Strategic factors on interpreting remanufacturing quality- Certifying framework to address warranty aftermarket for Malaysian industry

While the concept of remanufacturing is gaining popularity globally, literature and theory on strategic decision-making on certifying for warranty in this area remain limited. A strategic and establish concept flow is developed based on extensive literature review and surveys with experienced experts who are dealing with remanufactured, reconditioned, rebuilt and reused components. The remanufacturing research on evaluating quality assurance of remanufactured component targets macro-level parameters and the indicators which must be confirmed for evaluation. The strategic remanufacturing factors identified from the literature review are discussed in a brainstorming session with a number of remanufacturing researchers and academic experts. The study is further broadened by industrial surveys and case studies to justify the inputs on developing a framework to certify remanufactured components. Preliminary results have established the key factors of remanufacturing quality control that might lead to the strict quality assurance of remanufactured components. Later, the developed framework can be used as a benchmarking tool to certify remanufactured components and warranty issuance. The findings serve as the foundation for further research concerning Original Equipment Manufacturer (OEM) or Original Equipment Remanufacturer (OER) and Independent Equipment Remanufacturer (IER) in the Malaysian Remanufacturing Industry

Stitching, Healing and Empowering: Interrogating the Garden as a Space of Reclamation, Occupied Palestine

This folio sets out recent projects by Sharif and Golzari for the Palestine Regeneration Team (PART) which explores how architecture can ‘stitch, heal and empower’ communities in Occupied Palestine, combining built and speculative design. Founded with Murray Fraser in 2008, PART’s recent work explores how garden, landscape and green space can be used in reinforcing their identity and relationship to the land. Sharif and Golzari’s approach brings forward ‘absent’ narratives through spatial means. Using techniques of ‘social mapping’ and analysis of everyday life and traditional cultural practices, the projects promote low-cost, sustainable responses, forming part of an ongoing group of interlinked projects which offer architectural interventions to heal rural communities in Palestine. Projects can be seen as models, working and tested prototypes for other villages across the West Bank and Gaza. PART works with local NGOs, UN-Habitat and municipalities through the repair of landscapes and the regeneration of historic village centres across the West Bank and in the reconstruction of destroyed neighbourhoods in Gaza. This folio features case studies reflecting how PART’s pragmatic built interventions are complemented by more speculative and experimental design work. The former is represented here by the Beit Iksa project near Jerusalem, a part-ruined village regenerated through design participation into a stable and productive landscape where vegetable gardens and eco-playgrounds become spaces of reclamation. The more speculative work includes the Digital Garden project, part of both broader international dissemination of the built work and a method to develop and promote a positive, Palestinian-based creative response to a threatened identity that explores the potential for stealth interventions within the fissures created by Israeli occupation. PART’s work was shortlisted for the RIBA research awards 2016, and The Digital Garden was exhibited at the 2019 AWAN Festival UK, the Chicago Architecture Biennial and the 2020 Berlinale

Implementing a Chatbot Music Recommender System Based on User Emotion

The use of chatbots has become increasingly popular in recent years, as more organisations try to improve and streamline their customer service operations. One area which has been gaining momentum is the use of chatbots for music recommendation. Such systems utilise AI technologies to deliver personalised music recommendations to users via conversational interfaces. Chatbot music recommender systems present several benefits namely; they provide a personalised and natural experience which can be engaging for the users. Moreover, the users can engage in a dialogue whereby the system can better interpret the user context and preferences. This work presents the development of a chatbot personalised music recommender system, based on Natural Language Processing (NLP) techniques, coupled with a web interface that can provide song recommendations based on the user’s emotions

Kinematic Self-Similar Plane Symmetric Solutions

This paper is devoted to classify the most general plane symmetric spacetimes according to kinematic self-similar perfect fluid and dust solutions. We provide a classification of the kinematic self-similarity of the first, second, zeroth and infinite kinds with different equations of state, where the self-similar vector is not only tilted but also orthogonal and parallel to the fluid flow. This scheme of classification yields twenty four plane symmetric kinematic self-similar solutions. Some of these solutions turn out to be vacuum. These solutions can be matched with the already classified plane symmetric solutions under particular coordinate transformations. As a result, these reduce to sixteen independent plane symmetric kinematic self-similar solutions.Comment: 29 pages, accepted for publication in Classical Quantum Gravit

Energy and Momentum of a Class of Rotating Gravitational Waves

We calculate energy and momentum for a class of cylindrical rotating gravitational waves using Einstein and Papapetrou's prescriptions. It is shown that the results obtained are reduced to the special case of the cylindrical gravitational waves already available in the literature.Comment: 11 pages, no figure, Late

Performance of a multi-stack microchannel heat sink

The usage of a very large scale integrated circuits generate high heat fluxes and require an effective cooling system. A microchannel heat sink (MCHS) is one of the reliable cooling systems that had been applied. In terms of performance, a MCHS can be appraised by obtaining low total thermal resistance and pumping power. However, as the total thermal resistance decreases, the pumping power will increase. A few studies have been focused on the minimization of the thermal resistance and pumping power of a multi-stack MCHS. Optimization of two objective functions which are the total thermal resistance and pumping power has been done by using genetic algorithm. It is demonstrated that both objective functions can be minimized by optimizing two design variables which are the channel aspect ratio, α, and wall width ratio,β. It was found that the usage of a stacked configuration for the MCHS is able to reduce the total thermal resistance. From the optimization, it was found that the optimum number of stacks that can be implemented is three. With the three-stack configuration, the total thermal resistance found is 0.1180 K/W which is 21.8% less compared to the single-stack MCHS. However, the pumping power needed for the three-stack MCHS is increased by 0.17 % compared to single-stack which is 0.7535 W

Lead and Cadmium Levels of Five Commonly and Widely Consumed Leafy Vegetables in Kano State, Nigeria

The levels of the hazardous metals (Pb and Cd) in five different leafy vegetable plant samples ( viz: Hibiscus cannabinus, Cassia tora, Vernonia amygdalina, Corchorus olitorius, and Corchorus tridens) consumed by Kano inhabitants were investigated and found to be at concentration below the environmental lead action level set by US EPA/WHO. Cadmium was not detected in the samples. Low concentration of Pb and absence of Cd in all the plant samples analyzed are clear indication that these may not exhibit toxicity effects due to any of these metals. The consumers are therefore safe from their toxicity effect.Keywords: Lead, Cadmium, Leafy Vegetables, Kano, NigeriaNigerian Journal of Basic and Applied Science (2011), 19(2): 304-30

Real-Time Customer Emotion Analysis in E-Commerce based on Social Media Data: Insights and Opportunities

In this era of social media, it's essential for businesses to monitor their customers options and feelings regarding their services and products in a timely manner. Due to the ease of sharing opinions and feedback on social media, the customers can share their reviews about the business or a product instantly. This feedback can have a significant impact on the business's reputation and in turn on its revenue. In this regard, sentiment analysis has developed into a vital tool that companies can use to comprehend the emotional factors that influence client behavior and to aid them in making decisions that will increase customer pleasure. This work presents the use of social media data for real-time consumer emotion analysis in e-commerce. The study aims to identify the most expressed emotions and provide businesses with the ability to tailor their product and services accordingly. The employed dataset consists of 58,000 English comments that have been labelled for 27 different emotion categories. The study uses machine learning methods to categorize the emotions expressed in the comments, including convolutional neural networks and Bidirectional Encoder Representations from Transformers (BERT). The practical result of this research shows the importance of machine learning model coupled with a user interface that can provide stakeholders, such as e-commerce companies, with insights into consumer emotion as well as realtime customer sentiment about their goods and services

Fault Sneaking Attack: a Stealthy Framework for Misleading Deep Neural Networks

Despite the great achievements of deep neural networks (DNNs), the vulnerability of state-of-the-art DNNs raises security concerns of DNNs in many application domains requiring high reliability.We propose the fault sneaking attack on DNNs, where the adversary aims to misclassify certain input images into any target labels by modifying the DNN parameters. We apply ADMM (alternating direction method of multipliers) for solving the optimization problem of the fault sneaking attack with two constraints: 1) the classification of the other images should be unchanged and 2) the parameter modifications should be minimized. Specifically, the first constraint requires us not only to inject designated faults (misclassifications), but also to hide the faults for stealthy or sneaking considerations by maintaining model accuracy. The second constraint requires us to minimize the parameter modifications (using L0 norm to measure the number of modifications and L2 norm to measure the magnitude of modifications). Comprehensive experimental evaluation demonstrates that the proposed framework can inject multiple sneaking faults without losing the overall test accuracy performance.Comment: Accepted by the 56th Design Automation Conference (DAC 2019

Teleparallel Energy-Momentum Distribution of Spatially Homogeneous Rotating Spacetimes

The energy-momentum distribution of spatially homogeneous rotating spacetimes in the context of teleparallel theory of gravity is investigated. For this purpose, we use the teleparallel version of Moller prescription. It is found that the components of energy-momentum density are finite and well-defined but are different from General Relativity. However, the energy-momentum density components become the same in both theories under certain assumptions. We also analyse these quantities for some special solutions of the spatially homogeneous rotating spacetimes.Comment: 12 pages, accepted for publication in Int. J. Theor. Phy