On Boosting Integrated WLAN & ZigBee Network Performance via Load Balancing

Network traffic and overload are constantly increasing. This situation leads to congestion and packet losses at bottlenecks and across the different parts and devices of the network. Luckily, network technologies and techniques are developing rapidly. This paper is dedicated to applying and testing the impact of load balancing mechanisms on network performance. Two networking scenarios are considered: server on-premise and server on cloud . The research takes place in a vast scale network where two of the most popular technologies are spotted in an integrated multiprotocol scenario of Wireless Area networks (WLAN) with the Internet of Things (IoT) ZigBee. Previous studies were concerned by the challenges present due to the very different natures of IoT ZigBee and WLAN networks. This paper presents a better quality of service (QoS) by applying load balancing to these integrated scenarios. Not just that, it also introduces an even better Qos by deploying the rapidly growing popular technology of cloud computing to the same scenario of integrated networks with load balancing. By applying the same data rates with the same timers and networking parameters, network performance is measured and compared to show the difference between previous work without load balancing, and this papers work after deploying load balancing. The research shows whether load balancing has a positive or a negative effect on network performance or does not affect some cases. The network performance parameters under consideration are traffic dropped; traffic received, delay and throughput. Load balancing is tested regarding two different server positions

Prototyping Design and Optimization of Smart Electric Vehicles/Stations System using ANN

This paper demonstrates an experimental attempt to prototype electric vehicle charging station’s (EVCS) decision-making unit, using artificial neural network (ANN) algorithm. The algorithm acts to minimize the queuing delay in the station, with respect to the vehicle state of charge (SOC), and the expected arrival time. A simplified circuit model has been used to prototype the proposed algorithm, to minimize the overall queuing delay. Herein, the worst-case scenario is considered by having number of electric vehicles arriving to the station at the same time greater than the charging points available in the station side. Accordingly, the optimization technique was applied to reduce the mean charging time of the vehicles and minimize queuing delay. Results showed that this model can help in reducing the queuing delay by around 20% of the mean charging time of the station, while referring to a bare model without ANN algorithm as a reference

Smart green charging scheme of centralized electric vehicle stations

This paper presses a smart charging decision-making criterion that significantly contributes in enhancing the scheduling of the electric vehicles (EVs) during the charging process. The proposed criterion aims to optimize the charging time, select the charging methodology either DC constant current constant voltage (DC-CCCV) or DC multi-stage constant currents (DC-MSCC), maximize the charging capacity as well as minimize the queuing delay per EV, especially during peak hours. The decision-making algorithms have been developed by utilizing metaheuristic algorithms including the Genetic Algorithm (GA) and Water Cycle Optimization Algorithm (WCOA). The utility of the proposed models has been investigated while considering the Mixed Integer Linear Programming (MILP) as a benchmark. Furthermore, the proposed models are seeded using the Monte Carlo simulation technique by estimating the EVs arriving density to the EVS across the day. WCOA has shown an overall reduction of 13% and 8.5% in the total charging time while referring to MILP and GA respectively

Expression of muscle anabolic and metabolic factors in mechanically loaded MLO-Y4 osteocytes

Lack of physical activity results in muscle atrophy and bone loss, which can be counteracted by mechanical loading. Similar molecular signaling pathways are involved in the adaptation of muscle and bone mass to mechanical loading. Whether anabolic and metabolic factors regulating muscle mass, i.e., insulin-like growth factor-I isoforms (IGF-I Ea), mechano growth factor (MGF), myostatin, vascular endothelial growth factor (VEGF), or hepatocyte growth factor (HGF), are also produced by osteocytes in bone in response to mechanical loading is largely unknown. Therefore, we investigated whether mechanical loading by pulsating fluid flow (PFF) modulates the mRNA and/or protein levels of muscle anabolic and metabolic factors in MLO-Y4 osteocytes. Unloaded MLO-Y4 osteocytes expressed mRNA of VEGF, HGF, IGF-I Ea, and MGF, but not myostatin. PFF increased mRNA levels of IGF-I Ea (2.1-fold) and MGF (2.0-fold) at a peak shear stress rate of 44Pa/s, but not at 22Pa/s. PFF at 22 Pa/s increased VEGF mRNA levels (1.8- to 2.5-fold) and VEGF protein release (2.0- to 2.9-fold). Inhibition of nitric oxide production decreased (2.0-fold) PFF-induced VEGF protein release. PFF at 22 Pa/s decreased HGF mRNA levels (1.5-fold) but increased HGF protein release (2.3-fold). PFF-induced HGF protein release was nitric oxide dependent. Our data show that mechanically loaded MLO-Y4 osteocytes differentially express anabolic and metabolic factors involved in the adaptive response of muscle to mechanical loading (i.e., IGF-I Ea, MGF, VEGF, and HGF). Similarly to muscle fibers, mechanical loading enhanced expression levels of these growth factors in MLO-Y4 osteocytes. Although in MLO-Y4 osteocytes expression levels of IGF-I Ea and MGF of myostatin were very low or absent, it is known that the activity of osteoblasts and osteoclasts is strongly affected by them. The abundant expression levels of these factors in muscle cells, in combination with low expression in MLO-Y4 osteocytes, provide a possibility that growth factors expressed in muscle could affect signaling in bone cells

Functional body composition and related aspects in research on obesity and cachexia: report on the 12th Stock Conference held on 6 and 7 September 2013 in Hamburg, Germany

The 12th Stock Conference addressed body composition and related functions in two extreme situations, obesity and cancer cachexia. The concept of ‘functional body composition’ integrates body components into regulatory systems relating the mass of organs and tissues to corresponding in vivo functions and metabolic processes. This concept adds to an understanding of organ/tissue mass and function in the context of metabolic adaptations to weight change and disease. During weight gain and loss, there are associated changes in individual body components while the relationships between organ and tissue mass are fixed. Thus an understanding of body weight regulation involves an examination of the relationships between organs and tissues rather than individual organ and tissue masses only. The between organ/tissue mass relationships are associated with and explained by crosstalks between organs and tissues mediated by cytokines, hormones and metabolites that are coupled with changes in body weight, composition and function as observed in obesity and cancer cachexia. In addition to established roles in intermediary metabolism, cell function and inflammation, organ-tissue crosstalk mediators are determinants of body composition and its change with weight gain and loss. The 12th Stock Conference supported Michael Stocks' concept of gaining new insights by integrating research ideas from obesity and cancer cachexia. The conference presentations provide an in-depth understanding of body composition and metabolism

New minimally invasive surgical approach for excision of left atrial myxoma

A novel minimally invasive technique for left atrial myxoma surgery involving a combination of mini-sternotomy and restricted left atrial dome incision is described. Surgery is performed through a mini-J sternotomy at third intercostal space and a standard aorto-right atrial cannulation. Exposure of cardiac mass is obtained by a restricted incision of the left atrial dome which provides excellent view of the entire interatrial septum. Base of the tumor base is clearly visualized making the en-bloc excision extremely easy. Three cases were successfully treated with this technique and discharged with mild analgesic requirements. The limited invasiveness and the avoidance of wide incisions in the heart chambers are points of strength of this approach and allow to overcome the limitations of the currently used interatrial groove or transeptal approaches, as scarce visualization of the septum and site of tumor attachment and risk of conduction disturbances or traumatic injury to the mass