Measuring The Impact of Social Media Marketing on Individuals

Three problems associated with the use of social media in marketing include: 1. The difficulty in tracking, managing, and analyzing the traffic that comes from different social media networks. Google Analytics is one of the data analytic tools that deals with traffic efficiently. It recognizes traffic sources and categorizes them to give the advertiser insights into oncoming traffic to the company’s website. It provides comprehensive statistics about traffic, which can be useful for advertisers to measure the performance of their marketing campaigns. 2. The inability to measure the success of marketing campaigns to increase sales. A/B Testing is a useful way to tell advertisers about the best methods to enhance their final results. It examines the functionalities of websites and advertising techniques during social marketing campaigns that lead to direct or indirect impacts, which can boost sales. 3. The lack of finding target audiences in social media. Social media’s API, such as Twitter Ads, provides many features that can generate new leads. It gives advertisers the ability to target social media users based on their demography, geography, behavior, and interest. In the business section, the paper covers the impact of social media influencers on their followers and how companies use those influencers within their marketing campaigns. This information can help businesses achieve their social media marketing goals by using these solutions and following measurable plans. Furthermore, the paper mentions some successful case studies that have used these solutions effectively

Simulation based optimization of joint maintenance and inventory for multi-components manufacturing systems

Maintenance and spare parts management are interrelated and the literature shows the significance of optimizing them jointly. Simulation is an efficient tool in modeling such a complex and stochastic problem. In this paper, we optimize preventive maintenance and spare provision policy under continuous review in a non-identical multi-component manufacturing system through a combined discrete event and continuous simulation model coupled with an optimization engine. The study shows that production dynamics and labor availability have a significant impact on maintenance performance. Optimization results of Simulated Annealing, Hill Climb and Random solutions are compared. The experiments show that Simulated annealing achieved the best results although the computation time was relatively high. Investigating multi-objective optimization might provide interesting results as well as more flexibility to the decision maker

CONSENSUS GII.4 VIRUS LIKE PARTICLES; A VACCINE CANDIDATE BIOPHYSICAL CHARACTERIZATION, STABILIZATION, AND ADJUVANTS BINDING STUDIES

The World Health Organization (WHO) and the United Nations Children's Fund (UNICEF) estimate globally that 1.9 million children under the age of five years old die annually as consequence of diarrhea. Increasing need for hospitalization, which has negative effects on health care sectors, in addition to mortality incidences mark diarrheal related diseases a growing burden on both health care sectors and the global economy. Introducing novel measures to control and avert the spread of diarrheal disease are of paramount importance. Diarrhea is the main symptom in Acute gastroenteritis (AGE) and according to the United States' National Outbreak Reporting System (NORS), viral agents are the dominant precursors of epidemic AGE outbreaks. More than 90% of humans' acute non-bacterial gastroenteritis breakouts worldwide is caused by Noroviruses (NoVs). NoVs of the Caliciviridae family are none enveloped, positive sense, single stranded RNA virus, noncultivable in cell culture, containing three open reading frames (ORF). Expressing NoVs ORF2 in a baculovirus expression system produces empty virus-like particles (VLPs). These VLPs are very similar to the native virus in terms of morphology and antigenicity, yet lacking the genetic material essential for infectivity, making the VLPs a superb candidate for vaccine development. By comparing the capsid sequence of three different NoVs GII.4 strains, consensus GII.4 VLPs were produced as a potential vaccine with the goal of providing a broader protection against AGE. The main objective of this study is to understand the structural behavior of NoVs Consensus GII.4 VLPs, which is to be used as a vaccine. A complement of biophysical techniques has been employed to characterize the physical stability of Noroviruses Consensus GII.4 virus-like particles (VLPs) as a function of temperature and pH. The VLPs' physical stability are characterized by different spectroscopic techniques and the resulting data are used to construct empirical phase diagrams (EPDs) projecting the entire data set in the form of a colored image. These EPDs are used in the development of excipient screening assays to identify potential stabilizers of the VLPs in solution. The identified stabilizers are then subjected to further screening using fluorescence analysis to determine their optimal concentrations and use in combination. The generated data are used to construct binding isotherms for Consensus GII.4 VLP and aluminum salt adjuvants (Alhydrogel® and Adjuphos®). Binding isotherms were also generated for Norwalk VLP (a previously studied vaccine candidate) and aluminum salt adjuvants. Front Face Fluorescence Spectroscopy is used to evaluate the structural changes associated with Consensus GII.4 and Norwalk VLPs when bound to aluminum salt adjuvants

Use of 0.7-in. Diameter Prestressing Strand in Bridge Girders: Bond Behavior and Girder Stability

In prestressed concrete bridge girders, the use of 0.7-in. diameter strand will allow 35% increase in prestressing force than 0.6-in. diameter strand and 92% increase than 0.5-in. diameter strand. This increase in prestressing force will theoretically permit longer span lengths, shallow girders or fewer girders across the width of a given bridge. AASHTO bridge design and construction specifications do not specify the use of 0.7-in. diameter strands for precast prestressed girders. Lack of data on the use, and particularly the bond behavior, of 0.7-in. diameter strand prevent its wide use in bridge construction. In this thesis the bond behavior of 0.7-in. diameter strand is evaluated. In addition to geometric and material characterization, five strands of each diameter (0.5, 0.6 and 0.7-in.) were tested to evaluate the Hoyer effect. Test results indicate that the dilation ratio of the strand exceeds that predicted by the Poison ratio alone. A parametric investigation using the finite element method was conducted to evaluate the effects of strand dilation over the expected transfer length of the strand. Single-strand models were used to illustrate the Hoyer effect and four-strands models to investigate the effect of strand spacing. Potential for local cracking resulting from the Hoyer effect is identified. Thirty beam-end specimens having straight and 90o hooked anchorages with different embedment lengths in different weight concretes were tested to evaluate the relative bond capacity of the strands. Test results indicate a predictable variation in bond behavior not attributed to the strand size. All tests exhibited shorter development lengths (i.e., better bond) than that prescribed in design. The potential benefits of hooked anchorage are identified in resisting high longitudinal tensile forces related to beam-end shear effects. With the potential for longer girders, stability is a concern during all the stages of girder construction and erection. A few previously designed girders that had been optimized for length are evaluated for stability following the PCI method. Analysis indicated that stability generally could be achieved. When necessary, increasing the width of the top flange since Iy/Ix has the pronounced effect on improving stability

Applications of simulation in maintenance research

The area of asset maintenance is becoming increasingly important as greater asset availability is demanded. This is evident in increasingly automated and more tightly integrated production systems as well as in service contracts where the provider is contracted to provide high levels of availability. Simulation techniques are able to model complex systems such as those involving maintenance and can be used to aid performance improvement. This paper examines engineering maintenance simulation research and applications in order to identify apparent research gaps. A systematic literature review was conducted in order to identify the gaps in maintenance systems simulation literature. Simulation has been applied to model different maintenance sub-systems (asset utilisation, asset failure, scheduling, staffing, inventory, etc.) but these are typically addressed in isolation and overall maintenance system behaviour is poorly addressed, especially outside of the manufacturing systems discipline. Assessing the effect of Condition Based Maintenance (CBM) on complex maintenance operations using Discrete Event Simulation (DES) is absent. This paper categorises the application of simulation in maintenance into eight categories

Using discrete event simulation to investigate engineering product service strategies

As companies develop business models based on service provision through engineering products the role of information becomes increasingly important to achieving high levels of service performance. One approach to achieving higher levels of service performance is to deploy sensing technology in the product to provide the service operation with diagnostic and prognostic information. Simulation modelling techniques are able to capture operational performance of complex systems involving product and information flows and are therefore appropriate to modelling such service provision. This paper documents work carried out in this area and demonstrates the application of simulation when providing a service through engineered products. It would seem logical that receiving increasing product performance information would enable higher levels of service performance to be achieved. The work here shows how performance can be captured and the circumstances in which diagnostic and prognostic information is beneficial as well as when it has little effect

Measuring The Impact of Social Media Marketing on Individuals

Three problems associated with the use of social media in marketing include: 1. The difficulty in tracking, managing, and analyzing the traffic that comes from different social media networks. Google Analytics is one of the data analytic tools that deals with traffic efficiently. It recognizes traffic sources and categorizes them to give the advertiser insights into oncoming traffic to the company’s website. It provides comprehensive statistics about traffic, which can be useful for advertisers to measure the performance of their marketing campaigns. 2. The inability to measure the success of marketing campaigns to increase sales. A/B Testing is a useful way to tell advertisers about the best methods to enhance their final results. It examines the functionalities of websites and advertising techniques during social marketing campaigns that lead to direct or indirect impacts, which can boost sales. 3. The lack of finding target audiences in social media. Social media’s API, such as Twitter Ads, provides many features that can generate new leads. It gives advertisers the ability to target social media users based on their demography, geography, behavior, and interest. In the business section, the paper covers the impact of social media influencers on their followers and how companies use those influencers within their marketing campaigns. This information can help businesses achieve their social media marketing goals by using these solutions and following measurable plans. Furthermore, the paper mentions some successful case studies that have used these solutions effectively

Understanding the effects of different levels of product monitoring on maintenance operations: A simulation approach

The move towards integrating products and services has increased significantly. As a result, some business models, such as Product Service Systems (PSS) have been developed. PSS emphasises the sale of use of the product rather than the sale of the product itself. In this case, product ownership lies with the manufacturers/suppliers. Customers will be provided with a capable and available product for their use. In PSS, manufacturers/suppliers are penalised for any down time of their product according to the PSS contract. This has formed a pressure on the service providers (maintenance teams) to assure the availability of their products in use. This pressure increases as the products are scattered in remote places (customer locations). Authors have urged that different product monitoring levels are applied to enable service providers to monitor their products remotely allowing maintenance to be performed accordingly. They claim that by adopting these monitoring levels, the product performance will increase. Their claim is based on reasoning, not on experimental/empirical methods. Therefore, further experimental research is required to observe the effect of such monitoring levels on complex maintenance operations systems as a whole which includes e.g. product location, different types of failure, labour and their skills and locations, travel times, spare part inventory, etc. In the literature, monitoring levels have been classified as Reactive, Diagnostics, and Prognostics. This research aims to better understand and evaluate the complex maintenance operations of a product in use with different levels of product monitoring strategies using a Discrete Event Simulation (DES) approach. A discussion of the suitability of DES over other techniques has been provided. DES has proven its suitability to give a better understanding of the product monitoring levels on the wider maintenance system. The requirements for simulating a complex maintenance operation have been identified and documented. Two approaches are applied to gather these generic requirements. The first is to identify those requirements of modelling complex maintenance operations in a literature review. This is followed by conducting interviews with academics and industrial practitioners to find out more requirements that were not captured in the literature. As a result, a generic conceptual model is assimilated. A simulation module is built through the Witness software package to represent different product monitoring levels (Reactive, Diagnostics, and Prognostics). These modules are then linked with resources (e.g. labour, tools, and spare parts). To ensure the ease of use and rapid build of such a complex maintenance system through these modules, an Excel interface is developed and named as Product Monitoring Levels Simulation (PMLS). The developed PMLS tool needed to be demonstrated and tested for tool validation purposes. Three industrial case studies are presented and different experimentations are carried out to better understand the effect of different product monitoring levels on the complex maintenance operations. Face to face validation with case companies is conducted followed by an expert validation workshop. This work presents a novel Discrete Event Simulation (DES) approach which is developed to support maintenance operations decision makers in selecting the appropriate product monitoring level for their particular operation. This unique approach provides numerical evidence and proved that the higher product monitoring level does not always guarantee higher product availability

Rapid modeling of field maintenance using discrete event simulation

Discrete event simulation has been applied to a wide range of applications areas due to its ability to represent stochastic systems over time. Maintenance, particularly field maintenance, is complex due to the interaction of different sub-systems of use, maintenance, repair and inventory and the conflicting demands of minimizing cost and maximizing availability. The area of simulation of maintenance systems receives little treatment in the literature and tends to focus on reliability modeling of individual assets. The work presented here documents research to fill this gap by specifying, creating and testing simulation functionality to rapidly model field maintenance systems