Traditional AI Research Articles

Endocrine profiles of somatic nuclear transfer-derived pregnancies in dairy cattle

In cattle, several hormones and proteins are necessary for maintenance of a normal pregnancy that will result in a viable calf. Deviation from the normal cascade or expected profile of reproductive hormones and proteins may be associated with impairment of somatic nuclear transfer-derived pregnancies and the high rate of fetal loss. The objectives of this study were to characterize maternal plasma concentrations of pregnancy-specific protein B (PSPB), progesterone (P4), estrone sulphate (E1S), and estradiol (E2) during the last two-thirds of pregnancy (cloned calves), and to determine associations with gestational abnormalities. Cows with cloned fetuses, produced by either commercial (N = 16) or zona-free (N = 4) cloning techniques, were compared with pregnant animals derived from traditional embryo transfer (N = 6) or AI (N = 6), at various stages of gestation (Days 80, 120, 150, 180, 210, and 240; Day 0 = estrus). Fetal well-being was monitored with ultrasonography throughout gestation. At Day 80, progesterone concentration was lower (P < 0.0001) in nuclear transfer (NT) recipients than in control groups. Mean estrone sulphate concentrations did not vary significantly between NT and control groups. At Day 150, pregnancy-specific protein B concentrations were elevated (P < 0.002) in NT cows. Estradiol concentration was higher in NT recipients than control cows throughout the study period.

Soft Computing: A Continuously Evolving Concept

Abstract. Soft Computing (SC) is a concept with constantly evolving semantics, as researchers have adopted its main philosophy while adding various interpretations and facets to this concept. Originally defined as a loose association or partnership of components, SC has gone through several transformational phases. This paper will trace some of the phases experienced by the author as part of his understanding of the evolution of SC and its role in constructing decision-making models. The first phase is the hybridization phase, driven by the inherit ease of integration of SC components. The second phase is a two-level model characterization, based on the split between object-level and meta-level reasoning. This phase, inspired by traditional AI problem formulation, led to a third phase, in which we addressed the knowledge and meta-knowledge representation required by each of these reasoning levels using a linguistics analogy. The fourth phase is the extension of the heuristics used at the metalevel, e.g. M...

What is the Semantic Web and What Will it Do for eScience?

The paper discusses what kind of entity the proposed Semantic Web (SW) is, in terms of the relationship of natural language structure to knowledge representation (KR). It argues that there are three distinct views on the issue: first, that the SW is basically a renaming of the traditional AI knowledge representation task, with all the problems and challenges of that task. If that is the case, as many believe, then there is no particular reason to expect progress in this new form of presentation, as all the traditional problems of logic and representation reappear and it will be no more successful outside the narrow scientific domains where KR seems to work even though the formal ontology movement has brought some benefits. The paper contains some discussion of the relationship of current SW doctrine to representation issues covered by traditional AI, and also discusses issues of how far SW proposals are able to deal with difficult relationships in parts of concrete science. Secondly, there is a view that the SW will be the WorldWideWeb with its constituent documents annotated so as to yield their content or meaning structure more directly. This view of the SW makes natural language processing central as the procedural bridge from texts to KR, usually via a form of automated Information Extraction. This view is discussed in some detail and it is argued that this is in fact the only way of justifying the structures used as KR for the SW. There is a third view, possibly Berners-Lee's own, that the SW is about trusted databases as the foundation of a system of web processes and services, but it is argued that this ignores the whole history of the web as a textual system, and gives no better guarantee of agreed meanings for terms than the other two approaches.

Optimizing IVF with sexed sperm in cattle

Sperm-sorting by flow cytometry separates X-sperm from Y-sperm with an accuracy as high as 90% or more. This technology offers farmers and the livestock industry the potential to nearly double productivity, by producing the desired sex to optimize breeding programs. Sorting speed and fertility variation of sorted sperm, however, remain limiting factors for widespread application, particularly in traditional AI programs. Alternatively, in vitro fertilization is a feasible and efficient means to increase the fertilization efficiency of sex-sorted sperm in cattle. Procedures to increase fertilization rate and improve embryo quality include optimizing heparin concentrations for semen of each bull, reducing fertilization drop size to increase sperm concentration, use of fructose instead of glucose in culture media, and use of vitrification protocols with extremely rapid cooling and warming rates.

Artificial intelligence: a systems approach

This book offers students and AI programmers a new perspective on the study of artificial intelligence concepts. The essential topics and theory of AI are presented, but it also includes practical information on data input & reduction as well as data output (i.e., algorithm usage). Because traditional AI concepts such as pattern recognition, numerical optimization and data mining are now simply types of algorithms, a different approach is needed. This sensor / algorithm / effecter approach grounds the algorithms with an environment, helps students and AI practitioners to better understand them, and subsequently, how to apply them. The book has numerous up to date applications in game programming, intelligent agents, neural networks, artificial immune systems, and more. A CD-ROM with simulations, code, and figures accompanies the book. *Features *Covers not only AI theory, but modern applications e.g., game programming, machine learning, swarming, artificial immune systems, genetic algorithms, pattern recognition, numerical optimization, data mining, and more *Discusses the various computer languages of AI from LISP to JAVA and Python *Includes a CD-ROM with 100MB of simulations, code, and fi gures *Table of Contents 1. Introduction. 2. Search. 3. Games. 4. Logic. 5. Planning. 6. Knowledge Representation. 7. Machine Learning. 8. Probabilistic Reasoning. 9. Stochastic Search. 10. Neural Networks. 11. Intelligent Agents. 12. Hybrid Models. 13. Languages of AI.

Application of extension theory in misfire fault diagnosis of gasoline engines

A misfire fault diagnosis method in gasoline engines is proposed by extension theory. The extension diagnosis method is based on the matter-element model and extended correlation function for the misfire fault diagnosis of gasoline engines. First, the matter-element models of the engine fault are built according to diagnostics derived from specialists’ knowledge of practical experience and then, the fault types of misfire in engines can be directly identified by relation indices. The validity and reasonability of the proposed method is verified by the experimentation of EQ6102 engine. Diagnosis results show that the proposed method cannot only diagnose the main fault types of engines and can also detect useful information for future trends by the relation indices. This fault diagnosis method is easier and more practical than other traditional AI methods. Therefore, it will be favorable to diagnose the engine fault.

Ultrasonographic and histological characterization of the placenta of somatic nuclear transfer-derived pregnancies in dairy cattle

The high incidence of pregnancy loss and prenatal morbidity and mortality in cloned animals may be due to placental insufficiency, thereby compromising fetal survival. Our objective was to characterize morphological changes in fetal membranes of cloned bovine pregnancies. Two groups of cows with cloned fetuses, produced by two cloning techniques, a commercial group (n=16) and a hand-made group (n=4), and control fetuses derived from traditional embryo transfer (n=6) or AI (n=6), were compared at various stages of gestation (Days 80, 120, 150, 180, 210, and 240; Day 0=estrus). Thickness and shape of the amniotic membrane, placentome shape and length, umbilical cord shape and diameter, and fetal fluid echodensities were assessed by ultrasonography, and the placenta was evaluated histologically. Only eight (40%) of cloned pregnancies reached term and seven calves (35%) were alive at birth. Both placentome length and umbilical cord diameter were larger (P<0.05) in clones than in normal fetuses at all stages of gestation. Amniotic membrane abnormalities (Day 120) including focal edema and the presence of a series of nodules were detected in 38% of the clones and were always accompanied by hyper-echodense spikes or irregularities (detected ultrasonographically) around the umbilical cord. Histopathology revealed degenerate inflammatory cells, edematous chorioallantoic membranes, and decreased epithelial thickness. We inferred that these morphological anomalies of placentomes compromised fetal development, and we concluded that ultrasonographic monitoring of pregnancies enabled characterization of changes in the placentae and may be useful to assess fetal well-being.

반응형 계획에 기초한 자동화된 시맨틱 웹서비스의 조합

최근 들어 인공지능 계획기법을 이용하여 자동화된 시맨틱 웹서비스들 간의 조합을 구현하려는 연구들이 활발하게 이루어지고 있다. 하지만 일반적으로 전통적인 인공지능 계획기법들은 복잡한 제어구조를 포함하는 웹서비스 프로세스를 하나의 단위 행동이나 계획으로 표현하기 어렵고, 온톨로지에 포함된 의미 정보들을 계획생성에 충분히 반영할 수 없으며, 웹서비스들 사이의 입출력 데이터 흐름을 직접 모델링할 수 없고, 계획단계와 실행단계가 분리되어 있어 웹서비스 실행단계의 불확실성과 가변성을 계획단계에서 충분히 고려할 수 없다는 등의 한계점을 가지고 있다. 본 연구에서는 이러한 문제점들을 해결하기 위한 접근 방법으로서 반응형 계획을 이용한 시맨틱 웹서비스 조합을 제안하고, 프로토타입 시스템인 SWEEP을 구현하였다. e-Commerce 분야의 예제 웹서비스들을 대상으로 실험을 통해, 우리는 반응형 계획이 자동화된 시맨틱 웹서비스의 조합과 실행을 구현하기 위한 효과적인 기술임을 확인할 수 있었다. Recently, there have been a lot of works trying to realize automated composition of semantic web services though application of AI planning techniques. The traditional AI planning techniques, however, have some limitations: it is not easy to represent a web service process with complex control constructs as an action or a plan; it is hardly possible to consider enough the rich information contained in domain ontologies during the planning process; it is impossible to model directly the data flow from the outputs of a web service to the inputs of another web service; it is difficult to predict and deal with uncertainty and dynamics of the environment because the plan generation phase is supposed to be separated from the plan execution phase. In order to overcome some of these limitations, this paper suggests a reactive planning approach to automated composition of semantic web services. Through some experiments using several e-commerce web services, we found that the reactive planning is an effective way to realize automated composition of semantic web services.

Using AI and games for decision support in command and control

Developers of tomorrow's command and control centers are facing numerous problems related to the vast amount of available information obtained from various sources. On a lower level, huge amounts of uncertain reports from different sensors need to be fused into comprehensible information. On a higher level, representation and management of the aggregated information will be the main task, with prediction of future course of events being the uttermost goal. Unfortunately, traditional agent modeling techniques do not capture situations where commanders make decisions based on other commanders' reasoning about one's own reasoning. To cope with this problem, we propose a decision support tool for command and control situation awareness enhancements based on game theory for inference and coupled with traditional AI methods for uncertainty modeling.

Searching for computational creativity

Boden’s1,2) philosophical account of creativity has been criticised on the grounds that it does not properly capture some aspects of creative situations.5) Wiggins13) has presented a formalisation of Boden’s account, which allows such issues to be examined more precisely. We explore the relationship between traditional AI search methods and Boden’s abstraction of creative behaviour, and revisit Bundy’s argument in the context of that exploration.

Knowledge Is Power: A View from the Semantic Web

emerging Semantic Web focuses on bringing knowledge representationlike capabilities to Web applications in a Web-friendly way. ability to put knowledge on the Web, share it, and reuse it through standard Web mechanisms provides new and interesting challenges to artificial intelligence. In this paper, I explore the similarities and differences between the Semantic Web and traditional AI knowledge representation systems, and see if I can validate the analogy The Semantic Web is to KR as the Web is to hypertext.

364 DISTRIBUTION OF OVULATION AND SUBSEQUENT EMBRYO PRODUCTION USING LUTROPIN AND ESTRADIOL-17β FOR TIMED AI OF SUPERSTIMULATED BEEF FEMALES

This experiment was designed to compare timing of ovulation and embryo production between traditional superstimulatory and AI methods and the use of additional treatments of Estradiol-17β and pLH (Lutropin; Bioniche Animal Health, Belleville, Ontario, Canada) to facilitate timed AI in beef cows. A total of 31 mature cross-bred beef cows were randomly assigned three treatments. On Day 0, experimental cows were selected upon transrectal ultrasound evaluation for corpus leutum (&gt;10 mm) prior to CIDR insertion plus 2.5 mg estradiol-17β and 50 mg Progesterone i.m. Superstimulatory treatments with Folltropin-V (Bioniche Animal Health) began on Day 4 for 3.5 days (236 mg NIH-FSH-P10) in decreasing dosages (7 injections at 0700 and 1900). All cows received prostaglandin F (PGF) treatments of 625 mcg D-cloprostenol i.m. (Estrumate; Schering-Plough, Union, NJ, USA) in both AM and PM on Day 6, and CIDRs were removed in AM of Day 7, followed by the final injection of Folltropin. In addition, Heat Watch patches (Heat Watch; Cow Chips, Denver, CO, USA) were applied to optimize heat detection. Donors selected as control treatment were AI at 12 and 24 h post-onset of estrus (first mount) with frozen semen from the same bull. Donors selected on the Estradiol-17β treatment received 1 mg i.m. 12 h after CIDR removal and timed AI at 24 and 36 h. Donors selected for Lutropin treatment received 12.5 mg (5cc i.m.) 24 h after CIDR removal and were timed AI at 12 and 24 h. All AI procedures used 2 units from the same bull. All cows were examined by ultrasonography every 8 h beginning 24 h post-CIDR removal and ending at 60 h to determine the time and distribution of ovulation. Ovulation was determined by the disappearance of follicles (&gt;12 mm) from the prior examination. All AI and ultrasound procedures were performed by the same technician. There were no differences detected between the three treatments as evaluated by all the variables we studied (Table 1). However, donors treated with Lutropin tended to produced more viable embryos per collection and had a tighter degree of distribution of ovulations. Donors treated with Estradiol-17β tended to have fewer viable embryos. More research is needed to determine if donors can be timed AI without regard to estrus. Table 1. Mean onset of estrus, distribution of ovulation, and embryo production in superstimulated beef donors treated with Estradiol-17β, and Lutropin

An Active Symbols Theory of Chess Intuition

The well-known game of chess has traditionally been modeled in artificial intelligence studies by search engines with advanced pruning techniques. The models were thus centered on an inference engine manipulating passive symbols in the form of tokens. It is beyond doubt, however, that human players do not carry out such processes. Instead, chess masters instead carry out perceptual processes, carefully categorizing the chunks perceived in a position and gradually building complex dynamic structures to represent the subtle pressures embedded in the positions. In this paper we will consider two hypotheses concerning the underlying subcognitive processes and architecture. In the first hypothesis, a multiple-leveled chess representational structure is presented, which includes distance graphs (with varying levels of quality) between pieces, piece mobilities, and abstract roles. These representational schemes seem to account for numerous characteristics of human player's psychology. The second hypothesis concerns the extension of the architecture proposed in the Copycat project as central for modeling the emergent intuitive perception of a chess position. We provide a synthesis on how the postulated architecture models chess intuition as an emergent mixture of simultaneous distance estimations, chunk perceptions, abstract role awareness, and intention activations. This is an alternative model to the traditional AI approaches, focusing on the philosophy of active symbols.

Moving AI out of its infancy: changing our preconceptions

Explicit symbolic logic has faded from prominence, but the close coupling of AI and the digital computer, and of thought and the stepwise algorithm, seem about as strong and unquestioned as ever. Of course there's connectionism, but this too is mired in false assumptions that date back a long way. And it seems to have dragged neuroscience down with it to the extent that we now seem unable to think about real brains without resorting to models that owe too much of their inspiration to the three-layer perceptron. Traditional AI has excelled at solving certain kinds of problems. It can make systems that learn but not in any generally applicable way. AI is about making machines do what humans use intelligence to do, and often this doesn't actually require the machines to show any intelligence at all. But for many tasks, especially in robotics, the ability to see, learn, and perform complex motor actions is a prerequisite that the traditional approach has utterly failed to fulfill.

The Architecture of a Wisdom Machine (WM)

In this paper, we propose that wisdom can be distilled from knowledge, knowledge can be derived from information, information can be gathered from data and finally data can be assembled, acquired, switched and channeled by the existing tools and techniques borrowed from computer science and network technology. A variety of data sensors activate the system and at the second level the traditional AI techniques will process the data through the information and the knowledge levels. The final pinnacle of wisdom is an all-human activity where the mind is the super-processor from information and knowledge derived from six computer systems (or subsystems). Each subsystem performs a step either in a sequential or a recursive mode of execution to either forward a new concept in the dictionary of Wisdom or it will link and classify the realm of current activity to an existing tree of knowledge or as minutia of known knowledge.

Natural Language Assistant: A Dialog System for Online Product Recommendation

With the emergence of electronic-commerce systems, successful information access on electroniccommerce web sites becomes essential. Menu-driven navigation and keyword search currently provided by most commercial sites have considerable limitations because they tend to overwhelm and frustrate users with lengthy, rigid, and ineffective interactions. To provide an efficient solution for information access, we have built the NATURAL language ASSISTANT (NLA), a web-based natural language dialog system to help users find relevant products on electronic-commerce sites. The system brings together technologies in natural language processing and human-computer interaction to create a faster and more intuitive way of interacting with web sites. By combining statistical parsing techniques with traditional AI rule-based technology, we have created a dialog system that accommodates both customer needs and business requirements. The system is currently embedded in an application for recommending laptops and was deployed as a pilot on IBM's web site.

Online algorithms supporting emergence in distributed CAD systems

The rule-based approach from traditional AI and the conventional constraint satisfaction algorithms are not adequate to cope with the unpredictable events and interactive computations in distributed CAD environments. This paper claims that the problems faced by distributed CAD systems require solutions based on the concepts of emergence, reactivity, and online algorithms. The present paper presents Extended Constraints Graphs (ECGs) as online algorithms supporting emergence in a network of reactive agents. ECGs represent an effective solution for the nonlinear constraint problem in cyclic graphs, which are distributed over a heterogeneous computer network. The relationships between agents in an ECG are generic, distributed, recursive and nonlinear — a problem not solved in the literature. Also this paper presents a CORBA model integrated with a Geometry Bus to support distributed virtual prototype whose variables can be defined in terms of ECGs.

Towards an Efficient Library for SAT: a Manifesto

Abstract Abstract In recent years, prepositional satisfiability (SAT) has become increasingly popular outside its traditional AI and automated reasoning niche. Applications from diverse fields require efficient and sophisticated SAT solvers that can be easily integrated into existing tools. In this paper we outline a path towards an efficient library for SAT that should meet the rising standards of research and applications. Our first milestone is SIM, a library for clausal SAT based on the well known Davis-Logemann-Loveland (DLL) method. SIM provides a choice of heuristics and optimizations that are found separately in most state-of-the-art DLL-based solvers, and extensive experimental evaluation confirms that SIM's generality does not hinder its performance.

The animat contribution to cognitive systems research

Through a review of the research efforts that were presented at the last SAB2000 conference, this article describes the animat contribution to adaptive behavior in animals and robots. It stresses how the animat approach and traditional AI endeavors should complement each other in the study of human cognition. It discusses the current successes and drawbacks of animat research.

Angiotensin-converting enzyme and apolipoprotein B polymorphisms in coronary artery disease

The association between angiotensin-converting enzyme (ACE) as well as apolipoprotein B polymorphisms and dyslipidemia and coronary artery disease (CAD) is controversial. We assessed the distribution of ACE insertion and/or deletion, apolipoprotein B signal peptide insertion and/or deletion, and apolipoprotein B XbaI restriction fragment length polymorphisms in 388 nondiabetic patients. We studied 112 patients with angiographically defined asymptomatic CAD or with stable functional classes I and II angina and 139 patients with acute myocardial infarction who were age matched to 137 control subjects. Univariate analysis showed higher prevalence of XbaI X+/X+ genotype in patients with CAD (p = 0.02). ACE and apolipoprotein polymorphisms were not associated with lipid levels and the number of major coronary artery vessels with >50% reduction of lumen diameter. Overall, multivariable regression disclosed traditional risk factors and elevated levels of apolipoprotein B for men and reduced levels of apolipoprotein AI for women as independent variables for CAD. After adjustment for the most important subset of risk factors (age, hypertension, hypercholesterolemia, and smoking), apolipoprotein B XbaI polymorphism was disclosed as an independent variable for CAD. Apolipoprotein B XbaI was also selected as an independent variable for acute myocardial infarction after adjusting for age, hypertension, hypercholesterolemia, and smoking. Thus, in addition to traditional coronary risk factors, apolipoproteins B and AI, and apolipoprotein B XbaI polymorphism could be considered predictors of CAD.