Motorola (South Korea)

We review error resilience techniques for real-time video transport over unreliable networks. Topics covered include an introduction to today's protocol and network environments and their characteristics, encoder error resilience tools, decoder error concealment techniques, as well as techniques that require cooperation between encoder, decoder, and the network. We provide a review of general principles of these techniques as well as specific implementations adopted by the H.263 and MPEG-4 video coding standards. The majority of the article is devoted to the techniques developed for block-based hybrid coders using motion-compensated prediction and transform coding. A separate section covers error resilience techniques for shape coding in MPEG-4.

Traditionally, reliability assessment of new devices has been based on accelerated life tests. This approach is not practical for highly reliable devices, such as lasers, which are not likely to fail in experiments of reasonable length. An alternative approach is to monitor the devices for a period of time and assess their reliability from the changes in performance (degradation) observed during the experiment. In this article, we propose a methodology for designing experiments for degradation processes in which the amount of degradation over time levels off toward a plateau (maximum degradation) that is a function of stress. We provide (a) the stress levels for the experiment, (b) the proportion of devices to test at each stress level, (c) the times at which to measure the devices, and (d) the total number of devices to test. We apply the proposed methodology to an actual example.

An essential characteristic of large-scale software development is parallel development by teams of developers. How this parallel development is structured and supported has a profound effect on both the quality and timeliness of the product. We conduct an observational case study in which we collect and analyze the change and configuration management history of a legacy system to delineate the boundaries of, and to understand the nature of, the problems encountered in parallel development. The results of our studies are (1) that the degree of parallelism is very highhigher than considered by tool builders; (2) there are multiple levels of parallelism, and the data for some important aspects are uniform and consistent for all levels; (3) the tails of the distributions are long, indicating the tail, rather than the mean, must receive serious attention in providing solutions for these problems; and (4) there is a significant correlation between the degree of parallel work on a given component and the number of quality problems it has. Thus, the results of this study are important both for tool builders and for process and project engineers.

This practical, one-stop guide will quickly bring you up to speed on LTE and LTE-Advanced. With everything you need to know about the theory and technology behind the standards, this is a must-have for engineers and managers in the wireless industry. • First book of its kind describing technologies and system performance of LTE-A • Covers the evolution of digital wireless technology, basics of LTE and LTE-A, design of downlink and uplink channels, multi-antenna techniques and heterogeneous networks • Analyzes performance benefits over competing technologies, including WiMAX and 802.16m • Reflects the latest LTE Release-10 standards • Includes numerous examples, including extensive system and link results • Unique approach is accessible to technical and non-technical readers alike

Summary Knowing the location of sweet spots benefits the horizontal well drilling and the selection of perforation clusters. Generally, geoscientists determine sweet spots from the well-logging interpretation. In this paper, a group of prevalent classifiers [extreme gradient boosting (XGBoost), unbiased boosting with categorical features (CatBoost), and light gradient boosting machine (LightGBM)] based on gradient-boosting decision trees (GBDTs) are introduced to automatically determine sweet spots based on well-log data sets. Compared with linear support vector machines (SVMs), these robust algorithms can deal with comparative scales of features and learn nonlinear decision boundaries. Moreover, they are less influenced by the presence of outliers. Another prevailing approach, named generative adversarial networks (GANs), is implemented to augment the training data set by using a small number of training samples. An extensive application has been built for the field cases in a certain oilfield. We randomly select 73 horizontal wells for training, and 13 features are chosen from well-log data sets. Compared with conventional SVMs, the agreement rates of interpretation by XGBoost and CatBoost are significantly improved. Without special preprocessing of the input data sets and conditional tabular GAN (CTGAN) model fine tuning, the fake data set could still bring a relatively low agreement rate for all detections. Finally, we propose an ensemble-learning framework concatenating multilevels of classifiers and improve agreement rate. In this paper, we illustrate a new tool for categorizing the reservoir quality by using GBDTs and ensemble models, which further helps search and identify sweet spots automatically. This tool enables us to integrate experts’ knowledge to the developed model, identify logging curves more efficiently, and cover more sweet spots during the drilling and completion treatment, which immensely decrease the cost of log interpretation.

Context-sensing for context-aware HCI challenges the traditional sensor fusion methods with dynamic sensor configuration and measurement requirements commensurate with human perception. The Dempster-Shafer theory of evidence has uncertainty management and inference mechanisms analogous to our human reasoning process. Our Sensor Fusion for Context-aware Computing Project aims to build a generalizable sensor fusion architecture in a systematic way. This naturally leads us to choose the Dempster-Shafer approach as our first sensor fusion implementation algorithm This paper discusses the relationship between Dempster-Shafer theory and the classical Bayesian method, describes our sensor fusion research work using Dempster-Shafer theory in comparison with the weighted sum of probability method The experimental approach is to track a user's focus of attention from multiple cues. Our experiments show promising, thought-provoking results encouraging further research.

Issues of gender and mentoring are explored through several theoretical lenses—similarity-attraction paradigm, power dependence, social exchange, biological, and psychological theories—to provide a more comprehensive view of mentoring from a gender-based perspective. Issues related to gender and mentoring presented in past mentoring research and tenets from several theoretical bases are used to develop research propositions. The relevance of studying gender issues in mentoring is emphasized and suggestions for conducting research on gender and mentoring are presented.

This paper presents the transmission line model for analyzing the microstrip line inset fed patch antenna and also presents a curve fit formula for locating the exact inset length to obtain 50 I© input impedance. Accuracy of the formula is compared with the results obtained from the EM simulator.

The Long Term Evolution (LTE) of the WCDMA standard requires turbo decoding throughputs of up to 100 Mbps. Unfortunately, the existing WCDMA turbo interleaver does not permit an efficient high throughput implementation. The almost regular permutation (ARP) and quadratic polynomial permutation (QPP) interleavers were proposed to rectify this situation with QPP selected for LTE. In this paper, the interleavers are compared and a full suite of LTE designs and performance results for both are presented.

Orthogonal frequency division multiplexing (OFDM) is a modulation technique that resists the effects of a multipath channel when provided an ample cyclic prefix. No intersymbol interference is caused in channels whose impulse responses are shorter than the cyclic prefix length. However interference arises when this is not the case. This paper describes the degradation of the system under this scenario. In particular, simulations describing a suburban hilly environment are done for several cyclic prefix lengths.

Although using geolocation databases is a practical approach for enabling spectrum sharing, it poses a potentially serious privacy problem. Secondary users (queriers), through seemingly innocuous queries to the database, can determine the types and locations of incumbent systems operating in a given region of interest, and thus compromise the incumbents' operational privacy. When the incumbent systems (primary users) are commercial systems, this is typically not a critical issue. However, if the incumbents are federal government systems, including military systems, then the information revealed by the databases can lead to a serious breach of operational privacy. In this paper, we propose privacy-preserving mechanisms and techniques for an obfuscated geolocation database that can enable the coexistence of primary and secondary users while preserving the operational privacy of the primary users.

This document provides advice to the designers of digital communication equipment, link-layer protocols, and packet-switched local networks (collectively referred to as subnetworks), who wish to support the Internet protocols but may be unfamiliar with the Internet architecture and the implications of their design choices on the performance and efficiency of the Internet.

Resistive-type pressure sensor, which are mainly utilized in industry, are easy to manufacture and are not significantly affected by external electromagnetic fields, unlike capacitive type. However, the produce signal is not linear, and it is also difficult to measure a wide range of pressures using such a sensor. Therefore, before being utilized, the extracted nonlinear data from them need to be processed by. A resistive sensor that is capable of measuring a wide range of pressure of up to 4 MPa with constant linearity is presented. Moreover it can selectively control the sensing pressure band, or act as an on/off switch, without the need for any additional computer processing.

This study reports a single time-series quasi-experiment in a Canadian firm to evaluate the effect over a five-year period of implementing a structured, seven-step strategy to obtain improved organization performance through employee-centered management. A significant change in the condition of the human organization resulting from the intervention was measured over the five-year period and shown to be correlated with a 66% increase in profitability. The results of the study indicate that in the Canadian/U.S. context, employee-centered management is at least compatible with high performance and competitive advantage. There is also evidence that in some instances organization performance can be significantly enhanced through the participation and contribution of employees in problem-solving and decision-making processes.

Summary In this paper, development of a small signal model for 2 × 200 μm GaN HEMT based on the conventional 20‐element model is presented. The proposed model presents a direct parameter extraction algorithm, instead of the hybrid optimization approach, that provides simplification, accuracy, and less computational complexity. The extrinsic elements are extracted using a modified cold pinch‐off condition while discarding the unwanted forward biasing of the gate. The negative drain to source capacitance C ds is also observed in the ohmic region (for smaller V DS ). An excellent agreement found between the measured and modeled data for a wide range of frequencies and bias values shows the effectiveness of the proposed approach. The proposed modeling technique is validated with a good agreement between the achieved bias dependency of intrinsic parameter values and the respective theoretical parameter values.

This review/commentary addresses recent thermal and electromagnetic modeling studies that use image-based anthropomorphic human models to establish the local absorption of radiofrequency energy and the resulting increase in temperature in the body. The frequency range of present interest is from 100 MHz through the transition frequency (where the basic restrictions in exposure guidelines change from specific absorption rate to incident power density, which occurs at 3-10 GHz depending on the guideline). Several detailed thermal modeling studies are reviewed to compare a recently introduced dosimetric quantity, the heating factor, across different exposure conditions as related to the peak temperature rise in tissue that would be permitted by limits for local body exposure. The present review suggests that the heating factor is a robust quantity that is useful for normalizing exposures across different simulation models. Limitations include lack of information about the location in the body where peak absorption and peak temperature increases occur in each exposure scenario, which are needed for careful assessment of potential hazards. To the limited extent that comparisons are possible, the thermal model (which is based on Pennes' bioheat equation) agrees reasonably well with experimental data, notwithstanding the lack of theoretical rigor of the model and uncertainties in the model parameters. In particular, the blood flow parameter is both variable with physiological condition and largely determines the steady state temperature rise. We suggest an approach to define exposure limits above and below the transition frequency (the frequency at which the basic restriction changes from specific absorption rate to incident power density) to provide consistent levels of protection against thermal hazards. More research is needed to better validate the model and to improve thermal dosimetry in general. While modeling studies have considered the effects of variation in thickness of tissue layers, the effects of normal physiological variation in tissue blood flow have been relatively unexplored.

In this paper, we develop the AVTMR (all voting triple modular redundancy) system that is operated correctly in the case of a fault, and evaluate the AVTMR system in the failure rate based on MILSPEC-217F. The AVTMR system is designed in a triplicated voter and MC68000. The Markov model is designed to evaluate the reliability, availability and MTTF (mean time to failure). In this paper, we can see that the AVTMR system has a high dependability more than a single system by evaluation. Because the AVTMR system has a fault tolerant characteristic, it can be applied to airplane and railway systems.

<div class="htmlview paragraph">In this paper, we discuss the mathematical modeling of suspension and rollover characteristics. With dynamics analysis, a simple active suspension control is designed with rollover prevention. Also studied is the framework of how to integrate active suspension and steering in the emergency situations besides regular ride and handling suspension control. Simulation results are presented.</div>

Social work students are tasked with learning the meta and procedural competencies required of the profession while facing their own emotional responses to vulnerable populations and managing clients’ difficult experiences. Social work educators can support students in exploring, understanding, and learning to tolerate, regulate, and manage their emotional responses in preparation for practice. Neuroscience provides a foundation to discuss the role of emotions in social work education. A multipronged approach to teaching and learning emotion regulation for social work students is presented. Experiential learning, mindfulness and embodied practice, simulation and role playing, and practicum learning are discussed as methods to enhance social work students’ emotion regulation capacities in preparation for practice. Considerations for educators and implications for research are discussed.

Initiated by volunteer computing efforts, the computation outsourcing problem can become a compelling application for networked set-top-boxes and mobile devices. In this paper we extend such environments with the ability to provide secure payments in exchange for outsourced CPU cycles. Previous contributions in wired networks have almost exclusively tackled only one side of the problem -- offering incentives for volunteer participation and preventing worker laziness. This makes sense in static environments where reputable outsourcers have little to gain from incorrectly rewarding honest participation. However, this assumption is no longer valid in ad hoc environments, where unique identities are difficult to provide and anyone can outsource computations. In this paper we propose a solution that simultaneously ensures correct remuneration for jobs completed on time and prevents worker laziness. Our solution relies on an offline bank to generate and redeem payments; the bank is oblivious to interactions between outsourcers and workers. In particular, the bank is not involved in job computation or verification. Our experiments show that the solution is efficient: the bank can perform hundreds of payment transactions per second and the overheads imposed on outsourcers and workers are negligible.