Lorenz Atmospheric Energy Cycle in Climatic Projections

The aim of this study is to investigate whether different Representative Concentration Pathways (RCPs), as they are determined in the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), lead to different regimes in the energetics components of the Lorenz energy cycle. The four energy forms on which this investigation is based are the zonal and eddy components of the available potential and kinetic energies. The corresponding transformations between these forms of energy are also studied. RCPs are time-dependent, consistent scenarios of concentrations of radiatively active gases and particles. In the present study, four RCPs are explored, namely, rcp26, rcp45, rcp60, rcp85; these represent projections (for the future period 2006–2100) that result in radiative forcing of approximately 2.6, 4.5, 6.0 and 8.5 Wm−2 at year 2100, respectively, relative to pre-industrial conditions. The results are presented in terms of time projections of the energetics components from 2020 to 2100 and show that the different RCPs yield diverse energetics regimes, consequently impacting the Lorenz energy cycle. In this respect, projections under different RCPs of the Lorenz energy cycle are presented.

Implementasi Aplikasi Sistem Peramalan Persedian Barang Menggunakan Metode Single Moving Average Berbasis Web

Forecasting is an estimate of future demand based on several forecasting variables based on historical time series or a process of using historical data (past data) that has been owned to use this model and use this model to estimate future conditions.The Ivori mini market SME group is known to be a mini market that sells daily necessities. The goods provided by the ivori mini market are not focused on only one type of goods, but include all types of goods. Ivori mini market often runs out of stock because there is no inventory planning. The main purpose of making this application is to assist employees in determining inventory planning that must be provided next month. While the method used to make this forecast is a single moving average, one of the time series methods in forecasting. Single Moving Average is a forecasting method that is done by collecting a group of observed values, looking for the average value as a forecast for the future period. The result of this forecasting is to predict the number of sales that will occur in the coming month.

Forecasting of Kharif Cereal Production in Odisha by Using Spline Regression Technique

Cereals are prime determinant of agricultural status of the state mainly during kharif season. Forecasting of the production of kharif cereals is of utmost importance to formulate the agricultural policy and strategy of the state. The ARIMA model can be reliably used to forecast for short future periods because uncertainty in prediction increases when done for longer future periods. The predictions obtained from the ordinary regression model are valid only when the relationship between the independent variables and the dependent variable does not change significantly in the future period which can be rarely assumed. It is expected that the spline regression will overcome the respective discrepancies in both ARIMA and ordinary regression techniques of forecasting with the assumption that the future period which needs forecasting follows the same pattern as the last partitioned period. The entire period of data is split into different periods based on the scatter plot of the data The suitable regression models, such as, linear, compound, logarithmic and power model are fitted to the data on area and yield of kharif cereals by using the training set data. Selection of best fit model is done on the basis of overall significance of the model, model diagnostic test for error assumptions and model fit statistics. The selected best fit model is then cross validated with the testing set data. After successful cross validation of the selected best fit models, they are used for forecasting of the future values for their respective variables. The models found to be best fit and thus selected for cross validation purpose are compound spline model for both area and yield of kharif cereals respectively. Forecasting of area, yield and hence production of kharif cereals for six years ahead i.e., for the year 2020-21 to 2025-26 by using the selected best fit model after successful cross validation. The forecast values for production of kharif cereals are found to decrease despite increase in forecast values of yield which is due to decrease in forecast value of area.

Sistem Informasi PT Bintang Sidoraya Dengan Peramalan Penjualan Menggunakan Metode Statistical Parabolic Projection

PT Bintang Sidoraya Information Systems with Sales Forecasting Using Statistical Parabolic Projection Method. The problem that often occurs in companies is the sales prediction in the future period based on data and information in the previous period. These predictions will affect the decisions taken by management for stock availability for the coming period. Due to the demand for goods shipping from around all major cities in Indonesia, sufficient stock availability is needed to minimize the possibility of losing customers. This research was conducted to build an information system application to record data and accompanied by forecasting features using the Statistical Parabolic Projection method. The result of this research is an information system that successfully predicts sales that can facilitate the stock availability calculation for the future period.Keywords: PT Bintang Sidoraya, information systems, Statistical Parabolic Projection Abstrak. Permasalahan yang sering terjadi pada perusahaan ialah prediksi penjualan di periode yang akan datang berdasarkan data dan informasi pada periode sebelumnya. Prediksi tersebut akan berpengaruh terhadap keputusan yang diambil oleh manajemen untuk berapa persediaan stok periode yang akan datang. Karena permintaan pengiriman barang yang hampir mencakupi seluruh kota besar di Indonesia, diperlukan persediaan stok yang cukup untuk meminimalkan terjadinya potensi kehilangan pelanggan. Penelitian ini dilakukan untuk membangun aplikasi sistem informasi untuk melakukan perekapan data dan disertai fitur peramalan menggunakan metode Statistical Parabolic Projection. Hasil dari penelitian ini ialah sebuah sistem informasi yang berhasil melakukan prediksi penjualan yang dapat mempermudah penentuan jumlah stok pada periode mendatang.Kata kunci: PT Bintang Sidoraya, information systems, Statistical Parabolic Projection

Implementation of Markov Chain in Detecting Opportunities for Natural Disasters in Klaten (Case Study: Number of Floods, Landslides, and Hurricanes 2019-2020)

Java Island is one of the areas that is very fertile and densely populated, but on the other hand, Java Island is also one of the areas that is most frequently hit by natural disasters, one of which is Klaten Regency. Natural disaster itself is an event that threatens and disrupts human life caused by nature. Some of the natural disasters that often occur simultaneously in Klaten Regency are floods, landslides, and hurricanes. These three disasters usually occur during the rainy season. This of course makes the government need to take action by seeing the large chance of a disaster occurring in order to optimize disaster management. Then research will be carried out that aims to determine the chances of natural disasters occurring in the next few years. Forecasting will be carried out using the Markov chain method, with this method the probability value of the future period can be estimated using the current period probability value based on the characteristics of the past period. So that the value of the steady state chance of floods and landslides in period 36 (December 2023) and hurricanes in period 15 (March 2022) with the chances of a disaster are 34.21%, 15.38%, and 73.53%, respectively.Received August 31, 2021Revised October 27, 2021Accepted November 11, 2021

Simulation of the impact of climate change on runoff and drought in an arid and semiarid basin (the Hablehroud, Iran)

This study evaluates the impact of climate change (CC) on runoff and hydrological drought trends in the Hablehroud river basin in central Iran. We used a daily time series of minimum temperature (Tmin), maximum temperature (Tmax), and precipitation (PCP) for the baseline period (1982–2005) analysis. For future projections, we used the output of 23 CMIP5 GCMs and two scenarios, RCP 4.5 and RCP 8.5; then, PCP, Tmin, and Tmax were projected in the future period (2025–2048). The GCMs were weighed based on the K-nearest neighbors algorithm. The results indicated a rising temperature in all months and increasing PCP in most months throughout the Hablehroud river basin's areas for the future period. The highest increase in the Tmin and Tmax in the south of the river basin under the RCP 8.5 scenario, respectively, was 1.87 °C and 1.80 °C. Furthermore, the highest reduction in the PCP was 54.88% in August under the RCP 4.5 scenario. The river flow was simulated by the IHACRES rainfall-runoff model. The annual runoff under the scenarios RCP 4.5 and RCP 8.5 declined by 11.44% and 13.13%, respectively. The basin runoff had a downward trend at the baseline period; however, it will have a downward trend in the RCP 4.5 scenario and an upward trend in the RCP 8.5 scenario for the future period. This study also analyzed drought by calculating the streamflow drought index for different time scales. Overall, the Hablehroud river basin will face short-term and medium-term hydrological drought in the future period.

Evaluation of Climate in CMIP6 Models over Two Third Pole Subregions with Contrasting Circulation Systems

Reliable simulations of historical and future climate are critical to assessing ecological and hydrological responses over the Third Pole (TP). In this study, we evaluate the historical and future temperature and precipitation simulations of 18 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in southeastern TP (SETP) and the upstream of the Amu Darya and Syr Darya (UAS) regions, two typical TP subregions dominated by the Indian summer monsoon system and westerlies, respectively. Comparison against station observations suggests that CMIP6 models generally capture the intra-annual variability and spatial pattern of historical climate over both subregions. However, the wetting and cold biases observed in CMIP5 still persist in CMIP6; annual temperature is underestimated by most models and annual precipitation is overestimated by all models. Multi-model average cold biases in SETP and UAS are 1.18°C and 0.32°C, respectively, and wet biases in SETP and UAS are 119% and 46%, respectively. We further analyze climate projections under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. Both SETP and UAS subregions are projected to experience significant warming in 2015–2100, with warming trends 34%–42% and 40%–50% higher than the global trend, respectively. Model projections suggest that the warming trend will slow down under SSP1-2.6 and SSP2-4.5 but further intensify under SSP5-8.5 in 2050–2100. Monsoon-dominated SETP is projected to experience a significant wetting trend stronger than UAS over the entire future period, especially in summer (cf. winter in westerlies-dominated UAS). Concurrently, a significant drying trend in summer is found in UAS during 2050–2100 under SSP5-8.5, suggesting the intensified uneven distributions of seasonal precipitation based on projections.

SIR modelling of COVID-19 with cumulative cases, deaths, recovered and active cases in India

COVID-19 which has spread internationally very rapidly and has become a pandemic. In this research paper, we set forward a statistical model called SIR-Poisson helps us to determine the spread of infectious disease of COVID-19 in India. The proposed SIR-Poisson model is able to predict the range of the infected cases in a future period. It is also used to detect the transmission of the COVID-19. Using the SIR-Poisson model and based on daily reported we attempted to predict the future disease period over 104 days.

Pengaruh Senam Yoga Terhadap Penurunan Nyeri Haid (Dismenorea) Pada Mahasiswi Prodi D-III Fisioterapi Widya Husada Semarang

ABSTRAK Latar Belakang : Menstruasi merupakan suatu kondisi awal yang menandai mulai matangnya organ reproduksi pada remaja wanita. Proses ovulasi dan menstruasi dimulai pada usia antara 6-14 bulan setelah menarche (haid pertama). Menstruasi biasanya identik dengan nyeri haid (dismenorea), gangguan fisik serta emosi menjelang masa menstruasi atau biasa disebut PMS. Dismenorea terkadang dapat menimbulkan nyeri yang tak tertahankan hingga jatuh pingsan. Wanita melakukan segala hal untuk mengurangi nyeri atau bahkan mencegahnya. Yoga dapat menciptakan suasana relaksasi yang mampu melepaskan ketegangan otot. Maka perlu dilakukan pembuktian pengaruh yoga dapat membantu mengurangi nyeri haid (dismenorea) Presentasi Kasus : Sampel yang diambil dalam penelitian ini berjumlah 27 orang yang mengalami nyeri haid (Disminorea). Dari 150 Responden yang dikumpulkan, kemudian dilakukan proses assessment dengan metode study kasus (wawancara, observasi dan documenter) setelah dilakukan seleksi didapatkan 27 sampel yang sesuai dengan kriteria. Metode : Laporan kasus ini menilai tingkat nyeri haid (Disminorea) perbedaan pada hasil pre-test dan post test. Hasil : Perlakuan senam yoga dapat menurunkan nyeri pada mahasiswa dengan penurunan tingkat nyeri yang berbeda. Kesimpulan : Populasi dalam penelitian ini adalah mahasiswi Fisioterapi Widya Husada Semarang sebanyak 27 orang, dari hasil penelitian didapatkan nyeri haid (dismenorea) yang berkurang cukup signifikan dari 24 nyeri berat menjadi 2 orang nyeri ringan, dan 3 orang nyeri ringan menjadi nyeri hilang. Kata Kunci : Nyeri Haid (Dismenorea), Senam Yoga ABSTRACT Background : Menstrual is an initial condition that marks the beginning of reproductive organs in the female teenager. The process ofovulation and menstrual began at the age between 6-14 months after menarche (first menstrual). Periods are usually identical with menstrual pain (dismenorea), physical disorders and emotion in the future period or commonly called PMS. Dislodges can sometimes cause unbearable pain to fall fainting. Women do everything to reduce pain or even prevent it. Yoga can create relaxation atmosphere capable of releasing muscle tensions. So it needs to be done proving yoga influence can help reduce menstrual pain (dismenorea). Case Presentation : Samples taken in this study were totaling 27 people who experienced menstrual pain (Disminorea). Of the 150 Respondents were collected, then the assessment process was conducted by study-study method (interviews, observation and documenter) After the selection, there were 27 samples that fit the criteria. Method : This case's report assesses the menstrual pain level (Disminorea) differences on pre-tests and post tests. Result: Yoga exercise for yoga treatment can reduce pain in students with different levels lowering pain. Conclusion: The population in this study is a student Physiotherapist Husada Semarang as much as 27 people, From the results of the study, it was found that menstrual pain (dysmenorrhoea) was significantly reduced from 24 severe pain to 2 mild pain, and 3 mild pain to lost pain. Keywords: Menstrual Pain (dismenorea), Gymnastics Yoga

Scientometrics Analysis Method for Society 5.0

It includes the systematic examination and mapping of the literature studies written for Society 5.0 using the CiteSpace application, with the scientometrics analysis method, the identification of the network of relations, and the discovery and intellectual analysis of their bibliographic contents. 151 bibliographic records from the Scopus database were analyzed between January 2017 and May 2021. Qualitative analysis of the obtained quantitative data based on the interpretative paradigm was made. Analysis of countries, intellectual analysis, keywords; burst point and cluster analyzes were performed. The case is gaining increasing importance in the multi-disciplinary field. Since the phenomenon of Society 5.0 is still current and concerns the future period, it is seen that it is a developing field in the literature. In the literature about this case; The fact that scientometrics studies and CiteSpace analysis have never been done has increased the originality of the study. It will be important for super-smart society goals to specialize in the fields studied and to increase the working tendencies in the fields that are lacking (sociology, psychology, gerentology, etc. social sciences).