Search results for: car sequencing and operator allocation

Authors: G. R. Hashemi Tabar, G. R. Razmi, F. Mirshekar

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Echinococcus granulosus have ten strains from G1 to G9. Each strain is related to special intermediated host. The morphology, epidemiology, treatment and control in these strains are different. There are many morphological and molecular methods to differentiate of Echinococcus strains. However, using both methods were provided better information about identification of each strain. The aim of study was to identify Echinococcus granulosus strain of hydrated cysts in slaughtered sheep using morphological and molecular methods in Mashhad area. In the present study, the infected liver and lung with hydatid cysts were collected and transferred to laboratory. The hydatid cyst liquid was extracted and morphological characters of rostellar hook protosclocies were measured using micrometer ocular. The total length of large blade length of large hooks, total length of small and blade length of small hooks, and number of hooks per protoscolex were 23± 0.3μm, 11.7±0.5 μm, 19.3±1.1 μm,8±1.1 and 33.7±0.7 μm, respectively. In molecular section of the study, DNA each samples was extracted with MBST Kit and development of PCR using special primers (EgF, EgR) which amplify fragment of ITS1 gen. The PCR product was digested with Bsh1236I enzyme. Based on pattern of PCR-RLFP results (four band forming), G1, G2 and G3 strain of Echinococcus granulosus were obtained. Differentiation of three strains was done using sequencing analysis and G1 strain was diagnosed. The agreement between the molecular results with morphometric characters of rosetellar hook was confirmed the presence of G1 strain of Echinococcus in the slaughtered sheep of Mashhad area.

Keywords: Echinococcus granulosus, Hydatid cyst, PCR, sheep

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Authors: Dimitrios Ntardas, Alexandros Tzanetos, Georgios Dounias

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High Voltage Substations (HVS) are the intermediate step between production of power and successfully transmitting it to clients, making them one of the most important checkpoints in power grids. Nowadays - renewable resources and consequently distributed generation are growing fast, the construction of HVS is of high importance both in terms of quality and time completion so that new energy producers can quickly and safely intergrade in power grids. The resources needed, such as machines and workers, should be carefully allocated so that the construction of a HVS is completed on time, with the lowest possible cost (e.g. not spending additional cost that were not taken into consideration, because of project delays), but in the highest quality. In addition, there are milestones and several checkpoints to be precisely achieved during construction to ensure the cost and timeline control and to ensure that the percentage of governmental funding will be granted. The management of such a demanding project is a NP-hard problem that consists of prerequisite constraints and resource limits for each task of the project. In this work, a hybrid meta-heuristic method is implemented to solve this problem. Meta-heuristics have been proven to be quite useful when dealing with high-dimensional constraint optimization problems. Hybridization of them results in boost of their performance.

Keywords: hybrid meta-heuristic methods, substation construction, resource allocation, time-cost efficiency

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Authors: Samina Jam Nazeer Ahmad, Samia Yasin, Ijaz Ahmad, Muhammad Tahir, Jam Nazeer Ahmad

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Phytoplasmas are phloem-inhibited plant pathogenic bacteria that are transferred by insect vectors. Among biotic factors, Phytoplasma infection induces abnormality influencing the physiology as well as morphology of plants. In 16Sr-IX group phytoplasma-infected brassica compestris, flower abnormalities have been associated with changes in the expression of floral development genes. To determine whether methylation was involved in down-regulation of flower development, the process of DNA methylation and Demethylation was investigated as a possible mechanism for regulation of floral gene expression in phytoplasma infected Brassica transmitted by Orosious orientalis vector by using RT-PCR, MSRE-PCR, Southern blotting, Bisulfite Sequencing, etc. Transcriptional expression of methylated genes was found to be globally down-regulated in plants infected with phytoplasma, but not severely in those infested by insect vectors and variation in expression was found in genes involved in methylation. These results also showed that genes particularly orthologous to Arabidopsis APETALA3 involved in petal formation and flower development was down-regulated severely in phytoplasma-infected brassica and with the fact that phytoplasma and insect induce variation in developmental gene expression. The DNA methylation status of flower developmental gene in phytoplasma infected plants with 5-azacytidine restored gene expression strongly suggesting that DNA methylation was involved in down-regulation of floral development genes in phytoplasma infected brassica.

Keywords: genes expression, phytoplasma, DNA methylation, flower development

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Authors: Bezhan Ghvaberidze

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A multiple criteria optimization approach for the solution of the Fuzzy Vehicle Routing Problem (FVRP) is proposed. For the possibility environment the levels of movements between customers are calculated by the constructed simulation interactive algorithm. The first criterion of the bi-criteria optimization problem - minimization of the expectation of total fuzzy travel time on closed routes is constructed for the FVRP. A new, second criterion – maximization of feasibility of movement on the closed routes is constructed by the Choquet finite averaging operator. The FVRP is reduced to the bi-criteria partitioning problem for the so called “promising” routes which were selected from the all admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in the real-time computing. For the numerical solution of the bi-criteria partitioning problem the -constraint approach is used. An exact algorithm is implemented based on D. Knuth’s Dancing Links technique and the algorithm DLX. The Main objective was to present the new approach for FVRP, when there are some difficulties while moving on the roads. This approach is called FVRP for extreme conditions (FVRP-EC) on the roads. Also, the aim of this paper was to construct the solving model of the constructed FVRP. Results are illustrated on the numerical example where all Pareto-optimal solutions are found. Also, an approach for more complex model FVRP with time windows was developed. A numerical example is presented in which optimal routes are constructed for extreme conditions on the roads.

Keywords: combinatorial optimization, Fuzzy Vehicle routing problem, multiple objective programming, possibility theory

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Authors: Chris George, Adam Hamlin, Lily Pereg, Richard Charlesworth, Gal Winter

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Background: According to the ‘hygiene hypothesis’ the current rise in allergies and autoimmune diseases stems mainly from reduced microbial exposure due, amongst other factors, to urbanisation and distance from soil. However, this hypothesis is based on epidemiological and not biological data. Useful insights into the underlying mechanisms of this hypothesis can be gained by studying our interaction with soil. Soil microbiota may be directly ingested or inhaled by humans, enter the body through skin-soil contact or using plants as vectors. This study aims to examine the ability of soil microbiota to colonise the gut, study the interaction of soil microbes with the immune system and their potential protective activity. Method: The nutrition of the rats was supplemented daily with fresh or autoclaved soil for 21 days followed by 14 days of no supplementations. Faecal samples were collected throughout and analysed using 16S sequencing. At the end of the experiment rats were sacrificed and tissues and digesta were collected. Results/Conclusion: Results showed significantly higher richness and diversity following soil supplementation even after recovery. Specific soil microbial groups identified as able to colonise the gut. Of particular interest was the mucosal layer which emerged as a receptive host for soil microorganisms. Histological examination revealed innate and adaptive immune activation. Findings of this study reinforce the ‘hygiene hypothesis’ by demonstrating the ability of soil microbes to colonise the gut and activate the immune system. This paves the way for further studies aimed to examine the interaction of soil microorganisms with the immune system.

Keywords: gut microbiota, hygiene hypothesis, microbiome, soil

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Authors: Nouira Mariem, Ben Rayana Hazem, Ennigrou Samir

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Background and aim: During the past decade, the frequency of extrapulmonary forms of tuberculosis has increased. These forms are under-diagnosed using conventional tests. The aim of this study was to evaluate the performance of the Tuberculin Skin Test (TST) for the diagnosis of tuberculosis, using the ROC curve and Fagan’s Nomogram methodology. Methods: This was a case-control, multicenter study in 11 anti-tuberculosis centers in Tunisia, during the period from June to November2014. The cases were adults aged between 18 and 55 years with confirmed tuberculosis. Controls were free from tuberculosis. A data collection sheet was filled out and a TST was performed for each participant. Diagnostic accuracy measures of TST were estimated using ROC curve and Area Under Curve to estimate sensitivity and specificity of a determined cut-off point. Fagan’s nomogram was used to estimate its predictive values. Results: Overall, 1053 patients were enrolled, composed of 339 cases (sex-ratio (M/F)=0.87) and 714 controls (sex-ratio (M/F)=0.99). The mean age was 38.3±11.8 years for cases and 33.6±11 years for controls. The mean diameter of the TST induration was significantly higher among cases than controls (13.7mm vs.6.2mm;p=10-6). Area Under Curve was 0.789 [95% CI: 0.758-0.819; p=0.01], corresponding to a moderate discriminating power for this test. The most discriminative cut-off value of the TST, which were associated with the best sensitivity (73.7%) and specificity (76.6%) couple was about 11 mm with a Youden index of 0.503. Positive and Negative predictive values were 3.11% and 99.52%, respectively. Conclusion: In view of these results, we can conclude that the TST can be used for tuberculosis diagnosis with a good sensitivity and specificity. However, the skin induration measurement and its interpretation is operator dependent and remains difficult and subjective. The combination of the TST with another test such as the Quantiferon test would be a good alternative.

Keywords: tuberculosis, tuberculin skin test, ROC curve, cut-off

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Authors: Pankhuri Dagaonkar, Charumani Singh, Poornima Krothapalli, Krishna Karthik

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The backbone of any retail e-commerce success story is a unique design of supply chain network, providing the business an unparalleled speed and scalability. Primary goal of the supply chain strategy is to meet customer expectation by offering fastest deliveries while keeping the cost minimal. Meeting this objective at the large market that India provides is the problem statement that we have targeted here. There are many models and optimization techniques focused on network design to identify the ideal facility location and size, optimizing cost and speed. In this paper we are presenting a tactical approach to optimize cost of an existing network for a predefined speed. We have considered both forward and reverse logistics of a retail e-commerce supply chain consisting of multiple fulfillment (warehouse) and delivery centers, which are connected via sortation nodes. The mathematical model presented here determines if the shipment from a node should get sorted directly for the last mile delivery center or it should travel as consolidated package to another node for further sortation (resort). The objective function minimizes the total cost by varying the resort percentages between nodes and provides the optimal resource allocation and number of sorts at each node.

Keywords: distribution strategy, mathematical model, network design, supply chain management

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Authors: Tiago Sampaio, André Vasconcelos, Bruno Fragoso

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The Normalized Systems Theory, which is designed to be applied to software architectures, provides a set of theorems, elements and rules, with the purpose of enabling evolution in Information Systems, as well as ensuring that they are ready for change. In order to make that possible, this work’s solution is to apply the Normalized Systems Theory to the domain of enterprise architectures, using Archimate. This application is achieved through the adaptation of the elements of this theory, making them artifacts of the modeling language. The theorems are applied through the identification of the viewpoints to be used in the architectures, as well as the transformation of the theory’s encapsulation rules into architectural rules. This way, it is possible to create normalized enterprise architectures, thus fulfilling the needs and requirements of the business. This solution was demonstrated using the Portuguese Public Procurement System. The Portuguese government aims to make this system as fair as possible, allowing every organization to have the same business opportunities. The aim is for every economic operator to have access to all public tenders, which are published in any of the 6 existing platforms, independently of where they are registered. In order to make this possible, we applied our solution to the construction of two different architectures, which are able of fulfilling the requirements of the Portuguese government. One of those architectures, TO-BE A, has a Message Broker that performs the communication between the platforms. The other, TO-BE B, represents the scenario in which the platforms communicate with each other directly. Apart from these 2 architectures, we also represent the AS-IS architecture that demonstrates the current behavior of the Public Procurement Systems. Our evaluation is based on a comparison between the AS-IS and the TO-BE architectures, regarding the fulfillment of the rules and theorems of the Normalized Systems Theory and some quality metrics.

Keywords: archimate, architecture, broker, enterprise, evolvable systems, interoperability, normalized architectures, normalized systems, normalized systems theory, platforms

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity

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Authors: Maria Amodeo, Pasquale Arpaia, Marco Buzio, Vincenzo Di Capua, Francesco Donnarumma

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Different deep neural network architectures have been compared and tested to predict magnetic hysteresis in the context of pulsed electromagnets for experimental physics applications. Modelling quasi-static or dynamic major and especially minor hysteresis loops is one of the most challenging topics for computational magnetism. Recent attempts at mathematical prediction in this context using Preisach models could not attain better than percent-level accuracy. Hence, this work explores neural network approaches and shows that the architecture that best fits the measured magnetic field behaviour, including the effects of hysteresis and eddy currents, is the nonlinear autoregressive exogenous neural network (NARX) model. This architecture aims to achieve a relative RMSE of the order of a few 100 ppm for complex magnetic field cycling, including arbitrary sequences of pseudo-random high field and low field cycles. The NARX-based architecture is compared with the state-of-the-art, showing better performance than the classical operator-based and differential models, and is tested on a reference quadrupole magnetic lens used for CERN particle beams, chosen as a case study. The training and test datasets are a representative example of real-world magnet operation; this makes the good result obtained very promising for future applications in this context.

Keywords: deep neural network, magnetic modelling, measurement and empirical software engineering, NARX

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Authors: Arab M., Ait Abdallah M., Zeraoulia N., Boumaza H., Aoutia M., Griene L., Ait Abdelkader B.,

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breast and ovarian cancer are respectively the first and fourth leading causes of cancer among women in Algeria. A family story of cancer in the most important risk factor, and in most cases of families with breast and /or ovarian cancer, the pattern of cancer family can be attributed to mutation in BRCA1/2genes. objectibes: the aim of our study in to investigate the spectrum of BRCA1/2 germiline mutation in familial breast and /or ovarian cancer and to determine the prevalence and the nature of BRCA1/2mutation in Algeria methods: we deremined the prevalence of BRCA1/2 mutation within a cohort of 161 probands selected according the eisinger score double stranded sanger sequencing of all coding exons of BRCA1/2including flanking intronic region were performed results: we identified a total of 23 distinct deleterious mutations (class5) 12 differents mutations in BRCA1(52%) and 11 in BRCA2(48%). 78% (18/23) were protein truncating and 22%(5/23) missens mutations.3 novel deleterious mutations have been identified, which have not been described in public mutation database. one new mutation were found in two unrelated patients. the overall mutation detection rate in our study is 28,5%(46/161).more over, an UVS c7783 located in BRCA2 is found in two unrelated probands and segregate in the 02 families/ conclusion: our results sugget of large spectrum of BRCA1/2 mutation in Algerian breast/ovarian cancer family. The nature and prevalence of BRCA1/2mutation in algerian families are ongoing in a larger study, 80 probands are to day under investigation. This study which may therefore identify the genetic particularity of Algerian breast /ovarian cancer.

Keywords: BRCA1/2 mutations, hereditary breast cancer, algerian women, prvalence

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Authors: Hyeon-Kyo Lim, Tong-Il Jang, Yong-Hee Lee

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Human error is one of the most dreaded factors that may result in unexpected accidents, especially in nuclear power plants. For accident prevention, it is quite indispensable to analyze and to manage the influence of any factor which may raise the possibility of human errors. Out of lots factors, stress has been reported to have a significant influence on human performance. Therefore, this research aimed to develop a work-related stress management program which can guarantee Fitness-for-Duty (FFD) of the workers in nuclear power plants, especially those working in main control rooms. Major stress factors were elicited through literal surveys and classified into major categories such as demands, supports, and relationships. To manage those factors, a test and intervention program based on 4-level approaches was developed over the whole employment cycle including selection and screening of workers, job allocation, and job rotation. In addition, a managerial care program was introduced with the concept of Employee-Assistance-Program (EAP) program. Reviews on the program conducted by ex-operators in nuclear power plants showed responses in the affirmative, and suggested additional treatment to guarantee high performance of human workers, not in normal operations but also in emergency situations.

Keywords: human error, work performance, work stress, Fitness-For-Duty (FFD), Employee Assistance Program (EAP)

Procedia PDF Downloads 382

Authors: Piotr J. Balwierz, Mikhail Pachkov, Phil Arnold, Andreas J. Gruber, Mihaela Zavolan, Erik van Nimwegen

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Understanding the key players and interactions in the regulatory networks that control gene expression and chromatin state across different cell types and tissues in metazoans remains one of the central challenges in systems biology. Our laboratory has pioneered a number of methods for automatically inferring core gene regulatory networks directly from high-throughput data by modeling gene expression (RNA-seq) and chromatin state (ChIP-seq) measurements in terms of genome-wide computational predictions of regulatory sites for hundreds of transcription factors and micro-RNAs. These methods have now been completely automated in an integrated webserver called ISMARA that allows researchers to analyze their own data by simply uploading RNA-seq or ChIP-seq data sets and provides results in an integrated web interface as well as in downloadable flat form. For any data set, ISMARA infers the key regulators in the system, their activities across the input samples, the genes and pathways they target, and the core interactions between the regulators. We believe that by empowering experimental researchers to apply cutting-edge computational systems biology tools to their data in a completely automated manner, ISMARA can play an important role in developing our understanding of regulatory networks across metazoans.

Keywords: gene expression analysis, high-throughput sequencing analysis, transcription factor activity, transcription regulation

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Authors: Nusrat T. Chowdhury, M. F. Baki, A. Azab

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The production planning problem is concerned with specifying the optimal quantities to produce in order to meet the demand for a prespecified planning horizon with the least possible expenditure. Making the right decisions in production planning will affect directly the performance and productivity of a manufacturing firm, which is important for its ability to compete in the market. Therefore, developing and improving solution procedures for production planning problems is very significant. In this paper, we develop a Dantzig-Wolfe decomposition of a multi-item hierarchical production planning problem with capacity constraint and present a column generation approach to solve the problem. The original Mixed Integer Linear Programming model of the problem is decomposed item by item into a master problem and a number of subproblems. The capacity constraint is considered as the linking constraint between the master problem and the subproblems. The subproblems are solved using the dynamic programming approach. We also propose a multi-step iterative capacity allocation heuristic procedure to handle any kind of infeasibility that arises while solving the problem. We compare the computational performance of the developed solution approach against the state-of-the-art heuristic procedure available in the literature. The results show that the proposed heuristic-based decomposition approach improves the solution quality by 20% as compared to the literature.

Keywords: inventory, multi-level capacitated lot-sizing, emission control, setup carryover

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Authors: Hatthaphone Silimanotham, Michael Henry

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The effective maintenance of road bridge infrastructure is becoming a widely researched topic in the civil engineering field. Deterioration is one of the main issues in bridge performance, and it is necessary to understand how bridges deteriorate to optimally plan budget allocation for bridge maintenance. In Laos, many bridges are in a deteriorated state, which may affect the performance of the bridge. Due to bridge deterioration, the Ministry of Public Works and Transport is interested in the deterioration model to allocate the budget efficiently and support the bridge maintenance planning. A deterioration model can be used to predict the bridge condition in the future based on the observed behavior in the past. This paper analyzes the available inspection data of road bridges on the road classifications network to build deterioration prediction models for the main bridge type found at the provincial level (concrete slab, concrete girder, and steel truss) using probabilistic deterioration modeling by linear regression method. The analysis targets there has three bridge types in the 18 provinces of Laos and estimates the bridge deterioration rating for evaluating the bridge's remaining life. This research thus considers the relationship between the service period and the bridge condition to represent the probability of bridge condition in the future. The results of the study can be used for a variety of bridge management tasks, including maintenance planning, budgeting, and evaluating bridge assets.

Keywords: deterioration model, bridge condition, bridge management, probabilistic modeling

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Authors: Amr AbdelAzim Ali, G. A. Elsheikh, Moutaz M. Hegazy

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Reaction wheels (RWs) are generally used as main actuator in the attitude control system (ACS) of spacecraft (SC) for fast orientation and high pointing accuracy. In order to achieve the required accuracy for the RWs model, the main characteristics of the RWs that necessitate analysis during the ACS design phase include: technical features, sequence of operating and RW control logic are included in function (behavior) model. A mathematical model is developed including the various errors source. The errors in control torque including relative, absolute, and error due to time delay. While the errors in angular velocity due to differences between average and real speed, resolution error, loose in installation of angular sensor, and synchronization errors. The friction torque is presented in the model include the different feature of friction phenomena: steady velocity friction, static friction and break-away torque, and frictional lag. The model response is compared with the experimental torque and frequency-response characteristics of tested RWs. Based on the created RW model, some criteria of optimization based control torque allocation problem can be recommended like: avoiding the zero speed crossing, bias angular velocity, or preventing wheel from running on the same angular velocity.

Keywords: friction torque, reaction wheels modeling, software in the loop, spacecraft attitude control

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Authors: Bongs Lainjo

Abstract:

The evolution and escalation of bike-sharing programs (BSP) continue unabated. Since the sixties, many countries have introduced different models and strategies of BSP. These include variations ranging from dockless models to electronic real-time monitoring systems. Reasons for using this BSP include recreation, errands, work, etc. And there is all indication that complex, and more innovative rider-friendly systems are yet to be introduced. The objective of this paper is to analyze current variables established by different operators and streamline them identifying the most compelling ones using analytics. Given the contents of available databases, there is a lack of uniformity and common standard on what is required and what is not. Two factors appear to be common: user type (registered and unregistered, and duration of each trip). This article uses historical data provided by one operator based in the greater Washington, District of Columbia, USA area. Several variables including categorical and continuous data types were screened. Eight out of 18 were considered acceptable and significantly contribute to determining a useful and reliable predictive model. Bike-sharing systems have become popular in recent years all around the world. Although this trend has resulted in many studies on public cycling systems, there have been few previous studies on the factors influencing public bicycle travel behavior. A bike-sharing system is a computer-controlled system in which individuals can borrow bikes for a fee or free for a limited period. This study has identified unprecedented useful, and pragmatic parameters required in improving BSP ridership dynamics.

Keywords: sharing program, historical data, parameters, ridership dynamics, trip duration

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Authors: Kaleb Shiferaw, Berhanu Geberemedhin, Dereje Legesse

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Access to credit is often viewed as a key to transform semi-subsistence smallholders into market oriented producers. However, only a few studies have examined factors that affect farmers’ decision to allocate credit on farm activities in general and livestock production in particular. A trivariate probit model with double selection is employed to identify factors that affect farmers’ decision to allocate credit on livestock production using data collected from smallholder farmers in Ethiopia. After controlling for two sample selection bias – taking credit for the production season and decision to allocate credit on farm activities – land ownership and access to a livestock centered extension service are found to have a significant (p<0.001) effect on farmers decision to use credit for livestock production. The result showed farmers with large land holding, and access to a livestock centered extension services are more likely to utilize credit for livestock production. However since the effect of land ownership squared is negative the effect of land ownership for those who own a large plot of land lessens. The study highlights the fact that improving access to credit does not automatically translate into more productive households. Improving farmers’ access to credit should be followed by a focused extension services.

Keywords: livestock production, credit access, credit allocation, household decision, double sample selection

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Authors: Stella Chioma Nwizu, Emmanuel Nwangwu

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Entrepreneurship, Vocational, and Technical education is an education that prepares one for effective adaptation to the world of work. It equally makes individuals self-reliant, self-sufficient and contributes to the development of society. It is, therefore, imperative that this type of education should be a priority in the development of any nation and should be given the utmost political support because of its importance and increasing demand on a global scale. This paper qualitatively explores three research questions on the policy status of Entrepreneurial, Vocational, and Technical Education (EVTE) in Nigeria, challenges hindering the enhancement of Entrepreneurial skills, Vocational and Technical Education in Nigeria, and strategies for the way forward. The major sources of data are secondary, interview and observation. Findings revealed the need to revise the policy of ETVE to meet the needs of the changing world of work. Challenges identified include corruption, inadequate funding, inadequate equipment, unqualified TVET Teachers/Instructors, poor documentation, policy implementation, poor conditions of service, and poor supervision of TVET programmes. Finally, the study identified policy revision, improvement in budgetary allocation, collaboration, sensitization, Public-Private Partnership, and training and retraining of instructors as the way forward toward the amelioration of the issues raised.

Keywords: entrepreneurship, entrepreneurial skills, vocational and technical education, technical and vocational education and training, VTE policy

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Authors: Mojgan Rabiey, Shyamali Roy, Billy Quilty, Ryan Creeth, George Sundin, Robert W. Jackson

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Bacterial canker is a major disease of Prunus species such as cherry (Prunus avium). It is caused by Pseudomonas syringae species including P. syringae pv. syringae (Pss) and P. syringae pv. morsprunorum race 1 (Psm1) and race 2 (Psm2). Concerns over the environmental impact of, and developing resistance to, copper controls call for alternative approaches to disease management. One method of control could be achieved using naturally occurring bacteriophage (phage) infective to the bacterial pathogens. Phages were isolated from soil, leaf, and bark of cherry trees in five locations in the South East of England. The phages were assessed for their host range against strains of Pss, Psm1, and Psm2. The phages exhibited a differential ability to infect and lyse different Pss and Psm isolates as well as some other P. syringae pathovars. However, the phages were unable to infect beneficial bacteria such as Pseudomonas fluorescens. A subset of 18 of these phages were further characterised genetically (Random Amplification of Polymorphic DNA-PCR fingerprinting and sequencing) and using electron microscopy. The phages are tentatively identified as belonging to the order Caudovirales and the families Myoviridae, Podoviridae, and Siphoviridae, with genetic material being dsDNA. Future research will fully sequence the phage genomes. The efficacy of the phage, both individually and in cocktails, to reduce disease progression in vivo will be investigated to understand the potential for practical use of these phages as biocontrol agents.

Keywords: bacteriophage, pseudomonas, bacterial cancker, biological control

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Authors: Djamel Fawzi Hadj Sadok, Marrone Silvério Melo Dantas Pedro Henrique Dreyer, Gabriel Fonseca Reis de Souza, Daniel Bezerra, Ricardo Souza, Silvia Lins, Judith Kelner

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A radio base station (RBS), part of the radio access network, is a particular type of equipment that supports the connection between a wide range of cellular user devices and an operator network access infrastructure. Nowadays, most of the RBS maintenance is carried out manually, resulting in a time consuming and costly task. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. A suitable candidate for RBS maintenance automation is repairing faulty links between devices caused by missing or unplugged connectors. This paper proposes and compares two deep learning solutions to identify attached RJ45 connectors on network ports. We named connector detection, the solution based on object detection, and connector classification, the one based on object classification. With the connector detection, we get an accuracy of 0:934, mean average precision 0:903. Connector classification, get a maximum accuracy of 0:981 and an AUC of 0:989. Although connector detection was outperformed in this study, this should not be viewed as an overall result as connector detection is more flexible for scenarios where there is no precise information about the environment and the possible devices. At the same time, the connector classification requires that information to be well-defined.

Keywords: radio base station, maintenance, classification, detection, deep learning, automation

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Authors: Samer Muthana Sarsam, Abdul Samad Shibghatullah, Chit Su Mon, Abd Aziz Alias, Hosam Al-Samarraie

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Generative Artificial Intelligence chatbots (GAI chatbots) have emerged as promising tools in various domains, including higher education. However, their specific role within the educational context and the level of legal support for their implementation remain unclear. Therefore, this study aims to investigate the role of Bard, a newly developed GAI chatbot, in higher education. To achieve this objective, English tweets were collected from Twitter's free streaming Application Programming Interface (API). The Latent Dirichlet Allocation (LDA) algorithm was applied to extract latent topics from the collected tweets. User sentiments, including disgust, surprise, sadness, anger, fear, joy, anticipation, and trust, as well as positive and negative sentiments, were extracted using the NRC Affect Intensity Lexicon and SentiStrength tools. This study explored the benefits, challenges, and future implications of integrating GAI chatbots in higher education. The findings shed light on the potential power of such tools, exemplified by Bard, in enhancing the learning process and providing support to students throughout their educational journey.

Keywords: generative artificial intelligence chatbots, bard, higher education, topic modelling, sentiment analysis

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Authors: Dylber Qema

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Driven by recent developments in technology and the growing concern about the sustainability and environmental impact of conventional fuel use, the possibility of producing clean and sustainable energy in significant quantities from renewable energy sources has sparked interest all over the world. Solar energy is one of the sources for the generation of electricity, with no emissions or environmental pollution. The electricity produced by photovoltaics can supply a home or business and can even be sold or exchanged with the grid operator. A very positive effect of using photovoltaic modules is that they do not produce greenhouse gases and do not produce chemical waste, unlike all other forms of energy production. Photovoltaics are becoming one of the largest investments in the field of renewable generating units. Improving the reliability of the electric power system is one of the most important impacts of the installation of photovoltaics (PV). Renewable energy sources are so large that they can meet the energy demands of the whole world, thus enabling sustainable supply as well as reducing local and global atmospheric emissions. Albania is rated by experts as one of the most favorable countries in Europe for the production of electricity from solar panels. But the country currently produces about 1% of its energy from the sun, while the rest of the needs are met by hydropower plants and imports. Albania has very good characteristics in terms of solar radiation (about 1300–1400 kW/m2). Solar energy has great potential and is a permanent source of energy with greater economic efficiency. Photovoltaic energy is also seen as an alternative, as long periods of drought in Albania have produced crises and high costs for securing energy in the foreign market.

Keywords: capacity, ministry of tourism and environment, obstacles, photovoltaic energy, sustainable

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Authors: Nahed Al-Hajeri

Abstract:

There are several reasons which lead to a delay in project completion, out of all, one main reason is the delay in deliverable processing, i.e. submission and review of documents. Most of the project cycles start with a list of deliverables but without a sequence of submission of the same, means without a direction to move, leading to overlapping of activities and more interdependencies. Hence Project Design Deliverables (PDD) is developed as a solution to Organize Transmittals (Documents/Drawings) received from contractors/consultants during different phases of an EPC (Engineering, Procurement, and Construction) projects, which gives proper direction to the stakeholders from the beginning, to reduce inter-discipline dependency, avoid overlapping of activities, provide a list of deliverables, sequence of activities, etc. PDD attempts to provide a list and sequencing of the engineering documents/drawings required during different phases of a Project which will benefit both client and Contractor in performing planned activities through timely submission and review of deliverables. This helps in ensuring improved quality and completion of Project in time. The successful implementation begins with a detailed understanding the specific challenges and requirements of the project. PDD will help to learn about vendor document submissions including general workflow, sequence and monitor the submission and review of the deliverables from the early stages of Project. This will provide an overview for the Submission of deliverables by the concerned during the projects in proper sequence. The goal of PDD is also to hold responsible and accountability of all stakeholders during complete project cycle. We believe that successful implementation of PDD with a detailed list of documents and their sequence will help organizations to achieve the project target.

Keywords: EPC (Engineering, Procurement, and Construction), project design deliverables (PDD), econometrics sciences, management sciences

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Authors: Madoda Cekiso, Thenjiwe Meyiwa

Abstract:

Successful postgraduate supervision involves possessing research capabilities, being knowledgeable in specific disciplines, understanding interpersonal relations, exercising mentoring/guidance skills and having appropriate knowledge of own institutional regulatory systems for postgraduate studies. On the other hand, postgraduate students are expected to know what the postgraduate journey entails and the elements and requirements of a postgraduate study. This paper sought to explore and analyse the research experiences of supervisors and postgraduate research students at one South African higher education institution. The study was qualitative in nature and a case study design was followed. The sample was purposively selected and comprised 25 postgraduate students and 20 postgraduate supervisors from one Faculty of the said university. The study findings revealed that there was no clear contract or memorandum of understanding between the postgraduate students and their supervisors. As a result, both supervisors and postgraduate students were not aware of their responsibilities. Both supervisors and postgraduate students complained about the non-availability of postgraduate facilities and resources for postgraduate students. The results further revealed that the allocation of students to supervisors who are not experts in a particular field was a challenge for both postgraduate students and supervisors. The results also revealed that the supervisors were not happy about the commitment of the postgraduate students towards their studies. The supervisors also complained about the postgraduate students who cannot work independently. Based on the findings, the authors recommended that a memorandum of understanding between a postgraduate student and a supervisor might solve some of the challenges. We further recommended a match between the supervisor’s expertise and the student’s focus area.

Keywords: feedback, mentoring, postgraduate, supervisors, student, memorandum of understanding

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Authors: Nastaran Hajiheydari, Mohammad Soltani Delgosha

Abstract:

Vendor (supplier) selection is a group decision-making (GDM) process, in which, based on some predetermined criteria, the experts’ preferences are provided in order to rank and choose the most desirable suppliers. In the real business environment, our attitudes or our choices would be made in an uncertain and indecisive situation could not be expressed in a crisp framework. Intuitionistic fuzzy sets (IFSs) could handle such situations in the best way. VIKOR method was developed to solve multi-criteria decision-making (MCDM) problems. This method, which is used to determine the compromised feasible solution with respect to the conflicting criteria, introduces a multi-criteria ranking index based on the particular measure of 'closeness' to the 'ideal solution'. Until now, there has been a little investigation of VIKOR with IFS, therefore we extended the intuitionistic fuzzy (IF) VIKOR to solve vendor selection problem under IF GDM environment. The present study intends to develop an IF VIKOR method in a GDM situation. Therefore, a model is presented to calculate the criterion weights based on entropy measure. Then, the interval-valued intuitionistic fuzzy weighted geometric (IFWG) operator utilized to obtain the total decision matrix. In the next stage, an approach based on the positive idle intuitionistic fuzzy number (PIIFN) and negative idle intuitionistic fuzzy number (NIIFN) was developed. Finally, the application of the proposed method to solve a vendor selection problem illustrated.

Keywords: group decision making, intuitionistic fuzzy set, intuitionistic fuzzy entropy measure, vendor selection, VIKOR

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Authors: Jonathan Iworiso

Abstract:

Forecasting the equity premium out-of-sample is a major concern to researchers in finance and emerging markets. The quest for a superior model that can forecast the equity premium with significant economic gains has resulted in several controversies on the choice of variables and suitable techniques among scholars. This research focuses mainly on the application of Regression Training (RT) techniques to forecast monthly equity premium out-of-sample recursively with an expanding window method. A broad category of sophisticated regression models involving model complexity was employed. The RT models include Ridge, Forward-Backward (FOBA) Ridge, Least Absolute Shrinkage and Selection Operator (LASSO), Relaxed LASSO, Elastic Net, and Least Angle Regression were trained and used to forecast the equity premium out-of-sample. In this study, the empirical investigation of the RT models demonstrates significant evidence of equity premium predictability both statistically and economically relative to the benchmark historical average, delivering significant utility gains. They seek to provide meaningful economic information on mean-variance portfolio investment for investors who are timing the market to earn future gains at minimal risk. Thus, the forecasting models appeared to guarantee an investor in a market setting who optimally reallocates a monthly portfolio between equities and risk-free treasury bills using equity premium forecasts at minimal risk.

Keywords: regression training, out-of-sample forecasts, expanding window, statistical predictability, economic significance, utility gains

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Authors: Georgiana Onicescu, Yuqian Shen

Abstract:

Due to the complex nature of geo-referenced data, multicollinearity of the risk factors in public health spatial studies is a commonly encountered issue, which leads to low parameter estimation accuracy because it inflates the variance in the regression analysis. To address this issue, we proposed a two-stage variable selection method by extending the least absolute shrinkage and selection operator (Lasso) to the Bayesian spatial setting, investigating the impact of risk factors to health outcomes. Specifically, in stage I, we performed the variable selection using Bayesian Lasso and several other variable selection approaches. Then, in stage II, we performed the model selection with only the selected variables from stage I and compared again the methods. To evaluate the performance of the two-stage variable selection methods, we conducted a simulation study with different distributions for the risk factors, using geo-referenced count data as the outcome and Michigan as the research region. We considered the cases when all candidate risk factors are independently normally distributed, or follow a multivariate normal distribution with different correlation levels. Two other Bayesian variable selection methods, Binary indicator, and the combination of Binary indicator and Lasso were considered and compared as alternative methods. The simulation results indicated that the proposed two-stage Bayesian Lasso variable selection method has the best performance for both independent and dependent cases considered. When compared with the one-stage approach, and the other two alternative methods, the two-stage Bayesian Lasso approach provides the highest estimation accuracy in all scenarios considered.

Keywords: Lasso, Bayesian analysis, spatial analysis, variable selection

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Authors: V. Sulakatko, F. U. Vogdt, I. Lill

Abstract:

Construction technology and on-site construction activities have a direct influence on the life cycle costs of energy efficiently renovated apartment buildings. The systematic inadequacies of the External Thermal Insulation Composite System (ETICS) which occur during the construction phase increase the risk for all stakeholders, reduce mechanical durability and increase the life cycle costs of the building. The economic effect of these shortcomings can be minimised if the risk of the most significant on-site activities is recognised. The objective of the presented ETICS economic assessment concept is to evaluate the economic influence of on-site shortcomings and reveal their significance to the foreseeable future repair costs. The model assembles repair techniques, discusses their direct cost calculation methods, argues over the proper usage of net present value over the life cycle of the building, and proposes a simulation tool to evaluate the risk of on-site activities. As the technique is dependent on the selected real interest rate, a sensitivity analysis is anticipated to determine the validity of the recommendations. After the verification of the model on the sample buildings by the industry, it is expected to increase economic rationality of resource allocation and reduce high-risk systematic shortcomings during the construction process of ETICS.

Keywords: activity-based cost estimating, cost estimation, ETICS, life cycle costing

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Authors: Suwattana Visetnan, Premruethai Supungul, Sureerat Tang, Ikuo Hirono, Anchalee Tassanakajon, Vichien Rimphanitchayakit

Abstract:

In animals, infection by Gram-negative bacteria and certain viruses activates the Imd signaling pathway wherein the a NF-κB transcription factor, Relish, is a key regulatory protein for the synthesis of antimicrobial proteins. Infection by yellow head virus (YHV) activates the Imd pathway. To investigate the expression of genes involved in YHV infection and under the influence of PmRelish regulation, RNA interference and suppression subtractive hybridization (SSH) are employed. The genes in forward library expressed in shrimp after YHV infection and under the activity of PmRelish were obtained by subtracting the cDNAs from YHV-infected and PmRelish-knockdown shrimp with cDNAs from YHV-infected shrimp. Opposite subtraction gave a reverse library whereby an alternative set of genes under YHV infection and no PmRelish expression was obtained. Sequencing of 252 and 99 cDNA clones from the respective forward and reverse libraries were done and annotated through blast search against the GenBank sequences. Genes involved in defense and homeostasis were abundant in both libraries, 31% and 23% in the forward and reverse libraries, respectively. They were predominantly antimicrobial proteins, proteinases and proteinase inhibitors. The expression of antimicrobial protein genes, ALFPm3, crustinPm1, penaeidin3 and penaeidin5 were tested under PmRelish silencing and Gram-negative bacterium V. harveyi infection. Together with the results previously reported, the expression of penaeidin5 and also penaeidin3 but not ALFPm3 and crustinPm1 were under the regulation of PmRelish in the Imd pathway.

Keywords: relish, yellow head virus, penaeus monodon, antimicrobial proteins

Procedia PDF Downloads 190