Bottom-up synthesis of recursive functional programs using angelic execution

We present a novel bottom-up method for the synthesis of functional recursive programs. While bottom-up synthesis techniques can work better than top-down methods in certain settings, there is no prior technique for synthesizing recursive programs from logical specifications in a purely bottom-up fashion. The main challenge is that effective bottom-up methods need to execute sub-expressions of the code being synthesized, but it is impossible to execute a recursive subexpression of a program that has not been fully constructed yet. In this paper, we address this challenge using the concept of angelic semantics. Specifically, our method finds a program that satisfies the specification under angelic semantics (we refer to this as angelic synthesis), analyzes the assumptions made during its angelic execution, uses this analysis to strengthen the specification, and finally reattempts synthesis with the strengthened specification. Our proposed angelic synthesis algorithm is based on version space learning and therefore deals effectively with many incremental synthesis calls made during the overall algorithm. We have implemented this approach in a prototype called Burst and evaluate it on synthesis problems from prior work. Our experiments show that Burst is able to synthesize a solution to 94% of the benchmarks in our benchmark suite, outperforming prior work.

Deletion discussions on Hebrew Wikipedia: Negotiating global and local ideologies

Much research has documented how global technologies and platforms are part of specific cultures and reflect local values. In this study, I examine the case of Hebrew Wikipedia as representative of localization that is neither top-down (producer-driven) nor bottom-up (user-driven); but rather, it is implemented by mid-level, self-selecting bureaucratic administrators in an ongoing process that is driven by their own perceptions of Wikipedia’s mission. Through an analysis of Hebrew Wikipedia’s deletion discussion pages—in which editors decide what information should be excluded from Wikipedia—I demonstrate how national ideology customarily triumphs over the global, communitarian ethos of the Wikipedia project. Even when decisions are aligned with a more “global” agenda, editors still portray their choices as congruent with the national cause through strategic use of depersonalized discourses about Wikipedia’s policies. I thus argue that global, seemingly “neutral” policies can provide a discursive framework that conceals questions about the power of local ideologies.

Scale-up of prevention programmes: sustained state-wide use of programme delivery software is explained by normalised self-organised adoption and non-adoption

Background Population-level health promotion is often conceived as a tension between “top-down” and “bottom-up” strategy and action. We report behind-the-scenes insights from Australia’s largest ever investment in the “top-down” approach, the $45m state-wide scale-up of two childhood obesity programmes. We used Normalisation Process Theory (NPT) as a template to interpret the organisational embedding of the purpose-built software designed to facilitate the initiative. The use of the technology was mandatory for evaluation, i.e. for reporting the proportion of schools and childcare centres which complied with recommended health practices (the implementation targets). Additionally, the software was recommended as a device to guide the implementation process. We set out to study its use in practice. Methods Short-term, high-intensity ethnography with all 14 programme delivery teams across New South Wales was conducted, cross-sectionally, 4 years after scale-up began. The four key mechanisms of NPT (coherence/sensemaking, cognitive participation/engagement, collective action and reflexive monitoring) were used to describe the ways the technology had normalised (embedded). Results Some teams and practitioners embraced how the software offered a way of working systematically with sites to encourage uptake of recommended practices, while others rejected it as a form of “mechanisation”. Conscious choices had to be made at an individual and team level about the practice style offered by the technology—thus prompting personal sensemaking, re-organisation of work, awareness of choices by others and reflexivity about professional values. Local organisational arrangements allowed technology users to enter data and assist the work of non-users—collective action that legitimised opposite behaviours. Thus, the technology and the programme delivery style it represented were normalised by pathways of adoption and non-adoption. Normalised use and non-use were accepted and different choices made by local programme managers were respected. State-wide, implementation targets are being reported as met. Conclusion We observed a form of self-organisation where individual practitioners and teams are finding their own place in a new system, consistent with complexity-based understandings of fostering scale-up in health care. Self-organisation could be facilitated with further cross-team interaction to continuously renew and revise sensemaking processes and support diverse adoption choices across different contexts.

Memristive devices based on single ZnO nanowires - from material synthesis to neuromorphic functionalities

Memristive and resistive switching devices are considered promising building blocks for the realization of artificial neural networks and neuromorphic systems. Besides conventional top-down memristive devices based on thin films, resistive switching devices based on nanowires (NWs) have attracted great attention, not only for the possibility of going beyond current scaling limitations of the top-down approach, but also as model systems for the localization and investigation of the physical mechanism of switching. This work reports on the fabrication of memristive devices based on ZnO NWs, from NW synthesis to single NW-based memristive cell fabrication and characterization. The bottom-up synthesis of ZnO NWs was performed by low-pressure Chemical Vapor Deposition (LPCVD) according to a self-seeding Vapor-Solid (VS) mechanism on a Pt substrate over large scale (∼ cm2), without the requirement of previous seed deposition. The grown ZnO NWs are single crystalline with wurtzite crystal structure and are vertically aligned respect to the growth substrate. Single NWs were then contacted by means of asymmetric contacts, with an electrochemically active and an electrochemically inert electrode, to form NW-based electrochemical metallization memory (ECM) cells that show reproducible resistive switching behaviour and neuromorphic functionalities including short-term synaptic plasticity and Paired Pulse Facilitation (PPF). Besides representing building blocks for NW-based memristive and neuromorphic systems, these single crystalline devices can be exploited as model systems to study physicochemical processing underlaying memristive functionalities thanks to the high localization of switching events on the ZnO crystalline surface.

Corporate governance reform in Nigeria: upstream and downstream interventions

Purpose Internal (e.g. firm performance, internal stakeholders) and external pressures (e.g. globalisation, technology, corporate scandals) have intensified calls for corporate governance reforms across varieties of capitalism. Yet, corporate governance practices among developing economies remain problematic. Drawing insights from Africa’s largest economy (Nigeria) and relying on the resource dependence theorisation, this study aims to address two questions – what are the prerequisites for effective reforms; and what reforms yield robust corporate governance? Design/methodology/approach This study adopts a qualitative methodology comprising semi-structured interviews with 21 executives in publicly listed Nigerian firms. The interviews were analysed using the content analysis technique. Findings This study proposes two sequential reforms (i.e. the upstream and downstream). The upstream factors highlight the preconditions that support corporate governance reforms, i.e. government commitment and enabling environment, while the downstream reforms combine elements of awareness and regulation to proffer robust corporate governance interventions. Originality/value This research further stresses the need to consider a bottom-up approach to corporate governance in place of the dominant top-down strategy. This strategy allows agents to participate actively in corporate governance policy-making rather than a top-down model, which imposes corporate governance on agents.

Top-Down Machine Learning-Based Architecture for Cyberattacks Identification and Classification in IoT Communication Networks

With the prompt revolution and emergence of smart, self-reliant, and low-power devices, Internet of Things (IoT) has inconceivably expanded and impacted almost every real-life application. Nowadays, for example, machines and devices are now fully reliant on computer control and, instead, they have their own programmable interfaces, such as cars, unmanned aerial vehicles (UAVs), and medical devices. With this increased use of IoT, attack capabilities have increased in response, which became imperative that new methods for securing these systems be developed to detect attacks launched against IoT devices and gateways. These attacks are usually aimed at accessing, changing, or destroying sensitive information; extorting money from users; or interrupting normal business processes. In this research, we present new efficient and generic top-down architecture for intrusion detection, and classification in IoT networks using non-traditional machine learning is proposed in this article. The proposed architecture can be customized and used for intrusion detection/classification incorporating any IoT cyber-attack datasets, such as CICIDS Dataset, MQTT dataset, and others. Specifically, the proposed system is composed of three subsystems: feature engineering (FE) subsystem, feature learning (FL) subsystem, and detection and classification (DC) subsystem. All subsystems have been thoroughly described and analyzed in this article. Accordingly, the proposed architecture employs deep learning models to enable the detection of slightly mutated attacks of IoT networking with high detection/classification accuracy for the IoT traffic obtained from either real-time system or a pre-collected dataset. Since this work employs the system engineering (SE) techniques, the machine learning technology, the cybersecurity of IoT systems field, and the collective corporation of the three fields have successfully yielded a systematic engineered system that can be implemented with high-performance trajectories.

ATTRIBUTES AND PERFORMANCE OF FUND MANAGEMENT COMPANIES: EVIDENCE FROM THE LARGEST SHARIAH-COMPLIANT FUND MARKETS

Background and Purpose: The study examines the effect of fund management companies’ (FMCs) attributes on FMC performance in the four countries with the largest number of Islamic funds from 2007 to 2018. Methodology: The study uses pooled regression analysis on 70 FMCs, comprising Saudi Arabia (25), Malaysia (20), Indonesia (14) and Pakistan (11). The sample is further divided into FMC with Islamic funds focused (IFFMC) and conventional funds focused (CFFMC). Findings: Only past flows are insignificantly related to performance. Both proxies for size positively relate to returns, but only in the case of Saudi Arabia. In Pakistan, performance improves with assets under management (AUM), while in Malaysia and Indonesia, an increasing number of funds negatively relate to performance. A relatively high number of better performing funds positively affect FMC and vice versa. Additionally, there are significant differences in the factors determining IFFMC and CFFMC performance, with the number of funds and AUM positively affecting the performance of IFFMC but not CFFMC. Poorly performing funds adversely affect CFFMC but not IFFMC. Contributions: This study provides useful information for investors using a top-down approach to FMC then fund selection, and for managers in evaluating the impact of factors like FMC scale and scope on performance. The impact of these attributes differs between CFFMCs and IFFMCs which lies in the performance differences commonly observed, at the FMC and fund level. Keywords: Islamic funds management industries, Islamic mutual fund, fund performance, Islamic finance. Cite as: Marzuki, A., Bani Atta, A. A., & Worthington, A. (2022). Attributes and performance of fund management companies: Evidence from the largest Shariah-compliant fund markets. Journal of Nusantara Studies, 7(1), 114-141. http://dx.doi.org/10.24200/jonus.vol7iss1pp114-141