bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Nautical Almanac Office as a computing centre and the founding of the Scientific Computing Service
Authors: Croarken Mary 
Published: November 2023

Abstract
Thefundamental purpose of HM Nautical Almanac Office was to calculate and publish accurate ephemerides to aid navigation and to assist astronomers. These ephemerides were published annually as the Nautical almanac. Comrie’s principle responsibilities as Superintendent of the NAO were the supervision and improvement of the publication of the Nautical almanac. As part of this work Comrie undertook a major revision of the Nautical almanac, incorporated in the 19 31 Nautical almanac which had remained more or less unaltered since 1834. He rearranged, rewrote, and enlarged it to make it both more useful and easier to read. Comrie’s mechanization of the computing methods used to prepare the Nautical almanac (described in Chapter 3) introduced other revolutionary changes for the NAO.
The creation of a national computing centre
Authors: Croarken Mary 
Published: November 2023

Abstract
Within a year of the Admiralty Computing Service becoming operational Todd, Sadler, and A. Erdelyi, an Admiralty scientific consultant during the war, realized that the degree of centralized computation they could offer within the Admiralty did not go far enough. The ACS did not operate on a large enough scale to run a fully equipped computing service. It was not economically feasible to install punched card machines or a differential analyser for example. In some cases, therefore, computing efficiency was sacrificed because the most suitable type of equipment was not available to the ACS. Those responsible for the ACS, Todd and Sadler, were of the opinion that only centralization at the national level would achieve the economies of scale necessary to provide a fully equipped service.
Computing machine developments at Cambridge and Manchester
Authors: Croarken Mary 
Published: November 2023

Abstract
In Britain in the late 1940s there were three main centres which became heavily, and successfully, involved in the development of electronic stored program computers. These three centres were the NPL Mathematics Division, Cambridge University, and Manchester University. The computer research at the NPL has already been discussed and was part of the work which the Mathematics Division carried out as part of its role as a national computing centre. At Cambridge and Manchester the situation was very different. At Cambridge the existing Mathematical Laboratory was used as a vehicle for computing machinery development. At Manchester the computing centre developed around the research interests of the engineers and mathematicians based at the university.
Classifying clauses
Authors: Hogger Christopher John 
Published: November 2023

Abstract
Clauses may be classified according to the number of positive and negative literals they contain.
A definite clause contains exactly one positive literal and zero or more negative literals.
Example— happy(chris) or ,eating(chris, apple_crumble)
A positive unit clause is a definite clause containing no negative literals.
Example—happy(chris)
A negative unit clause is a negative clause with exactly one negative literal.
Example— ,desirable(pop_music)
A unit clause is either a positive unit clause or a negative unit clause, as in the last two examples.
A negative clause contains zero or more negative literals and no positive literals.
Example— ,happy(chris) or ,eating(chris, sheep’s_brains)
Search strategy
Authors: Hogger Christopher John 
Published: November 2023

Abstract
Given any program P and any query Q, the choice of some computation rule determines a unique SLD-tree rooted at Q. This tree represents all the SLD computations that can be derived using that computation rule. In general, different computation rules applied to a given input set {P, Q} will determine different SLD-trees, although-as observed previously-all those trees will agree upon the computed answer set.
A typical interpreter implements some fixed computation rule, although there are some interpreters which allow the user to choose a rule from a range of alternatives. A common way of specifying one’s own computation rule without considering the interpreter is to define that rule via a meta-program M interposed between the interpreter and the object program {P, Q); the interpreter then executes M using its own rule, and this action in turn drives the execution of the object program in accordance with the defined rule. Whichever such arrangement is made, however, we always know that some unique SLD-tree has to be incrementally constructed by the interpreter in order that it may search for answers.
Adequacy of the SLD paradigm
Authors: Hogger Christopher John 
Published: November 2023

Abstract
In previous Themes we have described the basic workings of a computational formalism founded upon the following principles:
The scope of the present course permits only a brief consideration of these issues; moreover, we must leave many other important issues wholly unaddressed.
A definite-clause program determines, for each m-ary predicate symbol p appearing in it, some relation Rp which is a subset of um where H is the Herbrand domain of the language. Now consider any function f mapping un to
H where n&gt;O. Clearly every such function f can be trivially represented by a corresponding (n+1)-ary relation Rp satisfying
The lattice of models for a definite program
Authors: Hogger Christopher John 
Published: November 2023

Abstract
First, since we shall deal here only with (H-)models and (H-)interpretations, the prefix 'H-' will henceforth be omitted but assumed by default. We begin by recalling that a model is just a particular set of ground atoms deemed to be true. Our main interest is in the question of whether a given model makes more atoms true than it needs to in order to satisfy a given definite program—equivalently, whether that model includes any smaller models.
Fix point interpretation of the minimal model
Authors: Hogger Christopher John 
Published: November 2023

Abstract
The process by which the method in Theme 45 generates each interpretation Ik+l from its predecessor lk can be cast as the application of a function Tp:
This function, which is a total mapping from the powerset of B(P) to itself, is specific to the given program P (hence the subscript P in its name) and is defined as follows:
Clearly this definition just formalizes our earlier informal account of how one interpretation is obtained from another.
Given any function f defined on a partially-ordered set [S, ], it is of primary interest to know whether or not that function is monotonic and/or continuous. It is monotonic if and only if for all ueS and veS, f(u) f(v) whenever u v and it is continuous if and only if
Program completion in predicate logic
Authors: Hogger Christopher John 
Published: November 2023

Abstract
The construction of the completion Comp(P) when P is a predicate-logic program is slightly more complicated than in the propositional case. Consider first the simplest example in which P comprises just a single ground assertion
The completion must express that ‘q’ holds for ‘a’ and for that term only-that is, (VX)(q(X) iff X=a). The ‘if’ component of the latter sentence is obtained by generalizing the given clause for ‘q’, so that in place of q(a) we write
The completion semantics for finite failure
Authors: Hogger Christopher John 
Published: November 2023

Abstract
The construction of a consequence•-oriented semantics for the finite failure extension is more problematic than for pure Horn-clause programs and queries. In the latter case we have a particularly simple connection between logical meaning and operational meaning:
As soon as we include Jtiil calls in our language no such connection applies--- a program containing fail is not a construct of classical logic and so is not amenable to the notion of classical logical consequence. Nevertheless, a variety of analogous connections have been suggested. The best-known of these is based upon the so-called completion semantics, which relies upon two ideas:
Plausible Inference and Negation in Horn Clause Logic
Authors: Niblett T B 
Published: November 2023

Abstract
We elucidate the role of probabilistic techniques in plausible reasoning and provide reasons why the probabilistic calculus is not adequate by itself for plausible reasoning in expert systems. We suggest a logic-based framework which uses an informal notion of argument as the basis for its representation of certainty. We argue that much of the manipulation of arguments should be done with non-numeric certainties. Probability measures should be introduced only late in the reasoning process, if at all. This scheme is illustrated with examples of the construction and evaluation of arguments. Although much of our work is tentative, we believe that it provides a basis for a well founded knowledge-based approach to plausible reasoning in expert systems.
A Note On First-Order Theories of Individual Concepts and Propositions
Authors: Arbab B 
Published: November 2023

Abstract
Certain classes of sentences when formalized in first-order logic, may give rise to paradoxical conclusions. Within this class are sentences with one or more occurrences of such words as know, believe, aware, discover, and so on. McCarthy (1979) has introduced the first order theory of individual concepts and propositions as a formal language for representing such sentences. McCarthy’s formal language is intended to avoid paradoxical conclusions. This paper presents an example whose formalization in the latter language gives rise to similar paradoxical conclusions.
Learning of Causality by a Robot
Authors: Mowforth P H , Zrimec T 
Published: November 2023

Abstract
This paper describes an experiment in which a robot is allowed randomly to explore the domain of object-pushing via controlled experi ments. The experiments consist of recording signals from sensors before and after an action has taken place. Each experiment may be considered as a state transformation recorded as a sequence of attribute values. Treating each transformation as a training example, a large set of data was collected and subjected to rule induction. Robust and useful trans formations were discovered which were represented as a hierarchical qualitative model. Further, results show that an actor-oriented, co ordinate frame provides the most compact description for the problem. One final observation is that this style of experimentation offers the potential for closed-loop learning in that, unlike other domains, as far as the robot is concerned, its world is the oracle.
Varying Levels of Abstraction in Qualitative Modelling
Authors: Mozetičt I , Institute J Stefan , Bratko I , University E Kardelj , Institute J Stefan , Urbančič T , Institute J Stefan 
Published: November 2023

Abstract
We describe a formalism for hierarchically representing qualitative models at various levels of abstraction. The formalism is based on logic, namely on typed Horn clauses also known as database clauses. The notion of abstraction is realized through a hierarchy of types for the domains of predicates. The abstraction hierarchy can be used in gener ating explanations with an adjustable degree of detail; also in improving search efficiency in solving tasks of diagnosis and control, as well as the learning of qualitative models. Results obtained at a simpler, more abstract level, can be used to guide the search at a more detailed and combinatorially more complex level. The corresponding algorithms are presented as PROLOG programs and their behaviour studied on example problems including a qualitative model of the heart.
PR0M1s: Experiments in Machine Learning and Protein Folding
Authors: Kingt R D 
Published: November 2023

Abstract
The aim of these experiments is to test the use of machine learning as a tool for forming theorie,o, from data. A machine-learning program (PRoMrs) was developed to form rules for predicting protein secondary structure from primary structure-an important unsolved problem in molecular biology. PROMIS uses a top-down controlled hill-climbing beam search with the rules for predicting secondary structure being search states. Structured background knowledge is used to transform the search space and control generalization. Six rules were found that are humanly comprehensible and provide a chemically meaningful descrip tion of the important factors in formation of secondary structure.
Logic and learning: Turing’s legacy
Authors: Muggleton S 
Published: November 2023

Abstract
Turing’s best known work is concerned with whether universal machines can decide the truth value of arbitrary logic formulae. However, in this paper it is shown that there is a direct evolution in Turing’s ideas from his earlier investigations of computability to his later interests in machine intelligence and machine learning. Turing realised that machines which could learn would be able to avoid some of the consequences of Godel’s and his results on incompleteness and undecidability. Machines which learned could continuously add new axioms to their repertoire. Inspired by a radio talk given by Turing in 1951, Christopher Strachey went on to implement the world’s first machine learning program. This particular first is usually attributed to A.L. Samuel. Strachey’s program, which did rote learning in the game of Nim, preceded Samuel’s checker playing program by four years. Neither Strachey’s nor Samuel’s system took up Turing’s suggestion of learning logical formulae. Developments in this area were delayed until Gordon Plotkin’s work in the early 1970’s. Computer-based learning of logical formulae is the central theme of the research area of Inductive Logic Programming, which grew directly out of the earlier work of Plotkin and Shapiro. In the present paper the author describes the state of this new field and discusses areas for future development.
The Discovery of Propositions in Noisy Data
Authors: Tsukimoto Hiroshi , Morita Chie 
Published: November 2023

Abstract
In science, the discovery of propositions in noisy data is important. This discovery is the unsupervised inductive learning with pruning. This chapter presents an efficient algorithm to induce an appropriate proposition from noisy data. A brief outline of the algorithm follows. The frequency data are transformed into a probability vector. The probability vector is transformed into a logical vector. This logical vector is then approximated by a classical logical vector. The classical logical vector is transformed into a logical proposition. This proposition is subsequently reduced to a minimum one. In this algorithm, the most original feature is the pruning method, which is executed at the approximation step. Such pruning is possible due to the transformation from a probability vector to a logical vector. The transformation is possible because (1) a proposition is represented as a vector in Euclidean space and (2) the probability vector can be transformed into a logical vector by a correspondence between the logical vector and the probability vector. Experimental results show that this algorithm performs well and also show that the propositions obtained by the algorithm basically satisfy MDL criteria. We apply this method to some problems to discover appropriate propositions or rules.
Inductive Logic Programming With Large-Scale Unstructured Data
Authors: Bain Michael 
Published: November 2023

Abstract
We report some recent developments from an ongoing project in which a chess endgame domain is providing benchmark experimental tests for the study of concept learning. The King and Rook against King (KRK) endgame is simple enough in chess terms but provides concept learning tasks which can be demanding, as evidenced in previous studies by a number of authors. For learning systems these tasks have highlighted problems of representation, such as the ability to express the structural relationships to be found in learning examples, and other issues like correctness, compression and comprehensibility. Our current focus is on inductive logic programming methods which are based on previously developed systems for the generalization and specialization of normal logic programs. In the current work we are principally concerned with improving these methods to be able to handle more examples during learning. The main contribution of this work consists of a new method of incremental learning, together with new results on a set of concept learning problems taken from the KRK endgame domain.
An experiment with browsers that learn
Authors: Parson Rupert , Muggleton Stephen 
Published: November 2023

Abstract
World Wide Web (WWW) usage is increasing rapidly. Users waste time downloading pages that turn out to have no interest to them. Interesting pages are often overlooked. Modern browsers allow the user to specify search strings. This paper experimentally investigates a different approach based on learning user WWW pages preferences from examples. WWW users were drawn from a class of students. The experiments show that the inductive logic programming algorithm Progol gives overall significant predictive accuracy of user interests. However, the results are highly polarized. Some users are very predictable and others not. The polarization was surprisingly found to correlate in all cases with student exam performance. This work was conducted as part of Parson’s MSc thesis [7].
The spontaneous self-organization of an adaptive language
Authors: Steels Luc 
Published: November 2023

Abstract
The paper studies how a group of distributed agents may spontaneously and autonomously develop a language to refer to other agents in their environment by engaging in a series of language games. The language is adaptive in the sense that it expands or adjusts to the entry of new agents and new meanings. The paper describes the language formation mechanisms and details the results of computational simulations.
The paper proposes a set of mechanisms by which a group of distributed agents may develop autonomously a language for identifying other agents in their environment. The set of agents and the set of features used for making distinctions is open-ended. The language autonomously adapts by the individual actions of agents with only local interactions.
Hollerith and the origins c.1880-1907
Authors: Martin Campbell-Kelly 
Published: November 2023

Abstract
Both IBM and ICL have their origins in the punched-card machines invented by Herman Hollerith in the 1880s. In 1896 Hollerith incorporated a small business, the Tabulating Machine Company (TMC), to manufacture and market his machines in the United States. In 1904 a British operation, The Tabulator Ltd, was formed to develop the punched-card business in Britain; this firm was re-incorporated in 1907 as the British Tabulating Machine Company (BTM). It was from these two firms, TMC and BTM, that IBM and ICL were to evolve.
The tabulating-machine companies were, however, part of a wider industrial phenomenon: the emergence of the office-machine industry, which was really the forerunner of today’s computer and informationsystems industries.
An interlude: the Second World War, 1939-1945
Authors: Martin Campbell-Kelly 
Published: November 2023

Abstract
On 3 September 1939 Britain declared war on Germany, and in December 1941 war was declared upon Japan. Victory in Europe came on 8 May 1945, and Victory over Japan the following August. The six years of war were a hiatus in the economic development of Britain, for in that period everything was sacrificed to the national war effort: ‘Foreign investments were sold, women conscripted, capital was run down and not replaced, civilian consumption was drastically reduced, exports were cut back.’ British industry was in the van of the contribution to the national war effort, and its control over its own destiny was almost completely curtailed.
Rapid growth in a changing market, 1975-1979
Authors: Martin Campbell-Kelly 
Published: November 2023

Abstract
The New Range launch of October 197 4 was, so to speak, only the end of the beginning. There remained the monumental R&D and manufacturing challenge of actually bringing the machines and software into the field. This task was to consume most of ICL’s technical resources during 1975-78.
During this period, however, the market itself was undergoing changes as radical as the transition from punched-card machines to computers in the early 1960s. These changes were in terms of new products, notably small business systems and networks, and new competitors manufacturing IBM-compatible mainframes. The growth that Cross had built into his corporate plan was not, in the event, to prove adequate to sustain the escalating R&D costs. When he left, in December 1977, his successor Chris Wilson would be faced with the problem of how to cover the widening gap between earnings and R&D spending.
Summing up: ICL and the evolving information business
Authors: Martin Campbell-Kelly 
Published: November 2023

Abstract
The concept of an ‘information business’ is a relatively new one. Thus, if we consider the period prior to the Second World War, BTM and Powers-Samas, the forebears of ICL, were considered to be members of the ‘office-appliance trade’: they were viewed as manufacturers of office machines, and that is certainly how they saw themselves. With the merger of the punched-card companies to form ICT in 1959, ICT and its competitors were seen by industrial commentators as being in the ‘computer business’-it was only within the companies themselves that the broader vision of information systems was beginning to emerge. By the 1970s, however, ICL and the other mainstream computer companies were clearly seen as being in the information business: the computer was now regarded as a means to an end, and not an end in itself.
Virus control methodologies
Authors: Louw Eric 
Published: November 2023

Abstract
Chapter 4 laid the foundation of a model for dealing with computer viruses in large organizations. Guided by the structure of Duffy and Assad’s framework for IS security and control, a series of discussions on the various aspects of virus control was presented. These discussions, often drawing on material covered in Chapters 2 and 3, resulted in a number of small frameworks and methodologies. Taken together, these small frameworks and methodologies cover the full range of activities required to set up an effective organizational virus control programme. Each of them, together with the lessons derived from empirical research, constitutes an element in the total methodology presented in this chapter. The intention here is to draw together all this material into practical virus control methodologies for both small and large organizations to use. Before doing this, however, we need to sketch in the typical organizational environment within which these virus control methodologies (VCMs) will have to be planned and implemented.
Feeding and metabolism of Appendicularia
Authors: Deibel D 
Published: November 2023

Abstract
Lohmann (1898, 1899, 1909a, 1933) was the first investigator to recognize the true function of the appendicularian house, which is to concentrate and collect particulate matter from the sea for feeding. He examined the gut contents of Oikopleura albicans and in this way identified an entirely new size class of plankton in the sea, which he called ‘nanoplankton’ (Lohmann, 1909a). The structure of the house is described in detail in Chapter 6; it is remarkably complex and its operation is only well understood in detail in a few oikopleurid species, and less well in a single fritillariid. Essentially, there are in oikopleurids usually three filters involved in food collection; their structure determining the size class of particles a given species can feed upon. The inhalent flow produced by oscillation of the tail draws water into the house via an external relatively coarse filter, then a food collecting filter or trap concentrates particulate material, which is drawn along a short tube to the mouth by the action of spiracular cilia. After entering the pharynx, the particles are trapped on a mucous filter and they enter the oesophagus.