scholarly journals Unsupervised Classification of Hydrophone Signals With an Improved Mel-Frequency Cepstral Coefficient Based on Measured Data Analysis

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 124937-124947 ◽  
Author(s):  
Kunde Yang ◽  
Xingyue Zhou
Keyword(s):  
Data Analysis ◽  
Unsupervised Classification ◽  
Measured Data ◽  
Mel Frequency Cepstral Coefficient

Clustering Analysis and Algorithms

2011 ◽  
pp. 389-396
Author(s):  
Xiangji Huang
Keyword(s):  
Cluster Analysis ◽  
Data Analysis ◽  
Clustering Analysis ◽  
Supervised Classification ◽  
Unsupervised Classification ◽  
Automatic Classification ◽  
Multidimensional Space ◽  
The Difference

Clustering is the process of grouping a collection of objects (usually represented as points in a multidimensional space) into classes of similar objects. Cluster analysis is a very important tool in data analysis. It is a set of methodologies for automatic classification of a collection of patterns into clusters based on similarity. Intuitively, patterns within the same cluster are more similar to each other than patterns belonging to a different cluster. It is important to understand the difference between clustering (unsupervised classification) and supervised classification.

Clustering Analysis and Algorithms

2011 ◽  
pp. 159-164 ◽  
Author(s):  
Xiangji Huang
Keyword(s):  
Cluster Analysis ◽  
Data Analysis ◽  
Clustering Analysis ◽  
Supervised Classification ◽  
Unsupervised Classification ◽  
Automatic Classification ◽  
Multidimensional Space ◽  
The Difference

Clustering is the process of grouping a collection of objects (usually represented as points in a multidimensional space) into classes of similar objects. Cluster analysis is a very important tool in data analysis. It is a set of methodologies for automatic classification of a collection of patterns into clusters based on similarity. Intuitively, patterns within the same cluster are more similar to each other than patterns belonging to a different cluster. It is important to understand the difference between clustering (unsupervised classification) and supervised classification.

Program Fajar Indah Sebagai Media Dakwah dalam Meningkatkan Pemahaman Keagamaan Masyarakat

2020 ◽  
Vol 5 (1) ◽  
pp. 21-38
Author(s):  
FAISAL AKBAR ◽  
Syamsuddin RS ◽  
Dadan Anugrah
Keyword(s):  
Qualitative Research ◽  
Data Analysis ◽  
Data Collection ◽  
Islamic Law ◽  
Public Trust ◽  
Broadcast Communication ◽  
Lecture Method ◽  
Radio Broadcast ◽  
Religious Understanding

Penelitian ini bertujuan untuk mengetahui metode Program Fajar Indah yang ada di Radio Citra Progo dalam meningkatkan pemahaman keagamaan masyarakat, mengetahui klasifikasi da’i pengisi program Fajar Indah, serta pesan dakwah dari program Fajar Indah. Penelitian ini menggunakan penelitian kualitatif dengan metode deskriptif. Pengumpulan data dalam penelitian ini menggunakan teknik observasi, wawancara dan dokumentasi. Analisis data digunakan penafsiran logika yang dihubungkan dengan konteks Komunikasi Penyiaran Islam. Hasil penelitian menunjukan bahwa Radio Citra Progo dalam program Fajar Indah menggunakan metode ceramah dengan pembawaan da’i yang santai ketika siaran. Adapun klasifikasi da’i dalam siaran dakwah ini, dapat dilihat dari wawasan keilmuan penyiar dalam menguasai Al Quran dan Hadist sebagai sumber hukum Islam dan kedisiplinan untuk menjalankan tugas sebagai da’i penyiar radio. Dalam siaran Program Fajar Indah terdapat pesan dakwah berupa materi Aqidah untuk meningkatkan kepercayaan masyarakat kepada Allah, mengimani rukun Iman dan rukun Islam, serta materi Akhlak yang diperintahkan oleh Allah dan dicontohkan oleh Nabi Muhammad SAW, materi Ibadah yang menyampaikan tatacara beribadah kepada Allah meliputi hukum pernikahan, hukum bertetangga, shodaqoh, sholat, puasa dan menyampaikan materi tentang hari-hari besar umat Islam. This study aims to determine the methods of the Beautiful Fajar Program on Radio Citra Progo in improving people's religious understanding, knowing the classification of preachers for the Fajar Indah program, and preaching messages from the Fajar Indah program. This study uses qualitative research with descriptive methods. Data collection in this study uses observation, interview and documentation techniques. Data analysis used the interpretation of logic connected with the context of Islamic Broadcast Communication. The results showed that Citra Progo Radio in the Fajar Indah program used a lecture method with a relaxed nature when broadcasting. The da'i classification in this da'wah broadcast, can be seen from the broadcaster's scientific insights in mastering the Qur'an and Hadith as a source of Islamic law and discipline to carry out their duties as radio broadcast preachers. In the broadcast of the Fajar Indah Program there is a da'wah message in the form of Aqeedah material to increase public trust in God, faith in the pillars of faith and pillars of Islam, as well as moral material ordered by God and exemplified by the Prophet Muhammad, the material of worship which conveys the procedure of worship to God including marriage law , neighborly law, shodaqoh, prayer, fasting and delivering material about the Muslim holidays.

Unsupervised classification of street architectures based on InfoGAN

2019 ◽  
Author(s):  
Ning Wang ◽  
Xianhan Zeng ◽  
Renjie Xie ◽  
Zefei Gao ◽  
Yi Zheng ◽  
...  
Keyword(s):  
Unsupervised Classification
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