issues de la base de trace MAWI. Les résultats obtenus mettent en évidence la possibilité de mettre en place des systèmes de détection d'anomalies autonomes et fonctionnant sans connaissance préalable
Anomaly detection has become a vital component of any network in today’s Internet. Ranging from non-malicious unexpected events such as flash-crowds and failures, to network attacks such as denials-of-service and network scans, network traffic anomalies can have serious detrimental effects on the performance and integrity of the network. The continuous arising of new anomalies and attacks create a continuous challenge to cope with events that put the network integrity at risk. Moreover, the inner polymorphic nature of traffic caused, among other things, by a highly changing protocol landscape, complicates anomaly detection system's task. In fact, most network anomaly detection systems proposed so far employ knowledge-dependent techniques, using either misuse detection signature-based detection methods or anomaly detection relying on supervised-learning techniques. However, both approaches present major limitations: the former fails to detect and characterize unknown anomalies (letting the network unprotected for long periods) and the latter requires training over labeled normal traffic, which is a difficult and expensive stage that need to be updated on a regular basis to follow network traffic evolution. Such limitations impose a serious bottleneck to the previously presented problem.We introduce an unsupervised approach to detect and characterize network anomalies, without relying on signatures, statistical training, or labeled traffic, which represents a significant step towards the autonomy of networks. Unsupervised detection is accomplished by means of robust data-clustering techniques, combining Sub-Space clustering with Evidence Accumulation or Inter-Clustering Results Association, to blindly identify anomalies in traffic flows. Correlating the results of several unsupervised detections is also performed to improve detection robustness. The correlation results are further used along other anomaly characteristics to build an anomaly hierarchy in terms of dangerousness. Characterization is then achieved by building efficient filtering rules to describe a detected anomaly. The detection and characterization performances and sensitivities to parameters are evaluated over a substantial subset of the MAWI repository which contains real network traffic traces.Our work shows that unsupervised learning techniques allow anomaly detection systems to isolate anomalous traffic without any previous knowledge. We think that this contribution constitutes a great step towards autonomous network anomaly detection.This PhD thesis has been funded through the ECODE project by the European Commission under the Framework Programme 7. The goal of this project is to develop, implement, and validate experimentally a cognitive routing system that meet the challenges experienced by the Internet in terms of manageability and security, availability and accountability, as well as routing system scalability and quality. The concerned use case inside the ECODE project is network anomaly
APA, Harvard, Vancouver, ISO, and other styles
8

Leto, Kevin. "Anomaly detection in HPC systems." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

Find full text
Abstract:
Nell’ambito dei supercomputer, l’attività di anomaly detection rappresenta un’ottima strategia per mantenere alte le performance del sistema (disponibilità ed affidabilità), consentendo di prevenire i guasti e di adattare l’attività di manutenzione alla salute del sistema stesso. Il supercomputer esaminato da questa ricerca è chiamato MARCONI ed appartiene al CINECA, consorzio interuniversitario italiano con sede a Bologna. I dati estratti per l’analisi si riferiscono in particolar modo al nodo “r183c12s04”, ma per provare la generalità dell’approccio sono stati eseguiti ulteriori test anche su nodi differenti (seppur di minor portata). L’approccio seguito sfrutta le potenzialità del machine learning, combinando addestramento non supervisionato e supervisionato. Un autoencoder viene addestrato in modo non supervisionato per ottenere una rappresentazione compressa (dimensionality reduction) dei dati grezzi estratti da un nodo del sistema. I dati compressi vengono poi forniti ad una rete neurale di 3 livelli (input, hidden, output) per effettuare una classificazione supervised tra stati normali e stati anomali. Il nostro approccio si è rilevato molto promettente, raggiungendo livelli di accuracy, precision, recall e f1_score tutti superiori al 97% per il nodo principale. Mentre livelli più bassi, ma comunque molto positivi (mediamente superiori al 83%) sono stati riscontrati per gli altri nodi presi in considerazione. Le performance non perfette degli altri nodi sono sicuramente causate dal basso numero di esempi anomalie presenti nei dataset di riferimento.
APA, Harvard, Vancouver, ISO, and other styles
9

Martin, Xiumin. "Accrual persistence and accrual anomaly." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/4824.

Full text
Abstract:
Thesis (Ph. D.)--University of Missouri-Columbia, 2007.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on September 28, 2007) Vita. Includes bibliographical references.
APA, Harvard, Vancouver, ISO, and other styles
10

Nguyen, Quyen Do. "Anomaly handling in visual analytics." Worcester, Mass. : Worcester Polytechnic Institute, 2008. http://www.wpi.edu/Pubs/ETD/Available/etd-122307-132119/.

Full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Books on the topic "Anomaly"

1

Frehley, Ace. Anomaly. Place of publication not identified]: eOne, 2017.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
2

Anomaly. Vancouver: Raincoast Books, 2007.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
3

Brian, Haberlin, Van Dyke Geirrod, and Takenaga Francis, eds. Anomaly. Los Angeles, CA: Anomaly Publishing, 2012.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
4

Kuper, Tonya. Anomaly. Fort Collins, CO: Entangled Publishing, LLC, 2014.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
5

Fleming, Anne. Anomaly. Vancouver: Raincoast Books, 2005.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
6

Fleming, Neil. Anomaly. Toronto, Ont: Playwrights Guild of Canada/Tim Foil Cup Creative, 2005.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
7

Smith, Raymond A. The American Anomaly. Fourth Edition. | New York: Routledge, 2019.: Routledge, 2018. http://dx.doi.org/10.4324/9781351034821.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Nazeer, Mansoor. Anomaly. Independently Published, 2017.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
9

Fleming, Anne. Anomaly. Raincoast Books, 2006.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
10

Gilwood, Michael. Anomaly. KG Books Publishing, 2013.

Find full text
APA, Harvard, Vancouver, ISO, and other styles
More sources

Book chapters on the topic "Anomaly"

1

Shekhar, Shashi, and Hui Xiong. "Anomaly Detection." In Encyclopedia of GIS, 20. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_57.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Friedewald, Vincent E. "Ebstein Anomaly." In Clinical Guide to Cardiovascular Disease, 615–22. London: Springer London, 2016. http://dx.doi.org/10.1007/978-1-4471-7293-2_46.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Corno, Antonio F. "Ebstein’s anomaly." In Congenital Heart Defects, 73–78. Heidelberg: Steinkopff, 2003. http://dx.doi.org/10.1007/978-3-642-57358-3_11.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Park, In Sook, Soo-Jin Kim, and Hyun Woo Goo. "Ebstein’s Anomaly." In An Illustrated Guide to Congenital Heart Disease, 391–411. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6978-0_17.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Duplij, Steven, Martin Schlichenmaier, Rolf Schimmrigk, Martin Schlichenmaier, Maxim Vybornov, Dimilry Leites, Masud Chaichian, et al. "Anomaly Matching." In Concise Encyclopedia of Supersymmetry, 33–34. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/1-4020-4522-0_22.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Chen, Thomas, Jürgen Fuchs, Steven Duplij, Evgeniy Ivanov, Steven Duplij, Alexander Gavrilik, Massimo Bianchi, et al. "Holomorphic Anomaly." In Concise Encyclopedia of Supersymmetry, 192. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/1-4020-4522-0_251.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Kibler, Maurice, Mohammed Daoud, Maurice Kibler, I. Carrillo-Ibarra, Hugo Garcia-Compean, Volodymyr Mazorchuk, Ingo Runkel, et al. "Konishi Anomaly." In Concise Encyclopedia of Supersymmetry, 220. Dordrecht: Springer Netherlands, 2004. http://dx.doi.org/10.1007/1-4020-4522-0_288.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Dearani, Joseph A., and Constantine Mavroudis. "Ebstein Anomaly." In Atlas of Adult Congenital Heart Surgery, 337–43. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14163-9_17.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Rhodes, Jonathan, and Alexander R. Opotowsky. "Ebstein’s Anomaly." In Exercise Physiology for the Pediatric and Congenital Cardiologist, 145–51. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-16818-6_20.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Hofbeck, Michael, Karl-Heinz Deeg, and Thomas Rupprecht. "Ebstein’s Anomaly." In Doppler Echocardiography in Infancy and Childhood, 131–41. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-42919-9_10.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Anomaly"

1

Zhang, Wanting, Le Gao, Shaoyong Li, and Wenqi Li. "Anomaly Detection with Partially Observed Anomaly Types." In 2021 2nd International Conference on Computer Communication and Network Security (CCNS). IEEE, 2021. http://dx.doi.org/10.1109/ccns53852.2021.00028.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Akcay, Samet, Dick Ameln, Ashwin Vaidya, Barath Lakshmanan, Nilesh Ahuja, and Utku Genc. "Anomalib: A Deep Learning Library for Anomaly Detection." In 2022 IEEE International Conference on Image Processing (ICIP). IEEE, 2022. http://dx.doi.org/10.1109/icip46576.2022.9897283.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Lin, T. Y. "Anomaly detection." In Proceedings New Security Paradigms Workshop. IEEE, 1994. http://dx.doi.org/10.1109/nspw.1994.656226.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Yepmo, Véronne. "Anomaly Explanation." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/844.

Full text
Abstract:
With the surge of deep learning and laws aiming at regulating the use of artificial intelligence, providing explanations to algorithms outputs has been a hot topic in the recent years. Most works are devoted to the explanation of classifiers outputs. The explanation of unsupervised machine learning algorithms, like anomaly detection, has received less attention from the XAI community. But this little interest is not imputable to the irrelevance of the topic. In this paper, we demonstrate the importance of anomaly explanation, the areas still needing investigation based upon our previous contributions to the field, and the future directions that will be explored.
APA, Harvard, Vancouver, ISO, and other styles
5

Chen, Xinqiang, Lumei Su, Guansen Deng, Mingyong Huang, Jiajun Wu, and Yanqing Peng. "Weak anomaly-reinforced autoencoder for unsupervised anomaly detection." In Thirteenth International Conference on Machine Vision, edited by Wolfgang Osten, Jianhong Zhou, and Dmitry P. Nikolaev. SPIE, 2021. http://dx.doi.org/10.1117/12.2587017.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Blum, Ashlae. "A Temporal Approach to Unsupervised Anomaly Detection." In A Temporal Approach to Unsupervised Anomaly Detection. US DOE, 2021. http://dx.doi.org/10.2172/1825324.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Tian, Bowen, Qinliang Su, and Jian Yin. "Anomaly Detection by Leveraging Incomplete Anomalous Knowledge with Anomaly-Aware Bidirectional GANs." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/313.

Full text
Abstract:
The goal of anomaly detection is to identify anomalous samples from normal ones. In this paper, a small number of anomalies are assumed to be available at the training stage, but they are assumed to be collected only from several anomaly types, leaving the majority of anomaly types not represented in the collected anomaly dataset at all. To effectively leverage this kind of incomplete anomalous knowledge represented by the collected anomalies, we propose to learn a probability distribution that can not only model the normal samples, but also guarantee to assign low density values for the collected anomalies. To this end, an anomaly-aware generative adversarial network (GAN) is developed, which, in addition to modeling the normal samples as most GANs do, is able to explicitly avoid assigning probabilities for collected anomalous samples. Moreover, to facilitate the computation of anomaly detection criteria like reconstruction error, the proposed anomaly-aware GAN is designed to be bidirectional, attaching an encoder for the generator. Extensive experimental results demonstrate that our proposed method is able to effectively make use of the incomplete anomalous information, leading to significant performance gains comparing to existing methods.
APA, Harvard, Vancouver, ISO, and other styles
8

Gu, Xiaowei, and Plamen Angelov. "Autonomous anomaly detection." In 2017 Evolving and Adaptive Intelligent Systems (EAIS). IEEE, 2017. http://dx.doi.org/10.1109/eais.2017.7954831.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Bhatkar, S., A. Chaturvedi, and R. Sekar. "Dataflow anomaly detection." In 2006 IEEE Symposium on Security and Privacy. IEEE, 2006. http://dx.doi.org/10.1109/sp.2006.12.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Natoli, Christopher, and Vincent Gramoli. "The Blockchain Anomaly." In 2016 IEEE 15th International Symposium on Network Computing and Applications (NCA). IEEE, 2016. http://dx.doi.org/10.1109/nca.2016.7778635.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Reports on the topic "Anomaly"

1

Pieper, S. C., and R. B. Wiringa. Nolen-Schiffer anomaly. Office of Scientific and Technical Information (OSTI), August 1995. http://dx.doi.org/10.2172/166459.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Schock, Alfred. Multicouple Anomaly Interpretation. Office of Scientific and Technical Information (OSTI), August 1986. http://dx.doi.org/10.2172/1033356.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Hayes-Sterbenz, Anna. The Reactor Neutrino Anomaly. Office of Scientific and Technical Information (OSTI), June 2013. http://dx.doi.org/10.2172/1084506.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Arbuckle, B., W. Breen, and A. H. Mumin. Richardson pluton uranium anomaly. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2015. http://dx.doi.org/10.4095/296621.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Miles, W., and D. Oneschuk. Magnetic anomaly map, Canada. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2016. http://dx.doi.org/10.4095/297337.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Jobin, D. M., M. Véronneau, and W. Miles. Gravity anomaly map, Canada. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2017. http://dx.doi.org/10.4095/299561.

Full text
APA, Harvard, Vancouver, ISO, and other styles
7

Wu, Jin Ginger, Lu Zhang, and X. Frank Zhang. Understanding the Accrual Anomaly. Cambridge, MA: National Bureau of Economic Research, October 2007. http://dx.doi.org/10.3386/w13525.

Full text
APA, Harvard, Vancouver, ISO, and other styles
8

Miles, W. F., W. R. Roest, and M. P. Vo. Magnetic anomaly map, Canada. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2000. http://dx.doi.org/10.4095/211516.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Miles, W. F., W. R. Roest, and M. P. Vo. Gravity anomaly map, Canada. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2000. http://dx.doi.org/10.4095/211519.

Full text
APA, Harvard, Vancouver, ISO, and other styles
10

Ng, B. Survey of Anomaly Detection Methods. Office of Scientific and Technical Information (OSTI), October 2006. http://dx.doi.org/10.2172/900157.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Anomaly' for particular source types:
Journal articles Dissertations / Theses Books
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography