Personalized Extractive Summarization Using an Ising Machine Towards Real-time Generation of Efficient and Coherent Dialogue Scenarios

We propose a personalized dialogue scenario generation system which transmits efficient and coherent information with a real-time extractive summarization method optimized by an Ising machine. The summarization problem is formulated as a quadratic unconstraint binary optimization (QUBO) problem, which extracts sentences that maximize the sum of the degree of user's interest in the sentences of documents with the discourse structure of each document and the total utterance time as constraints. To evaluate the proposed method, we constructed a news article corpus with annotations of the discourse structure, users' profiles, and interests in sentences and topics. The experimental results confirmed that a Digital Annealer, which is a simulated annealing-based Ising machine, can solve our QUBO model in a practical time without violating the constraints using this dataset.

LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval

Multimodal pre-training has propelled great advancement in vision-and-language research. These large-scale pre-trained models, although successful, fatefully suffer from slow inference speed due to enormous computational cost mainly from cross-modal attention in Transformer architecture. When applied to real-life applications, such latency and computation demand severely deter the practical use of pre-trained models. In this paper, we study Image-text retrieval (ITR), the most mature scenario of V+L application, which has been widely studied even prior to the emergence of recent pre-trained models. We propose a simple yet highly effective approach, LightningDOT that accelerates the inference time of ITR by thousands of times, without sacrificing accuracy. LightningDOT removes the time-consuming cross-modal attention by extracting pre-cached feature indexes offline, and employing instant dot-product matching online, which significantly speeds up retrieval process. In fact, our LightningDOT achieves superior performance across mainstream ITR benchmarks such as Flickr30k and COCO datasets, outperforming existing pre-trained models that consume 1000 times magnitude of computational hours using the same features.

نظم الزمن الحقيقي

يمكن تعريف النظام على أنه تقابل بين مجموعة مداخل و مخارج. يمكن نمذجة أي كينونة في الطبيعة على شكل نظام. النظم الحاسوبية هي نظم مكونة من برمجيات و عتاد مادي. نظام الزمن الحقيقي هو نظام يجب أن يحقق قيود صريحة (حدود محددة) على زمن الاستجابة.

An Enhanced Real-Time Routing Protocol with load distributionERTLD ;Compared to Baseline Routing Protocols In MWSN

Mobile wireless sensor network (MWSN) is a wireless ad hoc network that consists of avery large number of tiny sensor nodes communicating with each other in which sensornodes are either equipped with motors for active mobility or attached to mobile objectsfor passive mobility. A real-time routing protocol for MWSN is an exciting area of research because messages in the network are delivered according to their end-to-end deadlines (packet lifetime) while sensor nodes are mobile. This paper proposes an enhanced realtime with load distribution (ERTLD) routing protocol for MWSN which is based on our previousrouting protocol RTLD. ERTLD utilized corona mechanism and optimal forwardingmetrics to forward the data packet in MWSN. It computes the optimal forwarding nodebased on RSSI, remaining battery level of sensor nodes and packet delayover one-hop. ERTLDensures high packet delivery ratio and experiences minimum end-to-end delay in WSNand MWSN compared to baseline routing protocol. . In this paper we consider a highly dynamic wireless sensor network system in which the sensor nodes and the base station(sink) are mobile.ERTLD has been studied and verified and compared with baseline routing protocols RTLD,MM-SPEED , RTLCthrough Network Simulator- 2(NS2)

Enhancing the Quality of Service for Real Time and non-Real Time Application via Internet Network

Services that demanded by users via internet network are classified in two main kinds, Services work in real time such as video and voice in real time and use UDP protocol, and other services that work in non-real time such as web browsing (HTTP) and file transfer (FTP) which use TCP Protocol. In this research, we study and analyze algorithms that enhance the quality of service for various applications. For real time application, we use queues disciplines, which gives high priority for these services and achieves minimum delay. For non-real time application, we study congestion control algorithms, which achieve best performance for reliable transfer process with existing the congestion in the network. We used OPNET 14.5 program for simulating various services via internet network. Simulation results show achieving minimum delay for voice service, and achieving high transmission rate for FTP application with existing of packets loss in the network.

Support marketing campaigns decisions in mobile Telecommunications to provide Location-Based services, by using Big Data technologies

Our proposed work is to introduce a combination of active and passive customer modes. And this will enhance the detecting the customers, even though they are not using their mobile by making a call.

Databases Systems & Communication Techniques Applications in Medical Services

The purpose of this study is to offer help to patients through the employment of databases applications of existing and available telecommunication systems in medical services ,particularly treatment. So that it can be possible to avoided what can be avoided of health disasters that a human being encounter without warning. This study examines how modern technologies can be employed in controlling and processing some vital signs of human beings,particulary those who suffer some health problems affiliated with some diseases ,and keeping these problems under control in order to maintain the stability of the patients health statues. The vital signs that the study is applied to are blood pressure, pulse and blood glucose, since any of change in the value of any of these signs, positive or negative, may cause the patient to have a sudden health problems.

The Effect of the Service Time probability distribution provided to Task Queues in Real- Time Systems

Most of Real-Time Systems which use FIFO (First In First Out) algorithm to arrange the tasks in the queue suffer from a relatively long waiting-time. Our study concerns on the effect of service time probability distribution provided to the waiting tasks in the queues.

Modeling the Scheduling Algorithms of Periodic Tasks and Analyzing its Performance on Real-Time Multiprocessor Systems

The research presents molding and analytical study of several scheduling algorithms types in real-time multiprocessor systems. The performance of three scheduling algorithms have been analyzed : Earliest Deadline First Scheduling (EDF) , Least Laxity First Scheduling (LLF), and Earliest Deadline First until Zero Laxity Scheduling (EDZL). This paper considers the scheduling of n periodic, independed, and preempted tasks with implicit deadlines on a platform of m homogenous multiprocessor. It has compared in terms of the load on the processor (processor's busyness) , the number of migrations, and the number of preemptions and the number of times in which these algorithms did not succeed in achieving the time limits for tasks where the latter is considered the most important criterion in real time scheduling. It also considers scheduling growing task sets of periodic tasks starting from 4 task set up to 64 task set, in order to study the effect of increasing the number of tasks and processors also on the performance of the scheduling algorithms. As a result of research, the strengths and weaknesses in the performance of these three algorithms have presented. It is proposed the best type of real-time system to apply each algorithm according to the strengths of its performance.

A Proposed Approach to Reduce Digital Image Processing Time in Real Time Applications

This research introduces a new approach to reduce time execution of processing programs, by reducing the amount of processed data, especially in applications where the priority is to the execution time of the program over the detailed information of captured pictures, such as detection and tracking systems.