ترغب بنشر مسار تعليمي؟ اضغط هنا

Teaching Network Storage Technology Assessment Outcomes and Directions

34   0   0.0 ( 0 )
 نشر من قبل Timur Mirzoev
 تاريخ النشر 2014
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English




اسأل ChatGPT حول البحث

The paper presents academic content, delivery and assessment mechanisms used, available resources including initial lessons from teaching Networked Storage Technology as a special topics course to students enrolled in two specific programs - IT and CS. The course is based on the EMC s vendor-neutral Storage Technology Fundamentals course. Furthermore, this manuscript provides a detailed review of how the course fits into our curriculum, particularly, how it helps achieving the 2008 ABET assessment requirements.

قيم البحث

اقرأ أيضاً

The integration of renewable sources, communication and power networks with information and communication technologies is one of the main challenges in Smart Grids (SG) large-scale testing. For this reason, the coupling of simulators is commonly used to dynamically simulate several aspects of the SG infrastructure, in the so-called co-simulations. In this paper, we provide a scoping review of research of co-simulations in the context of Smart Grids: i) research areas and research problems addressed by co-simulations, ii) specific co-simulation aspects focus of research, iii) typical coupling of simulators in co-simulation studies. Based on the results, we discuss research directions of future SG co-simulation research in each of the identified areas.
In this paper, we propose a machine-learning assisted modeling framework in design-technology co-optimization (DTCO) flow. Neural network (NN) based surrogate model is used as an alternative of compact model of new devices without prior knowledge of device physics to predict device and circuit electrical characteristics. This modeling framework is demonstrated and verified in FinFET with high predicted accuracy in device and circuit level. Details about the data handling and prediction results are discussed. Moreover, same framework is applied to new mechanism device tunnel FET (TFET) to predict device and circuit characteristics. This work provides new modeling method for DTCO flow.
70 - Sudha Singh 2010
3G, processor of 2G services, is a family of standards for mobile telecommunications defined by the International Telecommunication Union [1]. 3G services include wide-area wireless voice telephone, video calls, and wireless data, all in a mobile env ironment. It allows simultaneous use of speech and data services and higher data rates.3G is defined to facilitate growth, increased bandwidth and support more diverse applications. The focus of this study is to examine the factors affecting the adoption of 3G services among Indian people. The study adopts the revised Technology Acceptance Model by adding five antecedents-perceived risks, cost of adoption, perceived service quality, subjective norms, and perceived lack of knowledge. Data have collected from more than 400 school/college/Institution students & employees of various Government/Private sectors using interviews & various convenience sampling procedures and analyzed using MS excel and MATLAB. Result shows that perceived usefulness has the most significant influence on attitude towards using 3G services, which is consistent with prior studies. Of the five antecedents, perceived risk and cost of adoption are found to be significantly influencing attitude towards use. The outcome of this study would be beneficial to private and public telecommunication organizations, various service providers, business community, banking services and people of India. Research findings and suggestions for future research are also discussed.
In this paper, we propose to model the energy consumption of smart grid households with energy storage systems as an intertemporal trading economy. Intertemporal trade refers to transaction of goods across time when an agent, at any time, is faced wi th the option of consuming or saving with the aim of using the savings in the future or spending the savings from the past. Smart homes define optimal consumption as either balancing/leveling consumption such that the utility company is presented with a uniform demand or as minimizing consumption costs by storing energy during off-peak time periods when prices are lower and use the stored energy during peak time periods when prices are higher. Due to the varying nature of energy requirements of household and market energy prices over different time periods in a day, households face a trade-off between consuming to meet their current energy requirements and/or storing energy for future consumption and/or spending energy stored in the past. These trade-offs or consumption preferences of the household are modeled as utility functions using consumer theory. We introduce two different utility functions, one for cost minimization and another for consumption balancing/leveling, that are maximized subject to respective budget, consumption, storage and savings constraints to solve for the optimum consumption profile. The optimization problem of a household with energy storage is formulated as a geometric program for consumption balancing/leveling, while cost minimization is formulated as a linear programming problem. Simulation results show that the proposed model achieves extremely low peak to average ratio in the consumption balancing/leveling scheme with about 8% reduction in consumption costs and the least possible amount for electricity bill with about 12% reduction in consumption costs in the cost minimization scheme.
A new multi-device wireless power transfer scheme that reduces the overall charging time is presented. The proposed scheme employs the intermediated energy storage (IES) circuit which consists of a constant power driving circuit and a super-capacitor . By utilizing the characteristic of high power density of the super-capacitor, the receiver can receive and store the energy in short duration and supply to the battery for long time. This enables the overlap of charging duration between all receivers. As a result, the overall charging time can be reduced.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا