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Designing a test battery for real-world visual search
Get PDFAlthough much research has investigated the mechanisms of visual search behaviour in laboratory-based computer tasks, there has been relatively little work on whether these results generalise to more naturalistic search tasks. In addition, work on real-world search has often been carried out by researchers working in very different disciplines, leading to a high degree of task fragmentation. Here, we detail our development of a ‘naturalistic search task battery’, which aims to provide a suite of open-source, reproducible, and standardised real-world search tasks, thus enabling the generation of comparable data across multiple studies and aiding theory and modelling in this area. We show that we can replicate findings from previous search tasks using Lego, demonstrating set-size effects and differences between search conditions. We also show effects of scene regularity using a ‘bookcase’ task where participants search for specific books on shelves. Finally, we use a ‘jigsaw’ task and a ‘Lego building’ task as examples of more complex real-world search tasks and show how we can use them to consider the effects of strategies. Finally, we consider whether performance on one task can predict performance on another, and thus to what extent similar cognitive capabilities underlie diverse ‘real-world’ search tasks
Paying to Match: Decentralized Markets with Information Frictions
No full textWe experimentally study decentralized one-to-one matching markets with transfers. We vary the information available to participants, complete or incomplete, and the surplus structure, supermodular or submodular. Several insights emerge. First, while markets often culminate in efficient matchings, stability is more elusive, reflecting the difficulty of arranging attendant transfers. Second, incomplete information and sub-modularity present hurdles to efficiency and especially stability; their combination drastically diminishes stability’s likelihood. Third, matchings form “from the top down” in complete-information supermodular markets, but exhibit many more and less-obviously ordered offers otherwise. Last, participants’ market positions matter far more than their dynamic bargaining styles for outcomes
An Advanced Air Suspension Control System Utilizing Intelligent Algorithms and Real-Time Terrain Detection
No full textThis paper presents On Air Active, an advanced aftermarket air suspension control system engineered to enhance vehicle ride comfort and stability through intelligent algorithms and robust hardware design. Utilizing a single height sensor and an ATmega328PB microcontroller, the system dynamically adjusts air pressure to maintain optimal vehicle height across varying loads and road conditions. Extensive testing on over ten commercial and disability vehicles validated On Air Active's reliability, energy efficiency, and resilience in harsh environments. Additionally, preliminary work employing a Gaussian noise model has been conducted to simulate terrain variations, laying the groundwork for future integration of AI-driven terrain detection and real-time suspension adjustments. These innovations position On Air Active as a cost-effective, easy-to-install solution, setting new standards in the aftermarket air suspension industry and contributing to the advancement of intelligent vehicle systems
Contention and Reliability-Aware Energy Efficiency Task Mapping on NoC-Based MPSoCs
Get PDFRecently, Network-on-Chip (NoC)-based Multi- Processor System-on-Chips (MPSoCs) have become popular computing platforms for real-time applications due to high communication performance and energy efficiency over traditional bus-based MPSoCs. Due to the nature of network structures, network congestion along with transient faults, can significantly affect communication efficiency and system reliability. Most existing works have rarely focused on the concurrent optimization of network contention, reliability, and energy consumption. Here, we study the problem of contention and reliability-aware task mapping under real-time constraints for dynamic voltage and frequency scaling-enabled NoC. The problem entails optimizing voltage/frequency on cores and links to reduce energy consumption and ensure system reliability, while task mapping and slack time are adopted to alleviate network contention and reduce latency. We aim to minimize computation and communication energy and balance workload. This problem is formulated as a mixed-integer nonlinear programming, and we present an effective linearization scheme that equivalently transforms it into a mixed-integer linear programming to find the optimal solution. To reduce computation time, we propose a three-step heuristic, including task allocation, frequency scaling and edge scheduling, and communication contention management. Finally, we perform extensive simulations to evaluate the proposed method. The results show we can achieve 31.6% and 21.7% energy savings, with 95.5% and 98.6% less contention than the existing methods
The Israeli parties' positions in comparative perspective
Get PDF The multidimensionality of the Israeli political system is expected given Israel’s electoral system and cleavage structure. We introduce a new dataset and measurement of party positions in Israel and provide evidence that Israel’s party system is comparable to other multiparty systems in Europe (CHES-EU) and Latin America (CHES-LA). We argue and provide evidence that the most important dimension in the Israeli party system, similar to other multiparty systems, is the general Left-Right continuum, which combines both economic and cultural policy issues. Yet, unlike other established democracies, parties’ positions on the Left-Right continuum are closely related to their positions on policies related to the Arab-Israeli conflict. We also discuss Israeli-specific issues which structure the Israeli party competition. The contribution of this paper is two-fold. First, it allows scholars of party competition to include Israel as a comparative case in their research. Second, it is the first study that provides valid and reliable measurement of Israeli parties’ positions across multiple issues. </jats:p
MARISMA: A modern and context-aware framework for assessing and managing information cybersecurity risks
Get PDFIn a globalised world dependent on information technology, ensuring adequate protection of an organisation's information assets has become a decisive factor for the longevity of the organisation's operation. This is especially important when these organisations are critical infrastructures that provide essential services to nations and their citizens. However, to protect these assets, we must first be able to understand the risks to which they are subject and how to manage them properly. To understand and manage such the risks, we need first to acknowledge that organisations have changed, and they now have an increasing reliance on information assets, which in many cases are shared with other organisations. Such reliance and interconnectivity means that risks are constantly changing, they are dynamic, and potential mitigation does not just rely on the organisation's own controls, but also on the controls put in place by the organisations with which it shares those assets. Taking the above requirements as essential, we have reviewed the state of the art, and we have concluded that current risk analysis and management systems are unable to meet all the needs inherent in this dynamic and evolving risk environment. This gap in the state of the art requires novel approaches that draw on the foundations of risk management, but they are adapted to the new challenges. This article fulfils this gap in the literature with the introduction of MARISMA, a novel security risk analysis and management framework. MARISMA is oriented towards dynamic and adaptive risk management, considering external factors such as associative risks between organisations. MARISMA also contributes to the state of the art through newly developed mechanisms for knowledge reuse and dynamic learning. An important advantage of MARISMA is the connections between its elements that make it possible to reduce the subjectivity inherent in classical risk analysis systems, thereby generating suggestions that allow the translation of perceived security risks into real security risks. The framework comprises a reusable meta-pattern comprising different elements and their interdependencies, a supporting method that guides the entire process, and a cloud-based tool that automates data management and risk methods. MARISMA has been applied to many companies from different countries and sectors (government, maritime, energy, and pharmaceutical). In this paper, we demonstrate its applicability through its application to a real world case study involving a company in the technology sector
Data stream clustering: introducing recursively extendable aggregation functions for incremental cluster fusion processes
Get PDFIn Data Stream (DS) learning, the system has to extract knowledge from data generated continuously, usually at high speed and in large volumes, making it impossible to store the entire set of data to be processed in batch mode. Hence, machine learning models must be built incrementally by processing the incoming examples, as data arrive, while updating the model to be compatible with the current data. In fuzzy DS clustering, the model can either absorb incoming data into existing clusters or initiate a new cluster. As the volume of data increases, there is a possibility that the clusters will overlap to the point where it is convenient to merge two or more clusters into one. Then, a cluster comparison measure (CM) should be applied, to decide whether such clusters should be combined, also in an incremental manner. This defines an incremental fusion process based on aggregation functions that can aggregate the incoming inputs without storing all the previous inputs. The objective of this paper is to solve the fuzzy DS clustering problem of incrementally comparing fuzzy clusters on a formal basis. Firstly, we formalize and operationalize incremental fusion processes of fuzzy clusters by introducing Recursively Extendable (RE) aggregation functions, studying construction methods and different classes of such functions. Secondly, we propose two approaches to compare clusters: similarity and overlapping between clusters, based on RE aggregation functions. Finally, we analyze the effect of those incremental CMs on the online and offline phases of the well-known fuzzy clustering algorithm d-FuzzStream, showing that our new approach outperforms the original algorithm and presents better or comparable performance to other state-of-the- art DS clustering algorithms found in the literature
A Sequential Mixed Method Study of Employee Job Satisfaction in Upscale Restaurants, Malaysia
Get PDFThe study determines the main factors affecting job satisfaction in upscale restaurants and their degree of comparative influence. The research initially involves qualitative data analysis of 20 interviews with restaurant employees representing five upscale restaurants in Kuala Lumpur (KL), followed by structural equation modeling of data retrieved from 368 questionnaires from 16 KL restaurants. The impact variance of four main determinants of job satisfaction are revealed, where the “working environment” has the highest impact, followed by “payment and compensation,” “promotion”, and finally, “workplace fairness”. Crucially, “workplace relationships” have a moderating effect on the relationship between the “work environment” and job satisfaction, implicating industry-applied recommendations to strengthen job satisfaction levels
Brief Use of Behavioral Activation Features Predicts Benefits of Self-help App on Depression Symptoms: Secondary Analysis of a Selective Prevention Trial in Young People
Get PDFObjective: To explore which CBT self-help app usage predicted depression during a selective prevention trial.
Method: A recent controlled trial (ECoWeB-PREVENT) randomised young people aged 16- 22, at increased risk for depression because of elevated worry/rumination, negative appraisals, and/or rejection sensitivity but without past or current history of major depression, to apps that provided self-monitoring, self-monitoring plus CBT self-help, or self-monitoring plus emotional competency self-help. Self-help included coping strategies for moment-by- moment use (Tools) and self-learning/planning exercises (Challenges). On the primary outcome (depression, PHQ-9) at 3-months follow-up (primary endpoint), only the CBT app outperformed self-monitoring. In this secondary analysis, only data from participants who used the CBT or self-monitoring apps at least once was analysed to test what app use predicted change in depression from baseline to 3 months.
Results: Of the original 1262 participants (79% female), 558 were included (CBT, baseline, n = 273, PHQ-9: M=7.48, SD=3.9; 3-months, N =163, PHQ-9: M =8.83, SD=4.92; Self- monitoring, baseline, n=285, PHQ-9: M=7.45, SD=4.26; 3-months, N=183, PHQ-9: M=7.48, SD=3.9). Neither total app use, self-monitoring, nor use of Tools predicted change in depression (all p’s >.05). Frequency of use of Challenges predicted lower depression symptoms and caseness at three months (β =-0.28, 95%CI -0.53 to -0.03, p =.029). Specifically, use of Behavioral Activation Challenges mediated the effects of the CBT app on depression over 3-months (β =-0.59, 95% CI: -1.13 to -0.05, p =.03).
Conclusions: Brief psychoeducation about behavioral activation principles in an app may protect young people from depression over 3-months, even when only used once
The generational shift toward the reciprocal disclosure of intimacy in daughter-father relationships through physical activity in the UK
Get PDFWithin family sociology during the past 30 years, while a general consensus has developed that most parents and children in the Western world have come to share relationships characterised by a greater degree of intimate disclosure, the extent to which parent–child relationships have become ‘purer’ and more egalitarian remains a contested issue. Although there has been a developing interest in involved fathering through sport and physical activity over the past decade, research has yet to concentrate on the consequences of this transformation for daughters. This article applies Mannheim’s tenet of generation entelechy to life history interviews with 14 women born between 1950 and 1994 to argue that involved fathering through physical activity offers conditions for daughters to realise a long-held desire to establish more emotionally reciprocated intimate bonds with fathers. Daughters described a shift from viewing fathers as emotionally uninvolved workers to becoming interdependent intimates