Scheduling Of Applications Research Articles

Effect of nitrogen schedule and management on yield of late-sown wheat (Triticum aestivum) in rice–wheat system

A field experiment was conducted during the winter (rabi) season of 2016–17 at the Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut, Uttar Pradesh, to evaluate the effect of nitrogen level and its schedule on late-sown wheat (Triticum aestivum L.) crop. The soil of the experimental field was well-drained, sandy loam, alkaline (pH 7.80), low in available nitrogen, medium in available phosphorus and potassium with an electrical conductivity 0.25 d/Sm. Eleven treatments comprising control, recommended dose of nitrogen (RDN) for timely as well as late-sown wheat (variety ‘PBW 226’) with different application schedule were tested in randomized block design with 3 replications. Growth parameters were significantly better in the treatments where major portion of N was applied during early growth period. The highest grain yield and harvest index were recorded in T8 treatment where 60% of recommended N in accordance to timely sown wheat was applied at sowing. This treatment was found statistically similar to T4 , [RDN for timely sown wheat 150 kg N in 2 split-50% N basal and 50% at crown-root initiation (CRI)], T6 (RDN for timely sown wheat 150 kg N in 3 splits-60% N basal, 30% at CRI and 10% at tillering) and T10 (RDN for timely sown wheat 150 kg N in 3 splits-60% N basal, 34% at CRI and 2% urea spray at tillering). Growth and yield-attributing characters were comparatively higher in T8 treatment. Available nutrients in soil after harvesting of wheat were found variable under different treatments.

Optimizing rate and time of nitrogen application for reducing nitrogen requirement and increasing productivity of wheat

As per 4Rs nutrient stewardship, the right timing and right rate of nitrogen (N) are two important attentions for profitable and sustainable crop production, particularly in the N deficient soil. The effectiveness of N utilization depends on the appropriate timing and amount of N application as per the crop demands at the critical stages of crop growth. The experiment was carried out at the experimental field of Agrotechnology Discipline, Khulna University, Bangladesh during the winter season of 2019-20 to investigate into the effect of schedule and rates of N application on wheat growth, yield and profitability. The experimental treatments comprised three application schedules (66% at sowing and 34% at the 3-leaf stage; 50% at 3-leaf, 30% at jointing and 20% at the booting stage; 50% at 6-leaf stage, 30% at jointing and 20% at the booting stage) and three nitrogen rates (120, 92 and 80 kg ha-1) with three replications. The yield attributes and yield of wheat were substantially affected by the schedule and rates of N application yet growth parameters were not significant. The highest grain yield, total dry matter, grains spike-1 and 1000-seed weight were achieved from the application of N @ 50% at 3-leaf, 30% at jointing and 20% at booting stages with 120 kg ha-1. Statistically similar results were also attained by the same application schedule with a reduced rat2.e of N (92 kg ha-1) due to proper distribution based on the crop requirement on different growth stages rather than the usual practice with a higher rate of N. The maximum net return (BDT 50687) and benefit-cost ratio (1.62) were found in the application of 92 kg ha-1 N in three splits @ 50% at 3-leaf, 30% at jointing and 20% at booting stages. The findings of this study revealed that the right application schedule reduces 25% N requirement and increases the grain yield of wheat.

Power Scheduling with Max User Comfort in Smart Home: Performance Analysis and Tradeoffs

The smart grid has enabled users to control their home energy more effectively and efficiently. A home energy management system (HEM) is a challenging task because this requires the most effective scheduling of intelligent home appliances to save energy. Here, we presented a meta-heuristic-based HEM system that integrates the Greywolf Algorithm (GWA) and Harmony Search Algorithms (HSA). Moreover, a fusion initiated on HSA and GWA operators is used to optimize energy intake. Furthermore, many knapsacks are being utilized to ensure that peak-hour load usage for electricity customers does not surpass a certain edge. Hybridization has proven beneficial in achieving numerous objectives simultaneously, decreasing the peak-to-average ratio and power prices. Widespread MATLAB simulations are cast-off to evaluate the routine of the anticipated method, Harmony GWA (HGWA). The simulations are for a multi-family housing complex outfitted with various cool gadgets. The simulation results indicate that GWA functions better regarding cost savings than HSA. In reputes of PAR, HSA is significantly more effective than GWA. The suggested method reduces costs for single and ten-house construction by up to 2200.3 PKR, as opposed to 503.4 in GWA, 398.10 in HSA and 640.3 in HGWA. The suggested approach performed better than HSA and GWA in PAR reduction. For single-family homes in HGWA, GWA and HSA, the reduction in PAR is 45.79%, 21.92% and 20.54%, respectively. The hybrid approach, however, performs better than the currently used nature-inspired techniques in terms of Cost and PAR.

DEVELOPMENT OF A MAINTENANCE POSSESSION SCHEDULER FOR A RAILWAY

Maintenance of rail infrastructure is an important element in rail operations to keep traffic moving. However, maintenance causes infrastructure to be taken out of service, which impacts traffic flow. In this study, the requirements of a maintenance possession scheduler for a South African application were investigated and a proposed solution was developed. The main objective of the scheduler was to minimise the deviation of the train service on a subset of rail infrastructure while ensuring that the required maintenance was done. An application case – the railway infrastructure between Bellville and Wellington in the Western Cape province of South Africa – was identified. A novel mixed-integer linear programming model that could do possession scheduling for 24 hours on a microscopic level was formulated for this case, and implemented in the software Cplex, after which it was validated. Finally, several experiments were conducted to investigate the model’s performance and the results. It was found that the model delivered optimal results in less than nine minutes, which makes it a feasible maintenance possession scheduler for day-to-day work in the immediate planning horizon. Keywords: rail scheduling, maintenance, mixed-integer linear programming

Failure Prediction for Scientific Workflows Using Nature-Inspired Machine Learning Approach

Scientific workflows have gained the emerging attention in sophisticated large-scale scientific problem-solving environments. The pay-per-use model of cloud, its scalability and dynamic deployment enables it suited for executing scientific workflow applications. Since the cloud is not a utopian environment, failures are inevitable that may result in experiencing fluctuations in the delivered performance. Though a single task failure occurs in workflow based applications, due to its task dependency nature, the reliability of the overall system will be affected drastically. Hence rather than reactive fault-tolerant approaches, proactive measures are vital in scientific workflows. This work puts forth an attempt to concentrate on the exploration issue of structuring a nature inspired metaheuristics-Intelligent Water Drops Algorithm (IWDA) combined with an efficient machine learning approach-Support Vector Regression (SVR) for task failure prognostication which facilitates proactive fault-tolerance in the scheduling of scientific workflow applications. The failure prediction models in this study have been implemented through SVR-based machine learning approaches and the precision accuracy of prediction is optimized by IWDA and several performance metrics were evaluated on various benchmark workflows. The experimental results prove that the proposed proactive fault-tolerant approach performs better compared with the other existing techniques.

Hot workability characteristics of two A335 P92 steels for power plant application: A comparative study

The article reports on the workability of two P92 steels having a chromium content of 8.29 and 9.48 wt%. Constitutive equations were used to calculate material parameters describing the hot deformation flow stress. Hot deformation tests were conducted using the Gleeble® 3500 thermomechanical facility. Test conditions were: temperature of 850-1000°C and strain rate of 0.1-10s-1 to a strain of 0.5. The flow stress curve results show that dynamic recovery was the only softening mechanism. A comparative study of the two steels revealed that Cr content had a marginal significance on the flow stress behaviour. Constitutive analysis results of the material parameters were: a stress exponent of 9.0 (P92-A), and 11.0 (P92-B), while the activation energy was 369 kJmol-1 (P92-A), and 472 kJmol-1 (P92-B). A brief explanation of the material parameter results is in this article. A flow stress model was developed to predict the flow stress behaviour of the two P92 steels investigated. The results show that the model accurately predicts the flow stress at all the deformation conditions applied. The statistical parameters showed a good correlation between the predicted and the experimental data. Therefore, this model can be used to develop metal forming schedules for industrial applications.

Investigation of the effect of mutual vaccination with pest des petits ruminants and polyvalent foot and mouth disease vaccines on the immune response of sheep.

Pest des petits ruminants (PPRs) and foot and mouth disease (FMD) are two viral infectious diseases affecting sheep dramatically causing great economic losses. Therefore, attention should be directed toward their control, especially through the application of well-designed vaccination schedules with specific potent vaccines. Determination of the possibility of sheep vaccination with PPR and FMD vaccines in a mutual schedule. Different groups of sheep have vaccinated with live attenuated PPR vaccine and inactivated polyvalent FMD vaccine in a mutual manner (one before the other at weekly intervals or simultaneously) followed by monitoring of the induced immunity to both vaccines using serum neutralization test (SNT) and enzyme linked immune sorbent assay (ELISA). SNT and ELISA revealed that there was no antagonizing effect of any vaccine on the immune response to the mutual vaccination of sheep to the other where the obtained antibody titers in single vaccinated sheep groups were similar to those in the simultaneous vaccinated group. Simultaneous vaccination of sheep with PPR and polyvalent FMD vaccine is of applicable benefit saving time, effort, and stress factors on the animals.

Towards a Methodology for Production Scheduling Using Reinforcement Learning Under Consideration of a Company's Individual Tasks and Goals

The impact of the covid pandemic and the chip crisis on industrial production are just a few examples that emphasize the complex and volatile environment production systems must cope with. Especially operational scheduling tasks intensely suffer from these influences due to increased complexity in decision-making as well as frequent rescheduling activities. At the same time, they highly affect production-related key performance indicators such as lead time or resource utilization. As several publications have already shown, applying innovative and data-based methods from the field of Reinforcement Learning (RL) to complex scheduling tasks provides great potential to handle the challenges arising from a complex and volatile environment. The building blocks of an RL approach strongly depend on a company's individual task specifications and optimization goals. Yet, a methodology that considers these specifications for the design of RL approaches in production scheduling has not been introduced, preventing the transfer from laboratory examples to wide-ranging industry applications. To address this research gap, this paper aims to provide a conceptual methodology to generate RL solutions depending on the scheduling tasks and objectives. The methodology proposed in this paper consists of four central modules that constitute the building blocks of an RL solution. The first module derives the action space for the RL approach based on the underlying scheduling tasks. The second module constructs the reward function of the RL approach based on a company's individual scheduling targets. The third module derives the state vector from the components of the reward function. The last module selects an appropriate optimization algorithm for the RL approach and merges the previous modules to learn an optimal scheduling policy in a simulation environment that can be applied to real-world problems. As a result, the application of RL-based scheduling enables production systems to meet current requirements and evolve into resilient and self-optimizing systems.

PENGEMBANGAN APLIKASI PENJADWALAN PRAKTIKUM MENGGUNAKAN ALGORITMA GENETIK DI LABORATORIUM KOMPUTER FAKULTAS TEKNOLOGI INFORMASI

ABSTRACT: Scheduling is an information medium used to facilitate the timing of the implementation of activities. As well as the implementation of the practicum at the Faculty of Information Technology, Bale Bandung University which determines the schedule using a scheduling application. However, in this practicum scheduling application, you can still input the same data and of course this can cause the practicum schedule to conflict. So to avoid the similarity of the practicum schedule data, it must be checked again manually. This practicum scheduling application needs to be developed again so that the implementation of the practicum will be helped more easily and practically. The development of this practicum scheduling application uses genetic algorithms to avoid the same data and recommend non- conflicting schedules. In the process of developing the application, practicum scheduling is carried out using the System Development Life Cycle (SDLC) waterfall model method with stages of analysis, design, implementation and testing. In addition to scheduling avoiding conflicts and displaying schedule recommendations using genetic algorithms plus also by using the add, edit and delete features multiple in one action to make it easier for users to process data, especially practical data, because every year they have to input practices or new students.

Assessment of Method and Application Schedule of Fertilizer N and K on Growth and Productivity of Summer Planted Sugarcane Crop (Saccharum officinarum L.) under Wide Spacing

Present investigation was carried out at Regional Research Station, Uchani (Karnal) of CCS Haryana Agricultural University, Hisar, India during 2020-21 to assess the effect of method and schedule of fertilizer application on growth, yield attributes and cane yield of summer planted sugarcane (Saccharum officinarum L.) crop under wide spacing (120 cm). The experiment was arranged in split plot design with two methods of fertilizer application (B1-broadcasting and B2- band placement) as main plot treatments and four sub plot treatments which include application of recommended dose of N and K fertilizer (RDF) in different number of splits at different no. of days after planting (DAP) i.e. T1 (five splits), T2 (six splits), T3 (seven splits) and T4 (three splits). Results concluded that majority of growth parameters, yield attributes and cane yield were significantly affected by both main and sub plot treatments at different stages of crop growth period. Treatment B2 registered significantly higher tiller population (110.59 and102.68 000 ha-1 at 60 and 120 DAP respectively), plant height (91.16, 141.18, 400.12 and 412.13 cm at 60, 120, 180 and 240 DAP respectively), no. of millable canes (NMC) (100.79 and 96.58 000 ha-1 in mid-September and at harvesting respectively) cane length (234.64 cm at harvesting) and cane yield (93.16 t ha-1)compared to B1. Among sub plot treatments, T1 outperformed all the other treatments in terms of growth, yield attributes and cane yield. Treatment T1 registered maximum plant height (150.43, 411.0 and 427.45 cm at 120, 180 and 240 DAP respectively), tiller population (104.72 000 ha-1 at 120 DAP), NMC (102.06 and 95.20 000 ha-1 in mid-September and at harvesting respectively) and cane yield (94.83 t ha-1). Germination percentage, cane girth, no. of internodes per cane and length of internodes was not significantly affected either by main or sub plot treatments.

Multi-stage mine production timetabling with optimising the sizes of mining operations: an application of parallel-machine flow shop scheduling with lot streaming

Multi-stage mine production timetabling with optimising the sizes of mining operations: an application of parallel-machine flow shop scheduling with lot streaming

Optimizing the Methods and Schedule of Fertilization Escalated Nutrient Uptake, Nutrient Use Efficiency and Dry Matter Yield of Sugarcane (Saccharum officinarum L.)

A field study was performed at Regional Research Station, Uchani (Karnal) of CCS Haryana Agricultural University, Hisar, India during 2020-21 to ascertain the role of precision nutrient management in enhancing nutrient availability to plants by amending the schedule and method of N and K fertilization in spring planted sugarcane (Saccharum officinarum L.) crop under wide spacing (120 cm). The experiment was devised under split plot design with three replications. The main plot treatments consisted of two methods of fertilizer placement (B1-broadcasting and B2-band placement) while sub plot treatments included four schedules of application of recommended dose of N and K (RDN+RDK) in five splits (T1), six splits (T2), seven splits (T3) and T4 (RDN in three splits, full dose of P and K at planting). All the main and sub plot treatments showed a remarkable influence on nutrient uptake (kg ha-1), partial factor (kg kg-1) productivity, dry matter accumulation (t ha-1) and plant macro-nutrient content. B1 and T1 among main and sub plot treatments respectively lead to greater nutrient uptake, partial factor productivitie of NPK and highest dry matter yield.

Bi-level optimization of resource allocation and appliance scheduling in residential areas using a Fog of Things (FOT) framework

Bi-level optimization of resource allocation and appliance scheduling in residential areas using a Fog of Things (FOT) framework

Macronutrient Status and Soil Chemical Properties as Influenced by Methods and Schedule of Fertilization in Karnal Alfisols under Sugarcane (Saccharum officinarum L.) Cultivation

An experiment was conducted at the Regional Research Station , Uchani (Karnal) of CCS Haryana Agricultural University, Hisar, India during 2020-21 to assess the effect of the method and schedule of fertilizer application on macronutrient status viz. available Nitrogen (N), Phosphorus (P) and potassium(K) and soil chemical properties i.e. soil pH, electrical conductivity (EC) and soil organic carbon (SOC) at different intervals of the crop growth period. The experiment was laid out in split plot design with two methods of fertilizer application (B1-broadcasting and B2- band placement) as main plot treatments and four sub plot treatments consisting of the application of recommended doses of N and K fertilizer (RDF) in the different number of splits at different number of days after planting (DAP) i.e. T1(five splits), T2(six splits), T3(seven splits) and T4(three splits). Results elucidated that the availability of all the macronutrients was significantly affected by both sub and main-plot treatments at different stages of crop growth period. Available N content was found to be significantly higher in B2 compared to B1 at all the time intervals from 75 DAP (131.86 Kg ha-1 ) to harvest (145.91 Kg ha-1 ) reaching the maximum at 180 DAP (142.80 Kg ha-1). Among the sub plot treatments, T4 and T1 respectively reported significantly higher values of available N from 75 DAP (134.51 Kg ha-1 ) to 90 DAP (147.08 Kg ha-1) and 90 DAP(153.10 Kg ha-1) to 150 DAP(162.11 Kg ha-1). At 180 DAP and at the time of harvesting, significantly higher values of available N (159.21 Kg ha-1 and 157.01Kg ha-1 ) were observed in treatments receiving fertilizer in T2 and T3 splits respectively. Available K content was significantly higher in B1 compared to B2 at all the time intervals except at 0, 150, 180 DAP and at harvest where the difference was not significant. Higher values of available K were reported under T4 upto 75 DAP (225.30 Kg ha-1) and thereafter, T1 exhibited significantly higher available K values upto 150 DAP (222.06 Kg ha-1). At 180 DAP and at the time of harvesting, significantly higher values of available K (225.10 Kg ha-1 227.48 Kg ha-1) were observed in T2 and T3 respectively. Available P content was significantly higher (24.63 Kg ha-1) in B1 compared to B2 at the time of harvesting. Soil pH, EC and SOC did not registered any significant change under any treatment. Overall treatment B2 and T1 emerged out be best among main and sub-plot treatments respectively. Availing the suitable methods and schedule of fertilization improved the status of micronutrients in soil during the active growth stage of crop.

Machine Learning for Fog Computing: Review, Opportunities and a Fog Application Classifier and Scheduler

Machine Learning for Fog Computing: Review, Opportunities and a Fog Application Classifier and Scheduler

MIRROR: Methodological Innovation to Remodel the Electric Loads to Reduce Economic OR Environmental Impact of User

Demand for electricity is constantly increasing, and production is facing new constraints due to the current world situation. An alternative to standard energy production methodologies is based on the use of renewable sources; however, these methodologies do not produce energy consistently due to weather factors. This results in a significant commitment of the user who must appropriately distribute loads in the most productive time slots. In this paper, a comparison is made between two methods of predicting solar energy production, one statistical and the other meteorological. For this work, a system capable of presenting the scheduling of household appliances is tested. The system is able to predict the energy consumption of the users and the energy production of the solar system. The system is tested using data from three different users, and the mean percentage of consumption reduction is about 77.73%. This is achieved through optimized programming of appliance use that also considers user comfort.

An improved greedy algorithm for stochastic online scheduling on unrelated machines

Most practical scheduling applications involve some uncertainty about the arriving times and lengths of the jobs. Stochastic online scheduling is a well-established model capturing this. Here the arrivals occur online, while the processing times are random. For this model, Gupta, Moseley, Uetz, and Xie recently devised an efficient policy for non-preemptive scheduling on unrelated machines with the objective to minimize the expected total weighted completion time. We improve upon this policy by adroitly combining greedy job assignment with αj-point scheduling on each machine. In this way we obtain a (3+5)(2+Δ)-competitive deterministic and an (8+4Δ)-competitive randomized stochastic online scheduling policy, where Δ is an upper bound on the squared coefficients of variation of the processing times. We also give constant performance guarantees for these policies within the class of all fixed-assignment policies. The αj-point scheduling on a single machine can be enhanced when the upper bound Δ is known a priori or the processing times are known to be δ-NBUE for some δ≥1. This implies improved competitive ratios for unrelated machines but may also be of independent interest.

Optimal Load Scheduling of Home Appliances Considering Operation Conditions

To reduce energy consumption arising from increasing energy efficiency in response to energy depletion around the world, energy price rises, climate change, and accidents of electric power are cooperating simultaneously. Recognizing the seriousness of the above-mentioned problems, feasible and effective policies for reducing greenhouse gas have been promoted in developed countries since the 2000s. Moreover, industry and academia are actively researching to develop energy-efficient and eco-friendly technologies, respectively. This study proposes an optimal model for scheduling home appliances that minimizes power costs by assuming a smart-home environment with smart metering and advanced metering infrastructure. In addition, a case-study was performed using actual data from South Korea, and sensitivity analysis was performed according to changes in parameters. The experiment considered possible real-life situations, such as an increase and decrease in power cost and a limitation in power usage, and proved that the proposed model was excellent to establish a power schedule for home appliances. This research result seems to serve as a guideline in relation to the control of home appliances to reduce power and smart homes.

National consensus on biologic dose reduction in psoriasis: a modified eDelphi procedure

BackgroundDose reduction of biologics for psoriasis is applied in daily practice, although guidelines are lacking. Striving for clear criteria is important, as it leads to a consistent application of dose reduction.ObjectiveTo achieve consensus on criteria for biologic dose reduction in psoriasis patients with stable and low disease activity.MethodsAn online Delphi procedure (eDelphi) was conducted. Dutch dermatologists were invited to participate in a maximum of 3 voting rounds. Proposed statements were selected based on literature review and included criteria for the application of dose reduction and dosing schedules. Biologic dose reduction was defined as ‘application of injection interval prolongation’. Proposed statements were rated using a 9-point Likert scale; consensus was reached when ≥70% of all voters rated ‘agree’ (7–9) and <15% rated ‘disagree’ (1–3).ResultsA total of 27 dermatologists participated and reached a consensus on 15 recommendations over 2 voting rounds. Agreed statements included criteria for dose reduction eligibility, criteria for dose reduction (dis)continuation, and dosing schedules for adalimumab, etanercept, and ustekinumab. Based on the eDelphi outcomes, an algorithm fit for implementation in current practice was developed.ConclusionsRecommendations of this national consensus process can guide clinicians, and consequently their patients, toward consistent application of biologic dose reduction.

Islamic events reminder system via short message service notifications alert

For persons working in the field of modern technology, the lack of awareness about Islamic events remains a significant obstacle. One of the numerous reasons why the event gets forgotten on its designated date. This prompted the creation of an automatic reminder system with mobile technology integration. This paper has the purpose of assisting people in remembering their daily Islamic events, as well as serving as a model for informing people of Islamic occasions via short message service (SMS) notifications. As a result, the main goal is to develop an Islamic model that uses SMS to inform people. To develop a free system based on the concept of recalling the most significant events in Muslim history in order to keep people informed. (Microsoft Visual Studio.net and Microsoft SQL Server Management Studio Express) as our main database. The text message reminder system is made up of two parts: an SMS application for automatic text messaging and a web-based application for customer registration and automatic reminder scheduling. The automated method delivered 100% of the SMS messages to the participants throughout the pilot testing. Finally, the system displayed a notice indicating that the text messages were successfully despatched, and the application was confirmed to be functional.