Miracle-dz/UniFAR-FTUs huggingface dataset:
2 Designing a Goal Agent for the Blocks World

Rational agents programmed in agent programming languages derive their choice of action from their beliefs and goals. One of the main benefits of such programming languages is that they facilitate a highlevel and conceptually elegant specification of agent behaviour. Qualitative concepts alone, however, are not sufficient to specify that this behaviour is also nearly optimal, a quality typically also associated with rational agents. Optimality in this context refers to the costs and rewards associated with action execution. It thus would be useful to extend agent programming languages with primitives that allow the specification of near-optimal behaviour. The idea is that quantitative heuristics added to an agent program prune some of the options generated by the qualitative action selection mechanism. In this paper, we explore the expressivity needed to specify such behaviour in the Blocks World domain. The programming constructs that we introduce allow for a high-level specification of such heuristics due to the fact that these can be defined by (re)using the qualitative notions of the basic agent programming language again. We illustrate the use of these constructs by extending a Goal Blocks World agent with various strategies to optimize its behaviour.
Operational Risks In Alternative Banking Channels In Kisumu County, Kenya

xi CHAPTER ONE: INTRODUCTION . 1 1.1 Back ground of the Study . 1 1.1.1 Operational Risk . 2 1.1.2 Alternative Banking Channels . 5 1.2 Research Problem . 8 1.3 Research Objectives . 10 1.4 Value of Study . 10 CHAPTER TWO: LITERATURE REVIEW . 12 2.
Deciding Probabilistic Bisimilarity over In nite-State Probabilistic Systems

We prove that probabilistic bisimilarity is decidable over probabilistic extensions of BPA and BPP processes. For normed subclasses of probabilistic BPA and BPP processes we obtain polynomial-time algorithms. Further, we show that probabilistic bisimilarity between probabilistic pushdown automata and nite-state systems is decidable in exponential time. If the number of control states in PDA is bounded by a xed constant, then the algorithm needs only polynomial time.
Handbook of Knowledge Representation Edited Situation Calculus

The situation calculus is a logical language for representing changes. It was first introduced by McCarthy in 1963, 1 and described in further details by McCarthy and Hayes [29] in 1969. The basic concepts in the situation calculus are situations, actions and fluents. Briefly, actions are what make the dynamic world change from one situation to another when performed by agents. Fluents are situation-dependent functions used to describe the effects of actions. There are two kinds of them, relational fluents and functional fluents. The former have only two values: true or false, while the latter can take a range of values. For instance, one may have a relational fluent called handempty which is true in a situation if the robot's hand is not holding anything. We may need a relation like this in a robot domain. One may also have a functional fluent called battery-level whose value in a situation is an integer between 0 and 100 denoting the total battery power remaining on one's laptop computer. According to McCarthy and Hayes [29], a situation is " the complete state of the universe at an instance of time ". But for Reiter [34], a situation is the same as its history which is the finite sequence of actions that has been performed since the initial situation S 0. We shall discuss Reiter's foundational axioms that make this precise later. Whatever the interpretation, the unique feature of the situation calculus is that situations are first-order objects that can be quantified over. This is what makes the situation calculus a powerful formalism for representing change, and distinguishes it from other formalisms such as dynamic logic [11]. To describe a dynamic domain in the situation calculus, one has to decide on the set of actions available for the agents to perform, and the set of fluents needed to describe the changes these actions will have on the world. For example, consider the classic blocks world where some blocks of equal size can be arranged into a set of towers on a table. The set of actions in this domain depends on what the imaginary agent can do. If we imagine the agent to be a one-handed robot that can be directed to grasp any block that is on the top of a tower, and either add it to the top of another tower or put it down on the table to make a …
OF SPIE

This paper describes and explains why image fusion, what is image fusion, and the current research status mainly on wavelet based pixel-based image fusion. Pixel-based image fusion defines the fusion process of original images or the images after pre-processing. Preliminary results of many researches show that the advantages of high-resolution panchromatic image and low-resolution multi-spectral image can be combined by image fusion and the information extraction capability can be improved. The fusion methods evolutes from traditional fusion methods, pyramid based fusion methods to nowadays wavelet based fusion methods. The popular wavelet theory based Mallat algorithm and “ j Trous” algorithm are explained. In order to overcome some shortcomings of Mallat algorithm and “ j Trous” algorithm, MRAIM algorithm is designed, which is based on the image formation principle and multi-resolution analysis theory. It formulates the Mallat algorithm and “ j Trous” algorithm from the theoretical point of view. It can improve the spatial resolution while preserve the hue and saturation unchanged.
Mining Dual Networks : Models , Algorithms and Applications

YUBAO WU, Electrical Engineering and Computer Science, Case Western Reserve University XIAOFENG ZHU, Epidemiology and Biostatistics, Case Western Reserve University LI LI, Family Medicine and Community Health, Case Western Reserve University WEI FAN, Baidu Research Big Data Lab RUOMING JIN, Computer Science, Kent State University XIANG ZHANG, Electrical Engineering and Computer Science, Case Western Reserve University
Aggregate and Veriﬁably Encrypted Signatures from Bilinear Maps ∗

An aggregate signature scheme is a digital signature that supports aggregation: Given n signatures on n distinct messages from n distinct users, it is possible to aggregate all these signatures into a single short signature. This single signature (and the n original messages) will convince the veriﬁer that the n users did indeed sign the n original messages (i.e., user i signed message M i for i = 1 , . . . , n ). In this paper we introduce the concept of an aggregate signature, present security models for such signatures, and give several applications for aggregate signatures. We construct an eﬃcient aggregate signature from a recent short signature scheme based on bilinear maps due to Boneh, Lynn, and Shacham. Aggregate signatures are useful for reducing the size of certiﬁcate chains (by aggregating all signatures in the chain) and for reducing message size in secure routing protocols such as SBGP. We also show that aggregate signatures give rise to veriﬁably encrypted signatures. Such signatures enable the veriﬁer to test that a given ciphertext C is the encryption of a signature on a given message M . Veriﬁably encrypted signatures are used in contract-signing protocols. Finally, we show that similar ideas can be used to extend the short signature scheme to give simple ring signatures.
Transgenic plants for phytoremediation of Arsenic and Chromium to enhance tolerance and hyperaccumulation

Phytoremediation of metals and other environmental pollutants is gaining importance as a cost-effective method for pollution mitigation and envisages sustainable development. This paper envisages prospects of phytoremediation for mitigation of heavy metal pollutants from the environment, with particular reference to arsenic (As) and chromium (Cr). Genetically engineered tailor-made plants have much potential for selective uptake, accumulation and sequestration of heavy metals. Recent developments in this area and state-of-the-art technology foresee genetically engineered plants with an ability to prevent accumulation of As in aerial parts of experimental plant systems, which could be extrapolated to edible plants such as rice, wheat and others. Similarly, hypereaccumulation in plant biomass is another important approach for removal of these toxic metals from the land and water ecosystems and mitigation of As and Cr pollution. The mechanisms of As hyperaccumulation by the hyperaccumulator plants has opened up scope for genetic engineering other prospective plant species to enhance hyperaccumulation of toxic metals in their aerial biomass. This review enumerates the mechanisms of hyperaccumulation in the plant systems, the potential genes that could be engineered to develop tailor made genetically engineered plants aimed for phytoremediation of As and Cr and other metals in general.
Packet Order Matters! Improving Application Performance by Deliberately Delaying Packets

Data centers increasingly deploy commodity servers with high-speed network interfaces to enable low-latency communication. However, achieving low latency at high data rates crucially depends on how the incoming trafﬁc interacts with the system’s caches. When packets that need to be processed in the same way are consecutive, i.e., exhibit high temporal and spatial locality, caches deliver great beneﬁts. In this paper, we systematically study the impact of temporal and spatial trafﬁc locality on the performance of commodity servers equipped with high-speed network interfaces. Our results show that ( i ) the performance of a variety of widely deployed applications degrades substantially with even the slightest lack of trafﬁc locality, and ( ii ) a trafﬁc trace from our organization reveals poor trafﬁc locality as networking protocols, drivers, and the underlying switching/routing fabric spread packets out in time (reducing locality). To address these issues, we built Reframer, a software solution that de-liberately delays packets and reorders them to increase trafﬁc locality. Despite introducing µs-scale delays of some packets, we show that Reframer increases the throughput of a network service chain by up to 84% and reduces the ﬂow completion time of a web server by 11% while improving its throughput by 20%.
Direct Access, High-Performance Memory Disaggregation with DirectCXL

New cache coherent interconnects such as CXL have recently attracted great attention thanks to their excellent hardware heterogeneity management and resource disaggregation capabilities. Even though there is yet no real product or platform integrating CXL into memory disaggregation, it is expected to make memory resources practically and efficiently disag-gregated much better than ever before. In this paper, we propose directly accessible memory dis-aggregation, D IRECT CXL that straight connects a host processor complex and remote memory resources over CXL’s memory protocol ( CXL.mem ). To this end, we explore a practical design for CXL-based memory disaggregation and make it real. As there is no operating system that supports CXL, we also offer CXL software runtime that allows users to utilize the underlying disaggregated memory resources via sheer load/store instructions. Since D IRECT CXL does not require any data copies between the host memory and remote memory, it can expose the true performance of remote-side disaggre-gated memory resources to the users.
Path Splitting: A Technique for Improving Data-Flow Analysis Massimiliano Poletto

The e(cid:11)ectiveness of traditional global optimizations is limited by the quality of data-(cid:13)ow information available to the compiler. The rich control structure of many programs hinders global optimizations by polluting data-(cid:13)ow information and forcing the compiler to make worst-case assumptions during data-(cid:13)ow analysis. Path splitting is a new technique for improving the amount of data-(cid:13)ow information statically available to the compiler. It replicates code in order to provide optimal reaching de(cid:12)nitions information within given regions of the control-(cid:13)ow graph. This improved information is used to extend the applicability of various classical code optimizations, including copy propagation, common subexpression elimination, dead code elimination, and code hoisting. An experimental implementation of path splitting in the SUIF C compiler indicates that path splitting e(cid:11)ectively restructures loops, reducing the cycle count within them by up to a factor of two, and resulting in over 7% run time performance improvements for C programs. Although path splitting can cause exponential growth in code size, applying it selectively limits code growth to below 5% for realistic C programs, and does not noticeably degrade cache performance.
Do Robot Performance and Behavioral Style a ↵ ect Human Trust ? A Multi-Method Approach

An important aspect of a robot’s social behavior is to convey the right amount of trustworthiness. Task performance has shown to be an important source for trustworthiness judgments. Here, we argue that factors such as a robot’s behavioral style, can play an important role as well. Our approach to studying the e↵ects of a robot’s performance and behavioral style on human trust involves experiments with simulated robots in Video Human-Robot Interaction (VHRI) and Immersive Virtual Environments (IVE). Although VHRI and IVE settings cannot substitute for the genuine interaction with a real robot, they can provide useful complementary approaches to experimental research in social Human Robot Interaction. VHRI enables rapid prototyping of robot behaviors. Simulating Human-Robot Interaction in IVEs can be a useful tool for measuring human responses to robots and help avoid the many constraints caused by realworld hardware. However, there are also di culties with the generalization of results from one setting (e.g., VHRI) to another (e.g. IVE or the real world), which we discuss. In this paper, we use animated robot avatars in VHRI to rapidly identify robot behavioral styles that a↵ect human trust assessment of the robot. In a subsequent study, we use an IVE to measure behavioral interaction between humans and an animated robot avatar equipped with behaviors from the VHRI experiment. Our findings reconfirm that a robot’s task performance R. van den Brule · W.F. G. Haselager Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Montessorilaan 3, 6525 HR Nijmegen E-mail: r.vandenbrule@donders.ru. nl R. van den Brule · R. Dotsch · G. Bijlstra · D.H. J. Wigboldus Behavioural Science Institute, Radboud University Nijmegen, Montessorilaan 3, 6525 HR Nijmegen influences its trustworthiness, but the e↵ect of the behavioral style identified in the VHRI study did not influence the robot’s trustworthiness in the IVE study.
0 Joint Link Prediction and Attribute Inference using a Social-Attribute Network

NEIL ZHENQIANG GONG, University of California at Berkeley AMEET TALWALKAR, University of California at Berkeley LESTER MACKEY, University of California at Berkeley LING HUANG, Intel Labs EUI CHUL RICHARD SHIN, University of California at Berkeley EMIL STEFANOV, University of California at Berkeley ELAINE (RUNTING) SHI, University of Maryland, College Park DAWN SONG, University of California at Berkeley
An Experimental Comparison of Remote Procedure Call and Group Communication

Unlike many other operating systems, Amoeba is a distributed operating system that provides group communication (i.e., one-to-many communication). We will discuss design issues for group communication, Amoeba’s group system calls, and the protocols to implement group communication. To demon-strate that group communication is a useful abstraction, we will describe a design and implementation of a fault-tolerant directory service. We discuss two versions of the directory service: one with Non-Volatile RAM (NVRAM) and one without NVRAM. We will give performance figures for both implementations.
ENSO-Related Global Ocean Heat Content Variations

The modulation of the full-depth global integrated ocean heat content (GOHC) by El Niño–Southern Oscillation (ENSO) has been estimated in various studies. However, the quantitative results and the mechanisms at work remain uncertain. Here, a dynamically consistent ocean state estimate is utilized to study the large-scale integrated heat content variations during ENSO events for the global ocean. The full-depth GOHC exhibits a cooling tendency during the peak and decaying phases of El Niño, which is a result of the negative surface heat flux (SHF) anomaly in the tropics (30°S–30°N), partially offset by the positive SHF anomaly at higher latitudes. The tropical SHF anomaly acts as a lagged response to damp the convergence of oceanic heat transport, which redistributes heat from the extratropics and the subsurface layers (100–440 m) into the upper tropical oceans (0–100 m) during the onset and peak of El Niño. These results highlight the global nature of the oceanic heat redistribution during ENSO events, as well as how the redistribution process affects the full-depth GOHC. The meridional heat exchange across 30°S and 30°N is driven by ocean current anomalies, while multiple processes contribute to the vertical heat exchange across 100 m simultaneously. Heat advection due to unbalanced mass transport is distinguished from the mass balanced one, with significant contributions from the meridional and zonal overturning cells being identified for the latter in the vertical direction. Results presented here have implications for monitoring the planetary energy budget and evaluating ENSO’s global imprints on ocean heat content in different estimates.
Composite picture to help to study and to define a Regional Economic Intelligence System

: Economic Intelligence is a French conception of organisational sustenance by an improvement of information management. At the end of 1990, this consideration emerged from the concepts of Competitive Intelligence, Business Intelligence and Knowledge Management, notably, being supported by French government. One of these applications is the Regional Economic Intelligence initiatives. The most prominent of these projects is the cluster of competitiveness call. But, it is not the only proposition, many other enterprise clusters initiatives or the Regional Economic Intelligence Devices (REID). Then, in front of this panel of different Territorial Economic Intelligence initiatives, we decided to propose a tool to help any decision-maker develop a Territorial Economic Intelligence Device. This might help shape the overview of some particular REID and other similar devices and it is associated with a tool to define a composite picture of the project of REID. These composite pictures are realized on the basis of information visualization technique of Chernoff faces. In this sense we have developed a methodology to identify the characteristics of a typical REID in terms of Economic Intelligence actions and other actions connected. We have associated these characteristics with quantification by parameters and these parameters were linked with a particular feature of Chernoff face.
DAReN: A Collaborative Approach Towards Reasoning And Disentangling

Computational learning approaches to solving visual reasoning tests, such as Raven’s Progressive Matrices (RPM), critically depend on the ability of the computational approach to identify the visual concepts used in the test (i.e., the representation) as well as the latent rules based on those concepts (i.e., the reasoning). However, learning of representation and reasoning is a challenging and ill-posed task, often approached in a stage-wise manner (first representation, then reasoning). In this work, we propose an endto-end joint representation-reasoning learning framework, which leverages a weak form of inductive bias to improve both tasks together. Specifically, we propose a general generative graphical model for RPMs, GM-RPM, and apply it to solve the reasoning test. We accomplish this using a novel learning framework Disentangling based Abstract Reasoning Network (DAReN) based on the principles of GM-RPM. We perform an empirical evaluation of DAReN over several benchmark datasets. DAReN shows consistent improvement over state-of-the-art (SOTA) models on both the reasoning and the disentanglement tasks. This demonstrates the strong correlation between disentangled latent representation and the ability to solve abstract visual reasoning tasks.
Provably curb man-in-the-middle attack-based ARP spoofing in a local network

Even today, internet users’ data security remains a significant concern. One problem is ARP poisoning, otherwise referred to as ARP spoofing. Such attacks are intended to exploit the identified ARP protocol vulnerability. Despite no straightforward remedy for ARP spoofing being apparent, certain actions may be taken to maintain one’s safety. The most basic and common defence against a poisoning attack is manually adding MAC and IP addresses to the static ARP cache table. However, this solution is ineffective for large networks where static entries require considerable time and effort to maintain, whether by human input or via special tools and settings for the static entries of network devices. Accordingly, this paper aimed to monitor network packet information and detect the behaviour of ARP poison attacks on operating systems, for instance Windows and Linux. The discovery and defence policy systematically and periodically check the MAC addresses in the ARP table, enabling alerts to be issued if a duplicate entry is detected. This enables the poison-IP address to be blocked before a reply is sent. Finally, the results showed that the superiority was successfully achieved in the detection, prevention and reporting mechanisms in the real-world environment.
Terms Suggestions Ideation Task Goals Domain / Data Knowledge Matched Documents Specification Evaluation Label Seeds

In this paper, we define the concept of exploratory labeling: the use of computational and interactive methods to help analysts categorize groups of documents into a set of unknown and evolving labels. While many computational methods exist to analyze data and build models once the data is organized around a set of predefined categories or labels, few methods address the problem of reliably discovering and curating such labels in the first place. In order to move first steps towards bridging this gap, we propose an interactive visual data analysis method that integrates human-driven label ideation, specification and refinement with machine-driven recommendations. The proposed method enables the user to progressively discover and ideate labels in an exploratory fashion and specify rules that can be used to automatically match sets of documents to labels. To support this process of ideation, specification, as well as evaluation of the labels, we use unsupervised machine learning methods that provide suggestions and data summaries. We evaluate our method by applying it to a real-world labeling problem as well as through controlled user studies to identify and reflect on patterns of interaction emerging from exploratory labeling activities. ACM Classification