Optimization of black oxide coating thickness as an adhesion promoter for copper substrate in plastic integrated-circuit packages

Copper-oxide coating applied onto the copper substrate has emerged as an alternative to metallic coatings to improve adhesion with polymeric adhesives and molding compounds. The interfacial-bond strengths between the black oxide-coated Cu substrate and epoxy-based, glob-top resin were measured in button-shear tests, and the failure mechanisms were identified from the fracture-surface examination. The emphasis was to establish the correlation between the coating thickness, the surface roughness, and the interfacial adhesion with respect to treatment time. It was found that at the initial stage of treatment a thin layer of flat, cuprous oxide developed, above which fibrillar-cupric oxide was formed with further treatment until saturation with densified fibrils at about 150 sec. The interfacial-bond strength between the oxide-coated copper substrate and glob-top resin increased gradually with increasing treatment time, until the bond strength reached a plateau constant after a treatment for about 150 sec. There was a functional similarity between the oxide thickness, the surface roughness, and the interface-bond strength with respect to treatment time. A treatment time of 150 sec is considered an optimal condition that can impart the highest interface adhesion.     

An energy-aware distributed clustering protocol in wireless sensor networks using fuzzy logic

Clustering is an effective approach for organizing a network into a connected hierarchy, load balancing, and prolonging the network lifetime. On the other hand, fuzzy logic is capable of wisely blending different parameters. This paper proposes an energy-aware distributed dynamic clustering protocol (ECPF) which applies three techniques: (1) non-probabilistic cluster head (CH) elections, (2) fuzzy logic, and (3) on demand clustering. The remaining energy of the nodes is the primary parameter for electing tentative CHs via a non-probabilistic fashion. A non-probabilistic CH election is implemented by introducing a delay inversely proportional to the residual energy of each node. Therefore, tentative CHs are selected based on their remaining energy. In addition, fuzzy logic is employed to evaluate the fitness (cost) of a node in order to choose a final CH from the set of neighboring tentative CHs. On the other hand, every regular (non CH) node elects to connect to the CH with the least fuzzy cost in its neighborhood. Besides, in ECPF, CH elections are performed sporadically (in contrast to performing it every round). Simulation results demonstrate that our approach performs better than well known protocols (LEACH, HEED, and CHEF) in terms of extending network lifetime and saving energy.     

IoTScal‐H : Hybrid monitoring solution based on cloud computing for autonomic middleware‐level scalability management within IoT systems and different SLA traffic requirements

Wireless sensor network (WSN) technologies have enabled ubiquitous sensing to intersect many areas of modern day living. The creation of these devices offers the ability to get, gather, exchange, and consume environmental measurement from the physical world in a communicating‐actuating network, called the Internet of Things (IoT). As the number of physical world objects from heterogeneous network environments grows, the data produced by these objects raise uncontrollably, bringing a delicate challenge into scalability management in the IoT networks. Cloud computing is a much more mature technology, offering unlimited virtual capabilities in terms of storage capacity and processing power. Ostensibly, it seems that cloud computing and IoT are evolving independently on their own paths, but in reality, the integration of clouds with IoT will lead to deal with the inability to scale automatically depending on the overload caused by the drastic growth of the number of connected devices and/or by the huge amount of exchanged data in the IoT networks. In this paper, our objective is to promote the scalability management, using hybrid mechanism that will combine traffic‐oriented mechanism and resources‐oriented mechanism, with adaption actions. By the use of autonomic middleware within IoT systems, we seek to improve the monitoring components's architectural design, based on cloud computing‐oriented scalability solution. The intention is to maximize the number of satisfied requests, while maintaining at an acceptable QoS level of the system performances (RTT of the system, RAM, and CPU of the middleware). In order to evaluate our solution performance, we have performed different scenarios testbed experiments. Generally, our proposed results are better than those mentioned as reference.     

Effect of Power Amplifier Nonlinearity on the Physical Layer Security of MIMO Systems

Wireless Personal Communications - This paper presents an analytical investigation on the effect of nonlinear high-power amplifiers on the physical layer security of multiple-input-multiple-output...     

Schedule-Based Cooperative Multi-agent Reinforcement Learning for Multi-channel Communication in Wireless Sensor Networks

Wireless sensor networks (WSNs) have become an important component in the Internet of things (IoT) field. In WSNs, multi-channel protocols have been developed to overcome some limitations related to the throughput and delivery rate which have become necessary for many IoT applications that require sufficient bandwidth to transmit a large amount of data. However, the requirement of frequent negotiation for channel assignment in distributed multi-channel protocols incurs an extra-large communication overhead which results in a reduction of the network lifetime. To deal with this requirement in an energy-efficient way is a challenging task. Hence, the Reinforcement Learning (RL) approach for channel assignment is used to overcome this problem. Nevertheless, the use of the RL approach requires a number of iterations to obtain the best solution which in turn creates a communication overhead and time-wasting. In this paper, a Self-schedule based Cooperative multi-agent Reinforcement Learning for Channel Assignment (SCRL CA) approach is proposed to improve the network lifetime and performance. The proposal addresses both regular traffic scheduling and assignment of the available orthogonal channels in an energy-efficient way. We solve the cooperation between the RL agents problem by using the self-schedule method to accelerate the RL iterations, reduce the communication overhead and balance the energy consumption in the route selection process. Therefore, two algorithms are proposed, the first one is for the Static channel assignment (SSCRL CA) while the second one is for the Dynamic channel assignment (DSCRL CA). The results of extensive simulation experiments show the effectiveness of our approach in improving the network lifetime and performance through the two algorithms.

     

Improved Turbo Decoding Using Soft Combining Principle

One great challenge in wireless communication systems is to ensure reliable communications. Turbo codes are known by their interesting capabilities to deal with transmission errors. In this paper, we present a novel turbo decoding scheme based on soft combining principle. Our method improves decoding performance using soft combining technique inside the turbo decoder. Working on Max-Log-Maximum a Posteriori (Max-Log-MAP) turbo decoding algorithm and using an Additive White Gaussian Noise (AWGN) channel model and 16 Quadrature Amplitude Modulation (16QAM), simulation results show that the suggested solution is efficient and outperforms the conventional Max-Log-MAP algorithm in terms of Bit Error Rate (BER). The performance analysis is carried out in terms of BER by varying parameters such as the Energy per bit to Noise power spectral density ratio ( \(\text {E}_{\text {b}}/\text {N}_{\text {o}}\) ), and decoding iterations number. We call our proposed solution Soft Combined Turbo Codes.     

A review of routing strategies for optical burst switched networks

The exact contribution of this paper is a review of existing state‐of‐the‐art routing strategies for optical burst switched networks developed by researchers to deal with burst contention before it happens. Routing schemes are implemented in space domain, which make them simple and cost effective. Additionally, the paper points out the importance of routing as an effective way to deal with burst contention compared to other solutions. It also underlines the main differences between contention avoidance schemes and contention resolution techniques for optical burst switched networks. We believe that this review will help different optical burst switched researchers involved in the development of route optimization algorithms to control burst contention. Copyright © 2011 John Wiley & Sons, Ltd.     

Antenna subset selection at multi‐antenna relay with adaptive modulation

In this paper, we proposed several antenna selection schemes for cooperative diversity systems with adaptive transmission. The proposed schemes were based on dual‐hop relaying where a relay with multiple‐antenna capabilities at reception and transmission is deployed between the source and the destination nodes. We analyzed the performance of the proposed schemes by quantifying the average spectral efficiency and the outage probability. We also investigated the trade‐off of performance and complexity by comparing the average number of active antennas, path estimations, and signal‐to‐noise ratio comparisons of the different proposed schemes. Copyright © 2011 John Wiley & Sons, Ltd.     

Electrochemical degradation of petroleum hydrocarbons (PAHS) from synthetic aqueous solutions

Water separated from crude oil and wastewater discharge from petroleum oil refineries contains significant quantity of dissolved hydrocarbons. Polycyclic aromatic hydrocarbons (PAHs) are major toxicants in wastewater of refineries. It is difficult to treat wastewater containing PAHs due to their recalcitrant property and low solubility. Conventional techniques for the treatment of wastewater are still a concern of toxicity. Electrochemical oxidation process has been found to be a favorable for treating wastewater. Electrodes with high stability and electrocatalytic activity are important factors for a successful electrochemical oxidation of toxic organics in wastewater. In this study titanium anodes were coated with tin, antimony and iridium oxide mixture from their respective salts by thermal decomposition method. FESEM and XRD used for surface characterization of Ti/SnO₂–Sb₂O₅–IrO₂ anode. Quantification of PAHs was done using GC–MS. Results confirm the presence of respective oxides on anode surface. Their electrocatalytic capability was tested for degradation of 16 priority PAHs in aqueous solution. Results reveal the complete degradation of naphthalene, acenaphthylene, acenaphthene and fluorene without using NaCl electrolyte. While in the presence of NaCl naphthalene, acenaphthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene and pyrene were completely removed. About 98% of total PAHs removal was found at all initial pH values 3, 6, and 9 in the presence of electrolyte. Current study will be helpful in improving quality of petroleum industry wastewater containing PAHs.     

3D seismic and formation micro-imager (FMI) integrated study to delineate depositional pattern of Abu Madi (Upper Miocene) clastic reservoir rocks in El-Wastani gas field,onshore Nile Delta,Egypt

Ten wells (EW-4, EW-5, EW-6, EW-7, EW-8, EW-9, EW-10, EW-12, EW-13 and EW-15) were interpreted using the composite well logs, data of core analysis, gamma-ray logs, formation micro-imager logs (FMI), and 3D seismic data in SEGY format to understand the stratigraphy of the onshore, Nile Delta, Egypt.The amplitude analysis of 3-D seismic horizon slice of Lower Abu Madi rock unit together with the lithostratigraphic correlation through the study area depending on the gamma-ray log “HSGR” (left to right increasing), and the identification of type of bed geometry, nature of bed contacts, type of the sedimentary structures and the dominant formative paleocurrents by using some available borehole micro-resistivity images (FMI) and core photos. All of these techniques are used together to define the different depositional facies and depositional environment of the Messinian clastics (Lower Abu Madi rock unit), which is considered to be the main reservoir in the El-Wastani gas field, onshore Nile Delta, Egypt.The present study of depositional pattern of the Upper Miocene clastics reservoir (Lower Abu Madi rock unit) revealed that it is represented by high sinuous meandering channels or paleo-valley and three types of fluvial facies were defined; channel fill, channel margin, and floodplain basin.