A review on CMOS delay lines with a focus on the most frequently used techniques for high-resolution delay step is presented. The primary types, specifications, delay circuits, and operating principles are presented. The delay circuits reported in this paper are used for delaying digital inputs and clock signals. The most common analog and digitally-controlled delay elements topologies are presented, focusing on the main delay-tuning strategies. IC variables, namely, process, supply voltage, temperature, and noise sources that affect delay resolution through timing jitter are discussed. The design specifications of these delay elements are also discussed and compared for the common delay line circuits. As a result, the main findings of this paper are highlighting and discussing the followings: the most efficient high-resolution delay line techniques, the trade-off challenge found between CMOS delay lines designed using either analog or digitally-controlled delay elements, the trade-off challenge between delay resolution and delay range and the proposed solutions for this challenge, and how CMOS technology scaling can affect the performance of CMOS delay lines. Moreover, the current trends and efforts used in order to generate output delayed signal with low jitter in the sub-picosecond range are presented.

Dielectrophoresis (DEP) is an electrode-medium process used to control the movement of Carbon nanotubes (CNTs) within a solution under nonuniform electric fields. CNTs are typically dispersed into a solvent to form a homogeneous suspension in order to prevent their aggregation and to improve solubility. This paper starts with a short review of the techniques used to improve the compatibility of CNTs with a target medium. Then, direct and indirect variations in CNTs’ velocities as a function of DEP force were investigated, under different dispersion mediums, for a rectangular electrode pair with a 10 μm gap subjected to a 500 kHz AC signal with an amplitude of 10 V. The effects of changes in permittivity, conductivity, viscosity, and density of the medium were presented and discussed. Simulation results from this study were used to further clarify the role of the medium on the motion of CNTs during alignment using a DEP process prior to an actual alignment.

The bagworm is a vicious leaf eating insect pest that threatens the oil palm plantations in Malaysia. The economic impact from defoliation of approximately 10% to 13% due to bagworm attack might cause about 33% to 40% yield loss over 2 years. Due to this, monitoring and detecting of bagworm populations in oil palm plantations is required as the preliminary steps to ensure proper planning of control actions in these areas. Hence, the development of an image processing algorithm for detection and counting of Metisa plana Walker, a species of Malaysia’s local bagworm, using image segmentation has been researched and completed. The color and shape features from the segmented images for real time object detection showed an average detection accuracy of 40% and 34%, at 30 cm and 50 cm camera distance, respectively. After some improvements on training dataset and marking detected bagworm with bounding box, a deep learning algorithm with Faster Regional Convolutional Neural Network (Faster R-CNN) algorithm was applied leading to the percentage of the detection accuracy increased up to 100% at a camera distance of 30 cm in close conditions. The proposed solution is also designed to distinguish between the living and dead larvae of the bagworms using motion detection which resulted in approximately 73–100% accuracy at a camera distance of 30 cm in the close conditions. Through false color analysis, distinct differences in the pixel count based on the slope was observed for dead and live pupae at 630 nm and 940 nm, with the slopes recorded at 0.38 and 0.28, respectively. The higher pixel count and slope correlated with the dead pupae while the lower pixel count and slope, represented the living pupae.

Particle manipulation is often required in the fabrication of microelectronic devices such as transistors and sensors. In this work, we succeeded in depositing aligned carbon nanotubes (CNTs) from an oxidized conglomerates carbon mixture using a simple low power procedure consisting of mild acid treatment and frequency-dependent dielectrophoretic (DEP) force. The treatment improved the dispersity and solubility of CNTs due to the functional groups introduced on their surface. The DEP force was generated with an AC signal of 1 MHz and 7.07 V_rms to attract the CNTs to a transparent electrode gap of 50 μm. Treatment quality was confirmed and characterized by Raman spectroscopy, Fourier-transform infrared spectroscopy (FTIR), energy dispersive x-ray analysis (EDX) and high-resolution transmission electron microscopy (HRTEM). Ultraviolet-visible spectroscopy (UV-vis) and dynamic light scattering (DLS) were used to analyze the dispersity and solubility of carbon particles and their size distribution in different solvents. The morphology of the deposited CNTs and amorphous carbon were observed by optical microscope and field-emission scanning electron microscope (FESEM). The procedure used in this work is cost-effective, scalable and essential for future assembly. Furthermore, the transparency of the system makes it suitable for real-time observation, transparent sensors, and the ability to integrate it into microfluidic channels.

This paper presents a new type of CMOS time-of-flight (TOF) range image sensor using single layer gates on field oxide structure for photo conversion and charge transfer. An additional process step to create an n-type buried layer is used. This simple structure allows the realization of a high resolution array with 15 times 15 mum² pixels in standard CMOS process. To minimize the influence of background light, the proposed pixel structure has charge draining gates. A small duty cycle optical pulse is also used for this purpose. The TOF sensor chip was successfully implemented and tested

Integrating a large number of embedded memories in System-on-Chips (SoC's) occupies up to more than 70% of the die size, thus requiring Built-In Self-Test (BIST) with the smallest possible area overhead. This paper analyzes MATS++(6N), March C-(10N), March SR(14N), and March CL(12N) test algorithms and shows that they cannot detect either Write Disturb Faults (WDFs) or Deceptive Read Destructive Faults (DRDFs) or both. Therefore to improve fault detection, an automation program is developed based on sequence operation (SQ) generation rules. However after solving the undetected fault, the outcome in term of its detection result of Static Double Cell Faults using the specified test algorithm especially Transition Coupling Faults (CFtrs), Write Destructive Coupling Faults (CFwds), Read Destructive Coupling Faults (CFrds) and Deceptive Read Destructive Faults (CFdrds) are observed.