Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of A Research and Development Platform for Mobile IPv6 based Protocols

The Internet is growing by combining various communication media. In the future, it is considered that the wireless connection, rapidly advancing recently, will be the core component of the Internet. The research goal is to design and evaluate the mobility platform for the mobile-centric future Internet. The platform adopts IPv6 and Mobile IPv6 as the base protocols because they are the only realistic options to support the large number of nodes in the future. There are two core points in the design of the mobility platform. One is the separation of signal processing and packet processing to make new protocol support easy. The other is the definition of a common communication interface between processing modules to help smooth information exchange. Using the platform, four different mobility extension protocols are implemented and evaluated. By implementing and operating them through the experiments using the live network have shown the adaptability of the proposed platform design. Third party researchers also use the platform, which objectively indicates that the platform is useful even for other researchers. Furthermore, a completely new protocol that did not exist at the design phase of the platform has been implemented and evaluated. With these results, the conclusion is possible that the proposed mobility platform design can be the future research and development platform for the mobile Internet technology.
Modeling and control of piezo-stage using neural networks

An online identification neural network model and an adaptive controller were designed and verified by simulations to inhibit the influence of hysteresis,creep and dynamic characteristics of a piezo-stage on the positioning accuracy.First,the double Sigmoid activation function was adopted to improve the activation functions of neural networks,and the similarities and differences between improved neural work model and PI hysteresis model were analyzed.Then,a BP neural network with three layers based on the improved activation function was designed as the online identification model of piezo-stage,and the correction formulas for the network weights,thresholds as well as the activation function thresholds were derived.Finally,the adaptive control scheme of the piezo-stage was proposed based on the online identification neural network model,which made use of another neural networks to complete the parameter adjustment of an adaptive PID controller.Experimental results show that the average error and the maximum error are 0.095 μm and 0.32 μm for the online identification neural network model,0.070 μm and 0.100 μm for the adaptive control scheme on tracking triangle waves,and 0.080 μm and 0.105 μm for the tracking multiple frequency wave,respectively.Obtained data prove that positioning accuracy of the piezo-stage is improved effectively.
News Headlines Classification Using Probabilistic Approach

This paper is aimed at news classification on basis of their headlines. Researchers have worked a lot for carrying out news classification at full text level but work in the domain of news headlines classification exists in very limited ratio, Therefore, after analyzing variety of existing news classification methodologies, a probabilistic framework is presented in this paper for classifying news headlines. News headlines classification process is divided into three modules, headlines pre-processing module, probability learning module, and news headlines classification module. Based on availability of variety of headlines, probabilistic framework is designed, which classifies each news headline to its pre-defined category by calculating its maximum probability in that category. Work has been performed using bag of words approach where each headline is split into words and each word is given a certain probability. Furthermore, it is shown that proposed system gives better accuracy results as compared to existing headline classification systems.
A modified hiding high utility item first algorithm (HHUIF) with item selector (MHIS) for hiding sensitive itemsets

In privacy preserving data mining, utility mining plays an important role. In privacy preserving utility mining, some sensitive itemsets are concealed from the database according to certain privacy policies. Hiding sensitive itemsets from the adversaries is becoming an important issue nowadays. Also, only very few methods are available in the literature to hide the sensitive itemsets in the database. One of the existing privacy preserving utility mining methods utilizes two algorithms, HHUIF and MSICF to conceal the sensitive itemsets, so that the adversaries cannot mine them from the modified database. To accomplish the hiding process, this method finds the sensitive itemsets and modifies the frequency of the high valued utility items. However, the performance of this method lacks if the utility value of the items are the same. The items with the same utility value decrease the hiding performance of the sensitive itemsets and also it has introduced computational complexity due to the frequency modification in each item. To solve this problem, in this paper a modified HHUIF algorithm with Item Selector (MHIS) is proposed. The proposed MHIS algorithm is a modified version of existing HHUIF algorithm. The MHIS algorithm computes the sensitive itemsets by utilizing the user defined utility threshold value. In order to hide the sensitive itemsets, the frequency value of the items is changed. If the utility values of the items are the same, the MHIS algorithm selects the accurate items and then the frequency values of the selected items are modified. The proposed MHIS reduces the computation complexity as well as improves the hiding performance of the itemsets. The algorithm is implemented and the resultant itemsets are compared against the itemsets that are obtained from the conventional privacy preserving utility mining algorithms.
To Evaluate The Effectiveness Of The Query Quality Prediction Model Computed Using Sr Algorithm.

We analyze the account of hard queries and suggest a novel framework to decide the degree of weakness for a keyword query over a database, manner in mind both the structure and the satisfied of the database and the query results. Researchers have future methods to envisage hard queries over unstructured text documents. We can generally categorize these methods into two groups as pre-retrieval and post-retrieval methods. There has not been any work on expect or analyzing the hitches of queries over databases. Researchers have future some methods to spot difficult queries over plain text document collections.
Efficient Brain-Computer Interface based on Event-Related Potential

Million of people around the world suffer from degenerative diseases that impair the normal neural pathways that control muscle movements. At late-stages of these diseases, people lose all voluntary muscle control and become completely “locked in” to their bodies, unable to communicate through normal or traditional means. Brain-computer interfaces (BCIs) can allow these patients to communicate again by creating a new communication channel directly from the brain to an external output device. Recent studies on amyotrophic lateral sclerosis (ALS) patients showed that event-related potential (ERP) based BCI technology could create new pathways of communication for paralyzed people. Although these technical demonstrations are encouraging, practical applications of ERP-based BCI technology that meet the needs of people with severe disabilities are significantly impeded primarily by two issues. First, ERPs as the control signals in ERP-based BCIs have an unfavorable ratio between signal (pure ERP components) and noise (neural background activity and various artifacts), which leads to unreliable ERP classification. Second, current epoch-based ERP classifications are still inefficient because they do not exploit full potentials of ERP signals. Mainly due to these two issues, current ERP-based BCI systems have produced impressive laboratory demonstrations but no device of appreciable clinical value. This dissertation sets out to address these problems, in order to work toward an ERP-based BCI system that can advance the practicality. To overcome the first issue of low signal to noise ratio (SNR) of the ERP signals, the classical Farwell-Donchin
Risk assessment of aging power transformers in the transmission network

The report of CIGRE WG A 2.37 "Transformer Reliability Survey" shows that the failure risk of a power transformer (PTR) in the 380 kV extra high voltage level increases significantly above the age of 30 years. Previous risk assessments for this transmission level show that about one third of the total risk is accounted for the asset group power transformer. With these recent figures this share has further increased. In addition, the predicted higher number of switching operations of the tap changer due to higher transmission network utilizations, which are e.g. caused by increased feed-in of renewable energies, a further intensification should be expected. The fact that the power transformer is the most capital-intensive asset, highest attention in asset management should be spent on this asset group. This paper presents the implications of these new findings on the risk assessment with a representative transmission network model, which is based on the data of a German transmission system operator. In addition an investment strategy developer for power transformers is shown to illustrate the effects of partial refurbishment or replacement on the overall network risk. The network and individual asset risk is determined with various load flow situations, lifecycle costs and age-dependent failure rates. These data are compressed to a single key figure by using a Value at Risk method. The investment strategy developer, which uses a multiple choice knapsack problem optimizer, determines the decisions for the individual power transformer if a partial refurbishment, replacement or usual treatment should be taken into account to get the minimum network risk for a limited investment budget. The target figures of the strategy developer are the reliability & availability of the overall transmission network and the investment budget. This optimum budget usage is found with the branch-and-bound algorithm of Sinha & Zolters. The technical and economic impact of partial refurbishment is dependent on the age as well as on the position of the power transformers in the network. The replacement of tap changer and the bushings at power transformers in mid-age (between 20 – 30 years) is a promising investment in asset base and network risk & availability in many cases. In contrast a partial refurbishment of PTR with an age of more than 40 years is not recommended in any case. The most important measure is still the timely replacement of power transformers at the end of life. These have the highest risks, irrespective of local positioning in the system, for the transmission system.
Compact Wideband Quadrature Hybrid based on Microstrip Technique

This paper introduces a new compact quadrature hybrid for wideband applications. Using the conventional technique of cascading two sections in a quadrature hybrid we designed a broadband coupler at a central frequency of 1.8 GHz. To improve the performance of this coupler and reduce its size we used the artificial transmission line concept, microstrip line loaded with shunt open ended stubs, and meandering lines. A size reduction of about 31% was achieved compared to the conventional one. The proposed design has a relative bandwidth of 41.6%, return loss and isolation loss are both better than 18 dB on all the entire band. The design was simulated using the CST Studio suite. Keywords—Quadrature hybrid, broadband coupler, miniaturization, CST Studio suite
The production of verbs in an optic aphasic patient

The paper reports the verb production of an optic aphasic patient. The patient is better at producing verbs than nouns but this advantage is evident only under certain conditions. His verb production on the basis of pictures of actions is not better than his noun production on the basis of pictures. His performance improves considerably when he is asked to name real actions. He has no problems in identifying the pictures and the effect remains strong even when the salient visual factor in actions is eliminated from the input. We argue that the selective advantage for verbs occurs at the level of semantics.
Optimization of Structural Design using Geometric Programming Method

The main objective of structural engineers throughout design history has been to obtain structure under the prescribed design conditions which can not only withstand external loads safety but also achieve an economic solution. This paper focuses on the use of geometric programming solution method to optimum design of plane truss structures. This approach is illustrated on planer truss optimization model and the results are discussed.
Improving E-Learning Videos Using Personalization and Social Signals

Videos can be more engaging and relevant to a course than a textbook, but their linear format frustrates many students. Content based topic detection and tracking algorithms are unlikely to be able to exploit the variety of presentation methods in video lectures; therefore we propose to develop a tool to make videos more navigable and more effective for information retrieval and teaching by tracking and exploiting behavior patterns of students who watch the video. Students will be able to personalize the content by highlighting the video, adding comments, and hiding portions of the video in order to skim the video more effectively. This will allow instructors to segment students based on their habits and preferred mode of learning and adapt the course material accordingly. In this paper we present our early results of indexing video lectures into chapters and developing a discussion board based on each chapter.
A Review Study on Secure Authentication in Mobile System

In mobile environment, the users communicate with each other about location based information and services with the help of network nodes. But providing security to data has become a difficult task. Currently available network security mechanisms are insufficient, but there is a greater demand for flexible, scalable security mechanisms. Mobile security is of vital importance but can’t be inbuilt. In this work, proposing two techniques for authenticating short encrypted messages that helps to preserve the confidentiality and integrity of the communicated messages. The messages to be authenticated must also be encrypted using the secure authentication codes that are more efficient than message authentication codes. The key idea in this technique is to provide the security using Encryption Algorithm. Security model should adjust with various capability requirements and security requirements of a mobile system This paper provides a survey on security in mobile systems
Property Driven Program Slicing

In this paper we are trying to combine the traditional proram slicing technique proposed by Mark Weiser[1] along with the static analysis and data ow analysis results on a given program to remove the statements that do not a ect a given property. Hence we named it Property Driven Program Slicing. In order to do that we apply a forward static analysis to extract properties of each variable in each program point, followed by a backward slicing algorithm to collect the slice based on the static analysis based informations.The aim of the present paper is to further re ne the traditional slicing technique by combining it with abstract interpretation and data ow analysis.This results into a deeper insight on the strong relation between slicing and property based dependency.
Pesticide: Using SMT Processors to Improve Performance of Pointer Bug Detection.

Pointer bugs associated with dynamically-allocated objects resulting in out-of-bounds memory access are an important class of software bugs. Because such bugs cannot be detected easily via static-checking techniques, dynamic monitoring schemes have been proposed. However, the key challenge with dynamic monitoring schemes is the runtime overhead (slowdowns of the order of 10x are common). Previous approaches have used thread-level speculation (TLS) to reduce the overhead. However, the approaches still incur substantial slowdowns while requiring complex TLS hardware. We make the key observation that because the monitor code and user code are largely and unambiguously independent, TLS hardware with all its complexity to handle speculative parallelism is unnecessary. We explicitly multithread the monitor code in which a thread checks one access and use SMT to exploit the parallelism in the monitor code. Despite multithreading the monitor code on SMT, dynamic monitoring slows down the user thread due to two problems: instruction overhead and insufficient overlap among the monitor threads. To address instruction overhead, we exploit the natural locality in the user thread addresses and memoize recent checks in a small table called the allocation-record-cache (ARC). However, programs making and accessing many small memory allocations cause many ARC misses and incur significant runtime overhead. To address this issue, we make a second key observation that because adjacent memory objects result in ARC entries with contiguous address ranges, the entries can be merged into one by simply merging the ranges into one. This merging increases the effective size of the ARC. Finally, insufficient overlap among monitor threads occurs because of inefficient synchronization to protect the allocation data structure updated by the user thread and read by the monitor threads. We make the third key observation that because monitor-thread reads occur for every check but user-thread writes occur only in allocations and deallocations, monitor reads are much more frequent than user writes. We propose a locking strategy, called biased lock, which puts the locking overhead on the writer away from the readers. We show that starting from a runtime overhead of 414% our scheme reduces this overhead to a respectable 24% running three monitor threads on an SMT using a 256-entry ARC with merging and biased lock.
A Semantics Based Approach for Cross Domain Access Control

With the development of cloud computing, the mutual understandability among distributed Access Control Policies (ACPs) and attribute of entities has become an important issue in the security field of open distributed environment. Semantic Web technology provides the solution to semantic interoperability of heterogeneous applications. In this paper, we analysis existing access control approaches and present a new Semantics Based Cross Domain Access Control Approach with Semantic Access Control Policy Language (SACPL) for describing ACPs. Semantic access control architecture is designed to embed SACPL language and Access Control Oriented Ontology System (ACOOS) into the access control process. Using the approach presented, access control across different domains can be effectively solved through the description and management of semantic attribute. This study enriches the research that the semantic web technology is applied in the field of security, and provides a new way of thinking of access control in cloud computing.
Cosine distance features for improved speaker verification

Similarities are used with people known already as a means to enhance speaker verification accuracy. Motivated by this, experimental work has been conducted regarding the use of cosine distance (CD) similarity with respect to a set of reference speakers, CD features, with a back-end support vector machine (CDF-SVM) classifier for speaker verification. A state-of-the-art i-vector with CD scoring (i-CDS) is used as the baseline system for the experiments and for the computation of CD similarity. Experimental results on the telephone speech of the core short2-short3 conditions of NIST 2008 speaker recognition evaluation (SRE), for female, male and both-gender trials, show that the proposed CDF-SVM outperforms the baseline i-CDS system. The CDF-SVM achieved an absolute improvement of 1.16% in equal error rate (EER) and 0.38% in minimum DCF over the baseline i-CDS for female trials. Similar performance improvements were also obtained for the male and all-gender trials of the SRE. Finally, fusing the CDF-SVM with i-CDS gave the best overall performance, an absolute improvement of 4.19% in EER and 1.99% in minimum DCF, over the individual CDF-SVM system performance for the all-gender trials. Similar performance improvements were also achieved for male and female trials.
McFIS in hierarchical bipredictve pictures-based video coding for referencing the stable area in a scene

In this paper, we outline a coding strategy that initializes the entropy coding engine of a video codec at pre-defined locations within a bit-stream. Coupled with the causal dependencies of state-of-the-art video coding systems, this enables wavefront processing of the entropy decoding and reconstruction process simultaneously. Approaches to wavefront processing have been considered by others, and those methods either address the reconstruction process solely or require transmitting image data in non-raster scan order. Here, our key contribution is that we enable simultaneous entropy/reconstruction wavefront processing while still preserving a raster scan strategy. In this paper, we describe the system, as well as different strategies for initializing the context models. The performance of the proposed methods is evaluated, and the bitrate increase is shown to be nominal.
ONLINE GAMES ACCEPTANCE: A LITERATURE REVIEW FROM THE EXTENDED TECHNOLOGY ACCEPTANCE MODEL

This study mainly to collect and discuss the existing literature of Technology Acceptance Model in the online game industries. For this purpose, we collected the relevant studies about electronic word-of-mouth, flow experience, personal technology readiness, and the applications of Technology Acceptance Model in online games. After modeling construction, Structural Equation Modeling was applied to examine the proposed measurement model. Finally, we proposed the discussion, conclusion and future work to understand this work’s improvement. Keyword: Technology Acceptance Model, Online Games, Electronic Word-of-Mouth, Flow Experience, Technology Readiness
On-line Motion Planning of an Autonomous Mobile Robot to Avoid Multiple Moving Obstacles Based on the Prediction of Their Future Trajectories

goal while avoiding multiple moving obstacles such as people and other mobile robots. The future trajectories of the obstacles depend on the future motion of the robot, since each obstacle also avoids other obstacles, including the robot. In other words, each obstacle has its own•emotion principle•fwhich determines its motion from the location of its goal and the motion of other obstacles. In this study, the robot infers the principles of all obstacles in its sensing area from their trajectories observed in real time. This means it can predict their future trajectories, which are influenced
U-Subway: A Smart Monitoring and Control System

Residents of urban areas are becoming increasingly concerned about air quality, especially that in indoor environment, such as the subway. The subway is the most important and most widely used public transportation system in the crowded Seoul Metropolitan Area. Seoul Metro tries to maintain subway air quality using single-purpose systems such as an environment monitoring system and a facility management system. However, since these systems are not interconnected, it is difficult to have an overall picture of the entire system and manage air quality efficiently. In order to monitor and control subway air quality using integrated data, we propose an integrated management system called AirCleaner. In conducting this research, we are actively cooperating with Seoul Metro, which provides system requirements, and with related companies. To make our system more robust, we used proven commercial solutions.