ATP: a Datacenter Approximate Transmission Protocol

Many datacenter applications such as machine learning and streaming systems do not need the complete set of data to perform their computation. Current approximate applications in datacenters run on a reliable network layer like TCP. To improve performance, they either let sender select a subset of data and transmit them to the receiver or transmit all the data and let receiver drop some of them. These approaches are network oblivious and unnecessarily transmit more data, affecting both application runtime and network bandwidth usage. On the other hand, running approximate application on a lossy network with UDP cannot guarantee the accuracy of application computation. We propose to run approximate applications on a lossy network and to allow packet loss in a controlled manner. Specifically, we designed a new network protocol called Approximate Transmission Protocol, or ATP, for datacenter approximate applications. ATP opportunistically exploits available network bandwidth as much as possible, while performing a loss-based rate control algorithm to avoid bandwidth waste and re-transmission. It also ensures bandwidth fair sharing across flows and improves accurate applications' performance by leaving more switch buffer space to accurate flows. We evaluated ATP with both simulation and real implementation using two macro-benchmarks and two real applications, Apache Kafka and Flink. Our evaluation results show that ATP reduces application runtime by 13.9% to 74.6% compared to a TCP-based solution that drops packets at sender, and it improves accuracy by up to 94.0% compared to UDP

A new three-dimensional sliding mode guidance law variation with finite time convergence

This paper develops a new three dimensional (3D) guidance law which guarantees the interception of manoeuvring targets in a finite time. The new guidance law accepts the concept that nullifying the line-of-sight (LOS) rate guarantees the interception of the target and its derivation is based on finite time sliding mode guidance. By using a 3D kinematic equation set constructed in a rotating coordinate system, the proposed guidance law alleviates an issue of general 3D guidance caused by the cross coupling effect between pitch and yaw planes. In theoretical analysis, finite time convergence of the new guidance law is proved and compared with that of a practical sliding mode guidance law. Characteristics such as energy consumption and convergence boundary layer are also theoretically analysed. Simulation results demonstrate that the new guidance law effectively intercepts manoeuvring targets in a finite time and analysis results are valid

Effect of poling temperature on piezoelectricity of CaZrO3-modified (K, Na)NbO3-based lead-free ceramics

Electrical poling is indispensable for endowing isotropic ferroelectric polycrystals with a net macroscopic polarization and hence piezoelectricity. However, little attention has been paid to the optimization of poling conditions in (K, Na)NbO3-based ceramics with a polymorphic phase transition. This study investigated the electrical properties of CaZrO3-modified (K, Na, Li)(Nb, Ta)O3lead-free piezoceramics as a function of the poling temperature. Peak piezoelectric coefficient d33of 352 ?? 7 pC/N and planar electromechanical coupling factor kpof 0.47 were obtained at the optimized poling temperature of 120??C, which crosses the polymorphic phase transition regime. In-depth analysis of the asymmetric polarization hysteresis loops and bipolar strain curves uncovered striking analogy between electrical poling and unipolar cycling in the current system, which is attributed to a competition between domain reorientation and space charge accumulation.open1

An improvement in three-dimensional pure proportional navigation guidance

This paper proposes an improved version of 3D pure proportional navigation (PPN) against a manoeuvring target. The main research hypothesis is that the performance of 3D PPN can be improved by properly selecting the direction of the guidance command as there exists an infinite number of potential directions complying with the PPN concept in 3D space. Analysis on the relative motion confirms the validity of the hypothesis and leads to the development of a new guidance algorithm. Unlike traditional 3D PPN, the guidance algorithm developed adapts the direction, but maintains the magnitude of the commanded acceleration proportional to only the line-of-sight (LOS) rate. The validity and performance of the proposed guidance algorithm are investigated through theoretical analysis and numerical simulations

iRFP is a real time marker for transformation based assays in high content screening

Anchorage independent growth is one of the hallmarks of oncogenic transformation. Here we show that infrared fluorescent protein (iRFP) based assays allow accurate and unbiased determination of colony formation and anchorage independent growth over time. This protocol is particularly compatible with high throughput systems, in contrast to traditional methods which are often labor-intensive, subjective to bias and do not allow further analysis using the same cells. Transformation in a single layer soft agar assay could be documented as early as 2 to 3 days in a 96 well format, which can be easily combined with standard transfection, infection and compound screening setups to allow for high throughput screening to identify therapeutic targets

Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-scale Lesion Database

Radiologists in their daily work routinely find and annotate significant abnormalities on a large number of radiology images. Such abnormalities, or lesions, have collected over years and stored in hospitals' picture archiving and communication systems. However, they are basically unsorted and lack semantic annotations like type and location. In this paper, we aim to organize and explore them by learning a deep feature representation for each lesion. A large-scale and comprehensive dataset, DeepLesion, is introduced for this task. DeepLesion contains bounding boxes and size measurements of over 32K lesions. To model their similarity relationship, we leverage multiple supervision information including types, self-supervised location coordinates and sizes. They require little manual annotation effort but describe useful attributes of the lesions. Then, a triplet network is utilized to learn lesion embeddings with a sequential sampling strategy to depict their hierarchical similarity structure. Experiments show promising qualitative and quantitative results on lesion retrieval, clustering, and classification. The learned embeddings can be further employed to build a lesion graph for various clinically useful applications. We propose algorithms for intra-patient lesion matching and missing annotation mining. Experimental results validate their effectiveness.Comment: Accepted by CVPR2018. DeepLesion url adde

Challenges Facing Small and Medium Tourism Enterprises: A Case Study in Kuala Sepetang

Tourism is increasingly being viewed as a development strategy for regional growth, especially in areas experiencing rural decline and economic contraction. In Malaysia, most of the rural tourism related firms are small and medium enterprises (SMEs). While the role of SMEs in destination development is widely studied, the opportunities and challenges facing tourism SMEs are underexplored. In this regard, this study aims to identify and explore the opportunities and challenges that rural tourism SMEs, particularly those faced by boat operators and strategies adopted to overcome these problems. Qualitative approach using in-depth interviews was adopted as a data collection strategy. The findings revealed that most of the boat operators based in Kuala Sepetang are male, with primary or secondary education. Reasons for the boat operators to ventured into tourism include to seek alternative income, to return to their hometown, or to satisfy their passion as a lifestyle entrepreneur. The main challenges the boat operators faced are (i) lack of qualified manpower; (ii) inadequate infrastructures; (iii) variable numbers of seasonal visitors; and (iv) competition among the boat operators