Mohamad Naufal Mohamad Saad

Detecting replicated nodes in Wireless Sensor Networks using random walks and network division

Wireless Sensor Networks are vulnerable to node replication attacks due to deployment in unattended environments and the lack of physical tamper-resistance. An adversary can easily capture and compromise sensor nodes and after replicating them, he inserts arbitrary number of replicas into the network to mount a wide variety of internal attacks. In this paper we propose a novel distributed solution (RAND) for the detection of node replication attack in static WSNs which combines random walks with network division and works in two phases. In the first phase called network configuration phase, the entire network is divided into different areas. In the second phase called replica detection phase, the clone is detected by following a claimer-reporter-witness framework and a random walk is employed within each area for the selection of witness nodes. Simulation results show that our scheme outperforms the existing witness node based strategies with moderate communication and memory overhead.

Scrutinising well-known countermeasures against clone node attack in mobile wireless sensor networks

Wireless Sensor Networks WSNs are often deployed in unattended environments where an adversary can easily physically capture and compromise sensor nodes. She then creates replicas of the compromised nodes instigating further attacks by spreading these replicas over the network, incurring serious damages to the network, so these replicas should be detected as early as possible. Most of the previous research efforts on detecting replica node attacks adopt static network models which are not suitable for mobile WSNs. In mobile WSN, sensor nodes are freely and randomly roaming all the time and they do not have any fixed neighbour to communicate with because these mobile nodes meet with one another occasionally and in an unpredictable manner. In this paper, we have surveyed all the existing solutions proposed so far for the detection of replica or clone nodes in mobile WSN by comparing them comprehensively and pointing out their drawbacks and shortcomings.

The Influences of Emotion on Learning and Memory

Emotion has a substantial influence on the cognitive processes in humans, including perception, attention, learning, memory, reasoning, and problem solving. Emotion has a particularly strong influence on attention, especially modulating the selectivity of attention as well as motivating action and behavior. This attentional and executive control is intimately linked to learning processes, as intrinsically limited attentional capacities are better focused on relevant information. Emotion also facilitates encoding and helps retrieval of information efficiently. However, the effects of emotion on learning and memory are not always univalent, as studies have reported that emotion either enhances or impairs learning and long-term memory (LTM) retention, depending on a range of factors. Recent neuroimaging findings have indicated that the amygdala and prefrontal cortex cooperate with the medial temporal lobe in an integrated manner that affords (i) the amygdala modulating memory consolidation; (ii) the prefrontal cortex mediating memory encoding and formation; and (iii) the hippocampus for successful learning and LTM retention. We also review the nested hierarchies of circular emotional control and cognitive regulation (bottom-up and top-down influences) within the brain to achieve optimal integration of emotional and cognitive processing. This review highlights a basic evolutionary approach to emotion to understand the effects of emotion on learning and memory and the functional roles played by various brain regions and their mutual interactions in relation to emotional processing. We also summarize the current state of knowledge on the impact of emotion on memory and map implications for educational settings. In addition to elucidating the memory-enhancing effects of emotion, neuroimaging findings extend our understanding of emotional influences on learning and memory processes; this knowledge may be useful for the design of effective educational curricula to provide a conducive learning environment for both traditional “live” learning in classrooms and “virtual” learning through online-based educational technologies.

Design and simulation of a high temperature MEMS micro-hotplate for application in trace gas detection

In this paper, we present the simulation results of a high temperature MEMS micro-hotplate. The electro-thermo-mechanical behaviors of micro- hotplates (MHP) have been simulated using CoventorWare. In the simulation, the effects of various thicknesses of the silicon nitride (Si3N4) membrane layer on the temperature, mechanical deflection and power consumption of the MHP are evaluated. The effect of the addition of a layer of silicon carbide (SiC) on the MHP temperature distribution is also investigated. Results show that as the thickness of the Si3N4 membrane is increased from 0.3 mum to 3 mum, the power consumption of the MHP increases from 7.1 mW to 34.3 mW while the displacement of the membrane remains constant at a value of about 5.8 mum. It is also demonstrated that when the MHP is designed with a silicon carbide (SiC) heat distributing layer above the silicon oxide (SiO2) insulating layer on top of the heater, the uniformity of the temperature on the MHP membrane is considerably improved as compared to a membrane without SiC.

Analysis and realization of defected ground structure (DGS) on bandpass filter

An end-coupled line bandpass filter (BPF) is proposed and designed by placing defected ground structure (DGS) in the ground plane. DGS is used for its property of miniaturizing the size of microwave filter and also improving the mutual coupling between the resonators. The proposed dumbbell shaped DGS is used to tune the bandpass filter to 2.4 GHz with dimension of 44 mm × 18 mm. A wide tuning range of 0.64 GHz is achieved by tuning the height, length and width dimension of DGS unit cell. This filter gives an insertion loss of -0.42 dB, a return loss of -12.31 dB and -3 dB bandwidth of 0.92 GHz. The effect of DGS structure parameters on the frequency of bandpass filter is discussed here. The discussion is concerned over the change in R, L and C parameters of the bandpass filter when defected ground structure is etched in its ground plane. The results conclude that the DGS brings a change in effective inductance and capacitance of a transmission line.

Design, simulation, modeling and characterization of micromachined microcantilever using coventorware software

Modeling and simulation of a microcantilever designed to achieve high resonant frequency on the sensing area is presented in this paper. Simple analytical models of the microcantilever are generated to achieve estimates of the device performance and to check the validity of the subsequent simulation. CoventorWare simulation software is used to design and process the micromachined microcantilever gas sensing platforms. Results indicate that with a periodic force of amplitude 0.05 N applied at the top of microcantilever, increasing its thickness from 1 µm to 5 µm increases the natural frequency from 10.203 KHz to 50.709 KHz. On the other hand an increase in the lengths of the microcantilever from 90 µm to 170 µm decreases its natural frequency from 30.437 KHz to 17.70 KHz, while increasing its widths from 60 µm to 140 µm increases its natural frequency from 23.854 KHz to 35.84 KHz. A comparison between simulation and mathematical model results for frequency showed close agreement.

Mitigation of stress: new treatment alternatives

Complaints of stress are common in modern life. Psychological stress is a major cause of lifestyle-related issues, contributing to poor quality of life. Chronic stress impedes brain function, causing impairment of many executive functions, including working memory, decision making and attentional control. The current study sought to describe newly developed stress mitigation techniques, and their influence on autonomic and endocrine functions. The literature search revealed that the most frequently studied technique for stress mitigation was biofeedback (BFB). However, evidence suggests that neurofeedback (NFB) and noninvasive brain stimulation (NIBS) could potentially provide appropriate approaches. We found that recent studies of BFB methods have typically used measures of heart rate variability, respiration and skin conductance. In contrast, studies of NFB methods have typically utilized neurocomputation techniques employing electroencephalography, functional magnetic resonance imaging and near infrared spectroscopy. NIBS studies have typically utilized transcranial direct current stimulation methods. Mitigation of stress is a challenging but important research target for improving quality of life.

Implementation of wireless sensor network in oil and gas specifically for personnel positioning application

The invention of WSN-based indoor positioning is to design effective personnel positioning system, monitor the personnel movement in oil and gas platform and alert the personnel if they entered a restricted area. Personnel tracking system in hazardous working environment such as in oil gas platform is very crucial due to GPS incapability inside a concrete building structure. Real-time monitoring of personnel health and condition is a top priority for immediate response in emergency situation. Communication device limitation in oil and gas platform will be hard for the supervisor to inform the personnel for an emergency evacuation. Personnel position application using WSN is determined based on RSSI values of multiple XBee multipoint RF modules consist of personnel node, fixed nodes and server node. A positioning algorithm will be used for the estimation of personnel location in the oil and gas platform. Sectioning method using XBee IEEE 802.15.4 as a WSN is proposed for personnel positioning application.

Design and characterization of embedded microheater on CMOS-MEMS resonator for application in mass-sensitive gas sensors

In utilizing CMOS-MEMS resonators as mass-sensitive platforms, a uniform temperature distribution on the membrane surface is critical. In this paper, a novel design of CMOS-MEMS resonator with embedded microheater to control the temperature over the sensing layer was successfully designed and characterized. The CMOS-MEMS resonator was fabricated using 0.35 μm CMOS and post-CMOS micromachining process. Temperature coefficient of resistance (TCR) of aluminum temperature sensor embedded in the membrane was determined by measurement of resistance variation as a function of temperature from 27°C and 150°C. The TCR of the temperature sensor is found to be 0.00386 and 0.00379 for measurements carried out while temperature is increasing and decreasing, respectively. The total resistance of the temperature sensor and the wire interconnects was theoretically determined to be 74.23 Ω and 94.82 Ω, respectively, making a total resistance of 169.05 Ω when measurements are made through the pads. On the other hand the measured resistance at 27°C is found to be 169.06 Ω which is in very good agreement with a difference of 0.006 %. The experimental results and analytical values of resistance of the temperature sensor as a function of temperatures shows a good agreement (1.07%). TCR of Al is found to 0.00382 with percentage difference of about 2.05 % from standard value (39 ×10-4 C-1).

Simulation and modeling the effect of temperature on resonant frequency of a CMOS-MEMS resonator

Simulation and modeling of the effect of temperature on resonant frequency of resonator that is maintained at high temperature (100 to 300°C) by a heater element using Coventor Ware software is presented in this paper. The principle of detection of the gaseous species is based on the change in resonant frequency of the microresonator due to change in mass induced by the adsorption of an analyte molecule onto the surface of the active material deposited on the microresonator. The theoretical resonant frequency is found to be 20.1 kHz. The frequency decreased from 20116.14 Hz to 19928.98 Hz with increasing temperature from 25°C to 300°C corresponding to a decrease in spring constant from 543.16 N/m to 533.1 N/m. The uniformity of the temperature distribution on the membrane area of the microresonator is also investigated and the temperature gradient is found to be 0.003°C/μm, which indicates a highly homogeneous temperature.