Search results

The purpose of this paper through the redundant monitoring unit reflecting the real-time temperature change of the array, an adaptive refresh circuit based on temperature is designed.

This paper proposed a circuit design for temperature-adaptive refresh with a fixed refresh frequency of traditional memory, high refresh power consumption at low temperature and low refresh frequency at high temperature.

Adding a metal oxide semiconductor (MOS) redundancy monitoring unit consistent with the storage unit to the storage bank can monitor the temperature change of the storage bank in real time, so that temperature-based memory adaptive refresh can be implemented.

According to the characteristics that the data holding time of dynamic random access memory storage unit decreases with the increase of temperature, a MOS redundant monitoring unit which is consistent with the storage unit is added to the storage array with the 2T storage unit as the core.

This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.

The authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.

All the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.

The results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.

A storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.

Previous research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.

Due to the importance of quality to customers, this study considers criteria of quality and profit and optimizes both in a multi-echelon cold chain of perishable agricultural products whose quality immediately begins to deteriorate after harvest. The two objectives of the proposed cold chain are to maximize profit and quality. Since postharvest quality loss in the supply chain depends on various decisions and factors, in addition to strategic decisions, the authors consider the temperature setting in refrigerated facilities and transportation vehicles due to the unfixed shelf life of the products which is related to the temperature found by Arrhenius formula.

The authors use bi-objective mixed-integer nonlinear programming to design a four-echelon supply chain. The authors integrate the supply chain echelons to detect the sources and factors of quality loss. The four echelons include supply, processing, storage and customer. The decisions, including facility location, assigning nodes of each echelon to corresponding nodes from the adjacent echelon, allocation of vehicles to transport the products from farms to wholesalers, processing selection, and temperature setting in refrigerated facilities, are made in an integrated way. Model verification and validation in the case study are done based on three perishable herbal plants.

The model obtains a 29% profit against a total cost of 71 and 93% of original quality of the crops is maintained, indicating a 7% quality loss. The final quality of 93% is the result of making a US$6m investment in the supply chain, including the procurement of high-quality raw materials; facility establishment; high-speed, high-capacity vehicles; location assignment; processing selection and refrigeration equipment in the storage and transportation systems, helping to maximize both the final quality of the products and the total profit.

The proposed supply chain model should help managers with modeling decisions, especially when it comes to cold chains for agricultural products. The model yields these results – optimal location-allocation decisions for the facilities to minimize distances between the network nodes, which save time and maintain the majority of the products’ original quality; choosing the most appropriate processing method, which reduces the perishability rate; providing high-capacity, high-speed vehicles in the logistics system, which minimizes transportation costs and maximizes the quality; and setting the right temperature in the refrigerated facilities, which mitigates the postharvest decay reaction rate of the products.

Comparison of the results of the present research with those of the traditional chain (obtained through experts) shows that since the designed chain increases the profit as well as the final quality, it has benefits for the main chain stakeholders, which are customers of agricultural products. This study model is expected to have a positive impact on the environment by placing strong emphasis on quality and preventing excessive waste generation and air pollution by imposing a financial penalty on extra demand production.

Since profit and quality of the final product are two important factors in all cultures and communities, the proposed supply chain model can be used in any food industry around the world. Applying the proposed model induces growth in local industries and promotes the culture of prioritizing quality in societies.

To the best of the authors’ knowledge, this is the first research on a bi-objective four-echelon (supply, processing, storage and customer) postharvest supply chain for agricultural products including that integrates transportation logistics and considers the deterioration rate of products as a time-dependent variable at different levels of decision-making.

The primary objective of this article is to examine current procurement, inventory control and management practices in modern healthcare, with a particular focus on the procurement and management of surgical supplies in a prominent public, highly specialized healthcare sector.

This study was conducted in three phases. In Phase 1, the study team interacted with various hospital management stakeholders, including the surgical hospital store, examined the current procurement process and identified challenges. Phase 2 focused on selecting items for a detailed study and collected the qualitative and quantitative details of the store department of the healthcare sector chosen. A detailed study analyzed revenue, output/demand, inventory levels, etc. In Phase 3, a decision-making framework is proposed, and inventory control systems are redesigned and demonstrated for the selected items.

It was observed that the demand for many surgical items had increased significantly over the years due to an increase in disposable/disposable items, while inventories fluctuated widely. Maximum inventory levels varied between 50 and 75%. Storage and availability were important issues for the hospital. It is assumed the hospital adopts the proposed inventory control system. In this case, the benefits can be a saving of 62% of the maximum inventory, 20% of the average stock in the system and optimal use of storage space, improving the performance and productivity of the hospital.

This study can help the healthcare sector administration to develop better systems for the procurement and delivery of common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels, and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.

This study can help the healthcare sector administration develop better systems for procuring and delivering common surgical items and efficient resource allocation. It can help provide adequate training to store staff. This study can help improve management/procurement policies, ordering and delivery systems, better service levels and inventory control of items in the hospital business context. This study can serve as a pilot study to further investigate the overall hospital operations.

This study is an early attempt to develop a decision framework and inventory control system from the perspective of healthcare inventory management. The gaps identified in real hospital scenarios are investigated, and theoretically based-inventory management strategies are applied and proposed.

Construction material management is an important process in supporting construction operations that affect project performance. Previous studies attempt to identify factors influencing material management in different stages such as procurement, transportation and utilization. However, they lack a model to explain the relationship between influential factors and the effectiveness of material management. Therefore, this study aims to validate the variables and key factors influencing the effectiveness of material management processes.

A total of 42 variables were reviewed from literature in different stages of material management process. Survey questionnaires were used to collect data about participants' perceptions on these variables. The respondents were 200 project engineers and project managers from construction sites and offices in Vietnam. Then factor analysis techniques were undertaken to validate the structure of factor groups. Two methods of exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were, respectively, performed to evaluate and verify the model's fit.

Factors influencing the effectiveness of material management were grouped into nine main factors, which are procurement issues, site conditions, planning and handling on site, industrial environments, contractual issues, quality control, suppliers and manufacturers' issues, transportation in and out site and security on site.

The paper has several implications for theory and methodology related to material management. It features influential factors in association with the material management effectiveness. Therefore, senior managers can more fully understand the errors in their works and propose timely solutions to limit the unwanted risks.

This research contributes on theoretical development on factors influencing effectiveness of material management processes. The key findings on influential factors can be applied to measure the effectiveness of material management processes.

Globally, consumer’s inclination towards functional foods had noticed due to their greater health consciousness coupled with enhanced health-care cost. The fact that probiotics could promote a healthier gut microbiome led projection of probiotic foods as functional foods and had emerged as an important dietary strategy for improved human health. It had established that ice cream was a better carrier for probiotics than fermented milked due to greater stability of probiotics in ice cream matrix. Global demand for ice cream boomed and probiotic ice cream could have been one of the most demanded functional foods. The purpose of this paper was to review the technological aspects and factors affecting probiotic viability and to standardize methodology to produce functional probiotic ice cream.

Attempt was made to search the literature (review and researched papers) to identify diverse factors affecting the probiotic viability and major technological challenge faced during formulation of probiotic ice cream. Keywords used for data searched included dairy-based functional foods, ice cream variants, probiotic ice cream, factors affecting probiotic viability and health benefits of probiotic ice cream.

Retention of probiotic viability at a level of >10⁶ cfu/ml is a prerequisite for functional probiotic ice creams. Functional probiotic ice cream could have been produced with the modification of basic mix and modulating technological parameters during processing and freezing. Functionality can be further enhanced with the inclusion of certain nutraceutical components such as prebiotics, antioxidant, phenolic compounds and dietary fibres. Based upon reviewed literature, suggested method for the manufacture of functional probiotic ice cream involved freezing of a probiotic ice cream mix obtained by blending 10% probiotic fermented milk with 90% non-fermented plain ice cream mix for higher probiotic viability. Probiotic ice cream with functional features, comparable with traditional ice cream in terms of technological and sensory properties could be produced and can crop up as a novel functional food.

Probiotic ice cream with functional features may attract food manufacturers to cater health-conscious consumers.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

This study aims to investigate the feasibility of proposed microgrid (MG) that comprises photovoltaic, wind turbines, battery energy storage and diesel generator to supply a residential building in Grindelwald which is chosen as the test location.

Three operational configurations were used to run the proposed MG. In the first configuration, the electric energy can be vended and procured utterly between the main-grid and MG. In the second configuration, the energy trade was performed within 15 kWh as the maximum allowable limit of energy to purchase and sell. In the third configuration, the system performance in the stand-alone operation mode was investigated. A whale optimization technique is used to determine the optimal size of MG in all proposed configurations. The cost of energy (COE) and other measures are used to evaluate the system performance.

The obtained results revealed that the first configuration is the most beneficial with COE of 0.253$/KWh and reliable 100%. Furthermore, the whale optimization algorithm is sufficiently feasible as compared to other techniques to apply in the applications of MG.

The value of the proposed research is to investigate to what extend the integration between MG and main-grid is beneficial economically and technically. As opposed to previous research studies that have focused predominantly only on the optimal size of MG.

The study examined the personal information management (PIM) challenges encountered by faculty in six universities in Ghana, their information refinding experiences and the perceived role of memory. The study tested the hypothesis that faculty PIM performance will significantly differ when the differences in the influence of personal factors (age, gender and rank) on their memory are considered.

The study was guided by a sample survey design. A questionnaire designed based on themes extracted from earlier interviews was used to collect quantitative data from 235 faculty members from six universities in Ghana. Data analysis was undertaken with a discrete multivariate Generalized Linear Model to investigate how memory intermediates in the relationship between age, gender and rank, and, refinding of stored information.

The paper identified two subfunctions of refinding (Refinding 1 and Refinding 2) associated with self-confidence in information re-finding, and, memory (Memory 1 and Memory 2), associated with the use of complimentary frames to locate previously found and stored information. There were no significant multivariate effects for gender as a stand-alone variable. Males who were aged less than 39 could refind stored information irrespective of the memory class. Older faculty aged 40–49 who possess Memory 1 and senior lecturers who possess Memory 2 performed well in refinding information. There was a statistically significant effect of age and memory; and rank and memory.

This study was limited to faculty in Ghana, whereas the study itself has implications for demographic differences in PIM.

Identifying how memory mediates the role of personal factors in faculty refinding of stored information will be necessary for the efforts to understand and design systems and technologies for enhancing faculty capacity to find/refind stored information.

Understanding how human memory can be augmented by technology is a great PIM strategy, but understanding how human memory and personal factors interplay to affect PIM is more important.

PIM of faculty has been extensively examined in the literature, and limitations of memory has always been identified as a constraint. Human memory has been augmented with technology, although the outcome has been very minimal. This study shows that in addition to technology augmentation, personal factors interplay with human memory to affect PIM. Discrete multivariate Generalized Linear Model applied in this study is an innovative way of addressing the challenges of assimilating statistical methodologies in psychosocial disciplines.

This study aims to investigate the influence of commercially available resins in water-based magenta pigment inkjet ink formulations on the properties of ink printability and the characteristics of ink application in food packaging. The impact of the resin on the jettability of the existing printability phase diagrams was also assessed.

Inks with different resin loadings were tested for selected properties, such as viscosity, particle size and surface tension. Stability was determined using a Turbiscan AGS turbidimeter and LumiFuge photocentrifuge analyzer. The ink layer fastness against abrasion and foodstuffs was evaluated using an Ugra device and according to PN-EN 646, respectively. JetXpert was used to assess Ricoh printhead jetting performance.

Printability diagrams successfully characterized the jettability of polyurethane inkjet inks on a multi-nozzle printhead and the binder improved droplet formation and printing precision.

Magenta water-based inkjet inks with commercial resins have been developed for printing on paper substrates. To the best of the authors’ knowledge, for the first time, inkjet ink stability was evaluated using the Turbiscan AGS and LumiFuge analyzers, and jettability models were verified using an industrial multi-nozzle printhead.