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Design and Implementation of a Drum-Buffer-Rope System
Get PDFPurpose: This paper investigates the selection, design and implementation of a Drum-Buffer-Rope (DBR) type of production pull-system in a panel fabrication plant characterised by extensive shared, batch resource resources within a low
volume UK manufacturer of large vehicles. This was the second of a series of two related research projects conducted under the aegis of a Lean initiative at this case firm.
Design/methodology/approach: A purposively selected longitudinal case study conducted over 24 months and organised around a two phase research design. The initial body of evidence included a detailed map constructed by a project team
of eight managers and accountants during a two day structured workshop; numerous unstructured interviews and observation of shop floor practices; document and archival analysis, and 140 photographs of the focal operation. Supplemented by extensive financial and operational data extracted from the firm’s accounting and MRP systems, including all data necessary to construct and implement bespoke capacity planning, work in progress (WIP) monitoring and simulation modelling tools. The case firm is anonymised.
Findings: The Lean manufacturing literature ignores the real-world issue of shared resources, and this gap is attributable to the concept of ‘rightsizing’ tools and equipment that is widely promoted within the Lean community. The case panel
plant is characterised by extensive shared resources; many of which are also batch processes. The most appropriate pull-system method for this production environment is DBR. The detailed design of the DBR mechanism required a
controlled transfer buffer of overhead conveyance capacity after the Drum because the extent of downstream process variability risked it being unable to offload panels, hence compromising throughput.
Research limitations/implications: The study is based upon a single case. This consequently has implications for the ability to generalise from the results.
Practical Implications: When the DBR pull-system design was implemented it reduced the number of panels in WIP by 60%. This equated to a 56% (18 days worth) reduction of manufacturing lead time and more than doubled the plant’s inventory turns (from 9.1 to 21.2). It also significantly improved delivery schedule adherence, with downstream jig stoppages in the Final Assembly falling from an average of six to less than one per week. The financial benefit was independently audited to equate to an annualised value of $850 K. Consequently, this project was awarded the first prize at its parent enterprise’s annual worldwide process improvement competition.
Originality/value: This paper details a novel technique that permits the routings of multiple value streams to be mapped and is useful for highlighting the identity and location of shared resources. It also contributes significantly to the literature that is available on the relationship between the Lean paradigm and the management of shared production resources, and adds to the literature on the detailed design and implementation of a DBR pull system in a jobbing-type of environment
Access to Medicines and the TRIPS Agreement: What Next for Sub-Saharan Africa?
Get PDFWhen the proposal for an international intellectual property (IP) rights protection was included as an item in the agenda for negotiation in the Uruguay Round of World Trade Organization negotiations, it was strongly opposed by developing countries including Brazil, India, Argentina and others. The developing countries and least developed countries (LDCs) from Africa, realising the difficulties the Agreement would put them in, had vigorously campaigned against the inclusion of IP rights protection within the multilateral trading system. One of the chief areas of concern for the developing countries and LDCs was the difficulty of accessing affordable medicines under the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS) regime. While the resistance was gradually eroded and eventually neutralised during the long drawn Uruguay Round of Negotiations, the developing countries and the LDCs gained a few concessions in the post-TRIPS era in the form of Doha Declaration, which in their opinion would have given them the opportunity to invoke the emergency provisions of the Agreement in times of need to access essential medicines for their citizens. This was not to be the case, as the ground realities were difficult to manoeuvre and there were more impediments to invoking the flexibilities than originally perceived. This article will suggest that the best option available for sub-Saharan Africa is seeking an outright amendment of the TRIPS Agreement, as working within the parameters of the Agreement to achieve the goal of access to affordable medicines is not a viable option. It will also be argued that unless it acts urgently to seek the amendment it may be too late, as it could find itself left behind by both developing countries from other continents and patent-holding developed countries alike
CRIMINALIZING CORRUPTION: THE GLOBAL INITIATIVES
Get PDFTHE CHAPTER REVIEWS THE UNITED NATIONAL CONVENTION AGAINST CORRUPTION (UNCAC)AND THE ANTI-CORRUPTION INITIATIVES IN AFRICA, EUROPE, THE AMERICAS AND ASIA-PACIFIC REGION. IT CRITICALLY REVIEWS THE SCOPE OF THE KEY PROVISIONS OF THE UNCAC AND THE EFFECTIVENESS OF THE MONITORING PROCEDURES
Horizons in the Pharmacotherapy of Obesity
Get PDFObesity drugs have had a chequered history. In the recent past, only the low efficacy, pancreatic lipase inhibitor orlistat was available worldwide and it was little used. The 5HT2C agonist lorcaserin, and two combinations of old drugs have been approved in the United States but not in Europe. The diabetes drug liraglutide has been approved in both the US and Europe and seems likely to be most widely accepted. In view of regulators’ caution in approving obesity drugs, some (like beloranib) may initially be progressed for niche obesity markets. New drug targets have been identified in brown adipose tissue with the aim of not only activating thermogenesis but also increasing the capacity for thermogenesis in this tissue. Attempts are being made to match the efficacy of bariatric surgery by mimicking multiple gut hormones. Unapproved pharmacotherapies are tempting for some patients. Others remain optimistic about more conventional routes to pharmacotherapy
Hybridisation of GNSS with other wireless/sensors technologies onboard smartphones to offer seamless outdoors-indoors positioning for LBS applications
No full textLocation-based services (LBS) are becoming an important feature on today’s smartphones (SPs) and tablets. Likewise, SPs include many wireless/sensors technologies such as: global navigation satellite system (GNSS), cellular, wireless fidelity (WiFi), Bluetooth (BT) and inertial-sensors that increased the breadth and complexity of such
services.
One of the main demand of LBS users is always/seamless positioning service. However, no single onboard SPs technology can seamlessly provide location information from
outdoors into indoors. In addition, the required location accuracy can be varied to support multiple LBS applications. This is mainly due to each of these onboard wireless/sensors technologies has its own capabilities and limitations. For example, when outdoors GNSS receivers on SPs can locate the user to within few meters and supply accurate time to within few nanoseconds (e.g. ± 6 nanoseconds). However, when SPs enter into indoors this capability would be lost. In another vain, the other onboard wireless/sensors technologies can show better SP positioning accuracy, but based on some pre-defined knowledge and pre-installed infrastructure. Therefore, to overcome such limitations, hybrid measurements of these wireless/sensors technologies into a positioning system can
be a possible solution to offer seamless localisation service and to improve location accuracy.
This thesis aims to investigate/design/implement solutions that shall offer seamless/accurate SPs positioning and at lower cost than the current solutions. This thesis proposes three novel SPs localisation schemes including WAPs synchronisation/localisation scheme, SILS and UNILS. The schemes are based on hybridising GNSS with WiFi, BT and inertial-sensors measurements using combined localisation techniques including time-of-arrival (TOA) and dead-reckoning (DR). The first scheme is to synchronise and to define location of WAPs via outdoors-SPs’ fixed location/time information to help indoors localisation. SILS is to help locate any SP seamlessly as it goes from outdoors to indoors using measurements of GNSS, synched/located WAPs and BT-connectivity signals between groups of cooperated SPs in the vicinity. UNILS is to integrate onboard inertial-sensors’ readings into the SILS to provide seamless SPs positioning even in deep indoors, i.e. when the signals of WAPs or BT-anchors are considered not able to be used.
Results, obtained from the OPNET simulations for various SPs network size and indoors/outdoors combinations scenarios, show that the schemes can provide seamless
and locate indoors-SPs under 1 meter in near-indoors, 2-meters can be achieved when locating SPs at indoors (using SILS), while accuracy of around 3-meters can be achieved when locating SPs at various deep indoors situations without any constraint (using UNILS). The end of this thesis identifies possible future work to implement the proposed schemes on SPs and to achieve more accurate indoors SPs’ location
Robust steganographic techniques for secure biometric-based remote authentication
No full textBiometrics are widely accepted as the most reliable proof of identity, entitlement to services, and for crime-related forensics. Using biometrics for remote authentication is becoming an essential requirement for the development of knowledge-based economy in the digital age. Ensuring security and integrity of the biometric data or templates is critical to the success of deployment especially because once the data compromised the whole authentication system is compromised with serious consequences for identity theft, fraud as well as loss of privacy. Protecting biometric data whether stored in databases or transmitted over an open network channel is a serious challenge and cryptography may not be the answer. The main premise of this thesis is that Digital Steganography can provide an alternative security solutions that can be exploited to deal with the biometric transmission problem.
The main objective of the thesis is to design, develop and test steganographic tools to support remote biometric authentication. We focus on investigating the selection of biometrics feature representations suitable for hiding in natural cover images and designing steganography systems that are specific for hiding such biometric data rather than being suitable for general purpose. The embedding schemes are expected to have high security characteristics resistant to several types of steganalysis tools and maintain accuracy of recognition post embedding. We shall limit our investigations to embedding face biometrics, but the same challenges and approaches should help in developing similar embedding schemes for other biometrics. To achieve this our investigations and proposals are done in different directions which explain in the rest of this section.
Reviewing the literature on the state-of-art in steganography has revealed a rich source of theoretical work and creative approaches that have helped generate a variety of embedding schemes as well as steganalysis tools but almost all focused on embedding random looking secrets. The review greatly helped in identifying the main challenges in the field and the main criteria for success in terms of difficult to reconcile requirements on embedding capacity, efficiency of embedding, robustness against steganalysis attacks, and stego image quality. On the biometrics front the review revealed another rich source of different face biometric feature vectors. The review helped shaping our primary objectives as (1) identifying a binarised face feature factor with high discriminating power that is susceptible to embedding in images, (2) develop a special purpose content-based steganography schemes that can benefit from the well-defined structure of the face biometric data in the embedding procedure while preserving accuracy without leaking information about the source biometric data, and (3) conduct sufficient sets of experiments to test the performance of the developed schemes, highlight the advantages as well as limitations, if any, of the developed system with regards to the above mentioned criteria.
We argue that the well-known LBP histogram face biometric scheme satisfies the desired properties and we demonstrate that our new more efficient wavelet based versions called LBPH patterns is much more compact and has improved accuracy. In fact the wavelet version schemes reduce the number of features by 22% to 72% of the original version of LBP scheme guaranteeing better invisibility post embedding.
We shall then develop 2 steganographic schemes. The first is the LSB-witness is a general purpose scheme that avoids changing the LSB-plane guaranteeing robustness against targeted steganalysis tools, but establish the viability of using steganography for remote biometric-based recognition. However, it may modify the 2nd LSB of cover pixels as a witness for the presence of the secret bits in the 1st LSB and thereby has some disadvantages with regards to the stego image quality.
Our search for a new scheme that exploits the structure of the secret face LBPH patterns for improved stego image quality has led to the development of the first content-based steganography scheme. Embedding is guided by searching for similarities between the LBPH patterns and the structure of the cover image LSB bit-planes partitioned into 8-bit or 4-bit patterns. We shall demonstrate the excellent benefits of using content-based embedding scheme in terms of improved stego image quality, greatly reduced payload, reduced lower bound on optimal embedding efficiency, robustness against all targeted steganalysis tools. Unfortunately our scheme was not robust against the blind or universal SRM steganalysis tool. However we demonstrated robustness against SRM at low payload when our scheme was modified by restricting embedding to edge and textured pixels. The low payload in this case is sufficient to embed a secret full face LBPH patterns.
Our work opens new exciting opportunities to build successful real applications of content-based steganography and presents plenty of research challenges
Oxygen deprivation and the cellular response to hypoxia in adipocytes – perspectives on white and brown adipose tissues in obesity
No full textRelative hypoxia has been shown to develop in white adipose tissue depots of different types of obese mouse (genetic, dietary), and this leads to substantial changes in white
adipocyte function. These changes include increased production of inflammation-related adipokines (such as IL-6, leptin, Angptl4, and VEGF), an increase in glucose utilization and
lactate production, and the induction of fibrosis and insulin resistance. Whether hypoxia also occurs in brown adipose tissue depots in obesity has been little considered. However,
a recent study has reported low pO2 in brown fat of obese mice, this involving mitochondrial loss and dysfunction.We suggest that obesity-linked hypoxia may lead to similar alterations in brown adipocytes as in white fat cells – particularly changes in adipokine production, increased glucose uptake and lactate release, and insulin resistance. This would be expected to compromise thermogenic activity and the role of brown fat in glucose homeostasis and triglyceride clearance, underpinning the development of the metabolic syndrome. Hypoxia-induced augmentation of lactate production may also stimulate the “browning” of white fat depots through recruitment of UCP1 and the development of brite adipocytes
Intelligence Studies, Universities and Security
Get PDFThis article offers a critical assessment of academic intelligence studies in higher education. It argues that universities (and academics) should value this subject far more highly than they currently do. Doing so will enhance better public understanding of an increasingly important and unique device in modern governance. It will also improve the quality of intelligence activity by raising awareness of both good and bad practice, encourage lawfulness by means of public understanding and so defending a vital public service from ill-informed attacks in today’s conflicted world. This, rather than training potential officers, should be the primary purpose of intelligence studies
Automatic Speech Emotion Recognition- Feature Space Dimensionality and Classification Challenges
No full textIn the last decade, research in Speech Emotion Recognition (SER) has become a major endeavour in Human Computer Interaction (HCI), and speech processing. Accurate SER is essential for many applications, like assessing customer satisfaction with quality of services, and detecting/assessing emotional state of children in care. The large number of studies published on SER reflects the demand for its use. The main concern of this thesis is the investigation of SER from a pattern recognition and machine learning points of view. In particular, we aim to identify appropriate mathematical models of SER and examine the process of designing automatic emotion recognition schemes. There are major challenges to automatic SER including ambiguity about the list/definition of emotions, the lack of agreement on a manageable set of uncorrelated speech-based emotion relevant features, and the difficulty of collected emotion-related datasets under natural circumstances. We shall initiate our work by dealing with the identification of appropriate sets of emotion related features/attributes extractible from speech signals as considered from psychological and computational points of views. We shall investigate the use of pattern-recognition approaches to remove redundancies and achieve compactification of digital representation of the extracted data with minimal loss of information. The thesis will include the design of new or complement existing SER schemes and conduct large sets of experiments to empirically test their performances on different databases, identify advantages, and shortcomings of using speech alone for emotion recognition. Existing SER studies seem to deal with the ambiguity/dis-agreement on a “limited” number of emotion-related features by expanding the list from the same speech signal source/sites and apply various feature selection procedures as a mean of reducing redundancies. Attempts are made to discover more relevant features to emotion from speech. One of our investigations focuses on proposing a newly sets of features for SER, extracted from Linear Predictive (LP)-residual speech. We shall demonstrate the usefulness of the proposed relatively small set of features by testing the performance of an SER scheme that is based on fusing our set of features with the existing set of thousands of features using common machine learning schemes of Support Vector Machine (SVM) and Artificial Neural Network (ANN). The challenge of growing dimensionality of SER feature space and its impact on increased model complexity is another major focus of our research project. By studying the pros and cons of the commonly used feature selection approaches, we argued in favour of meta-feature selection and developed various methods in this direction, not only to reduce dimension, but also to adapt and de-correlate emotional feature spaces for improved SER model recognition accuracy. We used rincipal Component Analysis (PCA) and proposed Data Independent PCA (DIPCA) by training on independent emotional and non-emotional datasets. The DIPCA projections, especially when extracted from speech data coloured with different emotions or from Neutral speech data, had comparable capability to the PCA in terms of SER performance. Another adopted approach in this thesis for dimension reduction is the Random Projection (RP) matrices, independent of training data. We have shown that some versions of RP with SVM classifier can offer an adaptation space for Speaker Independent SER that avoid over-fitting and hence improves recognition accuracy. Using PCA trained on a set of data, while testing on emotional data features, has significant implication for machine learning in general.
The thesis other major contribution focuses on the classification aspects of SER. We investigate the drawbacks of the well-known SVM classifier when applied to a preprocessed data by PCA and RP. We shall demonstrate the advantages of using the Linear Discriminant Classifier (LDC) instead especially for PCA de-correlated metafeatures.
We initiated a variety of LDC-based ensembles classification, to test performance of scheme using a new form of bagging different subsets of metafeature subsets extracted by PCA with encouraging results.
The experiments conducted were applied on two benchmark datasets (Emo-Berlin and FAU-Aibo), and an in-house dataset in the Kurdish language. Recognition accuracy achieved by are significantly higher than the state of art results on all datasets. The results, however, revealed a difficult challenge in the form of persisting wide gap in accuracy over different datasets, which cannot be explained entirely by the differences between the natures of the datasets. We conducted various pilot studies that were based on various visualizations of the confusion matrices for the “difficult” databases to build multi-level SER schemes. These studies provide initial evidences to the presence of more than one “emotion” in the same portion of speech.
A possible solution may be through presenting recognition accuracy in a score-based measurement like the spider chart. Such an approach may also reveal the presence of Doddington zoo phenomena in SER
