Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperation via contracts: stability and algorithms

Embedding incentive mechanisms into network applications is becoming more important since they encourage nodes, either end hosts or routers, to cooperate so as to provide a high performance and scalable service. In this paper, we consider a new approach of using contracts to encourage and maintain cooperation. We formally define the notion of contract in a network setting and illustrate how contracts can be applied to P2P-VoD systems and ISP networks. We also formally show under what conditions a balanced and stable contract can be formaed so that all parties involved will have the incentive to honor the contract. We then propose both centralized and distributed algorithms to find and implement a stable and balanced contract with fairness and security properties. The algorithms can serve as a new genre of incentive mechanisms which are robust against collusion and Sybil attacks.
The psychology of music

The psychology of music is a subfield of psychology that addresses questions of how the mind responds to, imagines, controls the performance of, and evaluates music. The history of this subfield has been greatly influenced by the major trends and developments in the parent discipline, and the organization of this chapter follows the traditional rubrics of that history. Earlier in the twentieth century there was a frequent distinction made between Tonpsychologie (the study of vibration, the ear, and the sensation of sound) and Musikpsychologie (the study of music as a form of cognition). Though the distinction seems less clear-cut today, this chapter recognizes its historical force and focuses on the latter category, with the former receiving extended treatment in Chapter 9, passim. Since at least the seventeenth century, proponents of one or another theory of music have frequently used the psychology of music as a touchstone. They assert propositions in the general form of “musical relationship has a valuation because there exists a relevant phenomenon or principle in the psychology of music. ” For example, one might view Rameau as having asserted that “the fifth and third, as progressions of the fundamental bass have the qualities of being good, natural, and fitting because Sauveur and other acousticians have shown these intervals to be present in every musical tone, as a macrocosm within a microcosm. ” Or Riemann could be viewed as having asserted that “harmonic relationships based on progressions of a major third or perfect fifth between the chordal ‘roots’ have the qualities of being directly intelligible and foundational because Helmholtz and other physiologists have shown that the frequency analysis of the inner ear privileges these intervals. ”
Human gait modelling considerations of biped locomotion for lower limb exoskeleton designs

The number of links in human’s gait model is dependent on factors such as the number of degree of freedoms and the total of actuated joints used in the design. This paper discusses on the modeling consideration of the human gait that related to the design the biped locomotion. Seven types of models are discussed in this paper which suited various biped locomotion design arrangements.
Estimation of genetic diversity for quantitative traits of commercial wheat (Triticum aestivum)

This research was conducted to assess the performance of wheat genotypes and to detect genotypes with adult plant resistance by evaluating them in a trap nursery. 36 commercial wheat cultivar were used in experiment. Morocco was sown on four sides of trial. Material was sown in augmented design. The data was recorded on different quantitative like Plant height (cm), no. of tillers/plant, spike length (cm), no of spikelets/plant, peduncle length (cm), stem diameter (mm) and flag leaf area. Selection of genotypes could be done from two main clusters to make cross for improvement of traits. No of tillers/plant, peduncle length, spike/length, spikelets/plant and plant height showed large genetic variability in Biplot and these variables could be used as selection criteria. Pak-81, Sindh-81, Mexipak-65, Sarsabaz, Chakwal-86 and Kiran-95 so these cultivars could be potentially used in future breeding programme for improvement of several quantitative traits according to results of Biplot analysis. Following genotypes were found moderate resistant against yellow rust viz. Anmol-9, Bahawalpur-200 and Bakhtawar-92 and could be used further in future breeding programme to stand against yellow ruts pressure. Maxipak-65 and WL-711 need to improve by incorporating yellow rust resistant genes.
Cooperative behavior acquisition by learning and evolution in a multi-agent environment for mobile robots

The objective of my research described in this dissertation is to realize learning and evolutionary methods for multiagent systems. This dissertation mainly consists of four parts. We propose a method that acquires the purposive behaviors based on the estimation of the state vectors in Chapter 3. In order to acquire the cooperative behaviors in multiagent environments, each learning robot estimates the Local Prediction Model (hereafter LPM) between the learner and the other objects separately. The LPM estimate the local interaction while reinforcement learning copes with the global interaction between multiple LPMs and the given tasks. Based on the LPMs which satisfies the Markovian environment assumption as possible, robots learn the desired behaviors using reinforcement learning. We also propose a learning schedule in order to make learning stable especially in the early stage of multiagent systems. Chapter 4 discusses how an agent can develop its behavior according to the complexity of the interactions with its environment. A method for controlling the complexity is proposed for a vision-based mobile robot. The agent estimates the full set of state vectors with the order of the major vector components based on the LPM. The environmental complexity is defined in terms of the speed of the agent while the complexity of the state vector is the number of the dimensions of the state vector. According to the increase of the speed of its own or others, the dimension of the state vector is increased by taking a trade-off between the size of the state space and the learning time. The vector-valued reward function is discussed in order to cope with the multiple tasks in Chapter 5. Unlike the traditional weighted sum of several reward functions, we introduce a discounted matrix to integrate them in order to estimate the value function, which evaluates the current action strategy. Owing to the extension of the value function, the learning agent can estimate the future multiple reward from the environment appropriately. Chapter 6 discusses how multiple robots can emerge cooperative behaviors through co-evolutionary processes. A genetic programming method is applied to individual population corresponding to each robot so as to obtain cooperative and competitive behaviors. The complexity of the problem can be explained twofold: co-evolution for cooperative behaviors needs exact synchronization of mutual evolutions, and three robot co-evolution requires well-complicated environment setups that may gradually change from simpler to more complicated situations.
Detection of Illegal Players in MMORPG by Classification Algorithms

Online games have become one of the most popular games in recent years. However, fraud such as real money trading and the use of game bot, has also increased accordingly. In order to maintain a balance in the virtual world, the operators of online games have taken a stern response to the players who conduct fraud. In this study, we have sorted out players' behaviors based on players' game playing time in order to support and find potentially illegal players in the MMORPG. In this paper, we added a topic model to the experiment and used k-means as a major tool to classify the players in the World of Warcraft Avatar History Dataset and find potentially illegal players. Keywords— Online game; fraud; topic model; k-means; classify
Plan-Space Hierarchical Planning with the Action Notation Modeling Language

Planning in robotics must be considered jointly with Acting. Planning is an open loop activity which produces a plan, based on action models, the current state of the world and the desired goal state. Acting, on the other hand, is a closed loop on the environment activity (to execute command and perceive the state of the world). These two deliberative activities must be integrated and need to handle time, concur-rency, synchronization, deadlines and resources. The timeline representation for temporal plan space planning and acting is very expressive; it is also quite flexible for integrating planning and acting. The ANML language is a recent proposal motivated by combining the expressiveness of the timeline representation with the decomposition of HTN methods. This paper reports on FAPE (Flexible Acting and Planning Environment), to our knowledge the first system integrating an ANML planner and actor. Our current focus is not efficient temporal planning per se, but the tight integration of acting and planning, which is addressed by: (i) extending HTN methods with refinements, given by PRS procedures, of planned action primitives into low-level commands, (ii) interleaving the planning process with acting, the former implements plan repair, extension and replanning, while the latter follows PRS skills refinements, and (iii) executing commands with a dispatching mechanism that synchronizes observed time points of action effects and events with planned time. FAPE has been integrated to a PR2 robot and experimented in a home-like environment. The paper presents how planning is performed and integrated with acting, and describes briefly the robotics experiments and reports on initial performances.
Enhanced Integrated Indoor Positioning Algorithm Utilising Wi-Fi Fingerprint Technique

This paper describes an integrated positioning algorithm utilizing Wi-Fi fingerprint technique for indoor positioning. The main contribution of this work is the improvement of positioning accuracy for indoor localization even in extreme RSSI fluctuation which leads to variation of positioning error. Several layers of Wi-Fi positioning is proposed, which are based on deterministic techniques, iterative Bayesian estimation, and also Kalman filter to enhance accuracy due to noise presence. Here, accumulated accuracy is introduced where the distribution of location error is determined by estimation at each test point on path movement. The results show that the integrated algorithm enhances the estimation accuracy in several scenarios which are different Wi-Fi chipsets and movement directions. The error distribution shows an achievement of up to 65% for error less than 5m compared to the basic deterministic technique of only 45%.
An artificial neural network controller based on MPSO-BFGS hybrid optimization for spherical flying robot

Spherical flying robot can perform various tasks in the complex and varied environment to reduce labor costs. However, it is difficult to guarantee the stability of the spherical flying robot in the case of strong coupling and time-varying disturbance. In this paper, an artificial neural network controller (ANNC) based on MPSO-BFGS hybrid optimization algorithm is proposed. The MPSO algorithm is used to optimize the initial weights of the controller to avoid the local optimal solution. The BFGS algorithm is introduced to improve the convergence ability of the network. We use Lyapunov method to analyze the stability of ANNC. The controller is simulated under the condition of nonlinear coupling disturbance. The experimental results show that the proposed controller can obtain the expected value in shoter time compared with the other considered methods.
PERANCANGAN APLIKASI MEDIA INFORMASI LOWONGAN KERJA PERUSAHAAN BAGI PENCARI KERJA BERBASIS WEB

Melihat realita tingginya jumlah pencari kerja di Indonesia saat ini, masih banyak pengangguran, serta sulitnya sebuah perusahaan dalam menseleksi calon karyawan yang akan diterima dalam perusahaannya, maka diperlukan sebuah sistem informasi perancangan sistem informasi lowongan kerja yang dapat mempermudah kedua belah pihak baik bagi pencari kerja maupun bagi perusahaan yang membutuhkan tenaga kerja. Pembangunan Sistem Informasi ini bertujuan untuk memberikan informasi seputar lowongan kerja dan informasi mengenai lowongan yang berbasis web agar memudahkan para pencari kerja untuk mendapatkan informasi secara cepat, mudah dan efisien. Sistem ini dirancang dengan menggunakan bahasa pemograman PHP dan database MySQL. Diharapkan dengan adanya informasi lowongan kerja online ini dapat memberikan kemudahan bagi pencari kerja dan masyarakat umum. The high amount of job seekers in Indonesia nowadays and the limitation of comprehensive information given by the company about the necessity of prospective employees needed based on its qualification. In order to bridge those two problems, one of solutions is by utilizing information system. The development of this Information System aims to give comprehensive information of job vacancies for all job seekers. Therefore the job seekers may directly apply job through system. This system is designed by using the system of waterfall development and by utilizing programme language of PHP/MySQL. The product produced is an online information system containing all informations of job vacancies which may give benefit for companies and job seekers exactly.
Effect of Workload Characteristics on Similarity Analysis

Workload characterization is the basis for similarity analysis, which is the core idea behind benchmark subsetting to pick up the most representative programs or program slices. The set of characteristics is crucial to the result of similarity analysis. Current studies typically use microarchitectureindependent characteristics (MICs) which reveal the inherent program behaviors to evaluate the similarities. In this paper, we propose a novel MICs: serializing instruction distance (SID). SID can describe the serializing instructions behavior that causes a significant performance loss of system-intensive mobile applications. The distribution of critical path length is also used as a MICs because it can reflect the inherent instruction level parallelism (ILP). Furthermore, we employ the comprehensive set of MICs to pick a representative set of program slices for each program of a mobile benchmark suites: Moby. The instructions per cycle (IPC) of each program slice is used to predict the whole program performance. The coefficient of variation of IPCs is under 6% and weighted average IPC prediction error is only 7%. Keywords—microarchitecture-independent characteristics; similarity analysis; mobile applications; serializing instruction
Analog to Digital Conversion

Objectives: (a) Describe the advantages of digital over analog communication. (b) Discuss the basic steps of the analog-to-digital conversion process: sampling, and quantizing/encoding. (c) Given an analog waveform, sampling rate, and resolution, determine the resulting quantized signal and the binary encoded A/D output. (d) Calculate the Nyquist sampling rate for an analog signal. (e) Given the number of bits in an A/D process, and sample frequency, determine the generated bit rate. (f) Define quantization error and state the ONLY way to improve it.
High Speed and Throughput Evaluation of SHA-1 Hash Function Design with Pipelining and Unfolding Transformation Techniques

In recent years, designing of SHA-1 hash function has become popular because it was important in security design application. One of the applications of SHA-1 hash function was HMAC where the architecture of SHA-1 needed to be improved in terms of speed and throughput in order to obtain the highperformance design. The objective of this project was to design high speed and throughput evaluation of SHA-1 hash function based on a combination of pipelining and unfolding techniques. By using both techniques in designing the architecture of SHA- 1 design, the speed of SHA-1 hash function can be increased significantly as well as throughput of the design. In this paper, five proposed SHA-1 architectures were designed with different stages of pipelining such as 1, 4 and 40 stages. The results showed the high-speed design of SHA-1 design can be obtained by using 40 stages pipelining with unfolding factor two. This design provided a high-speed implementation with maximum frequency of 308.17 MHz on Arria II GX and 458.59 MHz on Virtex 5 XC5VLX50T. Furthermore, the throughput of the design also increased about 150.269 Gbps and 223.618 Gbps on Arria II GX and Virtex 5 XC5VLX50T respectively. Thus, highspeed design of SHA-1 hash function was successfully obtained which can give benefit to society especially in security system data transmission and other types of hash functions.
Use of the Maximum Torque Sensor to Reduce the Starting Current in the Induction Motor

Use of the maximum torque sensor has been demonstrated able to improve the standard ramp-up technique in the induction motor circuit system. The induction motor used was of a threephase squirrel-cage motor controlled using a microcontroller 68HC11. From the simulation done, it has been found that this innovative technique could optimize the performance of motor by introducing low stator current and low power consumption over the standard ramp-up technique.
Internet tomography

Today's Internet is a massive, distributed network which continues to explode in size as e-commerce and related activities grow. The heterogeneous and largely unregulated structure of the Internet renders tasks such as dynamic routing, optimized service provision, service-level verification, and detection of anomalous/malicious behavior increasingly challenging tasks. The problem is compounded by the fact that one cannot rely on the cooperation of individual servers and routers to aid in the collection of network traffic measurements vital for these tasks. In many ways, network monitoring and inference problems bear a strong resemblance to other "inverse problems" in which key aspects of a system are not directly observable. Familiar signal processing problems such as tomographic image reconstruction, system identification, and array processing all have interesting interpretations in the networking context. This article introduces the new field of network tomography, a field which we believe will benefit greatly from the wealth of signal processing theory and algorithms.
Multi-mode Tracking of a Group of Mobile Sensors

We consider the problem of tracking a group of mobile nodes with limited available computational and energy resources given noisy RSSI measurements and position estimates from group members. The multilateration solutions are known for energy efficiency. However, these solutions are not directly applicable to dynamic grouping scenarios where neighbourhoods and resource availability may frequently change. Existing algorithms such as cluster-based GPS duty-cycling, individual-based tracking, and multilateration-based tracking can only partially deal with the challenges of dynamic grouping scenarios. To cope with these challenges in an effective manner, we propose a new group-based multi-mode tracking algorithm. The proposed algorithm takes the topological structure of the group as well as the availability of the resources into consideration and decides the best solution at any particular time instance. We consider a clustering approach where a cluster head coordinates the usage of resources among the cluster members. We evaluate the energy-accuracy trade-off of the proposed algorithm for various fixed sampling intervals. The evaluation is based on the 2D position tracks of 40 nodes generated using Reynolds' flocking model. For a given energy budget, the proposed algorithm reduces the mean tracking error by up to $20\%$ in comparison to the existing energy-efficient cooperative algorithms. Moreover, the proposed algorithm is as accurate as the individual-based tracking while using almost half the energy.
Soundscape Composition: Enhancing our understanding of changing soundscapes

This article discusses the affordances of soundscape composition and how the techniques and approaches of this genre have been embraced as an inter-disciplinary research methodology. Since its emergence from the World Soundscape Project, the concept of soundscape composition has set out to enhance our listening awareness of our soundscapes, inspiring and establishing a discourse that explores a sense of place through sound. Soundscape composition over the past decades has established itself as a popular compositional practice among acousmatic composers utilising compositional techniques that go beyond phonographic representation of acoustic environments. Electroacoustic techniques explore not only the transformation and processing of field recordings but also the spatialisation and performance techniques used to create immersive and realistic soundscapes. These compositional developments since the establishment of the World Soundscape Project have brought this genre of music to a wider audience as it has developed into a cross-disciplinary practice. Soundscape studies methodologies such as soundwalking, listening and recording are being utilised by a broader research cohort outside of soundscape composition. This article provides a survey of recent projects and compositions that incorporate a soundscape and cross-disciplinary approach that reflects a variety of cultural themes and issues within the disciplines of social, political and cultural science.
Dynamic polarity lexicon acquisition for advanced Social Media analytics

Social media analytics tool aims at eliciting information and knowledge about individuals and communities, as this emerges from the dynamics of interpersonal communications in the social networks. Sentiment analysis (SA) is a core component of this process as it focuses onto the subjective levels of this knowledge, including the agreement/rejection, the perception, and the expectations by which individual users socially evolve in the network. Analyzing user sentiments thus corresponds to recognize subjective opinions and preferences in the texts they produce in social contexts, gather collective evidence across one or more communities, and trace some inferences about the underlying social phenomena. Automatic SA is a complex process, often enabled by hand-coded dictionaries, called polarity lexicons, that are intended to capture the a priori emotional aspects of words or multiword expressions. The development of such resources is an expensive, and, mainly, language and task-dependent process. Resulting polarity lexicons may be inadequate at fully covering Social Media phenomena, which are intended to capture global communities. In the area of SA over Social Media, this article presents an unsupervised and language independent method for inducing large-scale polarity lexicons from a specific but representative medium, that is, Twitter. The model is based on a novel use of Distributional Lexical Semantics methodologies as these are applied to Twitter. Given a set of heuristically annotated messages, the proposed methodology transfers the known sentiment information of subjective sentences to individual words. The resulting lexical resource is a large-scale polarity lexicon whose effectiveness is measured with respect to different SA tasks in English, Italian, and Arabic. Comparison of our method with different Distributional Lexical Semantics paradigms confirms the beneficial impact of our method in the design of very accurate SA systems in several natural languages.