AN INTELLIGENT METHOD FOR REAL-TIME DETECTION OF DDOS ATTACK BASED ON FUZZY LOGIC

The paper puts forward a variance-time plots method based on slide-window mechanism tocalculate the Hurst parameter to detect Distribute Denial of Service(DDoS)attack in real time.Basedon fuzzy logic technology that can adjust itself dynamically under the fuzzy rules,an intelligent DDoSjudgment mechanism is designed.This new method calculates the Hurst parameter quickly and detectsDDoS attack in real time.Through comparing the detecting technologies based on statistics andfeature-packet respectively under different experiments,it is found that the new method can identifythe change of the Hurst parameter resulting from DDoS attack traffic with different intensities,andintelligently judge DDoS attack self-adaptively in real time.

Machine Learning Application for Prediction of Sapphire Crystals Defects

We investigate the impact of different numbers of positive and negative examples on machine learning for sapphire crystals defects prediction. We obtain the models of crystal growth parameters influence on the sapphire crystal growth. For example, these models allow predicting the defects that occur due to local overcooling of crucible walls in the thermal node leading to the accelerated crystal growth. We also develop the prediction models for obtaining the crystal weight, blocks, cracks, bubbles formation, and total defect characteristics. The models were trained on all data sets and later tested for generalization on testing sets, which did not overlap the training set.During training and testing, we find the recall and precision of prediction, and analyze the correlation among the features. The results have shown that the precision of the neural network method for predicting defects formed by local overcooling of the crucible reached 0.94.

ELECTRICAL RESISTANCE AND ACTIVATION ENERGY OF AMORPHOUS Ni-Si-B ALLOY FILM

The sheet resistance Rs and temperature coefficient of resistance(TCR)α(25-100°C)of amorphous Ni68Si15B17 films have been measured.The structure of films with Rs between 80-550Ω/sq.are more stable and have a lower TCR(10-6K-1-10-5K-1).In this range of Rs,TCR may change its sign,and the activation energy is much larger.

Comments on″Capacity Analysis of the Asymptotically Stable Multi-Valued Exponential Bidirectinal Associative Memory″

Asymptotical stability is an important property of the associative memory neural networks.In this comment,we demonstrate that the asymptotical stability analyses of the MVECAM and MV-eBAM in the asynchronous update mode by Wang et al are not rigorous,and then we modify the errors and further prove that the two models are all asymptotically stable in both synchronous and asynchronous update modes.

3D point clouds reconstruction of mixed reality model based on medical imaging

This project intends to deploy image information such as magnetic resonance imaging(MRI)and digital subtraction angiography(DSA)com bined with stereo positioning system to scan,display and locate anatomical structures such as bones and joints in corpses and living bodies.We employ 3D point clouds as efficient representations of MRI,and propose point clouds denoising and inpainting leveraging on the field of graph signal processing.Virtual reality surgery for specific patients,such as arthroplasty,can be performed multiple times in the ward,and the calculated force is communicated to the operator through the force feedback device to obtain a feel that is close to the actual operation.

Human epidermal growth factor receptor 2 expression in mixed gastric carcinoma

AIM: To investigate human epidermal growth factor receptor 2(HER2) amplification and protein expression in mixed gastric carcinoma.METHODS: Fluorescence in situ hybridization and immunohistochemistry were used to detect HER2 amplification and protein expression in 277 cases of mixed gastric carcinoma. Protein staining intensity was rate as 1+, 2+, or 3+.RESULTS: Of the 277 cases, 114(41.2%) expressed HER2 protein. HER2 3+ staining was observed in 28/277(10.1%) cases, 2+ in 37/277(13.4%) cases, and 1+ in 49/277(17.7%) cases. A HER2 amplification rate of 17% was detected, of which 25/28(89.3%) were observed in the HER2 3+ staining group, 17/37(45.9%) in 2+, and 5/49(10.2%) in 1+. Of the 47 patients with HER2 amplification who received chemotherapy plus trastuzumab, 22 demonstrated median progression-free and overall survivals of 9.1 mo and 16.7 mo, respectively, which were significantly better than those achieved with chemotherapy alone(5.6 mo and 12.1 mo, respectively) in 19 previously treated patients(P s < 0.05). CONCLUSION: HER2 detection in mixed gastric carcinoma displays high heterogeneity. Relativelyquantitative parameters are needed for assessing the level of HER2 amplification and protein expression.

Modulating Traffic Signal Phases to Realize Real-Time Traffic Control System

This paper proposes innovations to address challenges emanating from road traffic congestion. Improving economies create more car owners resulting in increased automobile manufacturing, increased vehicle population giving rise to higher emission of CO2 resulting in traffic congestion. Congested traffic has idling vehicles which emit higher CO2 and pollution. Besides, traffic congestion increases turnaround time, delivery time, commuting time and related logistical aspects. Commuting time negatively impacts working hours. Unless the traffic congestion is mitigated, the economy will take a beating creating a vicious ecology cycle. Building new roads, bridges or reconditioning of infrastructure is not always the best possible solutions. Efficient traffic management is a key to country’s economic growth. Various analytical models are employed to study, appreciate traffic congestion. The paper studies these models to infer that real time approach is the only solution. Several approaches are being worked on and few commercial systems too are available. These systems provide traffic information for course correction. However, it has latency and hence deviates from real time environment. Traffic congestion being highly dynamic in nature, it necessitates real time solution with real time inputs. It is proposed to integrate Real time traffic data with the traffic signal thus modulating the cycle timings at every junction. Deviation from static asymmetric cycle timing is implemented by assigning green phases based on density of vehicles. With minimalistic infrastructure and negligible incremental cost, the paper not only proposes to address traffic congestion but also paves the way for capturing traffic offenses, vehicle tracking and toll collection. The research is imminently realizable and makes a strong case for a PPP (Public Private Partnership) project.

AN EFFICIENT SIGNATURE SCHEME FROM CATALANO’S TRAPDOOR

Digital signature is one of the most important cryptographic primitives. We proposed a new digital signature scheme based on Catalano’s trapdoor. Since Catalano’s trapdoor is more efficient than existing trapdoors in number theory, our scheme need not modular exponentiation but several modular multiplications in the signing algorithm. We also proved our scheme is provably secure against adap-tively chosen message attack by using the Forking lemma.

A Model with Traffic Routers, Dynamically Managing Signal Phases to Address Traffic Congestion in Real Time

On-road Vehicular traffic congestion has detrimental effect on three lifelines: Economy, Productivity and Pollution (EPP). With ever increasing population of vehicles on road, traffic congestion is a major challenge to the economy, productivity and pollution, notwithstanding continuous developments in alternative fuels, alternative sources of energy. The research develops accurate and precise model in real time which computes congestion detection, dynamic signaling algorithm to evenly distribute vehicle densities while ensuring avoidance of starvation and deadlock situation. The model incorporates road segment length and breadth, quality and achievable average speed to compute road capacity. Vehicles installed with GPS enabled devices provide their location, which enables computing road occupancy. Road occupancy is evaluated based on number of vehicles as well as area occupied by vehicles. Ratio of road occupancy and road capacity provides congestion index important to compute signal phases. The algorithm ensures every direction is serviced once during a signaling cycle ensuring no starvation. Secondly, the definition of minimum and maximum signal timings ensures against dead lock situation. A simulator is developed to validate the proposition and proves it can ease congestion by more than 50% which is better than any of the contemporary approaches offering 15% improvement. In case of higher congestion index, alternate routes are suggested based on evaluation of traffic density graphs for shortest route or knowledge database. The algorithm to compute shortest route is optimized drastically, reducing computation cost to 3*√2N vis-à-vis computation cost of N2 by classical algorithms. The proposal brings down the cost of implementation per traffic junction from USD 30,000 to USD 2000.

基于BLS签名的弹性泄露签名方案(英文)

Digital signature,one of the most important cryptographic primitives,has been commonly used in information systems,and thus enhancing the security of a signature scheme can benefit such an application.Currently,leakage-resilient cryptography is a very hot topic in cryptographic research.A leakage-resilient cryptographic primitive is said to be secure if arbitrary but bounded information about the signer's secret key(involving other states) is leaked to an adversary.Obviously,the leakage-resilient signature is more secure than the common signature.We construct an efficient leakage-resilient signature scheme based on BLS signature in the bounded retrieval model.We also prove that our scheme is provably secure under BLS signature.

胃癌组织中HER2基因扩增与蛋白表达的研究(英文)

Objective: The aim of the study was to investigate the human epidermal growth factor receptor 2(HER2) gene amplification and protein expression and interpretation points in the stomach mixed carcinomas. Methods: Immunohistochemistry(IHC) and fluorescence in situ hybridization(FISH) technique were used to detect HER2 gene amplification and expression of HER2 protein in 442 cases of gastric mixed carcinoma. Results: The expression rate of HER2 protein was 41.2%(182/442): the HER2 protein expression IHC 3+ extensive type in 18 cases, partial type in 21 cases, focal type in 8 cases, accounting for 10.6%(47/442); the HER2 protein expression IHC 2+ extensive type in 23 cases, partial type in 28 cases, focal type in 11 cases, accounting for 14.0%(62/442); the HER2 protein expression IHC 1+ extensive type in 27 cases, partial type in 31 cases, focal type in 15 cases, accounting for 16.5%(73/442). HER2 gene amplification rate of 442 cases was 16.1%(71/442). In 182 cases of HER2 protein positive expression, the HER2 gene cluster amplification rate was 14.8%(27/182), large granular amplification rate 11.0%(20/182), punctate amplification rate 6.0%(11/182) and high polysomy 7.1%(13/182). In 71 cases of HER2 gene amplification, there was 42 cases of HER2 protein expression IHC 3+, 22 cases of HER2 protein expression IHC 2+, and 7 cases of IHC 1+. Conclusion: HER2 detection of gastric mixed carcinoma has great heterogeneity, HER2 protein positive expression is divided into extensive type, partial type and focal type, and HER2 gene positive amplification is divided into cluster amplification, large granular amplification, punctate amplification and high polysomy. These typing of HER2 protein expression and HER2 gene amplification provide reference index to quantify for targeted therapeutic effect of anticancer drugs.

MULTI-EPIPOLAR LINES MATCHING-BASED RAY-SPACE INTERPOLATION FOR FREE VIEWPOINT VIDEO SYSTEM

Ray-space based arbitrary viewpoint rendering without complex object segmentation or model construction is the main technology to realize Free Viewpoint Video(FVV) system for complex scenes. Ray-space interpolation and compression are two key techniques for the solution. In this paper,correlation among multiple epipolar lines in ray-space data is analyzed,and a new method of ray-space interpolation with multi-epipolar lines matching is proposed. Comparing with the pixel-based matching interpolation method and the block-based matching interpolation method,the proposed method can achieve higher Peak Signal to Noise Ratio(PSNR) in interpolating rayspace data and rendering arbitrary viewpoint images.

Shortest Alternate Path Discovery through Recursive Bounding Box Pruning

Congestion is a dynamic phenomenon and hence efficiently computing alternate shortest route can only help expedite decongestion. This research is aimed to efficiently compute shortest path for road traffic network so that congestion can be eased resulting in reduced CO2 emission and improved economy. Congestion detection is achieved after evaluating road capacity and road occupancy. Congestion index, a ratio of road occupancy to road capacity is computed, congestion index higher than 0.6 necessitates computation of alternate shortest route. Various algorithms offer shortest alternate route. The paper discusses minimization of graph based by removing redundant nodes which don’t play a role in computation of shortest path. The proposal is based on continuous definition of a bounding box every time a next neighboring node is considered. This reduces maximum number of contentious nodes repeatedly and optimizes the network. The algorithm is deployed from both the ends sequentially to ensure zero error and validate the shortest path discovery. While discovering shortest path, the algorithm also offers an array of shortest path in ascending order of the path length. However, vehicular traffic exhibits network duality viz. static and dynamic network graphs. Shortest route for static distance graph is pre-computed and stored for look-up, alternate shortest path based on assignment of congestion levels to edge weights is triggered by congestion index. The research also supports directed graphs to address traffic rules for lanes having unidirectional and bidirectional traffic.

Dynamic programming based ray-space interpolation for free-viewpoint video system

This paper presents a free viewpoint video(FVV)system based on ray-space interpolation method.The new algorithm matches individual pixels in corresponding scanline pairs by using a dynamic program-ming technique.A sparse intermediate view disparity map is projected from matched pixels firstly,andthe holes(occluded pixels)are filled in by propagating the disparity of neighboring background pixels.After interpolating dense view images,an arbitrary virtual view image can be easily rendered from thedense ray-space converted from these view images.The proposed method is evaluated on the Middleburydata set arid compared with other methods,experimental results show that the better quality of the inter-mediate view is obtained and the corresponding computational complexity is reduced significantly.

Simulating the mind and applications-a theory-based chance for understanding psychic transformations in somatic symptom disorders

With the new category of somatic symptom disorder/bodily distress disorder in ICD-11,research into pathogenetic and therapeutic pathways is stimulated.By turning away from the definition of somatoform disorders as“the lack of something physical explaining everything”,this new classification might offer a way to put the focus on the individual patient’s psychodynamic balance and conflicts and their condensation in the symptom.Modelling and simulation have a long history in science to gain insight also into complex phenomena.Considering the evolution of precision medicine many different parameters are meanwhile operationalised and ready for consequent process research.Calculation models have to fit to the complexity of this disorder category.In an interdisciplinary discourse between computer and medical/psychoanalytic scientists a multilayer,fine grained calculation model is elaborated.Starting from a clinical case history,within iterative discussion,by acknowledging the demand for interdisciplinary synergy and cooperation in science,psychoanalytic theory served as the basis for computer-scientific information technique.A parallelisation with the Mealy model helped to establish a meaningful calculation possibility for further process research.How psychic transformations can be understood properly in order to provide meaningful treatments,the respective training,and to conduct appropriate process-and outcome-research is established in simulating the mind and applications.

Recent advances of neural text generation:Core tasks,datasets,models and challenges

In recent years,deep neural network has achieved great success in solving many natural language processing tasks.Particularly,substantial progress has been made on neural text generation,which takes the linguistic and non-linguistic input,and generates natural language text.This survey aims to provide an up-to-date synthesis of core tasks in neural text generation and the architectures adopted to handle these tasks,and draw attention to the challenges in neural text generation.We first outline the mainstream neural text generation frameworks,and then introduce datasets,advanced models and challenges of four core text generation tasks in detail,including AMR-to-text generation,data-to-text generation,and two text-to-text generation tasks(i.e.,text summarization and paraphrase generation).Finally,we present future research directions for neural text generation.This survey can be used as a guide and reference for researchers and practitioners in this area.

Design and implementation of various datapath architectures for the ANU lightweight cipher on an FPGA

Since the dawn of the Internet of Things(IoT),data and system security has been the major concern for developers.Because most IoT devices operate on 8-bit controllers with limited storage and computation power,encryption and decryption need to be implemented at the transmitting and receiving ends,respectively,using lightweight ciphers.We present novel architectures for hardware implementation for the ANU cipher and present results associated with each architecture.The ANU cipher is implemented at 4-,8-,16-,and 32-bit datapath sizes on four different field-programmable gate array(FPGA)platforms under the same implementation condition,and the results are compared on every performance metric.Unlike previous ANU architectures,the new architectures have parallel substitution boxes(S-boxes)for high throughput and hardware optimization.With these different datapath designs,ANU cipher proves to be the obvious choice for implementing security in extremely resourceconstrained systems.

Evolution Analysis of Societal Risk Events by Risk Maps

Event evolution analysis which provides an effective approach to capture the main context of a story from explosive increased news texts has become the critical basis for many real applications,such as crisis and emergency management and decision making.Especially,the development of societal risk events which may cause some possible harm to society or individuals has been heavily concerned by both the government and the public.In order to capture the evolution and trends of societal risk events,this paper presents an improved algorithm based on the method of information maps.It contains an event-level cluster generation algorithm and an evaluation algorithm.The main work includes:1)Word embedding representation is adopted and event-level clusters are chosen as nodes of the events evolution chains which may comprehensively present the underlying structure of events.Meanwhile,clusters that consist of risk-labeled events enable to illustrate how events evolve along the time with transitions of risks.2)One real-world case,the event of"Chinese Red Cross",is studied and a series of experiments are conducted.3)An evaluation algorithm is proposed on the basis of indicators of map construction without massive human-annotated dataset.Our approach for event evolution analysis automatically generates a visual evolution of societal risk events,displaying a clear and structural picture of events development.

N-SOLITON SOLUTION OF G. Z. TU EQUATIONS

The equations was constructed by G. Z. Tu (Phys. Lett., 94A (1983), 340—342) as follows:

Design and implementation of construction cost prediction model based on SVM and LSSVM in industries 4.0

Purpose-In order to improve the accuracy of project cost prediction,considering the limitations of existing models,the construction cost prediction model based on SVM(Standard Support Vector Machine)and LSSVM(Least Squares Support Vector Machine)is put forward.Design/methodology/approach-In the competitive growth and industries 4.0,the prediction in the cost plays a key role.Findings-At the same time,the original data is dimensionality reduced.The processed data are imported into the SVM and LSSVM models for training and prediction respectively,and the prediction results are compared and analyzed and a more reasonable prediction model is selected.Originality/value-The prediction result is further optimized by parameter optimization.The relative error of the prediction model is within 7%,and the prediction accuracy is high and the result is stable.