Search results for: wheat yield prediction

Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

Procedia PDF Downloads 123

Authors: Kuo-Chun Chien, Chia-Hui Chang, Ren-Der Sun

Abstract:

Legal Judgment Prediction (LJP) is a subtask for legal AI. Its main purpose is to use the facts of a case to predict the judgment result. In Taiwan's criminal procedure, when prosecutors complete the investigation of the case, they will decide whether to prosecute the suspect and which article of criminal law should be used based on the facts and evidence of the case. In this study, we collected 305,240 indictments from the public inquiry system of the procuratorate of the Ministry of Justice, which included 169 charges and 317 articles from 21 laws. We take the crime facts in the indictments as the main input to jointly learn the prediction model for law source, article, and charge simultaneously based on the pre-trained Bert model. For single article cases where the frequency of the charge and article are greater than 50, the prediction performance of law sources, articles, and charges reach 97.66, 92.22, and 60.52 macro-f1, respectively. To understand the big performance gap between articles and charges, we used a bipartite graph to visualize the relationship between the articles and charges, and found that the reason for the poor prediction performance was actually due to the wording precision. Some charges use the simplest words, while others may include the perpetrator or the result to make the charges more specific. For example, Article 284 of the Criminal Law may be indicted as “negligent injury”, "negligent death”, "business injury", "driving business injury", or "non-driving business injury". As another example, Article 10 of the Drug Hazard Control Regulations can be charged as “Drug Control Regulations” or “Drug Hazard Control Regulations”. In order to solve the above problems and more accurately predict the article and charge, we plan to include the article content or charge names in the input, and use the sentence-pair classification method for question-answer problems in the BERT model to improve the performance. We will also consider a sequence-to-sequence approach to charge prediction.

Keywords: legal judgment prediction, deep learning, natural language processing, BERT, data visualization

Procedia PDF Downloads 106

Authors: Mohammad Taghi Karbalaei Aghamolki, Mohd Khanif Yusop, Fateh Chand Oad, Hamed Zakikhani, Hawa Zee Jaafar, Sharifh Kharidah, Mohamed Hanafi Musa, Shahram Soltani

Abstract:

The high temperatures during sensitive growth phases are changing rice morphology as well as influencing yield. In the glass house study, the treatments were: growing conditions [normal growing (32oC+2) and heat stress (38oC+2) day time and 22oC+2 night time], growth stages (booting, flowering and ripening) and four cultivars (Hovaze, Hashemi, Fajr, as exotic and MR219 as indigenous). The heat chamber was prepared covered with plastic, and automatic heater was adjusted at 38oC+2 (day) and 22oC+2 (night) for two weeks in every growth stages. Rice morphological and yield under the influence of heat stress during various growth stages showed taller plants in Hashsemi due to its tall character. The total tillers per hill were significantly higher in Fajr receiving heat stress during booting stage. In all growing conditions and growth stages, Hashemi recorded higher panicle exertion and flag leaf length. The flag leaf width in all situations was found higher in Hovaze. The total tillers per hill were more in Fajr, although heat stress was imposed during booting and flowering stages. The indigenous MR219 in all situations of growing conditions, growth stages recorded higher grain yield. However, its grain yield slightly decreased when heat stress was imposed during booting and flowering. Similar results were found in all other exotic cultivars recording to lower grain yield in the heat stress condition during booting and flowering. However, plants had no effect on heat stress during ripening stage.

Keywords: rice, growth, heat, temperature, stress, morphology, yield

Procedia PDF Downloads 257

Authors: Quang M. Dinh

Abstract:

Stigmatogobius pleurostigma is a commercial fish being caught increasingly in the Mekong Delta. Although it plays an important role for food supply, little is known about this species including morphology, distribution and growth pattern. Meanwhile, its population and age structure is unknown. The present study was conducted in the Mekong Delta to provide new data on population parameters of this goby species. The von Bertalanffy growth parameters were L∞= 8.6 cm, K = 0.83 yr⁻¹, and t0 = -0.07 yr⁻¹ basing on length frequency data analysis of 601 individuals. The fish total length at first capture was 3.8 cm; and fishing, natural and total mortalities of the fish population were 2.31 yr⁻¹, 1.17 yr⁻¹, and 3.48 yr⁻¹ respectively. The maximum fish yield (Eₘₐₓ), economic yield (E₀.₁) and yield of 50% reduction of exploitation (E₅₀) rates were 0.704, 0.555 and 0.335 based on the relative yield-per-recruit and biomass-per-recruit analyses. The fish longevity was 3.61 yr, and growth performance was 1.79. Three fish age groups were recorded in this study (0+, 1+ and 2+). The species is a potential aquaculture candidate because of its high growth parameter. This goby stock was overexploited in the Mekong Delta as its exploitation rate (E=0.34) was higher than E₅₀ (0.335). The mesh size of gillnets should be increased and avoid catching fish in June, recruitment time, for future sustainable fishery management.

Keywords: Stigmatogobius pleurostigma, age, population structure, Vietnam

Procedia PDF Downloads 181

Authors: Macdalyna Esther Ronie, Hasmadi Mamat, Ahmad Hazim Abdul Aziz, Mohamad Khairi Zainol

Abstract:

Current trends in gluten-free food development are increasingly leaning towards the utilization of pigmented rice flour, with a particular focus on Bario Merah Sederhana (BMS), a red-pigmented rice native to Sarawak, Malaysia. This study delves into the evaluation of the nutritional, textural, and sensory attributes of gluten-free rice bread produced from a blend of BMS rice flour and potato starch. The resulting samples are denoted as F1 (100% BMS rice flour), F2 (90% BMS rice flour and 10% potato starch), F3 (80% BMS rice flour and 20% potato starch), and F4 (70% BMS rice flour and 30% potato starch). Comparatively, these gluten-free rice bread formulations exhibit higher levels of ash and crude fiber, along with lower carbohydrate content when juxtaposed with conventional wheat bread. Notably, the crude protein content of the rice bread diminishes significantly (p<0.05) as the proportion of rice flour decreases, primarily due to the higher protein content found in wheat flour. The crumb of the rice bread appears darker owing to the red pigment in the rice flour, while the crust is lighter than that of the control sample, possibly attributable to a reduced Maillard reaction. Among the various rice bread formulations, F4 stands out with the least dough and bread hardness, accompanied by the highest levels of stickiness and springiness in both dough and bread, respectively. In sensory evaluations, wheat bread garners the highest rating (p<0.05). However, within the realm of rice breads, F4 emerges as a viable and acceptable formulation, as indicated by its commendable scores in color (7.03), flavor (5.73), texture (6.03), and overall acceptability (6.18). These findings underscore the potential of BMS in the creation of gluten-free rice breads, with the formulation consisting of 70% rice flour and 30% potato starch emerging as a well-received and suitable option.

Keywords: gluten-free bread, bario rice, proximate composition, sensory evaluation

Procedia PDF Downloads 219

Authors: Saeed Rauf

Abstract:

Purpose: Drought stress is a major production constraint in sunflowers and causes yield losses under tropical and subtropical environments having high evapo-tranpirational losses. Given the consequences, three trials were designed to evaluate drought-resistant sunflower hybrids. Research Methods: Field trials were conducted under a split-plot arrangement with 17 hybrids and two contrasting regimes at Sargodha, Pakistan and 7 hybrids at Karj, Iran. Water stress condition was simulated by holding water in a stress regime. Hybrids were also screened against five levels of osmotic-ally induced stress, i.e. 0-15%, under a completely randomized design with 3 replications. Findings: Hybrids H1 (C.112.× RH.344) and H3 (C.112.× RSIN.82) showed the highest seed yield ha-1 and early flowering at Karj Iran. Commercial hybrid had the highest CTD (18.2°C) followed by C112 × RH.344 (17.29 °C). Hybrid C.250 × R.SIN.82 had the highest seed yield (m-2), followed by C.112 × RH.365 and C.124 × RSIN.82 under both stress and non-stress regimes at Sargodha, Pakistan. Seedling trial results showed that 6 hybrids only germinated in 5 and 7.5% PEG-induced osmotic stress, respectively. H1 (C.112 × RH.344) and H2 (C.112 × RH.347) had the highest germination% at 5% and 7.5% osmotic stress (OS). Seedling vigor index (SVI) was the highest in H1 (C.112 × RH.344) hybrids at 5% OS, H2 had the highest SVI under 7.5% OS, followed by H3 (C112 × RH344) and H4 (C116 × RH344). Originality/Value: In view of above results, it was concluded that hybrid combination H1 had the highest seed yield under stress conditions in both environments. High seed yield may be due to its better germination and vigor index under stress conditions.

Keywords: climate change, CTD, genetic variability, osmotic stress

Procedia PDF Downloads 47

Authors: Mehdi Mirzaei Alavijeh, Farzad Jalilian

Abstract:

Background: Marijuana is the most widely used illicit drug worldwide, especially among adolescents and young adults, which can cause numerous complications. The aim of this study was to determine the pattern, motivation use, and factors related to marijuana use among Iranian youths based on the integrative model of behavioral prediction Methods: A cross-sectional study was conducted among 174 youths marijuana user in Kermanshah County and Isfahan County, during summer 2014 which was selected with the convenience sampling for participation in this study. A self-reporting questionnaire was applied for collecting data. Data were analyzed by SPSS version 21 using bivariate correlations and linear regression statistical tests. Results: The mean marijuana use of respondents was 4.60 times at during week [95% CI: 4.06, 5.15]. Linear regression statistical showed, the structures of integrative model of behavioral prediction accounted for 36% of the variation in the outcome measure of the marijuana use at during week (R2 = 36% & P < 0.001); and among them attitude, marijuana refuse, and subjective norms were a stronger predictors. Conclusion: Comprehensive health education and prevention programs need to emphasize on cognitive factors that predict youth’s health-related behaviors. Based on our findings it seems, designing educational and behavioral intervention for reducing positive belief about marijuana, marijuana self-efficacy refuse promotion and reduce subjective norms encourage marijuana use has an effective potential to protect youths marijuana use.

Keywords: marijuana, youth, integrative model of behavioral prediction, Iran

Procedia PDF Downloads 542

Authors: Cosmas Parwada, Ronald Mandumbu, Handseni Tibugari, Trust Chinyama

Abstract:

A 3-yr field experiment to evaluate effects of tillage and residue management on soil water storage (SWS), grain yield, harvest index (HI) and water use efficiency (WUE) of sorghum was done in sandy soils. Treatments were conventional (CT) and minimum (MT) tillage without residue retention and conventional (CT × RT) and minimum (MT × RT) tillage with residue retention. Change in SWS was higher under CT and MT than in CT × RT and MT × RT, especially in the 0-10 cm soil layer. Grain yield and HI were significantly (P < 0.05) lower in CT and MT than CT × RT and MT × RT. Grain yield and HI were significantly (P < 0.05) positively correlated to WUE but WUE significantly (P < 0.05) negatively correlated to sand (%) particle content. The SWS was lower in winter but higher in summer and was significantly correlated to soil organic carbon (SOC), sand (%), grain yield (t/ha), HI and WUE. The WUE linearly increasing from first to last cropping seasons in tillage with returned residues; higher in CT × RT and MT × RT that promoted SOC buildup than where crop residues were removed. Soil tillage decreased effects of residues on SWS, WUE, grain yield and HI. Minimum tillage coupled to residue retention sustainably enhanced WUE but further research to investigate the interaction effects of the tillage on WUE and soil fertility management is required. Understanding and considering the WUE in crops can be a primary condition for cropping system designs. The findings pave way for further research and crop management programmes, allowing to valorize the water in crop production.

Keywords: evapotranspiration, infiltration rate, organic mulch, sand, water use efficiency

Procedia PDF Downloads 197

Authors: Malee Santikunaporn, Neera Wongtyanuwat, Channarong Asavatesanupap

Abstract:

Pyrolysis of waste oil is an effective process to produce high quality liquid fuels. In this work, pyrolysis experiments of waste oil over Y zeolite were carried out in a semi-batch reactor under a flow of nitrogen at atmospheric pressure and at different reaction temperatures (350-450 ^oC). The products were gas, liquid fuel, and residue. Only liquid fuel was further characterized for its composition and properties by using gas chromatography, thermogravimetric analyzer, and bomb calorimeter. Experimental results indicated that the pyrolysis reaction temperature significantly affected both yield and composition distribution of pyrolysis oil. An increase in reaction temperature resulted in increased fuel yield, especially gasoline fraction. To obtain high amount of fuel, the optimal reaction temperature should be higher than 350 ^oC. A presence of Y zeolite in the system enhanced the cracking activity. In addition, the pyrolysis oil yield is proportional to the catalyst quantity.

Keywords: gasoline, diesel, pyrolysis, waste oil, Y zeolite

Procedia PDF Downloads 180

Authors: Lee P. Leon, Raymond Charles

Abstract:

This paper presents a method of evaluating the effect of aggregate angularity on hot mix asphalt (HMA) properties and its relationship to the Permanent Deformation resistance. The research concluded that aggregate particle angularity had a significant effect on the Permanent Deformation performance, and also that with an increase in coarse aggregate angularity there was an increase in the resistance of mixes to Permanent Deformation. A comparison between the measured data and predictive data of permanent deformation predictive models showed the limits of existing prediction models. The numerical analysis described the permanent deformation zones and concluded that angularity has an effect of the onset of these zones. Prediction of permanent deformation help road agencies and by extension economists and engineers determine the best approach for maintenance, rehabilitation, and new construction works of the road infrastructure.

Keywords: aggregate angularity, asphalt concrete, permanent deformation, rutting prediction

Procedia PDF Downloads 384

Authors: Ya-Li Tsai

Abstract:

Nitrogen is a vital element crucial for crop growth, significantly influencing crop yield. In rice cultivation, farmers often apply substantial nitrogen fertilizer to maximize yields. However, excessive nitrogen application increases the risk of lodging and pest infestation, leading to yield losses. Additionally, conventional flooded irrigation methods consume significant water resources, necessitating precise agricultural and intelligent water management systems. In this study, it leveraged physiological data and field images captured by unmanned aerial vehicles, considering fertilizer treatment and irrigation as key factors. Statistical models incorporating rice physiological data, yield, and vegetation indices from image data were developed. Missing physiological data were addressed using multiple imputation and regression methods, and regression models were established using principal component analysis and stepwise regression. Target nitrogen accumulation at key growth stages was identified to optimize fertilizer application, with the difference between actual and target nitrogen accumulation guiding recommendations for ear dressing dosage. Field experiments conducted in 2022 validated the recommended ear dressing dosage, demonstrating no significant difference in final yield compared to traditional fertilizer levels under alternate wetting and drying irrigation. These findings highlight the efficacy of applying recommended dosages based on fertilizer decision models, offering the potential for reduced fertilizer use while maintaining yield in rice cultivation.

Keywords: intelligent fertilizer management, nitrogen top and ear dressing fertilizer, rice, yield optimization

Procedia PDF Downloads 41

Authors: N. Viji, K. Siddeswaran

Abstract:

Field experiment was conducted at Eastern Block farm, Department of Farm Management, Tamil Nadu Agricultural University, Coimbatore during winter season of 2011-2012 to evaluate potassium salt based glyphosate (Roundup Crop Shield 460 SL) with and without intercultural operations on seed cotton yield and weed nutrient removal in irrigated cotton. The experiment was laid out in Randomized Block Design with treatments replicated thrice. The treatments consisted of POE glyphosate (Roundup Crop Shield 460 SL) at 1350 (T1), 1800 (T2), 2250 (T3) g a.e. ha-1, 1800 g a.e. ha-1 + IC (T4), PE pendimethalin at 750 g a.i. ha-1 + IC (T5), HW at 35 and 70 DAS + IC (T6), HWW at 35 and 70 DAS + IC (T7), PWW at 35 and 70 DAS + IC (T8), HW at 25 and 45 DAS (T9) and Unweeded control (T10). Among the weed management methods, decreased nutrient removal by weeds were observed with POE glyphosate at 1800 g a.e. ha-1 + IC which was comparable with PE pendimethalin at 750 g a.i. ha-1 + IC. Higher seed cotton yield was obtained with POE glyphosate at 1800 g a.e. ha-1 at 35 and 70 DAS with + IC at 45 and 55 DAS which was comparable with PE pendimethalin at 750 g a.i. ha-1 + IC at 45 and 55 DAS. Comparing treatments without intercultural operation, intercultural operation carried out treatments performed better and recorded more seed cotton yield.

Keywords: cotton, weed, glyphosate, nutrient

Procedia PDF Downloads 616

Authors: Saba Gachpaz, Hamid Reza Heidari

Abstract:

The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

Procedia PDF Downloads 63

Authors: Taliman Nisar Ahmad, Hirofume Saneoka

Abstract:

A pot experiment was conducted to investigate the effect of phosphorus (P) and potassium (K) nutrition on grain yield, phytic acid and grain quality of high-phytate (Akimaro) and low-phytate line. Phosphorus and potassium were applied as; P₁ (20 kg ha⁻¹) and P₂ (100 kg ha⁻¹), same as K₁ (20 kg ha⁻¹) and K₂ (100 kg ha⁻¹), respectively. Low-phytate soybean had the highest grain yield, and 75% increase was observed compared to the high-phytate under same treatments. Highly significant differences of seed phytate P were observed in both cultivars, and the phytate P in high-phytate was found 39% higher than low-phytate, whereas no significant differences observed in response to P and K treatment. Percentage of phytate P from total P in seeds was 28 to 35% in low-phytate and 72 to 81% in high-phytate in different treatments. The lipid content in low-phytate was found lowered compared to that of high-phytate. Crude protein in grains was also found significantly higher in PK combined. No significant difference was observed in seed calcium (Ca), magnesium (Mg), and Zinc (Zn) in different treatments, but high-phytate showed 87% increase in seed Ca and 76% of Mg compared to low-phytate; however, low-phytate showed 82% increase in Zn content over high-phytate. The result illustrates that low-phytate soybean achieved higher grain yield and grain Pi in response to increased P and K nutrition. To achieve higher yield and quality seeds from the low-phytate soybean, it is recommended that proper phosphorus and potassium nutrition to be applied suggested in this study.

Keywords: phytic acid, low-phytate soybean, high-phytate soybean, P and K nutrition, protein content, soybean

Procedia PDF Downloads 117

Authors: Salim Omar Raoof

Abstract:

This study was conducted in a private local sheep herd at Gabaraka village-Kirkuk-Iraq. Analysis of 77 ewes recorded and 7 Rams of local sheep presented in Gabaraka village farm plain, the age of ewes ranged between (2-4) years. The aim of this study is to investigate the genetic and non-genetic factors (type of birth, sex, and age of dam) affecting daily milk yield (DMY), birth weight (BW), weaning weight (WW) and Gain characteristics of local sheep raised under Iraq conditions, and it also aims at estimating heritability’s, BLUP. The overall mean of daily milk yield, (BW), (WW), and gain. Was 444.15gm,4.92kg,43.08kg, and 38.16kg, respectively. The results showed there was a significant effect of the type of birth and sex on (BW) and (WW). Also, the age of the dam had a significant effect on daily milk yield (BW), (WW), and gain. Generally, the estimate of heritability of DMP, BWT, WWT, and Gain tend to be 0.22, 0.17, 0.27, and 0.22, respectively. The breeding value (BLUP) for rams ranged between (-0.1684 to 0.188), (-0.205 to 0.310), and ( -0.0171 to 0.029) according to growth traits of Lambs BW, WW, and Gain, respectively. It concluded that the selection of ewes and rams at the population level in planned selection schemes is based on BLUP value and heritability.

Keywords: locally sheep, milk yield, Genetic parameters, BLUP value

Procedia PDF Downloads 57

Authors: Quang Minh Dinh, Jian Guang Qin, Sabine Dittmann, Dinh Dac Tran

Abstract:

The age and population structure the dermal gopy Parapocryptes serperaster were studied using length distributions, otolith and von Bertalanffy model in the Mekong Delta over a whole year through monthly sampling. The sex ratio of P. serperaster was near 1:1, and von Bertalanffy growth parameters were L∞= 25.2 cm, K = 0.74 yr-1, and t0 = -0.22 yr-1. Fish size at first entry to fishery was 14.6 cm, and fishing mortality (1.57 yr-1) and natural mortality (1.51 yr-1) accounted for 51% and 49% of the total mortality (3.07 yr-1), respectively. Relative yield-per-recruit and biomass-per-recruit analyses revealed the levels of maximum exploitation yield (Emax = 0.83), maximum economic yield (E0.1 = 0.71) and the yield at 50% reduction of exploitation (E0.5 = 0.37). Otoliths from 164 female and 196 male gobies were readable, and the otolith morphometry data were used for age identification. The mean age estimated by reading otolith annual rings and by analysing length frequency distribution was consistent. This study shows that the otolith morphometry is a reliable method for aging this goby and possibly also applicable for other tropical gobies. The fishery analysis indicates that this goby stock has not been overexploited in the Mekong Delta.

Keywords: Parapcryptes serperaster, otolith, age, pulation structure, Vietnam

Procedia PDF Downloads 633

Authors: Denys Osipenko, Jonathan Crook

Abstract:

Because of the variety of the card holders’ behaviour types and income sources each consumer account can be transferred to a variety of states. Each consumer account can be inactive, transactor, revolver, delinquent, defaulted and requires an individual model for the income prediction. The estimation of transition probabilities between statuses at the account level helps to avoid the memorylessness of the Markov Chains approach. This paper investigates the transition probabilities estimation approaches to credit cards income prediction at the account level. The key question of empirical research is which approach gives more accurate results: multinomial logistic regression or multistage conditional logistic regression with binary target. Both models have shown moderate predictive power. Prediction accuracy for conditional logistic regression depends on the order of stages for the conditional binary logistic regression. On the other hand, multinomial logistic regression is easier for usage and gives integrate estimations for all states without priorities. Thus further investigations can be concentrated on alternative modeling approaches such as discrete choice models.

Keywords: multinomial regression, conditional logistic regression, credit account state, transition probability

Procedia PDF Downloads 466

Authors: Zeeshan Muzammal, Usama Latif, Fouzia Younas, Syed Muhammad Hassan, Samia Razaq

Abstract:

Unexpected rainfall has always been an issue in the lifetime of crops and brings destruction for the farmers who harvest them. Unfortunately, Pakistan is one of the countries in which untimely rain impacts badly on crops like wash out of seeds and pesticides etc. Pakistan’s GDP is related to agriculture, especially in rural areas farmers sometimes quit farming because leverage of huge loss to their crops. Through our surveys and research, we came to know that farmers in the rural areas of Pakistan need rain information to avoid damages to their crops from rain. We developed a prototype using ICTs to inform the farmers about rain one week in advance. Our proposed solution has two ways of informing the farmers. In first we send daily messages about weekly prediction and also designed a helpline where they can call us to ask about possibility of rain.

Keywords: ICTD, farmers, mobile based, Pakistan, rural areas, weather prediction

Procedia PDF Downloads 553

Authors: Shigenori Togashi, Yukako Asano

Abstract:

We developed an effective microfluidic device for photoreactions with low reflectance and good heat conductance. The performance of this microfluidic device was tested by carrying out a photoreactive synthesis of benzopinacol and acetone from benzophenone and 2-propanol. The yield reached 36% with an irradiation time of 469.2 s and was improved by more than 30% when compared to the values obtained by the batch method. Therefore, the microfluidic device was found to be effective for improving the yields of photoreactions.

Keywords: microfluidic device, photoreaction, black aluminum oxide, benzophenone, yield improvement

Procedia PDF Downloads 231

Authors: Samual Ayeni, A. S. Akinbani

Abstract:

At present when the price of petroleum is going down beyond bearable level, there is a need to diversify the economy towards arable crop production since Nigeria is an agrarian country. Yam plays prominent role in solving the problem of hunger in Nigeria. There is scarcity of information on the effect of fertilizers in increasing the yield of yam and maintaining soil properties in South Western Nigeria. This study was therefore set up to determine fertilizer effect on properties and yield of yam. The experiment was conducted at Adeyemi College of Education Teaching and Research Farm to compare the effect of organic, Organomineral and mineral fertilizers on yield of yam. Ten treatments were used 10t/ha Wood Ash, 10t/ha Cattle Dung, 10t/ha Poultry Manure, 10t/ha Manufactured Organic, 10t/ha Organomineral Fertilizer, 400kg/ha NPK, 400kg/ha SSP, 400kg/ha Urea and control with treatment. The treatments were laid out in a Randomized Complete Block Design (RCBD) and replicated three times. Compared with control, Organomineral fertilizer significantly (P < 0.05) increased the soil moisture content, poultry manure, wood ash significantly decreased (< 0.05) the bulk density. Application of 10t/ha Organomineral fertilizer recorded the highest increase in the yield of yam among the treatments.

Keywords: organomineral fertilizer, organic fertilizer, SSP, bulk density

Procedia PDF Downloads 278

Authors: Sokkhey Phauk, Takeo Okazaki

Abstract:

The challenging task in educational institutions is to maximize the high performance of students and minimize the failure rate of poor-performing students. An effective method to leverage this task is to know student learning patterns with highly influencing factors and get an early prediction of student learning outcomes at the timely stage for setting up policies for improvement. Educational data mining (EDM) is an emerging disciplinary field of data mining, statistics, and machine learning concerned with extracting useful knowledge and information for the sake of improvement and development in the education environment. The study is of this work is to propose techniques in EDM and integrate it into a web-based system for predicting poor-performing students. A comparative study of prediction models is conducted. Subsequently, high performing models are developed to get higher performance. The hybrid random forest (Hybrid RF) produces the most successful classification. For the context of intervention and improving the learning outcomes, a feature selection method MICHI, which is the combination of mutual information (MI) and chi-square (CHI) algorithms based on the ranked feature scores, is introduced to select a dominant feature set that improves the performance of prediction and uses the obtained dominant set as information for intervention. By using the proposed techniques of EDM, an academic performance prediction system (APPS) is subsequently developed for educational stockholders to get an early prediction of student learning outcomes for timely intervention. Experimental outcomes and evaluation surveys report the effectiveness and usefulness of the developed system. The system is used to help educational stakeholders and related individuals for intervening and improving student performance.

Keywords: academic performance prediction system, educational data mining, dominant factors, feature selection method, prediction model, student performance

Procedia PDF Downloads 93

Authors: Seyed Habib Shojaei, Reza Eivazi, Mir Sajad Shojaei, Alireza Akbari, Pooria Mazloom, Seyede Mitra Sadati, Mir Zeinalabedin Shojaei, Farnaz Farbakhsh

Abstract:

To study the genetic diversity in rapeseeds and agronomic traits, an experiment was conducted using multivariate statistical methods at Agricultural Research Station of Kashmar in 2012-2013.In this experiment, ten genotypes of rapeseed in a Randomized Complete Block designs with three replications were evaluated. The following traits were studied: seed yield, number of days to the fifty percent of flowering, plant height, number of pods on main stem, length of the pod, seed yield per plant, number of seed in pod, harvest index, weight of 100 seeds, number of pods on lateral branch, number of lateral branches. In analyzing the variance, differences between cultivars were significant. The average comparative revealed that the most valuable variety was Licord regarding to the traits while the least valuable variety was Opera. In stepwise regression, harvest index, grain yield per plant and number of pods per lateral branches were entering to model. Correlation analysis showed that the grain yield with the number of pods per lateral branches and seed yield per plant have positive and significant correlation. In the factor analysis, the first five components explained more than 83% of the variance in the data. In the first factor, seed yield and the number of pods per lateral branches were of the highest importance. The traits, seed yield per plant, and pod per main stem were of a great significance in the second factor. Moreover, in the third factor, plant height and the number of lateral branches were more important. In the fourth factor, plant height and one hundred seeds weight were of the highest variance. Finally, days to fifty percent of flowering and one hundred seeds weight were more important in fifth factor.

Keywords: rapeseed, variance analysis, regression, factor analysis

Procedia PDF Downloads 232

Authors: Xiao Zhou, Jianlin Cheng

Abstract:

A single amino acid mutation can have a significant impact on the stability of protein structure. Thus, the prediction of protein stability change induced by single site mutations is critical and useful for studying protein function and structure. Here, we presented a deep learning network with the dropout technique for predicting protein stability changes upon single amino acid substitution. While using only protein sequence as input, the overall prediction accuracy of the method on a standard benchmark is >85%, which is higher than existing sequence-based methods and is comparable to the methods that use not only protein sequence but also tertiary structure, pH value and temperature. The results demonstrate that deep learning is a promising technique for protein stability prediction. The good performance of this sequence-based method makes it a valuable tool for predicting the impact of mutations on most proteins whose experimental structures are not available. Both the downloadable software package and the user-friendly web server (DNpro) that implement the method for predicting protein stability changes induced by amino acid mutations are freely available for the community to use.

Keywords: bioinformatics, deep learning, protein stability prediction, biological data mining

Procedia PDF Downloads 439

Authors: Shirley Lamptey, Lingling Li, Junhong Xie

Abstract:

Agriculture in the semi-arid is often challenged by overuse of N, inadequate soil water, and heavy carbon emissions thereby threatening sustainability. Field experiments were conducted to investigate the effect of nitrogen fertilization levels (0-N₀, 100-N₁₀₀, 200-N₂₀₀, and 300 kg ha⁻¹-N₃₀₀) on soil water dynamics, soil respiration (Rs), net ecosystem production (NEP), and biomass yield. Zero nitrogen soils decreased Rs by 23% and 16% compared to N₃₀₀ and N₂₀₀ soils, respectively. However, biomass yield was greatest under N₃₀₀ compared with N₀, which therefore translated into increased net primary production (NPP) by 89% and NEP by 101% compared to N₀. To a lesser extent, N₂₀₀ increased net primary production by 69% and net ecosystem production by 79% compared to N₀. Grain yields were greatest under N₃₀₀ compared with N₁₀₀ and N₀, which therefore translated into increased carbon emission efficiency (CEE) by 53%, 39% and 3% under N₃₀₀ compared to N₀, N₁₀₀, and N₂₀₀ treatments respectively. Under the conditions of this study, crop yield and CEE may be optimized at nitrogen application rates in the range of 200-300 kg ha⁻¹. Based on these results, there appears potential for 200 kg N ha⁻¹ to be used to improve yield and increase CEE in the context of the rainfall-limiting environment.

Keywords: carbon emission, carbon emission efficiency, C sequestration, N rates, semi-arid

Procedia PDF Downloads 215

Authors: Jayanta Kumar Ghosh, Swastik Sunil Goriwale, Himangshu Sarkar

Abstract:

Groundwater is one of the most valuable natural resources that society consumes for its domestic, industrial, and agricultural water supply. Its bulk and indiscriminate consumption affects the groundwater resource. Often, it has been found that the groundwater recharge rate is much lower than its demand. Thus, to maintain water and food security, it is necessary to monitor and management of groundwater storage. However, it is challenging to estimate groundwater storage (GWS) by making use of existing hydrological models. To overcome the difficulties, machine learning (ML) models are being introduced for the evaluation of groundwater level (GWL). Thus, the objective of this research work is to develop an ML-based model for the prediction of GWL. This objective has been realized through the development of an artificial neural network (ANN) model based on hydro-gravimetry. The model has been developed using training samples from field observations spread over 8 months. The developed model has been tested for the prediction of GWL in an observation well. The root means square error (RMSE) for the test samples has been found to be 0.390 meters. Thus, it can be concluded that the hydro-gravimetric-based ANN model can be used for the prediction of GWL. However, to improve the accuracy, more hydro-gravimetric parameter/s may be considered and tested in future.

Keywords: machine learning, hydro-gravimetry, ground water level, predictive model

Procedia PDF Downloads 109

Authors: Ishan Arora, Anurag Rathore

Abstract:

The primary objective of this work was to study the effect of resin chemistry, pH and molarity of binding and elution buffer on aggregate removal using Cation Exchange Chromatography and find the optimum conditions which can give efficient aggregate removal with minimum loss of yield. Four different resins were used for carrying out the experiments: Fractogel EMD SO3-(S), Fractogel EMD COO-(M), Capto SP ImpRes and S Ceramic HyperD. Runs were carried out on the AKTA Avant system. Design of Experiments (DOE) was used for analysis using the JMP software. The dependence of the yield obtained using different resins on the operating conditions was studied. Success has been achieved in obtaining yield greater than 90% using Capto SP ImpRes and Fractogel EMD COO-(M) resins. It has also been found that a change in the operating conditions generally has different effects on the yields obtained using different resins.

Keywords: aggregates, cation exchange chromatography, design of experiments, monoclonal antibodies

Procedia PDF Downloads 247

Authors: K. Roushanger, A. Soleymanzadeh

Abstract:

Weirs are structures often used in irrigation techniques, sewer networks and flood protection. However, the hydraulic behavior of this type of weir is complex and difficult to predict accurately. An accurate flow prediction over a weir mainly depends on the proper estimation of discharge coefficient. In this study, the Genetic Expression Programming (GEP) approach was used for predicting trapezoidal and rectangular sharp-crested side weirs discharge coefficient. Three different performance indexes are used as comparing criteria for the evaluation of the model’s performances. The obtained results approved capability of GEP in prediction of trapezoidal and rectangular side weirs discharge coefficient. The results also revealed the influence of downstream Froude number for trapezoidal weir and upstream Froude number for rectangular weir in prediction of the discharge coefficient for both of side weirs.

Keywords: discharge coefficient, genetic expression programming, trapezoidal weir

Procedia PDF Downloads 372

Authors: Khaled Al-Najjar, Ahmad Q. Al-Momani, Ahmed Elnahas, Reda Elsaid

Abstract:

The research was carried out using records of Awassi sheep bred in drylands at Al-Fjaj Station, Jordan. That aimed to study non-genetic factors affecting milk yield (MK), litter size at birth (LZB); estimate heritability, repeatability, and genetic and phenotypic correlation using SAS and MTDFREML programs. The results were as follows, the average MK and LZB were 92.84 (kg) and 1.16, respectively. MK was highly significantly affected by each parity, age of ewe, year of lambing, and lactation period, while only the year of lambing had a significant effect on LZB. The heritability and repeatability were 0.07 and 0.10 for MK, while it was 0.05 and 0.25 for LZB. The genetic and phenotypic correlations were 0.17 and 0.02 between MK and LZB, respectively. The research concluded that the herd is genetically homozygous and therefore needs to increase genetic variance by introducing LZB-improved rams and selecting females from dams who achieved at least four parties to increase returns in drylands.

Keywords: Awassi sheep, genetic parameters, litter size, milk yield

Procedia PDF Downloads 99

Authors: J. V. Thanikal, M. Torrijos, Philipe Sousbie, S. M. Rizwan, R. Senthil Kumar, Hatem Yezdi

Abstract:

Co-digestion is one of the advantages of anaerobic digestion process because; several wastes having complimentary characteristics can be treated in a single process. The anaerobic co-digestion process, which can be defined as the simultaneous treatment of two –or more – organic biodegradable waste streams by anaerobic digestion offers great potential for the proper disposal of the organic fraction of solid waste coming from source or separate collection systems. The results of biogas production for sewage sludge, when used as a single substrate, were low (350ml/d), and also the biodegradation rate was slow. Sewage sludge as a co-substrate did not show much effect on biogas yield. The vegetable substrates (Potato, Carrot, Spinach) with a total charge of 27–36 g VS, with a HRT starting from 3 days and ending with 1 day, shown a considerable increase in biogas yield 3.5-5 l/d.

Keywords: anaerobic digestion, co-digestion, vegetable substrate, sewage sludge

Procedia PDF Downloads 553

Authors: Ishan Arora, Anurag Rathore

Abstract:

The primary objective of this work was to study the effect of resin chemistry, pH and molarity of binding and elution buffer on aggregate removal using Cation Exchange Chromatography and find the optimum conditions which can give efficient aggregate removal with minimum loss of yield. Four different resins were used for carrying out the experiments: Fractogel EMD SO3-(S), Fractogel EMD COO-(M), Capto SP ImpRes and S Ceramic HyperD. Runs were carried out on the AKTA Avant system. Design of Experiments (DOE) was used for analysis using the JMP software. The dependence of the yield obtained using different resins on the operating conditions was studied. Success has been achieved by obtaining yield greater than 90% using Capto SP ImpRes and Fractogel EMD COO-(M) resins. It has also been found that a change in the operating conditions generally has different effects on the yields obtained using different resins.

Keywords: aggregates, cation exchange chromatography, design of experiments, monoclonal antibodies

Procedia PDF Downloads 241