Estimation of process capability based on continuous and attribute data

Runje, Biserka; Kondić, Živko; Novák, Antonín; Keran, Zdenka

doi:10.31803/tg-20190514132701

Cited by 2 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The importance of social media at times of disaster has been highlighted in many disaster emergency management practices and has attracted the attention of governments and research institutions. The available research methods are becoming highly diverse [Runje, 2019]. The early works on the use of social media in disaster situations have mostly relied on case studies.…”

Section: Social Media In Disaster Situationsmentioning

confidence: 99%

Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text

Bai¹,

Yu²,

Yu³

et al. 2021

jucs

View full text Add to dashboard Cite

With the rapid development of Internet information technology, the advantages of social media in terms of speed, content, form, and effect of communication are becoming increasingly significant. In recent years, more and more researchers have paid attention to the special value and role of social media tools in disaster information emergency management. Weibo is the most widely used Chinese social media tool. To effectively mine and apply the emergency function of disaster situation microblogs, a disaster situation information discovery and collection system capable of online incremental identification and collection are constructed for massive and disordered disaster microblog text streams. First, based on the deep learning- trained word vector model and a large-scale corpus, an unsupervised short-text feature representation method of disaster situation Weibo information is developed. According to the experimental results of the feature combination test and the training set scale test, the SVM algorithm was selected for disaster microblog information classification, which realized effective identification of disaster situation micro-bloggings. Then, the temporal information similarity and geographic information similarity are used to improve the single text similarity algorithm, and a Chinese disaster event online real-time detection model is constructed. Furthermore, the disaster-affected areas can be achieved in real-time based on the detection results. By crawling and classifying the micro-bloggings from the disaster-affected areas, it is possible to realize the incremental identification and collection of online disaster situation Weibo information. Finally, the empirical analysis of disaster events such as the “Leshan Earthquake” shows that the real- time intelligent identification and collection system for disaster situation Weibo micro-bloggings developed in this paper can obtain large-scale and useful data for disaster emergency management, which proving that this system is effective and efficient.

show abstract

Section: Social Media In Disaster Situationsmentioning

confidence: 99%

Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text

Bai¹,

Yu²,

Yu³

et al. 2021

jucs

View full text Add to dashboard Cite

show abstract

Process Capability Analysis for Qualitative Measures: Call Center Example

TERZİ KUMANDAŞ,

ELEVLİ

2023

Afyon Kocatepe University Journal of Sciences and Engineering

View full text Add to dashboard Cite

Üretilen ürün veya sunulan hizmetle ilgili kalite parametrelerinin önceden tahmin edilebilir ve kararlı bir yapıda olup olmadığını belirlemek üzere kontrol grafiklerinden yararlanılırken, tüketicilerin beklentilerini yansıtan spesifikasyonları karşılama düzeyini tespit etmek üzere süreç yeterlilik analizinden yararlanılmaktadır. “Uygun” ya da “Uygunsuz” gibi nitelemelerle ifade edilen nitel ölçümler için yapılan süreç yeterlilik analizi (SYA) çalışmalarının, sürekli rassal değişken olarak modellenen nicel ölçümler için yapılan çalışmalara kıyasla oldukça sınırlı düzeyde kaldığı görülmektedir. Oysaki çoğu üretim veya hizmet sürecinden, kaliteyle ilgili olumsuz gözlemlerin sayısına dayanan nitel ölçümler elde edilmektedir. Bu çalışmada bir özel hastanenin çağrı merkezinde kaçan (cevaplanmayan) çağrılara yönelik SYA yapılmıştır. Verilerin “kaçan” ve “cevaplanan” çağrı şeklinde iki kategoriden oluşan nitel ölçümlere dayanması nedeniyle Binom SYA’nden yararlanılmıştır. Dönemsel bazlı sigma seviyeleri üzerinden yapılan değerlendirme çağrı merkezi sürecinin yetersiz olduğunu göstermiştir. Son olarak ağaç diyagramı kullanılarak, sürecin iyileştirilmesine yönelik öneriler geliştirilmiştir.

show abstract

Estimation of process capability based on continuous and attribute data

Cited by 2 publications

References 4 publications

Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text

Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text

Process Capability Analysis for Qualitative Measures: Call Center Example

Contact Info

Product

Resources

About