Analysis of Stress Backlogs during Case-File Processing in Forensic Science Laboratory

Case-file backlogs were identified as one of the cause factors affecting the competitiveness of the forensic science laboratory (FSL). Backlogs represent case-files?that remain unprocessed or unreported within a selected time interval (year, week or month) which leads to increased customer complaints, rework, cost of analysis, degradation of biological samples, etc. Case-file backlogging was quantified in three consecutive years (2014 to 2016), using the following parameters: case-files received and case-files processed, difference of which gives case-files backlogged. There was a need to define time interval for a case-file to be regarded as backlogged (that is, one week), results of which can translate into backlogged case-files per month or year. A data collection tool was established and used for three work stations (forensic chemistry, biology/DNA and toxicology laboratories). The tool includes starting and ending date for each?time interval, in which the numbers of case-files received and processed were entered followed by computing the backlogs. It was observed that, case-files reported?increased between 2014 and 2016 leading to a decrease in backlogged case-files.?The annual percentage of the case-files backlogged was highest for forensic?toxicology. The highest number of case-files backlogged was observed for forensic?chemistry, followed by forensic biology/DNA. The number of case-files?backlogged per analyst per year was highest in 2014 and dropped continuously?towards 2016, being comparably higher in forensic biology/DNA and chemistry.?Probability density functions (PDFs) and cumulative distribution functions (CDFs)?of backlogs data indicated that a large number of backlogs created in previous?weeks were eliminated. It was concluded that the effect of case-file backlogging on FSL competitiveness can be minimized by continued management effort in backlog elimination.

A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics--A Supply Chain Backlog Elimination Framework

The diversity of data sources resulted in seeking effective manipulation and dissemination.The challenge that arises from the increasing dimensionality has a negative effect on the computation performance,efficiency,and stability of computing.One of the most successful optimization algorithms is Particle Swarm Optimization(PSO)which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search task.This research proposes an effective enhancement of PSO that tackles the challenge of randomness search which directly enhances PSO performance.On the other hand,this research proposes a generic intelligent framework for early prediction of orders delay and eliminate orders backlogs which could be considered as an efficient potential solution for raising the supply chain performance.The proposed adapted algorithm has been applied to a supply chain dataset which minimized the features set from twenty-one features to ten significant features.To confirm the proposed algorithm results,the updated data has been examined by eight of the well-known classification algorithms which reached a minimum accuracy percentage equal to 94.3%for random forest and a maximum of 99.0 for Naïve Bayes.Moreover,the proposed algorithm adaptation has been compared with other proposed adaptations of PSO from the literature over different datasets.The proposed PSO adaptation reached a higher accuracy compared with the literature ranging from 97.8 to 99.36 which also proved the advancement of the current research.

Metropolitan Housing Development in Urban Fringe Areas-A Case Study of Three Metropolitan Cities of South Africa: Johannesburg, Ekurhuleni and Tshwane

Purpose:The metropolitan cities of Johannesburg,Ekurhuleni and Tshwane play an important role in the economy of the Gauteng province in South Africa.The region constitutes to 22.4 percent of the total population of South Africa and has a strong presence and contributes in areas of manufacturing sector,financial and business services,retail and wholesale trade,etc.The rapid urban population,increase in the informal settlements and socio-economic opportunities has resulted in considerable urban sprawl in and around the urban fringe areas of these metropolitan cities.The urban fringe areas of these metros often come under the influence of rapid urbanization process and pressures.Coupled with the economical and potential land dynamics and lack of priority of spatial development guidelines,these areas attract rapid and haphazard development from communities and developers.Research Design/Methodology:This research is based on a qualitative approach through a comprehensive literature review that included content analysis of key documents on housing sector such as IDPs(Integrated Development Plans),Municipal Annual Reports,Growth Development Strategies,and among other sectoral documents on housing sector.Some of the key priority issues considered in the housing sector included:eradication of housing backlogs,spatial restructuring of housing,provision of choice in terms of location,tenure and housing typology.Findings:The current paper discusses the approaches of metropolitan housing development processes in three metropolitan cities of South Africa from Gauteng region,namely:Johannesburg,Ekurhuleni and Tshwane.The paper discusses the existing housing sectoral scenario along with the fringe areas in three cities with focus on:formal and informal settlements,housing segregation and the backlogs,current institutional arrangements,role of public private participation,and scope for alternate mechanisms.The paper concludes in discussion on sustainable development options for housing development in urban fringe areas.

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fully backlogged. Fuzzy optimal solution is obtained by considering hexagonal fuzzy numbers and for defuzzification Graded Mean Integration Representation Method. A numerical example is provided for the illustration of crisp and fuzzy, both models. To observe the effect of changes in parameters, sensitivity analysis is carried out.

一种SYN-Flooding攻击的防范对策

针对SYN Flooding攻击的特点,分析了常用的几种防御SYN Flooding攻击的方法,指出其防御方法的不足,提出一种FIFO淘汰防御方法,进行了攻击 防御实验,取得较好效果.

异地分布式多SCRUM项目产品Backlog分解过程影响因素分析

将异地分布和SCRUM方法相结合,分析产品Backlog分解过程,提出分解过程的几种重要影响因素:优先级设置、团队地理位置、任务稳定性、团队间差异、任务工作量估算。采用问卷调查的方法收集数据,然后用SPSS软件进行数据分析,研究各因素对产品Backlog分解过程的影响。研究结果表明,优先级和任务的稳定性以及工作量估算对产品Backlog分解过程有显著影响,而团队的地理位置和团队差异则没有显著影响。研究结果有助于SCRUM开发团队更好地完成产品Backlog的工作。

A Note on an Economic Lot-sizing Problem with Perishable Inventory and Economies of Scale Costs:Approximation Solutions and Worst Case Analysis

This paper presents an economic lot-sizing problem with perishable inventory and general economies of scale cost functions. For the case with backlogging allowed, a mathematical model is formulated, and several properties of the optimal solutions are explored. With the help of these optimality properties, a polynomial time approximation algorithm is developed by a new method. The new method adopts a shift technique to obtain a feasible solution of subproblem and takes the optimal solution of the subproblem as an approximation solution of our problem. The worst case performance for the approximation algorithm is proven to be （4√2 ＋ 5）/7. Finally, an instance illustrates that the bound is tight.

高效制定并使用Scrum开发的产品Backlog

Scrum开发过程框架中,产品Backlog是产品所要具备的所有功能的总纲,是Scrum过程的核心。产品Backlog就类似于传统顺序开发模型中的需求分析,但它不需要完全的确定和细化产品的需求,也不用形成完整使用说明,它用的是另一种恰到好处的方式。本文从三个方面讨论如何高效制定并使用产品Backlog,并举一个考务系统的Scrum开发实例进行深入说明,希望可以为刚转型Scrum的传统开发团队提供参考。

Exploiting Virtual Elasticity of Production Systems for Respecting OTD-Part 1: Post-Optimality Conditions for Ergodic Order Arrivals in Fixed Capacity Regimes

Respecting the on-time-delivery (OTD) for manufacturing orders is mandatory. This depends, however, on the probability distribution of incoming order rate. The case of non-equal distribution, such as aggregated arrivals, may compromise the observance of on-time supplies for some orders. The purpose of this paper is to evaluate the conditions of post-optimality for stochastic order rate governed production systems in order to observe OTD. Instead of a heuristic or a simulative exploration, a Cartesian-based approach is applied to developing the necessary and sufficient mathematical condition to solve the problem statement. The research result demonstrates that increasing speed of throughput reveals a latent capacity, which allows arrival orders above capacity limits to be backlog-buffered and rescheduled for OTD, exploiting the virtual manufacturing elasticity inherent to all production systems to increase OTD reliability of non JIT-based production systems.

高效制定并使用Scrum开发的产品Backlog

Scrum开发过程框架中,产品Backlog是产品所要具备的所有功能的总纲,是Scrum过程的核心。产品Backlog就类似于传统顺序开发模型中的需求分析,但它不需要完全的确定和细化产品的需求,也不用形成完整使用说明,它用的是另一种恰到好处的方式。本文从三个方面讨论如何高效制定并使用产品Backlog,并举一个考务系统的Scrum开发实例进行深入说明,希望可以为刚转型Scrum的传统开发团队提供参考。

An Inventory Model for Items with Two Parameter Weibull Distribution Deterioration and Backlogging

In this paper an inventory model is developed with time dependent power pattern demand and shortages due to deterioration and demand. The deterioration is assumed to follow a two parameter Weibull distribution. Three different cases with complete, partial, no backlogging are considered. The optimal analytical solution of the model is derived. Suitable numerical example has been discussed to understand the problem. Further sensitivity analysis of the decision variables has been done to examine the effect of changes in the values of the parameters on the optimal inventory policy.

Maintenance Capacity Planning: Determination of Maintenance Workforce

Determining the size of maintenance workforce is an essential element of maintenance planning. It is important for performing maintenance programs perfectly. However, it is a complex and challenging problem since it involves the consideration of several important factors. The mathematical model developed in this paper aims at finding out the optimal size of the maintenance workforce taking into account all of the important factors that affect this size. It is based on determining the needed number of workers with different skill levels and from different sources to meet maintenance workload of different grades that is to be performed in a specified planning horizon with minimum cost acquired.

POLYNOMIAL DYNAMIC PROGRAMMING ALGORITHMS FOR LOT SIZING MODELS WITH BOUNDED INVENTORY AND STOCKOUT AND/OR BACKLOGGING

This paper addresses a dynamic lot sizing problem with bounded inventory and stockout where both no backlogging and backlogging allowed cases are considered. The stockout option means that there is outsourcing in a period only when the inventory level at that period is non-positive. The production capacity is unlimited and production cost functions are linear but with fixed charges. The problem is that of satisfying all demands in the planning horizon at minimal total cost. We show that the no backlogging case can be solved in O（T^2） time with general concave inventory holding and outsourcing cost functions where T is the length of the planning horizon. The complexity can be reduced to O（T） when the inventory holding cost functions are also linear and have some realistic properties, even if the outsourcing cost functions remain general concave functions. When the inventory holding and outsourcing cost functions are linear, the backlogging case can be solved in O（ T^3 logT） time whether the outsourcing level at each period is bounded by the sum of the demand of that period and backlogging level from previous periods, or only by the demand of that period.

An EPQ model with variable production,probabilistic deterioration and partial backlogging under inflation

This paper develops an economic production quantity(EPQ)model under the effect of inflation and time value of money.The rate of replenishment is considered to be a variable and the generalized unit production cost function is formulated by incorporating several factors,such as raw material,labour,replenishment rate,advertisements and other factors of the manufacturing system.The selling price of a unit is determined by a mark-up over the production cost.We have considered three types of continuous probabilistic deterioration function,and also considered that the holding cost of the item per unit time is assumed to be an increasing linear function of time spent in storage.In addition,shortages are allowed and partially backlogged.This model aids in minimizing the total inventory cost by finding the optimal cycle length and the optimal production quantity.The optimal solution of the model is illustrated with the help of numerical examples.

Two-warehouse inventory model with non-instantaneously deteriorating items,stock-dependent demand,shortages and inflation

In this paper,a two-warehouse economic order quantity(EOQ)model for noninstantaneously deteriorating items with stock-dependent demand under the effects of inflation and the time value of money is presented.Also in this model,shortages are allowed and partially backlogged.The backlogging rate is dependent on the waiting time for the next replenishment.The objective of this model is to minimize the total inventory cost of the retailer by finding the optimal intervals and the optimal order quantity.An algorithm is designed to find the optimum solution of the proposed model.Numerical examples are given to demonstrate the results.Sensitivity analysis of the model with respect to several system parameters has been carried out and some managerial inferences are obtained.

Pricing and inventory decisions for non-instantaneous deteriorating items with price and promotional effort stochastic demand

This study investigates an inventory model for a non-instantaneous deteriorating item with partial backlogging wherein the demand is stochastic in nature and depends on price and promotional effort whereas the deterioration rate is time proportional.Under these settings,a mathematical model is developed with the objective to maximise the expected profit per unit time by determining the optimal price and the length of replenishment cycle.Some useful theoretical results are established to deduce the optimal replenishment schedule.An effective algorithmic procedure is developed to find the optimal solutions to the proposed model.The applicability of the proposed model is illustrated by numerical example.Sensitivity analysis of the optimal solution with respect to key parameters has been carried out and the implications are discussed.The study indicates that though promotional effort stimulates the market demand,it is beneficial in an economic sense when it applies in a conservative manner.

Multi-item EOQ model for fresh fruits with preservation technology investment,time-varying holding cost,variable deterioration and shortages

In a fruit wholesale shop,a fruiterer needs to maintain huge inventory of different ranges of fruit items for customers because of uncertainty in consumer preferences and behaviour.But demand of them may differ and different EOQ models for each item are required for optimal level of EOQ.This paper presents a single inventory model to assimilate these varieties.It is assumed that many fruit items bear constant rate of deterioration,some are with time proportional deterioration and some do not deteriorate.To control deterioration of the units in inventory,the advanced preservation technology is considered.The proposed single inventory model of this paper incorporates composite and heterogeneous features of multiple items and presents analysis for obtaining optimal level for output model parameters.

Analysis and optimization of an EOQ inventory model with promotional efforts and back ordering under delay in payments

In this paper,economic order quantity(EOQ)inventory model is considered subject to promotional efforts.We adopt a demand function which is dependent on sales teams’initiatives in which shortages are allowed which are completely backlogged under the condition of permissible delay in payments with timedependent holding cost.The main objective of this paper is to determine the optimal replenishment schedule and optimal order quantity to maximize the total profit.Expressions for various optimal indices are provided.First,we prove that a unique optimal replenishment schedule exists.Second,we present an effective iterative algorithm to obtain the optimal solution.Furthermore,we establish some useful theorems to characterize the optimal solution to determine the values of replenishment schedule and optimal order quantity.Third,we prove that the total profit is a concave function via differential calculus and present numerical examples using SCILAB 5.5.0 to illustrate the model.Finally,we extend the numerical example by performing a sensitivity analysis of the model parameters and discuss managerial insights.This study suggests to the management of firms to determine the optimal order quantity,optimal inventory cycle length and sales teams’initiatives/promotional effort in order to achieve their maximum profits.

Two-warehouse inventory model for non-instantaneous deteriorating items with optimal credit period and partial backlogging under inflation

This paper analyses an inventory model for non-instantaneous deteriorating items under a two-warehouse system with the effect of inflation and time value of money.We propose the model from the seller’s prospective by incorporating the fact that granting the trade credit from the seller to its buyer not only increases sales and revenue but also opportunity cost and default risk.Moreover,in this model,shortages are allowed and partially backlogged.The backlogging rate is dependent on the waiting time for the next replenishment.The purpose of this study is to determine the optimal credit period and the optimal order quantity such that the total profit of the seller is maximised.Some numerical examples are presented for illustrating the proposed inventory model.Furthermore,sensitivity analysis of the optimal solutions with respect to major parameters is carried out and some managerial inferences are obtained.

Demand and deterioration of items per unit time inventory models with shortages using genetic algorithm

Inventory management is a crucial task for any industry.In this paper,we have determined the optimum profit and economical order quantity under variety of assumptions such as the demand per unit time follows either a log-normal or a generalized exponential distribution.Parametric relationship between these two distributions,the proposed models become comparable.For modeling,we consider the expected demand and variable deterioration.Under these probabilistic assumptions,inventory models are developed for situations like no,complete and partial backlogging.Classical methods are unable to solve these situations under these assumptions.Thus genetic algorithm is proposed to solve these models.Economic order quantity is obtained for maximizing the total profit for the respective demand per unit time distributions.A real-world case study of a deteriorated product is presented to illustrate the procedures of the proposed inventory models.