Next Generation Transcriptome Sequencing and Quantitative Real-Time PCR Technologies for Characterisation of the Bemisia tabaci Asia 1 mtCOI Phylogenetic Clade

A programme of functional genomics research is underway at the University of Greenwich,UK,to develop and apply genomics technologies to characterise an economically-important but under-researched Bemisia tabaci（Hemiptera：Aleyrodidae）,the Asia 1 mtCOI phylogenetic group.A comparison of this putative species from India with other important B.tabaci populations and insect species may provide targets for the development of more effective whitefly control strategies.As a first step,next-generation sequencing（NGS）has been used to survey the transcriptome of adult female whitefly,with high quality RNA preparations being used to generate cDNA libraries for NGS using the Roche 454 Titanium DNA sequencing platform.Contig assemblies constructed from the resultant sequences（301 094 reads）using the software program CLC Genomics Workbench generated 3 821 core contigs.Comparison of a selection of these contigs with related sequences from other B.tabaci genetic groups has revealed good alignment for some genes（e.g.,HSP90）but misassemblies in other datasets（e.g.,the vitellogenin gene family）,highlighting the need for manual curation as well as collaborative international efforts to obtain accurate assemblies from the existing next generation sequence datasets.Nevertheless,data emerging from the NGS has facilitated the development of accurate and reliable methods for analysing gene expression based on quantitative real-time RT-PCR,illustrating the power of this approach to enable rapid expression analyses in an organism for which a complete genome sequence is currently lacking.

A Novel Algorithm of Error Check and Code Generation for Structured Flowchart

Structured flowchart( SFC) and Automatic code generation based on SFC( CG-SFC) have been widely used in software requirements,design and testing phases. Some CG-SFC tools such as Rhapsody have the ability to build flowchart and generate code,but they do not check whether a given flowchart is correct or structural. For unstructured error ‘goto'statements will be generated randomly. We proposed three algorithms and some error recognition criteria to solve those problems. Structure recognition algorithm can recognize Selection,While/for and do-while structures. Error recognition algorithm incorporating criteria can check all the errors. At last,we develop a CG-SFC system,and compared with existing Rhapsody,it shows that the proposed algorithms are correct and effective.

A Solution Based on Modeling and Code Generation for Embedded Control System

With the development of computer technology, embedded control system plays an important role in modern industry. For the embedded system, traditional development methods are time-consuming and system is not easy to maintain. Domain-specific modeling provides a solution for the problems. In this paper, we proposed development architecture for embedded control systems based on MIC. GME is used to construct meta-model and application model, model in-terpreter interprets model and stores model information in xml format document. The final cross-platform codes are automatically generated by different templates and xml format document. This development method can reduce time and cost in the lifecycle of system development.

Research and Application of Code Automatic Generation Algorithm Based on Structured Flowchart

It is of great significance to automatically generate code from structured flowchart. There are some deficiencies in existing researches, and their key algorithms and technologies are not elaborated, also there are very few full-featured integrated development platforms that can generate code automatically based on structured flowchart. By analyzing the characteristics of structured flowchart, a structure identification algorithm for structured flowchart is put forward. The correctness of algorithm is verified by enumeration iteration. Then taking the identified flowchart as input, an automatic code generation algorithm is proposed. Also the correctness is verified by enumeration iteration. Finally an integrated development platform is developed using those algorithms, including flowchart modeling, code automatic generation, CDT\GCC\GDB etc. The correctness and effectiveness of algorithms proposed are verified through practical operations.

Towards optimized tensor code generation for deep learning on sunway many-core processor

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application portability.Among the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware devices.In the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning workloads.This paper combines the trends in these two directions.Specifically,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as Sunway.In addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on Sunway.The experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative benchmarks.This work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in mind.We believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.

Simulation of large-scale numerical substructure in real-time dynamic hybrid testing

A solution scheme is proposed in this paper for an existing RTDHT system to simulate large-scale finite element （FE） numerical substructures. The analysis of the FE numerical substructure is split into response analysis and signal generation tasks, and executed in two different target computers in real-time. One target computer implements the response analysis task, wherein a large time-step is used to solve the FE substructure, and another target computer implements the signal generation task, wherein an interpolation program is used to generate control signals in a small time-step to meet the input demand of the controller. By using this strategy, the scale of the FE numerical substructure simulation may be increased significantly. The proposed scheme is initially verified by two FE numerical substructure models with 98 and 1240 degrees of freedom （DOFs）. Thereafter, RTDHTs of a single frame-foundation structure are implemented where the foundation, considered as the numerical substructure, is simulated by the FE model with 1240 DOFs. Good agreements between the results of the RTDHT and those from the FE analysis in ABAQUS are obtained.

Priority-Based Real-Time Stream Coding over Multi-Channel with Packet Erasures

Multi-channel can be used to provide higher transmission ability to the bandwidth-intensive and delay-sensitive real-time streams. However, traditional channel capacity theories and coding schemes are seldom designed for the real-time streams with strict delay constraint, especially in multi-channel context. This paper considers a real-time stream system, where real-time messages with different importance should be transmitted through several packet erasure channels, and be decoded by the receiver within a fixed delay. Based on window erasure channels and i.i.d.(identically and independently distributed) erasure channels, we derive the Multi-channel Real-time Stream Transmission(MRST) capacity models for Symmetric Real-time(SR) streams and Asymmetric Real-time(AR) streams respectively. Moreover, for window erasures, a Maximum Equilibrium Intra-session Code(MEIC) is presented for SR and AR streams, and is shown able to asymptotically achieve the theoretical MRST capacity. For i.i.d. erasures, we propose an Adaptive Maximum Equilibrium Intra-session Code(AMEIC), and then prove AMEIC can closely approach the MRST transmission capacity. Finally, the performances of the proposed codes are verified by simulations.

Real-time programmable coding metasurface antenna for multibeam switching and scanning

Novel electromagnetic wave modulation by programmable dynamic metasurface promotes the device design freedom,while multibeam antennas have sparked tremendous interest in wireless communications.A programmable coding antenna based on active metasurface elements(AMSEs)is proposed in this study,allowing scanning and state switching of multiple beams in real time.To obtain the planar array phase distribution in quick response,the aperture field superposition and discretization procedures are investigated.Without the need for a massive algorithm or elaborate design,this electronically controlled antenna with integrated radiation and phase-shift functions can flexibly manipulate the scattering state of multiple beams under field-programmable gate array(FPGA)control.Simulation and experimental results show that the multiple directional beams dynamically generated in the metasurface upper half space have good radiation performance,with the main lobe directions closely matching the predesigned angles.This metasurface antenna has great potential for future applications in multitarget radar,satellite navigation,and reconfigurable intelligent metasurfaces.

Developing Projects with Low-code Combined with ChatGPT

This paper aims to explore a simpler and more user-friendly way of generating software based on model-driven development.Previous studies have attempted to generate code from domain models,hoping to reduce coding time by increasing modeling time.However,as code tools become more advanced,it is challenging to improve efficiency because models are abstract while implementations are concrete.This paper proposes a novel approach that integrates ChatGPT as a plug-in into the whole R&D process and combines it with our code generation tool to enhance R&D efficiency.We have developed some demos to demonstrate the effectiveness of our approach.According to our evaluation,our approach can save more than 90%of the work in implementing the code generation tool,leaving only about 10%of the work for code review,code improvement,and unit testing.

Complementary Functions and Potential of Generative AI in Algorithm Education

In today’s digital era,algorithms have become an indispensable part of our daily lives and work.Algorithm education plays a crucial role in computer science and software engineering,aiming to cultivate students’problem-solving skills and computational thinking.However,traditional algorithm education often requires significant time and efforts from teachers,lacks interactivity,and provides limited examples.The rapid advancement of AI technology,particularly generative models,and large language models(LLMs),has the potential to revolutionize computer education.Models like OpenAI’s GPT-4 and ChatGPT have conversational capabilities and contribute to various aspects of computer education.GPT-3.5,as an assistant in algorithm education,assists teachers in automatically generating explanations and algorithmic examples to enhance students’understanding of algorithms.While existing research has certain limitations,such as focusing on specific scenarios and lacking comprehensive benchmark testing,this paper explores the role of ChatGPT(GPT-3.5)in algorithm education.By refining prompts and evaluating generative capabilities,the study demonstrates that GPT-3.5 holds significant potential as a teaching aid.With an average accuracy of 0.81.GPT-3.5 can generate explanations,code examples,and visualizations of the corresponding algorithms.Other tests including algorithm problem-solving and examples giving also prove the practicability of GPT-3.5 in algorithm education.

Design Framework of Unsourced Multiple Access for 6G Massive IoT

In this paper,ambient IoT is used as a typical use case of massive connections for the sixth generation(6G)mobile communications where we derive the performance requirements to facilitate the evaluation of technical solutions.A rather complete design of unsourced multiple access is proposed in which two key parts:a compressed sensing module for active user detection,and a sparse interleaver-division multiple access(SIDMA)module are simulated side by side on a same platform at balanced signal to noise ratio(SNR)operating points.With a proper combination of compressed sensing matrix,a convolutional encoder,receiver algorithms,the simulated performance results appear superior to the state-of-the-art benchmark,yet with relatively less complicated processing.

SRDAAR－QNPP：a computer code system for the real－time dose assessment of an accident release for Qinshan Nuclear Power Plant

The paper presents a computer code system 'SRDAAR- QNPP' for the real-time dose as-sessment of an accident release for Qinshan Nuclear Power Plant. It includes three parts:thereal-time data acquisition system, assessment computer. and the assessment operating code system. InSRDAAR-QNPP, the wind field of the surface and the lower levels are determined hourly by using amass consistent three-dimension diasnosis model with the topographic following coordinate system.A Lagrangin Puff model under changing meteorological condition is adopted for atmosphericdispersion, the correction for dry and wet depositions. physical decay and partial plume penetrationof the top inversion and the deviation of plume axis caused by complex terrain have been taken in-to account. The calculation domain areas include three square grid areas with the sideline 10 km, 40krn and 160 km and a grid interval 0.5 km, 2.0 km, 8.0 km respectively. Three exposure pathwaysare taken into account:the external exposure from immersion cloud and passing puff, the internalexposure from inhalation and the external exposure from contaminated ground. This system is ableto provide the results of concentration and dose distributions within 10 minutes after the data havebeen inputed.

Transmission over Cognitive Radio Channel with Novel Secure LT Code

With the increasing of communication applications in recent years, the demand for radio spectral resources has increased significantly. Cognitive radio scenario was proposed to improve spectrum efficiency in wireless communication systems. In cognitive radio network, it is essential that control information is sent securely and reliably. Ensuring the trustworthiness of the transmitting of spectrum sensing information is important in the CR networks since spectrum sensing directly affects spectrum management and incumbent coexistence. In this paper, the first secondary link channel model is presented, then a secure LT Code is proposed to be compatible with presented channel model and acquires good QoS. As we may know, LT code overcomes packet loss when the channel of the SU is reclaimed by PU. In the new proposed combined encoding and ciphered block, a LT code matrix is used to generate a symmetric cryptographic key. Thus, less complexity observed in the processing computation. Besides, cryptographic key is not sent over the channel. As a result, an attacker has no way to eavesdrop the key unless he is prepared to consider all possible key combinations. This replaced block supplies secure controlling channel and increases spectrum efficiency too.

Template-based AADL automatic code generation

Embedded real-time systems employ a variety of operating system platforms. Consequently, for automatic code generation, considerable redevelopment is needed when the platform changes. This results in major challenges with respect to the automatic code generation process of the architecture analysis and design language (AADL). In this paper, we propose a method of template-based automatic code generation to address this issue. Templates are used as carriers of automatic code generation rules from AADL to the object platform. These templates can be easily modified for different platforms. Automatic code generation for different platforms can be accomplished by formulating the corresponding generation rules and transformation templates. We design a set of code generation templates from AADL to the object platform and develop an automatic code generation tool. Finally, we take a typical data processing unit (DPU) system as a case study to test the tool. It is demonstrated that the autogenerated codes can be compiled and executed successfully on the object platform.

Multi-threaded code generation from Signal program to OpenMP

The use of multi-core processors will become a trend in safety critical systems. For safe execution of multi- threaded code, automatic code generation from formal spec- ification is a desirable method. Signal, a synchronous lan- guage dedicated for the functional description of safety crit- ical systems, provides soundness semantics for determinis- tic concurrency. Although sequential code generation of Sig- nal has been implemented in Polychrony compiler, deter- ministic multi-threaded code generation strategy is still far from mature. Moreover, existing code generation methods use certain multi-thread library, which limits the cross plat- form executions. OpenMP is an application program inter- face （API） standard for parallel programming, supported by several mainstream compilers from different platforms. This paper presents a methodology translating Signal program to OpenMP-based multi-threaded C code. First, the intermedi- ate representation of the core syntax of Signal using syn- chronous guarded actions is defined. Then, according to the compositional semantics of Signal equations, the Signal pro- gram is synthesized to dependency graph （DG）. After par- allel tasks are extracted from dependency graph, the Signal program can be finally translated into OpenMP-based C code which can be executed on multiple platforms.

Adaptive Learning Video Streaming with QoE in Multi-Home Heterogeneous Networks

In recent years,real-time video streaming has grown in popularity.The growing popularity of the Internet of Things(IoT)and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience(QoE)and performance objectives.Most researchers focused on Forward Error Correction(FEC)techniques when attempting to strike a balance between QoE and performance.However,as network capacity increases,the performance degrades,impacting the live visual experience.Recently,Deep Learning(DL)algorithms have been successfully integrated with FEC to stream videos across multiple heterogeneous networks.But these algorithms need to be changed to make the experience better without sacrificing packet loss and delay time.To address the previous challenge,this paper proposes a novel intelligent algorithm that streams video in multi-home heterogeneous networks based on network-centric characteristics.The proposed framework contains modules such as Intelligent Content Extraction Module(ICEM),Channel Status Monitor(CSM),and Adaptive FEC(AFEC).This framework adopts the Cognitive Learning-based Scheduling(CLS)Module,which works on the deep Reinforced Gated Recurrent Networks(RGRN)principle and embeds them along with the FEC to achieve better performances.The complete framework was developed using the Objective Modular Network Testbed in C++(OMNET++),Internet networking(INET),and Python 3.10,with Keras as the front end and Tensorflow 2.10 as the back end.With extensive experimentation,the proposed model outperforms the other existing intelligentmodels in terms of improving the QoE,minimizing the End-to-End Delay(EED),and maintaining the highest accuracy(98%)and a lower Root Mean Square Error(RMSE)value of 0.001.

Highly Optimized Code Generation for Stencil Codes with Computation Reuse for GPUs

Computation reuse is known as an effective optimization technique. However, due to the complexity of modern GPU architectures, there is yet not enough understanding regarding the intriguing implications of the interplay of compu- ration reuse and hardware specifics on application performance. In this paper, we propose an automatic code generator for a class of stencil codes with inherent computation reuse on CPUs. For such applications, the proper reuse of intermediate results, combined with careful register and on-chip local memory usage, has profound implications on performance. Current state of the art does not address this problem in depth, partially due to the lack of a good program representation that can expose all potential computation reuse. In this paper, we leverage the computation overlap graph （COG）, a simple representation of data dependence and data reuse with ＂element view＂, to expose potential reuse opportunities. Using COG, we propose a portable code generation and tuning framework for GPUs. Compared with current state-of-the-art code generators, our experimental results show up to 56.7% performance improvement on modern GPUs such as NVIDIA C2050.

RTP payload format for H.264/SVC scalable video coding

The scalable extension of H.264/AVC, known as scalable video coding or SVC, is currently the main focus of the Joint Video Team’s work. In its present working draft, the higher level syntax of SVC follows the design principles of H.264/AVC. Self-contained network abstraction layer units (NAL units) form natural entities for packetization. The SVC specification is by no means finalized yet, but nevertheless the work towards an optimized RTP payload format has already started. RFC 3984, the RTP payload specification for H.264/AVC has been taken as a starting point, but it became quickly clear that the scalable features of SVC require adaptation in at least the areas of capability/operation point signaling and documentation of the extended NAL unit header. This paper first gives an overview of the history of scalable video coding, and then reviews the video coding layer (VCL) and NAL of the latest SVC draft specification. Finally, it discusses different aspects of the draft SVC RTP payload format, in- cluding the design criteria, use cases, signaling and payload structure.

Microwave Photonics for Modern Radar Systems

The emerging new concepts and technologies based on microwave photonics have led to an ever-increasing interest in developing innovative radar systems with a net gain in functionality,bandwidth /resolution,size,mass,complexity and cost when compared with the traditional implementations. This paper describes the techniques developed in the last few years in microwave photonics that might revolutionize the way to design multifunction radar systems,with an emphasis on the recent advances in optoelectronic oscillators( OEOs),arbitrary waveform generation,photonic mixing,phase coding,filtering,beamforming,analog-to-digital conversion,and stable radio-frequency signal transfer. Challenges in implementation of these components and subsystems for meeting the technique requirements of the multifunction radar applications are discussed.