Miracle-dz/UniFAR-FTUs huggingface dataset:
CCNHCaching: A High-speed Caching Throughput Simulator for Information-Centric Networks

Information-Centric Networks (ICN) have attracted great research interests in recent years. Due to the prominent feature of in-network caching, ICN can reduce network latency and improve network throughput. Many researches boost the efforts on the caching simulators. However, the throughput of caching is fundamental to wire-speed forwarding for ICN routers, and there is no corresponding ICN simulator for caching throughput evaluation. In this paper, we propose a caching throughput simulator named CCNHCaching. A reading/writing request queue mechanism is proposed to simulate sequential memory accesses. Combining this mechanism with open-source memory simulators, CCNHCaching can implement precise caching throughput and network performance simulation. Besides, we propose a requesting algorithm to generate realistic high-speed requesting traffic. We compare several state-of-the-art caching schemes and evaluate their caching throughput. The results show that CCNHCaching can provide better evaluation for caching schemes, hence, promoting the development of caching mechanisms.
Geração (semi)automática de metadados: um contributo para a recuperação de objectos de aprendizagem

A alteração da Lei de Bases do Sistema Educativo Português, impulsionada pelo Processo de Bolonha, abre várias oportunidades de utilização do e-Learning não só no âmbito da formação contínua, mas também no contexto da formação inicial. Tal como em muitas outras instituições, o Moodle foi a opção de b-Learning mais natural e viável para a Escola Superior de Educação de Bragança. Com os recentes cursos (Plano Bolonha) foram identificados novos requisitos: necessidade de obter informação actual sobre os programas e conteúdos das diferentes disciplinas para suportar a tomada de decisão de inscrição em novas disciplinas; exigência de uma aprendizagem rápida; e obtenção de informação para suportar processos interdisciplinares. Essa informação reside na plataforma de e-Learning. Contudo, o Moodle não possui um mecanismo de pesquisa próprio que permita localizar e recuperar informação sobre os recursos de aprendizagem, garantindo que o objecto de aprendizagem propriamente dito não seja visualizado por utilizadores ou alunos não autorizados. A geração (semi)automática de metadados para facilitar a localização e recuperação dos objectos de aprendizagem foi a solução encontrada para responder aos requisitos identificados sem afectar a estrutura global do sistema de e-Learning. Assim, este artigo tem como principal objectivo descrever as actividades de especificação e desenvolvimento da solução encontrada.
Development of a residential use, utility interactive PV inverter with isolation transformer-less circuit-development aspects

A 3 kW residential use, utility interactive PV inverter with an isolation transformer-less circuit has been developed. Aiming at a cost effective, compact and highly efficient PV inverter, a prototype inverter was fabricated and tested. In order to improve efficiency, AC reactors and other components were specially designed and evaluated. A conversion efficiency of 94.5% was attained. The cost of the inverter is aimed at Y50/Watt on the basis of 3000 units/month production.
Nonlinear PI controller for systems with state constraint requirements

PI control is widely applied in industrial applications to guarantee a desired regulation for both linear and nonlinear systems. However, when a state constraint requirement is needed for the plant, conventional PI controllers fail to guarantee a desired upper bound for the system states of a generic nonlinear plant at all times. In this paper, a novel nonlinear PI controller is proposed to achieve regulation with state constraint satisfaction for a class of nonlinear systems with constant disturbances. An upper bound for the desired closed-loop system states is guaranteed based on nonlinear ultimate boundedness theory and closed-loop stability is analytically proven for the desired equilibrium point. In addition, a detailed analysis is presented for the appropriate design of the proportional and integral gains of the proposed controller. A practical example of a dc/dc power converter is investigated and simulation results demonstrate the effectiveness of the proposed nonlinear PI control compared to the conventional approach.
Application of intelligent techniques for voltage management of power transmission systems

This thesis presents a group of algorithms for the voltage and reactive power control (Vol/Var control) in transmission systems. The first algorithm is a rule-based technique. Transformers with a tap changer installed in the system are selected by the proposed technique as control devices. For each bus under voltage violation, the most effective control device is selected by using the minimum electric distance criteria. In order to demonstrate the efficiency of the method, several simulations were performed using an IEEE 30-bus network as a model system. The distance measure technique is compared with classic voltage regulation approach and a genetic algorithm based. The second algorithm is a hybrid algorithm. The objective is to minimize the number of manipulations of control devices within a 24 hours period, while the voltages at all buses are kept within the limits of a normal operation. A genetic algorithm is combined with two rulebased statements. Load behavior is analyzed by a first rule: The more acutely load varies, the more required manipulations in control devices will become. And, a second rule is implemented in order to estimate the ability of the controllable devices to decrease voltage violations. A study of different genetic algorithms (GA) applied to Voltage/VAr optimization was made. Notable works are compared and critiqued in terms of common features of GA, such as encoding format, local convergences, genetic operators, evaluation functions, and processing speed. Some thoughts and suggestions for future research are given. Finally, a multi-objective genetic algorithm, based on NSGA-II, is implemented to find an optimal condition of minimum voltage deviations, minimum power losses and minimum number of control actions of a transmission network system. Generators and transformers with off-nominal tap ratio are the devices to be controlled. Different probabilities of mutation factors are compared and it is proved that a more important mutation factor can improve the velocity of convergence without getting into a random search.
Robust Task Grouping with Representative Tasks for Clustered Multi-Task Learning

Multi-task learning aims to learn multiple tasks jointly by sharing information among related tasks such that the generalization performance over different tasks could be improved. Although multi-task learning has been demonstrated to obtain performance gain in comparison with the single task learning, the main challenge that learning what to share with whom is still not fully resolved. In this paper, we propose a robust clustered multi-task learning approach that clusters tasks into several groups by learning the representative tasks. The main assumption behind our approach is that each task can be represented by a linear combination of some representative tasks that can characterize all tasks. The correlation between tasks can be indicated by the corresponding combination coefficient. By imposing a row-sparse constraint on the correlation matrix, our approach could select the representative tasks and encourage information sharing among the related tasks. In addition, the $l_1,2 $-norm is applied to the representation loss to enhance the robustness of our approach. To solve the resulting bi-convex optimization problem, we design an efficient optimization method based on the alternating direction method of multipliers and accelerated proximal gradient method. Finally, experimental results on synthetic and real-world data sets validate the effectiveness of the proposed approach.
Incorporating Fiber Controls into FEM Model for Transversely Isotropic Materials

Physically plausible deformable models based on continuum mechanics have been a hot topic in computer graphics for decades, and many models have been proposed to improve performance speed and stability. However, most of the existing models focus on isotropic materials, while elastic objects with complex anisotropic properties are less studied. Based on the observation that a large group of objects have speciﬁc internal structures (ﬁbers) that determine their anisotropic behavior, we propose a ﬁber incorporated corotational FEM model that can approximate longitudinally anisotropic deformation. First, a ﬁber orientation ﬁeld is used to establish local frames for each element; then, the orientation information is combined into the FEM model by adding local transformations on element stiffness matrices. This proposed model can provide a control for directable deformations, and yields realistic anisotropic deformations. Large deformations can be accommodated; meanwhile, with pre-computation it adds no computational cost to the existing corotational FEM model during simulation. Convincing experimental results and analytical comparisons are presented, together with an accompanying video demonstration.
Attacks & Cryptographic Measures For Wireless Sensor Network

A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to monitor physical or environmental conditions, such as temperature, sound, pressure, etc. and to cooperatively pass their data through the network to a main location. The more modern networks are bi-directional, also enabling control of sensor activity. The development of wireless sensor networks was motivated by military applications such as battlefield surveillance; today such networks are used in many industrial and consumer applications, such as industrial process monitoring and control, machine health monitoring, and so on. Many algorithms are already developed for security in wireless sensor network but with many limitation . For instance key maintenance is a great problem faced in private key encryption methods and less security level is a problem of public key encryption methods even though key maintenance is easy . So by combining both the key exchange method both the problem can be solved.
Mobile capacity enhancement using unequally spaced antenna arrays

Adaptive arrays can significantly increase the cell capacity, improve signal quality, and reduce transmitter power requirements. We investigate the capacity improvement that can potentially be achieved via an optimised design strategy for an unequally spaced array. We also investigate the effect that fading correlation has on the performance of an unequally spaced adaptive array. Results are presented for optimum combining with flat fading. Computer simulations show that it is possible to achieve a gain of at least 1.5 dB for moderate to high signal-to-noise ratios (SNR) when compared to the equally spaced array.
Cuckoo and krill herd‐based k‐means++ hybrid algorithms for clustering

Clustering algorithms can be optimized using nature‐inspired techniques. Many algorithms inspired by nature, namely, firefly algorithm, ant colony optimization algorithm, and so forth, have improved clustering results. k‐means is a popular clustering technique but has limitations of local optima, which have been overcome using its various hybrids. k‐means++ is a hybrid k‐means clustering algorithm that gives the procedure to initialize centre of the clusters. In the proposed work, hybrids of nature‐inspired techniques using cuckoo and krill herd algorithm are implemented on k‐means++ algorithm to enhance cluster quality and generate optimized clusters. The designed algorithms are implemented, and the results are compared with their counterparts. Performance parameters such as accuracy, f‐measure, error rate, standard deviation, CPU time, cluster quality check, and so forth are used to measure the clustering capabilities of these algorithms. The results indicate the high performance of newly designed algorithms.
Equalized Cluster Head Election Routing Protocol for WSNs

In recent years, the growing interest in the WIRELESS SENSOR NETWORK (WISENET) is increases. Wireless Sensor Network is an emerging technology that promises a wide range of potential applications in both civilian and military areas. A sensor network consists of multiple detection stations called sensor nodes, each of which is small, lightweight and portable. Every sensor node is equipped with a Sensing Unit, Data Processing Unit, transceiver and power source. The development of WSNs largely depends on the availability of low-cost and low-power hardware and software platforms for sensor networks. Equalized Cluster Head Election Routing Protocol (ECHERP), pursues energy conservation through balanced clustering for Energy Efficiency.
On the formal foundation of a verification approach for system-level concurrent programs

Though program verification is known and used since decades, the verification of a complete computer system still remains a grand challenge. In essence, this challenge stems from the interaction of various programs. Different techniques have been proposed for the verification of communicating programs. Common to all, however, is that they rely on several (usually implicit) assumptions about the underlying system. Typically, such assumptions include compiler correctness, scheduler fairness, and a certain noninterference between the local program behavior and its environment. This thesis aims at discharging these assumptions for the processes of the microkernel Vamos. More specifically, this work formally justifies the abstraction from a kernel model with explicit, deterministic scheduling to a concurrent process system with non-deterministic but temporally fair scheduling. Our formal results form the foundation of a verification approach for system-level concurrent programs. We outline this approach on example properties of a user-mode operating system. Obwohl es schon jahrzehntelang Programmverifikation gibt, wird die Verifikation eines kompletten Computersystems auch heute noch als eine grose Herausforderung angesehen. Im Wesentlichen ergibt sich diese Herausforderung aus der vielfaltigen Interaktion von Programmen. Verschiedene Techniken wurden fur die Verifikation kommunizierender Programme vorgeschlagen. Alle haben jedoch gemein, dass sie sich auf mehrere (meist implizite) Annahmen uber das zugrunde liegende System stutzen. In der Regel sind solche Annahmen Compiler-Korrektheit, Scheduler-Fairness und eine gewisse Storfreiheit des lokalen Programmverhaltens vom Verhalten seiner Umgebung. Die vorliegende Dissertation beschaftigt sich mit der Entlastung dieser Annahmen fur die Prozesse des Mikrokerns Vamos. Genauer gesagt, rechtfertigt diese Arbeit formal die Abstraktion von einem Kernmodell mit explizitem, deterministischem Scheduling zu einem nebenlaufigen Prozesssystem mit nicht-deterministischem, aber temporal fairem Scheduling. Die formalen Ergebnisse bilden die Grundlage eines Verifikationsansatzes fur nebenlaufige, systemnahe Programme. Dieser Ansatz wird am Beispiel von Eigenschaften eines User-Mode-Betriebssystems erlautert.
POWER SYSTEM STABILITY ENHANCEMENT BY PV DISTRIBUTED GENERATION

the present paper investigates the effect of penetration of photovoltaic generation (PVGs)systems on the transient and small signal stability. Recently interest in photovoltaic (PV)power generation systems is increasing rapidly and the installation of large PV systems orlarge groups of PV systems that are interconnected with the power system grid is acceleratingdespite their high cost and low efficiency due to environmental issues and depletions of fossilfuels. Photovoltaic generators (PVGs) have significant impacts on the existing power systems,these impacts may be either positively or negatively depending on many factors such as PVGslocation, size and inverter characteristics. The eigenvalue analysis and the transient analysisof the system are done without any PVGs penetration and with PVGs penetration and then theresults are compared. The investigation is applied on IEEE-39 bus test system. The stabilityanalysis is carried out using simulation program of power system analysis tool box (PSAT). فی ھذا البحث تم دراسة تأثیر اضافة أنظمة تولید الطاقة الکھروضوئیةبسرعة ، وتسارع ترکیب أنظمة کھروضوئیة (PV) والصغیر. تزاید الاھتمام مؤخرا بنظم تولید الطاقة الکھروضوئیةکبیرة أو مجموعات کبیرة من الأنظمة الکھرو ضوئیة المترابطة مع شبکة نظام الطاقة على الرغم من کلفتھا العالیةوانخفاض کفاءتھا بسبب المشکلات البیئیة واستنزاف الطاقة و الوقود الحفری. المولدات الکھروضوئیة لھا تأثیرات کبیرةعلى أنظمة الطاقة الحالیة ، وقد تکون ھذه التأثیرات إما إیجابیة أو سلبیة اعتمادا ع لى العدید من العوامل مثل موقعوحجمھا وخصائصھا العاکسة. یتم تحلیل القیمة الذاتیة والتحلیل العابر للنظام دون اضافة ای خلایا کھروضوئیة PVGsوتم تنفیذ تحلیل . IEEE- وکذلک مع اضافة خلایا کھروضوئیة ثم تتم مقارنة النتائج. تم تطبیق الاختبارات علی شبکة 39. (PSAT) الاستقرار باستخدام برنامج محاکاة
Integration Distance Similarity with Keyword Algorithm for Improving Cohesion between Sentences in Text Summarization

In recent time the exponential growth of textual information available on the Web, end user need to be able to access information in summary form. Commonly the method to get the summary is extraction method. One of extraction method that easier and commonly used is Keyword Algorithm, but this algorithm has a weakness in the cohesion between the sentences. Distance similarity method is one method used for solving the cohesion problem. The idea of this paper is to improve cohesion between sentences based on extraction of keyword algorithm. The hybrid keyword algorithm and the distance similarity method is proposed. The proposed method was compared three distance similarity such as Cosine, Dice and Jaccard that looking for the cohesiveness between sentences according to keyword algorithm extraction and performance as standard of evaluation. The result showed that Dice has the highest cohesion degree is 45.87 %. Although the best performance is Cosine that performance is influenced with gold standard of abstractive human summary.
Dynamic Optimal Capital Structure and Technological Change

An electrical method and apparatus for stimulating cardiac cells causing contraction to force hemodynamic output during fibrillation, hemodynamically compromising tachycardia, or asystole. High level electrical fields are applied to the heart to give cardiac output on an emergency basis until the arrhythmia ceases or other intervention takes place. The device is used as a stand alone external or internal device, or as a backup to an ICD, atrial defibrillator, or an anti-tachycardia pacemaker. The method and apparatus maintain some cardiac output and not necessarily defibrillation.
Power Flow Analysis for Four Buses System by NR Method

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/ by/4.0) ABSTRACT Power flow studies provide a systematic mathematical approach for determination of various bus voltages, there phase angle, active and reactive power flows through different branches, generators and loads under steady state condition. In this paper, the purpose of power flow analysis is to determine four bus system power flows. Case studies have been performed on Lawpita Taungoo Kamarnat Hlawga (230kV) Line (Myanmar). This paper presents a reliable method to meet the requirements by developing a Newton-Raphson based load flow calculation program through which control setting of Shunt Compensator can be determined directly. This program computes the voltage magnitude and angle at each bus in a power system under balanced steady state conditions. Real and reactive power flows for all buses, as well as line flow and line losses, are also computed. And then the compensation of shunt capacitor is proposed for load flow analysis and also for overall loss minimization and improvement in system voltage profile.
Constant-Envelope Space-Time Shift Keying

From the power amplifier's perspective, the peak-to-average power ratio (PAPR) is of essential importance, especially for both single-RF and reduced-RF multiple-input multiple-output (MIMO) single-carrier schemes. In this context, many of the diversity-oriented index modulation schemes—including the full-RF space-time shift keying (STSK) and the single-RF asynchronous STSK (ASTSK) that invoke randomized signals—exhibit eroded energy-efficiency. To circumvent this problem, we propose a holistic signal construction approach for single-RF, reduced-RF, and full-RF MIMO setups, which always achieve both perfect 0 dB PAPR transmission and inter-channel interference (ICI) free signal detection. More explicitly, first of all, we conceive a new family of single-RF constant-envelope ASTSK (CE-ASTSK), which is capable of substantially outperforming conventional spatial modulation (SM) in both Rayleigh fading and Ricean fading associated with increasing line-of-sight (LoS) power. Second, we propose the new full-RF CE-STSK concept, which is capable of outperforming the orthogonal space-time block codes (STBCs) without either increasing PAPR or imposing ICI. This is particularly beneficial because the conventional linear dispersion code (LDC) approaches always compromise the orthogonality of STBC and hence impose ICI. Third, we also conceive the reduced-RF versions of CE-STSK, which outperform both generalized spatial modulation (GSM) and space-time block coded spatial modulation (STBC-SM). Finally, the proposed schemes are intrinsically amalgamated with turbo detection assisted channel coding, which further confirms the superiority of CE-ASTSK and CE-STSK over SM and STBC in the single-RF and full-RF modes, respectively.
PERFORMANCE COMPARISON OF DIFFERENT MULTI-RESOLUTION TRANSFORMS FOR IMAGE FUSION

This paper analyses the comparision of image fusion combines information from multiple images of the same scene to get a composite image that is more suitable for human visual perception or further image-processing tasks. In this project, we compare various multi-resolution decomposition algorithms, especially the latest developed image decomposition methods, such as curvelet and contourlet, for image fusion. The investigations include the effect of decomposition levels and filters on fusion performance. By comparing fusion results, we give the best candidates for multi-focus images, infrared-visible images, and medical images. The experimental results show that the shift-invariant property is of great importance for image fusion. In addition, we also conclude that short filter usually provides better fusion results than long filter, and the appropriate setting for the number of decomposition levels is four.
Mining Frequent Intemsets in Memory-Resident Databases

Due to the present-day memory sizes, a memory-resident database has become a practical option. Consequently, new methods designed to mining in such databases are desirable. In the case of disk-resident databases, breadth-first search methods are commonly used. We propose a new algorithm, based upon depth-first search in a set-enumeration tree. For memory-resident databases, this method turns out to be superior to breadth-first search.