scholarly journals Suicide Research and Adolescent Suicide Trends in New Zealand

2008 ◽  
Vol 8 ◽  
pp. 287-302 ◽  
Author(s):  
Said Shahtahmasebi
Keyword(s):  
Time Series ◽  
New Zealand ◽  
Adolescent Suicide ◽  
Time Series Data ◽  
Current Knowledge ◽  
Medical Model ◽  
Well Being ◽  
Young Person ◽  
Series Data ◽  
International Experts

In recent years, there have been a number of claims and counterclaims from suicide research using time series and longitudinal data; in particular, the linkage of increased antidepressant prescriptions to a decrease in suicide rates. Suicide time series appear to have a memory compounded with seasonal and cyclic effects. Failure to take into account these properties may lead to misleading conclusions, e.g., a downward blip is interpreted as the result of current knowledge and public health policies, while an upward blip is explained as suicide being complex depending on many variables requiring further research. In previous publications, I argued that this misuse of time series data is the result of an uncritical acceptance of a medical model that links mental ill-health to suicide. The consequences of such research behaviour are further increases in antidepressant prescriptions and medications to those who should not be prescribed them, with adverse effects showing across the population, e.g., the prescription of antidepressants to very young children (some under 1 year of age) in New Zealand. Moreover, the New Zealand Evidence-based Health Care Bulletin recommends an authoritarian approach for every interaction with a young person to check their psychosocial well-being. When viewed holistically, this kind of human behaviour makes researchers, policy makers (politicians), treatment, and practitioners, and society in general part of the problem rather than the solution. This paper explores some dynamic aspects of suicide, using only official data with particular reference to youth suicide, and suggests that the medical model of suicide is only an attempt to treat depression without addressing suicide, and recommends the creation of a unified database through understanding the society that individuals live in. It is hoped that this paper will stimulate debate and the collaboration of international experts regardless of their school of thought.

Time Series Analysis of Individual Music Therapy in Dementia

GeroPsych ◽  
2015 ◽  
Vol 28 (3) ◽  
pp. 113-122 ◽  
Author(s):  
Arthur Schall ◽  
Julia Haberstroh ◽  
Johannes Pantel
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Music Therapy ◽  
Time Series Data ◽  
Well Being ◽  
Research Area ◽  
Series Data ◽  
Communication Behavior ◽  
Series Analysis ◽  
Study Results

Abstract. This pilot study evaluated the effects of individual music therapy on communication behavior and emotional well-being in persons with advanced dementia. Contrary to more common qualitative designs in dementia-related music therapy research, we used time series analysis of videographed music therapy sessions. This quantitative statistical method for modeling and explaining time-dependent processual data has not been employed in this research area before. Based on aggregated time series data, the results showed positive and statistically significant intervention effects on participants’ communication behavior, situational well-being, and their expression of positive emotions. The study results indicate that, by choosing appropriate outcomes, video-based time series analysis is sensitive and well suited to displaying the effects of music therapy in dementia care.

scholarly journals The quest of tourism and overall well-being: the developing economy of Pakistan

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Asif Khan ◽  
Sughra Bibi ◽  
Jiaying Lyu ◽  
Mohammad Alam ◽  
Muhammad Mussa Khan ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Developing Economies ◽  
Tourism Development ◽  
Well Being ◽  
Series Data ◽  
Developing Economy ◽  
Content Type ◽  
Objective Indicators

Purpose This study aims to examine the causal relationship between tourism and overall well-being. The main objective of this research is to inform the policymakers that tourism can play a vital role in shaping the overall well-being in the developing economies. Design/methodology/approach This investigation used several time series techniques and procedures that include bounds test and autoregressive distributed lag mechanism to analyze the relationship between tourism and overall well-being in Pakistan by using time series data for the period 1980-2016. Findings The findings suggest a significant positive relationship between tourism and overall well-being both in the short and long run. The authors find that tourism and overall well-being affect each other positively. Practical implications This research indicates that policymakers and government can improve the overall well-being through tourism development. However, tourism policies and long-term planning should be focused on sustainable developments for achieving long-term goals. Besides, special incentives should be provided to the private sector for tourism development. Originality/value To the best of the authors’ knowledge, this is the first investigation that examines the causal relationships between tourism and overall well-being through objective indicators in a developing economy. This study fills the immense literature gap and provides new directions to scholars to investigate the mentioned relationship through objective indicators.

Graphical Exploratory Data Analysis for Categorical Longitudinal and Time Series Data

2013 ◽  
Author(s):  
Stephen J. Tueller ◽  
Richard A. Van Dorn ◽  
Georgiy Bobashev ◽  
Barry Eggleston
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Exploratory Data

Faktor-Faktor Yang Mempengaruhi Nilai Tukar Dollar Amerika Serikat Terhadap Rupiah Tahun 2000–2013

2017 ◽  
Vol 1 (2) ◽  
pp. 177-191
Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Money Supply ◽  
Time Series Data ◽  
The United States ◽  
Economic Conditions ◽  
Series Data ◽  
Arch Model ◽  
United States Dollar ◽  
The Exchange Rate

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.

An Anomaly Detection Method with Exemplar Subsequence for Time Series Data

2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai
Keyword(s):  
Time Series ◽  
Anomaly Detection ◽  
Time Series Data ◽  
Detection Method ◽  
Series Data

The Comparison of Land Subsidence between East and West Side of Bangkok, Thailand

2020 ◽  
Vol 17 (3) ◽  
pp. 1
Author(s):  
Angkana Pumpuang ◽  
Anuphao Aobpaet
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Time Series Data ◽  
Series Data ◽  
Industrial Estates ◽  
Vertical Displacements ◽  
Land Deformation ◽  
Extensive Farming ◽  
Chao Phraya River ◽  
Set Up

The land deformation in line of sight (LOS) direction can be measured using time series InSAR. InSAR can successfully measure land subsidence based on LOS in many big cities, including the eastern and western regions of Bangkok which is separated by Chao Phraya River. There are differences in prosperity between both sides due to human activities, land use, and land cover. This study focuses on the land subsidence difference between the western and eastern regions of Bangkok and the most possible cause affecting the land subsidence rates. The Radarsat-2 single look complex (SLC) was used to set up the time series data for long term monitoring. To generate interferograms, StaMPS for Time Series InSAR processing was applied by using the PSI algorithm in DORIS software. It was found that the subsidence was more to the eastern regions of Bangkok where the vertical displacements were +0.461 millimetres and -0.919 millimetres on the western and the eastern side respectively. The districts of Nong Chok, Lat Krabang, and Khlong Samwa have the most extensive farming area in eastern Bangkok. Besides, there were also three major industrial estates located in eastern Bangkok like Lat Krabang, Anya Thani and Bang Chan Industrial Estate. By the assumption of water demand, there were forty-eight wells and three wells found in the eastern and western part respectively. The number of groundwater wells shows that eastern Bangkok has the demand for water over the west, and the pumping of groundwater is a significant factor that causes land subsidence in the area.Keywords: Subsidence, InSAR, Radarsat-2, Bangkok

Producers' Response to Changes in Prices and Marketing Policies: A Case Study of Sugarcane and Paddy in Eastern U.P. by S. C. Gupta and A. Majid. New York: Asia Publishing House, 1965.

1968 ◽  
Vol 8 (2) ◽  
pp. 308-309
Author(s):  
Mohammad Irshad Khan
Keyword(s):  
New York ◽  
Time Series ◽  
Time Series Data ◽  
Publishing House ◽  
Economic Incentives ◽  
The Other ◽  
Series Data ◽  
Poor Countries ◽  
Northern India

It is alleged that the agricultural output in poor countries responds very little to movements in prices and costs because of subsistence-oriented produc¬tion and self-produced inputs. The work of Gupta and Majid is concerned with the empirical verification of the responsiveness of farmers to prices and marketing policies in a backward region. The authors' analysis of the respon¬siveness of farmers to economic incentives is based on two sets of data (concern¬ing sugarcane, cash crop, and paddy, subsistence crop) collected from the district of Deoria in Eastern U.P. (Utter Pradesh) a chronically foodgrain deficit region in northern India. In one set, they have aggregate time-series data at district level and, in the other, they have obtained data from a survey of five villages selected from 170 villages around Padrauna town in Deoria.

Neural Network Techniques for Time Series Prediction: A Review

2019 ◽  
Vol 3 (3) ◽  
Author(s):  
Muhammad Faheem Mushtaq ◽  
Urooj Akram ◽  
Muhammad Aamir ◽  
Haseeb Ali ◽  
Muhammad Zulqarnain
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Time Series ◽  
Time Series Data ◽  
Weather Prediction ◽  
Time Series Prediction ◽  
Series Data ◽  
Prediction Problem ◽  
Neural Network Models ◽  
Physical Time

It is important to predict a time series because many problems that are related to prediction such as health prediction problem, climate change prediction problem and weather prediction problem include a time component. To solve the time series prediction problem various techniques have been developed over many years to enhance the accuracy of forecasting. This paper presents a review of the prediction of physical time series applications using the neural network models. Neural Networks (NN) have appeared as an effective tool for forecasting of time series.  Moreover, to resolve the problems related to time series data, there is a need of network with single layer trainable weights that is Higher Order Neural Network (HONN) which can perform nonlinearity mapping of input-output. So, the developers are focusing on HONN that has been recently considered to develop the input representation spaces broadly. The HONN model has the ability of functional mapping which determined through some time series problems and it shows the more benefits as compared to conventional Artificial Neural Networks (ANN). The goal of this research is to present the reader awareness about HONN for physical time series prediction, to highlight some benefits and challenges using HONN.

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