Artificial intelligence capability: Conceptualization,measurement calibration,and empirical study on its impact on organizational creativity and firm performance

Artificial intelligence (AI) has been heralded by many as the next source of business value. Grounded on the resource-based theory of the firm and on recent work on AI at the organizational context, this study (1) identifies the AI-specific resources that jointly create an AI capability and provides a definition, (2) develops an instrument to capture the AI capability of the firms, and (3) examines the relationship between an AI capability and organizational creativity and performance. Findings empirically support the suggested theoretical framework and corresponding instrument and provide evidence that an AI capability results in increased organizational creativity and performance.     

Taking advantage of collective knowledge in emergency response systems

When large groups work on a theme, they have the potential to produce a lot of useful knowledge, regardless of whether they are acting in a coordinated manner or individually. Spontaneously generated information has received much attention in recent years, as organizations and businesses discover the power of crowds. New technologies, such as blogs, Twitter, wikis, photo sharing, collaborative tagging and social networking sites, enable the creation and dissemination of content in a relatively simple way. As a result, the aggregate body of knowledge is growing at an accelerated rate. Many organizations are looking for ways to harness this power, which is being called collective intelligence. Research has shown that it is possible to obtain high quality results from collectively produced work.In this paper, we consider the domain of emergency response. Research has shown that individuals respond quickly and massively to emergencies, and that they try to help with the situation. Thus, it seems like a logical step to attempt to harness collective knowledge for emergency management. Disaster relief groups and field command frequently suffer from lack of up to date information, which may be critical in a rapidly evolving situation. Some of this information could be generated by the crowd at large, enabling more effective response to the situation. In this paper, we discuss the possibilities for the introduction of collective knowledge in disaster relief and present architecture and examples of how this could be accomplished.     

地下金属矿山斜坡道浆土路修筑工艺及应用研究

斜坡道是地下金属矿山的主要运输通道,其道路质量直接影响着矿山的安全运输和经济效益。针对斜坡道混凝土浇筑路面存在的筑路成本高、养护时间长、使用寿命短及维护困难等不足,引入浆土路修筑技术,开展了地下金属矿山斜坡道浆土路筑路材料配比试验、黏土搓条和崩解试验、水洗筛分试验,并在云南卡房分公司完成了浆土路试验路段的修筑。结果表明：浆土路筑路技术能够很好地应用于地下矿山道路修筑,具有施工工艺简单、筑路成本低、施工周期短、承载能力强、抑尘防滑和低碳环保等诸多优点,为地下金属矿山道路修筑提供了工程借鉴,对于矿山降本增效、节能减排及安全高效具有重要的意义。     

Biomimetic Polymer Nanostructures by Injection Molding

The nanometer scale topography of self‐assembling structural protein complexes in animals is believed to induce favorable cell responses. An important example of such nanostructured biological complexes is fibrillar collagen that possesses a cross‐striation structure with a periodicity of 69 nm and a peak‐to‐valley distance of 4–6 nm. Bovine collagen type I was assembled into fibrillar structures in vitro and sedimented onto solid supports. Their structural motif was transferred into a nickel replica by physical vapor deposition of a small‐grained metal layer followed by galvanic plating. The resulting inverted nickel structure was found to faithfully present most of the micrometer and nanometer scale topography of the biological original. This nickel replica was used as a die for the injection molding of a range of different thermoplastic polymers. Total injection molding cycle times were in the range of 30–45 seconds. One of the polymer materials investigated, polyethylene, displayed poor replication of the biological nanotopographical motif. However, the majority of the polymers showed very high replication fidelity as witnessed by their ability to replicate the cross‐striation features of less than 5 nm height difference. The latter group of materials includes poly(propylene), poly(methyl methacrylate), poly(L ‐lactic acid), polycaprolactone, and a copolymer of cyclic and linear olefins (COC). This work suggests that the current limiting factor for the injection molding of nanometer scale topography in thermoplastic polymers lies with the grain size of the initial metal coating of the mold rather than the polymers themselves.

     

Acquiring logistics process intelligence: Methodology and an application for a Chinese bulk port

The processes of logistics service providers are considered as highly human-centric, flexible and complex. Deviations from the standard operating procedures as described in the designed process models, are not uncommon and may result in significant uncertainties. Acquiring insight in the dynamics of the actual logistics processes can effectively assist in mitigating the uncovered risks and creating strategic advantages, which are the result of uncertainties with respectively a negative and a positive impact on the organizational objectives.In this paper a comprehensive methodology for applying process mining in logistics is presented, covering the event log extraction and preprocessing as well as the execution of exploratory, performance and conformance analyses. The applicability of the presented methodology and roadmap is demonstrated with a case study at an important Chinese port that specializes in bulk cargo.     

Recommending suitable learning scenarios according to learners’ preferences: An improved swarm based approach

The paper presents a new approach for recommending suitable learning paths for different learners groups. Selection of the learning path is considered as recommendations to choosing and combining the sequences of learning objects (LOs) according to learners’ preferences. Learning path can be selected by applying artificial intelligence techniques, e.g. a swarm intelligence model. If we modify and/or change some LOs in the learning path, we should rearrange the alignment of new and old LOs and reallocate pheromones to achieve effective learning recommendations. To solve this problem, a new method based on the ant colony optimisation algorithm and adaptation of the solution to the changing optimum is proposed. A simulation process with a dynamic change of learning paths when new LOs are inserted was chosen to verify the method proposed. The paper contributes with the following new developments: (1) an approach of dynamic learning paths selection based on swarm intelligence, and (2) a modified ant colony optimisation algorithm for learning paths selection. The elaborated approach effectively assist learners by helping them to reach most suitable LOs according to their preferences, and tutors – by helping them to monitor, refine, and improve e-learning modules and courses according to the learners’ behaviour.     

A UNIFIED FRAMEWORK OF TARGETED MARKETING USING CUSTOMER PREFERENCES

One of the fundamental tasks of targeted marketing is to elicit associations between customers and products. Based on the results from information retrieval and utility theory, this article proposes a unified framework of targeted marketing. The customer judgments of products are formally described by preference relations and the connections of customers and products are quantitatively measured by market value functions. Two marketing strategies, known as the customer‐oriented and product‐oriented marketing strategies, are investigated. Four marketing models are introduced and examined. They represent, respectively, the relationships between a group of customers and a group of products, between a group of customers and a single product, between a single customer and a group of products, and between a single customer and a single product. Linear and bilinear market value functions are suggested and studied. The required parameters of a market value function can be estimated by exploring three types of information, namely, customer profiles, product profiles, and transaction data. Experiments on a real‐world data set are performed to demonstrate the effectiveness of the proposed framework.     

基于交叠社团相似性的生物网络关键节点识别

生物网络是研究生物特性的一个重要工具,目前已经有许多方法用于研究生物网络,关键节点分析是其中最常用的方法之一。关键节点分析通常是根据一定的规则为网络中的各节点分配一个函数值,并由此来确定网络中各节点的重要程度,目前已经发表了一些方法。然而,这些方法在单独使用的情况下,获得的关键节点的生物学意义一般较低,存在一定的缺陷。本文从节点对社团贡献的角度建立关键节点识别方法,首先提取网络中富含生物学功能意义的社团,然后依据交叠社团的相似性为各节点分配贡献值,最后通过两个生物网络实例论证了方法的有效性。     

苦参生物碱杀虫生物活性测定

以桃蚜等9种试虫为供试靶标，研究了苦参根提取物和苦参碱、氧化苦参碱、槐果碱、野靛碱的杀虫活性。试验结果表明：苦参生物碱具有一定的杀虫活性，9种试虫中，苦参根提取物对蚜虫的活性最高，其对蚕豆蚜的LC50为20．635mg／L；即使在最高剂量为4000mg/L时，也不能直接杀死粘虫、小菜蛾和棉铃虫。4种生物碱对朱砂叶螨活性均较低，LC50均大于2500mg／L。野靛碱是4种生物碱中杀虫活性最高的，对淡色库蚊、桃蚜、蚕豆蚜、褐飞虱和家蝇的LC50分别为172．431mg/L、207．667mg／L、85．212mg／L、266．179mg／L和763．224mg／L；而且对褐飞虱、桃蚜和家蝇的活性高于苦参根提取物，苦参碱对蚜虫的活性高于氧化苦参碱和槐果碱，槐果碱对淡色库蚊、褐飞虱和家蝇的活性高于苦参碱和氧化苦参碱。