Analysis of Cooperation in Undertaking Business Between Chinese Software Outsourcing Vendors

Chinese outsourcing vendors attach great importance on cooperation in undertaking business between each other now. Cooperation in undertaking business can help enterprises to obtain complementary resources or capabilities, in order to achieve breakthrough in expanding market. Combined with survey data, this article analyzes the causes of cooperation in undertaking business between outsourcing vendors, and current situation about the cooperation is discussed. On this basis, several suggestions are further put forward.Key words: Software outsourcing; Outsourcing vendor; Cooperation; Undertaking busines

Advances in the application of 18F-FDG PET/CT radiomics for diagnosis, treatment and prognosis prediction of lymphoma

Lymphoma is a highly heterogeneous hematological malignancy that can affect multiple organs throughout the body, exhibiting significant clinical variations among its subtypes. 18F-fluorodeoxyglucose (18F-FDG) PET/CT plays a crucial role in the clinical diagnosis and treatment of lymphoma by facilitating anatomical localization and quantification of metabolic characteristics of highly aggressive lymphomas. This imaging examination method enables a comprehensive evaluation by comparing the metabolic changes before and after treatment, as well as the metabolic difference between lesions and blood pools. However, the heterogeneity of lymphoma, coupled with the limitations of 18F-FDG PET/CT in differentiation, poses challenges for physicians and adversely impacts the clinical treatment plan and prognosis of patients. With the advancement of computer hardware and image analysis technology, radiomics technology, based on the extraction of imaging features of lesions for analysis and diagnosis, has emerged. Numerous researchers have dedicated their efforts to exploring imageomics in lymphoma assessment by using 18F-FDG PET/CT. By integrating feature data with relevant clinical information, models have been developed to effectively correlate image information, clinical data, pathology, and survival outcomes, thereby enhancing the accuracy and efficiency of imaging diagnosis. Furthermore, the utilization of predictive models for prognosis and treatment efficacy has the potential to mitigate subjective errors arising from disparities in physician experience, thereby contributing to the realization of personalized medicine. This review intends to comprehensively summarize the research progress of 18F-FDG PET/CT radiomics in the diagnosis, treatment and evaluation of lymphoma in recent years, from the aspects of diagnosis and differential diagnosis, prognosis prediction and risk grading, drug efficacy prediction and radiomics analysis algorithm optimization, so as to provide insights for future research in machine learning and the development of medical imaging analysis techniques

Using Big Data Analytics to Improve HIV Medical Care Utilisation in South Carolina: A Study Protocol

Introduction Linkage and retention in HIV medical care remains problematic in the USA. Extensive health utilisation data collection through electronic health records (EHR) and claims data represent new opportunities for scientific discovery. Big data science (BDS) is a powerful tool for investigating HIV care utilisation patterns. The South Carolina (SC) office of Revenue and Fiscal Affairs (RFA) data warehouse captures individual-level longitudinal health utilisation data for persons living with HIV (PLWH). The data warehouse includes EHR, claims and data from private institutions, housing, prisons, mental health, Medicare, Medicaid, State Health Plan and the department of health and human services. The purpose of this study is to describe the process for creating a comprehensive database of all SC PLWH, and plans for using BDS to explore, identify, characterise and explain new predictors of missed opportunities for HIV medical care utilisation. Methods and analysis This project will create person-level profiles guided by the Gelberg-Andersen Behavioral Model and describe new patterns of HIV care utilisation. The population for the comprehensive database comes from statewide HIV surveillance data (2005-2016) for all SC PLWH (N approximate to 18000). Surveillance data are available from the state health department\u27s enhanced HIV/AIDS Reporting System (e-HARS). Additional data pulls for the e-HARS population will include Ryan White HIV/AIDS Program Service Reports, Health Sciences SC data and Area Health Resource Files. These data will be linked to the RFA data and serve as sources for traditional and vulnerable domain Gelberg-Anderson Behavioral Model variables. The project will use BDS techniques such as machine learning to identify new predictors of HIV care utilisation behaviour among PLWH, and \u27missed opportunities\u27 for re-engaging them back into care. Ethics and dissemination The study team applied for data from different sources and submitted individual Institutional Review Board (IRB) applications to the University of South Carolina (USC) IRB and other local authorities/agencies/state departments. This study was approved by the USC IRB (#Pro00068124) in 2017. To protect the identity of the persons living with HIV (PLWH), researchers will only receive linked deidentified data from the RFA. Study findings will be disseminated at local community forums, community advisory group meetings, meetings with our state agencies, local partners and other key stakeholders (including PLWH, policy-makers and healthcare providers), presentations at academic conferences and through publication in peer-reviewed articles. Data security and patient confidentiality are the bedrock of this study. Extensive data agreements ensuring data security and patient confidentiality for the deidentified linked data have been established and are stringently adhered to. The RFA is authorised to collect and merge data from these different sources and to ensure the privacy of all PLWH. The legislatively mandated SC data oversight council reviewed the proposed process stringently before approving it. Researchers will get only the encrypted deidentified dataset to prevent any breach of privacy in the data transfer, management and analysis processes. In addition, established secure data governance rules, data encryption and encrypted predictive techniques will be deployed. In addition to the data anonymisation as a part of privacy-preserving analytics, encryption schemes that protect running prediction algorithms on encrypted data will also be deployed. Best practices and lessons learnt about the complex processes involved in negotiating and navigating multiple data sharing agreements between different entities are being documented for dissemination

Towards Strengthening Deep Learning-based Side Channel Attacks with Mixup

In recent years, various deep learning techniques have been exploited in side channel attacks, with the anticipation of obtaining more appreciable attack results. Most of them concentrate on improving network architectures or putting forward novel algorithms, assuming that there are adequate profiling traces available to train an appropriate neural network. However, in practical scenarios, profiling traces are probably insufficient, which makes the network learn deficiently and compromises attack performance. In this paper, we investigate a kind of data augmentation technique, called mixup, and first propose to exploit it in deep-learning based side channel attacks, for the purpose of expanding the profiling set and facilitating the chances of mounting a successful attack. We perform Correlation Power Analysis for generated traces and original traces, and discover that there exists consistency between them regarding leakage information. Our experiments show that mixup is truly capable of enhancing attack performance especially for insufficient profiling traces. Specifically, when the size of the training set is decreased to 30% of the original set, mixup can significantly reduce acquired attacking traces. We test three mixup parameter values and conclude that generally all of them can bring about improvements. Besides, we compare three leakage models and unexpectedly find that least significant bit model, which is less frequently used in previous works, actually surpasses prevalent identity model and hamming weight model in terms of attack results

Mark ratio modulation over pulse position modulation

Orthogonal modulation superimposes non-amplitude-modulated signals on Manchester coded or pulse position modulated amplitude shift keying (ASK) signals, allowing two traffic flows with different bit rates to be modulated on the same wavelength channel, and hence improving spectrum efficiency. Inspired by the orthogonal modulation, this paper proposes a novel modulation format, i.e., mark ratio modulation over pulse position modulation (PPM), which utilizes the mark ratio difference between the PPM symbols and the inverse PPM symbols to deliver an overlaid signal. Better than traditional orthogonal modulation, in the mark ratio modulation over PPM, both low-speed and high-speed traffic flows are modulated by ASK with no need to sacrifice the extinction ratio, while keeping the reception simple and easy. According to theoretical analysis and test, we found 4PPM is a good option, which can balance the trade-off between the PPM signal\u27s effective bit rate and the mark ratio modulated signal\u27s quality

On the Propagation of a Geoeffective Coronal Mass Ejection during March 15 -- 17, 2015

The largest geomagnetic storm so far in the solar cycle 24 was produced by a fast coronal mass ejection (CME) originating on 2015 March 15. It was an initially west-oriented CME and expected to only cause a weak geomagnetic disturbance. Why did this CME finally cause such a large geomagnetic storm? We try to find some clues by investigating its propagation from the Sun to 1 AU. First, we reconstruct the CME's kinematic properties in the corona from the SOHO and SDO imaging data with the aid of the graduated cylindrical shell (GCS) model. It is suggested that the CME propagated to the west $\sim$$33^\circ$$\pm$$10^\circ$ away from the Sun-Earth line with a speed of about 817 km s$^{-1}$ before leaving the field of view of the SOHO/LASCO C3 camera. A magnetic cloud (MC) corresponding to this CME was measured in-situ by the Wind spacecraft two days later. By applying two MC reconstruction methods, we infer the configuration of the MC as well as some kinematic information, which implies that the CME possibly experienced an eastward deflection on its way to 1 AU. However, due to the lack of observations from the STEREO spacecraft, the CME's kinematic evolution in interplanetary space is not clear. In order to fill this gap, we utilize numerical MHD simulation, drag-based CME propagation model (DBM) and the model for CME deflection in interplanetary space (DIPS) to recover the propagation process, especially the trajectory, of the CME from $30 R_S$ to 1 AU. It is suggested that the trajectory of the CME was deflected toward the Earth by about $12^\circ$, consistent with the implication from the MC reconstruction at 1 AU. This eastward deflection probably contributed to the CME's unexpected geoeffectiveness by pushing the center of the initially west-oriented CME closer to the Earth.Comment: 10 pages, 5 figures, 1 table, accepted by JGR - Space Physic