A characterization of (regular) circular languages generated by monotone complete splicing systems

Circular splicing systems are a formal model of a generative mechanism of circular words, inspired by a recombinant behaviour of circular DNA. Some unanswered questions are related to the computational power of such systems, and finding a characterization of the class of circular languages generated by circular splicing systems is still an open problem. In this paper we solve this problem for monotone complete systems, which are finite circular splicing systems with rules of a simpler form. We show that a circular language L is generated by a monotone complete system if and only if the set Lin(L) of all words corresponding to L is a pure unitary language generated by a set closed under the conjugacy relation. The class of pure unitary languages was introduced by A. Ehrenfeucht, D. Haussler, G. Rozenberg in 1983, as a subclass of the class of context-free languages, together with a characterization of regular pure unitary languages by means of a decidable property. As a direct consequence, we characterize (regular) circular languages generated by monotone complete systems. We can also decide whether the language generated by a monotone complete system is regular. Finally, we point out that monotone complete systems have the same computational power as finite simple systems, an easy type of circular splicing system defined in the literature from the very beginning, when only one rule of a specific type is allowed. From our results on monotone complete systems, it follows that finite simple systems generate a class of languages containing non-regular languages, showing the incorrectness of a longstanding result on simple systems.     

Non-confluence in divisionless P systems with active membranes

We describe a solution to the SAT problem via non-confluent P systems with active membranes, without using membrane division rules. Furthermore, we provide an algorithm for simulating such devices on a nondeterministic Turing machine with a polynomial slowdown. Together, these results prove that the complexity class of problems solvable non-confluently and in polynomial time by this kind of P system is exactly the class .     

Combining knowledge from different sources

Abstract: The present paper deals with the problem of an assessment of symptoms in medical diagnosis. A unified interpretation of symptoms is necessary to estimate their significance in a diagnosis. Yet, even if they are properly defined, different evaluations of them based on experts' knowledge or statistical estimation are possible. The present study aims at combining evaluations that may originate from an expert or can be found from statistical features of the data, as well as those determined for 'easy' and 'difficult' diagnostic cases. A model of diagnostic inference is proposed in the framework of the Dempster–Shafer theory extended for fuzzy focal elements. The basic probability assignment defined in this theory estimates weights of symptoms. Two basic probability assignments can be created and then combined. In this way weights of symptoms represent knowledge common for two kinds of data or obtained from an expert and from data. Thus, a combination of heuristics and data mining results becomes possible. An algorithm of the basic probability assignment calculation is suggested and tested for medical data: a database from the internet and individually gathered data.     

An integrated approach for rating engineering characteristics’ final importance in product-service system development

Product-service system (PSS) approach has emerged as a competitive strategy to impel manufacturers to offer a set of product and services as a whole. A three-domain PSS conceptual design framework based on quality function deployment (QFD) is proposed in this research. QFD is a widely used design tool considering customer requirements (CRs). Since both product and services influence satisfaction of customer, they should be designed simultaneously. Identification of the critical parameters in these domains plays an important role. Engineering characteristics (ECs) in the functional domain include product-related ECs (P-ECs) and service-related ECs (S-ECs). ECs are identified by translating customer requirements (CRs) in the customer domain. Rating ECs’ importance has a great impact on achieving an optimal PSS planning. The rating problem should consider not only the requirements of customer, but also the requirements of manufacturer. From the requirements of customer, the analytic network process (ANP) approach is integrated in QFD to determine the initial importance weights of ECs considering the complex dependency relationships between and within CRs, P-ECs and S-ECs. In order to deal with the vagueness, uncertainty and diversity in decision-making, the fuzzy set theory and group decision-making technique are used in the super-matrix approach of ANP. From the requirements of manufacturer, the data envelopment analysis (DEA) approach is applied to adjust the initial weights of ECs taking into account business competition and implementation difficulty. A case study is carried out to demonstrate the effectiveness of the developed integrated approach for prioritizing ECs in PSS conceptual design.     

Integrating cognitive load theory and concepts of human–computer interaction

With the continually increasing complexity of e-learning environments, there is a need for integrating concepts of cognitive load theory (CLT) with concepts of human–computer interaction (HCI). Basic concepts of both fields were reviewed and contrasted. A literature review was conducted within the literature database “The Guide to Computing Literature,” searching for “cognitive load theory” and “Sweller.” Sixty-five publications contained “cognitive load” in their titles or abstracts. Each publication was checked to see whether it contained the concepts of intrinsic, extraneous, or germane cognitive load. The review showed that CLT concepts have been adopted in HCI. However, the concept of germane cognitive load has attracted less attention up to the present time. Two conceptual models are proposed. The first model divides extraneous cognitive load into load induced by the instructional design and load caused by software usage. The model clarifies the focus of traditional usability principles and of existing instructional design principles derived from CLT. The second model fits CLT concepts into the basic components of user-centered design. The concept of germane cognitive load illustrates that an increase of cognitive load can be desirable when designing e-learning environments. Areas for future interdisciplinary research are sketched.     

OWA rough set model for forecasting the revenues growth rate of the electronic industry

Business operation performance is related to corporation profitability and directly affects the choices of investment in the stock market. This paper proposes a hybrid method, which combines the ordered weighted averaging (OWA) operator and rough set theory after an attribute selection procedure to deal with multi-attribute forecasting problems with respect to revenue growth rate of the electronic industry. In the attribute selection step, four most-important attributes within 12 attributes collected from related literature are determined via five attribute selection methods as the input of the following procedure of the proposed method. The OWA operator can adjust the weight of an attribute based on the situation of a decision-maker and aggregate different attribute values into a single aggregated value of each instance, and then the single aggregated values are utilized to generate classification rules by rough set for forecasting operation performance.To verify the proposed method, this research collects the financial data of 629 electronic firms for public companies listed in the TSE (Taiwan Stock Exchange) and OTC (Over-the-Counter) market in 2004 and 2005 to forecast the revenue growth rate. The results show that the proposed method outperforms the listing methods.     

基于D-S证据的多语段融合语音情感识别

为获得更丰富的情感信息、有效识别长语音的情感状态,提出基于D-S证据理论的多粒度语段融合语音情感识别方法。采用2种分段方法对语音样本分段,用SVM对语段进行识别,再利用D-S证据理论对各语音段识别结果进行决策融合,得到2种分段方法下语音的情感识别结果,将这2个识别结果进一步融合得到最终结果。实验结果表明,该方法具有较好的整体识别性能,能有效提高语音情感的识别率。     

提取与检验电子证据的若干实践要点

提取电子证据应当按照案发后及时保护好计算机犯罪现场、保存涉案计算机和各种资料、收集相关资料、询问当事人、现场勘查文档记录等步骤开展工作。电子证据的存储介质不同,对其检验与固定的方法也不尽相同。     

基于数据融合的高压断路器故障诊断方法研究

为了提高高压断路器的故障诊断水平,对采用D-S证据理论将不同类型传感器获得的信息进行数据融合的方法进行了研究,并将其运用到高压断路器的故障诊断中。实例分析结果表明,D-S证据理论能够提高高压断路器故障诊断的进度、准确性和可靠性,并且融合的数据越多,故障诊断的可靠性越高。该方法具有普遍适用性。     

利用创新技法指导控制策略创新初探

控制策略的创新在控制理论与工程的发展中起到举足轻重的作用,如何使控制策略的创新更加科学高效是一个需要研究的问题。提出利用创新技法指导控制策略创新的思想。讨论了创新技法对控制策略创新的指导作用及意义,归纳了可用于控制领域的7大类创新技法,对创新技法的应用层次、协同使用和依存性问题进行了初步讨论。最后以3个例子展示了创新技法对控制策略创新的指导作用和所带来的显著功效。