Search results for: multiple distribution supply chain network

Authors: Sandra Mitrovic, Gaurav Singh

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In many industries, including telecommunications, churn prediction has been a topic of active research. A lot of attention has been drawn on devising the most informative features, and this area of research has gained even more focus with spread of (social) network analytics. The call detail records (CDRs) have been used to construct customer networks and extract potentially useful features. However, to the best of our knowledge, no studies including network features have yet proposed a generic way of representing network information. Instead, ad-hoc and dataset dependent solutions have been suggested. In this work, we build upon a recently presented method (node2vec) to obtain representations for nodes in observed network. The proposed approach is generic and applicable to any network and domain. Unlike node2vec, which assumes a static network, we consider a dynamic and time-evolving network. To account for this, we propose an approach that constructs the feature representation of each node by generating its node2vec representations at different timestamps, concatenating them and finally compressing using an auto-encoder-like method in order to retain reasonably long and informative feature vectors. We test the proposed method on churn prediction task in telco domain. To predict churners at timestamp ts+1, we construct training and testing datasets consisting of feature vectors from time intervals [t1, ts-1] and [t2, ts] respectively, and use traditional supervised classification models like SVM and Logistic Regression. Observed results show the effectiveness of proposed approach as compared to ad-hoc feature selection based approaches and static node2vec.

Keywords: churn prediction, dynamic networks, node2vec, auto-encoders

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Authors: Mojtaba Mahmoodian, Joshua Phelan, Mehdi Shahparvari

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With a large percentage of countries’ total infrastructure expenditure attributed to water network maintenance, it is essential to optimise maintenance strategies to rehabilitate or replace underground pipes before failure occurs. The aim of this paper is to provide water utility managers with a maintenance management approach for underground water pipes, subject to external loading and material corrosion, to give the lowest life cycle cost over a predetermined time period. This reliability-based maintenance management methodology details the optimal years for intervention, the ideal number of maintenance activities to perform before replacement and specifies feasible renewal options and intervention prioritisation to minimise the life cycle cost. The study was then extended to include feasible renewal methods by determining the structural condition index and potential for soil loss, then obtaining the failure impact rating to assist in prioritising pipe replacement. A case study on optimisation of maintenance plans for the Melbourne water pipe network is considered in this paper to evaluate the practicality of the proposed methodology. The results confirm that the suggested methodology can provide water utility managers with a reliable systematic approach to determining optimum maintenance plans for pipe networks.

Keywords: water pipe networks, maintenance management, reliability analysis, optimum maintenance plan

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Authors: Ayman A. Swelum, Abdullah N. Al-Owaimer, Mohamed A. Abouheif

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This study aimed to evaluate the effects of sheep breed and the number of embryos transferred on the success of multiple ovulation and embryo transfer (MOET). Sixteen Najdi and Naeimi ewes were used as donors. Multiple ovulation was achieved using equine chorionic gonadotropin (eCG). Thirty-five recipient ewes were divided into four groups: Najdi or Naeimi ewes that received either one or two embryos. After lambing, the gestation length, litter size, and sex of the lambs were recorded. The rates of pregnancy, lambing, and embryo survival were lower in the recipient Najdi than Naeimi ewes when two embryos were transferred. In contrast, the Naeimi ewes that received one embryo had a significantly lower embryo transfer success. In conclusion, the response of ewes to multiple ovulation stimulation using eCG was significantly high in Naeimi ewes (9.8±1.17). Moreover, transferring one embryo resulted in a significantly high pregnancy rate in the Najdi sheep (60%).

Keywords: embryo transfer, multiple ovulation, Najdi, Naeimi, sheep

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Authors: Sanita Rubene, Martins Vilnitis, Juris Noviks

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Aerated concrete is a load bearing construction material, which has high heat insulation parameters. Walls can be erected from aerated concrete masonry constructions and in perfect circumstances additional heat insulation is not required. The most common problem in aerated concrete heat insulation properties is the humidity distribution throughout the cross section of the masonry elements as well as proper and conducted drying process of the aerated concrete construction because only dry aerated concrete masonry constructions can reach high heat insulation parameters. In order to monitor drying process of the masonry and detect humidity distribution throughout the cross section of aerated concrete masonry construction application of electrical impedance spectrometry is applied. Further test results and methodology of this non-destructive testing method is described in this paper.

Keywords: aerated concrete, electrical impedance spectrometry, humidity distribution, non-destructive testing

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Authors: Farnoosh Attar

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Nowadays, buffalo’s milk due to has highly nutritional properties, has a special place among consumers and its application for the production of dairy products due to the high technological properties is increasing day by day. In the present study, the physicochemical characteristics of Iranian buffalo’s milk were compared with cow's milk. According to chemical analysis, the amount of fat, protein, and total solid was higher in buffalo milk than cow's milk (respectively, 8.2%, 4.73%, and 15.92% compared with 3.5%, 3.25%, and 12.5%). Also, the percentage of cholesterol buffalo’s milk was less than in cow's milk. In contrast, no significant difference between the pH, acidity, and specific gravity was observed. The size of buffalo milk fat globules was larger than cow's milk. In addition, the profile of buffalo free fatty acids milk showed the relatively high distribution of long chain saturated fatty acids. The presence of four major bands related to αs casein, β casein, β-lactoglobulin, and α-lactalbumin with quite higher intensity than cow’s milk was also observed. The results obtained will provide a reference investigation to improve the developing of buffalo milk standard.

Keywords: buffalo milk, physicochemical characterization, standardization, dairy products

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Authors: Young Hee Geum

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We compare optimal quartic order method for the multiple zeros of nonlinear equations illustrating the basins of attraction. To construct basins of attraction effectively, we take a 600×600 uniform grid points at the origin of the complex plane and paint the initial values on the basins of attraction with different colors according to the iteration number required for convergence.

Keywords: basins of attraction, convergence, multiple-root, nonlinear equation

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Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev

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The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.

Keywords: distillation, machine learning, neural networks, quantization

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Authors: Maryam Shayan

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Programming frameworks have been utilized as a part of chemical industry process safety operation and configuration to enhance its effectiveness. This paper gives a brief survey and investigation of the best in class and effects of programming frameworks in process security. A study was completed by talking staff accountable for procedure wellbeing practices in the Iranian chemical process industry and diving into writing of innovation for procedure security. This article investigates the useful and operational attributes of programming frameworks for security and endeavors to sort the product as indicated by its level of effect in the administration chain of importance. The study adds to better comprehension of the parts of Information Communication Technology in procedure security, the future patterns and conceivable gaps for innovative work.

Keywords: programming frameworks, chemical industry process, process security, administration chain, information communication technology

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Authors: Ishtiaq Wahid, Masood Ahmad, Nighat Ayub, Sajad Ali

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Lifetime of a wireless sensor network (WSN) is directly proportional to the energy consumption of its constituent nodes. Routing in wireless sensor network is very challenging due its inherit characteristics. In hierarchal routing the sensor filed is divided into clusters. The cluster-heads are selected from each cluster, which forms a hierarchy of nodes. The cluster-heads are used to transmit the data to the base station while other nodes perform the sensing task. In this way the lifetime of the network is increased. In this paper a comparative study of hierarchal routing protocols are conducted. The simulation is done in NS-2 for validation.

Keywords: WSN, cluster, routing, sensor networks

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Authors: Ali Nadi, Ali Edrissi

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Relief demand and transportation links availability is the essential information that is needed for every natural disaster operation. This information is not in hand once a disaster strikes. Relief demand and network condition has been evaluated based on prediction method in related works. Nevertheless, prediction seems to be over or under estimated due to uncertainties and may lead to a failure operation. Therefore, in this paper a stochastic programming model is proposed to evaluate real-time relief demand and network condition at the onset of a natural disaster. To address the time sensitivity of the emergency response, the proposed model uses reinforcement learning for optimization of the total relief assessment time. The proposed model is tested on a real size network problem. The simulation results indicate that the proposed model performs well in the case of collecting real-time information.

Keywords: disaster management, real-time demand, reinforcement learning, relief demand

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Authors: Muhammad R. Ahmed, Mohammed Aseeri

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Wireless Sensor Network (WSN) consists of low-cost and multi functional resources constrain nodes that communicate at short distances through wireless links. It is open media and underpinned by an application driven technology for information gathering and processing. It can be used for many different applications range from military implementation in the battlefield, environmental monitoring, health sector as well as emergency response of surveillance. With its nature and application scenario, security of WSN had drawn a great attention. It is known to be valuable to variety of attacks for the construction of nodes and distributed network infrastructure. In order to ensure its functionality especially in malicious environments, security mechanisms are essential. Malicious or internal attacker has gained prominence and poses the most challenging attacks to WSN. Many works have been done to secure WSN from internal attacks but most of it relay on either training data set or predefined threshold. Without a fixed security infrastructure a WSN needs to find the internal attacks is a challenge. In this paper we present an internal attack detection method based on maximum entropy model. The final experimental works showed that the proposed algorithm does work well at the designed level.

Keywords: internal attack, wireless sensor network, network security, entropy

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Authors: Alok Raghav, Jamal Ahmad

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Background: Serum albumin glycation and advanced glycation end products (AGE) formation correlates in diabetes and its associated complications. Extensive modified human serum albumin is used to study the biochemical, electrochemical and functional properties in hyperglycemic environment with relevance to diabetes. We evaluate Spectroscopic, side chain modifications, amino acid analysis, biochemical and functional group properties in four glucose modified samples. Methods: A series four human serum albumin samples modified with glucose was characterized in terms of amino acid analysis, spectroscopic properties and side chain modifications. The diagnostic technique employed incorporates UV Spectroscopy, Fluorescence Spectroscopy, biochemical assays for side chain modifications, amino acid estimations, electrochemical and optical characterstic of glycated albumin. Conclusion: Glucose modified human serum albumin confers AGEs formation alters biochemical, electrochemical, optical, and functional property that depend on the reactivity of glucose and its concentration used for in-vitro glycation. A biochemical, electrochemical, optical, and functional characterization of modified albumin in-vitro produced AGE product that will be useful to interpret the complications and pathophysiological significance in diabetes.

Keywords: human serum albumin, glycated albumin, adavanced glycation end products, associated pathologies

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Authors: Jitendra Aswani

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In the first section of this study, impact of Global Financial Crisis (GFC) on the synchronization of fourteen Asian Stock Markets (ASM’s) of countries like Hong Kong, India, Thailand, Singapore, Taiwan, Pakistan, Bangladesh, South Korea, Malaysia, Indonesia, Japan, China, Philippines and Sri Lanka, has been analysed using the network science and its metrics like degree of node, clustering coefficient and network density. Then in the second section of this study by introducing the US stock market in existing network and developing a Minimum Spanning Tree (MST) spread of crisis from the US stock market to Asian Stock Markets (ASM) has been explained. Data used for this study is adjusted the closing price of these indices from 6th January, 2000 to 15th September, 2013 which further divided into three sub-periods: Pre, during and post-crisis. Using network analysis, it is found that Asian stock markets become more interdependent during the crisis than pre and post crisis, and also Hong Kong, India, South Korea and Japan are systemic important stock markets in the Asian region. Therefore, failure or shock to any of these systemic important stock markets can cause contagion to another stock market of this region. This study is useful for global investors’ in portfolio management especially during the crisis period and also for policy makers in formulating the financial regulation norms by knowing the connections between the stock markets and how the system of these stock markets changes in crisis period and after that.

Keywords: global financial crisis, Asian stock markets, network science, Kruskal algorithm

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Authors: Shelby Simpson, William Stanley, Namir Naba, Xiaodi Wang

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Both t-SNE and UMAP are brand new state of art tools to predominantly preserve the local structure that is to group neighboring data points together, which indeed provides a very informative visualization of heterogeneity in our data. In this research, we develop a t-SNE and UMAP base neural network image classification algorithm to embed the original dataset to a corresponding low dimensional dataset as a preprocessing step, then use this embedded database as input to our specially designed neural network classifier for image classification. We use the fashion MNIST data set, which is a labeled data set of images of clothing objects in our experiments. t-SNE and UMAP are used for dimensionality reduction of the data set and thus produce low dimensional embeddings. Furthermore, we use the embeddings from t-SNE and UMAP to feed into two neural networks. The accuracy of the models from the two neural networks is then compared to a dense neural network that does not use embedding as an input to show which model can classify the images of clothing objects more accurately.

Keywords: t-SNE, UMAP, fashion MNIST, neural networks

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Authors: Jyh J. Chen, Fu H. Yang, Ming H. Liao

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This study describes a capillary-based device integrated with the heating and cooling modules for polymerase chain reaction (PCR). The device consists of the reaction polytetrafluoroethylene (PTFE) capillary, the aluminum blocks, and is equipped with two cartridge heaters, a thermoelectric (TE) cooler, a fan, and some thermocouples for temperature control. The cartridge heaters are placed into the heating blocks and maintained at two different temperatures to achieve the denaturation and the extension step. Some thermocouples inserted into the capillary are used to obtain the transient temperature profiles of the reaction sample during thermal cycles. A 483-bp DNA template is amplified successfully in the designed system and the traditional thermal cycler. This work should be interesting to persons involved in the high-temperature based reactions and genomics or cell analysis.

Keywords: polymerase chain reaction, thermal cycles, capillary, TE cooler

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Authors: Ken Munro

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Cruise ships are possibly the most complex collection of systems it is possible to find in one physical, moving location. Propulsion, navigation, power generation and more, combined with a hotel, restaurant, casino, theatre etc, with safety and fire control systems to boot. That complexity creates huge challenges with keeping OT and IT systems apart. Ships engines are often remotely managed, network segregation is often defeated through troubleshooting when at sea. This session will refer to multiple entertaining and informative tales of taking control of ships, including accessing a ships Azipods via a game simulator for passengers. Fortunately, genuine attacks against vessels are very rare, but the effects and impacts to world trade are becoming increasingly obvious.

Keywords: maritime security, cybersecurity, OT, IT, networks

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Authors: Mourad Bakouka, Abdelaziz Rabehi

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Companies need to have logistics and transportation in place that can adapt to the changing nature of construction sites. This ensures they can react quickly when needed. A study was conducted to develop a way to locate and track materials on construction sites. The system is an RFID/GPS integration that's required to pull off this feat. The study also reports how the platform has been used in construction. They found many advantages to using it, including reductions in both time and costs as well as improved management of materials orders. . For example, the time in which a project could start up was shortened from two weeks to three days with just a single digital order. As of now, the technology is still limited in its widespread adoption due largely to overall lack of awareness and difficulty connecting to it. However, as more and more companies embrace it in construction, the technology is expected to become ubiquitous. The developed platform provides contractors and construction managers with real-time information about the status of materials and work, allowing them to better manage the workflow in a project. The study sheds new light on this subject, which is essential to know. This work is becoming increasingly aware of the use of smart tools in constructing buildings.

Keywords: materials management, internet of things (IoT), radio frequency identification (RFID), construction site, supply chain management

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Authors: RuiJin Zhang, HengJiang Cai, JinSong Gui

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It takes Patinopecten yessoensis larvae more than 20 days from spawning to settlement. Due to the natural environmental factors such as current, Patinopecten yessoensis larvae are transported to a distance more than hundreds of kilometers, leading to a high instability of their spatial and temporal distribution and great difficulties in the natural spat collection. Therefore predicting the distribution is of great significance to improve the operating efficiency of the collecting. Hydrodynamic model of Northern China Yellow Sea was established and the motions equations of physical oceanography and verified by the tidal harmonic constants and the measured data velocities of Dalian Bay. According to the passivity drift characteristics of the larvae, combined with the hydrodynamic model and the particle tracking model, the spatial and temporal distribution prediction model was established and the spatial and temporal distribution of the larvae under the influence of flow and wind were simulated. It can be concluded from the model results: ocean currents have greatest impacts on the passive drift path and diffusion of Patinopecten yessoensis larvae; the impact of wind is also important, which changed the direction and speed of the drift. Patinopecten yessoensis larvae were generated in the sea along Zhangzi Island and Guanglu-Dachangshan Island, but after two months, with the impact of wind and currents, the larvae appeared in the west of Dalian and the southern of Lvshun, and even in Bohai Bay. The model results are consistent with the relevant literature on qualitative analysis, and this conclusion explains where the larvae come from in the perspective of numerical simulation.

Keywords: numerical simulation, Patinopecten yessoensis larvae, predicting model, spatial and temporal distribution

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Authors: Ali Akbar Heydari

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Control charts are an important tool of statistical quality control. Thesecharts are used to detect and eliminate unwanted special causes of variation that occurred during aperiod of time. The design and operation of control charts require the determination of three design parameters: the sample size (n), the sampling interval (h), and the width coefficient of control limits (k). Thevariable parameters (VP) x-bar controlchart is the x-barchart in which all the design parameters vary between twovalues. These values are a function of the most recent process information. In fact, in the VP x-bar chart, the position of each sample point on the chart establishes the size of the next sample and the timeof its sampling. The synthetic x-barcontrol chartwhich integrates the x-bar chart and the conforming run length (CRL) chart, provides significant improvement in terms of detection power over the basic x-bar chart for all levels of mean shifts. In this paper, we introduce the syntheticVP x-bar control chart for monitoring changes in the process mean. To determine the design parameters, we used a statistical design based on the minimum out of control average run length (ARL) criteria. The optimal chart parameters of the proposed chart are obtained using the Markov chain approach. A numerical example is also done to show the performance of the proposed chart and comparing it with the other control charts. The results show that our proposed syntheticVP x-bar controlchart perform better than the synthetic x-bar controlchart for all shift parameter values. Also, the syntheticVP x-bar controlchart perform better than the VP x-bar control chart for the moderate or large shift parameter values.

Keywords: control chart, markov chain approach, statistical design, synthetic, variable parameter

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Authors: Mohammed Affanuddin H. Siddique, Jayesh S. Shukla, Chetan B. Meshram

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The neural networks are one of the power tools of machine learning. After the invention of perceptron in early 1980's, the neural networks and its application have grown rapidly. Neural networks are a technique originally developed for pattern investigation. The structure of a neural network consists of neurons connected through synapse. Here, we have investigated the different algorithms and cost function reduction techniques for optimization of vertical axis wind turbine (VAWT) rotor blades. The aerodynamic force coefficients corresponding to the airfoils are stored in a database along with the airfoil coordinates. A forward propagation neural network is created with the input as aerodynamic coefficients and output as the airfoil co-ordinates. In the proposed algorithm, the hidden layer is incorporated into cost function having linear and non-linear error terms. In this article, it is observed that the ANNs (Artificial Neural Network) can be used for the VAWT’s optimization.

Keywords: VAWT, ANN, optimization, inverse design

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Authors: Saidi Nabiha, Khaled Zaatouri, Walid Fajraoui, Tahar Ezzeddine

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The market of Wireless Sensor Network WSN has a great potential and development opportunities. Researchers are focusing on optimization in many fields like efficient deployment and routing protocols. In this article, we will concentrate on energy efficiency for WSN because WSN nodes are habitually deployed in severe No Man’s Land with batteries are not rechargeable, so reducing energy consumption represents an important challenge to extend the life of the network. We will present the design of new WSN mote based on ultra low power STM32L microcontrollers and the ZIGBEE transceiver CC2520. We will compare it to existent motes and we will conclude that our mote is promising in energy consumption.

Keywords: component, WSN mote, power consumption, STM32L, sensors, CC2520

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Authors: Melanie Adrian, Elspeth McCulloch, Emily-Jean Gallant

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Resources -financial, physical, and human- are increasingly constrained in higher education. University classes are getting bigger, and the concomitant grading burden on faculty is growing rapidly. Multiple-choice exams are seen by some as one solution to these changes. How much students retain, however, and what their testing experience is, continues to be debated. Are multiple-choice exams serving students well, or are they bearing the burden of these developments? Is there a way to address both the resource constraints and make these types of exams more meaningful? In short, how do we engender evaluation methods for large-scale classes that provide opportunities for heightened student learning and enrichment? The following article lays out a testing approach we have employed in four iterations of the same third-year law class. We base our comments in this paper on our initial observations as well as data gathered from an ethics-approved study looking at student experiences. This testing approach provides students with multiple opportunities for revision (thus increasing chances for long term retention), is both individually and collaboratively driven (thus reflecting the individual effort and group effort) and is automatically graded (thus draining limited institutional resources). We found that overall students appreciated the approach and found it more ‘humane’, that it notably reduced pre-exam and intra-exam stress levels, increased ease, and lowered nervousness.

Keywords: exam, higher education, multiple-choice, law

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Authors: Nan Deng, Zhenqiu Liu

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Thousands of patients with metastatic tumors were diagnosed with cancers of unknown primary sites each year. The inability to identify the primary cancer site may lead to inappropriate treatment and unexpected prognosis. Nowadays, a large amount of genomics and transcriptomics cancer data has been generated by next-generation sequencing (NGS) technologies, and The Cancer Genome Atlas (TCGA) database has accrued thousands of human cancer tumors and healthy controls, which provides an abundance of resource to differentiate cancer types. Meanwhile, deep convolutional neural networks (CNNs) have shown high accuracy on classification among a large number of image object categories. Here, we utilize 25 cancer primary tumors and 3 normal tissues from TCGA and convert their RNA-Seq gene expression profiling to color images; train, validate and test a CNN classifier directly from these images. The performance result shows that our CNN classifier can archive >80% test accuracy on most of the tumors and normal tissues. Since the gene expression pattern of distant metastases is similar to their primary tumors, the CNN classifier may provide a potential computational strategy on identifying the unknown primary origin of metastatic cancer in order to plan appropriate treatment for patients.

Keywords: bioinformatics, cancer, convolutional neural network, deep leaning, gene expression pattern

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Authors: Joanna Smoluk-Sikorska, Władysława Łuczka

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Organic farming is an important element of sustainable agriculture. It has been developing very dynamically in Poland, especially since Poland’s accession to the EU. Nevertheless, properly functioning organic market is a necessary condition justifying development of organic agriculture. Despite significant improvement, this market in Poland is still in the initial stage of growth. An important element of the market is distribution, especially retail, which offers specified product range to consumers. Therefore, there is a need to investigate retail outlets offering organic food in order to improve functioning of this part of the market. The inquiry research conducted in three types of outlets offering organic food, between 2011 and 2012 in the 8 largest Polish cities, shows that the majority of outlets offer cereals, processed fruit and vegetables as well as spices and the least shops – meat and sausages. The distributors mostly indicate unsatisfactory product range of suppliers as the reason for this situation. The main providers of the outlets are wholesalers, particularly in case of processed products, and in fresh products – organic farms. A very important distribution obstacle is dispersion of producers, which generates high transportation costs and what follows that, high price of organics. In the investigated shops, the most often used price calculation method is a cost method. The majority of the groceries and specialist shops apply margins between 21 and 40%. The margin in specialist outlets is the highest, in regard to the qualified service and advice. In turn, most retail networks declare the margin between 0 and 20%, which is consistent with low-price strategy applied in these shops. Some lacks in the product range of organics and in particular high prices cause that the demand volume is rather low. Therefore there is a need to support certain market actions, e.g. on-farm processing or promotion.

Keywords: organic food, retail, product range, supply sources

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Authors: Rachel Y. Zhang, Christopher K. Anderson

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A critical aspect of revenue management is a firm’s ability to predict demand as a function of price. Historically hotels have used simple time series models (regression and/or pick-up based models) owing to the complexities of trying to build casual models of demands. Machine learning approaches are slowly attracting attention owing to their flexibility in modeling relationships. This study provides an overview of approaches to forecasting hospitality demand – focusing on the opportunities created by machine learning approaches, including K-Nearest-Neighbors, Support vector machine, Regression Tree, and Artificial Neural Network algorithms. The out-of-sample performances of above approaches to forecasting hotel demand are illustrated by using a proprietary sample of the market level (24 properties) transactional data for Las Vegas NV. Causal predictive models can be built and evaluated owing to the availability of market level (versus firm level) data. This research also compares and contrast model accuracy of firm-level models (i.e. predictive models for hotel A only using hotel A’s data) to models using market level data (prices, review scores, location, chain scale, etc… for all hotels within the market). The prospected models will be valuable for hotel revenue prediction given the basic characters of a hotel property or can be applied in performance evaluation for an existed hotel. The findings will unveil the features that play key roles in a hotel’s revenue performance, which would have considerable potential usefulness in both revenue prediction and evaluation.

Keywords: hotel revenue, k-nearest-neighbors, machine learning, neural network, prediction model, regression tree, support vector machine

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Authors: A. Chellil, A. Nour, S. Lecheb , H. Mechakra, L. Addar, H. Kebir

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This paper present a mechanical characteristics on fatigue crack propagation in Aluminium Plate based on strain and stress distribution using the abaqus software. The changes in shear strain and stress distribution during the fatigue cycle with crack growth is identified. In progressive crack in the strain distribution and the stress is increase in the critical zone. Numerical Modal analysis of the model developed, prove that the Eigen frequencies of aluminium plate were decreased after cracking, and this reduce is nonlinear. These results can provide a reference for analysts and designers of aluminium alloys in aeronautical systems. Therefore, the modal analysis is an important factor for monitoring the aeronautic structures.

Keywords: aluminum alloys, plate, crack, failure

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Authors: Ntandoyenkosi Moyo

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Majority of rural Eastern Cape villages of South Africa households do not have access to safe water supply. Due to changes in climatic conditions for example higher temperatures, these sources become not reliable in supplying adequate and safe water to the population. These rural populations due to the drying up of water resources have to find other alternative ways to get water. Climate change has an impact on the reliability of water resources and this has an impact on rural communities. This study seeks to establish what alternative ways do people use when affected by unfavorable conditions like less rainfall and increased temperatures. The study also seeks to investigate any local and provincial intervention in the provision of water to the village. Interventions can be in the form of programmes or initiatives that involve water supply strategies. The community should participate fully in making sure that their place is serviced. The study will identify households with improved sources (JOJO tanks) and those with unimproved sources (rivers) and investigate what alternatives they resort to when their sources dry up. The study also investigates community views on whether they have any challenges of water supply (reliability and adequacy) as required by section 27(1) (b) of the constitution which states that everyone should have access to safe and clean water.

Keywords: rural water resources, temperature, improved sources, unimproved sources

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Authors: Paulu Saramge Shalika Nirupani Seram

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The study delves into the complex dynamics of social networks and how they affect paddy farmers’ adoption of agricultural technologies, which are included in Yaya Development program, Weedy rice program and Good Agricultural Practices (GAP) program in Matara district. Identify the social networks among the farmers of ongoing Extension Programs in Matara district, examine the farmers’ adoption level to the ongoing extension programs in Matara district, analyze the impacts of social networks for the adoption to the technologies of ongoing extension programs and give suggestions and recommendations to improve the social network of paddy farmers in Matara District for ongoing extension programs are the objectives of this research. A structured questionnaire survey was conducted with 25 farmers from Matara-North (Wilpita), 25 farmers from Matara-Central (Kamburupitiya), and 25 farmers from Matara-South (Malimbada). UCINET (Version -6.771) software was used for social network analysis, and other than that, descriptive statistics and inferential statistics were used to analyze the findings. Matara-North has the highest social network density, and Matara-South has the lowest social network density according to the social network analysis. Dissemination of intensive technologies requires the most prominent actors of the social network, and in Matara district, agricultural instructors have the highest ability to disseminate technologies. The influence of actors in the social network, the trustworthiness of AI officers, and the trust of indigenous knowledge about paddy cultivation have a significant effect on the technology adoption of farmers. The research endeavors to contribute a nuanced understanding of the social networks and agricultural technology adoption in Matara District, offering practical insights for stakeholders involved in agricultural extension services.

Keywords: agricultural extension, paddy cultivation, social network, technology adoption

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Authors: Mari Jaakkola, Jasmiina Haverinen, Tiina Tolonen, Vesa Virtanen

Abstract:

These process monitoring of biogas plant gives valuable information of the function of the process and help to maintain a stable process. The costs of basic monitoring are often much lower than the costs associated with re-establishing a biologically destabilised plant. Reactor acidification through reactor overload is one of the most common reasons for process deterioration in anaerobic digesters. This occurs because of a build-up of volatile fatty acids (VFAs) produced by acidogenic and acetogenic bacteria. VFAs cause pH values to decrease, and result in toxic conditions in the reactor. Ammonia ensures an adequate supply of nitrogen as a nutrient substance for anaerobic biomass and increases system's buffer capacity, counteracting acidification lead by VFA production. However, elevated ammonia concentration is detrimental to the process due to its toxic effect. VFAs are considered the most reliable analytes for process monitoring. To obtain accurate results, sample storage and transportation need to be carefully controlled. This may be a challenge for off-line laboratory analyses especially when the plant is located far away from the laboratory. The aim of this study was to investigate the correlation between fatty acids, ammonium, and bacteria in the anaerobic digestion samples obtained from an industrial biogas factory. The stability of the analytes was studied comparing the results of the on-site analyses performed in the factory site to the results of the samples stored at room temperature and -18°C (up to 30 days) after sampling. Samples were collected in the biogas plant consisting of three separate mesofilic AD reactors (4000 m³ each) where the main feedstock was swine slurry together with a complex mixture of agricultural plant and animal wastes. Individual VFAs, ammonium, and nutrients (K, Ca, Mg) were studied by capillary electrophoresis (CE). Longer chain fatty acids (oleic, hexadecanoic, and stearic acids) and bacterial profiles were studied by GC-MSD (Gas Chromatography-Mass Selective Detector) and 16S rDNA, respectively. On-site monitoring of the analytes was performed by CE. The main VFA in all samples was acetic acid. However, in one reactor sample elevated levels of several individual VFAs and long chain fatty acids were detected. Also bacterial profile of this sample differed from the profiles of other samples. Acetic acid decomposed fast when the sample was stored in a room temperature. All analytes were stable when stored in a freezer. Ammonium was stable even at a room temperature for the whole testing period. One reactor sample had higher concentration of VFAs and long chain fatty acids than other samples. CE was utilized successfully in the on-site analysis of separate VFAs and NH₄ in the biogas production site. Samples should be analysed in the sampling day if stored in RT or freezed for longer storage time. Fermentation reject can be stored (and transported) at ambient temperature at least for one month without loss of NH₄. This gives flexibility to the logistic solutions when reject is used as a fertilizer.

Keywords: anaerobic digestion, capillary electrophoresis, ammonium, bacteria

Procedia PDF Downloads 168

Authors: Amar Omeiri

Abstract:

This paper presents a three-phase shunt active power filter for current harmonics suppression and reactive power compensation using the supply current as reference. The proposed APF has a simple control circuit; it consists of detecting the supply current instead of the load current. The advantages of this APF are simplicity of control circuits and low implementation cost. The simulation results show that the proposed APF can compensate the reactive power and suppress current harmonics with two types of non-linear loads.

Keywords: active power filter, current harmonics and reactive power compensation, PWM inverter, Total Harmonic Distortion, power quality

Procedia PDF Downloads 588