Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of the farmer field school approach on small-scale vegetable producers' knowledge and production in Alice, Eastern Cape, South Africa

This paper investigates the impact of the farmer field school approach on the knowledge and production of small-scale vegetable producers, namely home gardeners. Farmer field schools were developed in the 1980s by the Food and Agriculture Organisation as a form of adult education in agriculture. It is a group-based approach in which a facilitator meets with producers on a regular basis and sets in motion a process by which producers ‘learn how to learn’. It remains an open question whether the farmer field school approach could be a solution to South Africa’s abiding problem of weak agricultural extension. In early 2015, the University of Fort Hare and the Nkonkobe Farmers’ Association initiated a number of study groups in the Alice area of the Eastern Cape Province of South Africa, based largely on farmer field school principles. The research findings reported in this article are part of an effort to determine to what extent these study groups had the desired effect. After administering surveys to 118 study group members, before and after comparisons were drawn with regards to members’ self-assessed knowledge and skills, and production levels of a number of garden vegetables. The findings revealed an impressive increase in self-assessed knowledge and skills, as well as in production, consumption and selling of vegetables. Based on these findings and given the current state of agricultural extension in South Africa, it can be recommended that expansion of the farmer field school approach takes place in other areas, while attempting to better understand the mechanisms underlying the improvements already observed.
Benchmarking elasticity of FaaS platforms as a foundation for objective-driven design of serverless applications

Application providers have to solve the trade-off between performance and deployment costs by selecting the "right" amount of provisioned computing resources for their application. The high value of changing this trade-off decision at runtime fueled a decade of combined efforts by industry and research to develop elastic applications. Despite these efforts, the development of elastic applications still demands significant time and expertise from application providers. To address this demand, FaaS platforms shift responsibilities associated with elasticity from the application developer to the cloud provider. While this shift is highly promising, FaaS platforms do not quantify elasticity; thus, application developers are unaware of how elastic FaaS platforms are. This lack of knowledge significantly impairs effective objective-driven design of serverless applications. In this paper, we present an experiment design and corresponding toolkit for quantifying elasticity and its associated trade-offs with latency, reliability, and execution costs. We present results for the evaluation of four popular FaaS platforms by AWS, Google, IBM, Microsoft, and show significant differences between the service offers. Based on our results, we assess the applicability of the individual FaaS platforms in three scenarios under different objectives: web serving, online data analysis, and offline batch processing.
Web Link Analysis: estimating a document’s importance from its context

The World Wide Web is a fascinating, useful, and important phenomenon of our time. It is also a graph—that is, a network, in which the nodes are Web pages and the links are one-way hyperlinks. This network view of the Web is basic to the challenging but practical endeavour of Web link analysis. Web link analysis takes the network of hyperlinks as a given input, and uses this information to give a quantitative score which estimates the importance of each page in the graph. In this article we give a pedagogical overview of the main ideas around, and mathematical approaches to, Web link analysis.
FP-Crawlers: Studying the Resilience of Browser Fingerprinting to Block Crawlers

Data available on the Web, such as financial data or public reviews, provides a competitive advantage to companies able to exploit them. Web crawlers, a category of bot, aim at automating the collection of publicly available Web data. While some crawlers collect data with the agreement of the websites being crawled, most crawlers do not respect the terms of service. CAPTCHAs and approaches based on analyzing series of HTTP requests classify users as humans or bots. However, these approaches require either user interaction or a significant volume of data before they can classify the traffic. In this paper, we study browser fingerprinting as a crawler detection mechanism. We crawled the Alexa top 10K and identified 291 websites that block crawlers. We show that fingerprinting is used by 93 (31.96%) of them and we report on the crawler detection techniques implemented by the major fingerprinters. Finally, we evaluate the resilience of fingerprinting against crawlers trying to conceal themselves. We show that although fingerprinting is good at detecting crawlers, it can be bypassed with little effort by an adversary with knowledge on the fingerprints collected.
TREATING PICA BY RECREATING THE SCENE

Two men with intellectual disability were treated for life-threatening pica using a modified "Recreate the Scene" methodology. Both men were prompted to attempt to engage in pica and then blocked and punished. A means to escape punishment was introduced. In both cases, the effects of pica were substantially ameliorated, and both men experienced significant improvements in life quality. Experimental design limitations prevent the assumption of a pure cause-effect relationship between treatment and effect. The treatment package was described in terms of the anxiety relief training model.
Trustless Groups of Unknown Order with Hyperelliptic Curves

Groups of unknown order are of major interest due to their applications including time-lock puzzles, verifiable delay functions, and accumulators. In this paper we focus on trustless setup: in this setting, the most popular unknown-order group construction is ideal class groups of imaginary quadratic fields. We argue that the full impact of Sutherland's generic group-order algorithm has not been recognised in this context, and show that group sizes currently being proposed in practice (namely, approximately 830 bits) do not meet the claimed security level. Instead, we claim that random group orders should be at least 3300 bits to meet a 128-bit security level. For ideal class groups this leads to discriminants of around 6656 bits, which are much larger than desirable. One drawback of class groups is that current approaches require approximately 2log_2(N) bits to represent an element in a group of order N. We provide two solutions to mitigate this blow-up in the size of representations. First, we explain how an idea of Bleichenbacher can be used to compress class group elements to (3/2)log_2(N) bits. Second, we note that using Jacobians of hyperelliptic curves (in other words, class groups of quadratic function fields) allows efficient compression to the optimal element representation size of log_2(N) bits. We discuss point-counting approaches for hyperelliptic curves and argue that genus-3 curves are secure in the trustless unknown-order setting. We conclude that in practice, Jacobians of hyperelliptic curves are more efficient in practice than ideal class groups at the same security level---both in the group operation and in the size of the element representation.
Use case specifications: How complete are they?

The flexibility of the use cases in specifying requirements from informal textual descriptions to more formal ones makes them usable in different contexts and purposes. However, the versatility of use cases regarding their admissible structure raises a natural concern about the specification completeness. This paper reports on the analysis of the eight different variants of use case template regarding their functional completeness, ability to express the set of particular functionalities, by comparing their information contents exercised by comprehensive questionnaires on five different problem specifications. The questionnaire was obtained from two sources: one based on the understanding of the functionality to be implemented and the other based on the functionality documented in eight different use case templates under study. Our results suggested that use cases can be used to specify a complete set of requirements intended to develop a software system. We found that the choice of a use case template influences the completeness of the specification. A more detailed analysis of the eight different variants of use case template resulted in the identification of 21 significant use case elements. We showed that by incorporating these significant use case elements in a given template, the completeness of the specification could be further enhanced.
On the Security Goals of White-Box Cryptography

We discuss existing and new security notions for white-box cryptography and comment on their suitability for Digital Rights Management and Mobile Payment Applications, the two prevalent use-cases of white-box cryptography. In particular, we put forward indistinguishability for white-box cryptography with hardware-binding (IND-WHW) as a new security notion that we deem central. We also discuss the security property of application-binding and explain the issues faced when defining it as a formal security notion. Based on our proposed notion for hardware-binding, we describe a possible white-box competition setup which assesses white-box implementations w.r. t. hardware-binding. Our proposed competition setup allows us to capture hardware-binding in a practically meaningful way.While some symmetric encryption schemes have been proven to admit plain white-box implementations, we show that not all secure symmetric encryption schemes are white-boxeable in the plain white-box attack scenario, i.e., without hardware-binding. Thus, even strong assumptions such as indistinguishability obfuscation cannot be used to provide secure white-box implementations for arbitrary ciphers. Perhaps surprisingly, our impossibility result does not carry over to the hardware-bound scenario. In particular, Alpirez Bock, Brzuska, Fischlin, Janson and Michiels (ePrint 2019/1014) proved a rather general feasibility result in the hardware-bound model. Equally important, the apparent theoretical distinction between the plain white-box model and the hardware-bound white-box model also translates into practically reduced attack capabilities as we explain in this paper.
Hardware Private Circuits: From Trivial Composition to Full Verification

The design of glitch-resistant higher-order masking schemes is an important challenge in cryptographic engineering. A recent work by Moos et al. (CHES 2019) showed that most published schemes (and all efficient ones) exhibit local or composability flaws at high security orders, leaving a critical gap in the literature on hardware masking. In this article, we first extend the simulatability framework of Belaïd et al. (EUROCRYPT 2016) and prove that a compositional strategy that is correct without glitches remains valid with glitches. We then use this extended framework to prove the first masked gadgets that enable trivial composition with glitches at arbitrary orders. We show that the resulting “Hardware Private Circuits” approach the implementation efficiency of previous (flawed) schemes. We finally investigate how trivial composition can serve as a basis for a tool that allows verifying full masked hardware implementations (e.g., of complete block ciphers) at any security order from their HDL code. As side products, we improve the randomness complexity of the best published refreshing gadgets, show that some S-box representations allow latency reductions and confirm practical claims based on implementation results.
A Step towards Context Identification for Conversational Search

The system comprises of three different components. The first component makes a decision whether to incorporate contextual information for the current query in ongoing conversation. The decision is based on the KL-divergence between the retrieved documents for the original query and whether the query consists of pronouns. The second component identifies the contextual information (if required) for the answering the current query. This identification is performed using an SVM classifier which uses BERT attention weights along with other linguistic features. Finally, the third component utilises Indri for document retrieval.
Deterministic-Prover Zero-Knowledge Proofs

Zero-knowledge proof systems enable a prover to convince a veriﬁer of the validity of a statement without revealing anything beyond that fact. The role of randomness in interactive proofs in general, and in zero-knowledge in particular, is well known. In particular, zero-knowledge with a deterministic veriﬁer is impossible for non-trivial languages (outside of BPP ). Likewise, it was shown by Goldreich and Oren (Journal of Cryptology, 1994) that zero-knowledge with a deterministic prover is also impossible for non-trivial languages. However, their proof holds only for auxiliary-input zero knowledge and a malicious veriﬁer . In this paper, we initiate the study of the feasibility of zero-knowledge proof systems with a deterministic prover in settings not covered by the result of Goldreich and Oren. We prove the existence of deterministic-prover auxiliary-input honest-veriﬁer zero-knowledge for any NP language, under standard assumptions. In addition, we show that any language with a hash proof system has a deterministic-prover honest-veriﬁer statistical zero-knowledge proof, with an eﬃcient prover. Finally, we show that in some cases, it is even possible to achieve deterministic-prover uniform zero-knowledge for a malicious veriﬁer. Our contribution is primarily conceptual, and sheds light on the necessity of randomness in zero knowledge in settings where either the veriﬁer is honest or there is no auxiliary input.
Estratto Tesi di Laurea Metamolds Computational Design of Silicone Molds

We propose a new method for fabricating digital objects through reusable silicone molds. Molds are generated by casting liquid silicone into custom 3D printed containers called metamolds . Metamolds automatically deﬁne the cuts that are needed to extract the cast object from the silicone mold. The shape of metamolds is automatically designed through a novel segmentation technique, which takes into account both geometric and topological constraints involved in the process of mold casting. Our technique is simple, does not require to change the shape or the topology of the input objects, and only requires oﬀ-the-shelf materials and technologies. We successfully tested our method on a set of challenging examples with complex shapes and rich geometric detail.
ECG Signal Processing and Analysis for Accurate Features Extraction

Heart is the most essential organ of the body which maintain the circulation of blood to various parts of the human body. Arrhythmia, a rhythmic disorder of the heart due to which heart cannot pump blood properly. The main purpose of this work to extract potential biomarkers of arrhythmia using two algorithms: Pan-Tompkins Algorithm and Wavelet based algorithm. ECG signals used in the system were downloaded from the MIT-BIH arrhythmia database. These signals were then imported to MATLAB and pre-processed. QRS complexes of the ECG signal are accurately detected by using the abovementioned algorithms. Features including QRS duration, RR interval and PR interval were accurately calculated for the entire dataset. Performance of the two algorithms done based on accuracy of the QRS detector.
Corpus-based Acquisition and Analysis of Support Verb Constructions

This thesis deals with Support Verb Constructions (SVCs) and their automatic acquisiton. SVCs are verbal strucures, consisting of a verb and a noun, which form a unit in both syntactic and semantic aspects. As SVCs are hard to interpret on both counts, they are especially challenging for natural language processing. We test the possibilities of the acquisiton of SVCs by means of corpusbased methods with few linguistic resources. In particular, we investigate the phenomenon in Portuguese. The acquisition is carried out in a two-stage approach. First, we extract SVCs using a bilingual parallel corpus. Starting from a list of Portuguese full verbs which approximately correspond to the meaning of an SVC, we use the alignment information to retrieve Portuguese expressions which are semantically appropriate SVCs. In this context, the parallel language acts as a ‘pivot’ to connect the Portuguese full verb and SVCs. In the next step, we analyse the possibilities to refine the retrieved expressions. It turns out that it is difficult to use information about the support verb’s arguments to do such a filtering. Instead, we calculate association measures (e.g. pointwise mutual information) and compile a ranking. This second step, thus, is conducted on the monolingual level. The experiments show that the presented approach works very well: we retrieve semantically appropriate SVCs and achieve a maximum precision of 91% and a maximum recall of 86% in two different settings. However, the applicability of the approach depends on the contextual diversity of the initial full verb. Heterogeneity complicates the acquisition of high quality SVCs.
Modeling of the Snowdrift in Cold Regions: Introduction and Evaluation of a New Approach

Unbalanced, or non-uniform, snow loads caused by snow drifting or sliding in cold regions with heavy snowfalls, can be a serious problem for the building industry. However, the methods for predicting snow distribution still need to be improved. Field observation is the most direct and reliable method to study snow distribution, but because the natural environment is uncontrollable and varies dramatically, sometimes conclusions may be confused under the influence of the many variables in the investigation. This paper proposes a snowing experiment approach using an outdoor snow–wind combined experiment facility for the study of snow distribution. The facility can produce a stable and controllable wind field and snowfall environment. Experiments which focused on snowdrift around a building were conducted during the winter to make an evaluation of the repeatability and reliability of the new approach. Finally, from the analysis of results, it was demonstrated that the experimental facility was stable and that the similarity criterion adopted for the snowing pattern was reliable. Especially, the minimum value of the friction speed ratio was suggested to ensure the test accuracy.
Evaluating Mixed Integer Programming Models for Solving Stochastic Inventory Problems

We formulate mixed integer programming (MIP) models to obtain approximate solutions to finite horizon stochastic inventory models. These deterministic formulations of necessity make a number of simplifying assumptions, but their special structure permits very short model solution times under a range of experimental conditions. We evaluate the performance of these models using simulation optimization to estimate the true optimal solutions. Computational experiments identify several demand and cost scenarios in which the MIP models yield near-optimal solutions, and other cases where they fail, suggesting directions for future research.
How Does Terrorism Lend Itself to Constructivist Understanding?

Since the 9/11 attacks, traditional IR scholars have been finding it quite difficult to understand the War on Terror (WoT), the working of al-Qaeda, or anything to do with its Islamic ideologies. Rationalist approaches such as Realism and Liberalism, hardly had anything to contribute to the understanding of 9/11 attacks motivated by religious convictions. ‘Constructivism seemed best placed in evaluating terrorism,’ though constructivist exploration into terrorism has been few and far between (Lynch, 2006).
A Few-Shot Practical Behavioral Biometrics Model for Login Authentication in Web Applications

—Risk based authentication has been advocated as complement to traditional authentication mechanisms in order to raise the bar against attackers in possession of stolen credentials. Behavioral biometrics has received attention in the literature in the past decade, however the best results have been obtained in the so-called continuous setting and with enough training data, usually spanning several hours of user interaction. In this paper we explore the more challenging scenario of behavioral biometrics as an effective risk-based authentication technique using both mouse and keyboard information at login time (static authentication), assuming only between 3 and 7 login sessions per user for training. In a controlled but realistic experiment with 89 subjects we achieve a FRR of 10.73% and FAR of 23.34% for a model trained using only 5 login attempts, each performed in less than 30 seconds on average. We also evaluate our prototype with 2000 users from production data in the banking domain.
Likely striping in stochastic nematic elastomers

For monodomain nematic elastomers, we construct generalised elastic–nematic constitutive models combining purely elastic and neoclassical-type strain energy densities. Inspired by recent developments in stochastic elasticity, we extend these models to stochastic–elastic–nematic forms, where the model parameters are defined by spatially independent probability density functions at a continuum level. To investigate the behaviour of these systems and demonstrate the effects of the probabilistic parameters, we focus on the classical problem of shear striping in a stretched nematic elastomer for which the solution is given explicitly. We find that, unlike the neoclassical case, where the inhomogeneous deformation occurs within a universal interval that is independent of the elastic modulus, for the elastic–nematic models, the critical interval depends on the material parameters. For the stochastic extension, the bounds of this interval are probabilistic, and the homogeneous and inhomogeneous states compete, in the sense that both have a a given probability to occur. We refer to the inhomogeneous pattern within this interval as ‘likely striping’.
Neural Models for Simple Algorithmic Games

In the past few years there has been a resurgence of work on neural models for game playing [5, 2, 6]. Several works have also demonstrated the ability of neural models to learn to answer common-sense questions about a restricted environment [11], and to carry out simple algorithms, such as sorting and reversal of inputs [1, 9, 3, 13]. In [5, 2, 6, 3, 13] the models were trained with reinforcement learning or using discrete search, allowing possibly delayed rewards with discrete action spaces.
Current status of SPIDER CODAS and its evolution towards the ITER compliant NBI CODAS

Abstract– The ITER Neutral Beam Test Facility currently under construction at Padova, Italy, consists of two experiments: SPIDER to test the ITER-size ion source with -100 kV acceleration potential, and MITICA to test the full ITER Neutral Beam Injector operating at -1 MV acceleration potential. While the former represents an intermediate step, also finalized to the ITER Diagnostic Neutral Beam, the latter will represent the final design and implementation of the full prototype of the ITER Heating Neutral Beams. Consequently, for the Control and Data Acquisition System (CODAS) of SPIDER there are no requirements for compliance with ITER CODAC, whereas the MITICA Heating Neutral Beam Plant System will comply with the ITER directives for CODAC management because that final system will be eventually integrated in ITER. SPIDER CODAS is currently under commissioning and the integration of the different frameworks that operate in an integrated way proved successful. The experience and solutions gained in SPIDER CODAS development will be reused as far as possible in MITICA and to provide at the same time the required CODAC compatibility, a set of ITER-like layers (networks) will be defined, using exactly the same protocol defined for ITER interfaces.