Performance Measurement: A Conceptual Framework for Supply Chain Practices

AbstractMe--asurement of Supply Chain (SC) performance with regards to key practices of SC paradigms is the area which is under research. Presently there are no guidance or set rules under which we can measure SC performance. The lack of clarity and comparability concerns in this area creates misunderstanding and makes it more difficult to formulate a clear strategy. The aim of this research is to identify antecedents of existing SC paradigm's practices, as well as antecedents for SC performance measurement to formulate a conceptual framework. Based on this research, new sustainable SC performance measurement conceptual framework is proposed for existing SC paradigms. The detailed analysis presented in this research paper offers a set of characteristics and structure that industry as well as academia could use it as a guidance framework to measure SC performance

Exploring Robustness of Neural Networks through Graph Measures

Motivated by graph theory, artificial neural networks (ANNs) are traditionally structured as layers of neurons (nodes), which learn useful information by the passage of data through interconnections (edges). In the machine learning realm, graph structures (i.e., neurons and connections) of ANNs have recently been explored using various graph-theoretic measures linked to their predictive performance. On the other hand, in network science (NetSci), certain graph measures including entropy and curvature are known to provide insight into the robustness and fragility of real-world networks. In this work, we use these graph measures to explore the robustness of various ANNs to adversarial attacks. To this end, we (1) explore the design space of inter-layer and intra-layers connectivity regimes of ANNs in the graph domain and record their predictive performance after training under different types of adversarial attacks, (2) use graph representations for both inter-layer and intra-layers connectivity regimes to calculate various graph-theoretic measures, including curvature and entropy, and (3) analyze the relationship between these graph measures and the adversarial performance of ANNs. We show that curvature and entropy, while operating in the graph domain, can quantify the robustness of ANNs without having to train these ANNs. Our results suggest that the real-world networks, including brain networks, financial networks, and social networks may provide important clues to the neural architecture search for robust ANNs. We propose a search strategy that efficiently finds robust ANNs amongst a set of well-performing ANNs without having a need to train all of these ANNs.Comment: 18 pages, 15 figure

Speak Pakistan: Challenges in Developing Pakistan Sign Language using Information Technology

Gesture based communication called Sign Language (SL) is the fundamental communication channel between hard of hearing individuals. Communication through signing is a visual motion dialect. Hard of hearing individuals use gesture based communication as their primary medium for correspondence. Different countries have their own sign language as the United States of America has American Sign Language (ASL), China has Chinese Sign Language (CSL), India has Indian Sign Language (ISL), and similarly Pakistan has Pakistan Sign Language (PSL). Most of the developed nations have addressed the issues of their hearing impaired people by launching projects involving Information Technology to reduce this gap between a deaf and a normal person. In central and south Asia, a considerable work has been conducted on ISL and CSL. However, Pakistan Sign Language is a linguistically under-investigated in the absence of any structured information about the language contents, grammar, and tools and services for communication. Hence, the major contributions of this research are to highlight the challenges to bridge this communication gap for Pakistani deaf community by using the existing literature, and to propose an Information Technology based architectural framework to identify major components to build applications which may help bridging the gap between the deaf and normal people of the country

Locking Versus Non-Locking Miniplates in the Treatment of Mandibular Fractures in Above 35 Years Age Patients

Objective: To compare the frequency of short term post-operative infection of locking plates versus non-locking plate in mandibular fractures in patients above 35 years of age. Methodology: A randomized controlled study was conducted at the Department of Oral and Maxillofacial Surgery, Pakistan Institute of Medical Sciences, Islamabad from January 2018 to January 2019, involving a 100 patients (50 patients in each group). On the basis of history, clinical features, orthopantomogram (OPG) and intraoperative findings, the diagnosis of mandibular fractures was established. Group A patients were treated with reduction and fixation of fracture with locking miniplates and miniscrews following champy’s principle of osteosynthesis. Whereas in group B patients, fractures were reduced and fixed with non-locking miniplates and miniscrews following champy’s principle of osteosynthesis. Results: Effect modifiers such as age, gender, and type of fracture were controlled by stratification. A post-stratification chi-square test was applied. The 1 patient that had infection in group A had an age range 50- 65 years (53 years) (P value: 0.197) while the 2 patients that had infection in group B were younger in age range of 35-50 years (36 years and 38 years) (P value: 0.322). The 1 patient who had infection in group A was female (P value: 0.043) while the 2 patients of group B who had infection were also females (P value: 0.027). In group A, only 1 patient had infection at the para-symphysis of mandible according to site (P value: 0.494). In group B, 1 patient had infection at para-symphysis of mandible and 1 at the body of the mandible site (P value: 0.599).  The results were not statistically significant in terms of infection by the end of 3rd week. Conclusion: The study concludes that insignificant post-operative infection rates while managing mandibular fractures either by locking plates or non-locking plates.

Activation of nano kaolin clay for bio-glycerol conversion to a valuable fuel additive

High production of biodiesel results in a surplus of glycerol as a byproduct that leads to a drastic decline in the glycerol price as well as overall biodiesel production. Alternative methods must be introduced for the economical process for biodiesel production via utilization of crude glycerol into valuable chemicals or fuel additives. This study introduces an ecofriendly process of solketal synthesis from glycerol and acetone in the presence of a novel metakaolin clay catalyst, which is a useful additive in biodiesel or gasoline, in order to enhance the octane number and to control the emissions. Moreover, kaolin clay catalysts are low cost, abundantly available, eco-friendly and one of the more promising applications for solketal synthesis. In this study, raw kaolin clay was activated with an easy acid activation technique, modification in physicochemical and textural properties were determined by using X-ray diffraction (XRD), Fourier Transform Infra-Red (FTIR) spectroscopy, Brunauer–Emmett–Teller (BET) and Field Emission Scanning Electron Microscope. Among all acid-treated catalysts, metakaolin K3 have shown best catalytic properties, high surface area and pore size after acid activation with 3.0 mol/dm3 at 98 °C for 3 h. Acetalization of glycerol with acetone carried out in the presence of an environmentally friendly and inexpensive novel metakaolin K3 catalyst. The maximum yield of solketal obtained was 84% at a temperature of 50 °C, acetone/glycerol molar ratio 6/1 and for 90 min with novel metakaolin clay catalyst. Effect of various parameters (time, temperature, acetone/glycerol molar ratio, catalyst loading) on the solketal yield and glycerol conversion was discussed in detail. This approach offers an effective way to transform glycerol into solketal—a desirable green chemical with future industrial applications

A Novel Artificial Neural Network (ANN) Using The Mayfly Algorithm for Classification

acceptedVersio

Promoting entrepreneurship and affordable financing for uptake of improved toilets in Nigeria

Meeting the SDG targets on Sanitation in Nigeria requires households to construct over 2.4 million improved toilets every year up to 2030, which is a 15-fold increase in the current rate of latrine uptake. Hence business as usual is not an option for the country in the run up to 2030. Markets forces must be mobilized. The two-pronged strategy deployed in Nigeria addresses the issue of markets as well as affordable finances. Toilet Business Owners (TBOs) are trained and mobilized as successful for-profit enterprises by the existing public-sector enterprise development agencies while cheaper financing is being mobilized from both Public and private/commercial sources through local MFIs and community saving groups. This approach has led to the construction of 4650 improved toilets in 06 Local Government Areas of Nigeria and holds promise for the future