Modeling and control for a Gough‐Stewart platform CNC machine

In this paper, a complete dynamic model on task space for a 6 degrees of freedom (DOF) Gough‐Stewart platform‐type computer numerical control (CNC) machine is derived. The rotation terms of the legs are included for those inertia effects cannot be negligible in the machine tool applications. The formulation derived by means of the Euler‐Lagrange method is convenient for designing the adaptive control law. Also, the average‐type force model for end milling process is derived and included in the dynamic model and control. A composite adaptive control scheme is developed by use of filtering dynamics technique. An appropriate estimator gain is designed in the parameter adaptation law that is useful for estimating the selected important cutting parameters. Experimental results verify the proposed adaptive control scheme can achieve good tracking performance. © 2004 Wiley Periodicals, Inc.     

A hybrid rough-cut process planning for quality

This paper proposes a hybrid approach to develop a rough-cut process planning for quality. The approach aims to determine key process alternatives with an adequate process capability by systematic quality planning and assessment methods during the initial planning stage of the product development cycle. It consists of four steps: (1) identification of quality characteristics (2) planning of the process quality by combining quality function deployment (QFD) with the process failure mode and effect analysis (FMEA) (3) a selection of process alternatives, and (4) an assessment of process quality through a quality measure index, called the composite process capability (CCP). The process alternatives with an adequate CCP selected during the early design stage can then be not only used as the guidelines for detailed process planning but also as feedback for the product design and other functions for design evaluation and improvement. This approach is helpful to reduce or even eliminate the iterations of modification of process plans. A prototype system called the rough-cut process planning for quality (RPPFQ) has been developed for validation. A case study concerned with a satellite frame part is presented to illustrate the approach and prototype system in this paper.     

A new parametric control method for freeform mesh models

Parametric modeling technology is difficult to apply to freeform mesh models since there is no efficient way to impose geometric constraints. In this paper, we propose a novel method to control freeform mesh models parametrically. Our approach is to construct a control mesh that surrounds an object model and then impose constraints on it. The control mesh is parametrically controlled and the shape of the object model is modified by using an existing freeform deformation method. This paper is mainly concerned with automated construction of a control mesh and treatment of geometric constraints. Procedures for creating a control mesh are as follows: 1) determine the optimal orientation of the model, 2) project the model along three axes and extract contours, 3) create 2D control polygons for the contours, and 4) construct the 3D control mesh from the 2D control polygons. Geometric constraints are imposed on the edges and faces of a control mesh. Types of constraints are given by either a relative relationship between elements or an absolute displacement. A new control mesh is calculated by solving these constraints and the original model is modified accordingly. We tested our algorithms for two freeform models.     

MicroRNAs as Potential Biomarkers in the Differential Diagnosis of Lipomatous Tumors and Their Mimics

Adipocytic tumors are the most common subtype of soft tissue tumors. In current clinical practice, distinguishing benign lipomas from well-differentiated liposarcomas (WDLPS), as well as dedifferentiated liposarcomas (DDLPS) from their morphologic mimics, remains a significant diagnostic challenge. This is especially so when examining small biopsy samples and without the aid of additional ancillary tests. Recognizing the important role that microRNAs (miRNAs) play in tumorigenesis and their potential utility in tumor classification, we analyzed routine clinical tissue samples of benign and malignant lipomatous tumors, as well as other sarcoma mimics, to identify distinguishing miRNA-based signatures that can aid in the differential diagnosis of these entities. We discovered a 6-miRNA signature that separated lipomas from WDLPS with high confidence (AUC of 0.963), as well as a separate 6-miRNA signature that distinguished DDLPS from their more aggressive histologic mimics (AUC of 0.740). Functional enrichment analysis unveiled possible mechanistic involvement of these predictive miRNAs in adipocytic cancer-related biological processes and pathways such as PI3K/AKT/mTOR and MAPK signaling, further supporting the relevance of these miRNAs as biomarkers for adipocytic tumors. Our results demonstrate that miRNA expression profiling may potentially be used as an adjunctive tool for the diagnosis of benign and malignant adipocytic tumors. Further validation studies are warranted.     

Evolution of RFIC Handset PAs

The first official shift in communication systems from fixed-location devices to portable/mobile devices happened in 1973 when Martin Cooper, general manager of Motorola's Communications Systems Division at the time, placed the first mobile call from a New York street using AT&T's network. Four years later, the first cell phone was made in Chicago with free trials offered to more than 2,000 people. The first commercial handset to receive FCC approval was Motorola's DynaTAC in 1983 [1], which was made available to the public a year later. This 1.13 kg (2.5 lb) phone that cost consumers US$3,500 was only able to achieve approximately 35 minutes of talk time and took almost 15 years to develop with the cost totaling US$100 million.     

Transition‐Metal Dichalcogenide NiTe2: An Ambient‐Stable Material for Catalysis and Nanoelectronics

By means of theory and experiments, the application capability of nickel ditelluride (NiTe₂) transition‐metal dichalcogenide in catalysis and nanoelectronics is assessed. The Te surface termination forms a TeO₂ skin in an oxygen environment. In ambient atmosphere, passivation is achieved in less than 30 min with the TeO₂ skin having a thickness of about 7 Å. NiTe₂ shows outstanding tolerance to CO exposure and stability in water environment, with subsequent good performance in both hydrogen and oxygen evolution reactions. NiTe₂‐based devices consistently demonstrate superb ambient stability over a timescale as long as one month. Specifically, NiTe₂ has been implemented in a device that exhibits both superior performance and environmental stability at frequencies above 40 GHz, with possible applications as a receiver beyond the cutoff frequency of a nanotransistor.     

Conception of Stretchable Resistive Memory Devices Based on Nanostructure‐Controlled Carbohydrate‐block‐Polyisoprene Block Copolymers

It is discovered that the memory‐type behaviors of novel carbohydrate‐block ‐polyisoprene (MH‐b ‐PI) block copolymers‐based devices, including write‐once‐read‐many‐times, Flash, and dynamic‐random‐access‐memory, can be easily controlled by the self‐assembly nanostructures (vertical cylinder, horizontal cylinder, and order‐packed sphere), in which the MH and PI blocks, respectively, provide the charge‐trapping and stretchable function. With increasing the flexible PI block length, the stretchability of the designed copolymers can be significantly improved up to 100% without forming cracks. Thus, intrinsically stretchable resistive memory devices (polydimethylsiloxane(PDMS)/carbon nanotubes(CNTs)/MH‐b ‐PI thin film/Al) using the MH‐b ‐PI thin film as an active layer is successfully fabricated and that using the MH‐b ‐PI_12.6k under 100% strain exhibits an excellent ON/OFF current ratio of over 10⁶ (reading at ?1 V) with stable V _set around ?2 V. Furthermore, the endurance characteristics can be maintained over 500 cycles upon 40% strain. This work establishes and represents a novel avenue for the design of green carbohydrate‐derived and stretchable memory materials.     

Nested-Ring Mach–Zehnder Interferometer in Silicon-on-Insulator

For the first time, a nested-ring Mach-Zehnder interferometer (MZI) on silicon-on-insulator is realized using a complementary metal-oxide-semiconductor-based process. In this letter, we verify that the device operates in two modes: the inner-loop resonance dominant mode due to strong build-up inside the inner-ring, and the double-Fano resonances mode due to strong light interaction with the outer loop. The results show that the inner-loop resonance is highly sensitive to the MZI arm imbalance compared to the double-Fano resonance mode. Based on these considerations, we obtain a good fit between theory and experiment.     

Minimizing broadcast latency and redundancy in asynchronous wireless sensor networks

Asynchronous duty cycle Medium Access Control (MAC) protocols do not require global synchronization because nodes determine their wake-up schedule independently. As a result, these MACs have superior performance to those that employ synchronous duty-cycles in terms of energy expenditure, and advantageously, they are simple to implement. A key limitation is that they do not support efficient broadcast. A node needs to transmit a broadcast packet multiple times via unicast because only a subset of its neighbors may be awake at any given point in time. To address this problem, this paper proposes a centralized and distributed asynchronous broadcast algorithm that achieves minimal broadcast latency and redundancy. In addition, it uses a novel asynchronous MAC protocol that ensures all neighbors of a broadcasting node are awake to receive a broadcast. The performance of our algorithms is evaluated under different network configurations. We show via extensive simulation studies that our algorithms have near optimal network performance in terms of broadcast latency. In particular, compared to OTAB, the best broadcast scheduling algorithm to date, the broadcast latency and transmission times achieved by our designs are 1/5 and 1/2 that of OTAB, respectively.     

Selection of network and learning parameters for an adaptive neural robotic control scheme

This paper presents the results of a study in the design of a neural network based adaptive robotic control scheme. The neural network used here is a two hidden layer feedforward network and the learning scheme is the well-known backpropagation algorithm. The neural network essentially provides the inverse of the plant and acts in conjunction with a standard PD controller in the feedback loop. The objective of the controller is to accurately control the end position of a single link manipulator in the presence of large payload variations, variations in the link length and also variations in the damping constant. Based on results of this study, guidelines are presented in selecting the number of neurons in the hidden layers and also the parameters for the learning scheme used for training the network. Results also indicate that increasing the number of neurons in the hidden layer will improve the convergence speed of learning scheme up to a certain limit beyond which the addition of neurons will cause oscillations and instability. Guidelines for selecting the proper learning rate, momentum and fast backpropagation constant that ensure stability and convergence are presented. Also, a relationship between the r.m.s. error and the number of iterations used in training the neural network is established.