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Статті в журналах з теми "SNORD"

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Автор: Grafiati

Опубліковано: 14 вересня 2021

Оновлено: 1 лютого 2022

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1

Cohen, Eran, Dana Avrahami, Kati Frid, Tamar Canello, Ephrat Levy Lahad, Sharon Zeligson, Shira Perlberg, et al. "Snord 3A: A Molecular Marker and Modulator of Prion Disease Progression." PLoS ONE 8, no. 1 (January 21, 2013): e54433. http://dx.doi.org/10.1371/journal.pone.0054433.

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2

Kishore, Shivendra, Amit Khanna, Zhaiyi Zhang, Jingyi Hui, Piotr J. Balwierz, Mihaela Stefan, Carol Beach, Robert D. Nicholls, Mihaela Zavolan, and Stefan Stamm. "The snoRNA MBII-52 (SNORD 115) is processed into smaller RNAs and regulates alternative splicing." Human Molecular Genetics 19, no. 7 (January 6, 2010): 1153–64. http://dx.doi.org/10.1093/hmg/ddp585.

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3

Ho, Shuk-Mei, Ana Cheong, Hung-Ming Lam, Wen-Yang Hu, Guang-Bin Shi, Xuegong Zhu, Jing Chen, et al. "Exposure of Human Prostaspheres to Bisphenol A Epigenetically Regulates SNORD Family Noncoding RNAs via Histone Modification." Endocrinology 156, no. 11 (August 6, 2015): 3984–95. http://dx.doi.org/10.1210/en.2015-1067.

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4

Askarian-Amiri, M. E., J. Crawford, J. D. French, C. E. Smart, M. A. Smith, M. B. Clark, K. Ru, et al. "SNORD-host RNA Zfas1 is a regulator of mammary development and a potential marker for breast cancer." RNA 17, no. 5 (April 1, 2011): 878–91. http://dx.doi.org/10.1261/rna.2528811.

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5

Shaw, P. J., A. F. Beven, D. J. Leader, and J. W. Brown. "Localization and processing from a polycistronic precursor of novel snoRNAs in maize." Journal of Cell Science 111, no. 15 (August 1, 1998): 2121–28. http://dx.doi.org/10.1242/jcs.111.15.2121.

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We have shown previously that groups of U14 snoRNA genes are clustered with other, novel snoRNAs in maize. These genes are transcribed polycistronically from an upstream promoter to give a precursor snoRNA, which is processed by a splicing-independent mechanism. The clusters contain both box C/D snoRNAs, thought to guide rRNA O-ribose methylations, and the first plant box H/ACA snoRNA so far identified, thought to guide an rRNA pseudo-uridylation. Here we show that four novel snoRNAs identified as members of U14-containing gene clusters each show distinct sub-nucleolar localizations. Two of the snoRNAs (snoR2, a box H/ACA snoRNA, and snoR3, a box C/D snoRNA) colocalise closely with nucleolar rDNA transcription sites. A third box C/D snoRNA, U49, is localised to a more extended region which includes the transcription sites. On the other hand snoR1, another box C/D snoRNA, is located in a quite different region of the nucleolus, and shows a similar distribution to that of 7–2/MRP, a snoRNA involved in the later pre-rRNA cleavage reactions. This may indicate that this snoRNA is involved at later stages of processing, whereas the other snoRNAs are involved early or cotranscriptionally. Probes to intergenic spacer regions of the precursor snoRNA have been used to determine the location of the precursor. This shows a clear labelling of both the dense fibrillar component of the nucleolus, and of coiled bodies. This distribution implies that the polycistronic precursor is imported into the nucleolus for processing to the mature snoRNAs, and that the import or processing pathway involves coiled bodies.

6

Akhtari, Farida S., Tammy M. Havener, Masahide Fukudo, John R. Jack, Howard L. McLeod, Tim Wiltshire, and Alison A. Motsinger-Reif. "The influence of Neanderthal alleles on cytotoxic response." PeerJ 6 (October 23, 2018): e5691. http://dx.doi.org/10.7717/peerj.5691.

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Various studies have shown that people of Eurasian origin contain traces of DNA inherited from interbreeding with Neanderthals. Recent studies have demonstrated that these Neanderthal variants influence a range of clinically important traits and diseases. Thus, understanding the genetic factors responsible for the variability in individual response to drug or chemical exposure is a key goal of pharmacogenomics and toxicogenomics, as dose responses are clinically and epidemiologically important traits. It is well established that ethnic and racial differences are important in dose response traits, but to our knowledge the influence of Neanderthal ancestry on response to xenobiotics is unknown. Towards this aim, we examined if Neanderthal ancestry plays a role in cytotoxic response to anti-cancer drugs and toxic environmental chemicals. We identified common Neanderthal variants in lymphoblastoid cell lines (LCLs) derived from the globally diverse 1000 Genomes Project and Caucasian cell lines from the Children’s Hospital of Oakland Research Institute. We analyzed the effects of these Neanderthal alleles on cytotoxic response to 29 anti-cancer drugs and 179 environmental chemicals at varying concentrations using genome-wide data. We identified and replicated single nucleotide polymorphisms (SNPs) from these association results, including a SNP in the SNORD-113 cluster. Our results also show that the Neanderthal alleles cumulatively lead to increased sensitivity to both the anti-cancer drugs and the environmental chemicals. Our results demonstrate the influence of Neanderthal ancestry-informative markers on cytotoxic response. These results could be important in identifying biomarkers for personalized medicine or in dissecting the underlying etiology of dose response traits.

7

Salminen, Iiro Ilmari, Bernard J. Crespi, and Mikael Mokkonen. "Baby food and bedtime: Evidence for opposite phenotypes from different genetic and epigenetic alterations in Prader-Willi and Angelman syndromes." SAGE Open Medicine 7 (January 2019): 205031211882358. http://dx.doi.org/10.1177/2050312118823585.

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Prader–Willi and Angelman syndromes are often referred to as a sister pair of neurodevelopmental disorders, resulting from different genetic and epigenetic alterations to the same chromosomal region, 15q11-q13. Some of the primary phenotypes of the two syndromes have been suggested to be opposite to one another, but this hypothesis has yet to be tested comprehensively, and it remains unclear how opposite effects could be produced by changes to different genes in one syndrome compared to the other. We evaluated the evidence for opposite effects on sleep and eating phenotypes in Prader–Willi syndrome and Angelman syndrome, and developed physiological–genetic models that represent hypothesized causes of these differences. Sleep latency shows opposite deviations from controls in Prader–Willi and Angelman syndromes, with shorter latency in Prader–Willi syndrome by meta-analysis and longer latency in Angelman syndrome from previous studies. These differences can be accounted for by the effects of variable gene dosages of UBE3A and MAGEL2, interacting with clock genes, and leading to acceleration (in Prader–Willi syndrome) or deceleration (in Angelman syndrome) of circadian rhythms. Prader–Willi and Angelman syndromes also show evidence of opposite alterations in hyperphagic food selectivity, with more paternally biased subtypes of Angelman syndrome apparently involving increased preference for complementary foods (“baby foods”); hedonic reward from eating may also be increased in Angelman syndrome and decreased in Prader–Willi syndrome. These differences can be explained in part under a model whereby hyperphagia and food selectivity are mediated by the effects of the genes SNORD-116, UBE3A and MAGEL2, with outcomes depending upon the genotypic cause of Angelman syndrome. The diametric variation observed in sleep and eating phenotypes in Prader–Willi and Angelman syndromes is consistent with predictions from the kinship theory of imprinting, reflecting extremes of higher resource demand in Angelman syndrome and lower demand in Prader–Willi syndrome, with a special emphasis on social–attentional demands and attachment associated with bedtime, and feeding demands associated with mother-provided complementary foods compared to offspring-foraged family-type foods.

8

Supriyatno, Bambang, Rusmala Deviani, Alan R. Tumbelaka, Evita KB Ifran, and Nastiti N. Rahajoe. "Characteristics and risk factors of snoring and the prevalence of suspected obstructive sleep apnea in children." Paediatrica Indonesiana 45, no. 1 (October 10, 2016): 40. http://dx.doi.org/10.14238/pi45.1.2005.40-5.

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Background Snoring as a consequence of upper airway obstruc-tion is common in children. Snoring can be considered as normal,but might also reflect a disease such as obstructive sleep apnea(OSA), which is associated with serious morbidities. In Indonesia,data on the characteristics and risk factors of snoring and obstruc-tive sleep apnea is limitedObjectives The aims of this study were to find out the character-istics and risk factors of snoring in children and to determine theprevalence of suspected OSA in snoring children.Methods A cross-sectional study was carried out on children aged5-13 years using parental questionnaires scored according to theBrouilette formula. All children underwent physical examination forweight, height and tonsil size. Adenoid radiology was performedon part of the samples.Results Of the 917 questionnaires distributed, only 658 were com-pleted. The ratio of boys to girls was equal. Obesity was detectedin 18.3% of children, among whom 54.2% snored. Obese childrenwere 2.1 times more likely to snore. Besides obesity, rhinitis andatopy were found to be associated with snoring (PR= , 95%CI ;and PR= , 95%CI ; respectively). Asthma and tonsil hypertrophywere shown not to be predisposing factors of snoring. Childrenwith adenoid hypertrophy were 1.8 times more likely to snore ha-bitually. The prevalence of snoring and suspected OSA in childrenaged 5-13 years were 31.6% and 5.9%, respectively.Conclusion Risk factors of snoring were obesity, adenoid hyper-trophy, atopy and rhinitis. Prevalence of snoring in children age 5-13 years was 31.6% and that of suspected OSA cases was 5.9%.

9

Sabekti, Muhamad Agung. "Pembuatan Web Interface Snort untuk Managemen Firewall dengan Operasi CRUD (Create, Read, Update, Delete) pada File System Snort dan Pengujian Web dengan Serangan serta Notifikasi pada Email dan Telegram." Indonesian Journal of Applied Informatics 3, no. 2 (August 4, 2019): 74. http://dx.doi.org/10.20961/ijai.v3i2.27836.

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<p><em>Snort</em> merupakan salah satu aplikasi <em>firewall</em> yang dikonfigurasi dalam terminal linux, meliputi konfigurasi <em>snort</em>, <em>input rule snort</em>, dan hasil alert <em>snort</em> pada terminal linux. Untuk mempermudah monitoring alert diterminal linux, maka alert diimplementasikan pada email dan telegram serta guna mempermudah dalam aktifitas dalam aktifitas input rule snort maka dibuatlah <em>web interface snort </em>. Metode untuk menangani Snort berjalan pada <em>mode inline</em> dengan menggunakan modul <em>daq_afpacket</em> dalam snort itu sendiri, dan untuk melakukan blok ketika terjadi serangan, snort menggunakan <em>firewall iptables</em>. Alert diimplementasikan pada email menggunakan protokol <em>ssmtp</em> dan pada telegram menggunakan id dan api telegram. Hasil dari penelitian menyatakan pembuatan web <em>interface</em> dapat dengan mudah mengelola <em>rule</em> dan alert <em>snort</em>, serta dapat diaplikasikan dalam beberapa serangan yang diujikan.</p><p>_______________________________________________</p><p>Abstract</p><p><em>In general, snort is a firewall application that is configured in Linux terminals, including the implementation of snort, input snort rules, and snort warning results on Linux terminals. To monitor the linux warning alarm, the alerts are implemented on e-mail and telegram, as well as for input information in snort mode and then create a snort web interface. The method for handling Snort runs in inline mode by using the daq_afpacket module in the snort itself, and to block when an attack occurs, snort uses the iptables firewall. Alerts are implemented in e-mail using the ssmtp protocol and on telegrams using id and telegram fires. The results of the study state that making web interfaces can easily manage rules and snort alerts, and can be applied in several attacks that are tested.</em></p>

10

Karunajeewa, Asela S., Udantha R. Abeyratne, and Craig Hukins. "Silence–breathing–snore classification from snore-related sounds." Physiological Measurement 29, no. 2 (January 23, 2008): 227–43. http://dx.doi.org/10.1088/0967-3334/29/2/006.

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11

Lindblom, Scott S. "Adults who snore." Postgraduate Medicine 101, no. 6 (June 1997): 171–91. http://dx.doi.org/10.3810/pgm.1997.06.228.

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12

Alexander, Roger E. "Adults who snore." Journal of Oral and Maxillofacial Surgery 55, no. 10 (October 1997): 1188–89. http://dx.doi.org/10.1016/s0278-2391(97)90313-x.

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13

Hayashi, Shota, Meiyo Tamaoka, Tomoya Tateishi, Yuki Murota, Ibuki Handa, and Yasunari Miyazaki. "A New Feature with the Potential to Detect the Severity of Obstructive Sleep Apnoea via Snoring Sound Analysis." International Journal of Environmental Research and Public Health 17, no. 8 (April 24, 2020): 2951. http://dx.doi.org/10.3390/ijerph17082951.

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The severity of obstructive sleep apnoea (OSA) is diagnosed with polysomnography (PSG), during which patients are monitored by over 20 physiological sensors overnight. These sensors often bother patients and may affect patients’ sleep and OSA. This study aimed to investigate a method for analyzing patient snore sounds to detect the severity of OSA. Using a microphone placed at the patient’s bedside, the snoring and breathing sounds of 22 participants were recorded while they simultaneously underwent PSG. We examined some features from the snoring and breathing sounds and examined the correlation between these features and the snore-specific apnoea-hypopnea index (ssAHI), defined as the number of apnoea and hypopnea events during the hour before a snore episode. Statistical analyses revealed that the ssAHI was positively correlated with the Mel frequency cepstral coefficients (MFCC) and volume information (VI). Based on clustering results, mild snore sound episodes and snore sound episodes from mild OSA patients were mainly classified into cluster 1. The results of clustering severe snore sound episodes and snore sound episodes from severe OSA patients were mainly classified into cluster 2. The features of snoring sounds that we identified have the potential to detect the severity of OSA.

14

Zhang, Zixing, Jing Han, Kun Qian, Christoph Janott, Yanan Guo, and Bjorn Schuller. "Snore-GANs: Improving Automatic Snore Sound Classification With Synthesized Data." IEEE Journal of Biomedical and Health Informatics 24, no. 1 (January 2020): 300–310. http://dx.doi.org/10.1109/jbhi.2019.2907286.

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15

Dewi Paramitha, Ida Ayu Shinta, Gusti Made Arya Sasmita, and I. Made Sunia Raharja. "Analisis Data Log IDS Snort dengan Algoritma Clustering Fuzzy C-Means." Majalah Ilmiah Teknologi Elektro 19, no. 1 (October 15, 2020): 95. http://dx.doi.org/10.24843/mite.2020.v19i01.p14.

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Snort is one of open source IDS to detect intrusion or potentially malicious activity on network traffic. Snort will give alert for every detected intrusion and write the alerts in log. Log data in IDS Snort will help network administrator to analyze the vulnerability of network security system. Clustering algorithm such as FCM can be used to analyze the log data of IDS Snort. Implementation of the algorithm is based on Python 3 and aims to cluster alerts in log data into 4 risk categories, such as low, medium, high, and critical. The outcome of this analysis is to show cluster results of FCM and to visualize the types of attacks that IDS Snort has successfully detected. Evaluation process is done by using Modified Partition Coefficient (MPC) to determine the validity of FCM.

16

Saganowski, Łukasz, and Tomasz Andrysiak. "Snort IDS Hybrid ADS Preprocessor." Image Processing & Communications 17, no. 4 (December 1, 2012): 17–22. http://dx.doi.org/10.2478/v10248-012-0024-0.

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Abstract The paper presents hybrid anomaly detection preprocessor for SNORT IDS - Intrusion Detection System [1] base on statistical test and DWT - Discrete Wavelet Transform coefficient analysis. Preprocessor increases functionality of SNORT IDS system and has complementary properties. Possibility of detection network anomalies is increased by using two different algorithms. SNORT captures network traffic features which are used by ADS (Anomaly Detection System) preprocessor for detecting anomalies. Chi-square statistical test and DWT subband coefficients energy values are used for calculating of normal network traffic profiles. We evaluated proposed SNORT extension with the use of test network.

17

Gunawan, Agus Riki, Nyoman Putra Sastra, and Dewa Made Wiharta. "Penerapan Keamanan Jaringan Menggunakan Sistem Snort dan Honeypot Sebagai Pendeteksi dan Pencegah Malware." Majalah Ilmiah Teknologi Elektro 20, no. 1 (March 1, 2021): 81. http://dx.doi.org/10.24843/mite.2021.v20i01.p09.

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Intisari- Sistem komputer yang terkoneksi jaringan internet beresiko terhadap ancaman atau serangan. Sistem Snort dan Honeypot merupakan sistem kemanan berlapis yang dimana jaringan internal akan di awasi selama 24 jam setiap harinya, sehingga jika terdapat data masuk yang mencurigakan sistem akan memberikan informasi otomatis bahwa adanya serangan berupa malware atau hacker. Snort dapat mendeteksi dan menyimpan 250519 jumlah data dengan 27 atribut yang disediakan Snort secara default. Honeypot dapat mendeteksi dan menyimpan sebanyak 248.574 data yang dimana tercatat 10 jenis serangan. System honeypot mendeteksi 10 jenis serangan yang berbeda dengan IP address pada setiap serangan. Dari 10 jenis serangan diambil 5 jenis serangan terbesar dan 5 IP address terbesar pada setiap jenis serangan. Sehingga fungsi sistem snort dan honeypot telah dapat mendeteksi adanya serangan serta menyimpan data penyerang pada sistem, dan dapat berjalan secara bersamaan pada satu jaringan. Kata kunci : Snort IDS, Honeypot, Keamanan Jaringan, Malware

18

Michalek-Zrabkowska, Monika, Mieszko Wieckiewicz, Piotr Macek, Pawel Gac, Joanna Smardz, Anna Wojakowska, Rafal Poreba, Grzegorz Mazur, and Helena Martynowicz. "The Relationship between Simple Snoring and Sleep Bruxism: A Polysomnographic Study." International Journal of Environmental Research and Public Health 17, no. 23 (December 2, 2020): 8960. http://dx.doi.org/10.3390/ijerph17238960.

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Simple snoring is defined as the production of sound in the upper aerodigestive tract during sleep, not accompanied by other pathologies. Sleep bruxism (SB) refers to repetitive phasic, tonic, or mixed masticatory muscle activity during sleep. In this study, we investigated the relationship between simple snoring and SB in patients without obstructive sleep apnea (OSA). A total of 565 snoring subjects underwent polysomnography. After examination, individuals with OSA were excluded from the study group. Finally, 129 individuals were analyzed. The bruxism episode index was positively correlated with maximum snore intensity. Phasic bruxism was positively correlated with snore intensity in all sleep positions. Bruxers had a significantly decreased average and minimum heart rate compared with non-bruxers. Supine sleep position seemed to have a significant impact on snore intensity and SB. In summary, our study showed the relationship between SB, snore intensity, and body position. Phasic bruxism was positively correlated with snore intensity despite the body position, which is an interesting and novel finding.

19

Acosta, Andres, and Leonardo Rodriguez. "Snort como herramienta administrativa." INVENTUM 3, no. 5 (July 7, 2008): 74–78. http://dx.doi.org/10.26620/uniminuto.inventum.3.5.2008.74-78.

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Snort como una herramienta de sniffer puede ser utilizado en forma ilegal capturando tráfico, en el cual se puede filtrar información privada de una empresa. Este artículo pretende dar a entender que su uso se puede orientar a una forma administrativa para asegurar una red, de tal forma que esta herramienta nos informe sobre hechos o eventos ocurridos dentro de unas reglas preestablecidas por el administrador de la red. Así mismo, describe algunas características de Snort, como su ubicación dentro del esquema de red y la creación de reglas, controlando así el tráfico entrante y saliente. Snort como IDS busca aumentar la seguridad, vigilar y examinar el tráfico de la red en busca de datos sospechosos, además de detectar los primeros instantes de un ataque que pueden comprometer de manera importante la seguridad de la red.

20

TATE, JUDY, and FREDERICK J. TASOTA. "More than a Snore." Nursing 32, no. 8 (August 2002): 46–49. http://dx.doi.org/10.1097/00152193-200208000-00046.

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21

Nigam, Vivek, and Roland Priemer. "A Snore Extraction Method from Mixed Sound for a Mobile Snore Recorder." Journal of Medical Systems 30, no. 2 (April 2006): 91–99. http://dx.doi.org/10.1007/s10916-005-7986-z.

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22

Nakamura, Koki, Kenta Iwai, and Takanobu Nishiura. "Multi-channel feedforward active noise control system for reducing snore noise with snore noise-term detection." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 5 (August 1, 2021): 1107–19. http://dx.doi.org/10.3397/in-2021-1755.

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In this paper, a multi-channel feedforward active noise control system for reducing snore noise with noise-term detection is proposed. The snore noise consists of a noise-term and a silent-term, and it is difficult to reduce the snore noise by the active noise control system. Since the conventional multi-channel feedforward active noise control system updates the noise control filters even in the silent-term, the conventional active noise control system updates the noise control filters unnecessarily. Therefore, the proposed multi-channel feedforward active noise control system introduces threshold processing to update the noise control filters only in the noise-term. Owing to this process, it is possible to reduce the update count of the noise control filters. Simulation results show that the proposed active noise control system can reduce the snore noise as same as the conventional active noise control system and can reduce the update count of the noise control filters compared to the conventional active noise control system.

23

Blotskiy, A. A., V. V. Antipenko, and R. A. Blotskiy. "THE SNORE PHENOMENON AT CHILDREN." Amur Medical Journal, no. 3 (2017): 110–11. http://dx.doi.org/10.22448/amj.2017.3.110-111.

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24

Dian Pratiwi, Yuni, Enggar Alfianto, and Shah Khadafi. "IMPLEMENTASI METODE INTRUSION DETECTION SYSTEM (IDS) MENGGUNAKAN PERANGKAT LUNAK PORTSENTRY DAN SNORT BERBASIS SISTEM OPERASI LINUX UBUNTU 16.04 LTS." e-NARODROID 4, no. 2 (September 28, 2018): 35–48. http://dx.doi.org/10.31090/narodroid.v4i2.732.

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Abstract : Sistem keamanan jaringan merupakan salah satu faktor penting dalam menjaga jaringan dari ancaman penyusup yang dapat merusak dan mencuri data melalui sebuah koneksi jaringan. Untuk menerapkan keamanan dalam jaringan dapat menggunakan metode sederhana yaitu Intrusion Detection System (IDS) dimana metode tersebut mampu mendeteksi akses yang tidak sah pada sebuah sistem jaringan. Penerapan metode IDS pada penelitian ini menggunakan dua tools keamanan jaringan yaitu Portsentry dan Snort yang merupakan perangkat lunak bersifat open source. Kedua tools IDS tersebut akan dikolaborasikan dan diuji dalam mendeteksi adanya serangan seperti ping of death, scanning port dan sniffing. Dari hasil kolaborasi kedua tools IDS tersebut bahwa Portsentry mampu mendeteksi adanya scanning port sekaligus memblokir serangan, namun tidak dapat mendeteksi jenis serangan seperti ping of death dan sniffing karena dianggap aman. Sedangkan Snort dapat mendeteksi semua jenis serangan seperti ping of death, scanning port dan juga sniffing namun tidak dapat memblokir serangan tersebut. Meskipun demikian, implementasi metode IDS untuk deteksi serangan menggunakan Portsentry dan Snort masih dapat dikolaborasikan dengan baik. Kata Kunci : Metode IDS, Portsentry, Snort, ping of death, scanning port, sniffing

25

Accardo, Jennifer, and Jennifer Reesman. "Can You Hear Me Snore?" Journal of Clinical Sleep Medicine 09, no. 11 (November 15, 2013): 1221–23. http://dx.doi.org/10.5664/jcsm.3180.

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26

Millman, Richard P. "Did the Fat Boy Snore?" Chest 89, no. 5 (May 1986): 621–22. http://dx.doi.org/10.1378/chest.89.5.621.

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27

Merrill, Jonathan R. "Snore-Induced Mallory-Weiss Syndrome." Journal of Clinical Gastroenterology 9, no. 1 (February 1987): 88–89. http://dx.doi.org/10.1097/00004836-198702000-00022.

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Kuo, Sen M., Sreeram R. Chakravarthy, Rakesh Gireddy, and Abhijit Gupta. "Active snore noise control systems." Noise Control Engineering Journal 56, no. 1 (2008): 16. http://dx.doi.org/10.3397/1.2826409.

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STEVENS, MOLLY. "Snore: Public sleeping in China." Ethnographic Praxis in Industry Conference Proceedings 2013, no. 1 (September 2013): 413. http://dx.doi.org/10.1111/j.1559-8918.2013.00054.x.

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30

Salah, K., and A. Kahtani. "Improving Snort performance under Linux." IET Communications 3, no. 12 (2009): 1883. http://dx.doi.org/10.1049/iet-com.2009.0114.

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31

Purba, Winrou Wesley, and Rissal Efendi. "Perancangan dan analisis sistem keamanan jaringan komputer menggunakan SNORT." AITI 17, no. 2 (February 23, 2021): 143–58. http://dx.doi.org/10.24246/aiti.v17i2.143-158.

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PT. Promanufacture Indonesia merupakan sebuah perusahaan yang memerlukan adanya jaringan internet agar dapat mengolah data anggota, barang, cctv dan lain-lain. Semua file dan data anggota, barang, cctv dan lain-lain akan disimpan di dalam sebuah server. Server di PT. Promanufacture Indonesia hanya mengandalkan sistem firewall saja. Dengan menggunakan firewall saja sistem keamanan jaringan tidak akan terjamin keamanannya. Maka diperlukan sebuah sistem untuk menjaga keamanan jaringan tersebut, yaitu SNORT. SNORT merupakan perangkat lunak yang akan memberikan peringatan ketika terjadi penyusupan kedalam sistem komputer. Tujuan dari penelitian ini adalah merancang dan menganalisa sistem keamanan komputer di PT. Promanufacture Indonesia dengan menggunakan perangkat lunak SNORT. Hasil dari penelitian ini dapat digunakan oleh pengelola jaringan PT. Promanufacture Indonesia untuk menjaga sistem keamanan jaringan komputer pada perusahaan tersebut.

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Partinen, M. "Ischaemic stroke, snoring and obstructive sleep apnoea." Neurology Bulletin XXXII, no. 3-4 (July 15, 2000): 75–76. http://dx.doi.org/10.17816/nb79499.

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Ischemic stroke usually occurs in the morning before noon; according to the latest data, - most often between 10 and 12 hours. Individuals who snore every night or nearly every night (habitual snoring) have been found to be more at risk of ischemic stroke than those who snore intermittently. Habitual snoring is a common manifestation of obstructive sleep apnea, often associated with being overweight.

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Aminanto, Alja, and Wiwin Sulistyo. "Simulasi Sistem Keamanan Jaringan Komputer Berbasis IPS Snort dan Honeypot Artilery." AITI 16, no. 2 (June 17, 2020): 135–50. http://dx.doi.org/10.24246/aiti.v16i2.135-150.

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The Intrusion Prevention System (IPS) Snort is a server security System that can prevent attacks by examining and recording all data packets as well as recognizing packets with sensors, when the attack has been identified, IPS Snort will deny the access (block) and log of all data packets identified. However by using only IPS Snort which can only check and note the Allert attacks that are incoming in less sense to secure a server by collaborating with the other server's secure system in the sense of being able to make the network security of the server better. Honeypot Artillery chosen which works when there is a Hacker trying to penetrate through open ports can be detected as if hackers can break through the system, then Honeypot Artillery will provide information about who attackers and how the attacker could enter the Snort IPS system for later record in the database that can be viewed on the Web interface, Allert recorded on the experiment that has been done in the database as much as 9453 on TCP protocol as much as 9%, UDP as much as < 1%, and ICMP As much as 91%.

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Jerichow, Anders. "Taiwan i kort snor." Udenrigs, no. 2 (June 1, 2011): 102–6. http://dx.doi.org/10.7146/udenrigs.v0i2.118874.

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Li, Jing Jiao, Yong Chen, Ho Cholman, Zhen Lin Lu, and Ling Qiao Nan. "Design and Implementation of NIDS String Matching Based on SOPC." Advanced Materials Research 424-425 (January 2012): 551–54. http://dx.doi.org/10.4028/www.scientific.net/amr.424-425.551.

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String matching is a key problem in many network processing applications. Current implementations of this process using software are time consuming. This paper presents a string matching system that based on FPGA. This paper uses DM9000A to receive network data and uses Snort rule and HashMem function to match pattern. With software simulation the conflict pattern of Snort rules found out and processed separately. In the system, conflict can be high-speed solved. With the PC handle string matching that more than 16 Byte, the FPGA processing speed has improved greatly .The experimental results show that the system throughput is 1.22Gbps, more than 20 times of the software method. When processing more Snort rules system throughput is not affected. Experimental results show that the system can quickly adapt to the demand for hardware reconfiguration and meet the network application requirements.

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Ng, Andrew Keong, and Tong San Koh. "Analysis and Modeling of Snore Source Flow With Its Preliminary Application to Synthetic Snore Generation." IEEE Transactions on Biomedical Engineering 57, no. 3 (March 2010): 552–60. http://dx.doi.org/10.1109/tbme.2009.2034139.

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Marta, I. Komang Krisna Ade, I. Nyoman Buda Hartawan, and I. Kadek Susila Satwika. "ANALISIS SISTEM MONITORING KEAMANAN SERVER DENGAN SMS ALERT BERBASIS SNORT." INSERT : Information System and Emerging Technology Journal 1, no. 1 (June 25, 2020): 25. http://dx.doi.org/10.23887/insert.v1i1.25874.

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AbstrakKeamanan server merupakan hal penting yang perlu diberikan perhatian lebih saat melakukan konfigurasi server. Pada umumnya serangan yang terjadi pada server diketahui setelah terjadinya kegagalan pada server dalam memberikan layanan. Pada penelitian ini, dibangun sebuah sistem keamanan server yang dapat melakukan monitoring pada sebuah server ketika terdeteksi adanya aktivitas yang tidak wajar. Pemberitahuan akan dikirimkan melalui SMS (Short Message Service) ke handphone Administrator jaringan. Sistem yang dibangun melakukan pendeteksian intrusi pada server secara realtime menggunakan SNORT. Ketika terjadi akses yang tidak wajar pada server, maka SNORT akan mendeteksi dan mengirimkan informasi terjadinya aktivitas yang tidak wajar ke Administrator jaringan. Sistem ini diujikan dengan lima jenis serangan yakni PING Attack, DoS/DDoS Attack, Port Scanning, Telnet Access dan FTP Access. Parameter yang diamati pada penelitian ini adalah beban aktivitas yang terjadi pada sumber daya server meliputi CPU, Memory (RAM) dan beban jaringan. Hasil penelitian menunjukkan bahwa saat terjadi upaya serangan terhadap server, SNORT dapat menghasilkan alert yang akan disimpan pada log sekaligus dikirimkan ke handphone Administrator melalui SMS. AbstractServer security is an important thing that needs to be given more attention when configuring a server. In general, attacks that occur on the server are known after a failure on the server in providing services. In this study, a server security system was built that could monitor a server when an unusual activity was detected. Notifications will be sent via SMS (Short Message Service) to the network Administrator's smartphone. The system is built to detect intrusions on the server in real time using SNORT. When improper access occurs on the server, SNORT will detect and send information about the occurrence of unusual activity to the network Administrator. This system is tested with five types of attacks namely PING Attack, DoS / DDoS Attack, Port Scanning, Telnet Access and FTP Access. The parameters observed in this study are the activity load that occurs on server resources including CPU, Memory (RAM) and network load. The results showed that when an attempt was made to attack the server, SNORT could produce alerts that would be stored in a log as well as sent to the Administrator's smartphone via SMS.

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Murali, Rajmohan, Chitra Desilva, John F. Thompson, and Richard A. Scolyer. "Non-Sentinel Node Risk Score (N-SNORE): A Scoring System for Accurately Stratifying Risk of Non-Sentinel Node Positivity in Patients With Cutaneous Melanoma With Positive Sentinel Lymph Nodes." Journal of Clinical Oncology 28, no. 29 (October 10, 2010): 4441–49. http://dx.doi.org/10.1200/jco.2010.30.9567.

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Purpose Sentinel node (SN) biopsy allows identification of patients with melanoma at risk of further metastatic disease in regional non-sentinel nodes (NSN). We investigated clinicopathologic factors that predict NSN positivity in an attempt to identify patients who may be safely spared completion lymph node dissection (CLND). Patients and Methods Clinicopathologic factors previously shown to be predictive of NSN positivity were analyzed in 409 patients with SN-positive disease (309 of whom underwent CLND) managed at a single melanoma center. A weighted score Non-Sentinel Node Risk Score [N-SNORE] incorporating predictive factors was derived, and the efficacy of N-SNORE at stratifying risk of NSN involvement was studied. Results Factors independently predictive of NSN positivity included primary tumor regression, proportion of harvested SNs involved by melanoma (%PosSN), sex (trend), and SN tumor burden indices (maximum size of largest deposit [MaxSize], % cross-sectional area of SN occupied by tumor, tumor penetrative depth, intranodal location of tumor) and perinodal lymphatic invasion (PLI). Of SN tumor burden criteria, MaxSize was the strongest predictor. N-SNORE was the sum of scores for five parameters: sex (female = 0, male = 1), regression (absent = 0, present = 2), %PosSN (absent = 0, present = 2), MaxSize (≤ 0.5 mm = 0, 0.51 to 2.00 mm = 1, 2.01 to 10.00 mm = 2, > 10.00 mm = 3), and PLI (absent = 0, present = 3). N-SNOREs of 0, 1 to 3, 4 to 5, 6 to 7, and ≥ 8 were associated with very low (0%), low (5% to 10%), intermediate (15% to 20%), high (40% to 50%), and very high (70% to 80%) risks of NSN involvement. Conclusion A weighted score (N-SNORE) based on clinicopathologic characteristics accurately stratifies risk of NSN involvement in patients with melanoma. If validated in future studies, N-SNORE will better predict prognosis, aid in management decisions, and stratify patient groups for entry into clinical trials.

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Ananta, Ahmadi Yuli. "SELEKSI NOTIFIKASI SERANGAN BERBASIS IDS SNORT MENGGUNAKAN METODE K-MEANS." SMARTICS Journal 3, no. 2 (October 31, 2017): 31–37. http://dx.doi.org/10.21067/smartics.v3i2.1954.

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Berkembangnya teknologi saat ini diikuti juga dengan berkembangnya serangan untuk merusak teknologi tersebut khususnya didalam jaringan komputer seperti DOS attack, port scanning, sniffer dll. Oleh karena itu dibutuhkan sebuah sistem yang bisa mendeteksi serangan secara realtime. Penyeleksian notifikasi serangan pada jaringan komputer berbasis IDS snort menggunakan metode k-means adalah sistem yang mendeteksi serangan jaringan berdasarkan data log pada snort dengan cara mengelompokkan data log tersebut menjadi 2 jenis serangan, bahaya dan tidak bahaya. Kemudian sistem ini akan mengirimkan notifikasi berupa SMS lewat aplikasi SMS gateway untuk serangan yang berjenis bahaya ke ponsel administrator jaringan. Sistem ini mendeteksi jenis serangan dengan proses pengelompokkan dari 100 data training yang diambil secara acak dari rules yang ada di snort. Proses pengelompokkan jenis serangan ini menggunakan metode k-means karena metode ini dapat mengelompokkan data dengan ukuran besar dengan cepat. Tentunya metode ini sangat ditentukan oleh pembangkitan centroid awal yang di ambil secara acak.

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Panggabean, Parningotan. "ANALISIS NETWORK SECURITY SNORT METODE INTRUSION DETECTION SYSTEM UNTUK OPTIMASI KEAMANAN JARINGAN KOMPUTER." Jursima 6, no. 1 (June 8, 2018): 1. http://dx.doi.org/10.47024/js.v6i1.107.

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<p><em>Perkembangan teknologi informasi, khususnya jaringan komputer memungkinkan terjadinya pertukaran informasi yang mudah, cepat dan semakin kompleks. Keamanan jaringan komputer harus diperhatikan guna menjaga validitas dan integritas data serta informasi yang berada dalam jaringan tersebut. Masalah yang dihadapi adalah adanya Log Bug yang didapatkan pada komputer server Dinas Lingkungan Hidup Kota Batam yang diindikasikan adanya serangan Denial of Service (DoS) pada komputer tersebut. Berdasarkan masalah diatas maka penulis mencoba membuat sebuah penelitian yang berjudul “Analisis Network Security Snort menggunakan metode Intrusion Detection System (IDS) untuk Optimasi Keamanan Jaringan Komputer” dan diharapkan dapat mendeteksi serangan Denial of Service (DoS). Intrusion Detection System (IDS) adalah sebuah tool, metode, sumber daya yang memberikan bantuan untuk melakukan identifikasi, memberikan laporan terhadap aktivitas jaringan komputer. Aplikasi yang digunakan untuk mendeteksi serangan menggunakan Snort. Snort dapat mendeteksi serangan DoS. Serangan DoS dilakukan dengan menggunakan aplikasi Loic.</em></p>

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Flanagan, Dennis. "A Removable Snore Reduction Appliance for a Mandibular Edentulous Patient." Journal of Oral Implantology 35, no. 5 (October 1, 2009): 221–24. http://dx.doi.org/10.1563/aaid-joi-d-09-00007.1.

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Abstract A snore reduction appliance can be constructed for the atrophic mandibular edentulous patient. Two endosseous implants can be surgically placed that retain a complete mandibular denture and, in turn, an overlying bimaxillary removable snore reduction appliance. A dual laminate appliance is vacu-form fitted to the maxillary teeth and the mandibular denture and luted in a protrusive relation with cold cure acrylic. The appliance maintains the mandible in a protrusive position to open the upper airway to reduce snoring.

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Arman, Molavi, and Nur Rachmat. "IMPLEMENTASI SISTEM KEAMANAN WEB SERVER MENGGUNAKAN PFSENSE." Jusikom : Jurnal Sistem Komputer Musirawas 5, no. 1 (May 31, 2020): 13–23. http://dx.doi.org/10.32767/jusikom.v5i1.752.

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Seorang network administrator haruslah memiliki amanat dan rasa tanggung jawab terhadap network tempat dia bekerja dan mengamankan sumber daya perangkat device network sebagaimana mestinya. Kampus adalah salah satu tempat dosen, mahasiswa dan karyawan sebagai pengguna internet dan sistem informasi akademik kampus yang berbasis web. Pengguna atau user bisa menggunakan fasilitas dengan benar dan bisa pula menyalahgunakan ataupun tanpa sengaja mengganggu traffic network dan layanan sistem informasi pada kampus. Oleh karena itu, diperlukan suatu sistem dalam mengatasi dan menanggulangi penyalahgunaan kecerobohan sengaja atau tidak sengaja berupa ancaman terhadap web server. Sistem yang mendeteksi gangguan keamanan ini diimplementasikan dengan menggunakan aplikasi snort pada pfsense dan pfsense sebagai sistem operasi router yang diletakkan berhadapan dengan internet. Metode penelitian menggunakan PPDIOO sebagai metode pengembangan dalam implementasi. Berdasarkan hasil percobaan sistem snort mampu mengetahui sebagai alert dan menyimpannya di dalam log seperti serangan ping of death dan slowloris. Berdasarkan log snort pfsense mampu melakukan pemblokiran otomatis dalam durasi tertentu

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Falaleeva, Marina, Amadis Pages, Zaneta Matuszek, Sana Hidmi, Lily Agranat-Tamir, Konstantin Korotkov, Yuval Nevo, Eduardo Eyras, Ruth Sperling, and Stefan Stamm. "Dual function of C/D box small nucleolar RNAs in rRNA modification and alternative pre-mRNA splicing." Proceedings of the National Academy of Sciences 113, no. 12 (March 8, 2016): E1625—E1634. http://dx.doi.org/10.1073/pnas.1519292113.

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C/D box small nucleolar RNAs (SNORDs) are small noncoding RNAs, and their best-understood function is to target the methyltransferase fibrillarin to rRNA (for example,SNORD27performs 2′-O-methylation of A27 in 18S rRNA). Unexpectedly, we found a subset of SNORDs, includingSNORD27, in soluble nuclear extract made under native conditions, where fibrillarin was not detected, indicating that a fraction of theSNORD27RNA likely forms a protein complex different from canonical snoRNAs found in the insoluble nuclear fraction. As part of this previously unidentified complex,SNORD27regulates the alternative splicing of the transcription factorE2F7pre-mRNA through direct RNA–RNA interaction without methylating the RNA, likely by competing withU1small nuclear ribonucleoprotein (snRNP). Furthermore, knockdown ofSNORD27activates previously “silent” exons in several other genes through base complementarity across the entireSNORD27sequence, not just the antisense boxes. Thus, some SNORDs likely function in both rRNA and pre-mRNA processing, which increases the repertoire of splicing regulators and links both processes.

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Shah, Syed Ali Raza, Biju Issac, and Seibu Mary Jacob. "Intelligent Intrusion Detection System Through Combined and Optimized Machine Learning." International Journal of Computational Intelligence and Applications 17, no. 02 (June 2018): 1850007. http://dx.doi.org/10.1142/s1469026818500074.

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In this paper, an existing rule-based intrusion detection system (IDS) is made more intelligent through the application of machine learning. Snort was chosen as it is an open source software and though it was performing well, it showed false positives (FPs). To find the best performing machine learning algorithms (MLAs) to use with Snort so as to improve its detection, we tested some algorithms on three available datasets. Support vector machine (SVM) was chosen along with fuzzy logic and decision tree based on their accuracy. Combined versions of algorithms through ensemble SVM along with other variants were tried on the generated traffic of normal and malicious packets at 10[Formula: see text]Gbps. Optimized versions of the SVM along with firefly and ant colony optimization (ACO) were also tried, and the accuracy improved remarkably. Thus, the application of combined and optimized MLAs to Snort at 10[Formula: see text]Gbps worked quite well.

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Widodo, Rio, and Imam Riadi. "Intruder Detection Systems on Computer Networks Using Host Based Intrusion Detection System Techniques." Buletin Ilmiah Sarjana Teknik Elektro 3, no. 1 (January 13, 2021): 21. http://dx.doi.org/10.12928/biste.v3i1.1752.

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The openness of access to information raises various problems, including maintaining the validity and integrity of data, so a network security system is needed that can deal with potential threats that can occur quickly and accurately by utilizing an IDS (intrusion detection system). One of the IDS tools that are often used is Snort which works in real-time to monitor and detect the ongoing network by providing warnings and information on potential threats in the form of DoS attacks. DoS attacks run to exhaust the packet path by requesting packets to a target in large and continuous ways which results in increased usage of CPU (central processing unit), memory, and ethernet or WiFi networks. The snort IDS implementation can help provide accurate information on network security that you want to monitor because every communication that takes place in a network, every event that occurs and potential attacks that can paralyze the internet network are monitored by snort.

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Pettit. "When Smitty Stopped Pretending to Snore." Eugene O'Neill Review 36, no. 2 (2015): 150. http://dx.doi.org/10.5325/eugeoneirevi.36.2.0150.

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Tasneem, Aaliya, Abhishek Kumar, and Shabnam Sharma. "Intrusion Detection Prevention System using SNORT." International Journal of Computer Applications 181, no. 32 (December 17, 2018): 21–24. http://dx.doi.org/10.5120/ijca2018918280.

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Michaelson, Peter G., and Eric A. Mair. "Popular Snore Aids: Do They Work?" Otolaryngology–Head and Neck Surgery 130, no. 6 (June 2004): 649–58. http://dx.doi.org/10.1016/j.otohns.2003.11.008.

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49

Ahmed, Ghilman, Muhammad Naeem Ahmed Khan, and Muhammad Shamraiz Bashir. "A Linux-based IDPS using Snort." Computer Fraud & Security 2015, no. 8 (August 2015): 13–18. http://dx.doi.org/10.1016/s1361-3723(15)30076-2.

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Phillips, B. A. "Popular Snore Aids: Do They Work?" Yearbook of Pulmonary Disease 2006 (January 2006): 250. http://dx.doi.org/10.1016/s8756-3452(08)70202-0.

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