430 research outputs found
HEVC-SVS: Low-level HEVC features and CNN features for TVSum, SumMe, OVP and VSUMM datasets
No full textProposed HEVC feature sets along with CNN features from GoogleNet, AlexNet, Inception-ResNet-V2, and VGG16 for TVSum, SumMe, OVP and VSUMM datasets. The new modified datasets names are "HEVC-SVS-TVSum", "HEVC-SVS-SumMe", "HEVC-SVS-OVP" and "HEVC-SVS-VSUMM", respectively.The datasets contain the original ground truth data they came with, and these stayed unmodified.Upon using any of these datasets, please do cite our publications where we proposed the HEVC feature set for the first time:If you are using (HEVC-SVS-OVP) and/or (HEVC-SVS-VSUMM) datasets: https://ieeexplore.ieee.org/document/9815254/@article{issa_cnn_2022,title = {{CNN} and {HEVC} {Video} {Coding} {Features} for {Static} {Video} {Summarization}},volume = {10},issn = {2169-3536},url = {https://ieeexplore.ieee.org/document/9815254/},doi = {10.1109/ACCESS.2022.3188638},urldate = {2022-09-29},journal = {IEEE Access},author = {Issa, Obada and Shanableh, Tamer},year = {2022},pages = {72080--72091},}If you are using (HEVC-SVS-TVSum) and/or (HEVC-SVS-SumMe) datasets: https://www.mdpi.com/2076-3417/13/10/6065@article{issa_static_2023,title = {Static {Video} {Summarization} {Using} {Video} {Coding} {Features} with {Frame}-{Level} {Temporal} {Subsampling} and {Deep} {Learning}},volume = {13},issn = {2076-3417},url = {https://www.mdpi.com/2076-3417/13/10/6065},doi = {10.3390/app13106065},number = {10},journal = {Applied Sciences},author = {Issa, Obada and Shanableh, Tamer},month = may,year = {2023},pages = {6065},}Make sure to also cite the original authors for each of the datasets:TVSum (https://people.csail.mit.edu/yalesong/tvsum/)SumMe (https://gyglim.github.io/me/vsum/index.html)OVP and VSUMM (https://www.sites.google.com/site/vsummsite/download)Acknowledgement:The work in this research project is supported by the American University of Sharjah under research grant number FRG22-E-E44. This research work represents the opinions of the author(s) and does not mean to represent the position or opinions of the American University of Sharjah
HEVC-SVS: Low-level HEVC features and CNN features for TVSum, SumMe, OVP and VSUMM datasets
No full text**HEVC-SVS Datasets**Proposed HEVC feature sets along with CNN features from GoogleNet, AlexNet, Inception-ResNet-V2, and VGG16 for TVSum, SumMe, OVP and VSUMM datasets. The new modified datasets names are "HEVC-SVS-TVSum", "HEVC-SVS-SumMe", "HEVC-SVS-OVP" and "HEVC-SVS-VSUMM", respectively.The datasets contain the original ground truth data they came with, and these stayed unmodified.Upon using any of these datasets, please do cite our publication where we proposed the HEVC feature set for the first time:If you are using (HEVC-SVS-OVP) and/or (HEVC-SVS-VSUMM) datasets:@article{issa_cnn_2022,title = {{CNN} and {HEVC} {Video} {Coding} {Features} for {Static} {Video} {Summarization}},volume = {10},copyright = {Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC-BY-NC-ND)},issn = {2169-3536},url = {https://ieeexplore.ieee.org/document/9815254/},doi = {10.1109/ACCESS.2022.3188638},urldate = {2022-09-29},journal = {IEEE Access},author = {Issa, Obada and Shanableh, Tamer},year = {2022},pages = {72080--72091},}If you are using (HEVC-SVS-TVSum) and/or (HEVC-SVS-SumMe) datasets:{ PENDING }Make sure to also cite the original authors for each of the datasets:TVSum:@INPROCEEDINGS{7299154, author = {Yale Song and Vallmitjana, Jordi and Stent, Amanda and Jaimes, Alejandro}, booktitle = {2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, title = {TVSum: Summarizing web videos using titles}, year = {2015}, volume = {}, number = {}, pages = {5179-5187}, doi = {10.1109/CVPR.2015.7299154}}SumMe:@inproceedings{GygliECCV14, author ={Gygli, Michael and Grabner, Helmut and Riemenschneider, Hayko and Van Gool, Luc}, title = {Creating Summaries from User Videos}, booktitle = {ECCV}, year = {2014}}OVP and VSUMM:@article{Avila, title = "VSUMM: A mechanism designed to produce static video summaries and a novel evaluation method", journal = "Pattern Recognition Letters", volume = "32", number = "1", pages = "56 - 68", year = "2011", note = "<ce:title>Image Processing, Computer Vision and Pattern Recognition in Latin America</ce:title>", issn = "0167-8655", doi = "10.1016/j.patrec.2010.08.004", author = "Sandra Eliza Fontes de Avila and Ana Paula Brand„o Lopes and Antonio da Luz Jr. and Arnaldo de Albuquerque Ara˙jo",}Acknowledgement:The work in this research project is supported by the American University of Sharjah under research grant number FRG22-E-E44. This research work represents the opinions of the author(s) and does not mean to represent the position or opinions of the American University of Sharjah
Optimasi Proses Klasterisasi di MySQL DBMS dengan Mengintegrasikan Algoritme MIC-Kmeans Menggunakan Bahasa SQL dalam Stored Procedure
Get PDFProses klasterisasi data di DBMS akan lebih efisien jika dilakukan langsung di dalam DBMS itu sendiri karena DBMS mendukung untuk pengelolaan data yang baik. SQL-Kmeans merupakan salah satu metode yang sebelumnya telah digunakan untuk mengintegrasikan algoritme klasterisasi K-means ke dalam DBMS menggunakan SQL. Akan tetapi, metode ini juga membawa kelemahan dari algoritme K-means itu sendiri yaitu lamanya iterasi untuk mencapai konvergen dan keakuratan hasil klasterisasi yang belum optimal akibat dari proses inisialisasi centroid awal secara acak. Algoritme Median Initial Centroid (MIC)-Kmeans merupakan pengembangan dari algoritme K-means yang bisa memberikan solusi optimal dalam menentukan awal centroid yang berdampak pada keakuratan dan lamanya iterasi. Dengan keunggulan yang dimiliki algoritme MIC-Kmeans, maka dalam penelitian ini dipilih sebagai alternatif algoritme yang diintegrasikan dalam proses klasterisasi data secara langsung di DBMS menggunakan SQL. Proses integrasinya meliputi 4 tahap yaitu tahap inisialisasi tabel dataset, tahap pemetaan algoritme MIC-Kmeans pada SQL dan tabel dataset, tahap perancangan SQL untuk tiap hasil pemetaan dan tahap implementasi rancangan SQL dalam MySQL stored procedure. Hasil pengujian menunjukkan bahwa metode SQL MIC-Kmeans bisa mengurangi 43% jumlah iterasi dan mengurangi 39% waktu yang dibutuhkan dari metode SQL-Kmeans untuk mencapai konvergen. Selain itu, nilai rata-rata silhouette coefficient metode SQL MIC-Kmeans adalah 0,79 dan masuk dalam kategori strong structure (nilai rentang 0,7 sampai 1). Sedangkan nilai rata-rata silhouette coefficient metode SQL-Kmeans adalah 0,68 dan masuk dalam kategori medium structure (nilai rentang 0,5 sampai 0,7).AbstractThe process of data clustering in the DBMS will be more efficient because the DBMS supports good data management. SQL-Kmeans is a method that has been used to integrate K-means clustering algorithms into DBMS using SQL. However, it carries the weakness of the K-means algorithm itself in the duration of iterations to reach convergence and the accuracy of clustering due to the centroid initialization process randomly. Median Initial Centroid (MIC)-Kmeans algorithm is a development of the K-means algorithm that can provide the optimal solution in determining the initial centroid which has an impact on the accuracy and duration of iterations. With the advantages of the MIC-Kmeans algorithm, the method was chosen as an alternative algorithm to be integrated in the DBMS using SQL for a clustering. The integration process includes 4 stages, there are dataset initialization, SQL algorithm mapping and dataset table, SQL design for each mapping result, and implementation SQL in the MySQL stored procedure. The test results show that the SQL MIC-Kmeans method can reduce 43% the number of iterations and reduce 39% of the time required from the SQL-Kmeans method to reach convergence. In addition, the average value of the coefficient SQL MIC-Kmeans method is 0.79 and categorized as strong structure (value ranges from 0.7 to 1). While, the average value of the coefficient SQL-Kmeans method is 0.68 and categorized as medium structure (value ranges from 0.5 to 0.7)
Integrasi Algoritma K-Means Dengan Bahasa SQL Untuk Klasterisasi IPK Mahasiswa (Studi Kasus: Fakultas Ilmu Komputer Universitas Brawijaya)
Get PDFAbstrakSecara umum, aplikasi klasterisasi diimplementasikan di luar DBMS dengan mengambil data terlebih dahulu dari basisdata untuk disimpan sementara dalam variabel program (misal dalam sebuah array), kemudian baru dilakukan proses klasterisasi. Permasalahan waktu dan keamanan dalam pengambilan data dari DBMS dan besarnya data yang akan diklasterisasi mendorong metode lain dimana proses klasterisasi bisa langsung dilakukan di DBMS. Klasterisasi dilakukan dengan mengintegrasikan algoritma klasterisasi pada DBMS menggunakan bahasa SQL. Pada penelitian ini difokuskan pada perancangan dan pengimplementasian integrasi algoritma klasterisasi K-means pada Relational DBMS dengan menggunakan bahasa SQL. Proses klasterisasi dilakukan dengan studi kasus data akademik mahasiswa di Fakultas Ilmu Komputer universitas Brawijaya dengan fitur IPK, sks tempuh, sks lulus dan semester. Berdasarkan hasil uji coba dataset akademik dengan variasi jumlah dimensi, jumlah klaster dan metode perhitungan jarak yang berbeda, telah didapatkan hasil pengklasteran data dengan benar. Berdasarkan hasil perhitungan kompleksitas waktu untuk tiap tahap implementasi K-means menggunakan SQL dan tanpa SQL, menunjukkan hasil kompleksitas waktu asimptotik yang sama dimana tahap menghitung euclidean distance membutuhkan kompleksitas waktu yang paling tinggi.Kata kunci: Clustering, K-means, SQL, IPK (Indeks Prestasi Kumulatif)AbstractGenerally, clustering implemented with taking data from database to be stored temporarily in a program variable (eg, in an array) then continue with clustering process. Direct clustering where the data is stored by integrating the clustering algorithm using the SQL language on the DBMS is proposed. In this study focused on the design and implementation of K-means clustering algorithm on a Relational DBMS using the SQL language. The clustering process carried out with a case study of GPA student in the Faculty of Computer Science University of Brawijaya. Based on results with a variety of dimensions, the number of clusters and different distance calculation methods, has obtained clustering data correctly. Based on time complexity to review each stage of the implementation K - means using SQL and without SQL, showing the same results of asymptotic time complexity where phase euclidean distance still requires the highest time complexity.Keywords: Clustering, K-means, SQL, GPA (Grade Point Average)AbstrakSecara umum, aplikasi klasterisasi diimplementasikan di luar DBMS dengan mengambil data terlebih dahulu dari basisdata untuk disimpan sementara dalam variabel program (misal dalam sebuah array), kemudian baru dilakukan proses klasterisasi. Permasalahan waktu dan keamanan dalam pengambilan data dari DBMS dan besarnya data yang akan diklasterisasi mendorong metode lain dimana proses klasterisasi bisa langsung dilakukan di DBMS. Klasterisasi dilakukan dengan mengintegrasikan algoritma klasterisasi pada DBMS menggunakan bahasa SQL. Pada penelitian ini difokuskan pada perancangan dan pengimplementasian integrasi algoritma klasterisasi K-means pada Relational DBMSdengan menggunakan bahasa SQL. Proses klasterisasi dilakukan dengan studi kasus data akademik mahasiswa di Fakultas Ilmu Komputer universitas Brawijaya dengan fitur IPK, sks tempuh, sks lulus dan semester. Berdasarkan hasil uji coba dataset akademik dengan variasi jumlah dimensi, jumlah klaster dan metode perhitungan jarak yang berbeda, telah didapatkan hasil pengklasteran data dengan benar. Berdasarkan hasil perhitungan kompleksitas waktu untuk tiap tahap implementasi K-means menggunakan SQL dan tanpa SQL, menunjukkan hasil kompleksitas waktu asimptotik yang sama dimana tahap menghitung euclidean distance membutuhkan kompleksitas waktu yang paling tinggi. Kata kunci: Clustering, K-means, SQL, IPK (Indeks Prestasi Kumulatif)Abstract
Generally, clustering implemented with taking data from database to be stored temporarily in a program variable (eg, in an array) then continue with clustering process.Directclustering where the data is storedby integrating the clustering algorithm using the SQL language on the DBMS is proposed.In this study focused on the design and implementation of K-means clustering algorithm on a Relational DBMS using the SQL language. The clustering process carried out with a case study of GPA student in the Faculty of Computer Science University of Brawijaya.Based on results with a variety of dimensions, the number of clusters and different distance calculation methods, has obtained clustering data correctly. Based on time complexity to review each stage of the implementation K - means using SQL and without SQL, showing the same results of asymptotic time complexity where phase euclidean distance still requires the highest time complexity. Keywords: Clustering, K-means, SQL, GPA (Grade Point Average
A folkloristic image of homeland in the novel „The Issa valley“ by Czesław Miłosz
No full texte-ISSN 2029-8692The article reveals that the novel The Issa valley by Czesław Miłosz aims to represent the Issa valley as a preserver of an archaic cultural heritage, mainly by using folklore genres which have preserved mythical thinking (mythological songs, belief legends and historical legends). It may be observed that nearly all folklore material at least in some detail is associated with the river Issa – the fulcrum of the represented world. In the novel, folklore material is employed when the author seeks to reveal a junction of paganism and Christianity and the battle between them, which continues both in the collective world outlook of the inhabitants of the Issa valley and in the inner world of a particular person. Orienting himself to folkloristic prototypes, the author in his novel epitomizes individual characters. Moreover, the article discloses that mythological songs about the Sun and the Moon, which in the novel are introduced as registered on the river Issa (Nevėžis is a prototype of Issa), in reality are taken from a song collection by L. Rėza Dainos oder Litthauische Volkslieder (1825), published in Lithuania Minor.Kultūrų studijų katedra / Department of Cultural StudiesHumanitarinių mokslų fakultetas / Faculty of HumanitiesVytauto Didžiojo universitetas / Vytautas Magnus Universit
PEMAKNAAN SIMBOL MATSU (マツ) DALAM ANTOLOGI HAIKU ISSA AND BEING HUMAN KAJIAN SEMIOTIKA 「Issa And Being Human」という俳句のアンソロジにおけるマツのシンボの意味『記号論研究』
Get PDFABSTRACT
Azzahra, Qonita. 2018. "Meaning of the Matsu Symbol (マツ) in the Anthology of Haiku Issa And Being Human Semiotics Study". Thesis S1 Japanese Language and Culture Program, Faculty of Cultural Sciences, Diponegoro University. Supervisor Nur Hastuti, S.S., M.Hum.
This study examines the meaning of the pine symbol found in Kobayashi Issa's haiku and the relation between the pine symbol and the background of Issa's life. The author will analyze five haiku which contain pine symbols, from the anthology of Issa And Being Human Haiku (Lanoue in 2017). This study aims to find the meaning of pine symbols and how they relate to the background of the life of Kobayashi Issa.
The method used in this study is literature study. Whereas to analyze the meaning of the pine symbol found in haiku, uses the semiotic theory of C.S. Peirce. After knowing the true meaning of the pine symbol, the author then relates it to the background of the life of Kobayashi Issa. This way is to find out if there is a connection between the pine symbols and the background of the life of Kobayashi Issa.
From the analysis, it is known that the symbol of pine could mean strength, fortitude, kindness, longevity, and a bright future / luck. While the relationship between the pine symbol and the background of the life of Kobayashi Issa is as a description of the properties that Issa has or wants. Living side by side with pine trees makes Issa very understanding of the true characters of pine. That is why he put a lot of pine symbols into his haiku to describe his own nature.
Keywords: semiotics, Kobayashi Issa, symbol of pine, Issa's life
A contribution to the study of Gnathia ware from Issa
Get PDFKeramika tipa Gnathia pronađena je na 38 nalazišta duž istočne
obale Jadrana i bliže mu unutrašnjosti. Ipak, najviše posuda te
keramičke vrste pronađeno je u antičkoj Isi. Brojnost i određene
značajke u obliku i ukrasu na posudama iz Ise otvorile su
pretpostavku o lokalnoj isejskoj proizvodnji keramike tipa
Gnathia. Prvi je tu pretpostavku iznio Branko Kirigin. Na temelju
proučavanja grobnog inventara s nekropole na Martvilu u Visu
podijelio je posude tipa Gnathia iz Ise u četiri faze. Autorica je
pomoću arheoloških komparativnih metoda analize dekoracije i
morfologije na svim dosad objavljenim posudama ove vrste na
istočnom Jadranu usporedila novije spoznaje o ovoj keramičkoj
vrsti s Kiriginovim tezama. Također je ponudila razvoj tipologije
posuda isejske keramike tipa Gnathia unutar kronološkog okvira
od sredine 3. do kraja 2. st. pr. Kr.Gnathia ware was found at 38 sites on the eastern Adriatic coast
and its immediate interior. Nonetheless, the most vessels of this
pottery type were found in Antique-era Issa. The high number
and specific characteristics in the shape and ornamentation on
the vessels from Issa have led to the hypothesis on local Issa
production of this pottery type. Branko Kirigin first stated this
hypothesis on the basis of study of the tomb inventory from the
necropolis at Martvilo in Vis, dividing the Gnathia vessels from
Issa into four phases. Using stylistic methods for the attribution
of painters and groups, analysis of morphology on all vessels thus
far published in the eastern Adriatic, the author compared new
knowledge on this pottery type with Kirigin’s theses. She also offers
a development of the typology of the Issa Gnathia ware vessels
inside a chronological framework from the mid-third to the end of
the second century BC
The Endurance of Palestinian Political Factions
No full textThe Endurance of Palestinian Political Factions is an ethnographic study of Palestinian political factions in Lebanon through an immersion in daily home life. Perla Issa asks how political factions remain the center of political life in the Palestinian camps in the face of mounting criticism. Through an examination of the daily, mundane practices of refugees in Nahr el-Bared camp in particular, this book shows how intimate, interpersonal, and kin-based relations are transformed into political networks and offers a fresh analysis of how those networks are in turn metamorphosed into political structures. By providing a detailed and intimate account of this process, this book reveals how factions are produced and reproduced in everyday life despite widespread condemnation. “Utilizing rich ethnographic fieldwork, Perla Issa provides an engaging analysis of Palestinian factions in the refugee camp of Nahr el-Bared. Her book illuminates the centrality of political factions to quotidian social interactions and the rhythms of everyday life.” Adam Hanieh, author of Money, Markets, and Monarchies: The Gulf Cooperation Council and the Political Economy of the Contemporary Middle East “How do political factions maintain centrality in Palestinian political life even when they are widely unpopular and even delegitimized? How are such factions reproduced in the face of widespread condemnation? The questions that animate this manuscript are vitally important.” Ilana Feldman, author of Life Lived in Relief: Humanitarian Predicaments and Palestinian Refugee Politic
The Endurance of Palestinian Political Factions
Get PDFThe Endurance of Palestinian Political Factions is an ethnographic study of Palestinian political factions in Lebanon through an immersion in daily home life. Perla Issa asks how political factions remain the center of political life in the Palestinian camps in the face of mounting criticism. Through an examination of the daily, mundane practices of refugees in Nahr el-Bared camp in particular, this book shows how intimate, interpersonal, and kin-based relations are transformed into political networks and offers a fresh analysis of how those networks are in turn metamorphosed into political structures. By providing a detailed and intimate account of this process, this book reveals how factions are produced and reproduced in everyday life despite widespread condemnation. “Utilizing rich ethnographic fieldwork, Perla Issa provides an engaging analysis of Palestinian factions in the refugee camp of Nahr el-Bared. Her book illuminates the centrality of political factions to quotidian social interactions and the rhythms of everyday life.” Adam Hanieh, author of Money, Markets, and Monarchies: The Gulf Cooperation Council and the Political Economy of the Contemporary Middle East “How do political factions maintain centrality in Palestinian political life even when they are widely unpopular and even delegitimized? How are such factions reproduced in the face of widespread condemnation? The questions that animate this manuscript are vitally important.” Ilana Feldman, author of Life Lived in Relief: Humanitarian Predicaments and Palestinian Refugee Politic
The meaning and syntax of mental verb predicates in the Issa Valley by Czesław Milosz
No full textThe author discusses the ways concepts are expressed in Czesław Milosz's novel Issa Valley, analyzing formal and semantic features of mental verb predicates and phraseological connotations functioning as such predicates in contexts. She emphasizes the lack of border features and social differences between the nobility and villagers speech in the lexis defining thinking processes.414916
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