Enabling machine understandable exchange of energy consumption information in intelligent domotic environments

In the 21st century, all the major countries around the world are coming together to reduce the impact of energy generation and consumption on the global environment. Energy conservation and its efficient usage has become a top agenda on the desks of many governments. In the last decade, the drive to make homes automated and to deliver a better assisted living picked pace and the research into home automation systems accelerated, usually based on a centralized residential gateway. However most devised solutions fail to provide users with information about power consumption of different house appliances. The ability to collect power consumption information can lead us to have a more energy efficient society. The goal addressed in this paper is to enable residential gateways to provide the energy consumption information, in a machine understandable format, to support third party applications and services. To reach this goal, we propose a Semantic Energy Information Publishing Framework. The proposed framework publishes, for different appliances in the house, their power consumption information and other properties, in a machine understandable format. Appliance properties are exposed according to the existing semantic modeling supported by residential gateways, while instantaneous power consumption is modeled through a new modular Energy Profile ontology.     

Dominant Mechanisms for Metal Removal from Acidic Aqueous Solutions by Cement Kiln Dust

Copper and zinc ions were removed from synthetic acidic aqueous solutions onto cement kiln dust (CKD) particles in a single component system. The objectives of this study were to: distinguish between adsorption and precipitation when both mechanisms are occurring simultaneously; define their individual contributions; and consequently, specify the dominant mechanism. This was achieved by conducting a new experimental procedure for the precipitation phase that depended on CKD leachate in combination with a derivation of a simultaneous adsorption-precipitation equation. High removal efficiencies, approaching 100?%, of the Cu and Zn ions, were attained. Precipitation was the dominant mechanism for removing low concentrations of these metals, while adsorption appears to be more significant in removal of high metal concentrations.     

The Double Edge Sword Based Distributed Executor Service

Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload. Consequently, the performance of software-intensive system is suffered. Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword. On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs. And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS. We evaluated the results of the proposed system against state of the art DTPSs by a client-server based simulator and found that our system outperformed by sustaining smaller response times.     

Delay and link utilization aware routing protocol for wireless multimedia sensor networks

Wireless Multimedia Sensor Networks (WMSNs) consist of networks of interconnected devices involved in retrieving multimedia content, such as, video, audio, acoustic, and scalar data, from the environment. The goal of these networks is optimized delivery of multimedia content based on quality of service (QoS) parameters, such as delay, jitter and distortion. In multimedia communications each packet has strict playout deadlines, thus late arriving packets and lost packets are treated equally. It is a challenging task to guarantee soft delay deadlines along with energy minimization, in resource constrained, high data rate WMSNs. Conventional layered approach does not provide optimal solution for guaranteeing soft delay deadlines due to the large amount of overhead involved at each layer. Cross layer approach is fast gaining popularity, due to its ability to exploit the interdependence between different layers, to guarantee QoS constraints like latency, distortion, reliability, throughput and error rate. The paper presents a channel utilization and delay aware routing (CUDAR) protocol for WMSNs. This protocol is based on a cross-layer approach, which provides soft end-to-end delay guarantees along with efficient utilization of resources. Extensive simulation analysis of CUDAR shows that it provides better delay guarantees than existing protocols and consequently reduces jitter and distortion in WMSN communication.     

A semi-Markovian model for low-cycle elastic-plastic fatigue crack growth

Elastic-plastic fatigue crack growth is described by a continuous time semi-Markovian stochastic process. The load on the member is considered to be deterministic and the resistance is assumed to be random. Crack growth resistance is described by an equation employing the J-integral. Quantities of interest that can be obtained from this model include emergency statistics and probability distributions on the time to reach a critical crack length. The model is tested with fatigue crack propagation data for A533B pressure vessel steel. The results indicate that the model underpredicts the mean first-passage time at the start of a test but predicts it well in the mid-ranges and towards the end of the test; the variance of the process is better predicted for specimens that undergo large plasticity than those with low plasticity.     

THE EFFECTS OF STRESS RATIO, COMPRESSIVE PEAK STRESS AND MAXIMUM STRESS LEVEL ON FATIGUE BEHAVIOUR OF 2024-T3 ALUMINIUM ALLOY

Abstract— Fatigue crack growth behaviour of 2024-T3 aluminium alloy is investigated as a function of stress ratio, compressive peak stress and maximum stress level. It is found that as the stress ratio and the magnitude of the compressive peak stress are increased, the threshold stress intensity range decreased linearly. Intermediate and near threshold growth rate data are analysed with different formulae for effective stress intensity range. The data covered different values of stress ratio, compressive peak stress and maximum stress level. A formula for the crack opening stress level is introduced as a function of stress ratio, compressive peak stress and maximum stress level. The formula permitted a good correlation between crack growth data for both positive stress ratio and negative compressive peak stress values. Using the new formula, intermediate and near threshold crack growth data for the 2024-T3 aluminium alloy yielded a unique crack growth rate vs effective stress intensity range curve for all stress ratio and compressive peak stress values investigated. This suggests that for the 2024-T3 aluminium alloy the crack growth rate vs effective stress intensity range curve does not depend on stress ratio, compressive peak stress, or maximum stress level. The significance of the new equation and the crack growth rate versus effective stress intensity range curve is that they allow a designer to find crack growth rate vs stress intensity range data for the 2024-T3 aluminium alloy in both intermediate and near threshold regions for the particular stress ratio, compressive peak stress and maximum stress level conditions of the component under investigation.     

Translating the impact of knowledge management into knowledge‐based innovation: The neglected and mediating role of knowledge‐worker satisfaction

The purpose of knowledge management is innovation. However, this study proposes that the existence of knowledge management in the knowledge‐worker's work environment can nurture the overall satisfaction of knowledge worker. As the ultimate purpose of knowledge management is innovation performance, therefore, the satisfaction of knowledge worker as an outcome of knowledge management should be greater innovation performance. Consequently, the purpose of this study is to test the mediating role of satisfaction of knowledge worker between knowledge management and innovation. The study collected the data from 306 knowledge workers (engineers and managers) of software houses from Pakistan. The SmartPLS 3 Version 2.7 software that uses the PLS‐SEM (Partial Least Square‐Structural Equation Modelling) technique was used. The results indicate that satisfaction of knowledge worker mediates between two knowledge management processes (knowledge creation and knowledge sharing) and innovation significantly. However, it does not mediate between knowledge utilization and innovation significantly.     

CDCSS: cluster-based distributed cooperative spectrum sensing model against primary user emulation (PUE) cyber attacks

In cognitive radio network, the secondary users (SUs) use the spectrum of primary users for communication which arises the security issues. The status of SUs as legitimate users is compulsory for the stability of the system. This paper addresses the issue of delay caused by a band-selection decision process that directly affects the security and performance. The model cluster-based distributed cooperative spectrum sensing is proposed. In this model, cluster heads (CHs) exchange control information with other CHs and ordinary nodes. This model significantly reduced the delay, sensing, convergence, routing, in band-selection process. This also reduces the energy consumption while sensing the spectrum which seriously leads to performance upgradation. The simulated results show the improved performance of cognitive radio networks in terms of delay, packet loss ratio and bandwidth usage as compared to cluster-based cooperative spectrum sensing model. The opportunity for primary user emulation attacker is minimized as the overall delay is reduced.