Food security modelling using two stage hybrid model and fuzzy logic risk assessment

Food security has become a key issue worldwide in recent years. According to the Department for Environment Food and Rural Affair (DEFRA) UK, the key components of food security are food availability, global resource sustainability, access, food chain resilience, household food security, safety and confidence of public towards food system. Each of these components has its own indicators which need to be monitored. Only a few studies had been made towards analysing food security and most of these studies are based on conventional data analysis methods such as the use of statistical techniques. In handling food security datasets such as crops yield, production, economy growth, household behaviour and others, where most of the data is imprecise, non-linear and uncertain in nature, it is better to handle the data using intelligent system (IS) techniques such as fuzzy logic, neural networks, genetic algorithm and hybrid systems, rather than conventional techniques. Therefore this thesis focuses on the modelling of food security using IS techniques, and a newly developed hybrid intelligent technique called a 2-stage hybrid (TSH) model, which is capable of making accurate predictions. This technique is evaluated by considering three applications of food security research areas which relate to each of the indicators in the DEFRA key food security components. In addition, another food security model was developed, called a food security risk assessment model. This can be used in assessing the level of risk for food security. The TSH model is constructed by using two key techniques; the Genetic Algorithm (GA) module and the Artificial Neural Network (ANN) module, where these modules combine the global and local search, by optimizing the inputs of ANN in the first stage process and optimizing of weight and threshold of ANN, which is then used to remodel the ANN resulting in better prediction. In evaluating the performance of the TSH prediction model, a total of three datasets have been used, which relate to the food security area studied. These datasets involve the prediction of farm household output, prediction of cereal growth per capita as the food availability main indicators in food security component, and grain security assessment prediction. The TSH prediction model is benchmarked against five others techniques. Each of these five techniques uses an ANN as the prediction model. The models used are: Principal Component Analysis (PCA), Multi-layered Perceptron-Artificial Neural Network (MLP-ANN), feature selection (FS) of GA-ANN, Optimized Weight and Threshold (OWTNN) and Sensitive Genetic Neural Optimization (SGNO). Each of the application datasets considered is used to show the capability of the TSH model in making effective predictions, and shows that the general performance of the model is better than the other benchmarked techniques. The research in this thesis can be considered as a stepping-stone towards developing other tools in food security modelling, in order to aid the safety of food security

Applying the Bayesian Technique in Designing a Single Sampling Plan

 The Bayesian sampling plans for production inspection are considered a technique of sampling inspection techniques for determining the characteristics of the sampling plan based on the assumption that the rate of defectives is a random variable that varies from one production batch to the next, resulting in a probability distribution f(p) that could be determined based on experience and the available quality information available. As part of this study, the parameters of a single Bayesian sampling plan (n,c) were derived by using the Beta-Binomial distribution and compared with those of other single sampling plans. Researchers have identified (ALA company for soft drinks), which handles product quality control. 120 production batches were selected, and the size of the batch and the number of defective items were used to determine the proportion of defective items, given that the variable varies randomly from one production batch to the next. Bayesian and decision-making models can be implemented to create a single sampling inspection process that is close to the actual quality level. The researchers discovered that when the decision-making model was used, the sample size was minimal compared to other inspection plans, leading to a low inspection cost

Anti-inflammatory activity of Nigella sativa oil in rats

Nigella sativa (N. sativa), commonly known as black seed, has been a well known herb since ancient times with a wide range of healing properties. The aim of this study was to investigate anti-inflammatory activity of N. sativa seed oil at three dosages on carrageenan-induced paw oedema, total white blood cell (TWBC) count and plasma protein in rats. Acute inflammation was induced by subplantar injection of carrageenan (0.1 ml, 1 % w/v) into the rat hind paw. 500 mglkg, 1000 mg/kg and 1500 mg/kg of N. sativa oil were administrated orally. Paw oedema, total white blood cell count and plasma protein were assessed. N. sativa seed oil exerted significant inhibition of paw oedema at the dosage of 1500 mg/kg at second hour and plasma protein at a dosage of 1000 mg/kg at third hour (p< 0.05). No significant inhibition ofTWBC count was exerted by N. sativa seed oil at third hour after treatment at dosages used in this study. There was also dose-dependent correlation of N. sativa seed oil on inhibition of paw oedema. These results support the traditional use of N. sativa seed oil for the treatment of inflammatory diseases

Perencanaan Embung Tamanrejo Kecamatan Sukorejo, Kabupaten Kendal

The population and community activities that lead to increased irrigation water demand is increasing and causing problems between water balance demand and water availability. To overcome this case was built water building of small dam. Tamanrejo small dam situated on the Kajar River, Sukorejo Kendal Regency. Tamanrejo small dam is planned to meet the needs of irrigation water in the District Sukorejo, irrigation area that will be served an estimated area of 750 acres. Discharge mainstay Kajar River calculated based FJ. Mock method with the probability of 20% is not being met. In Agustus until November there is a shortage of water at 108.493,75 m3. Small dam volume of 126.073,69 m3 is at an elevation of +140,00 m to +147,00 m. The result of water balance calculations indicate that the volume of 126.073,69 m3 can to meet the need of irrigation water when the river have flow shortage. Calculation results obtained irrigation water needs 1,54 l/sec/acres as irrigation water requirement rate on average. Construction of a small dam Tamanrejo be making use of the spillway and dam embankment body. Determination of dimensions small dam Tamanrejo use flood discharge plan from the HSS Gama I method of 83,189 m3/sec with a return period of 50 years. The planned small dam 11 m high, with a base elevation ponds +140,00 m, +151,00 m small dam crest elevation. Small dam crest width of 5,00 m, upstream slope of 1:3 and downstream slope of 1:2,25. In planning small dam Tamanrejo used ogee type open spillway (overflow spillway) with a width of 25 m, length 13 m and elevation crest spillway at +147,00 m, using an eject USBR type III with a length of 5,00 m. Plan Implementation time is 24 weeks with work plan budget of Rp. 6,258,700,000.00 (Six Billion Two Hundred Fiffty Eight Million Seven Hundred Thousand Rupiah). Conclusion with built small dam can overcome the shortage of irrigation water

The Evaluation of Potentiostats: Electrochemical Detection Devices

This study evaluated the performance of three types of potentiostats; EmStat, CheapStat and UTMStat. EmStat is the smallest potentiostat available in the market. CheapStat is an open-source potentiostat suitable for educational applications. In addition, UTMStat is the extension of CheapStat, which was designed to overcome few weaknesses of CheapStat such as the input controller/ switch and data storage handling of the cyclic voltammogram. The cyclic voltammetry and amperometry measurements of ions ferrocyanide ([Fe(CN)6]4−) and chloride (Cl-) were carried out for each potentiostat. EmStat potentiostat is not only able to detect but also to measure ferrocyanide and chloride ions. However, CheapStat and UTMStat are only able to detect and measure ferrocyanide ions. The experiment is unable to be conducted due to limitation of waveform selection on both devices. Nevertheless, CheapStat and UTMStat could provide a reliable measurement to realize miniaturized lab-on-chip applications as shown in this study

Flexible ECG circuit fabrication and application using vinyl cutting technique

The aim of this study is to prove the capability of vinyl cutting technique to cut the conductive traces of electronic circuit layout which used a copper tape (Copper tape 1181 from 3M) on flexible substrate to replace the method of using nano-scale particle material. A wireless electrocardiography (ECG) circuit was integrated and fabricated on flexible substrate, namely a polyethylene terephthalate (PET) substrate by using vinyl cutting method to produce the conductive line traces. After that, the fabricated circuit is used for acquiring ECG signals from a patient simulator and human subjects to measure the performance differences and compatibility as a wearable device. In the data processing stage, ECG data were denoised using sym20 from Wavelet Transform tool provided by MATLAB. Then, Signal-to-noise-ratio (SNR) was calculated and used as the signal quality indicator. At the end of the study, flexible circuit performance was compared to MIT-BIH Arrhythmia database and it shows that there is no significance difference between both. In conclusion, vinyl cutting method shows a promising fabrication output on PET substrate as the performance of both flexible ECG circuit is comparable with rigid ECG circuit by a previous study

PEMENUHAN KEBUTUHAN OKSIGENASI DENGAN PEMBERIAN POSISI HEAD UP 30˚ PADA PASIEN STROKE

Stroke as cerebrovascular damage, is a loss of brain function caused by cessation or reduced blood supply to an area of the brain, resulting in local or global neurological dysfunction. Substandard blood flow in stroke patients can lead to hemodynamic abnormalities, where hemodynamic conditions affect the distribution of oxygen throughout the body, affect heart function and reduce oxygen saturation so that stroke is an emergency case and requires fast and appropriate help. Purpose: of this study was to determine how to fulfill the need for oxygenation by giving a 30˚ head up position in stroke patients. Method: used is a literature study or literature review using articles/journals in the form of fulfilling oxygen needs by giving a 30˚ head up position in stroke patients. Results: showed that there was a significant increase in oxygen saturation levels after the 30˚ head up position in stroke patients. Conclusion :of this study is that one of the interventions that can be carried out in fulfilling oxygenation in stroke patients is giving a 30 head up position with a head elevation or 30˚ head up position that can facilitate increased cerebral blood flow and maximize cerebral tissue oxygenatio

Characterisation, performance and optimisation of nanocellulose metalworking fluid (MWF) for green machining process

The present research attempts to develop a hybrid coolant by mixing alumina nanoparticles with cellulose nanocrystal (CNC) into ethylene glycol-water (60:40) and investigate the viability of formulated hybrid nanocoolant (CNC-Al2O3-EG-Water) towards enhancing the machining behavior. The two-step method has been adapted to develop the hybrid nanocoolant at various volume concentrations (0.1, 0.5, and 0.9%). Results indicated a significant enhancement in thermal properties and tribological behaviour of the developed hybrid coolant. The thermal conductivity improved by 20-25% compared to the metal working fluid (MWF) with thermal conductivity of 0.55 W/m℃. Besides, a reduction in wear and friction coefficient was observed with the escalation in the nanoparticle concentration. The machining performance of the developed hybrid coolant was evaluated using Minimum Quantity Lubrication (MQL) in the turning of mild steel. A regression model was developed to assess the deviations in the tool flank wear and surface roughness in terms of feed, cutting speed, depth of the cut, and nanoparticle concentration using Response Surface Methodology (RSM). The mathematical modeling shows that cutting speed has the most significant impact on surface roughness and tool wear, followed by feed rate. The depth of cut does not affect surface roughness or tool wear. Surface roughness achieved 24% reduction, 39% enhancement in tool length of cut, and 33.33% improvement in tool life span. From this, the surface roughness was primarily affected by spindle cutting speed, feed rate, and then cutting depth while utilising either conventional water or composite nanofluid as a coolant. The developed hybrid coolant manifestly improved the machining behaviour