Controllability of Efficiency of Antiviral Therapy in Hepatitis B Virus Infections

An optimal control problem for a mathematical model of efficiency of antiviral therapy in hepatitis B virus infections is considered. The aim of the study is to control the new viral production, block the new infection cells and maintain the number of uninfected cells in the given range. The optimal controls represent the efficiency of antiviral therapy in inhibiting viral production and preventing new infections. Defining the cost functional, the optimal control problem is converted into the constrained optimization problem and the first order optimality system is derived. For the numerical simulation, we propose the steepest descent algorithm based on the adjoint variable method. A computer program in MATLAB is developed for the numerical simulations.

A Multi-period Profit Maximization Policy for a Stochastic Demand Inventory System with Upward Substitution

This paper deals with a periodic-review substitutable inventory system for a finite and an infinite number of periods. Here an upward substitution structure, a substitution of a more costly item by a less costly one, is assumed, with two products. At the beginning of each period, a stochastic demand comes for the first item only, which is quality-wise better and hence costlier. Whenever an arriving demand finds zero inventory of this product, a fraction of unsatisfied customers goes for its substitutable second item. An optimal ordering policy has been derived for each period. The results are illustrated with numerical examples. A sensitivity analysis has been done to examine how sensitive the optimal solution and the maximum profit are to the values of the discount factor, when there is a large number of periods.

Six Sigma Process and its Impact on the Organizational Productivity

The six sigma method is a project-driven management approach to improve the organization-s products, services, and processes by continually reducing defects in the organization. Understanding the key features, obstacles, and shortcomings of the six sigma method allows organizations to better support their strategic directions, and increasing needs for coaching, mentoring, and training. It also provides opportunities to better implement six sigma projects. The purpose of this paper is the survey of six sigma process and its impact on the organizational productivity. So I have studied key concepts , problem solving process of six sigmaas well as the survey of important fields such as: DMAIC, six sigma and productivity applied programme, and other advantages of six sigma. In the end of this paper, present research conclusions. (direct and positive relation between six sigma and productivity)

Solving a New Mixed-Model Assembly LineSequencing Problem in a MTO Environment

In the last decades to supply the various and different demands of clients, a lot of manufacturers trend to use the mixedmodel assembly line (MMAL) in their production lines, since this policy make possible to assemble various and different models of the equivalent goods on the same line with the MTO approach. In this article, we determine the sequence of (MMAL) line, with applying the kitting approach and planning of rest time for general workers to reduce the wastages, increase the workers effectiveness and apply the sector of lean production approach. This Multi-objective sequencing problem solved in small size with GAMS22.2 and PSO meta heuristic in 10 test problems and compare their results together and conclude that their results are very similar together, next we determine the important factors in computing the cost, which improving them cost reduced. Since this problem, is NPhard in large size, we use the particle swarm optimization (PSO) meta-heuristic for solving it. In large size we define some test problems to survey it-s performance and determine the important factors in calculating the cost, that by change or improved them production in minimum cost will be possible.

Internal Behavior of Biological Nutrient Removal System for Advanced Wastewater Treatment

The purpose of this research was develop a biological nutrient removal (BNR) system which has low energy consumption, sludge production, and land usage. These indicate that BNR system could be a alternative of future wastewater treatment in ubiquitous city(U-city). Organics and nitrogen compounds could be removed by this system so that secondary or tertiary stages of wastewater treatment satisfy their standards. This system was composed of oxic and anoxic filter filed with PVDC and POM media. Anoxic/oxic filter system operated under empty bed contact time of 4 hours by increasing recirculation ratio from 0 to 100 %. The system removals of total nitrogen and COD were 76.3% and 93%, respectively. To be observed internal behavior in this system SCOD, NH3-N, and NO3-N were conducted and removal shows range of 25~100%, 59~99%, and 70~100%, respectively.

Preliminary Evaluation of Feasibility for Wind Energy Production on Offshore Extraction Platforms

A preliminary evaluation of the feasibility of installing small wind turbines on offshore oil and gas extraction platforms is presented. Some aerodynamic considerations are developed in order to determine the best rotor architecture to exploit the wind potential on such installations, assuming that wind conditions over the platforms are similar to those registered on the roofs of urban buildings. Economical considerations about both advantages and disadvantages of the exploitation of wind energy on offshore extraction platforms with respect to conventional offshore wind plants, is also presented. Finally, wind charts of European offshore winds are presented together with a map of the major offshore installations.

Productivity and Energy Management in Desert Urban

Growing world population has fundamental impacts and often catastrophic on natural habitat. The immethodical consumption of energy, destruction of the forests and extinction of plant and animal species are the consequence of this experience. Urban sustainability and sustainable urban development, that is so spoken these days, should be considered as a strategy, goal and policy, beyond just considering environmental issues and protection. The desert-s climate has made a bunch of problems for its residents. Very hot and dry climate in summers of the Iranian desert areas, when there was no access to modern energy source and mechanical cooling systems in the past, made Iranian architects to design a natural ventilation system in their buildings. The structure, like a tower going upward the roof, besides its ornamental application and giving a beautiful view to the building, was used as a spontaneous ventilation system. In this paper, it has been tried to name the problems of the area and it-s inconvenience, then some answers has pointed out in order to solve the problems and as an alternative solution BADGIR (wind-catcher) has been introduced as a solution knowing that it has been playing a major role in dealing with the problems.

Improving TNT Curing Process by Using Infrared Camera

Among the chemicals used for ammunition production, TNT (Trinitrotoluene) play a significant role since World War I and II. Various types of military weapon utilize TNT in casting process. However, the TNT casting process for warhead is difficult to control the cooling rate of the liquid TNT. This problem occurs because the casting process lacks the equipment to detect the temperature during the casting procedure This study presents the temperature detected by infrared camera to illustrate the cooling rate and cooling zone of curing, and demonstrates the optimization of TNT condition to reduce the risk of air gap occurred in the warhead which can result in the destruction afterward. Premature initiation of explosive-filled projectiles in response to set-back forces during gunfiring cause by casting defects. Finally the study can help improving the process of the TNT casting. The operators can control the curing of TNT inside the case by rising up the heating rod at the proper time. Consequently this can reduce tremendous time of rework if the air gaps occur and increase strength to lower elastic modulus. Therefore, it can be clearly concluded that the use of Infrared Cameras in this process is another method to improve the casting procedure.

Consumer Product Demand Forecasting based on Artificial Neural Network and Support Vector Machine

The nature of consumer products causes the difficulty in forecasting the future demands and the accuracy of the forecasts significantly affects the overall performance of the supply chain system. In this study, two data mining methods, artificial neural network (ANN) and support vector machine (SVM), were utilized to predict the demand of consumer products. The training data used was the actual demand of six different products from a consumer product company in Thailand. The results indicated that SVM had a better forecast quality (in term of MAPE) than ANN in every category of products. Moreover, another important finding was the margin difference of MAPE from these two methods was significantly high when the data was highly correlated.

Hand Written Digit Recognition by Multiple Classifier Fusion based on Decision Templates Approach

Classifier fusion may generate more accurate classification than each of the basic classifiers. Fusion is often based on fixed combination rules like the product, average etc. This paper presents decision templates as classifier fusion method for the recognition of the handwritten English and Farsi numerals (1-9). The process involves extracting a feature vector on well-known image databases. The extracted feature vector is fed to multiple classifier fusion. A set of experiments were conducted to compare decision templates (DTs) with some combination rules. Results from decision templates conclude 97.99% and 97.28% for Farsi and English handwritten digits.

Evaluation and Analysis of Lean-Based Manufacturing Equipment and Technology System for Jordanian Industries

International markets driven forces are changing continuously, therefore companies need to gain a competitive edge in such markets. Improving the company's products, processes and practices is no longer auxiliary. Lean production is a production management philosophy that consolidates work tasks with minimum waste resulting in improved productivity. Lean production practices can be mapped into many production areas. One of these is Manufacturing Equipment and Technology (MET). Many lean production practices can be implemented in MET, namely, specific equipment configurations, total preventive maintenance, visual control, new equipment/ technologies, production process reengineering and shared vision of perfection.The purpose of this paper is to investigate the implementation level of these six practices in Jordanian industries. To achieve that a questionnaire survey has been designed according to five-point Likert scale. The questionnaire is validated through pilot study and through experts review. A sample of 350 Jordanian companies were surveyed, the response rate was 83%. The respondents were asked to rate the extent of implementation for each of practices. A relationship conceptual model is developed, hypotheses are proposed, and consequently the essential statistical analyses are then performed. An assessment tool that enables management to monitor the progress and the effectiveness of lean practices implementation is designed and presented. Consequently, the results show that the average implementation level of lean practices in MET is 77%, Jordanian companies are implementing successfully the considered lean production practices, and the presented model has Cronbach-s alpha value of 0.87 which is good evidence on model consistency and results validation.

Microalgae-based Oil for Biodiesel Production

Biodiesel is traditionally produced from oleaginous plants. On the other hand, increasing biodiesel production from these raw materials could create problems of food supply. Producing biodiesel from microalgae could help to overcome this difficulty, because microalgae are rich in lipids and do not compete for arable lands. However, no studies had compared vegetable and microalgae oil-based biodiesel in terms of yield, viscosity and heat of combustion. In the present study, commercial canola and microalgae oil were therefore transesterified with methanol under a homogenous alkali catalyst (potassium hydroxide) at 100oC for 1h. The result showed that microalgae-based oil has a higher yield in biodiesel with 89.7% (g biodiesel/g oil) and a lower kinematic viscosity (22oC) of 4.31 mm/s2 than canola oil.

A Hybrid Model of ARIMA and Multiple Polynomial Regression for Uncertainties Modeling of a Serial Production Line

Uncertainties of a serial production line affect on the production throughput. The uncertainties cannot be prevented in a real production line. However the uncertain conditions can be controlled by a robust prediction model. Thus, a hybrid model including autoregressive integrated moving average (ARIMA) and multiple polynomial regression, is proposed to model the nonlinear relationship of production uncertainties with throughput. The uncertainties under consideration of this study are demand, breaktime, scrap, and lead-time. The nonlinear relationship of production uncertainties with throughput are examined in the form of quadratic and cubic regression models, where the adjusted R-squared for quadratic and cubic regressions was 98.3% and 98.2%. We optimized the multiple quadratic regression (MQR) by considering the time series trend of the uncertainties using ARIMA model. Finally the hybrid model of ARIMA and MQR is formulated by better adjusted R-squared, which is 98.9%.

Irrigation Scheduling for Maize and Indian-mustard based on Daily Crop Water Requirement in a Semi- Arid Region

Maize and Indian mustard are significant crops in semi-arid climate zones of India. Improved water management requires precise scheduling of irrigation, which in turn requires an accurate computation of daily crop evapotranspiration (ETc). Daily crop evapotranspiration comes as a product of reference evapotranspiration (ET0) and the growth stage specific crop coefficients modified for daily variation. The first objective of present study is to develop crop coefficients Kc for Maize and Indian mustard. The estimated values of Kc for maize at the four crop growth stages (initial, development, mid-season, and late season) are 0.55, 1.08, 1.25, and 0.75, respectively, and for Indian mustard the Kc values at the four growth stages are 0.3, 0.6, 1.12, and 0.35, respectively. The second objective of the study is to compute daily crop evapotranspiration from ET0 and crop coefficients. Average daily ETc of maize varied from about 2.5 mm/d in the early growing period to > 6.5 mm/d at mid season. The peak ETc of maize is 8.3 mm/d and it occurred 64 days after sowing at the reproductive growth stage when leaf area index was 4.54. In the case of Indian mustard, average ETc is 1 mm/d at the initial stage, >1.8 mm/d at mid season and achieves a peak value of 2.12 mm/d on 56 days after sowing. Improved schedules of irrigation have been simulated based on daily crop evapo-transpiration and field measured data. Simulation shows a close match between modeled and field moisture status prevalent during crop season.

An Intelligent Optimization Model for Multi-objective Order Allocation Planning

This paper presents a multi-objective order allocation planning problem with the consideration of various real-world production features. A novel hybrid intelligent optimization model, integrating a multi-objective memetic optimization process, a Monte Carlo simulation technique and a heuristic pruning technique, is proposed to handle this problem. Experiments based on industrial data are conducted to validate the proposed model. Results show that (1) the proposed model can effectively solve the investigated problem by providing effective production decision-making solutions, which outperformsan NSGA-II-based optimization process and an industrial method.

Energy Evaluation and Utilization of Cassava Peel for Lactating Dairy Cows

The experiment was then conducted to investigate the effect of cassava peel addition in the concentrate on the performance of lactating dairy cows. Twenty four Holstein Friesian crossbred (>87.5% Holstein Friesian) lactating dairy cows in mid lactation; averaging 12.2+2.1 kg of milk, 119+45 days in milk, 44.1+6.2 months old and 449+33 kg live weight, were stratified for milk yield, days in milk, age, stage of lactation and body weight, and then randomly allocated to three treatment groups. The first, second and third groups were fed concentrates containing the respective cassava peel, 0, 20 and 40%. All cows were fed ad libitum corn silage and freely access to clean water. Dry matter intake, 4%FCM, milk composition and body weight change were affected (P

Robust Design and Optimization of Production Wastes: An Application for Industries

This paper focuses on robust design and optimization of industrial production wastes. Past literatures were reviewed to case study Clamason Industries Limited (CIL) - a leading ladder-tops manufacturer. A painstaking study of the firm-s practices at the shop floor revealed that Over-production, Waiting time, Excess inventory, and Defects are the major wastes that are impeding their progress and profitability. Design expert8 software was used to apply Taguchi robust design and response surface methodology in order to model, analyse and optimise the wastes cost in CIL. Waiting time and overproduction rank first and second in contributing to the costs of wastes in CIL. For minimal wastes cost the control factors of overproduction, waiting-time, defects and excess-inventory must be set at 0.30, 390.70, 4 and 55.70 respectively for CIL. The optimal value of cost of wastes for the months studied was 22.3679. Finally, a recommendation was made that for the company to enhance their profitability and customer satisfaction, they must adopt the Shingeo Shingo-s Single Minute Exchange of Dies (SMED), which will immediately tackle the waste of waiting by drastically reducing their setup time.

Anaerobic Treatment of Petroleum Refinery Wastewater

Anaerobic treatment has many advantages over other biological method particularly when used to treat complex wastewater such as petroleum refinery wastewater. In this study two Up-flow Anaerobic Sludge Blanket (UASB) reactors were operated in parallel to treat six volumetric organic loads (0.58, 1.21, 0.89, 2.34, 1.47 and 4.14 kg COD/m3·d) to evaluate the chemical oxygen demand (COD) removal efficiency. The reactors were continuously adapting to the changing of operation condition with increase in the removal efficiency or slight decrease until the last load which was more than two times the load, at which the reactor stressed and the removal efficiency decreased to 75% with effluent concentration of 1746 mg COD/L. Other parameters were also monitored such as pH, alkalinity, volatile fatty acid and gas production rate. The UASB reactor was suitable to treat petroleum refinery wastewater and the highest COD removal rate was 83% at 1215 kg/m3·d with COD concentration about 356 mg/L in the effluent.

Fermentative Production of Dextran using Food Industry Wastes

Dextran is a D-glucose polymer which is produced by Leuconostoc mesenteroides grown in a sucrose-rich media. The organism was obtained from the Persian Type Culture Collection (PTCC) and was transferred in MRS broth medium at 30°C and pH 6.8 for 24 h. After preparation of inoculums, organisms were inoculated into five liquid fermentation media containing either molasses or cheese whey or different combinations of cheese whey and molasses. After certain fermentation period, the produced dextran was separated and dried. Dextran yield was calculated and significant differences in different media were observed. Furthermore, FT-IR analysis was performed and the results showed that there were no significant differences in the produced dextran structures.

Exploiting Machine Learning Techniques for the Enhancement of Acceptance Sampling

This paper proposes an innovative methodology for Acceptance Sampling by Variables, which is a particular category of Statistical Quality Control dealing with the assurance of products quality. Our contribution lies in the exploitation of machine learning techniques to address the complexity and remedy the drawbacks of existing approaches. More specifically, the proposed methodology exploits Artificial Neural Networks (ANNs) to aid decision making about the acceptance or rejection of an inspected sample. For any type of inspection, ANNs are trained by data from corresponding tables of a standard-s sampling plan schemes. Once trained, ANNs can give closed-form solutions for any acceptance quality level and sample size, thus leading to an automation of the reading of the sampling plan tables, without any need of compromise with the values of the specific standard chosen each time. The proposed methodology provides enough flexibility to quality control engineers during the inspection of their samples, allowing the consideration of specific needs, while it also reduces the time and the cost required for these inspections. Its applicability and advantages are demonstrated through two numerical examples.