Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancement in Channel Equalization Using Particle Swarm Optimization Techniques

This work proposes an improved inertia weight update method and position update method in Particle Swarm Optimization (PSO) to enhance the convergence and mean square error of channel equalizer. The search abilities of PSO are managed by the key parameter Inertia Weight (IW). A higher value leads to global search whereas a smaller value shifts the search to local which makes convergence faster. Different approaches are reported in literature to improve PSO by modifying inertia weight. This work investigates the performance of the existing PSO variants related to time varying inertia weight methods and proposes new strategies to improve the convergence and mean square error of channel equalizer. Also the position update method in PSO is modified to achieve better convergence in channel equalization. The simulation presents the enhanced performance of the proposed techniques in transversal and decision feedback models. The simulation results also analyze the superiority in linear and nonlinear channel conditions.
Professional advice ∗

This paper studies strategic communication by an expert who is concerned about appearing to be well informed. The expert is assumed to observe a private signal with a simple and particularly tractable (“multiplicative linear”) structure. The quality of the expert’s information is evaluated on the basis of the advice given and the realized state of the world. In equilibrium of this reputational cheap-talk game, no more than two messages are e ﬀ ectively reported. The model is extended to consider sequential communication by experts with conditionally independent signals. In the long run, learning is incomplete and herd behavior arises
Vision-based satellite position measurement

Satellite orbit measurement based on ground station,such as USB and VLBI,is restricted in its observation arcs.In addition,the long distance of deep space explorer mission forms a new challenge to current satellite TTC system.If the satellite can estimate its position by its own CCD camera,the time and distance constraints will be eliminated.With a view of this,a vision-based position estimation method for satellite was proposed.It registered satellite image with a reference image and then estimated the satellite's position according to photogrammetry.An experiment using the image,orbit data of space mission was conducted.By mutually verifying the vision method and the traditional method,it illustrates the effectiveness and accuracy.Our vision-based position estimation method is a good complement to the traditional method;it can save work of ground observation stations and have a promising application prospect in deep space exploration.
Combining static analysis and dynamic learning to build context sensitive models of program behavior

This dissertation describes a family of models of program behavior, the Hybrid Push Down Automata (HPDA) that can be acquired using a combination of static analysis and dynamic learning in order to take advantage of the strengths of both. Static analysis is used to acquire a base model of all behavior defined in the binary source code. Dynamic learning from audit data is used to supplement the base model to provide a model that exactly follows the definition in the executable but that includes legal behavior determined at runtime. Our model is similar to the VPStatic model proposed by Feng, Giffin, et al., but with different assumptions and organization. Return address information extracted from the program call stack and system call information are used to build the model. Dynamic learning alone or a combination of static analysis and dynamic learning can be used to acquire the model. We have shown that a new dynamic learning algorithm based on the assumption of a single entry point and exit point for each function can yield models of increased generality and can help reduce the false positive rate. Previous approaches based on static analysis typically work only with statically linked programs. We have developed a new component-based model and learning algorithm that builds separate models for dynamic libraries used in a program allowing the models to be shared by different program models. Sharing of models reduces memory usage when several programs are monitored, promotes reuse of library models, and simplifies model maintenance when the system updates dynamic libraries. Experiments demonstrate that the prototype detection system built with the HPDA approach has a performance overhead of less than 6% and can be used with complex real-world applications. When compared to other detection systems based on analysis of operating system calls, the HPDA approach is shown to converge faster during learning, to detect attacks that escape other detection systems, and to have a lower false positive rate.
Key management for wireless sensor network security

Wireless Sensor Networks (WSNs) have attracted great attention not only in industry but also in academia due to their enormous application potential and unique security challenges. A typical sensor network can be seen as a combination of a number of low-cost sensor nodes which have very limited computation and communication capability, memory space, and energy supply. The nodes are self-organized into a network to sense or monitor surrounding information in an unattended environment, while the self-organization property makes the networks vulnerable to various attacks. Many cryptographic mechanisms that solve network security problems rely directly on secure and efficient key management making key management a fundamental research topic in the field of WSNs security. Although key management for WSNs has been studied over the last years, the majority of the literature has focused on some assumed vulnerabilities along with corresponding countermeasures. Specific application, which is an important factor in determining the feasibility of the scheme, has been overlooked to a large extent in the existing literature. This thesis is an effort to develop a key management framework and specific schemes for WSNs by which different types of keys can be established and also can be distributed in a self-healing manner; explicit/implicit authentication can be integrated according to the security requirements of expected applications. The proposed solutions would provide reliable and robust security infrastructure for facilitating secure communications in WSNs. There are five main parts in the thesis. In Part I, we begin with an introduction to the research background, problems definition and overview of existing solutions. From Part II to Part IV, we propose specific solutions, including purely Symmetric Key Cryptography based solutions, purely Public Key Cryptography based solutions, and a hybrid solution. While there is always a trade-off between security and performance, analysis and experimental results prove that each proposed solution can achieve the expected security aims with acceptable overheads for some specific applications. Finally, we recapitulate the main contribution of our work and identify future research directions in Part V. To my dear husband Ming (Alex) Lu and son Allen Ziye Lu.
SALIENCY BASED IMAGE CATEGORY RECOGNITION

A novel approach using visual attention technique is proposed for classification that categorises objects in challenging conditions. Image classification is one of the most challenging problems in computer vision, especially in the presence of intra-class variation, clutter, occlusion and pose changes. Image classification refers to the labelling of images into one of the predefined categories. In image classification it is very difficult to deal with background information. The background image regions, whether considered as contexts of the foreground or noise to the foreground, can be globally handled by fusing information from different scales. Saliency driven image multi-scale nonlinear diffusion filtering can be used for this classification process. The resulting scale space in general preserves important structures such as edges, lines in the foreground, and inhibits and smoothes clutter in the background.
Chinese Query Recommendation by Weighted SimRank

Query recommendation as an important technology used in search engines suggests relevant queries to help users to reformulate more accurate queries.Existing approaches of query suggestion compute query similarity based on direct matching of query properties.However,it is hard to find the semantic relevant queries that are related indirectly.In this paper,queries are modeled by a query relation graph where query similarity is computed using WSimRank,a revised algorithm based on SimRank.WSimRank takes the edge information and global structure of query relation graph into account so that it can find the latent semantic relations between queries.To reduce the high complexity of basic WSimRank w.r. t real large query relation graph,this paper changes the WSimRank into a state graph and optimized with dynamic programming and pruning.Experiments on large real search engine query logs show that WSimRank outperforms SimRank and other conventional approaches on query suggestion.The MAP of query suggestions generated by WSimRank achieves nearly 0.9.
Organisational development : purposefully engaging change : part III

Extracted from text . I Organisational development: purposefully engaging change Part III 40 Management Today March 2005 Dr Chris van Tonder lectures in change management and organisational development at the University of Johannesburg. In the penultimate article in this series on organisational development we consider organisational change more from the perspective of change management models as a means of structuring and guiding our thinking and actions during organisational change. A somewhat different change model embedded in the ever popular change equations offers 'if then' formulae for change success (or failure). Carnall's equation is particularly useful and we conclude the discussion of change models .
GESTÃO DE RISCOS: ANÁLISE DA EVIDENCIAÇÃO DE RISCOS NAS CONCESSIONÁRIAS DE RODOVIAS LISTADAS NA BOVESPA COM BASE NA METODOLOGIA COSO

The highway concessionaires signed concession contracts with the public sector and invest in infrastructure that, when the contract expires, returns to the government. Thus, companies in the sector are exposed to risks that must be identified and highlighted. Thus, the objective of the study is to identify the risks disclosed and analyze the content of disclosure of risk management at dealerships of roads listed in the Bovespa based on the COSO methodology. The research is classified as descriptive research, document analysis and qualitative approach. The survey sample consists of 16 companies listed in the exploration segment of the Bovespa highways. The results indicate that the risks more evident by the companies of highways exploration segment are related to the market. It follows that the risks disclosed by companies follow uniformity (mimetic isomorphism) with regard to the disclosure and content.
HeapCraft Social Tools: Understanding and Improving Player Collaboration in Minecraft

We introduce a framework to infuence and analyze player collaboration in Minecraft. The framework consists of a telemetry system and several tools to influence player behavior and provide value to server administrators to increase adoption. The data collection includes almost every aspect of gameplay and can be used for analysis beyond player collaboration.1 We started collecting data from several Minecraft servers in March 2015. Most data will be made available to researchers upon request.2 We have also demonstrated the use of our framework to statistically analyze player behavior in Minecraft. More details can be found [1].
Interface to the Routing System (I2RS) for Service Chaining: Use Cases and Requirements

Service chaining is the concept of applying an ordered set of services to a packet or a flow. Services in the chain may include network services such as load-balancing, firewalling, intrusion prevention, and routing among others. Criteria for applying a service chain to a packet or flow can be based on packet/flow attributes that span the OSI layers (e.g., physical port, Ethernet MAC header information, IP header information, transport, and application layer information). This document describes use cases and I2RS (Information to the Rousting System) requirements for the discovery and maintenance of services topology and resources. It also describes use cases and I2RS requirements for controlling the forwarding of a packet/flow along a service chain based on packet/flow attributes.
An improved open-ended waveguide measurement technique on parameters /spl epsiv//sub /spl gamma// and /spl mu//sub /spl gamma// of high-loss materials

An improved technique of using rectangular waveguide aperture for simultaneous measurement of the electromagnetic parameters /spl epsiv//sub /spl gamma// and /spl mu//sub /spl gamma// of materials is developed in this paper. Both multilayer and single-layer medium sheet samples can be tested. Samples are sandwiched between a flange of an open-ended waveguide and a shorting plate. The parameters are obtained by using an optimization technique by fitting the theoretical values of the reflection coefficients /spl Gamma/(/spl epsiv//sub /spl gamma//,/spl mu//sub /spl gamma//) to the measured values with /spl epsiv//sub /spl gamma//,/spl mu//sub /spl gamma// as the argument. The related details, test theories, waveguide design, sample preparation, and error analysis are also discussed in this paper. The experimental results are validated by the measurements performed using the reflection-transmission method using an automatic network analyzer and the published data from manufactures. By virtue of its open-ended waveguide configuration, this technique is well suited for sheet or coating materials, and it might be applied for industrial on-the-worksite testing or biomedical analysis.
Current Trends in the Adoption of the CMMI® Product Suite

This paper examines the current state ofadoption of the Capability Maturity Model®Integration (CMMI) Product Suite.It is based onappraisal reports submitted to and processed bythe Software Engineering Institute (SEISM) as ofJuly 10, 2003.Relevant appraisal data-including organization type, geographicdistribution, and appraisal history-are used todescribe CMMI adoption and use patterns.Thispaper also explains some characteristics of theappraisal process and obtained results.
Low cost inkjet printing for the fast prototyping of surface EMG detection systems

In the last years, printing techniques have been developed for the realization of electronic circuits using functional inks. In this field inkjet printing technology has a number of attractive features and received a lot of interest with the development of specifically designed functional inks, including conductive inks based on silver nanoparticles or organic polymers. Some works in literature investigated the use of inkjet printing technique for the development of electrophysiological sensors. The aim of this work was to explore the potentialities of low cost inkjet printing for the prototyping of high-density electrode arrays for the detection of surface electromyographic signal (sEMG). A low cost inkjet system for the printing of conductive tracks based on standard office printer has been setup and tested for the prototyping of sEMG detection systems. The setup allowed the printing of high density bi-dimensional electrode arrays. The sEMG detection systems have been tested on the abductor pollicis muscle and biceps brachii muscle during isometric and dynamic contractions. The detected signals show a good quality and a stable contact without movement artifacts. The proposed system offers the possibility to design and print electrode arrays with different electrode patterns in a few minutes. This characteristic allows developing sEMG detection systems that can be adapted to the anatomy of the muscles under investigation in a short time.
Technology and higher education: using e-learning tutorial as a pedagogy for innovation and flexible learning

The study was conducted to identify the use of an e-learning tutorial by pre-service teachers in educational psychology at the Teacher Training Institutions in Malaysia. This exploratory study involved 45 pre-service teachers, and the methods used to collect data were questionnaires and protocol interviews. Our preliminary study showed that the adoption of the traditional tutorial, which was a face-to-face interaction, lacked detailed discussion, was less comprehensive and only partially fulfilled the pro-forma and Teaching Learning Objectives (TLO) scheme. Therefore, an e-learning tutorial was implemented as an alternative method in the teaching and learning processes. The results showed that the use of the e-learning tutorial increased the mastery of knowledge and enhanced the higher order thinking skills of the pre-service teachers in their educational psychology courses. The study also found that the teachers thought the learning process was more enjoyable, quicker and easier than the traditional tutorial. Furthermore, the e-learning tutorial could be accessed anywhere and at any time, which in turn can reduce learning costs. The pre-service teachers were more collaboratively creative and critical during the e-learning tutorial discussion than during the traditional tutorial.
Optimization of the wind turbine layout and transmission system planning for a large-scale offshore wind farm by AI technology

Interest in using offshore wind power is rapidly increasing worldwide. A typical offshore wind farm may have hundreds of generators installed within an area ranging from several to tens of square kilometers. Therefore, many feasible schemes have been developed for optimizing wind turbine locations and internal line connections in a wind farm. The planner must search for the optimal scheme in terms of wind power output and installation and operation costs. This study proposes a novel procedure for optimizing wind turbine location and connection line topology by using artificial intelligent techniques: the Genetic Algorithm (GA) is used to optimize the layouts for the offshore wind farm, and Ant Colony System (ACS) algorithm is used to optimize line connection topology. The wake effect, real cable parameters and wind speed series are also considered. The proposed concepts and methods can improve the economy and efficiency of offshore wind farms worldwide.
Complex Network Characteristics of Urban Road Network Topology

Taking the smoothly continuous road center-line segments as the basic analysis unit of road network topology,the topologies of twelve urban road networks in China were abstracted with the dual approach,then the complex network characteristics of these urban road networks have been uncovered through statistic analysis.The conclusions showed that the topologies of these urban road networks in China had the universal properties of the small-world network and scale-free network.
Parallelisms Of Complete Designs

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Text-Line and Character Segmentation for Off-line Recognition of Handwritten Japanese Text

Text-line and character segmentation is one of the most important steps to develop an Optical Character Recognition (OCR) system for handwritten text. Due to distortions of handwriting, i.e., variations of character size, irregular gaps between characters and touching of characters, etc., however, the step is still a difficult task. This paper proposes a method for segmenting Japanese text-lines and characters from off-line handwritten text pages. The proposed method includes: text-line segmentation using a morphological method, zone projection and character separation for each segmented text-line by vertical projection, Stroke Width Transform (SWT), bridge finding and Voronoi diagrams. The method segments curved, touching and skew text-lines and complicated touching characters.
Formative Assessment: The One-Minute Paper vs. the Daily Quiz.

Regular assessment is a vital part of effective teaching and learning. For this, the “oneminute paper” has been popular among faculty. While many teachers who have used it find huge benefits from it, there are also several weaknesses of this tool that are commonly reported by its users. This paper suggests the “daily quiz” as a better tool for assessing and promoting students’ learning. The tool provides a better incentive setup that elicits a more sustained serious response-effort from the students, as well as a sharper focus in assessing cognitive learning. Furthermore, research results in the literature on the effects of frequent testing and the notion of “effortful retrieval” support the author’s experience with the daily quiz. End-of-term surveys of students’ opinions about the usefulness of the daily quiz also confirm the tremendous benefits from this tool. This paper compares the major characteristics of the “minute-paper” versus the daily quiz, based on a survey of the literature as well as the author’s experiences with these tools. This paper will be of interest to those who employ (or are planning to employ) frequent assessment in their classes. It gives them an analysis of the costs and benefits of two common assessment tools.
Secure Multi-Cloud framework by Homomorphic Encryption

The possibility of Homomorphic encryption is to ensure data confidentiality while outsourcing data from cloud server or at cloud level, however with spare abilities to process over encoded information, seeking encrypted data information, and so on. A homomorphism is a property by which an issue in one algebraic framework can be changed over to an issue in another algebraic framework, be tackled and the arrangement later can likewise be changed over back effectively. In this way, homomorphism makes secure point out of calculation to an outsider attainable. Different liable encryption schemes have either multiplicative or additive substance Homomorphic property and are without further protest being used for individual applications. As such, a Fully Homomorphic Encryption (FHE) scheme which could play out any discretionary calculation over encoded data. In this paper, we propose a multi-cloud proposal of M conveyed servers to repartition the information (data) and to practically allow accomplishing a FHE.
Shear strength of Canadian softwood structural lumber

An experimental study has been conducted to evaluate the longitudinal shear strength of nominal 38 × 185 mm and 38 × 285 mm Canadian softwood select structural lumber using a two-span five-point bending test procedure with test span to specimen depth ratios of 6 and 5. Based on American Society for Testing and Materials shear block test results of small clear specimens, finite element analyses coupled with Weibull weakest link theory have been used to predict the shear failure loads of the lumber. Good agreement between the predicted and measured median failure loads has been observed. This study has shown that the Weibull shape parameter is species dependent, which yields a higher unit volume shear strength under constant stresses; therefore, the characteristic shear strength values adopted in the current Canadian Code on Engineering Design in Wood might be conservative for select structural dimension lumber.