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Social signal processing under affective computing aims at recognizing and extracting useful human social interaction patterns. Fight is a common social interaction in real life. A fight detection system finds wide applications. This paper aims to detect fights in a natural and low-cost manner.

Research works on fight detection are often based on visual features, demanding substantive computation and good video quality. In this paper, the authors propose an approach to detect fight events through motion analysis. Most existing works evaluated their algorithms on public data sets manifesting simulated fights, where the fights are acted out by actors. To evaluate real fights, the authors collected videos involving real fights to form a data set. Based on the two types of data sets, the authors evaluated the performance of their motion signal analysis algorithm, which was then compared with the state-of-the-art approach based on MoSIFT descriptors with Bag-of-Words mechanism, and basic motion signal analysis with Bag-of-Words.

The experimental results indicate that the proposed approach accurately detects fights in real scenarios and performs better than the MoSIFT approach.

By collecting and annotating real surveillance videos containing real fight events and augmenting with well-known data sets, the authors proposed, implemented and evaluated a low computation approach, comparing it with the state-of-the-art approach. The authors uncovered some fundamental differences between real and simulated fights and initiated a new study in discriminating real against simulated fight events, with very good performance.

To provide further evidence on the effectiveness of analytical procedures (APs) used in auditing. Computer simulation experiments are used to examine the error detection ability of a set of APs. Two different types of errors are examined and compared on the basis of the Type I and Type II errors they produce. The results of the experiments support earlier performance assessments of APs based upon simulated data. Higher noise levels reduce performance but a more detailed modeling of the process generating the data appears to produce a compensatory increase in performance. Contrary to earlier findings, some annual APs performed better than their related monthly counterparts. Case study and experimental results are better reconciled than in previous studies. The findings are based upon simulated data and deal with two types of error only. The experiments model the data generating process underlying accounting numbers but are simplifications of the real situation. Future research based upon the same approach but using more sophisticated experimental models and dealing with a wider class of errors would be useful. The findings echo earlier recommendations that APs should not be relied upon as lone, substantive testing devices for error and fraud. The simulation experiments use Statistical Activity Cost Theory to generate accounting numbers from specified, underlying stochastic processes. This allows errors to be related to transactions, i.e. the level at which they typically occur, whereas in prior experimental work errors have only been related to accounts.

The purpose of this paper is to discuss the use of stereoscopic virtual technology in textile and fashion studies in particular to the area of chemical experiment. The development of a designed virtual platform, called Stereoscopic Chemical Laboratory (SCL), is introduced.

To implement the suggested educational approaches of SCL, a set of teaching and learning materials with emphasis on the application methods was revised from the existing subjects. The architecture of SCL includes building of virtual objects with the Autodesk software Maya and designing of interactivity by using Unity, a game engine system. Prototype version of the SCL has been passed to selected academic colleagues and students for further evaluation and application feedback.

Textile students can conduct laboratory experiments associated with coloration and finishing of textile technologies in a stereoscopic 3D and multisensory laboratory, and hence enhance their learning experience. With the use of SCL, students can learn relevant experiment tools, experimental processes, procedures, and safety and health precautions.

There is very limited educational or training approach in applying stereoscopic virtual reality in teaching activities. In the area of textile experiment, the authors could say it is virtual and does not exist in current research domains.

The objective of the paper is to amalgamate theories of text retrieval from various research traditions into a cognitive theory for information retrieval interaction. Set in a cognitive framework, the paper outlines the concept of polyrepresentation applied to both the user's cognitive space and the information space of IR systems. The concept seeks to represent the current user's information need, problem state, and domain work task or interest in a structure of causality. Further, it implies that we should apply different methods of representation and a variety of IR techniques of different cognitive and functional origin simultaneously to each semantic full‐text entity in the information space. The cognitive differences imply that by applying cognitive overlaps of information objects, originating from different interpretations of such objects through time and by type, the degree of uncertainty inherent in IR is decreased. Polyrepresentation and the use of cognitive overlaps are associated with, but not identical to, data fusion in IR. By explicitly incorporating all the cognitive structures participating in the interactive communication processes during IR, the cognitive theory provides a comprehensive view of these processes. It encompasses the ad hoc theories of text retrieval and IR techniques hitherto developed in mainstream retrieval research. It has elements in common with van Rijsbergen and Lalmas' logical uncertainty theory and may be regarded as compatible with that conception of IR. Epistemologically speaking, the theory views IR interaction as processes of cognition, potentially occurring in all the information processing components of IR, that may be applied, in particular, to the user in a situational context. The theory draws upon basic empirical results from information seeking investigations in the operational online environment, and from mainstream IR research on partial matching techniques and relevance feedback. By viewing users, source systems, intermediary mechanisms and information in a global context, the cognitive perspective attempts a comprehensive understanding of essential IR phenomena and concepts, such as the nature of information needs, cognitive inconsistency and retrieval overlaps, logical uncertainty, the concept of ‘document’, relevance measures and experimental settings. An inescapable consequence of this approach is to rely more on sociological and psychological investigative methods when evaluating systems and to view relevance in IR as situational, relative, partial, differentiated and non‐linear. The lack of consistency among authors, indexers, evaluators or users is of an identical cognitive nature. It is unavoidable, and indeed favourable to IR. In particular, for full‐text retrieval, alternative semantic entities, including Salton et al.'s ‘passage retrieval’, are proposed to replace the traditional document record as the basic retrieval entity. These empirically observed phenomena of inconsistency and of semantic entities and values associated with data interpretation support strongly a cognitive approach to IR and the logical use of polyrepresentation, cognitive overlaps, and both data fusion and data diffusion.

Simulations exist for the prediction of the behaviour of building structural systems under fire, including two-way coupled fire-structure interaction. However, these simulations do not include detailed models of the connections, whereas these connections may impact the overall behaviour of the structure. Therefore, this paper proposes a two-scale method to include screw connections.

The two-scale method consists of (a) a global-scale model that models the overall structural system and (b) a small-scale model to describe a screw connection. Components in the global-scale model are connected by a spring element instead of a modelled screw, and the stiffness of this spring element is predicted by the small-scale model, updated at each load step. For computational efficiency, the small-scale model uses a proprietary technique to model the behaviour of the threads, verified by simulations that model the complete thread geometry, and validated by existing pull-out experiments. For four screw failure modes, load-deformation behaviour and failure predictions of the two-scale method are verified by a detailed system model. Additionally, the two-scale method is validated for a combined load case by existing experiments, and demonstrated for different temperatures. Finally, the two-scale method is illustrated as part of a two-way coupled fire-structure simulation.

It was shown that proprietary ”threaded connection interaction” can predict thread relevant failure modes, i.e. thread failure, shank tension failure, and pull-out. For bearing, shear, tension, and pull-out failure, load-deformation behaviour and failure predictions of the two-scale method correspond with the detailed system model and Eurocode predictions. Related to combined load cases, for a variety of experiments a good correlation has been found between experimental and simulation results, however, pull-out simulations were shown to be inconsistent.

More research is needed before the two-scale method can be used under all conditions. This relates to the failure criteria for pull-out, combined load cases, and temperature loads.

The two-scale method bridges the existing very detailed small-scale screw models with present global-scale structural models, that in the best case only use springs. It shows to be insightful, for it contains a functional separation of scales, revealing their relationships, and it is computationally efficient as it allows for distributed computing. Furthermore, local small-scale non-convergence (e.g. a screw failing) can be handled without convergence problems in the global-scale structural model.

The interruption of on-campus teaching and learning, due to the COVID-19 pandemic, forced universities around the globe to rethink their pedagogical models and adopt innovative strategies and approaches that enabled continuity of learning. Engineering schools and faculties were faced with the challenge of how to continue to engage students with the practical component of coursework, especially in terms of lab work and experimentation, which are mandatory requirements for degree awards.

This study documents how the Faculty of Engineering in a university in Oman engaged students with the practical component of their course during the pandemic by launching the remote DoIt@Home Lab. The DoIt@Home Lab approach included the design and development of video recorded labs, virtual labs, simulation exercises and DoIt@Home experiments which were provided to students as teaching tools and guides to conducting home experiments remotely.

This study presents the DoIt@Home Lab approach introduced to Year 2 Chemistry for engineering students. Students' grades improved by 11% over the previous year when the course was delivered face-to-face. Failure rates dropped by 8% while the number of students earning a 3.25 grade point average (GPA) or higher increased by 18%.

The DoIt@Home Lab for engineering courses could enhance students' learning experience and create an effective remote learning environment. While the DoIt@Home Lab was created to supplement on-campus activity in the event of a temporary disruption, it can also be used to supplement regular face-to-face program delivery.

This paper aims to present social trust as a variable of influence by demonstrating the possibilities of trusted social nodes to improve influential capability and rate of successfully influenced social nodes within a social networking environment.

This research will be conducted using simulated experiments. The base algorithm in research uses genetics algorithm diffusion model (GADM) where it carries out social influence calculations within a social networking environment. The GADM algorithm will be enhanced by integrating trust values into its influential calculations. The experiment simulates a virtual social network based on a social networking site architecture from the data set used to conduct experiments on the enhanced GADM and observe their influence capabilities.

The presence of social trust can effectively increase the rate of successfully influenced social nodes by factorizing trust value of one source node and acceptance rate of another recipient node into its probabilistic equation, hence increasing the final acceptance probability.

This research focused exclusively on conceptual mathematical models and technical aspects so far; comprehensive user study, extensive performance and scalability testing is left for future work.

Two key contributions of this paper are the calculation of social trust via content integrity and the application of social trust in social influential diffusion algorithms. Two models will be designed, implemented and evaluated on the application of social trust via trusted social nodes and domain-specified (of specific interest groups) trusted social nodes.

Managerial accounting education generally insists that managers should never consider sunk costs. This suggestion seems inconsistent with a common mode of thinking about future rewards: quasi-hyperbolic discounting. This paper aims to explore the conflict between sunk cost consideration and quasi-hyperbolic discounting and to illustrate when sunk cost consideration may be appropriate.

The author conducted three numerical experiments, i.e. simulated experiments based on analytical models, to demonstrate how it can be beneficial to consider sunk costs in some circumstances. All three numerical experiments assume quasi-hyperbolic discounting. First, the author tested considering sunk costs with future rewards that are certain. Second, the author tested considering sunk costs with uncertain future rewards. Finally, the author tested two different educational interventions to change decision-makers’ thought patterns.

The author found that considering sunk costs worsens decisions when there is bad news and improves them when there is good news. The author found that an educational intervention that partially dissuades managers from considering sunk costs improves decisions when bad news arrives and worsens them when good news arrives. The author also found that an educational intervention that reduces uncertainty improves decisions when bad news arrives and does not worsen these decisions when good news arrives.

The author provided numerical examples of situations in which considering sunk costs is valuable. The findings on educational interventions provide information about the tradeoffs of teaching that sunk costs should never be considered.

Robonaut is a humanoid robot designed by the Robotic Systems Technology Branch at NASA's Johnson Space Center in a collaborative effort with Defense Advanced Research Projects Agency. This paper describes the implementation of haptic feedback into Robonaut and Robosim, the computer simulation of Robotonaut. In the first experiment, we measured the effects of varying feedback to a teleoperator during a handrail grasp task. Second, we conducted a teleoperated task, inserting a flexible beam into an instrumented receptacle. In the third experiment, we used Robonaut to perform a two‐arm task where a compliant ball was translated in the robot's workspace. The experimental results are encouraging as the Dexterous Robotics Lab continues to implement force feedback into its teleoperator hardware architecture.

This paper aims to propose the framework of a decision support system (DSS) to select the optimal number of suppliers that are candidate to join a supply chain network.

The DSS bases the decision on the cost evaluation of the transaction among the buyer and the potentially available suppliers by way of a Monte Carlo approach. In particular, the presented DSS includes a statistical module and the DSS core. The former module estimates (in a probabilistic way) the exchange performance indices, i.e. total cost of the transaction, purchasing price and additional costs of purchasing, while the latter module implements the transaction evolution making use of a simulation model. The DSS is tested by way of a case study, namely the supply of a customized product by a general contractor in the construction industry.

The obtained DSS results are validated with the actual data of the purchasing, and confirm the underlying model suitability and the DSS effectiveness for purchasing management in supply chains. The DSS is able to evaluate the total cost of purchasing and the optimal number of suppliers to contact before the transaction takes place and may be employed by the buyer to forecast the cost of the purchase and take decisions to minimize such a performance index of the exchange.

Perspectives on future research include further validations of the DSS, also considering other factors than price in the transaction evaluation.

The paper shows that the DSS can be successfully employed to identify managerial guidelines that can be followed by practitioners, particularly when the first supply of a product has to be carried out.